I would like to express most sincere thanks for the following people who made this educational experience possible for me:
Katherine Scott, Ph.D., Chairperson of my committee, for her inspiration, skilled guidance, patience, and wisdom.
Raymond Andrew, Ph.D., for his thoughtful comments on my publications and thesis.
Jeffrey Fitzsimmons, Ph.D., for discussions about coils, NMR in general, and his insight into people.
Richard Briggs, Ph.D., for discussions about pulse sequence techniques and pH measurements.
Thomas Mareci, Ph.D., for discussions about lactate editing and localization techniques.
Haejin Kang, Ph.D., for teaching me how to use the animal spectrometer, implementing phosphorus spectroscopy of implanted tumors in mice, acquiring data, and constructing two of the phosphorus coils used in my studies. He has been an "adopted brother" to me and I will always remember my time with him.
Byron Croker, M.D., for help with culturing tumor cells, planning mouse studies, and reviewing results of the tumor culture and mouse experiments.
William Brey, Randy Duensing, Andrew Mitchell, fellow graduate students, who have shared time and thoughts with me.
Carol Sweeney, for the cell culture work, mouse husbandry, collection and fitting of mouse data, and being a friend.
Jim Scott, for construction of the in-magnet ergometer and phantoms, helping to collect exercise data, volunteering to spend time in the magnet, and discussions ranging from RF coils to Shiitake mushrooms.
Barbara Beck, for instruction on coil construction.
Teresa Lyles, M.S., for her secretarial and statistical expertise, and her moral support.
Christine Stopka, Ph.D., for her wonderful personality and encouragement to study claudication patients with magnetic resonance spectroscopy.
Lori K. Marburger, M.S., who trained the peripheral vascular disease patients, performed the exercise tests and analyzed the data from the initial batch of patients.
William Breshue, Ph.D., for referral of congestive heart failure and heart transplant patients and for stimulating discussions about phosphorus metabolism and exercise physiology.
Alka Velenik, Ph.D., for setting up the transfer of exercise data from the Seimens scanner to a workstation for analysis.
Michael Welsh, for coordinating spectroscopy sessions for the congestive heart failure patients and help in analyzing data.
Michael Ingenio, M.D., for helping to acquire data on more recent claudication patients.
Aubrey Sobczak, for help in fitting spectra and entering data.
Susan Kohler, Ph.D., for her helpful suggestions on implementing magnetic resonance spectroscopy on out patients and for writing a macro for manipulation of chemical shift imaging data.
Suzanne Spanier, M.D., for helpful discussions and providing pathological correlation for the musculoskeletal tumor cases.
Juan Vasquez, for helping to work out "bugs" in the hardware of the whole body scanner.
Drs. Mark Scarborough and Tom Nelson for referral of musculoskeletal tumor patients.
Nancy Dixon, RN, for helping to coordinate the spectroscopy sessions with the tumor patients' chemotherapy hospitalizations.
Drs. Rudy Gurtner and James Seeger for referral of our peripheral vascular disease patients.
Vincent Groupé, Ph.D., for encouraging me to return to Graduate School for my Ph.D., and for teaching me to ascribe any success I may have to God, and not to my own questionable superiority.
Joanne Ballinger, PharmD, my wife, who has been patient with my odd hours through graduate school.
Christopher and Jennifer, my son and daughter, for helping me to keep my sense of humor, to live one day at a time, and to enjoy my second childhood.
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Table 3-1 Results of Four-day Growth Assay
Table 3-2 P-31 T1 Relaxation Times in Normal Skeletal Muscle
Table 3-3 Reproducibility of P-31 metabolites, normalized and unnormalized, in volunteers.
Table 3-4 Normalized Metabolite Signal for Tumor and Skeletal Muscle.
Table 3-5 Difference between rectal and skin temperature in mice.
Table 4-1 Mouse Metabolite Results Normalized to Unsuppressed Water Signal
Table 4-2 Summary of Tumor Patients.
Table 4-3 Peak positions of Metabolites of Interest
Table 4-4 T1 and T2 Relaxation Measurements from Four Volunteers and One Patient.
Table 4-5 Summary of Cho/Cr ratio data.
Table 4-6 Per Cent Change (decrease) in the Cho/Cr Ratio in Tumors with Follow up
Table 5-1 Mean and Standard Deviation of Resting Metabolites and pH
Table 5-2 Mean and Standard Deviation of the Metabolites and pH at their maximum extreme at or near the end of the exercise test
Table 5-3 Mean and Standard Deviation of the Recovery Rates of Metabolites and pH
Table 5-4 MVC and Time to Fatigue during Exercise Test
Figure 3-1 RF coil position over mouse tumor.
Figure 3-2 Representative spectra from an untreated tumor at five days (bottom) and twenty-three days (top) post implantation. The PME peak is labeled with a long arrow, the PCr peak with a short arrow. Note the increase in size of the PME peak and the decrease in size of the PCr peak on day twenty-three.
Figure 3-3 Graph of the mean volume of treated and untreated tumors as a function of time. Arrow marks chemo day.
Figure 3-4 Graph of the mean PME of the treated and untreated tumors as a function of time. Arrow marks chemo day.
Figure 3-5 Graph of the mean PCr/Pi ratio for the treated and untreated tumors as a function of time.
Figure 3-6 ROC Curve for detecting untreated tumors with PCr/Pi ratio. The true positive rate (sensitivity) is plotted as a function of the false positive rate (1-specificity).
Figure 3-7 Mean change in volume of sensitive and resistant tumors as a function of time. All of the mice received chemotherapy on day 0.
Figure 3-8 Mean change in PCr/Pi for sensitive and resistant mice as a function of time. All of the mice received chemotherapy on day 0. Change in the PCr/Pi ratio is seen as early as day 1 post chemotherapy. This change occurs before any change in the volume of the tumors (compare with Figure 3-9).
Figure 3-9 Graph of the mean PME ± one standard deviation vs time for sensitive and resistant mice. All of the mice received chemotherapy on day zero.
Figure 3-10 ROC Curve for detecting resistant tumors with the change in slope of the PCr/Pi ratio postchemotherapy. The true positive rate (sensitivity) is plotted as a function of the false positive rate (1-specificity).
Figure 3-11 Photograph of the 1.5 T General Electric Signa whole-body imager.
Figure 3-12 Photograph of CSI data superimposed on an axial MR image of tumor. The arrow points to the femur. Surrounding the black cortex of the femur on the left, right and top, is the malignant tumor appearing grey. The white areas below the femur are mostly fat. The small light grey object at the bottom of the photograph is the external standard.
Figure 3-13 Pre and post baseline-corrected P-31 spectra from the skeletal muscle of a normal volunteer.
Figure 3-14 Graph demonstrating linearity of the PO4 signal plotted as a function of the CSI voxel volume.
Figure 3-15 P-31 spectrum from malignant tumor in a patient. Note lower signal to noise when compared to a normal volunteer (Figure 3-13).
Figure 3-16 Example of a fitted tumor spectrum from patient.
Figure 3-17 Rectal temperature of the unheated anesthetized and the unheated, unanesthetized mice vs time postanesthesia. One anesthetized mouse showed a spontaneous increase in temperature after about 1.25 hours.
Figure 3-18 Rectal temperature of the heated, anesthetized mice vs time postanesthesia. The slight dip in temperature before 30 mins occurred while the mice and the coil were being positioned.
Figure 3-19 Graph of the pH of the six heated mice vs experiment number. Note lack of significant change over time (experiment number).
Figure 3-20 Graph of the pH of the six unheated, anesthetized mice vs rectal temperature. Regression lines have been fitted to the data of all but one of the mice. See the text for an explanation.
Figure 3-21 Graph of peak areas of the PCr, Pi, and ATP as a function of time. Experiment numbers are at approximately 15 min intervals.
Figure 4-1 Diagram of RF coil used for H-1 MRS and MRI of mouse tumors in the 2 T spectrometer.
Figure 4-2 Diagram of slice-selective SE pulse sequence with three CHESS water suppression pulses for H-1 MRS of mouse tumors.
Figure 4-3 H-1 spectra from mouse tumor acquired on 2T spectrometer. The top spectrum is with water suppression; the bottom spectrum is without water suppression.
Figure 4-4 Water-suppressed H-1 spectrum from mouse tumor acquired on 1.5 T whole-body MR scanner.
Figure 4-5 T1 and T2 weighted images of tumor in mouse. a) T1-weighted SE image (TR: 0.5 sec, TE: 30 ms). b) T2-weighted SE image (TR: 2 sec, TE: 80 ms). The tumor is grey in shade with an arrow pointing to the tumor/muscle interface. The white areas around the tumor are subcutaneous fat.
Figure 4-6 T1-weighted images, pre and post gadolinium-DTPA enhancement. a) Pre contrast image. b) Post contrast image. Note improved delineation of tumor/muscle boundary (arrows) on post contrast image. The skin is seen as a thin rim of light grey between the bright subcutaneous fat and the black air. Along the far right side of the tumor/muscle interface in the postcontrast image, there is evidence of muscle invasion by the tumor, not appreciated on the precontrast image.
Figure 4-7 Spectra from phantoms containing Glutamine/Glutamate, Creatine/Creatinine, Taurine, and Choline.
Figure 4-8 H-1 spectrum from skeletal muscle of normal volunteer with metabolite peaks of interest labeled.
Figure 4-9 Spectra from lactate phantom. The top two spectra were obtained with different mixing times as indicated. Subtraction of two spectra resulted in preservation of the lactate signal and elimination of the residual water signal as seen in the bottom spectrum.
Figure 4-10 Lactate editing of normal skeletal muscle. Note the elimination of most of the lipid and residual water signal. No significant lactate is seen in normal muscle spectra.
Figure 4-11 Lactate editing of malignant tumor. Residual signal seen on the difference spectrum probably represents both lactate and unsubtracted lipid.
Figure 4-12 MR images showing graphic selection of spectroscopy voxel using the STEAM sequence. a) Sagittal spin echo image of a volunteer's brain with desired voxel outlined. b) Localized image acquired with the STEAM sequence from area outlined on sagittal image.
Figure 4-13 Graph demonstrating linearity of the water signal with the voxel volume varying in size from about one cc up to at least 27 cc.
Figure 4-14 H-1 spectrum from a phantom containing a combination of choline, glutamine, taurine, and creatine used to help identify peak positions.
Figure 4-15 Tumor spectrum simulation with combination of spectra from phantoms.
Figure 4-16 Spectra from the same tumor in different locations showing the considerable spectral heterogeneity in the tumor
Figure 4-17 ROC curve for the accuracy of the Cho/Cr ratio in distinguishing malignant from benign tissue. The area under the curve was estimated to be 0.9727±0.0269.
