Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy.

Automatic segmentation cardiac motion cardiac substructures contour variation dose uncertainty

Journal

Clinical oncology (Royal College of Radiologists (Great Britain))
ISSN: 1433-2981
Titre abrégé: Clin Oncol (R Coll Radiol)
Pays: England
ID NLM: 9002902

Informations de publication

Date de publication:
04 Apr 2024
Historique:
received: 17 07 2023
revised: 27 03 2024
accepted: 02 04 2024
medline: 23 4 2024
pubmed: 23 4 2024
entrez: 22 4 2024
Statut: aheadofprint

Résumé

Delineation variations and organ motion produce difficult-to-quantify uncertainties in planned radiation doses to targets and organs at risk. Similar to manual contouring, most automatic segmentation tools generate single delineations per structure; however, this does not indicate the range of clinically acceptable delineations. This study develops a method to generate a range of automatic cardiac structure segmentations, incorporating motion and delineation uncertainty, and evaluates the dosimetric impact in lung cancer. Eighteen cardiac structures were delineated using a locally developed auto-segmentation tool. It was applied to lung cancer planning CTs for 27 curative (planned dose ≥50 Gy) cases, and delineation variations were estimated by using ten mapping-atlases to provide separate substructure segmentations. Motion-related cardiac segmentation variations were estimated by auto-contouring structures on ten respiratory phases for 9/27 cases that had 4D-planning CTs. Dose volume histograms (DVHs) incorporating these variations were generated for comparison. Variations in mean doses (Dmean), defined as the range in values across ten feasible auto-segmentations, were calculated for each cardiac substructure. Over the study cohort the median variations for delineation uncertainty and motion were 2.20-11.09 Gy and 0.72-4.06 Gy, respectively. As relative values, variations in Dmean were between 18.7%-65.3% and 7.8%-32.5% for delineation uncertainty and motion, respectively. Doses vary depending on the individual planned dose distribution, not simply on segmentation differences, with larger dose variations to cardiac structures lying within areas of steep dose gradient. Radiotherapy dose uncertainties from delineation variations and respiratory-related heart motion were quantified using a cardiac substructure automatic segmentation tool. This predicts the 'dose range' where doses to structures are most likely to fall, rather than single DVH curves. This enables consideration of these uncertainties in cardiotoxicity research and for future plan optimisation. The tool was designed for cardiac structures, but similar methods are potentially applicable to other OARs.

Identifiants

DOI: 10.1016/j.clon.2024.04.002 PMID: 38649309
pubmed: 38649309
pii: S0936-6555(24)00143-2
doi: 10.1016/j.clon.2024.04.002
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Auteurs

V Chin (V)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool and Macarthur Cancer Therapy Centres, Department of Radiation Oncology, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia; University of Sydney, Image X Institute, Sydney, Australia. Electronic address: vicky.chin@unsw.edu.au.

R N Finnegan (RN)

Ingham Institute for Applied Medical Research, Sydney, Australia; University of Sydney, Institute of Medical Physics, Sydney, Australia; Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia.

P Chlap (P)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool and Macarthur Cancer Therapy Centres, Department of Radiation Oncology, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia.

L Holloway (L)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool and Macarthur Cancer Therapy Centres, Department of Radiation Oncology, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia; University of Sydney, Institute of Medical Physics, Sydney, Australia.

D I Thwaites (DI)

University of Sydney, Institute of Medical Physics, Sydney, Australia; St James's Hospital and University of Leeds, Leeds Institute of Medical Research, Radiotherapy Research Group, Leeds, United Kingdom.

J Otton (J)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool Hospital, Department of Cardiology, Sydney, Australia.

G P Delaney (GP)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool and Macarthur Cancer Therapy Centres, Department of Radiation Oncology, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia.

S K Vinod (SK)

University of New South Wales, South Western Sydney Clinical School, Sydney, Australia; Liverpool and Macarthur Cancer Therapy Centres, Department of Radiation Oncology, Sydney, Australia; Ingham Institute for Applied Medical Research, Sydney, Australia.

Classifications MeSH