To evaluate the clinical accuracy and utility of a commercial deep learning-based auto-segmentation tool by Siemens for delineating brain metastases (GTV) and organs-at-risk (OAR) on contrast-enhanced MRI.
Author profile
Vaisakh Nappady Joy, PhD
Siemens Healthineers
Evaluation of a Deep Learning-Based Auto-Contouring Tool for Brain Metastases and Organs-at-Risk on MRI
Poster Program · Therapy Physics
Safety and Precision In a Same-Day, MRI-Only Simulation with Adaptive VMAT SRS/SRT Workflow: Integrating Synthetic CT and AI-Driven Quality Assurance
The efficacy of stereotactic radiosurgery (SRS) and radiotherapy (SRT) for brain metastases is often compromised by tumor growth and soft tissue changes between simulation and treatment. To eliminate these latencies, we clinically implemented a novel same-day...
Poster Program · Therapy Physics
Theranostic Aguix Nanoparticles As an MRI Contrast Agent for Tumor Delineation
AGuIX nanoparticles, composed of a polysiloxane core with gadolinium chelates, are a theranostic agent, providing both MRI contrast and radiosensitization. The ongoing NanoBrainMets clinical trial looks to evaluate the therapeutic efficacy of AGuIX by quantif...
Poster Program · Therapy Physics