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Application of MR Spectroscopic Techniques for the Development and Translation of Metabolite Markers Characterizing Infiltrating Glioma

Abstract

Despite ever more advanced characterization, the family of malignant central nervous system diseases known as infiltrating glioma remain pernicious and resistant to treatment. Because of their molecular and pathologic heterogeneity, they are among the most complex cancers in adults, with tremendous variability in patient outcomes being observed across oncologic subtypes. Over the course of therapy, magnetic resonance imaging (MRI) is critical to evaluating the level of response as the diagnostic standard for clinical management. Conventional MRI, having superior soft tissue contrast, provides a non-invasive means of detecting abnormalities that are embedded within neural anatomy. However, gauging the full extent of tumor is difficult owing to non-specific changes, which may either reflect benign processes in the aftermath of treatment or tumor infiltration.

Given the ambiguity associated with anatomical imaging, magnetic resonance spectroscopy (MRS) has emerged as a technique that can add diagnostic value to clinical practice by probing signature chemical species characterizing disease. The primary focus of this work was the development of translatable biomarkers for infiltrating glioma using analogous ex vivo methodology that has greater sensitivity and spectral resolution. By analyzing image-guided tissue samples acquired from a large cohort of patients with pathologically distinct subtypes, it was possible to characterize metabolite expression across diverse swathes of tumor representing natural heterogeneity. Quantified data revealed distinct metabolomic profiles for each of the clinically relevant subtypes that enabled their differential classification. Importantly, classification models were able to predict malignant progression on the basis of these profiles, highlighting the potential to determine pathologic trajectory. Separate analysis of contrast-based radiographic subtypes of the most aggressive form of glioma demonstrated unique metabolite expression in the portion of tumor that fails to exhibit contrast and is therefore masked on standard imaging.

Since some of the metabolite markers discovered exhibited features that diminished the lifetime of their signal, technical development of an in vivo MRS sequence was also undertaken. The creation of radiofrequency (RF) pulses with reduced peak power requirements was critical to the design of the sequence and enabled improved signal fidelity over longer acquisition times when incorporated into existing frameworks. Results from this project and those obtained ex vivo support greater clinical integration of spectroscopy.

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