Developing an Online Interactive Volumetric Surface Viewer for Visualizing Spatial Distribution of Intracranial Lesions.

Abstract

The exact location of intracranial neoplasms and metastatic lesions within the cortex may provide key insights into predicting treatment effectiveness and toxicities. Modern neuroimaging approaches have enabled precise, rapid diffeomorphic alignment from individual brains to an atlas, allowing the registration of contours and dose distributions onto a common template. However, there is a paucity of intuitive tools to perform such functions. Here, we developed an online interactive volumetric surface viewer that displays distribution of brain lesions of specific clinical features within the context of prior radiation treatment in populations of patients on a common atlas. Data from 647 patients treated at our institution with radiotherapy for intracranial lesions were analyzed with FreeSurfer to perform intensity normalization, skull-stripping, and affine registration to Talairach coordinates. A custom-built VoxelMorph model was trained to register T1 MRIs to a common atlas. Radiation dose maps and contours on underlying CT simulation scans were rigidly aligned to the T1 MRIs. The diffeomorphic warps were then applied to the radiation dose maps and contours, including the gross tumor volumes. Surface rendering of the template atlas was performed using FreeSurfer and visualized using PyCortex. Clinical information including primary sites for brain metastases, lesion size, survival, recurrence, use of anti-epileptic medications, radiation necrosis, and neuro-cognitive toxicity was embedded into the PyCortex viewer. The custom-trained VoxelMorph model enabled rapid normalization of the T1MRIs to the atlas brain. PyCortex allows for interactive visualization of the spatial distribution of lesions on the cortical surface across a rich array of clinical parameters. Initial maps have qualitatively revealed a predilection for metastases in the right hemisphere. This WebGL viewer allows intuitive clinical interrogation on a visual surface enabling population inferences. For example, one can visualize the distribution of brain metastases of a large patient cohort based on their primary tumor sites, propensity for seizure and risk for radionecrosis. We successfully built an online interactive viewer to visualize the spatial distribution of intracranial lesions on a common reference. Our approach extends prior work allowing visual interaction of lesions and real-time generation of inference maps by combining a front-end viewer and back-end database of clinical data. This viewer may represent a critical step towards uncovering the location-dependent breakdown of the blood-brain-barrier, differentiating the propensity of primary lesions metastasizing to brain regions, and allowing the discovery of associations of previously understudied spatial neighborhoods. We plan to release a publicly available web-based viewer to further explore, interrogate, and inform future radiation treatments.