- Email: [email protected]
Magnetic resonance spectroscopy and clinical cancer prognosis1
Guest Editorial
Magnetic Resonance Spectroscopy and Clinical Cancer Prognosis1 Kristen L. Zakian, PhD, Jason A. Koutcher, MD, PhD
While magnetic resonance imaging (MRI) revolutionized imaging in cancer, in vivo magnetic resonance spectroscopy (MRS), due to its potential to probe physiology, generated hopes of noninvasive assessment of tumor prognosis and changes related to treatment effects. Major advances such as the production of highly stable 1.5 Tesla clinical scanners, volume localization pulse sequences (image-selected in vivo spectroscopy [ISIS] (1), point-resolved spectroscopy [PRESS] (2), stimulated echo acquisition mode [STEAM] (3), chemical shift imaging [CSI] (4)), automated shimming algorithms, and proton-decoupling brought MRS to the level of investigative tool in the late 1980s and many sites began to apply it to various clinical questions. The in vivo 31P MR spectrum includes membrane phospholipid anabolites (phosphoethanolamine [PE], phosphocholine [PC]) and catabolites (glycerophosphoethanolamine [GPE], glycerophosphocholine [GPC]), high-energy phosphates (phosphocreatine [PCr], nucleotide triphosphates [NTP]) and inorganic phosphate (Pi). Thus it is possible to noninvasively assess a tumor’s energetic status as well as to observe alterations in cell membrane phospholipid metabolism. In addition, it is possible to derive the intracellular pH value from the relative chemical shifts of several peaks in the spectrum. Hence there are numerous 31P-containing molecular targets for study as possible markers of prognosis or treatment effects. Because of the inherently poor sensitivity of 31P MRS, most previous studies have investigated superficial tumors Acad Radiol 2004; 11:365–367 1 From the Departments of Medical Physics (K.L.Z., J.A.K.), Radiology (K.L.Z., J.A.K.), and Medicine (J.A.K.), Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021. Address correspondence to K.L.Z. e-mail: [email protected]
©
AUR, 2004 doi:10.1016/j.acra.2004.02.004
and their changes in metabolism with therapy. An ongoing effort at Duke University has used 31P MRS to investigate the relationship between tumor metabolism, hypoxia, and response to hyperthermia and radiation in soft tissue sarcomas (5–9). Pre-therapy pH and water T2 were shown to predict necrosis in human tumors (6,9), with higher T2 values and/or higher pH correlating positively with percent necrosis at the time of surgical resection. When changes between pre-treatment and followup studies were assessed, a decrease in NTP/PME, where PME ⫽ PE⫹PC, correlated with ⬎95% necrosis (6) and changes in NTP/Pi and PCr/Pi correlated negatively with percent necrosis at surgery (9). A recent study of 20 bone sarcoma patients at our institution has also demonstrated that better a priori tumor energetic status as indicated by the pre-treatment NTP/Pi value strongly predicts eventfree survival (10). It is noteworthy that in both the soft tissue and bone sarcoma studies, parameters related to energy metabolism were found to correlate with response and patients whose tumors had higher energy levels prior to therapy had better outcome. Kettelhack et al. found that the change in PME/NTP following isolated limb perfusion in extremity sarcomas predicted clinical response in 28 extremity sarcoma patients (11). In 12 head and neck tumor patients who underwent proton-decoupled 31P MRS, the pretreatment PME/NTP ratio was lower in complete vs. incomplete responders (12). Thus prior 31P MRS studies have indicated that cell membrane metabolism and tumor energy status may influence prognosis. The study by Arias-Mendoza et al. (13) presented in the April issue of Academic Radiology is the largest clinical 31P MRS study applied to a priori tumor prognosis to date with 46 patients yielding usable MR studies in 27 different patients. The number of unusable studies is not unexpected considering the fact that the methodology in
365
GUEST EDITORIAL
