Object: To investigate the effect of temperature (0 versus 37 degrees C) in the high-resolution magic angle spinning spectroscopy (HRMAS) pattern of human brain tumor biopsies and its influence in recognition-based tumor type prediction. This proof-of-principle study addressed the bilateral discrimination between meningioma (MM) and glioblastoma multiforme (GBM) cases.
Materials and methods: Forty-three tumor biopsy samples were collected (20 MM and 23 GBM), kept frozen and later analyzed at 0 degrees C and 37 degrees C by HRMAS. Post-HRMAS histopathology was used to validate the tumor type. Time-course experiments (100 min) at both temperatures were carried out to monitor HRMAS pattern changes. Principal component analysis and linear discriminant analysis were used for classifier development with a training set of 20 biopsies.
Results: Temperature-dependent, spectral pattern changes mostly affected mobile lipids and choline-containing compounds resonances and were essentially reversible. Incubation of 3 MM and 3 GBM at 37 degrees C during 100 minutes produced irreversible pattern changes below 13% in a few resonances. Classification performance of an independent test set of 7 biopsies was 100% for the pulse-and-acquire, CPMG at echo times (TE) of 30 ms and 144 ms and Hahn Echo at TE 30 ms at 0 degrees C and 37 degrees C. The performance for Hahn Echo spectra at 136 ms was 83.3% at 0 degrees C and 100% at 37 degrees C.
Conclusion: The spectral pattern of mobile lipids changes reversibly with temperature. HRMAS demonstrated potential for automated brain tumor biopsy classification. No advantage was obtained when acquiring spectra at 37 degrees C with respect to 0 degrees C in most of the conditions used for the discrimination addressed.