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Magnetic Resonance Spectroscopy Guided Brain Tumor Resection: Differentiation Between Recurrent Glioma and Radiation Change in Two Diagnostically Difficult Cases

Published online by Cambridge University Press:  18 September 2015

Mark C. Preul ,
Richard Leblanc ,
Zografos Caramanos ,
Reza Kasrai ,
Sridar Narayanan  and
Douglas L. Arnold
Mark C. Preul
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
Richard Leblanc*
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
Zografos Caramanos
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
Reza Kasrai
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
Sridar Narayanan
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
Douglas L. Arnold
Affiliation:
Department of Neurology and Neurosurgery, MR Spectroscopy Unit and Neurolmaging Laboratory, Montreal Neurological Hospital and Institute, Montreal
*
Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, Quebec, Canada H3A 2B4
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Abstract:

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Background:

It is often difficult to differentiate a recurrent glioma from the effects of post-operative radiotherapy by means of conventional neurodiagnostic imaging. Proton magnetic resonance spectroscopic imaging (1H-MRSI), that allows in vivo measurements of the concentration of brain metabolites such as choline-containing phospholipids (Cho), may provide in vivo biochemical information helpful in distinguishing areas of tumor recurrence from areas of radiation effect.

Patients and Methods:

Two patients who had undergone resection and post-operative radiotherapy for a cerebral glioma became newly symptomatic. Computed tomographic (CT) and magnetic resonance imaging (MRI) performed after the intravenous infusion of contrast material, and in one case, [18F] fluorodeoxyglucose positron emission tomography (PET), could not differentiate between the possibilities of recurrent glioma and radiation effect. The patients underwent 1H-MRSI prior to reoperation and the 1H-MRSI results were compared to histological findings originating from the same locations.

Results:

A high Cho signal measured by 1H-MRSI was seen in areas of histologicallyproven dense tumor recurrence, while low Cho signal was present where radiation changes predominated.

Conclusions:

The differentiation between the recurrence of a cerebral glioma and the effects of post-operative irradiation was achieved using 1H-MRSI in these two patients whose conventional neurodiagnostic imaging was equivocal for such a distinction. Where these two conditions are present, metabolite images from 1H-MRSI, such as that based on Cho, can be co-registered with other imaging modalities such as MRI and may also be integrated with functional MRI or functional PET within a multimodal imaging-guided surgical navigation system to assure maximal resection of recurrent tumor while minimizing the risk of added neurological damage.

Type
Expedited Publication
Information
Canadian Journal of Neurological Sciences , Volume 25 , Issue 1 , February 1998 , pp. 13 - 22
Copyright
Copyright © Canadian Neurological Sciences Federation 1998

