rtdsm
rtdsm generates dose-surface maps (DSMs) from DICOM radiotherapy data to enable spatial analysis of dose distributions for hollow organs in dose–outcome studies.
Key Features:
- DSM calculation: Computes DSMs from DICOM RT data to represent spatial dose distributions on hollow-organ surfaces.
- User customizability: Provides configurable parameters to adjust DSM calculations and analysis settings for specific study requirements.
- Equivalent dose conversions: Performs conversions between dose metrics to enable comparisons across different treatment plans or studies.
- DSM feature extraction: Extracts common DSM-derived features used to quantify spatial dose patterns and identify radiosensitive subregions.
- DSM accumulation: Accumulates DSMs to support longitudinal analyses and comparative studies.
- DSM slicing methods: Implements planar and noncoplanar slicing approaches to generate alternative DSM representations.
Scientific Applications:
- Dose–outcome studies: Enables analysis of spatial dose distributions when correlating delivered dose with clinical outcomes.
- Radiosensitive subregion identification: Supports detection of spatially localized regions of sensitivity within hollow organs using DSM features.
- Inter-treatment comparison: Facilitates comparison of DSMs across different treatment plans or modalities via equivalent dose conversions and DSM metrics.
- Longitudinal and comparative analyses: Allows accumulation and comparison of DSMs over time or between cohorts for longitudinal studies.
Methodology:
Implementation and testing of two DSM slicing methods—planar and noncoplanar—to assess their effects on output DSMs.
Topics
Details
- License:
- GPL-3.0
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- Python
- Added:
- 10/9/2022
- Last Updated:
- 11/24/2024
Operations
Publications
Patrick HM, Kildea J. Technical note: <i>rtdsm</i>—An open‐source software for radiotherapy dose‐surface map generation and analysis. Medical Physics. 2022;49(11):7327-7335. doi:10.1002/mp.15900. PMID:35912447.
DOI: 10.1002/mp.15900
PMID: 35912447