title: A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma.
abstract: The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, due to the heterogeneous and infiltrative nature of gliomas, identifying the optimal region for biopsy with conventional magnetic resonance imaging (MRI) can be quite difficult. This is especially true for low grade gliomas, which often are non-enhancing tumors. To improve the management of patients with these tumors, the field of neuro-oncology requires an imaging modality that can specifically identify a tumor's most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution whole-brain 3D sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histology analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically-stained tissue specimens. As a proof of concept, we describe the combination of these two techniques in a small cohort of grade III glioma patients. In this work, we aim to set forth a systematic pipeline to stimulate histopathology-image validation of advanced MRI techniques, such as sMRI.
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA.
authors.forename: J Scott
authors.initials: JS
authors.lastname: Cordova
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA.
authors.forename: Saumya S
authors.initials: SS
authors.lastname: Gurbani
authors.affiliation: Department of Neurosurgery, Emory University School of Medicine; Winship Cancer Institute of Emory University.
authors.forename: Jeffrey J
authors.initials: JJ
authors.lastname: Olson
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA.
authors.forename: Zhongxing
authors.initials: Z
authors.lastname: Liang
authors.affiliation: Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA; Department of Biomedical informatics, Emory University School of Medicine.
authors.forename: Lee A D
authors.initials: LA
authors.lastname: Cooper
authors.affiliation: Winship Cancer Institute of Emory University; Department of Radiation Oncology, Emory University School of Medicine.
authors.forename: Hui-Kuo G
authors.initials: HG
authors.lastname: Shu
authors.affiliation: Department of Radiation Oncology, Emory University School of Medicine.
authors.forename: Eduard
authors.initials: E
authors.lastname: Schreibmann
authors.affiliation: Department of Pathology, Emory University School of Medicine.
authors.forename: Stewart G
authors.initials: SG
authors.lastname: Neill
authors.affiliation: Department of Neurosurgery, Emory University School of Medicine; Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY.
authors.forename: Constantinos G
authors.initials: CG
authors.lastname: Hadjipanayis
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA.
authors.forename: Chad A
authors.initials: CA
authors.lastname: Holder
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA; Winship Cancer Institute of Emory University.
authors.forename: Hyunsuk
authors.initials: H
authors.lastname: Shim
keywords: biopsy planning; grade III glioma; image-histology correlation; quantitative histological image analysis; spectroscopic MRI