References

REFERENCES

1.Preul, MC, Collins, DL, Arnold, DL. Differential diagnosis of human intracranial tumors in vivo using 1H-MR spectroscopic imaging and feature space for spectral pattern recognition. In: Shorvon, SD, Fish, DR, Andermann, F, Bydder, GM, Stefan, H, eds. Magnetic Resonance Scanning and Epilepsy. New York: Plenum, 1993: 299–313.Google Scholar
2.Preul, MC, Caramanos, Z, Collins, DL, et al. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy. Nature Medicine 1996; 2: 323–325.CrossRefGoogle ScholarPubMed
3.Preul, MC, Narayanan, S, Co meau, R, et al. Intraoperative, interactive guidance of stereotactic brain tumor biopsy or resection using in vivo biochemical image - anatomical image integration. J Neurosurg 1996; 84: 344A.Google Scholar
4.Preul, MC, Caramanos, Z, Leblanc, R, et al. Improved stereotactic brain tumor biopsy or resection using in vivo biochemical imaging: accurate prediction of regional tissue chemicopathological characteristics leads to more accurate target planning. J Neurosurg 1997; 86: 361A–362A.Google Scholar
5.Heesters, MA, Kamman, RL, Mooyaart, EL, Go KG. Localized proton spectroscopy of inoperable brain gliomas. Response to radiation therapy. J Neurooncol 1993; 17: 27–35.CrossRefGoogle ScholarPubMed
6.Wald, LL, Nelson, SJ, Day, MR, et al. Serial proton magnetic resonance spectroscopy imaging of glioblastoma multiforme after brachytherapy. Journal of Neurosurgery 1997; 87: 525–534.CrossRefGoogle ScholarPubMed
7.Tedeschi, G, Lundbom, N, Raman, R, et al. Increased choline signal coinciding with malignant degeneration of cerebral gliomas: a serial proton magnetic resonance spectroscopy imaging study. Journal of Neurosurgery 1997; 87: 516–524.CrossRefGoogle ScholarPubMed
8.Culver, KW, Rom, Z, Wallbridge, S, et al. In vivo gene transfer with retroviral-producer cells for the treatment of experimental brain tumors. Science 1992; 256: 1550–1552.CrossRefGoogle Scholar
9.Moolten, FL, Wells, JM. Curability of tumors bearing herpes thymidine kinase genes transferred by retroviral vectors. Journal of the National Cancer Institute 1990; 82: 297–300.CrossRefGoogle ScholarPubMed
10.Ezzedine, ZD, Martuza, RL, Platika, D, et al. Selective killing of glioma cells in culture and in vivo by retrovirus transfer of the herpes simplex thymidine kinase gene. New Biologist 1991; 3: 608–614.Google Scholar
11.Ram, Z, Culver, KW, Walbridge, S, Blaese, RM, Oldfield, EH. In situ retroviral-mediated gene transfer for the treatment of brain tumors in rats. Cancer Research 1993; 53: 83–88.Google ScholarPubMed
12.Sandoz Pharma Ltd. Study no. GLIB 201-E-00 Gene therapy for the treatment of glioblastoma multiforme with in vivo tumor transduction with the herpes simplex thymidine kinase gene/ganciclovir system. Sandoz Pharma Ltd 1995.Google Scholar
13.Fulham, MJ, Bizzi, A, Dietz, MJ, et al. Mapping of brain tumor metabolites with proton MR spectroscopic imaging: clinical relevance. Radiology 1992; 185: 675–686.CrossRefGoogle ScholarPubMed
14.Furuya, S, Naruse, S, Ide, M, et al. [The clinical application of multivoxel 1H-CSI (chemical shift imaging) in brain tumors]. [Japanese]. Nippon Igaku Hoshasen Gakkai Zasshi 1991; 51: 836–838.Google Scholar
15.Alger, JR, Frank, JA, Bizzi, A, et al. Metabolism of human gliomas: assessment with H-l MR spectroscopy and F-18 fluorodeoxyglucose PET [see comments]. Radiology 1990; 177: 633–641.CrossRefGoogle Scholar
16.Negendank, WG, Sauter, R, Brown, TR, et al. Proton magnetic resonance spectroscopy in patients with glial tumors: a multicenter study. J Neurosurg 1996; 84: 449–458.CrossRefGoogle ScholarPubMed
17.Kauppinen, RA, Williams, SR. Nuclear magnetic resonance spectroscopy studies of the brain. [Review]. Prog Neurobiol 1994; 44: 87–118.CrossRefGoogle ScholarPubMed
18.Klein, J, Koppen, A, Loffelhoz, K, Schmitthenner, J. Uptake and metabolism of choline by rat brain after acute choline administration. Journal of Neurochemistry 1992; 58: 870–876.CrossRefGoogle ScholarPubMed
19.Sibson, R. Studies in the robustness of multidimensional scaling: Procrustes statistics. Journal of the Royal Statistical Society 1978; 40: 234–238.Google Scholar
20.Collingnon, A, Maes, F, Delaere, D, et al. Automated muli-modality image registration based on information theory. Information Processing in Medical Imaging 1995; proceedings: 263–274.Google Scholar
21.Collins, DL, Neelin, P, Peters, TM, Evans, AC. Automatic 3-D intersubject registration of MR volumetric data in standardized Talairach space. Journal of Computer Assisted Tomography 1994; 18: 192–205.CrossRefGoogle Scholar
22.Woods, RP, Mazziotta, JC, Cherry, SR. MRI-PET registration with automated algorithm. J Comput Assist Tomogr 1993; 17: 536–546.CrossRefGoogle ScholarPubMed
23.Neelin, P, Crossman, J, Hawkes, DJ, Ma, Y, Evans, AC. Validation of an MRI/PET landmark registration method using 3D simulated PET images and point simulations. Computerized Medical Imaging and Graphics 1993; 17: 351–356.CrossRefGoogle ScholarPubMed
