Advancements and Challenges in Computer-Assisted Medical Interventions for Image-Guided Prostate Cancer Treatments

Computer-assisted medical interventions (CAMI) provide assistance to a physician (surgeon, interventional radiologist, etc.) to make the best diagnostic or therapeutic decisions for their patient and to execute the interventions safely and clinically efficiently. This entails constructing and continuously updating a digital twin using patient-specific multimodal information (such as images and signals) and prior knowledge (including atlases, models, and statistical data) and leveraging these for intervention planning and simulation. The execution phase is facilitated by various medical devices, whether robotic or not. Clinical scenarios featuring deformable and dynamic organs necessitate real-time monitoring and adjustment of the intervention plan. Achieving minimal invasiveness mandates the integration of devices and sensors to enhance perception and dexterity. Two illustrative examples of image-based prostate cancer treatments (laparoscopic prostate surgery and ultrasound-based brachytherapy) are used to provide insight into the current state of the field and to address existing challenges and bottlenecks of CAMI.

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Publication Details

Journal
Annual Review of Biomedical Engineering
Published
2026-05-01
DOI
https://doi.org/10.1146/annurev-bioeng-102723-015625
Primary Topic
Advanced Radiotherapy Techniques
Type
article
Field-Weighted Citation Impact
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article

Advancements and Challenges in Computer-Assisted Medical Interventions for Image-Guided Prostate Cancer Treatments

Jocelyne Troccaz, Sandrine Voros
Annual Review of Biomedical Engineering
Advanced Radiotherapy Techniques
article

Advancements and Challenges in Computer-Assisted Medical Interventions for Image-Guided Prostate Cancer Treatments

Jocelyne Troccaz, Sandrine Voros
article en

Abstract

Computer-assisted medical interventions (CAMI) provide assistance to a physician (surgeon, interventional radiologist, etc.) to make the best diagnostic or therapeutic decisions for their patient and to execute the interventions safely and clinically efficiently. This entails constructing and continuously updating a digital twin using patient-specific multimodal information (such as images and signals) and prior knowledge (including atlases, models, and statistical data) and leveraging these for intervention planning and simulation. The execution phase is facilitated by various medical devices, whether robotic or not. Clinical scenarios featuring deformable and dynamic organs necessitate real-time monitoring and adjustment of the intervention plan. Achieving minimal invasiveness mandates the integration of devices and sensors to enhance perception and dexterity. Two illustrative examples of image-based prostate cancer treatments (laparoscopic prostate surgery and ultrasound-based brachytherapy) are used to provide insight into the current state of the field and to address existing challenges and bottlenecks of CAMI.

Annual Review of Biomedical EngineeringVol. 28(1)
Centre National de la Recherche Scientifique (FR), Inserm (FR), Université Grenoble Alpes (FR)
Good health and well-being
Openalex Percentile: Top 9%
Advanced Radiotherapy Techniques
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