Accuracy and consistency of intensity-based deformable image registration in 4DCT for tumor motion estimation in liver radiotherapy planning.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2022
Historique:
received: 15 12 2021
accepted: 23 06 2022
entrez: 8 7 2022
pubmed: 9 7 2022
medline: 14 7 2022
Statut: epublish

Résumé

We investigate the accuracy of intensity-based deformable image registration (DIR) for tumor localization in liver stereotactic body radiotherapy (SBRT). We included 4DCT scans to capture the breathing motion of eight patients receiving SBRT for liver metastases within a retrospective clinical study. Each patient had three fiducial markers implanted. The liver and the tumor were delineated in the mid-ventilation phase, and their positions in the other phases were estimated with deformable image registration. We tested referenced and sequential registrations strategies. The fiducial markers were the gold standard to evaluate registration accuracy. The registration errors related to measured versus estimated fiducial markers showed a mean value less than 1.6mm. The positions of some fiducial markers appeared not stable on the 4DCT throughout the respiratory phases. Markers' center of mass tends to be a more reliable measurement. Distance errors of tumor location based on registration versus markers center of mass were less than 2mm. There were no statistically significant differences between the reference and the sequential registration, i.e., consistency and errors were comparable to resolution errors. We demonstrated that intensity-based DIR is accurate up to resolution level for locating the tumor in the liver during breathing motion.

Identifiants

pubmed: 35802593
doi: 10.1371/journal.pone.0271064
pii: PONE-D-21-39615
pmc: PMC9269460
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0271064

Déclaration de conflit d'intérêts

The authors LBS, MJ, SN and IRV received grants and/or educational fees from Varian Medical Systems.

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Auteurs

José D Tascón-Vidarte (JD)

Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.

Line Bjerregaard Stick (LB)

Department of Oncology, Copenhagen, Denmark.

Mirjana Josipovic (M)

Department of Oncology, Copenhagen, Denmark.

Signe Risum (S)

Department of Oncology, Copenhagen, Denmark.

Julien Jomier (J)

Kitware SAS, Villeurbanne, France.

Kenny Erleben (K)

Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.

Ivan Richter Vogelius (IR)

Department of Oncology, Copenhagen, Denmark.

Sune Darkner (S)

Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.

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Classifications MeSH