the early cases was still being optimized. In the last 19 patients studied, 17 were successful, indicating that the technology has matured to the level where these studies may be reliably performed. This study demonstrated that 31P MRS can predict prognosis in non-Hodgkin’s lymphoma and may fulfill some of its early promise. The ratio PME/NTP was found to be higher in patients destined to fail therapy. The MRS parameter correlated significantly with both clinical response and time to treatment failure (TTF). In addition, when combined with the international prognostic index (IPI), a standard prognosis marker in non-Hodgkin’s lymphoma based upon age, stage, performance status, lactate dehydrogenase level, and extranodal sites (14,15), the result was a more powerful predictor of both response and TTF. The area under the receiver operator characteristic (ROC) curve for prediction of treatment response using an IPI-dependent (PE⫹PC)/NTP cutoff was 0.929 compared with 0.853 for (PE⫹PC)/NTP alone and 0.682 for IPI alone. While large by 31P MRS standards, the number of subjects did not permit segregation by tumor pathology or treatment protocol. However, this study has lain the groundwork for a large multi-institutional trial to determine whether these results are repeatable in a larger population and whether segregation by pathology, treatment regimen, or other parameter provides more detailed prognostic information. To clinicians, this significant addition to standard clinical prognostic information could be extremely valuable in planning the optimal treatment for a patient. In current clinical practice, treatment for non-Hodgkin’s lymphomas is chosen based on pathology and the international prognostic index. However, despite the utility of the factors incorporated in the IPI, further studies are ongoing to validate other predictive factors (16,17). The current study suggests that non-invasively measured 31P MRS metabolic parameters may have prognostic value that must be validated by statistically rigorous, multi-institutional studies to ensure their validity prior to clinical applications such as the enhancement of treatment stratification strategies. Elevated levels of the phospholipid precursors phosphocholine and phosphoethanolamine in human tumors have been detected by numerous investigators using 31P MRS (18 –22). Phosphoethanolamine is a precursor in the conversion pathway of ethanolamine to phosphatidylethanolamine; similarly, phosphocholine is a precursor to phosphatidylcholine. In early studies, resolution of the PE and PC peaks, which are separated by 0.5 ppm, was difficult and the sum of the two, ie, total phosphomonoesters (PME) was generally reported. When proton-decoupling
366
Academic Radiology, Vol 11, No 4, April 2004
is applied, the two peaks are better resolved; however, as Arias-Mendoza point out, experimental conditions can still result in imperfect resolution. The reasons for the elevation in PME in tumors and for the difference in PME levels in responders vs. nonresponders are still under investigation. To be sure, 31P MRS has its drawbacks. A 31P channel is required on the scanner as well as a proton-decoupler if the highest quality spectra are to be obtained. The studies are lengthy and the voxel size large. However, the ability to predict outcome prior to any treatment would be of tremendous benefit to clinicians planning treatment and to patients who could be spared significant morbidity. As more and more sites are installing high-field (3 Tesla) MR scanners, there is potential to reduce voxel size and/or scan time in 31P studies. Thus in superficial tumors such as lymphomas, sarcomas, and head and neck tumors, there is a body of data accruing that strongly suggests that valuable prognostic information can be obtained from 31P MRS studies. Despite the Herculean efforts at patient recruitment and technology development by the group from Fox Chase Cancer Center, the numbers of patients in this and other similar studies (6,10,12), remain small from a statistical perspective. It is clear that to validate these data will require the cooperative effort of multiple large institutions that have access to both state-of-the-art MRS technology and a large population of appropriate patients who could be enrolled in studies. Undoubtedly, to convince clinical