MEMRI‐based imaging pipeline for guiding preclinical studies in mouse models of sporadic medulloblastoma. Issue 1 (12th August 2019)

• Record Type: Journal Article
• Authors: Rallapalli, Harikrishna; Tan, I‐Li; Volkova, Eugenia; Wojcinski, Alexandre; Darwin, Benjamin C.; Lerch, Jason P.; Joyner, Alexandra L.; Turnbull, Daniel H.
• Is Part Of: Magnetic resonance in medicine. Volume 83:Issue 1(2020)
• Page Start: 214
• Page End: 227
• Publication Date: 2019-08-12
• Subjects: linear discriminant analysis (LDA) -- MRI -- segmentation; Sonic hedgehog (SHH) -- tumor associated macrophages and microglia (TAMs); Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.27904
• Languages: English
• ISSNs: 0740-3194

Abstract

Abstract : Purpose: Genetically engineered mouse models of sporadic cancers are critical for studying tumor biology and for preclinical testing of therapeutics. We present an MRI‐based pipeline designed to produce high resolution, quantitative information about tumor progression and response to novel therapies in mouse models of medulloblastoma (MB). Methods: Sporadic MB was modeled in mice by inducing expression of an activated form of the Smoothened gene (aSmo) in a small number of cerebellar granule cell precursors. aSmo mice were imaged and analyzed at defined time‐points using a 3D manganese‐enhanced MRI‐based pipeline optimized for high‐throughput. Results: A semi‐automated segmentation protocol was established that estimates tumor volume in a time‐frame compatible with a high‐throughput pipeline. Both an empirical, volume‐based classifier and a linear discriminant analysis‐based classifier were tested to distinguish progressing from nonprogressing lesions at early stages of tumorigenesis. Tumor centroids measured at early stages revealed that there is a very specific location of the probable origin of the aSmo MB tumors. The efficacy of the manganese‐enhanced MRI pipeline was demonstrated with a small‐scale experimental drug trial designed to reduce the number of tumor associated macrophages and microglia. Conclusion: Our results revealed a high level of heterogeneity between tumors within and between aSmo MB models, indicating that meaningful studies of sporadic tumor progression and response to therapy could not be conducted without an imaging‐based pipeline approach.