Predicting cervical cancer target motion using a multivariate regression model to enable patient selection for adaptive external beam radiotherapy.
Adaptive radiotherapy
Cervical cancer
Image guided radiotherapy
Interfraction motion
Mathematical modelling
Journal
Physics and imaging in radiation oncology
ISSN: 2405-6316
Titre abrégé: Phys Imaging Radiat Oncol
Pays: Netherlands
ID NLM: 101704276
Informations de publication
Date de publication:
Jan 2024
Jan 2024
Historique:
received:
17
10
2023
revised:
06
02
2024
accepted:
08
02
2024
medline:
29
2
2024
pubmed:
29
2
2024
entrez:
29
2
2024
Statut:
epublish
Résumé
Interfraction motion during cervical cancer radiotherapy is substantial in some patients, minimal in others. Non-adaptive plans may miss the target and/or unnecessarily irradiate normal tissue. Adaptive radiotherapy leads to superior dose-volume metrics but is resource-intensive. The aim of this study was to predict target motion, enabling patient selection and efficient resource allocation. Forty cervical cancer patients had CT with full-bladder (CT-FB) and empty-bladder (CT-EB) at planning, and daily cone-beam CTs (CBCTs). The low-risk clinical target volume (CTV The Two-CT model was based upon rectal volume, dice similarity coefficient between CT-FB and CT-EB CTV Uterocervix motion is complex and multifactorial. We present two multivariate models which predicted motion with reasonable accuracy using pre-treatment information, and outperformed the only published method.
Sections du résumé
Background and purpose
UNASSIGNED
Interfraction motion during cervical cancer radiotherapy is substantial in some patients, minimal in others. Non-adaptive plans may miss the target and/or unnecessarily irradiate normal tissue. Adaptive radiotherapy leads to superior dose-volume metrics but is resource-intensive. The aim of this study was to predict target motion, enabling patient selection and efficient resource allocation.
Materials and methods
UNASSIGNED
Forty cervical cancer patients had CT with full-bladder (CT-FB) and empty-bladder (CT-EB) at planning, and daily cone-beam CTs (CBCTs). The low-risk clinical target volume (CTV
Results
UNASSIGNED
The Two-CT model was based upon rectal volume, dice similarity coefficient between CT-FB and CT-EB CTV
Conclusion
UNASSIGNED
Uterocervix motion is complex and multifactorial. We present two multivariate models which predicted motion with reasonable accuracy using pre-treatment information, and outperformed the only published method.
Identifiants
pubmed: 38419803
doi: 10.1016/j.phro.2024.100554
pii: S2405-6316(24)00024-1
pmc: PMC10901141
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100554Informations de copyright
© 2024 The Author(s).
Déclaration de conflit d'intérêts
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Lei Wang is part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London; and part-funded by Elekta Ltd. Helen McNair is funded by a National Institute for Health Research and Health Education England (HEE/NIHR) Senior Clinical Lectureship (ICA-SCL-2018–04-ST2-002). Emma Harris has received research funding from Elekta Ltd and Cancer Research UK Programme Foundation Award A23557. Susan Lalondrelle has received research funding and speaking fees from Elekta Ltd.