oncologists, appropriate stratification (treatment-naı¨ve patients vs. patients who have previously failed therapy, various histologies, etc.) will be required, which will further increase the number of patients required for study. Support from the National Institutes of Health (NIH) will be necessary to coordinate and complete a project of the magnitude necessary to validate this and studies of other tumor sites. In addition to NIH support, a critical component for the success of a large study will be recognition by the major MR vendors of the potential value of this tool so that they too will invest in upgrading the technology, and simplifying and increasing the robustness of both the acquisition and analysis of the data. Historically, MRI was developed at academic centers (23–26). However, it only became a clinically powerful tool when major vendors recognized its future value and invested in developing improved hardware and software, so that images could be readily and reproducibly obtained. A similar effort by the major MR manufacturers will be necessary if 31P MRS is
ZAKIAN AND KOUTCHER
Academic Radiology, Vol 11, No 4, April 2004
to become a robust and reproducible tool, both in major academic centers and also in the community. While both cellular energetics and cell membrane metabolism appear to be related to outcome, at least some of the necessary prognostic information may be available from proton spectroscopy. Levels of lactate (energetics) and total choline (membrane metabolism) may be studied by proton MRS. Proton techniques have the advantage of shorter scan times, smaller voxel sizes, and applicability on standard scanner hardware. Various human proton MRS studies have been performed attempting to link baseline tumor proton characteristics to prognosis. For example, correlation between baseline proton spectra and treatment response or outcome has been reported in extracranial lymphomas and germ cell tumors (27) and in multiple studies of recurrent gliomas (28 –30). Whether phosphorus or proton techniques are used, data are accumulating that indicate that MRS will play an important role in cancer prognosis. The speed with which that will occur will depend on the availability of funding and vendor cooperation.
12.
13.
14. 15.
16.
17.
18.
19.
20. REFERENCES 1. Ordidge RJ, Connelly A, Lohman JAB. Image-selected in vivo spectroscopy (ISIS): A new technique for spatially selective NMR spectroscopy. J Magn Reson 1986; 66:283–294. 2. Bottomley P. Selective volume method for performing localized NMR spectroscopy. US patent 4 480 228. 1984. 3. Frahm J, Bruhn H, Gyngell MNL, Merboldt KD, Hanicke W, Sauter R. Localized high-resolution proton NMR spectroscopy using stimulated echoes: Initial applications to human brain in vivo. Magn Reson Med 1989; 9:79 –93. 4. Brown TR, Kincaid BM, Ugurbil K. NMR chemical shift imaging in three dimensions. Proc Natl Acad Sci U S A 1982; 79:3523–3526. 5. Brizel DM, Scully SP, Harrelson JM, et al. Radiation therapy and hyperthermia improve the oxygenation of human soft tissue sarcomas. Cancer Res 1996; 56:5347–5350. 6. Sostman HD, Prescott DM, Dewhirst MW, et al. MR imaging and spectroscopy for prognostic evaluation in soft-tissue sarcomas. Radiology 1994; 190:269 –275. 7. Prescott DM, Charles HC, Sostman HD, et al. Therapy monitoring in human and canine soft tissue sarcomas using magnetic resonance imaging and spectroscopy. Int J Radiat Oncol Biol Phys 1994; 28:415– 423. 8. Sostman HD, Charles HC, Rockwell S, et al. Soft-tissue sarcomas: detection of metabolic heterogeneity with P-31 MR spectroscopy. Radiology 1990; 176:837– 843. 9. Dewhirst MW, Sostman HD, Leopold KA, et al. Soft-tissue sarcomas: MR imaging and MR spectroscopy for prognosis and therapy monitoring. Work in progress. Radiology 1990; 174(3 Pt 1):847– 853. 10. Zakian KL, Shukla-Dave A, Meyers P, et al. Identification of prognostic markers in bone sarcomas using proton-decoupled phosphorus magnetic resonance spectroscopy. Cancer Res 2003; 63:9042–9047. 11. Kettelhack C, Wickede M, Vogl T, Schneider U, Hohenberger P. 31Phosphorus-magnetic resonance spectroscopy to assess histologic
21.
22.
23. 24.
25.
26. 27.
28.
29.
