A Framework for Clinical Validation of Automatic Contour Propagation: Standardizing Geometric and Dosimetric Evaluation

Amy Frederick; Michael Roumeliotis; Petra Grendarova; Peter Craighead; Tasnima Abedin; Elizabeth Watt; Ivo A Olivotto; Tyler Meyer; Sarah Quirk

doi:10.1016/j.prro.2019.06.017

A Framework for Clinical Validation of Automatic Contour Propagation: Standardizing Geometric and Dosimetric Evaluation

Pract Radiat Oncol. 2019 Nov;9(6):448-455. doi: 10.1016/j.prro.2019.06.017. Epub 2019 Jul 4.

Authors

Amy Frederick¹, Michael Roumeliotis², Petra Grendarova³, Peter Craighead³, Tasnima Abedin⁴, Elizabeth Watt⁵, Ivo A Olivotto³, Tyler Meyer², Sarah Quirk²

Affiliations

¹ Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada; Division of Medical Physics, Tom Baker Cancer Centre, Calgary, Alberta, Canada. Electronic address: amy.frederick2@ucalgary.ca.
² Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada; Division of Medical Physics, Tom Baker Cancer Centre, Calgary, Alberta, Canada; Department of Oncology, University of Calgary, Calgary, Alberta, Canada.
³ Department of Oncology, University of Calgary, Calgary, Alberta, Canada; Division of Radiation Oncology, Tom Baker Cancer Centre, Calgary, Alberta, Canada.
⁴ Clinical Research Unit, Tom Baker Cancer Centre, Calgary, Alberta, Canada.
⁵ Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada; Division of Medical Physics, Tom Baker Cancer Centre, Calgary, Alberta, Canada.

PMID: 31279940
DOI: 10.1016/j.prro.2019.06.017

Abstract

Purpose: The objective of this work was to outline and demonstrate a standardized framework for evaluating automatically propagated contour quality against expert contours. A 2-pronged approach is used to evaluate contour quality: a geometric evaluation to identify geometric and spatial discrepancies between propagated and expert contours, and a comprehensive dosimetric comparison to provide clinical context for the results.

Methods and materials: The standardized framework requires a primary image, with reference contours and a radiation therapy treatment plan, and a secondary image. Reference contours are automatically propagated onto the secondary image anatomy and compared with expert contours obtained in an interobserver study. The standardized framework outlines geometric and dosimetric evaluation methodologies for determining indistinguishability between propagated and expert contours in a cohort analysis. Propagated contours are geometrically compared with expert contours in terms of the Dice similarity coefficient and the mean distance to agreement. Statistical analysis is performed on the central tendency and variability of Dice similarity coefficient and mean distance to agreement values over the patient cohort. Dosimetric evaluation involves computing the mean and 95% confidence intervals for the differences in cumulative dose-volume histograms for propagated and expert contours. A case study in accelerated partial breast irradiation was shown to demonstrate the framework.

Results: The standardized framework was applied to a case study of 24 patient data sets with 3 radiation oncologists providing the expert contours. Cohort analysis indicated that propagated contours were geometrically indistinguishable and dosimetrically distinguishable from expert contours.

Conclusions: The recommended framework standardizes the comparison of geometric and dosimetric parameters to demonstrate indistinguishability of propagated contours from expert contours. Adoption of this framework is vital for consistent and comprehensive validation of automatic contour propagation for use in large-scale cohort analyses.

MeSH terms

Female
Humans
Male
Radiometry / methods*
Reproducibility of Results