Figure 4-18 Spectra from two of the tumors, before and after therapy. a) Chondrosarcoma. The bottom spectrum is from pre therapy, the top is from thirty days post therapy. b) Osteosarcoma. The bottom spectrum is from pre therapy, the middle from 3 days after the start of chemotherapy, and the top is from 20 days post start of chemotherapy.
Figure 4-19 Graphs of the change in the Cho/Cr ratio for four patients and volume of tumor for three patients with follow up. a) Patient C.P., Malignant fibrous histiocytoma. b) Patient L.D., Ewing's Sarcoma. c) Patient L.W., Chondrosarcoma. d) Patient C.M., Osteosarcoma.
Figure 4-20 Graph showing the change of the normalized H-1 metabolites in the four tumor patients with followup post therapy.
Figure 5-1 Set of spectra from one of the exercise patients, pre and postexercise test. The bottom spectrum is preexercise, the remainder are postexercise in order of time posttest.
Figure 5-2 Metabolite levels and pH as a function of time for two IC patients, pre- and posttraining. The top is from a patient with moderate disease, the bottom from a patient with severe disease.
a) PCr; b) Pi; c) PME; d) pH.
Figure 5-3 Spectra from exercise testing of PVD, CHF, and normal patients at 85% of their MVC. The spectra are at 32 sec intervals. The left-hand set of spectra are from a normal volunteer, the middle set are from a PVD patient, and the right-hand set are from a CHF patient. The first three spectra in each series, from bottom up, are resting spectra. During exercise, the PCr and Pi change the most in the claudicant and the least in the normal subject. Recovery is slowest in the claudicant and fastest in the normal. The CHF patient shows spectral changes between those of the normal and the claudicant.
figure 5-4 Graph of metabolite concentrations and pH as a function of time for a normal volunteer. Each number represents a 32 sec time increment.
ADP Adenosine Diphosphate
ATP Adenosine Triphosphate
CHESS CHEmical Shift Selective
CHF Congestive Heart Failure
Cho Choline
CI Confidence Interval
CIS Cisplatin (cis-diamminedichloroplatinum)
Cr Creatine/Creatinine
CT Computed Tomography
DANTE Delays Alternating with Nutations for Tailored Excitation
FID Free Induction Decay
FOV Field of View
Glu Glutamate/Glutamine
HCCTP hexachlorocyclotriphosphazene
IC Intermittent Claudication
ISIS Image-Selected In vivo Spectroscopy
Lac Lactate
MR Magnetic Resonance
MRI Magnetic Resonance Imaging
MRS Magnetic Resonance Spectroscopy
NMR Nuclear Magnetic Resonance
PCr Phosphocreatine
Pi Inorganic phosphate
PME Phosphomonoesters
PDE Phosphodiesters
ppm parts per million
PRESS Point RESolved Spectroscopy
PVD Peripheral Vascular Disease
ROC Receiver Operating Characteristics
RF Radio Frequency
SE Spin Echo
S/N Signal-to-Noise
SPARS SPAtially Resolved Spectroscopy
STEAM STimulated Echo Acquisition Mode
T Tesla
TE Echo Time
TM Mixing Time
TR Repetition Time
VOI Volume of Interest
Chairman: Katherine N. Scott
Major Department: Nuclear Engineering Sciences
The objective of this thesis is to develop and implement magnetic resonance spectroscopy (MRS) techniques in the diagnosis, treatment monitoring, and basic understanding of the disease process in metabolic and neoplastic musculoskeletal disorders.
P-31 MRS is used to do the following: detect chemotherapy-resistant human osteosarcomas implanted into a nude mouse model; determine anesthetic and temperature effects on spectra in the nude mouse model; monitor the metabolic changes in skeletal muscle that occur in peripheral vascular disease (PVD) patients with claudication; and compare metabolic changes in skeletal muscle of PVD and congestive heart failure (CHF) patients with age-matched normal volunteers. Development of P-31 MRS in the therapy monitoring of patients with musculoskeletal tumors is also presented. Water suppressed, proton magnetic resonance spectroscopy is developed for use in diagnosis and monitoring of the therapy response of musculoskeletal neoplasms including osteosarcoma.
Significant changes in the phosphocreatine to inorganic phosphate ratio are found in treated and sensitive osteosarcomas in mice before change in the size of the tumors. This ratio does not change significantly in either untreated or resistant tumors. Minimal direct anesthetic effects are seen on P-31 metabolites and pH in implanted osteosarcoma in mice. A profound effect of anesthesia is seen on the thermoregulatory ability of the mice. The changes in pH with change in temperature match those described in other animal models and humans.
Proton spectroscopy is successfully implemented in eleven musculoskeletal patients and statistically significant differences in the choline to creatine (Cho/Cr) ratio between malignant tumors and necrosis, edema, benign tumors, and normal muscle are found. Four of the patients with malignant tumors have follow up studies. Follow up studies show a statistically significant drop in Cho/Cr ratio with treatment. In one patient, a change is seen within three days of the start of chemotherapy.
Significant increase in the post-exercise rate of recovery of the phosphorylated sugar peaks and pH is seen using P-31 MRS following low-intensity training of PVD patients. Significant differences in the rate of recovery of high energy metabolites and pH in skeletal muscle are seen between normal volunteers and PVD, CHF, and heart transplant patients.
Magnetic resonance spectroscopy (MRS) of intact biological tissues was first reported by two groups: Moon and Richards using P-31 MRS to examine intact red blood cells in 1973 (1), and Hoult et al. using P-31 MRS to examine excised leg muscle from the rat in 1974 (2). Since then MRS has been applied to almost every organ of the body including brain (3-7), heart (8-11), liver (8, 12-14), kidney (15-17), prostate (18-20), and extremities (21-23). MRS is useful for looking at disorders of metabolism, tumors and certain inflammatory and ischemic diseases. Most of the work with in vivo MRS in humans has been in the brain. Abnormalities have been seen, sometimes with earlier detection than for any other diagnostic procedure short of biopsy, in primary brain tumors (6, 24-31), infections such as AIDS (32, 33), demyelinating disorders such as multiple sclerosis (34), epilepsy (35), and stroke (36, 37).
Spectroscopic changes are documented in a variety of enzyme deficiencies, mitochondrial abnormalities, dystrophies, inflammatory myopathies, and thyroid disease. In muscle these diseases include phosphofructokinase deficiency, amyloglucosidase deficiency, Duchenne muscular dystrophy, Becker muscular dystrophy, dermatomyositis, polymyositis, inclusion body myositis, hypothyroidism, and congestive heart failure (CHF) (38-43).
The research presented in this thesis deals with application of MRS to disorders of the extremities, specifically, the musculoskeletal system. These applications have been relatively neglected except unlocalized P-31 MRS of mitochondrial and enzyme abnormalities. Diseases of the musculoskeletal system for which MRS may have some value include metabolic (including ischemic) diseases and neoplasms. MRS may be useful for diagnosis, treatment monitoring, or understanding of the basic mechanism of these diseases.
Changes in muscle function and P-31 metabolism of patients are reported with both peripheral vascular disease (44-46) and CHF (47-49). P-31 MRS data are presented in this thesis from a unique treatment for peripheral vascular disease (PVD) patients introduced a few years ago (44). This treatment was implemented recently on PVD patients locally.
MRS of neoplastic disease involving the musculoskeletal system has not been evaluated extensively. This is probably a result of the rare occurrence of musculoskeletal tumors and the demanding technical problems. For this thesis, several types of musculoskeletal tumors in humans and an osteosarcoma model in mice are studied with P-31 and proton (H-1) MRS. I hope that this technique will eventually allow detection of chemotherapy and radiation therapy nonresponders in humans earlier than conventional imaging procedures. This would result in reducing the delay for surgery and reducing unnecessary chemotherapy and radiation therapy costs. Our spectroscopy research group plans to extend the animal research to evaluating new drugs for reversing
chemotherapy resistance. This will be applied to humans later if successful in the animal model.
The effects of temperature and anesthesia on the P-31 metabolites and pH will be examined in mice. If present, these effects could alter the results of the chemotherapy studies.
The following are the hypotheses that will be tested in this dissertation:
Mouse P-31 Tumor Studies
The presence or absence of statistically significant differences in the rates of change of the phosphocreatine/inorganic phosphate ratio (PCr/Pi) and phosphomonoesters (PME) between a) untreated and treated mice; and b) chemotherapy-treated sensitive and resistant mice will be determined. This information will be used to calculate the sensitivity and specificity for detecting the untreated mice and the resistant mice.
Human P-31 Tumor Studies
The PCr/Pi ratio and the PME signal will be examined in spontaneous musculoskeletal tumors in humans, using localized P-31 MRS, in hopes of using this information to detect tumors that fail to respond to therapy.
Anesthetic and Temperature Dependence of P-31 Metabolites
The presence or absence of the following phenomena will be determined:
1) Anesthesia with Innovar-Vet causes loss of thermoregulation in nude mice at doses required for immobilization for MRS studies.
2) Intracellular pH in implanted osteosarcoma in the nude mouse exhibits a temperature dependency similar to that reported in other tissues and in other models, including humans.
3) Anesthesia effects may be seen in the pH and P-31 metabolites of osteosarcoma.
Animal H-1 Tumor Study
An osteosarcoma mouse model will be used to determine the following:
1) Localized H-1 MR spectra, using water suppression techniques, will be successfully acquired from osteosarcomas implanted in nude mice.
2) Proton spectra from mouse tumors will show abnormalities in the choline/creatine (Cho/Cr) ratio.
Human H-1 Tumor Study
The H-1 MRS of mice will be complemented with examination of musculoskeletal tumors in humans to evaluate the following hypotheses:
1) Localized H-1 MR spectra, using water suppression techniques, will be successfully acquired from spontaneous musculoskeletal tumors, including osteosarcomas, in humans.
2) Viable tumor tissue will be distinguished from normal muscle, edematous tissue, and necrosis by H-1 MRS in humans.
3) The response to chemotherapy of musculoskeletal tumors in humans will be detected and quantified by changes in the H-1 spectrum.
4) The localized H-1 spectral data from humans will be correlated with magnetic resonance imaging (MRI), computed tomography (CT), and histopathology of the tumors.
5) Changes in Cho/Cr ratio will be used to differentiate chemotherapy non-responders from responders and will do so earlier than with MRI or CT.
Exercise Studies
We will use P-31 MRS of leg muscle in conjunction with exercise testing to test the following:
1) Improvement in the post-exercise recovery rates of phosphorus metabolites and pH will be seen after low-intensity exercise training.
