Go-Smart: Web-based computational modeling of minimally invasive cancer treatments

Abstract

The web-based Go-Smart environment is a scalable system that allows the prediction of minimally invasive cancer treatment. Interventional radiologists create a patient-specific 3D model by semi-automatic segmentation and registration of pre-interventional CT (Computed Tomography) and/or MRI (Magnetic Resonance Imaging) images in a 2D/3D browser environment. This model is used to compare patient-specific treatment plans and device performance via built-in simulation tools. Go-Smart includes evaluation techniques for comparing simulated treatment with real ablation lesions segmented from follow-up scans. The framework is highly extensible, allowing manufacturers and researchers to incorporate new ablation devices, mathematical models and physical parameters

A thermoelastic deformation model of tissue contraction during thermal ablation

“…For a safe clinical implementation of such techniques, it is important to accurately determine the volume of ablated tissue. Pre-procedural planning, such as experimental data and computer simulation tools, can provide such information and thus aid in determining the optimal patient specific treatment [1][2][3].…”

“…Studies have attempted to develop a computational framework to predict the performance of different ablation devices and procedures for clinical implementation [1][2][3], characterised from ex vivo and in vivo animal studies [4,5]. These models, however, have not considered the effects of tissue contraction during hyperthermic ablation therapies, which can be observed on immediate post-procedural images both in clinical and experimental settings [6,7].…”

PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

“…The state of the art for production-quality hybrid computational cloud and HPC for in silico processing of clinical cases is currently represented by projects such as EurValve [30, 31,37] and GoSmart [38,39], having achieved significant progress in developing integrated, comprehensive frameworks. EurValve has also come up with an integrated cloud/HPC computing solution to back up its MEE, dedicated for simulations of valvular heart conditions.…”

Building Educational Simulations Using KSA Open Data

“…The OpenAugury framework comprises two primary facets: a highly-adaptable simulation domain model (see Figure 2) and a compatible technical architecture. This structure draws on work performed in a clinical context [29] to create a clinicianfacing, model-independent simulation framework for multi-modal cancer treatments [30,31]. The present work is a case study of the existing OpenAugury framework-built with support from OpenDataNIapplied to the KSA context and open data, thereby demonstrating the framework's adaptability, to allow the dynamic addition of physical phenomena, geographic settings, data sources in a highly contrasting context.…”