30.
tumor response noninvasively after isolated limb perfusion for soft tissue tumors. Cancer 2002; 94:1557–1564. Shukla-Dave A, Poptani H, Loevner LA, et al. Prediction of treatment response of head and neck cancers with P-31 MR spectroscopy from pretreatment relative phosphomonoester levels. Acad Radiol 2002; 9:688 – 694. Arias-Mendoza F, Smith MR, Brown TR. Predicting treatment response in non-Hodgkin’s lymphoma from the pretreatment tumor content of phosphoethanolamine plus phosphocholine. Acad Radiol 2004; 11:368 –376. Smith MR. Non-Hodgkin’s lymphoma. Current Problems in Cancer 1996; 20:1– 80. A predictive model for aggressive non-Hodgkin’s lymphoma. The International Non-Hodgkin’s Lymphoma Prognostic Factors Project. N Engl J Med 1993; 329:987–994. Korkolopoulou P, Angelopoulou MK, Kontopidou F, et al. Prognostic implications of proliferating cell nuclear antigen (PCNA), AgNORs and P53 in non-Hodgkin’s lymphomas. Leuk Lymphoma 1998; 30:625– 636. Ristamaki R, Joensuu H, Soderstrom KO, Jalkanen S. CD44v6 expression in non-Hodgkin’s lymphoma: an association with low histological grade and poor prognosis. J Pathol 1995; 176:259 –267. Negendank WG, Padavic-Shaller KA, Li CW, et al. Metabolic characterization of human non-Hodgkin’s lymphomas in vivo with the use of proton-decoupled phosphorus magnetic resonance spectroscopy. Cancer Res 1995; 55:3286 –3294. Negendank WG, Crowley MG, Ryan JR, Keller NA, Evelhoch JL. Bone and soft-tissue lesions: diagnosis with combined H-1 MR imaging and P-31 MR spectroscopy. Radiology 1989; 173:181–188. Li CW, Kuesel AC, Padavic-Shaller KA, et al. Metabolic characterization of human soft tissue sarcomas in vivo and in vitro using protondecoupled phosphorus magnetic resonance spectroscopy. Cancer Res 1996; 56:2964 –2972. Koutcher JA, Ballon D, Graham M, et al. 31P NMR spectra of extremity sarcomas: diversity of metabolic profiles and changes in response to chemotherapy. Magn Reson Med 1990; 16:19 –34. Francis IR, Chenevert TL, Gubin B, et al. Malignant hepatic tumors: P-31 MR spectroscopy with one-dimensional chemical shift imaging. Radiology 1991; 180:341–344. Damadian R. Tumor detection by nuclear magnetic resonance. Science 1971; 171:1151–1153. Damadian R, Goldsmith M, Minkoff L. NMR in cancer: XVI. FONAR image of the live human body. Physiol Chem Phys 1977; 9:97–100, 108. Lauterbur PC. Image formation by induced local interactions: Examples employing nuclear magnetic resonance. Nature 1973; 242:190 – 191. Mansfield P, Grannell PK. NMR “diffraction” in solids? J Phys C: Solid State Phys 1973; 6(L422–L427). Schwarz AJ, Maisey NR, Collins DJ, Cunningham D, Huddart R, Leach MO. Early in vivo detection of metabolic response: a pilot study of 1H MR spectroscopy in extracranial lymphoma and germ cell tumours. Br J Radiol 2002; 75:959 –966. Tarnawski R, Sokol M, Pieniazek P, et al. 1H-MRS in vivo predicts the early treatment outcome of postoperative radiotherapy for malignant gliomas. Int J Radiat Oncol Biol Phys 2002; 52:1271–1276. Graves EE, Nelson SJ, Vigneron DB, et al. A preliminary study of the prognostic value of proton magnetic resonance spectroscopic imaging in gamma knife radiosurgery of recurrent malignant gliomas. Neurosurgery 2000; 46:319 –326; discussion 326 –318. Preul MC, Caramanos Z, Villemure JG, et al. Using proton magnetic resonance spectroscopic imaging to predict in vivo the response of recurrent malignant gliomas to tamoxifen chemotherapy. Neurosurgery 2000; 46:306 –318.