2) Significant differences will be seen in the immediate post-exercise metabolite levels and pH in the skeletal muscle of PVD patients, CHF patients, heart transplant patients, and normal volunteers.
3) Significant differences will be seen in post-exercise recovery rate of phosphorus metabolites and pH in skeletal muscle of PVD patients, CHF patients, heart transplant patients, and normal volunteers following exercise.
Mouse P-31 Tumor Studies
Phosphorus MRS data will be collected from an osteosarcoma mouse model using a 2 Tesla (T) MR spectrometer. Data will be obtained and analyzed to show any statistically significant differences in metabolite levels between untreated and treated mice and between treated sensitive and resistant tumor mice.
Human P-31 Tumor Study
1) Existing localization techniques on a 1.5 T whole body magnetic resonance (MR) scanner (Signa, General Electric Company, Milwaukee) will be evaluated and (if necessary) modified to obtain well-localized P-31 spectra. Chemical shift imaging (CSI) techniques will be evaluated with phantoms, human volunteers, and patients. Spectral data will be obtained with signal-to-noise and spectral resolution adequate to show metabolite concentration differences between normal muscle, treated tumors, and untreated tumors.
2) Localized spectra of the tumor, necrosis, and surrounding normal and edematous tissue will be compared to the MRI in the humans.
Anesthetic and Temperature Dependence of P-31 Metabolites
1) Nude mice with implanted tumors will be anesthetized with Innovar-Vet and their rectal and skin temperature measured over a two hour period to detect any loss of thermoregulation.
2) Serial P-31 spectra will be obtained from anesthetized mice that become hypothermic and from mice that are heated to maintain normal body temperature over a two-hour period. Peak areas and pH will be measured and correlated with the rectal temperature and the time from injection of anesthesia.
Animal H-1 Tumor Study
Surface coils and a Faraday shield will be used initially for localization in mice in a 2 T spectrometer/imager. Water suppression techniques will be evaluated with phantoms and mice to obtain 200+ fold suppression of water. Spectral data will have spectral resolution sufficient to resolve the Cho and Cr peaks (0.2 ppm).
Human H-1 Study
1) Existing localization techniques on the whole-body MR scanner will be evaluated and (if necessary) modified to obtain well-localized H-1 spectra. Various water suppression techniques will be evaluated with phantoms, human volunteers, and patients to obtain 200+ fold suppression of water. Shimming and adjustment of voxel size will be done to obtain a spectral resolution sufficient to resolve the Cho and Cr peaks (0.2 ppm).
2) Localized spectra of the tumor, necrosis, and surrounding normal and edematous tissue will be compared to the MRI in the tumor patients.
3) The prebiopsy H-1 spectral data will be correlated with MRI and CT, and the histopathology of the biopsy material in humans.
4) Changes in spectral data during and after therapy will be documented. These changes will be compared with imaging data, gross and microscopic histopathology, and tumor response to therapy. Estimates of the ability of H-1 MRS to distinguish benign from malignant tissues and therapy responders from nonresponders will be made.
Exercise Studies
1) Recovery rates will be calculated for pH and P-31 metabolite levels obtained in the whole body MR scanner following a treadmill exercise stress test of PVD patients before and after low-intensity exercise training. The data will be tested for any significant changes from pre- to posttraining.
2) P-31 metabolite levels and pH will be measured from PVD patients, CHF patients, heart transplant patients, and normal volunteers in the whole body MR scanner during and following exercise with an in-magnet ergometer. Absolute metabolite concentrations and recovery rates will be calculated. Differences
in these parameters among the four groups of subjects will be determined.
Part of the work presented in this dissertation was done in collaboration with others. The treated and untreated mouse section and the sensitive and resistant mouse section were a joint effort of J.R. Ballinger, H. Kang, and C.A. Sweeney. Specific details of each person's contribution are presented later. The sections on P-31 spectroscopy of musculoskeletal tumors in humans and anesthetic and temperature dependence of pH and P-31 metabolites in mice, and the chapter on H-1 spectroscopy of musculoskeletal tumors was work of J.R. Ballinger alone. The spectroscopy results in the chapter on P-31 spectroscopy of skeletal muscle in peripheral vascular disease and congestive heart failure was also the work of J.R. Ballinger, with the ancillary exercise testing performed by C. Stopka, W. Breshue, and colleagues. A. Velenik, a postdoctorate fellow at the time, set up and performed the transfer of some exercise data from the Siemens scanner to a workstation for analysis.
Radio Frequency Localization
In vivo MRS generally requires some degree of localization. With implanted tumors in mice, it is desirable to obtain the signal from the tumor only and not from underlying muscle. Muscle and fat are found surrounding most musculoskeletal tumors in humans. Muscle may cause signal contamination in both unlocalized P-31 and H-1 tumor spectra, and fat may cause undesirable lipid contamination in H-1 tumor spectra. Localization requirements are less strenuous in P-31 MRS of calf muscle for metabolic studies. Here too, potential problems exist without some degree of localization. Different muscle groups are used to different degrees in any given exercise (for example the soleus and the gastrocnemius in the calf). These two muscle groups also have different proportion of muscle fiber types (50). Both these factors may introduce variability in spectral data.
Surface Coil Localization
The simplest localization technique is with a surface coil. Localization with this technique relies on the limited extent of the B1 field to define the volume of interest (51). The distance from the coil at which a 90o tip angle occurs (providing the maximum signal) may be varied by adjusting the amplitude or length of the radio frequency (RF) pulse. This technique has been used for localizing implanted tumors in nude mice by various authors, including ourselves (18, 52, 53). A Faraday shield around the base of the tumor may be used to remove additional unwanted signal from surrounding muscle and other tissues (54).
Selective Presaturation
Another localization technique involves selective saturation of the spins outside the volume of interest (VOI). Excitation and dephasing of the spins outside the VOI are immediately followed by acquisition of a free induction decay (FID), spin echo (SE), or stimulated echo from the tissue inside the VOI. This technique may be combined with selective excitation localization techniques. The VOI may be defined by saturating orthogonal slabs or cylindrical volumes (55-57).
Selective Excitation
Several localization techniques use selective excitation and detection of spins to detect the signal from within a VOI. One of the original volume excitation localization techniques is VSE (volume selective excitation) (58). More accurate localization techniques with less power deposition are used more commonly now. ISIS (Image-selected in vivo spectroscopy) localization (59) has been used frequently with P-31 MRS and has been reported at least once with H-1 MRS of the human brain (60). This technique uses three 180o inversion RF pulses with gradients to select orthogonal slabs, defining the VOI at the intersection. This is followed by a 90o excitation pulse and signal acquisition. An eight-step phase cycling routine is used to eliminate the residual signal from outside the desired voxel. Additional spatial presaturation pulses may be necessary to eliminate additional extraneous signal from outside the VOI as the result of subtraction errors during the ISIS experiment. A multivolume ISIS technique has been described using multiple-line frequency selective pulses (61). For n volumes, 2n experiments must be done. The number of experiments would not be a problem for a small number of voxels with in vivo spectroscopy as we need about 256 averages for adequate signal-to-noise.
Commonly used selective excitation localization techniques for H-1 MRS include STEAM (STimulated Echo Acquisition Mode) (62, 63), PRESS (Point Resolved Spectroscopy) (64, 65), and SPARS (SPAtially Resolved Spectroscopy) (66, 67). STEAM selectively excites three orthogonal planes with two 90o RF pulses and one 180o RF pulse followed by acquisition of a stimulated echo. A localized image may be obtained to confirm proper positioning and size of the VOI. This sequence collects only one-half of the original signal but allows a short echo time (TE) (20 ms or less).
If more signal is necessary because of a small VOI or low levels of metabolites, the entire signal can be collected as a spin echo using the PRESS technique. PRESS consists of gradient localized 90o-180o-180o RF pulses. The SPARS technique consists of three sets of 90o-180o-90o RF pulses applied in the presence of gradients. SPARS localization results in significant contamination from outside the VOI unless care is taken in adjusting the 180o pulses. This problem is not seen with STEAM (22). It has a greater RF load on the patient than STEAM or PRESS (66). There is a sacrifice of a longer echo time in the PRESS and particularly the SPARS techniques resulting in T2 decay of the signal. This is rarely a problem with H-1 MRS because of the long T2 relaxation times of observable metabolites (68-70).
Chemical Shift Imaging
Chemical Shift Imaging (CSI) involves the use of stepped gradients to phase encode the spectra in one to three dimensions (71, 72). CSI has one major advantage over single volume localization methods. Spectra from multiple locations within the VOI may be sampled simultaneously (59, 73, 74). Sampling multiple areas within a tumor is desirable because of the heterogeneity of many tumors. Spectra from adjacent normal tissue are sometimes desirable.
There are two significant disadvantages of these methods. First, 45% or more of the signal from a voxel comes from bleeding from other voxels (75). This occurs because CSI uses a finite number of phase encoding steps to generate a limited series of sine and cosine functions to encode discrete and discontinuous voxels. The bleeding can be reduced with the use of selective Fourier transform localization (75, 76). With this technique, the k-space data set is weighted by a function that maximizes the signal from acquisitions with small gradients and minimizes the signal from acquisitions with strong gradients. Maximum SNR per unit time is accomplished with this technique by varying the number of averages at each phase-encoded step. Similar results may be obtained with post processing by multiplying the k-space data matrix in the spatial directions by an apodizing function, such as a Hanning, sine, Gaussian, or Fermi function. Use of a filter causes a small drop in SNR, yielding approximately 2% less signal than a CSI acquisition without a filter. The filter decreases the contamination from outside the voxel to about 11% (75). The width of the response function in each spatial dimension increases by 1.6 times that without weighing the data. To compensate for the increase in width of the response function, the phase encoded steps may be increased by 1.6 or the field of view (FOV) may be decreased by the same factor. A modification of the selective Fourier transform CSI experiment was developed using variable flip angles at different phase encoding steps to reduce bleed and improved SNR per unit time (77). The efficiency of these techniques has been compared recently (78).
The adult human is approximately 60% water by weight; skeletal muscle is approximately 79% water (79). This results in a concentration of water in skeletal muscle of about 44 M. The concentration of metabolites of interest in H-1 MRS is between 5 mM and 30 mM. This 1400+ fold difference in concentration results in a dynamic range problem for the receiver and the analog-to-digital converter of most spectroscopy systems and causes difficulty in quantitating accurately nearby peaks. It is therefore desirable to reduce or eliminate the water signal for detection and accurate quantification of metabolites.
