Role of MR Spectroscopy in Differentiating Radiation Necrosis from Tumor Recurrence. Effects of radiation Injury.

1. Role of MR Spectroscopy in Differentiating Radiation Necrosis from Tumor Recurrence. Effects of radiation Injury. Elias A1, Carlos RC1, Smith EA1, Maly P2, Sundgren PC1 2 1Department of Radiology, University of Michigan Health Systems, Ann Arbor, MI 48109, USA 2Department of Radiology, Skåne University hospital , Lund University, Lund, Sweden 

2. Learning Objectives • Magnetic resonance spectroscopy (MRS) to detect early radiation changes. • Describe the most current data in differentiating tumor recurrence from radiation necrosis. • Metabolic ratio with highest statistical yield. • Application to clinical practice - Prediction models.

3. Disclosures The authors do not currently have and have not within the past 12 months had a financial interest or other relationship with a commercial organization that may have an interest in the content of this presentation.

4. Introduction • Present management of new enhancing lesion at the vicinity of treated brain neoplasm • invasive brain biopsy • clinical course • imaging follow-up • Differentiation on conventional MR imaging • Diagnostic dilemma - no specific imaging characteristics • post therapeutic changes • non specific enhancement to gadolinium • Radiation oncology protocols • improved outcome with high radiation dose • dose limiting radiation injury

5. Tumor recurrence versus radiation injury • Radiation necrosis 5 - 24 % after conventional therapy • Early radiation changes are evident as early as 2- 6 months after therapy • Overlapping imaging features/findings between radiation injury and tumor recurrence Marks JE, Baglan RJ, Prassad SC, Blank WF. Cerebral radionecrosis: incidence and risk in relation to dose, time, fractionation and volume.Int J Radiation Oncology Biol Phys 1981;7(2): 243-52.

6. Background Early radiation white matter changes • Radiation oncology protocols • improved outcome with high radiation dose • dose limiting radiation injury • Clinical status deterioration

7. Early radiation white matter changes A B post Gd-DTPA T1-weighted images before RT (A) and 6 months after the completion of RT (B) Sundgren PC, et al. Metabolic alterations; a biomarker for radiation-induced injury of normal brain. An Spectroscopy study. JMRI 2009 Feb;29(2):291-7

8. Pre treatment 3 weeks in RT 6 months after RT

9. Differences of ratios of NAA/Cr (square) and Cho/Cr (triangle) compared to the values prior to RT. Significant interval changes were observed in NAA/Cr and Cho/Cr during and after RT

10. Early radiation white matter changes Conclusion • Occult injury to the normal brain begins during RT • and remains evident for at least 6 months. • Supports the hypothesis that MRS is sensitive for • early detection of metabolic changes in normal • brain tissue undergoing radiation Sundgren PC, Nagesh V, Elias A, Tsien C, Junck L, Gomez Hassan D, Lawrence T, Chenevert TL, Rogers L, McKeever P, Cao Y. Metabolic alterations; a biomarker for radiation-induced injury of normal brain. An Spectroscopy study. JMRI 2009 Feb;29(2):291-7

11. Controversy in the diagnosis of radiation necrosis vs tumor recurrence with MRS • lesions often mixed • which type of MRS sequences to use • ratio calculations • - normalized ratios • - in lesion measurements • role of MRS in clinical decision making

12. Controversy regarding measurements and calculations • MRS findings have been shown to correlate well with pathologic specimens obtained at biopsy and/or resection • No consensus in the spectroscopy community regarding measurements, ratios and methods to use when performing ratio calculations Background Rock JP et al. Neurosurgery 2002; 51:912-20.