367
Magnetic Resonance Spectroscopy and Clinical Cancer Prognosis1 Kristen L. Zakian, PhD, Jason A. Koutcher, MD, PhD
While magnetic resonance imaging (MRI) revolutionized imaging in cancer, in vivo magnetic resonance spectroscopy (MRS), due to its potential to probe physiology, generated hopes of noninvasive assessment of tumor prognosis and changes related to treatment effects. Major advances such as the production of highly stable 1.5 Tesla clinical scanners, volume localization pulse sequences (image-selected in vivo spectroscopy [ISIS] (1), point-resolved spectroscopy [PRESS] (2), stimulated echo acquisition mode [STEAM] (3), chemical shift imaging [CSI] (4)), automated shimming algorithms, and proton-decoupling brought MRS to the level of investigative tool in the late 1980s and many sites began to apply it to various clinical questions. The in vivo 31P MR spectrum includes membrane phospholipid anabolites (phosphoethanolamine [PE], phosphocholine [PC]) and catabolites (glycerophosphoethanolamine [GPE], glycerophosphocholine [GPC]), high-energy phosphates (phosphocreatine [PCr], nucleotide triphosphates [NTP]) and inorganic phosphate (Pi). Thus it is possible to noninvasively assess a tumor’s energetic status as well as to observe alterations in cell membrane phospholipid metabolism. In addition, it is possible to derive the intracellular pH value from the relative chemical shifts of several peaks in the spectrum. Hence there are numerous 31P-containing molecular targets for study as possible markers of prognosis or treatment effects. Because of the inherently poor sensitivity of 31P MRS, most previous studies have investigated superficial tumors Acad Radiol 2004; 11:365–367 1 From the Departments of Medical Physics (K.L.Z., J.A.K.), Radiology (K.L.Z., J.A.K.), and Medicine (J.A.K.), Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021. Address correspondence to K.L.Z. e-mail: [email protected]
©
AUR, 2004 doi:10.1016/j.acra.2004.02.004
and their changes in metabolism with therapy. An ongoing effort at Duke University has used 31P MRS to investigate the relationship between tumor metabolism, hypoxia, and response to hyperthermia and radiation in soft tissue sarcomas (5–9). Pre-therapy pH and water T2 were shown to predict necrosis in human tumors (6,9), with higher T2 values and/or higher pH correlating positively with percent necrosis at the time of surgical resection. When changes between pre-treatment and followup studies were assessed, a decrease in NTP/PME, where PME ⫽ PE⫹PC, correlated with ⬎95% necrosis (6) and changes in NTP/Pi and PCr/Pi correlated negatively with percent necrosis at surgery (9). A recent study of 20 bone sarcoma patients at our institution has also demonstrated that better a priori tumor energetic status as indicated by the pre-treatment NTP/Pi value strongly predicts eventfree survival (10). It is noteworthy that in both the soft tissue and bone sarcoma studies, parameters related to energy metabolism were found to correlate with response and patients whose tumors had higher energy levels prior to therapy had better outcome. Kettelhack et al. found that the change in PME/NTP following isolated limb perfusion in extremity sarcomas predicted clinical response in 28 extremity sarcoma patients (11). In 12 head and neck tumor patients who underwent proton-decoupled 31P MRS, the pretreatment PME/NTP ratio was lower in complete vs. incomplete responders (12). Thus prior 31P MRS studies have indicated that cell membrane metabolism and tumor energy status may influence prognosis. The study by Arias-Mendoza et al. (13) presented in the April issue of Academic Radiology is the largest clinical 31P MRS study applied to a priori tumor prognosis to date with 46 patients yielding usable MR studies in 27 different patients. The number of unusable studies is not unexpected considering the fact that the methodology in
365
GUEST EDITORIAL