Desirable features of a solvent suppression technique include uniform excitation of the nonsuppressed peaks of interest. Hore has summarized other desirable features for solvent suppression pulse sequences:
(a) insensitivity to Bo inhomogeneity and small errors in the choice of transmitter frequency; (b) wide band excitation, preferably on both sides of the solvent; (c) insensitivity to pulse imperfections (B1 inhomogeneity, nonideal pulse shapes, off resonance effects, phase shift errors); (d) only linear phase correction required; (e) simple modification to obtain a 180o pulse; and (f) easy to program and use. (80) pp. 285-286
One of the first proposed methods for reducing the water signal in H-1 MRS was Redfield's long, weak 90 degree RF pulse (81). The pulse results in a narrow bandwidth of excitation centered off resonance from water and on the frequency of the metabolite resonance of interest. This method is sensitive to magnetic field inhomogeneity resulting in incomplete suppression of the water peak, or nonuniform excitation of the desired metabolite, or both. The length of the pulse results in T2 weighting to the signal and a rolling baseline artifact. Redfield later introduced a "2-1-4 pulse" sequence that uses alternating 180 degree phase shifts of a constant amplitude RF pulse in a timing pattern of 2-1-4-1-2 (82). This results in a sinusoidal excitation spectrum where the water resonance is at a null point. This sequence results in a 100-fold decrease in the water signal. Disadvantages of the 2-1-4 sequence include nonuniform excitation of resonances of different chemical shifts and incomplete water suppression.
Plateau and Gueron introduced a sequence of strong pulses for water suppression (83). These pulses are simpler to generate and less sensitive to errors in pulse amplitude than Redfield's soft pulses. This sequence consists of two pulses separated by a delay (90o, , -90o, acquire) with the pulses centered on the water frequency. In the rotating frame of reference, the water magnetization vector is flipped on to the +x axis. After a period , the water vector has remained unchanged in position, while other resonances have undergone precession in the x-y plane. The second pulse returns the water vector to the z axis resulting in no component in the x-y plane and therefore no signal. The off resonant vectors will have a component of varying degree remaining in the x-y plane resulting in a signal. The amplitude of the signal from the other spins follows a sinusoidal pattern in the frequency domain, with maximum signal from those spins resonating at ± 1/(4) Hz, ± 3/(4) Hz, etc. relative to the frequency of water. In a modification of this technique by Bleich and Wilde (84) (90o, , +90o, acquire) the RF pulse is centered f Hz away from the water resonance such that the peak of interest is located f/2 from water. The water vector is allowed to rotate 180o in time at which time the second pulse returns it to the z axis. The peak of interest will remain in the x-y plane. These two hard-pulse sequences result in a 300-fold decrease in the water signal. Disadvantages of these sequences include the high sensitivity of the water suppression to phase shifts of the RF pulses and to amplitude balance in the RF channels (80).
Hore first described the binomial pulse sequences in 1983 in two papers (80, 85). The binomial pulse sequences were developed to have the following properties: 1) a broad null to accommodate widening of the water peak due to magnetic field inhomogeneity and to allow for minor errors in the setting of the transmitter frequency; 2) a wide band of excitation in the remainder of the spectrum of interest; 3) insensitivity to imperfections in the RF pulse shape and amplitude (as may be caused by finite rise and fall times, inhomogeneous RF fields from surface coils, and off resonance effects due to the long pulse lengths needed by whole body coils); and 4) a short sequence length to allow for T1 measurements if desired.
The Fourier transformations of the binomial pulse sequences approximate the desirable features of the excitation spectrum at small flip angles. Hore chose a sinusoidal function for an excitation spectrum: S()=sinn(/2). The inverse Fourier transformation of this function gives a series consisting of equally spaced delta functions with alternating signs given by the binomial coefficients (80). This series can be approximated by a series of equally spaced short pulses whose amplitudes are given by the binomial series, e.g., 1,2,1; 1,3,3,1; 1,4,6,4,1. The RF pulses alternate 180o phase shifts. The longer sequences have broader null regions and would therefore be more efficient in case of a broad water peak. The disadvantage of the longer sequences is that a large frequency dependent phase shift is introduced into the spectrum (86). The symmetric sequences (1,1; 1,3,3,1) are insensitive to minor errors in the flip angle compared to the asymmetric sequences. This is because each pulse in a symmetric sequence has an oppositely phased pulse of the same amplitude. Signal errors resulting from imperfect 180o phase shifts can be corrected with phase cycling (87). An approximately 1000 fold decrease in the water signal can be obtained with the most commonly implemented binomial sequence: 1,3,3,1. Additional sequences that may be used are 1,1,8,8,1,1 and 1,5,20,20,5,1 (86).
Water suppressed spectroscopy can also be performed using presaturation with a narrow bandwidth, frequency selective RF pulse, the so-called CHESS (CHEmical Shift Selective) technique (62, 88-92). Frahm et al. describe a combination of two CHESS pulses followed by STEAM localization (93). Greater suppression can be obtained using three CHESS pulses (94, 95), a technique we have available on our whole body scanner. Addition or substitution of a binomial sequence (80, 85), or a DANTE (Delays Alternating with Nutations for Tailored Excitation) sequence (96) are alternatives. The water suppression from T2 decay with the long TE PRESS localization technique can be supplemented with preceding CHESS pulses or an inversion pulse (97).
Lactate editing is necessary in in vivo experiments for at least two reasons. First, the peak position (1.33 ppm) overlaps that of the lipid signals (1.10-1.48 ppm) and second, the lactate signal intensity may be several times smaller than the lipid signal.
Several spectroscopic techniques may be used for lactate editing including homonuclear double-resonance difference (98, 99), double quantum coherence transfer (100-104), and zero quantum coherence (105-108). A zero quantum technique for lactate editing has been described using stimulated echo localization (105). This sequence is the only technique available to us to use on the whole-body imager at this time.
Lactate methyl protons are J-coupled to the adjacent methylene protons, resulting in phase modulation that is a function of the TE and the mixing time (TM). The lipid protons that resonate at a similar frequency show only mild J-coupling and do not exhibit significant phase modulation (109). By acquiring two spectra with a different TM and subtracting, the lipid signal can be removed, leaving only the lactate signal. The lactate peak phase modulation alternates minima and maxima at TE = 1/2J where J is the coupling constant for lactate and equals 7.35 Hz. At 1/J = 136 ms, the lactate peak modulates with the TM with a period of 1/ f where f is the chemical shift between the methyl and methylene peaks of lactate. At 1.5 T, f is equal to 178.5 Hz. Best results are obtained by keeping the TE constant at 136 ms and varying the TM.
The homonuclear double-resonance difference technique requires two transmitters and subtraction of spectra. This works well with in vitro and ex vivo work in spectrometers but most whole-body imagers do not have two transmitters. Most of the double quantum coherence transfer techniques result in a 50% loss of the lactate signal and require phase cycling to help reduce the water signal. Double quantum coherence transfer techniques have been reported that require no phase cycling and might be more desirable for in vivo experiments but have not yet been implemented on whole body imagers (110, 111).
An alternative to zero and double quantum editing techniques is to take advantage of the short T1 of lipids compared to lactate by the use of a 180o inversion pulse to null the lipid signal. As a result of using this technique, 20%-30% of the lactate signal is lost. The inversion pulse has been used with a binomial spin echo sequence to obtain both water and lipid suppression (112). This inversion pulse has been combined with two CHESS pulses for both water and lipid suppression (113) and is available now on our whole body spectrometer.
The differences in T2 between lipids and lactate were used in a mouse model to eliminate most of the lipid signal (57). This is effective when only a small amount of lipid is present and required a TE of at least 270 ms.
Tofts and Wray have published a comprehensive review of quantitation methods (114). They include a discussion of the assumptions and problems of each technique. Buchli and Boesiger have published recently an evaluation of the accuracy and reproducibility of several techniques for quantitation of P-31 spectra (115).
Twelve factors to be considered in quantitating in vivo MR spectroscopy follow:
1) The minimum detection limits for metabolites are about 0.5 mM for P-31 and 0.1 mM for H-1.
2) "NMR invisibility" sometimes occurs when a metabolite is not mobile enough (i.e., rapidly rotating or translating) to give a narrow peak. Much of the choline and phosphomonoester, for example, is bound in cell membranes as phospholipids and is not visible in normal tissue.
3) Normal tissues and to a greater degree, tumors, are heterogeneous. The heterogeneity may be macroscopic (fat vs. muscle or tumor vs. necrosis) or microscopic (different tumor subtypes or intracellular vs. extracellular metabolites).
4) The transmitter (B1) homogeneity and receiver sensitivity must be considered. Surface coils have quite an inhomogeneous B1 field. Volume coils are better in terms of B1 homogeneity.
5) Coil loading must be considered where using external standards for reference.
6) Peak ratios avoid some transmitter, receiver and coil problems. The problem with peak ratios is that changes in individual metabolites are not determined; changes may occur in both the numerator and the denominator. This is less of a problem in normal tissues where certain metabolites have relatively constant concentration (such as adenosine triphosphate (ATP) in muscle or water in brain and muscle), unlike the situation found in tumors.
7) Tissue extracts have been used to help quantitate MRS data, however, the concentrations depend on what technique is used and how efficient the technique is in extracting all of the metabolite.
8) External standards may be used for quantitation. These should experience the same B1 field and receiver sensitivity as the tissue or corrections should be made for differences. When the external standard is used during a separate experiment from the tissue, coil loading must be considered.
9) Internal standards may be used as alluded to under (6) above. Both ATP and internal water are frequently used. In tumors or metabolic diseases, they may not be as constant as in normal tissue, adding possible error and variability to results. Exogenous standards given internally have been used primarily in animals. Their invasive and possible toxic effects are drawbacks in humans.
10) Concentration measurements require some sort of volume determination unless the volume of the tissue and the standard are the same.
11) Relaxation effects need to be considered when TR < 5 T1 for the metabolites of interest or the standard. Also, if there is a delay of acquisition as occurs with spin echoes and stimulated echoes, T2 decay must be considered unless the TE << T2 for the metabolites and standard. Variation of the water T1 and T2 times has been found in implanted mammary adenocarcinoma in mice as a function of the age of tumor (116).
12) Various methods have been used to measure the signal magnitude in NMR spectra. These include manual measurements of peak height, triangulated peak areas, and cutting out and weighing the paper that the spectrum is drawn on. Automated methods include integrating the spectrum between two points, fitting Lorentzian or Gaussian shaped curves to the frequency-domain data, or fitting damped sinusoids to the time-domain data (117, 118). The manual methods are time consuming and peak height and triangulation are not very accurate unless the peak line width and shape remain the same. Integration works well on well separated but not overlapping peaks. Some authors claim that fitting of the time domain data is more reproducible than fitting of the frequency domain data. Problems with time domain fitting include the need for very good SNR and the more computer intensive processing than is required for fitting frequency data.
