Cloud quantitative imaging for whole-body tumor burden in neurofibromatoses

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Project Summary / Abstract The neurofibromatoses (NFs), including NF1, NF2, and schwannomatosis, are a group of autosomal-dominant neurogenetic disorders characterized by a predisposition in virtually 100% of patients to develop multiple nerve sheath tumors. The determination of tumor burden on magnetic resonance imaging (MRI) is indispensable for the longitudinal management of NF patients, which includes life-long follow-up for the monitoring of tumor progression and the assessment of treatment response. However, volumetric quantification of NF tumors is not a clinical routine because of the technical challenges in the accurate and reproducible segmentation of highly-irregular and infiltrating NF tumors, in particular plexiform neurofibromas on MRI. The goal of this STTR project is to develop cloud quantitative imaging (CQI) for NF software, denoted as CQI-NF, which will provide the technical and clinical service for volumetric quantification of NF tumors on whole-body and regional MRI via "virtualization" (cloud computing) technology. The product developed in this STTR will provide access to this technology for the NF clinical community nationwide and worldwide without the excessive cost to maintain on-site advanced volumetric imaging analysis software and hardware. This project will be built upon existing technologies for volumetric imaging analysis developed on the software platform “3DQI” in the 3D Imaging Lab at Massachusetts General Hospital (MGH), and will be evaluated using 200 longitudinal whole-body and regional MRI cases collected from the NF community worldwide. The specific aims of this Phase II project are: (1) Development of CQI-NF system: We will continue to develop the CQI-NF system prototyped in our Phase I project to improve the accuracy and efficiency of segmentation by paralleling dynamic-threshold level set (DT level set) in multi-server platform, combining deep-learning in DT level set for the segmentation of NF tumors, and to translate the CQI-NF system from 3DQI/NF into a private cloud platform (such as TeraRecon's iNtuition CLOUD) for the provision of volumetric quantification of NF using a software-as-a-service (SaaS) model in the NF community. (2) Evaluation of CQI-NF system: We will conduct a retrospective clinical study to evaluate the accuracy and reproducibility of the CQI-NF system in the longitudinal monitoring of 200 NF patients collected at MGH Cancer Center and our clinical collaborators worldwide in the NF community. (3) Preparation of FDA 510(k) clearance submission: We will establish the quality management system for CQI-NF to meet FDA regulation, and prepare the required documentation for FDA 510(k) clearance submission for the long-term project goal of clinical translation of CQI-NF. The successful development and validation of the proposed CQI-NF system will have a high clinical impact in the NF community by providing a cloud-computing infrastructure for the volumetric imaging analysis of NF on MRI, which is not available in current clinical routine, thereby leading to a substantial advance in the longitudinal management of NF patients.