Using pattern analysis of in vivo proton MRSI data to improve the diagnosis and surgical management of patients with brain tumors.

Abstract

We have used pattern analysis of proton magnetic resonance spectroscopic imaging (1H MRSI) data in a variety of situations related to the clinical management of patients with brain tumors and other cerebral space-occupying lesions (SOLs). Here, we review how 'leave-one-out' linear discriminant analyses (LDAs) of in vivo 1H MRSI spectral patterns have enabled us to quickly, accurately, and non-invasively: (1) discriminate amongst tissue arising from the five most common types of supratentorial tumors found in adults, and (2) use the metabolic heterogeneity of cerebral SOLs to predict certain pathological characteristics that are useful in guiding stereotaxic biopsy and selective tumor resection. These findings suggest that pattern analysis of 1H MRSI data can significantly improve the diagnostic specificity and surgical management of patients with certain cerebral SOLs.