The significant factors to consider in measuring metabolite concentrations from in vivo experiments using MRS have been expressed in an equation by Bottomley and Hardy (119). The equation is as follows:
[M] is the metabolite concentration
[s] is the standard concentration
subscripts m and s denote metabolite and standard, respectively
S is the NMR signal
V is the sample volume
is the detection coil sensitivity
F is a function accounting for T1 saturation effects
is the flip angle
E is a function accounting for T2 decay occurring during the delay time Td
Two specific methods proposed for quantitation of in vivo MR spectra include the following: Michaelis et al. suggest the use of control spectra obtained from standard solutions in separate experiments but under identical experimental conditions including identical coil loading (120). This paper and two other abstracts report the use of the water signal present in the brain as a control or calibration standard for the quantitation of proton spectra (121, 122). This method was originally proposed by Thulborn and Ackerman (123). The water concentration in the brain is relatively constant (75-85%) (121).
Recently a combination technique using both an internal standard and an external standard was proposed for proton spectroscopy (124). Alger et al. use tissue water as an internal standard and a reference tube of distilled water as an external standard. The metabolite signals are referenced to the internal water signal in the same volume of tissue. This in turn is referenced to the ratio of water signal intensities of the same tissue volume and the reference standard obtained from a short TE MRI image. The concentration of pure water in the reference standard is known, and with estimates of the relaxation factors of the metabolites, tissue water and external reference standard, the metabolite concentration can be calculated. The metabolite concentration would be computed by the following equation:
[M] is the metabolite concentration
M is the metabolite NMR signal
W is the unsuppressed tissue water signal
Nu is the number of acquisitions used to obtain the unsuppressed water signal
Ns is the number of acquisitions used to obtain the water suppressed spectra
Np is the number of equivalent protons producing the metabolite's signal
[Wv] is the tissue water concentration derived from the equation below:
55 M is the concentration of pure water in the standard
Wv is the signal intensity of water in the region of interest from the MRI
Wr is the signal intensity of the pure water reference from the MRI
C1-4 are the correction factors for T1 and T2 relaxation
C5 is a correction factor for sensitivity differences in the receiver coil for the standard and volume of interest.
This method is quite attractive for use in in vivo experiments with humans. Images are obtained to measure volume changes in the tumors or tissue of interest and to provide a localization guide for gradient localization techniques. Little additional time would be required in using this quantitation technique.
Extensive literature exists describing abnormal P-31 spectra of animal and human tumors. There are fewer reports of alteration of the P-31 spectra following therapy. For a concise review see Negendank (125).
General Problem
Osteosarcoma is a relatively rare malignancy of bone occurring predominantly in teenagers and young adults with an annual incidence in the United States of approximately 2100 new cases (126, 127). Bone tumors account for about 5% of all childhood malignancies. Osteosarcomas comprise about 60% of malignant childhood bone tumors (128). The tumor consists of malignant osteoid-forming cells, i.e., those cells that form the organic matrix in which bone ossification occurs (129). These tumors occur primarily in the metaphyseal or growth regions of long bones, especially near the knee in the distal femur and proximal tibia. They have a propensity with time to extend beyond the bone into the adjacent soft tissues and joints.
Less common forms of osteosarcoma occur in older adults (usually > 50 yrs. old) associated with either a benign disease called Paget's disease or with previous radiation therapy (129). Earlier in this century, there were two groups of patients, that we no longer see, that developed osteosarcomas. Patients with tuberculosis of the spine were once treated with irradiation; and watch-dial painters often placed their brushes containing radium-226 doped paint in their mouths. Both groups had an increased incidence of osteosarcoma (130). These less common forms have a poorer prognosis than the primary osteosarcoma in children. Osteosarcomas in children have not been directly associated with any external or environmental factors, but are usually associated with the rapid growth that occurs in this age group (128). In some cases, osteosarcomas are associated with potentially inherited and acquired genetic defects (131-134).
History of Treatment
Before 1972, the 5-year survival rate of osteosarcoma was 20%, amputation being the primary treatment method (135). Post-operative adjuvant therapy was introduced by Jaffe in 1972, reporting a 30% to 40% response rate (136). In 1977, Jaffe introduced the idea of pre-operative or neoadjuvant chemotherapy with a primary response rate of 60% (137). The 5-year survival rate for osteosarcoma in humans from three recent randomized trials, reviewed by Eiber and Rosen in 1989, was 70% (range 66% to 77%) (129). These three clinical studies used combination chemotherapy including doxorubicin, methotrexate, and cisplatin. The 30% mortality rate in this review article is from drug-resistant tumors.
Surgical management of osteosarcoma following chemotherapy currently includes amputation, disarticulation, and limb salvage procedures. Limb salvage procedures involve the replacement of the effected segment of bone with normal donor bone. This preserves normal function of the patient's limb, unlike amputation and disarticulation. This may be possible if tumor involvement of the soft tissues and bone marrow is not extensive and if the adjacent joint is not traversed.
Monitoring of Therapy Response with Imaging Techniques
Response to chemotherapy is followed with MRI and CT, however, these modalities depend primarily on evaluating gross anatomical features such as change in tumor size. Detection of a significant response to chemotherapy with conventional clinical and imaging techniques requires a 4-6 week period. This results in a delay of either definitive surgery or change in the chemotherapy regimen if the desired response fails to occur.
A significant diagnostic problem is distinguishing soft tissue extension of tumor from surrounding edema and inflammation. Edema was present in six out of 21 osteosarcomas reported in a recent paper (138). Neither CT nor MRI (with or without enhancement) can accurately detect the difference between tumor and edema in osteosarcoma (138), chondrosarcoma (139), and soft-tissue tumors (140) and inflammation in soft-tissue tumors (141).
A 90% necrosis of the tumor on histopathological examination has a better prognostic value for patient survival than tumor size, site, and classification (142). The survival rate was 91% for patients with greater than 90% necrosis, compared to 14% survival for patients with less than 90% necrosis. Unfortunately, current imaging techniques including standard MRI fail to accurately determine the amount of necrosis in osteosarcomas and other malignant musculoskeletal tumors (141, 143-145). Two recent papers report the use of dynamic Gd-DTPA enhanced MRI to predict the amount of necrosis following chemotherapy. The first paper was able to distinguish >90% necrosis from <90% necrosis (143). The second paper mapped six osteosarcomas into 11 to 56 regions each (146). The fraction of regions with rapid signal intensity change with time predicts the histopathological grade of the tumor, i.e., <50% necrosis, 50%-90% necrosis, >90% necrosis, and 100% necrosis. Individual regions were occasionally false positive for tumor when vascular fibrosis was present. Two recent abstracts discriminate chemotherapy responders from nonresponders based on the rate on contrast enhancement after a bolus injection of gadopentetate dimeglumine (147, 148).
P-31 Magnetic Resonance Spectroscopy
P-31 spectra of tumors and malignant cells consist mainly of peaks for phosphomonoester (PME), inorganic phosphate (Pi), phosphodiester (PDE), phosphocreatine (PCr), nucleoside triphosphate (Primarily ATP) and diphosphodiester (DPDE). The PME peak contains various sugar phosphates, phosphoryl ethanolamine (PE), and phosphoryl choline (PC). The latter two are precursors of phospholipids and are produced by choline and ethanolamine kinases (149). Phospholipids are important constituents of cell membranes and organelles involved in the synthesis of proteins and generation of energy (150). The PDE peak consists primarily of glycerolphosphoryl choline (GPC) and glycerolphosphoryl ethanolamine (GPE), which are membrane breakdown products (149).
Thus, the P-31 spectrum gives information on phospholipid synthesis (PC and PE) and degradation (GPC & GPE), cell energetics (PCr, ATP, & Pi), pH (Pi and PCr positions) (151) and glycoprotein/glycolipid synthesis (DPDE). Actively growing cells (as in malignant tumors) have high rates of energy consumption and protein/membrane synthesis and breakdown, contributing to P-31 spectral abnormalities.
P-31 spectra of bone tumors, including osteosarcoma in humans, show increased PME, PDE, and Pi, and a decrease in PCr (152-159) relative to normal skeletal muscle. The concentration of ATP may increase, decrease, or remain unchanged, depending on the study. The pH of the tumors is also variable, depending on the type and the stage of the tumor. An elevated pH is seen in two studies (153, 154), a normal pH is seen in four studies (152, 155, 158, 160), both slightly elevated and normal values in one study (159).
Treatment Response
P-31 MR spectral changes may be seen in human osteosarcoma patients on the second day after beginning chemotherapy (152). A decrease in PME in human osteosarcomas as a response to chemotherapy is reported (159, 161, 162). An increase in the PCr/Pi ratio is reported, following treatment, in human osteosarcoma (153, 159), soft tissue sarcomas (162), and in murine osteosarcoma (163), mammary adenocarcinoma (164), RIF-1 tumors (165), and 9L gliosarcoma (166).
Subtle changes may be present in osteosarcomas and other tumors within one hour of the start of chemotherapy (153, 167). The prognostic value of these changes is uncertain. Following chemotherapy in humans, long term decrease in PDE is associated with >90% necrosis (154). An increase in the PCr/Pi ratio is correlated with a decreased transverse tumor diameter by Semmler et al. (153). Ross et al. (152) observe a decrease in PME and ATP relative to PCr. Pi showed biphasic behavior with respect to time in his study, initially decreasing, then increasing. Wehrle et al. (165) observe biphasic behavior of Pi with respect to the chemotherapy dose in RIF-1 tumors implanted in mice. A decrease in Pi relative to -NTP (nucleoside triphosphate) is seen at moderate doses of cyclophosphamide (150 mg/kg i.p., LD10 or less). At high doses (200 mg/kg, approximately LD50 dose), they observe an increase in Pi relative to -NTP. Wehrle also observes a decrease in PME and an alkaline shift in pH. Koutcher showed a significant increase in PDE/PME in malignant fibrous histiocytomas that responded to chemotherapy compared to a slight decrease or no change with nonresponders (162). The responders also had a significantly lower PDE/PME before chemotherapy compared to nonresponders. Redmond et al. show a significant decrease in PME in human osteosarcomas (159). A recent abstract found that the PCr/Pi and PCr/ATP ratios discriminate between chemotherapy responders and nonresponders (168).
pH Changes
Alkaline shifts in tumor pH following treatment have been seen for a variety of tumors including non-Hodgkin's lymphoma (169). The pH in three osteosarcomas following chemotherapy failed to change significantly (159).
