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Related Experiment Video

Updated: Aug 5, 2025

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

SurVolT: Surface to Volume conversion Tool. A proof of concept.

Alexia Gorecki¹, Veronica Sorgato¹, Christophe Mazzara²

¹Department of Radiotherapy, Daniel Hollard Cancer Institute, Grenoble, France; School of Medical Physics, Faculty of Medicine, Grenoble Alpes University, France.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)

|March 29, 2023

Summary

A new tool, SurVolT, converts daily surface data into volumetric changes for CT scans, enabling adaptive radiotherapy. This surface-guided radiotherapy approach is crucial for precise cancer treatments.

Keywords:

Adaptive radiotherapy Anatomical changes DICOM Image registration SGRT Surface deformation

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Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments

Published on: February 27, 2013

Area of Science:

Medical Physics
Radiotherapy Technology
Image Processing

Background:

Accurate patient positioning and monitoring are critical in modern radiotherapy.
Anatomical changes during treatment can affect dose delivery accuracy.
Integrating real-time surface data into treatment planning is an emerging area.

Purpose of the Study:

To develop SurVolT, a novel conversion tool for applying volumetric changes to DICOM CT data.
To utilize daily surface (obj) data from AlignRT® for volumetric adjustments.
To primarily validate the tool for breast cancer radiotherapy treatments.

Main Methods:

SurVolT extracts AlignRT® .obj files and deforms contours based on surface data.
The tool substitutes external contours and deforms Planning Treatment Volume (PTV) contours.
Validation involved phantoms mimicking edema and anthropomorphic models, with final application on a patient.

Main Results:

Phantom validation demonstrated accurate bolus thickness estimation (5.8±1.2mm vs. 5mm expected).
Non-rigid image deformation accurately followed the new external contour at the treated area.
Negligible deformation was observed in non-target regions, ensuring localized adjustments.

Conclusions:

SurVolT represents a proof of concept for converting surface data to volumetric data in radiotherapy.
This tool is a fundamental step towards implementing Surface-Guided Radiotherapy (SGRT)-based adaptive radiotherapy.
The findings support the potential of SGRT for enhancing treatment precision and adaptability.