Clinical Application of Deep Learning-Assisted Needles Reconstruction in Prostate Ultrasound Brachytherapy.

Journal: International journal of radiation oncology, biology, physics

PMID: 39800329

Abstract

PURPOSE: High dose rate (HDR) prostate brachytherapy (BT) procedure requires image-guided needle insertion. Given that general anesthesia is often employed during the procedure, minimizing overall planning time is crucial. In this study, we explore the clinical feasibility and time-saving potential of artificial intelligence (AI)-driven auto-reconstruction of transperineal needles in the context of ultrasound (US)-guided prostate BT planning.

Authors

Mathieu Goulet

Département de radio-oncologie, CISSS de Chaudière-Appalaches, Lévis, Québec, Canada. Electronic address: Mathieu_goulet@ssss.gouv.qc.ca.
Patricia Duguay-Drouin

Département de radio-oncologie, CISSS de Chaudière-Appalaches, Lévis, Québec, Canada.
Julia Mascolo-Fortin

Département de radio-oncologie, CISSS de Chaudière-Appalaches, Lévis, Québec, Canada.
Julien Mégrourèche

Département de radio-oncologie, CISSS de Chaudière-Appalaches, Lévis, Québec, Canada.
Nadia Octave

Département de radio-oncologie, CISSS de Chaudière-Appalaches, Lévis, Québec, Canada.
James Man Git Tsui

Department of Radiation Oncology, McGill University Health Center, Montreal, Québec, Canada.

Keywords

Brachytherapy Deep Learning Feasibility Studies Humans Image Processing, Computer-Assisted Male Needles Prostate Prostatic Neoplasms Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Image-Guided Time Factors Ultrasonography Ultrasonography, Interventional

External Resources

View on PubMed Access via DOI PubMed (39800329)

Clinical Application of Deep Learning-Assisted Needles Reconstruction in Prostate Ultrasound Brachytherapy.

Abstract

Authors

Keywords

External Resources

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