Surgical removal of tumors is an inexact science, requiring physicians to feel, visually analyze, and compare tissue sections to pre-op imaging. In brain operations in particular it is of utmost importance to remove the whole tumor while avoiding damaging any healthy tissue.
In theory pathological examination may work, but it is so time consuming that it’s impractical in reality to wait a half hour for results on every sample. Researchers at Purdue University have developed a new technique that uses desorption electrospray ionization mass spectrometry (DESI-MS) to measure lipid content of tissues and using that characterize them as healthy or cancerous. The study used brain tissue samples removed during actual surgeries, but the end goal of the project is to create a tool that can be used intraoperatively to guide the scalpel just where it needs to go. The work was done in conjunction with clinicians at Harvard’s Brigham and Women’s Hospital.
From the study absract in Proceedings of the National Academy of Sciences:
In this study, a classifier was built to discriminate gliomas and meningiomas based on 36 glioma and 19 meningioma samples. The classifier was tested and results were validated for intraoperative use by analyzing and diagnosing tissue sections from 32 surgical specimens obtained from five research subjects who underwent brain tumor resection. The samples analyzed included oligodendroglioma, astrocytoma, and meningioma tumors of different histological grades and tumor cell concentrations. The molecular diagnosis derived from mass-spectrometry imaging corresponded to histopathology diagnosis with very few exceptions. Our work demonstrates that DESI-MS technology has the potential to identify the histology type of brain tumors. It provides information on glioma grade and, most importantly, may help define tumor margins by measuring the tumor cell concentration in a specimen. Results for stereotactically registered samples were correlated to preoperative MRI through neuronavigation, and visualized over segmented 3D MRI tumor volume reconstruction. Our findings demonstrate the potential of ambient mass spectrometry to guide brain tumor surgery by providing rapid diagnosis, and tumor margin assessment in near–real time.