Purpose: To develop a statistical and anatomical population‐based model that can be used to validate the accuracy and integrity of head and neck normal tissue structures of individual patients for use in preplanning and/or online adaptive radiation therapy. Methods: Normal tissue contours from 29 patients treated for head and neck cancers were used in development of the model. For each patient, DICOM plan and structure files were exported from the treatment planning system to an in‐house developed software program which calculated anatomic metrics for volume, shape, and intra‐structure distances for all structures. A statistical analysis of these metrics produced population specific rules that were used within the software program to evaluate the accuracy of head and neck contours for subsequent patients. The contour assessment program included only metrics for which the standard deviation was less than a heuristically determined limit of 15% of the mean for that metric. To verify the softwares utility, 42 common contouring errors were intentionally introduced within 9 specific structures for 9 different patients. These errors included incorrect laterality, position, size and shape, inclusion of small isolated pixels, deleted segments, and empty structures. The evaluation of all 9 head and neck structure sets was blinded to the nature and number of the generated errors. Results: The contour accuracy and integrity program correctly identified 40 of 42 generated errors. Small modifications to the structures shape and volume were the most difficult to correctly identify; however the program correctly identified all positional and laterality errors, deleted/isolated segments, small pixels, and deleted contours. Conclusion: Rules developed from a statistical analysis of anatomic population‐based metrics can provide much of the necessary information to correctly and efficiently evaluate the accuracy and integrity of a unique patient contour structure set for IMRT preplanning or for an online adaptive radiation therapy protocol.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging