Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods.

MRI-only radiation therapy dosimetric assessment population-based evaluation quality assurance synthetic CT assessment voxel-wise analysis

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2022
Historique:
received: 14 06 2022
accepted: 20 09 2022
entrez: 27 10 2022
pubmed: 28 10 2022
medline: 28 10 2022
Statut: epublish

Résumé

The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method and a generative adversarial network. The CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.

Identifiants

pubmed: 36300084
doi: 10.3389/fonc.2022.968689
pmc: PMC9589295
doi:

Types de publication

Journal Article

Langues

eng

Pagination

968689

Informations de copyright

Copyright © 2022 Chourak, Barateau, Tahri, Cadin, Lafond, Nunes, Boue-Rafle, Perazzi, Greer, Dowling, de Crevoisier and Acosta.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Hilda Chourak (H)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.
The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia.

Anaïs Barateau (A)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Safaa Tahri (S)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Capucine Cadin (C)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Caroline Lafond (C)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Jean-Claude Nunes (JC)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Adrien Boue-Rafle (A)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Mathias Perazzi (M)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Peter B Greer (PB)

School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia.
Radiation Oncology, Calvary Mater Newcastle Hospital, Newcastle, NSW, Australia.

Jason Dowling (J)

The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia.

Renaud de Crevoisier (R)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Oscar Acosta (O)

University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France.

Classifications MeSH