Advantages of P-31 MRS
1) The high energy phosphates so important to tumor metabolism, i.e., PCr and ATP, are readily seen at 1.5 T. ATP is important as the immediate source of energy for most metabolic processes. Decreased levels are found in tumors with reversal following effective treatment. ATP is identified and quantified by H-1 MRS in human skeletal muscle at 4.1 T (170) but not at 1.5 T. Total creatine can be resolved with H-1 MRS, however PCr and Cr cannot be separated at 1.5 T.
(2) The different phosphoesters, PME and PDE are easily resolved with P-31 MRS. Although the PME and PDE peaks show similar changes in implanted osteosarcoma in mice (157), with decoupling techniques the various components of the PME peak (PE and PC) can be resolved and appear to have individual significance (171). The elevated PME in most malignant tumors is related to increase in PC; however, elevated PE and decreased PC have been reported in human colon cancer (172). The PE/PC ratio may be a more sensitive indicator of malignancy and of tumor response to therapy than PME alone (171).
(3) The P-31 spectrum has no solvent signal to interfere with resolution of metabolite peaks, unlike the water signal seen with in vivo H-1 MRS.
Treated and Untreated Mice
Materials and Methods
Our goal is to develop better techniques to monitor the chemotherapy response of tumors. In the present study, we used phosphorus NMR spectroscopy to compare the changes in phosphomonoester(PME) signal and the phosphocreatine/inorganic phosphate (PCr/Pi) ratio from implanted human osteosarcoma in the nude mouse with and without chemotherapy (treated and untreated). We evaluated the accuracy of the change in PME and PCr/Pi in detecting the untreated mouse. This is a logical precursor to studying resistant and sensitive tumors in mice. In the latter case we would wish to predict which tumors are resistant.
The study protocol, data acquisition and preliminary analysis was performed by Haejin Kang, Ph.D. as part of his graduate work. The study is included in this thesis because extensive work has been done with the raw data beyond that presented previously. Specifically, the following work was done by or under my direction: a) spectra were refit, b) statistical analysis was performed on the PME changes with treatment, c) the possible explanation of volume changes accounting solely for the PME changes was addressed, and d) changes in PCr/Pi were investigated in terms of predicting treatment response independent of volume change. In addition, experiments were performed by myself to check the reproducibility of metabolite measurements using repeated spectral acquisitions on three mice.
Materials and Methods
Animal preparation
The nude, athymic mouse is a well characterized and accepted model for the study of the properties of human tumor cells (154, 173-175). Human tumors studied in nude mice include small cell carcinoma of the lung (154, 163, 173), mammary carcinoma (163), ovarian carcinoma (163), neuroblastoma (176) and prostate carcinoma (177). Human osteosarcoma in mice has not been studied with MRS to my knowledge; however, the murine Dunn osteosarcoma has been (163). Our experience has shown that human osteosarcomas, unlike some other human tumors, grow relatively well in nude mice. Our spontaneous regression rate of implanted osteosarcomas in nude mice is 1.5% (n=180) with none occurring in study mice. The mice that showed regression were from earlier preliminary studies. These mice were approximately 14 weeks old at time of implantation and were not irradiated. Nude mice older than 12 weeks have been shown to gradually develop T-cell activity that is apparently the cause for the observed tumor regression (178, 179). This tumor cell line makes bone in the mouse, repeating its human origin. We have also shown that the cell line responds to the same chemotherapeutic agents as do native osteosarcomas in humans. The kinetics of chemotherapeutic agents in nude mice has been studied and compared to the kinetics in humans (176, 180-183).
Twenty-two female Balb-c mice, weighing between 25-30 grams, were quarantined and acclimated to environmental conditions of 27oC±2o and 40-50% humidity for 5-7 days before implantation. The mice were fed and watered ad libitum.
At 10 weeks of age, the mice were irradiated in a Cs144 gamma irradiator (Gammacell 40, Atomic Energy of Canada Limited, Ottawa, Canada) at a dose of approximately 500 Rads to suppress any early T cell activity (184, 185). The next day, a suspension of 6 x 107 trypsinized cells from a standard tissue culture (186) of the human osteosarcoma cell line 791T (Zoma Corp., Berkeley, CA) was implanted subcutaneously over the gluteus maximus of the anesthetized mice. The mice were anesthetized for both implantation and spectroscopy. An intraperitoneal (i.p.) injection of 0.04-0.05 ml of Innovar-Vet (fentanyl citrate 0.4 mg/ml and droperidol 20 mg/ml, Pittman Moore, Washington Crossing, NJ), diluted to 10% v/v with normal saline, was used for anesthesia. This dose provides adequate anesthesia for one to two hours. The mice were irradiated and implanted with tumor cell suspension by Carol Sweeney, laboratory technician. The tissue culture work that she did was under the direction of Byron Croker, M.D., Director of Pathology at the VA Medical Center, Gainesville, FL.
Cisplatin (7 mg/kg, Bristol Laboratories, Evansville, IN), dissolved in 0.9% sodium chloride, was administered in 11 mice via a tail vein on day nine post implantation. This dose of cisplatin is a dose that is pharmacokinetically equivalent to the clinical dose in humans (Rational Dose) (176, 183). The tumors were followed with MRS for at least three weeks post implantation.
Spectroscopy
Spectroscopy was performed on a Spectroscopy Imaging Systems Corporation Model VIS 85/310 imaging spectrometer with a 310 mm diameter horizontal bore Oxford Instruments magnet operating at 2 T (34.61 MHz for P-31). Haejin Kang Ph.D., built the RF coil, and acquired the data. The spectrometer was operated from and the spectra analyzed on a Sun 3/110 work station (Sun Microsystems, Inc., Mountain View, CA). A home-made, 3-turn solenoid coil with an internal diameter of 13 mm and a depth of 6 mm (volume of the coil: 0.80 cc), double-tuned to H-1 and P-31, was positioned over the tumor as shown in Fig. 3-1. A fenestrated Faraday shield was positioned around the base of the tumor for further localization by excluding signal from adjacent muscle (not shown) (54). On histological evaluation, the skin of the nude mouse is quite thin and frequently has no muscle associated with it. It probably contributes little to the NMR signal. This is unlike the rat where significant subcutaneous muscle is present. There is probably a
Figure 3-1. RF coil positioned over mouse tumor.
significant contribution to the signal from muscle underlying the tumor that is not shielded by the Faraday shield. This is discussed later under the Results and Discussion section.
The magnet was shimmed on the water peak on each mouse to a line width of between 0.2 and 0.4 ppm. P-31 spectroscopy was performed with a non-selective 3-lobed, 12 µsec, 90o, sinc-shaped RF pulse followed 30 µsec later by acquisition of the FID signal. The 90o RF pulse power was set by maximizing the signal from the tumor. The acquisition parameters were: 2000 acquisition points, TR1.5 sec, spectral width=2000 Hz, 1024 averages, and a 26 min acquisition time. The total exam time was about 50 min. Spectroscopy was performed one day before implantation, then twice a week starting when the tumors were 0.23 cc ±0.07 in volume (nine days post implantation).
The volume of the tumors was initially calculated with the formula for an ellipsoidal volume (/6)*L*W*D from measurements made with calipers where L, W, and D are the length, width, and depth of the tumor respectively (155). Later, the tumor volume was calculated as the average of the formulas for an ellipsoid and for a prolate spheroid formed by rotation of an ellipse about its major axis, L: (/6)*L*W*D and (/6)*L*W2. We have found that this method of volume calculation is the best estimate of tumor volume. The average of these two formulas had a better correlation coefficient with the volume of water displaced by excised tumors of different sizes (compared to the two formulas separately, as shown in the Results and Discussion section). Imaging of the tumor to determine size was tried but failed to give adequate signal-to-noise (S/N) to distinguish the tumor, muscle interface in a 15 min period. The filling factor for the coil during the acquisitions immediately before and after chemotherapy ranged from 0.25 to 0.625. Reproducibility of spectra and metabolite signals was checked by J.R. Ballinger by obtaining 6-7 sequential spectra each in three additional mice with tumors (See Results and Discussion).
After 10 Hz line broadening of the FID and Fourier transformation of the data, the spectra were fit using the Fitspec software provided by SISCO. Zero and first order phase correction were applied to the frequency domain data. Fitting of spectra was performed initially by Carol Sweeney and Haejin Kang and later by Carol Sweeney and J.R. Ballinger.
Analysis of data
Data were statistically analyzed by J.R. Ballinger. The PME area and PCr/Pi ratio were used in statistical analysis. The change in each was compared to the volume changes of the tumors. An unpaired, two-tailed Student's t-test was used to test the difference between the treated and untreated mice in the PME change from the day after chemotherapy to the following session (four days later). The change in the slope of the PCr/Pi curve from pre-chemotherapy to the first study post-chemotherapy was tested for significance in both the treated and untreated mice with a paired, two-tailed Student's t-test. A receiver operating characteristic (ROC) curve was used as an indicator of the predictive value of the change in the slope of PCr/Pi in detecting tumor treatment.
Results and Discussion
Results
Two treated mice died as the result of the anesthesia and a third was sacrificed because of an eye infection. This compares favorably with the rat mortality rate from moderate to high doses of Innovar-Vet (6%-18%) even though the dose per kg in mice is higher (187-189). Smaller amounts of Innovar-Vet were inadequate in sedating the mice.
Using six to seven consecutive spectra, reproducibility of the spectra and metabolite areas was checked in each of three mice by calculating the per cent standard error:
The range of the per cent standard error for PME was 7.8% to 14.1%, for Pi 9.0% to 11.1%, and for PCr 3.5% to 9.9%. The range of the standard error for the PCr/Pi ratio was 8.6% to 12.1%. Thus, the reproducibility of the spectral acquisition and peak fitting appears quite reasonable.
We had a final number of 10 untreated mice and 9 treated mice. Representative spectra from an untreated tumor at five days and twelve days post implantation are shown in Figure 3-2. Figure 3-3 is a graph of the time course of the average tumor volume of the treated and untreated mice. Comparison of the three techniques of calculating the volume of the tumors was made by using a paired t-test to test the significance of the difference between the three formulas and the volume measured by water displacement of 36 excised tumors. The ellipsoidal volume formula (/6)*L*W*D underestimated the volume by an average of 0.32 cc (31% of the actual volume), which was statistically significant (p<0.0001). The prolate spheroid formula (/6)*L*W2 overestimated tumor volume by an average of 0.21 cc (20%), which was statistically significant (p=0.04). The mean of these two formulas underestimated the tumor volume by 0.06 cc (5.6%), which was not statistically significant (p=0.39).
