AIMC Topic: Organs at Risk

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Direct-to-Treatment Adaptive Radiation Therapy: Live Planning of Spine Metastases Using Novel Cone Beam Computed Tomography.

International journal of radiation oncology, biology, physics
PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy is carried out using a synthetic CT (sCT) created through deformable registration between the patient-specific fan-beam CT, fan-beam computed tomography (FBCT), and...

Geometric and Dosimetric Evaluation of a RayStation Deep Learning Model for Auto-Segmentation of Organs at Risk in a Real-World Head and Neck Cancer Dataset.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).

Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy.

Scientific reports
This study was conducted to develop and validate a novel deep reinforcement learning (DRL) algorithm incorporating the segment anything model (SAM) to enhance the accuracy of automatic contouring organs at risk during radiotherapy for cervical cancer...

A knowledge-based planning model to identify fraction-reduction opportunities in brain stereotactic radiotherapy.

Journal of applied clinical medical physics
OBJECTIVE: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the ...

Dose prediction via deep learning to enhance treatment planning of lung radiotherapy including simultaneous integrated boost techniques.

Medical physics
BACKGROUND: Recent studies have shown deep learning techniques are able to predict three-dimensional (3D) dose distributions of radiotherapy treatment plans. However, their use in dose prediction for treatments with varied prescription doses includin...

Evaluation and failure analysis of four commercial deep learning-based autosegmentation software for abdominal organs at risk.

Journal of applied clinical medical physics
PURPOSE: Deep learning-based segmentation of organs-at-risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model-based autocontouring methods. While several commercial deep learning-base...

A deep learning-based peer review method for radiotherapy planning.

Medical physics
BACKGROUND: Quality control (QC) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Traditionally, QC relies on standard indicators and subjective assessments, which may lead to inconsistencies.

The implementation of knowledge-based planning with partial OAR contours for prostate radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Intra- and inter-observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to address this challenge is the use of partial contours for treatment planning, focusing on uninvolved or ...

Automating the optimization of proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning.

Medical physics
BACKGROUND: Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task where a large number of potentially conflicting planning objectives are involved. Deep reinforcement le...

Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors.

Radiation oncology (London, England)
PURPOSE: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and mon...