13. Controversy regarding measurements and calculations In a recent study of 25 patients we compared the ability of standard metabolic and normalized ratios to discriminate between recurrent tumor and radiation changes. • Inclusion criteria: • - primary intracranial neoplasm • - radiation therapy treatment • - new contrast enhanced lesion

14. Controversy regarding measurements and calculations • Data and statistical analysis • Wilcoxon and rank-sum test • Nonparametric alternative to the two-sample t-test • Statistical significance was set at a p-value ≤ 0.05 • Receiver operating characteristic (ROC) curve • Statistical significance was set at a p-value ≤ 0.05 Methods

15. Controversy regarding measurements and calculations Spectral analysis in a 35 y.o. woman with a left posterior parietal contrast enhancing lesion on follow-up MRI at 27 months

16. Controversy regarding measurements and calculations Results

17. Controversy regarding measurements and calculations Non-normalized Cho/NAA ratio AzROC= 0.92 Normalized Cho/NAA ratio AzROC= 0.77

18. Conclusion Controversy regarding measurements and calculations • Non-normalized ratios have the best discriminatory ability compared to normalized ratios • Cho/NAA ratio had the highest sensitivity and specificity to differentiate and correctly classify new contrast enhancing lesions in patients with radiation-treated primary brain tumors

19. Background Prediction models for clinical decision making Currently patients are subjected to invasive biopsy to determine diagnosis of new contrast enhancing lesions to differentiate between recurrent tumor and radiation changes.

20. Prediction models for clinical decision making Materials • 33 patients • Inclusion criteria: • Primary intracranial neoplasm • Previous treatment with XRT • New contrast enhancing lesion Smith E et al Developing an prediction model . AJR Am J Roentgenol. 2009 Feb;192(2):W45-52

21. Prediction models for clinical decision making • Wilcoxon rank sum analysis • non-parametric data • small sample size • Logistic regression model Statistical analysis

22. Prediction models for clinical decision making • Lesions classified into two groups • - recurrent neoplasm • - post radiation changes • Lesion classification methods • - histopathologic diagnosis • - imaging and clinical follow up

23. Prediction models for clinical decision making Results

24. 1.00 0.75 Sensitivity 0.50 0.25 0.00 0.00 0.25 0.50 0.75 1.00 1 - Specificity Prediction models for clinical decision making • Cho/NAA • Sensitivity = 85% • Specificity = 69.2% • Area under the ROC curve = 0.92

25. Prediction models for clinical decision making • Post test probability was estimated • Linear regression model • Range of Cho/NAA values

26. Results: Prediction Model 80% 15%

27. Results: Prediction Model Probability of recurrent tumor using Cho /NAA ratio New contrast Pr ≤ 15% Routine follow - up enhancing lesion on (0/5) conventional MRI 15< Pr <80% Biopsy (33) (6/13) MR Spectroscopy Pr ≥ 80% Immediate Treatment (14/15) stratified Clinical Decision Making Risk - Smith E et al Developing an prediction model ..AJR Am J Roentgenol. 2009 Feb;192(2):W45-52

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29. MR spectroscopy Proton (1H) MRSmost used technique in clinical routine SVS (single voxel spectroscopy) STEAM / PRESS TE 20-35ms / 135-270 ms, TR 2000-3000ms VOI ( 2x2x2 cm ) placements basal ganglia, normal / abnormal white matter gray matter 2D-CSI (chemical shift imaging) PRESS TE 35 ms / 144 ms / 280 ms, TR 2000ms larger VOI - cover larger regions of normal and abnormal brain, basal ganglia, centrum semiovale

30. MR spectroscopy Protocol • 2D-CSI (chemical shift imaging) • PRESS • TE 35 ms / 144 ms / 280 ms • TR 1000 - 2000 ms • FOV 16 cm • Matrix 16 x 16 • Slice thickness 10 - 20 mm • Scan time 4.2 minutes • Functool 2000 (GE Healthcare)

31. Important brain metabolites • NAA 2.0ppm neuron marker, adult peak at age 15 • Cr1 3.03ppm fairly stable marker for energy dependent systems in brain cells • Cr2 3.9ppm ratio Cr2/Cr1=2/3 • Cho 3.25ppm tumor fraction/demyelination • Lac 1.32ppm hypoxia (anaerobic) Lac peak is inverted at TE 144 ms

32. Metabolic ratios normal abnormal NAA/Cr 2.0 <1.6 NAA/Cho 1.6 <1.2 Cho/Cr 1.2 >1.5 Cho/NAA 0.7 > 1.0