the early cases was still being optimized. In the last 19 patients studied, 17 were successful, indicating that the technology has matured to the level where these studies may be reliably performed. This study demonstrated that 31P MRS can predict prognosis in non-Hodgkin’s lymphoma and may fulfill some of its early promise. The ratio PME/NTP was found to be higher in patients destined to fail therapy. The MRS parameter correlated significantly with both clinical response and time to treatment failure (TTF). In addition, when combined with the international prognostic index (IPI), a standard prognosis marker in non-Hodgkin’s lymphoma based upon age, stage, performance status, lactate dehydrogenase level, and extranodal sites (14,15), the result was a more powerful predictor of both response and TTF. The area under the receiver operator characteristic (ROC) curve for prediction of treatment response using an IPI-dependent (PE⫹PC)/NTP cutoff was 0.929 compared with 0.853 for (PE⫹PC)/NTP alone and 0.682 for IPI alone. While large by 31P MRS standards, the number of subjects did not permit segregation by tumor pathology or treatment protocol. However, this study has lain the groundwork for a large multi-institutional trial to determine whether these results are repeatable in a larger population and whether segregation by pathology, treatment regimen, or other parameter provides more detailed prognostic information. To clinicians, this significant addition to standard clinical prognostic information could be extremely valuable in planning the optimal treatment for a patient. In current clinical practice, treatment for non-Hodgkin’s lymphomas is chosen based on pathology and the international prognostic index. However, despite the utility of the factors incorporated in the IPI, further studies are ongoing to validate other predictive factors (16,17). The current study suggests that non-invasively measured 31P MRS metabolic parameters may have prognostic value that must be validated by statistically rigorous, multi-institutional studies to ensure their validity prior to clinical applications such as the enhancement of treatment stratification strategies. Elevated levels of the phospholipid precursors phosphocholine and phosphoethanolamine in human tumors have been detected by numerous investigators using 31P MRS (18 –22). Phosphoethanolamine is a precursor in the conversion pathway of ethanolamine to phosphatidylethanolamine; similarly, phosphocholine is a precursor to phosphatidylcholine. In early studies, resolution of the PE and PC peaks, which are separated by 0.5 ppm, was difficult and the sum of the two, ie, total phosphomonoesters (PME) was generally reported. When proton-decoupling
366
Academic Radiology, Vol 11, No 4, April 2004
is applied, the two peaks are better resolved; however, as Arias-Mendoza point out, experimental conditions can still result in imperfect resolution. The reasons for the elevation in PME in tumors and for the difference in PME levels in responders vs. nonresponders are still under investigation. To be sure, 31P MRS has its drawbacks. A 31P channel is required on the scanner as well as a proton-decoupler if the highest quality spectra are to be obtained. The studies are lengthy and the voxel size large. However, the ability to predict outcome prior to any treatment would be of tremendous benefit to clinicians planning treatment and to patients who could be spared significant morbidity. As more and more sites are installing high-field (3 Tesla) MR scanners, there is potential to reduce voxel size and/or scan time in 31P studies. Thus in superficial tumors such as lymphomas, sarcomas, and head and neck tumors, there is a body of data accruing that strongly suggests that valuable prognostic information can be obtained from 31P MRS studies. Despite the Herculean efforts at patient recruitment and technology development by the group from Fox Chase Cancer Center, the numbers of patients in this and other similar studies (6,10,12), remain small from a statistical perspective. It is clear that to validate these data will require the cooperative effort of multiple large institutions that have access to both state-of-the-art MRS technology and a large population of appropriate patients who could be enrolled in studies. Undoubtedly, to convince clinical oncologists, appropriate stratification (treatment-naı¨ve patients vs. patients who have previously failed therapy, various histologies, etc.) will be required, which will further increase the number of patients required for study. Support from the National Institutes of Health (NIH) will be necessary to coordinate and complete a project of the magnitude necessary to validate this and studies of other tumor sites. In addition to NIH support, a critical component for the success of a large study will be recognition by the major MR vendors of the potential value of this tool so that they too will invest in upgrading the technology, and simplifying and increasing the robustness of both the acquisition and analysis of the data. Historically, MRI was developed at academic centers (23–26). However, it only became a clinically powerful tool when major vendors recognized its future value and invested in developing improved hardware and software, so that images could be readily and reproducibly obtained. A similar effort by the major MR manufacturers will be necessary if 31P MRS is
ZAKIAN AND KOUTCHER
Academic Radiology, Vol 11, No 4, April 2004
to become a robust and reproducible tool, both in major academic centers and also in the community. While both cellular energetics and cell membrane metabolism appear to be related to outcome, at least some of the necessary prognostic information may be available from proton spectroscopy. Levels of lactate (energetics) and total choline (membrane metabolism) may be studied by proton MRS. Proton techniques have the advantage of shorter scan times, smaller voxel sizes, and applicability on standard scanner hardware. Various human proton MRS studies have been performed attempting to link baseline tumor proton characteristics to prognosis. For example, correlation between baseline proton spectra and treatment response or outcome has been reported in extracranial lymphomas and germ cell tumors (27) and in multiple studies of recurrent gliomas (28 –30). Whether phosphorus or proton techniques are used, data are accumulating that indicate that MRS will play an important role in cancer prognosis. The speed with which that will occur will depend on the availability of funding and vendor cooperation.
12.
13.
14. 15.
16.
17.
18.
19.
20. REFERENCES 1. Ordidge RJ, Connelly A, Lohman JAB. Image-selected in vivo spectroscopy (ISIS): A new technique for spatially selective NMR spectroscopy. J Magn Reson 1986; 66:283–294. 2. Bottomley P. Selective volume method for performing localized NMR spectroscopy. US patent 4 480 228. 1984. 3. Frahm J, Bruhn H, Gyngell MNL, Merboldt KD, Hanicke W, Sauter R. Localized high-resolution proton NMR spectroscopy using stimulated echoes: Initial applications to human brain in vivo. Magn Reson Med 1989; 9:79 –93. 4. Brown TR, Kincaid BM, Ugurbil K. NMR chemical shift imaging in three dimensions. Proc Natl Acad Sci U S A 1982; 79:3523–3526. 5. Brizel DM, Scully SP, Harrelson JM, et al. Radiation therapy and hyperthermia improve the oxygenation of human soft tissue sarcomas. Cancer Res 1996; 56:5347–5350. 6. Sostman HD, Prescott DM, Dewhirst MW, et al. MR imaging and spectroscopy for prognostic evaluation in soft-tissue sarcomas. Radiology 1994; 190:269 –275. 7. Prescott DM, Charles HC, Sostman HD, et al. Therapy monitoring in human and canine soft tissue sarcomas using magnetic resonance imaging and spectroscopy. Int J Radiat Oncol Biol Phys 1994; 28:415– 423. 8. Sostman HD, Charles HC, Rockwell S, et al. Soft-tissue sarcomas: detection of metabolic heterogeneity with P-31 MR spectroscopy. Radiology 1990; 176:837– 843. 9. Dewhirst MW, Sostman HD, Leopold KA, et al. Soft-tissue sarcomas: MR imaging and MR spectroscopy for prognosis and therapy monitoring. Work in progress. Radiology 1990; 174(3 Pt 1):847– 853. 10. Zakian KL, Shukla-Dave A, Meyers P, et al. Identification of prognostic markers in bone sarcomas using proton-decoupled phosphorus magnetic resonance spectroscopy. Cancer Res 2003; 63:9042–9047. 11. Kettelhack C, Wickede M, Vogl T, Schneider U, Hohenberger P. 31Phosphorus-magnetic resonance spectroscopy to assess histologic
21.
22.
23. 24.
25.
26. 27.
28.
29.
