Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Authors

Hana Baroudi
Kristy K Brock
Wenhua Cao
Xinru Chen
Caroline Chung
Laurence E Court
Mohammad D El Basha
Maguy Farhat
Skylar Gay
Mary P Gronberg
Aashish Chandra Gupta
Soleil Hernandez
Kai Huang
David A Jaffray
Rebecca Lim
Barbara Marquez
Kelly Nealon
Tucker J Netherton
Callistus M Nguyen
Brandon Reber
Dong Joo Rhee
Ramon M Salazar
Mihir D Shanker
Carlos Sjogreen
McKell Woodland
Jinzhong Yang
Cenji Yu
Yao Zhao

Language

English

Publication Date

2-10-2023

Journal

Diagnostics

DOI

10.3390/diagnostics13040667

PMID

36832155

PMCID

PMC9955359

PubMedCentral® Posted Date

2-10-2023

PubMedCentral® Full Text Version

Post-print

Abstract

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

Keywords

artificial intelligence, quality assurance, radiotherapy treatment planning

Published Open-Access

yes

Recommended Citation

Baroudi, Hana; Brock, Kristy K; Cao, Wenhua; et al., "Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?" (2023). Faculty, Staff and Student Publications. 411.
https://digitalcommons.library.tmc.edu/uthshis_docs/411