A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy

Autor: Wolfgang A. Tomé, Markus Oechsner, Yogisha Mallya, Prashant Kumar, Buelent Polat, Charlotte L. Brouwer, Anne Richter, Shiyu Song, Nicholas Hardcastle, Karl Bzdusek, Stephane Allaire, Paul W. H. Wittendorp, Donald M. Cannon, Matthias Guckenberger, Michael J. Myers, Nesrin Dogan
Jazyk: angličtina
Rok vydání: 2012
Předmět:
lcsh:Medical physics. Medical radiology. Nuclear medicine
STRATEGIES
lcsh:R895-920
Image registration
Computed tomography
lcsh:RC254-282
Imaging data
Head and neck radiotherapy
Treatment plan
Radiation oncology
mental disorders
medicine
Humans
Radiology
Nuclear Medicine and imaging
Computer vision
ddc:610
Adaptive radiotherapy
Head and neck cancer
MEGAVOLTAGE COMPUTED-TOMOGRAPHY
RISK
medicine.diagnostic_test
business.industry
Radiotherapy Planning
Computer-Assisted
Research
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
CANCER
nervous system diseases
INTENSITY-MODULATED RADIOTHERAPY
VARIABILITY
Oncology
Multicenter study
nervous system
Head and Neck Neoplasms
Radiology Nuclear Medicine and imaging
Radiation Oncology
Radiographic Image Interpretation
Computer-Assisted
Artificial intelligence
Deformable image registration
Nuclear medicine
business
Algorithms
psychological phenomena and processes
Zdroj: Radiation oncology, 7:90. BMC
Radiation Oncology, Vol 7, Iss 1, p 90 (2012)
Radiation Oncology (London, England)
ISSN: 1748-717X
Popis: Background Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. Methods Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility. Results Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits. Conclusion DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.
Databáze: OpenAIRE
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