30.
tumor response noninvasively after isolated limb perfusion for soft tissue tumors. Cancer 2002; 94:1557–1564. Shukla-Dave A, Poptani H, Loevner LA, et al. Prediction of treatment response of head and neck cancers with P-31 MR spectroscopy from pretreatment relative phosphomonoester levels. Acad Radiol 2002; 9:688 – 694. Arias-Mendoza F, Smith MR, Brown TR. Predicting treatment response in non-Hodgkin’s lymphoma from the pretreatment tumor content of phosphoethanolamine plus phosphocholine. Acad Radiol 2004; 11:368 –376. Smith MR. Non-Hodgkin’s lymphoma. Current Problems in Cancer 1996; 20:1– 80. A predictive model for aggressive non-Hodgkin’s lymphoma. The International Non-Hodgkin’s Lymphoma Prognostic Factors Project. N Engl J Med 1993; 329:987–994. Korkolopoulou P, Angelopoulou MK, Kontopidou F, et al. Prognostic implications of proliferating cell nuclear antigen (PCNA), AgNORs and P53 in non-Hodgkin’s lymphomas. Leuk Lymphoma 1998; 30:625– 636. Ristamaki R, Joensuu H, Soderstrom KO, Jalkanen S. CD44v6 expression in non-Hodgkin’s lymphoma: an association with low histological grade and poor prognosis. J Pathol 1995; 176:259 –267. Negendank WG, Padavic-Shaller KA, Li CW, et al. Metabolic characterization of human non-Hodgkin’s lymphomas in vivo with the use of proton-decoupled phosphorus magnetic resonance spectroscopy. Cancer Res 1995; 55:3286 –3294. Negendank WG, Crowley MG, Ryan JR, Keller NA, Evelhoch JL. Bone and soft-tissue lesions: diagnosis with combined H-1 MR imaging and P-31 MR spectroscopy. Radiology 1989; 173:181–188. Li CW, Kuesel AC, Padavic-Shaller KA, et al. Metabolic characterization of human soft tissue sarcomas in vivo and in vitro using protondecoupled phosphorus magnetic resonance spectroscopy. Cancer Res 1996; 56:2964 –2972. Koutcher JA, Ballon D, Graham M, et al. 31P NMR spectra of extremity sarcomas: diversity of metabolic profiles and changes in response to chemotherapy. Magn Reson Med 1990; 16:19 –34. Francis IR, Chenevert TL, Gubin B, et al. Malignant hepatic tumors: P-31 MR spectroscopy with one-dimensional chemical shift imaging. Radiology 1991; 180:341–344. Damadian R. Tumor detection by nuclear magnetic resonance. Science 1971; 171:1151–1153. Damadian R, Goldsmith M, Minkoff L. NMR in cancer: XVI. FONAR image of the live human body. Physiol Chem Phys 1977; 9:97–100, 108. Lauterbur PC. Image formation by induced local interactions: Examples employing nuclear magnetic resonance. Nature 1973; 242:190 – 191. Mansfield P, Grannell PK. NMR “diffraction” in solids? J Phys C: Solid State Phys 1973; 6(L422–L427). Schwarz AJ, Maisey NR, Collins DJ, Cunningham D, Huddart R, Leach MO. Early in vivo detection of metabolic response: a pilot study of 1H MR spectroscopy in extracranial lymphoma and germ cell tumours. Br J Radiol 2002; 75:959 –966. Tarnawski R, Sokol M, Pieniazek P, et al. 1H-MRS in vivo predicts the early treatment outcome of postoperative radiotherapy for malignant gliomas. Int J Radiat Oncol Biol Phys 2002; 52:1271–1276. Graves EE, Nelson SJ, Vigneron DB, et al. A preliminary study of the prognostic value of proton magnetic resonance spectroscopic imaging in gamma knife radiosurgery of recurrent malignant gliomas. Neurosurgery 2000; 46:319 –326; discussion 326 –318. Preul MC, Caramanos Z, Villemure JG, et al. Using proton magnetic resonance spectroscopic imaging to predict in vivo the response of recurrent malignant gliomas to tamoxifen chemotherapy. Neurosurgery 2000; 46:306 –318.
367