Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy

To propose a clinically oriented quantitative metric, Hu similarity coefficient (HSC), to evaluate contour quality, gauge the performance of auto contouring methods, and aid effective allocation of clinical resources. The HSC is defined as the ratio of the number of boundary points of the initial contour that doesn't require modifications over the number of boundary points of the final adjusted contour. To demonstrate the clinical utility of the HSC in contour evaluation, we used publicly available pelvic CT data from the Cancer Imaging Archive. The bladder was selected as the organ of interest. It was contoured by a certified medical dosimetrist and reviewed by a certified medical physicist. This contour served as the ground truth contour. From this contour, we simulated two contour sets. The first set had the same Dice similarity coefficient (DSC) but different HSCs, whereas the second set kept a constant HSC while exhibiting different DSCs. Four individuals were asked to adjust the simulated contours until they met clinical standards. The corresponding contour modification times were recorded and normalized by individual's manual contouring times from scratch. The normalized contour modification time was correlated to the HSC and DSC to evaluate their suitability as quantitative metrics assessing contour quality. The HSC maintained a strong correlation with the normalized contour modification time when both sets of simulated contours were included in analysis. The correlation between the DSC and normalized contour modification time, however, was weak. Compared to the DSC, the HSC is more suitable for evaluating contour quality. We demonstrated that the HSC correlated well with the average normalized contour modification time. Clinically, contour modification time is the most relevant factor in allocating clinical resources. Therefore, the HSC is better suited than the DSC to assess contour quality from a clinical perspective.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-12-04
DOI
https://doi.org/10.1038/s41598-024-81167-7
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy

Min Yang, Harold Yang Hu, Shaw Yang Hu, Yanle Hu
Scientific Reports
Radiomics and Machine Learning in Medical Imaging
article

Hu similarity coefficient: a clinically oriented metric to evaluate contour accuracy in radiation therapy

Min Yang, Harold Yang Hu, Shaw Yang Hu, Yanle Hu
article en

Abstract

To propose a clinically oriented quantitative metric, Hu similarity coefficient (HSC), to evaluate contour quality, gauge the performance of auto contouring methods, and aid effective allocation of clinical resources. The HSC is defined as the ratio of the number of boundary points of the initial contour that doesn't require modifications over the number of boundary points of the final adjusted contour. To demonstrate the clinical utility of the HSC in contour evaluation, we used publicly available pelvic CT data from the Cancer Imaging Archive. The bladder was selected as the organ of interest. It was contoured by a certified medical dosimetrist and reviewed by a certified medical physicist. This contour served as the ground truth contour. From this contour, we simulated two contour sets. The first set had the same Dice similarity coefficient (DSC) but different HSCs, whereas the second set kept a constant HSC while exhibiting different DSCs. Four individuals were asked to adjust the simulated contours until they met clinical standards. The corresponding contour modification times were recorded and normalized by individual's manual contouring times from scratch. The normalized contour modification time was correlated to the HSC and DSC to evaluate their suitability as quantitative metrics assessing contour quality. The HSC maintained a strong correlation with the normalized contour modification time when both sets of simulated contours were included in analysis. The correlation between the DSC and normalized contour modification time, however, was weak. Compared to the DSC, the HSC is more suitable for evaluating contour quality. We demonstrated that the HSC correlated well with the average normalized contour modification time. Clinically, contour modification time is the most relevant factor in allocating clinical resources. Therefore, the HSC is better suited than the DSC to assess contour quality from a clinical perspective.

Scientific ReportsVol. 14(1)
George Washington University (US), WinnMed (US), Dignity Health (US), Mayo Clinic in Arizona (US), Mayo Clinic Hospital (US), Mayo Clinic in Florida (US), Vitalant (US)
Openalex Percentile: Top 61%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.