A graph of the time course of the average amount of PME is shown in Figure 3-4 for the treated and the untreated mice. PME levels of the treated mice decrease from day 10 to day 14 post implantation (day 1 to day 5 post chemotherapy).
Figure 3-2 Representative spectra from an untreated tumor at five days (Bottom) and twenty-three days (top) post implantation. The PME peak is labeled with a long arrow, the PCr peak with a short arrow. Note the increase in size of the PME peak and the decrease in size of the PCr peak on day twenty-three.
Figure 3-3 Graph of the mean volume of treated and untreated tumors as a function of time. Arrow marks chemo day.
Figure 3-4 Graph of the mean PME of the treated and untreated tumors as a function of time. Arrow marks chemo day.
The changes in Figure 3-4 roughly mirror the changes in volume of the tumors seen in Figure 3-3. PME levels of untreated mice increased or remained unchanged during this period.
Figure 3-5 shows a graph of the PCr/Pi ratio for the treated and untreated mice over time. The posttreatment slope of the PCr/Pi curve for the treated mice shows a significant change (increase) from the pretreatment slope (p=0.0249) with a 95% confidence interval of (+0.0669, +0.755). The posttreatment slope of the PCr/Pi curve for the untreated mice does not show a significant change in direction from the pretreatment slope (p=0.4448, confidence interval: (0.253, +0.530)). During the time that the PCr/Pi slope of the treated tumors changes, the slope of the volume curves does not change (Figure 3-3). Note that the above statistical analysis was not testing directly for differences between the change in PCr/Pi slopes between the treated and untreated tumors. Testing the differences in slope for the same mouse allows use of a paired t-test. The paired t-test, allows use of a smaller number of subjects than an unpaired t-test. The posttreatment slope we have used is from day 7 to day 10 postimplantation, or from two days before treatment to one day post treatment. Ideally, we would want to measure the posttreatment slope from the day of treatment onward. This is not possible for technical reasons and because of the fragility of the mice. An alternative is to project the pretreatment slope to the day of treatment, and use that point as the initial point for the posttreatment slope calculation. This procedure results in little change in the results. The new p value is 0.0303 with an area
Figure 3-5 Graph of the mean PCr/Pi ratio for the treated and untreated tumors as a function of time. Arrow marks chemotherapy day.
under the ROC curve equal to 0.723±0.131 (see below for original ROC area).
Sensitivity in this study is the number of detected untreated mice divided by the actual number of untreated mice for a given decision threshold for PCr/Pi slope change. The specificity is the number of treated mice called treated divided by the total number of treated mice. The complementary nature of sensitivity and specificity can be represented with a ROC curve (190-193) as shown in Fig. 3-6.
The sensitivity (true positive fraction) is plotted as a function of 1-specificity (false positive fraction) for detecting an untreated tumor at various levels of PCr/Pi slope change post treatment. The points for our ROC curve were obtained from Charles E. Metz's LABROC1 program that fits binomial curves to the PCr/Pi slope data for the treated mice and from the untreated mice by the maximum-likelihood algorithm (194, 195). A point on the ROC curve is obtained by calculating the area under the binomial curves located to the right of a particular threshold or PCr/Pi value. The calculated areas correspond to the true positive fraction and to the false positive fraction. This process is repeated for several thresholds to obtain the entire curve. A straight diagonal line from the bottom left corner to the top right corner would indicate no predictive value of the test (area=0.5). The larger the area under the curve, up to one, the greater the predictive value or efficacy of the test. In this study we obtained an area of 0.64±0.12. The area under a ROC curve is independent of the position of the decision threshold, unlike accuracy, and may therefore be a better measure of test performance (191).
Figure 3-6 ROC Curve for detecting untreated tumors with PCr/Pi ratio. The true positive rate (sensitivity) is plotted as a function of the false positive rate (1-specificity).
Discussion
Our data show a difference in the change of the slope of the PME curves between treated and untreated osteosarcomas implanted into nude mice; however, this PME change occurs simultaneously with the change of the volume of the tumors. The PME changes could be related to differences in the amount of skeletal muscle being volume-averaged from under the tumor rather than actual concentration changes within the tumor. We are currently acquiring data using a slice selective localization technique that will eliminate contamination of our tumor spectrum by underlying muscle.
The PCr/Pi slope changes ((PCr/Pi)/t) that we see are statistically significant and occur prior to changes in volume of the tumor. There is overlap of the data from these two groups as shown in the figures. We would want to have a high specificity for detecting an untreated tumor (or in humans, a nonresponder to chemotherapy) to avoid discontinuing a treatment that is working. Using a threshold of change in the slope of PCr/Pi equal to -0.63, we obtained an 86% specificity and a 29% sensitivity. Using a decision threshold of 0.40, we can obtain a 60% specificity and a 60% sensitivity. These results will undoubtedly improve with better localization as we will have less of a dilutional effect from skeletal muscle contamination.
Sensitive and Resistant Mice
Materials and Methods
The objective of this experiment was to determine if changes in PCr/Pi and PME can be used to predict lack of tumor response to chemotherapy in a murine model of a chemotherapy-resistant human osteosarcoma.
Introduction
In a previous section, the use of phosphorus NMR spectroscopy (MRS) to compare the changes in phosphocreatine to inorganic phosphate ratio (PCr/Pi) and phosphomonoester (PME) signal from implanted human osteosarcoma in the nude mouse, with and without chemotherapy was described. The accuracy of using post treatment PCr/Pi changes to detect untreated mice was evaluated, and a statistically significant difference between the treated and untreated mice was found. It is hypothesized that a similar difference in the change in PCr/Pi between treated cisplatin-resistant and cisplatin-sensitive human osteosarcomas implanted in the nude mouse will be found.
Tumor cell line characteristics and preparation
The 791T osteosarcoma cell line (Zoma Corp., Berkeley, CA) is a high-grade, non-metastatic tumor cell in humans. The doubling time in vitro is twelve and one-half hours. The growth-rate in nude mice depends on the number of cells implanted: 0.4 cc tumors in 40-45 days for 4 x 107 cells and 6-8 days for 8 x 107 cells. In the nude mouse, the tumors can grow to ca. 6 cc, but become very necrotic and ulcerative at this stage. In our study, the mice are sacrificed before the tumors reach 2 cc in size.
Carol Sweeney, Biological Laboratory Technician, cloned the 791T-E10 (E10) cell line from 791T by using limiting dilution cloning, to produce a uniform cell population. Both cell lines grow as monolayers in Dulbecco's modified Eagle medium (DMEM) supplemented with 10% bovine calf serum, 15 mM HEPES buffer, and 2 mM L-glutamine. Drug resistant sublines were derived from E10 cells by intermittent treatment of the cells with increasing concentrations of cisplatin (E10-CIS subline). Cisplatin (cis-diamminedichloroplatinum) was obtained as Platinol (Bristol-Myers U.S. Pharmaceutical and Nutritional Group, Evansville, IN). Cells were seeded in T25 flasks at a concentration of 1 x 104 to 3 x 104 cells/ml; twenty-four hours later they were treated with concentrations of cisplatin in DMEM ranging from 10-22 µg/ml for one hour. The cells were rinsed twice with DMEM and then cultured in fresh DMEM until their numbers reached that of the untreated cells. The concentration of cisplatin chosen for later treatments depended on the length of time it took for cells to recover from the previous treatment.
A modified version of the chromium (Cr-51) release assay, developed by Brunner et al. (196), was used by Carol Sweeney and Jim Scott, Senior Chemist, to measure the short term (<24 hours) cytotoxicity of cisplatin (0 mg/ml - 100 mg/ml) to E10 drug-sensitive and E10-CIS drug-resistant cell lines.
A four-day growth assay was then used to compare the level of resistance of E10 (drug-sensitive) to E10-CIS (drug-resistant) cells beyond 24 hours. 1.8 x 105 cells were seeded on 60 x 15 mm dishes; twenty-four hours later, the cells were treated with varying concentrations of cisplatin in DMEM (0-32 µg/ml). Each concentration in each cell line and controls was run in triplicate. After one hour, cells were washed once with DMEM, then fresh DMEM was added to all plates. Four days later, cells were trypsinized and counted using a Coulter counter. The concentration
of the drug that resulted in 50% cell inhibition after four days (IC50) was determined from a dose response curve.
E10 and E10-CIS were frozen in multiple vials for use in mouse studies so that all mice would receive cells of approximately the same "age" (passage number) and level of resistance. For further information on the cell culture technique see the paper by Blommaert et al. (186).
Animal model
Twenty-one female BALB/c-nu/nu mice, weighing between 20-30 grams, were used for this study. Mice were treated similarly to those used in the treated and untreated study.
When the mice were 7-10 weeks old, and one day after irradiation, a suspension of 6 x 107 E10 or E10-CIS cells in DMEM was injected subcutaneously over the gluteus maximus by Carol Sweeney. The mice were anesthetized with an i.p. injection of Innovar (fentanyl citrate 0.05 mg/ml and droperidol 2.5 mg/ml, Pittman Moore, Washington Crossing, NJ) for implantation (0.05 ml) and for MRS (0.35-0.38 ml) of the tumor site. Innovar is approximately 1/10 the concentration of Innovar-Vet, the later being used for the first mouse study. The change in anesthetic was only because of the lack of availability of Innovar-Vet at the time of the second study. The dose of Innovar was adjusted appropriately to account for differences in concentration.
Each mouse was administered a single injection of 7 mg/kg cisplatin in a tail vein on approximately day 12 post implantation by Carol Sweeney, when the tumor volume reached about 1/2 cc (0.502 cc ± 0.190). The tumors were followed with MRS for at least three weeks post implantation.
Spectroscopy
Spectroscopy data collection and fitting were performed by Haejin Kang, with assistance from Carol Sweeney and J.R. Ballinger, as described in the previous section. In addition, an external standard containing 0.018 cc of 1 M hexachlorocyclotriphosphazene in benzene was located above the tumor, in the plane of the top of the coil. MRS was performed starting six days before chemotherapy, then twice weekly for three weeks.
Analysis of data
Analysis of the data was performed by J.R. Ballinger. The peak areas were normalized to the external standard to eliminate variability in the data from changes in instrumental sensitivity. The PCr/Pi data were found not to be in a normal distribution by a Shapiro-Wilks test; therefore, a Student's t-test could not be used. Instead, a two-tailed Wilcoxon Rank Sum Test was used to test the difference between the sensitive and resistant mice in the PCr/Pi change from the day before chemotherapy to two days following chemotherapy (three days later). The PME data were tested with both a two-tailed Student's t-test and the Wilcoxon Rank Sum Test. A ROC curve was drawn to show the predictive value of the change in the PCr/Pi slope in detecting the resistant tumors.
Results and Discussion
Tumor cell line
The chromium release assay showed spontaneous release of chromium (2 hours to 24 hours 5% to 35%, respectively, of total activity) did not differ significantly with drug concentration or cell line. This suggests that the cytotoxic effects of cisplatin at the concentrations tested occurs beyond 24 hours.
Drug sensitivities of the parent and resistant cell lines were compared based on their respective IC50's determined from the four-day growth assay that was run six times for each cell line (See Table 3-1). The E10-CIS subline was five times more resistant than the E10 parent cell line.
Table 3-1. Results of Four-day Growth Assay.1
| Osteosarcoma Cell Line | ||
| Cisplatin Concentration | 4.49±0.26 µg/ml | 22.56±6.57 µg/ml |
1Concentration of cisplatin at which the viable cell number is 50% inhibited compared to the cell number of untreated controls (IC50).
Animal study
Two of the cisplatin-sensitive tumors failed to grow well before chemotherapy and were excluded from the analysis. One mouse was sacrificed due to eye infection and weight loss. We had a final number of eight cisplatin-resistant and ten cisplatin-sensitive mice.
Spectra were similar in appearance and quality to those shown in the experiment comparing treated and untreated mice. The mean volume of the sensitive and resistant tumors as a function of time is shown in Figure 3-7. The graph of the mean PCr/Pi vs time (Figure 3-8) shows a divergence in the slopes after treatment of the tumors. This change in the slope of the PCr/Pi occurs before significant changes in tumor volume. The two-tailed, Wilcoxon Rank Sum Test shows statistical significance at the =0.05 level in the
Figure 3-7 Mean change in volume of sensitive and resistant tumors as a function of time. All of the mice received chemotherapy on day zero.
Figure 3-8 Mean change in PCr/Pi for sensitive and resistant mice as a function of time. All of the mice received chemotherapy on day 0. Change in the PCr/Pi ratio is seen as early as day 1 post chemotherapy. This change occurs before any change in the volume of the tumors (compare with Figure 3-9).
difference between the post treatment slopes for the sensitive and the resistant tumors. The change in the slope of the sensitive tumor from pre- to post-chemotherapy was tested and had a p value between 0.05 and 0.1. The change in the slope of the resistant tumor pre- to post-chemotherapy was not significant with a p value greater than 0.1. Calculating the post treatment slope from the projected value of PCr/Pi at time of treatment resulted in no significant change in these results.
The graph of the mean PME levels vs time (Figure 3-9) showed a transient and statistically insignificant decrease in the slope from day one to day five post chemotherapy in the sensitive tumors, paralleling roughly the change in tumor volume. The resistant tumors showed no change in the slope after chemotherapy.
The ability of the data to detect the resistant tumor may be expressed with a ROC curve as discussed earlier (190-193). The points on the ROC curve (Figure 3-10) were generated using Charles Metz's LABROC1 program that fits a binomial curve to the PCr/Pi data (194, 195). The area under the curve reflects the predictive value of the test with an area of 0.5 indicating no value and an area of one indicating a "perfect" test. Using the post-chemotherapy slopes for the ROC analysis, we obtained an area of 0.6674±0.1249.
Discussion
Our data show a slight but statistically significant difference in the change in PCr/Pi after treatment between sensitive and resistant osteosarcomas implanted into nude mice. The PCr/Pi change occurs before change in volume of the tumor. We would want to have a high specificity for detecting a resistant or
Figure 3-9 Graph of the mean PME ± one standard deviation vs time for sensitive and resistant mice. All of the mice received chemotherapy on day zero.
Figure 3-10 ROC Curve for detecting resistant tumors with the change in slope of the PCr/Pi ratio postchemotherapy. The true positive rate (sensitivity) is plotted as a function of the false positive rate (1-specificity).
nonresponder to chemotherapy to avoid discontinuing a treatment that is working. Using the post treatment PCr/Pi slopes to detect the resistant tumor, we can select a threshold that will give us a 70% specificity and a 54% sensitivity. This is not quite as good as our data with treated and untreated sensitive tumors but is qualitatively similar. We achieved an 80% specificity and a 63% sensitivity in the treated and untreated sensitive tumors. The difference between these two studies is to be expected since there was only a 5-fold difference in drug sensitivity of the two cell lines in vitro. We are currently acquiring data using a slice selective localization technique that may improve our ability to distinguish between sensitive and resistant tumors by diminishing contamination of our tumor spectra by underlying muscle.
Materials and Methods
Extensive developmental work has been done with phantoms and volunteers in vivo MRS. Because of the small number of osteosarcoma patients being referred to us and the low signal-to-noise seen in the one tumor patient that had P-31 MRS, we chose to delay acquisition of P-31 spectra from additional patients until after construction of a double-tuned, quadrature H-1/P-31 coil and possibly implementation of proton decoupling of spectra. We were obtaining H-1 spectra from patients that had significantly better signal-to-noise than the P-31 spectra, and so chose to concentrate on H-1 MRS.
Instrumentation
The 1.5 T GE Signa whole-body magnet was used for phantoms, volunteers, and the patient (Figure 3-11). A half-saddle coil double-tuned to H-1 and P-31 was used for most of the study. The coil was constructed by Jim Scott.
Localization development
In the background section, the considerable heterogeneity of tumors was noted. Therefore, we chose to use 2D-CSI for our experiments. This technique gives better spatial resolution than 1D-CSI and is not as time consuming as 3D-CSI. Two problems had to be overcome, the intervoxel bleeding that is inherently present with use of the technique, and registration of the CSI spectra with the image and volume of interest.
CSI and image registration was necessary to know from what part of the tumor or adjacent soft tissues a given spectrum came from. The SA/GE software allows the grid of spectra to be superimposed onto an image for this purpose. Because of differences in the way the images and the CSI data are acquired,
Figure 3-11 Photograph of the 1.5 T General Electric Signa whole- body imager.
flip and translation corrections were needed for an exact match. A left-to-right and top-to-bottom flip were required to match the image and CSI matrix in terms of orientation. A half CSI voxel shift was necessary in both spatial directions because the image localizing and CSI localizing gradients have different symmetry about the x and y axes. The flip and translation corrections were checked with phantoms and volunteers to ensure proper positioning.
Occasionally, a CSI voxel did not fall exactly on the area of interest. The voxel can be shifted by using a first order phase correction on the k-space data in the gradient (not time) dimensions. Susan Kohler, Ph.D., formerly of GE Medical Systems, was kind enough to write a macro for us to do this data manipulation. This macro was also tested on phantoms and volunteers.
Relaxation measurements
T1 relaxation measurements were made on volunteers since we were using a TR on the order of one T1 time of some of our metabolites. Partial saturation experiments were used, varying the TR from 1.6 sec to 11 secs. Data from these experiments were fit with a monoexponential curve using Statistica software (StatSoft, Tulsa, OK).
Shimming
Whole volume shimming on the water peak with H-1 MRS using a hard pulse was initially used in phantoms and in volunteers. The homogeneity obtained was only fair, so a slice selective shimming technique was subsequently used.
Spectral analysis
The CSI experiments use phase encoding gradients turned on after the acquisition 90o RF pulse is applied. In our case, this results in a loss of eight dwell periods (2 ms) of data from the FID. As a result, a large first order phase correction is necessary, resulting in a prominent baseline roll.
This is corrected using the sinc deconvolution technique mentioned in the Techniques chapter. When we first started, this technique had not been automated. I took eight point sine waves with relative frequencies matching those of the major metabolites, Fourier transformed them and added them to the distorted P-31 spectrum. The relative magnitudes of the added functions matched approximately the peak heights of the P-31 metabolites. The absolute magnitudes had to be adjusted empirically. Recently, the sinc deconvolution technique has been automated and included in the SA/GE software.
Reproducibility and linearity
The reproducibility of the signal measurements from phantoms and from volunteers was tested over the short term (2 hours) and a long term (2-3 months).
The linearity of the signal to the voxel size was checked with phantoms using the CSI technique. We expected to use different size voxels depending on the size of the tumor and location.
Normalization of data
An external standard containing 2 cc of 0.5 M or 1 M HCCTP was positioned at the base of the coil and used to normalize the data and control for instrumental variation. The CSI volume included the standard in one of the voxels. When the standard overlapped voxels, the shifting technique mentioned above was used to position the signal from the standard in the middle of one voxel. Because we used a half-saddle coil to acquire our data, the sensitivity of the coil to different voxels varied. This positional dependence was corrected for by a factor arrived from measurements of the signal from a large phantom containing a solution of PO4 in solution.
Tumor patient experiment
The single patient that we did was a 75-year old woman with a pleomorphic sarcoma, most consistent with a dedifferentiated liposarcoma, in her leg. We used the double-tuned half-saddle coil described above with the external standard. A localizing T1 weighted SE pulse sequence was used to obtain images through the tumor. At the widest part of the tumor, shimming was performed on an axial slice, 3.0 cm in thickness. Two-dimension CSI was then performed at this slice with a 16 x 16 matrix, 30 cm FOV, 2 sec TR, and two signal averages resulting in an acquisition time of about 17 min. The voxel volume is equal to thickness[(FOV/matrix)1.6]2 where 1.6 is a correction factor for use of the Hanning filter. In this patient's case, this gives us a volume of 27 cc. There were six voxels containing mostly tumor. Spectra from these voxels were analyzed in the fashion described above. PME was normalized to the external standard with a correction for coil sensitivity differences. The PCr/Pi ratio was calculated.
Results and Conclusions
Localization development
The amount of intervoxel bleed was reduced significantly with the use of a Hanning window. The signal from voxels not containing the phantom represented 31% of the total signal from the standard without the Hanning window and 4.9% with the Hanning window. This was best demonstrated with a small, 20 cc bottle of 500 mM HCCTP solution.
Good registration of the image and CSI data was obtained. The CSI shifting macro worked well. Figure 3-12 shows a photograph of the CSI data superimposed on an image of a human tumor that we examined with P-31 MRS.
Relaxation measurements
Table 3-2 shows the mean and standard deviation of measurements of T1 time for the P-31 metabolites obtained from calf skeletal muscle of three volunteers:
| PME | Pi | PDE | PCr | ATP |
| 3.79±1.31 sec |