24.Evans, AC, Marrett, S, Torrescorzo, J, Ku, S, Collins, DL. MRI-PET correlation in three dimensions using a volume of interest (VOl) atlas. Journal of Cerebral Blood Flow and Metabolism 1991; 11: A69–A78.CrossRefGoogle Scholar
25.Alexander, E3rd, Loeffler, JS, Schwartz, RB, et al. Thallium-210 technetium-99m HMPAO single-photon emission computed tomography (SPECT) imaging for guiding stereotactic craniotomies in heavily irradiated mailgnant glioma patients. Acta Neurochirurgica (Wien) 1993; 122: 215–217.CrossRefGoogle Scholar
26.Buchpiguel, CA, Alavi, JB, Alavi, A, Kenyon, LC. PET versus SPECT in distinguishing radiation necrosis from tumor recurrence in the brain [clinical conference]. Journal of Nuclear Medicine 1995; 36: 159–164.Google ScholarPubMed
27.Schwartz, RB, Carvalho, PA, Alexander, E3rd, et al. Radiation necrosis vs. high-grade recurrent glioma: differentiation by using dualisotope SPECT with 201TI and 99mTc-HMPAO. American Journal of Neuroradiology 1991; 12: 1187–1192.Google ScholarPubMed
28.Tyler, JL, Villemure, JG, Evans, AC, et al. Metabolic and hemodynamic evaluation of gliomas using positron emission tomography. Journal of Nuclear Medicine 1987; 28: 1123–1133.Google ScholarPubMed
29.Janus, TJ, Kim, EE, Tilbury, R., et al. Use of [18F]fluorodeoxyglucose positron emission tomography in patients with primary malignant brain tumors. Annals of Neurology 1993; 33: 540–548.CrossRefGoogle ScholarPubMed
30.Aronen, HJ, Gazit, IE, Louis, DN, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. RAdiology 1994; 191: 41–51.CrossRefGoogle ScholarPubMed
31.Preul, MC, Caramanos, Z, Collins, DL, Arnold, DL. Linear discriminant analysis based on proton MR spectroscopic imaging of human brain tumors improves pre-operative diagnosis. Proc Soc Magn Reson 1994; 2: 125 (Abstract).Google Scholar
32.Luyten, PR, Marien, AJH, Heindel, W, et al. Metabolic imaging of patients with intracranial tumors 1H MR spectroscopic imaging and PET. RAdiology 1990; 176: 791–799.Google Scholar
33.Cristensen, H, Lour, HO, Clausen, J, Biering, F. Phospholipids and glycolipids of tumors of the central nervous system. Journal of Neurochemistry 1965; 12: 614–627.Google Scholar
34.Miller, BL, Chang, L, Booth, R. In vivo 1H-MRS choline: correlation with in vitro chemistry/histology. Life Sciences 1996; 58: 1929–1935.CrossRefGoogle ScholarPubMed
35.Kuesel, AC, Donnelly, SM, Halliday, W, Sutherland, GR, Smith, IC. Mobile lipids and metabolic heterogeneity of brain tumors as detectable by ex vivo 1H MR spectroscopy. NMR Biomed 1994; 7: 172–180.CrossRefGoogle ScholarPubMed
36.Usenius, JP, Kauppinen, RA, Vainio, PA, et al. Quantitative metabolite patterns of human brain tumors: detection by 1H NMR spectroscopy in vivo and in vitro. J Comput Assist Tomogr 1994; 18: 705–713.CrossRefGoogle ScholarPubMed
37.Remy, C, Arus, C, Ziegler, A, et al. In vivo, ex vivo, and in vitro one-and two-dimensional nuclear magnetic resonance spectroscopy of an intracerebral glioma in rat brain: assignment of resonances. J Neurochem 1994; 62: 166–179.CrossRefGoogle ScholarPubMed
38.Peeling, J, Sutherland, G. High-resolution 1H NMR spectroscopy studies of extracts of human cerebral neoplasms. Magn Reson Med 1992; 24: 123–136.CrossRefGoogle ScholarPubMed
39.Gill, SS, Thomas, DG, Van Bruggen, N, et al. Proton MR spectroscopy of intracranial tumors: in vivo and in vitro studies. J Comput Assist Tomogr 1990; 14: 497–504.CrossRefGoogle ScholarPubMed
40.Steen, RG. Response of solid tumors to chemotherapy monitored by in vivo 3IP nuclear magnetic resonance spectroscopy: a review. Cancer Research 1989; 49: 4075–4085.Google Scholar
41.Demaerel, P, Johannik, K, Van Hecke, P, et al. Localized 1H NMR spectroscopy in fifty cases of newly diagnosed intracranial tumors. J Comput Assist Tomogr 1991; 15: 67–76.CrossRefGoogle ScholarPubMed
42.Arnold, DL, Shoubridge, EA, Viilemure, JG, Feindel, W. Proton and phosphorus magnetic resonance spectroscopy of human astrocytomas in vivo. Preliminary observations on tumor grading. NMR Biomed 1990; 3: 184–189.CrossRefGoogle ScholarPubMed
43.Segebarth, CM, Baleriaux, DF, Luyten, PR, den Hollander, JA. Detection of metabolic heterogeneity of human intracranial tumors in vivo by IH NMR spectroscopic imaging. Magn Reson Med 1990; 13: 62–76.CrossRefGoogle Scholar
44.Bruhn, H, Frahm, J, Gyngell, ML, et al. Noninvasive differentiation of tumors with use of localized H-l MR spectroscopy in vivo: initial experience in patients with cerebral tumors [see comments]. Radiology 1989; 172: 541–548.CrossRefGoogle Scholar
45.Usenius, JP, Tuohimetsa, S, Vainio, P, et al. Automated classification of human brain tumors by neural network analysis using in vivo 1H magnetic resonance spectroscopic metabolite phenotypes. Neuroreport 1996; 7: 1597–1600.CrossRefGoogle ScholarPubMed
46.Kuesel, AC, Sutherland, GR, Halliday, W, Smith, IC. 1H MRS of high grade astrocytomas: mobile lipid accumulation in necrotic tissue. NMR Biomed 1994; 7: 149–155.CrossRefGoogle ScholarPubMed