AIMC Topic: Radiotherapy Dosage

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Deep-learning-based linac beam modelling with sparse beam data measurements.

Physics in medicine and biology
This paper introduces linac beam modelling network (LBMnet), a deep-learning-based approach for efficient linac beam modelling, generating percentage depth dose (PDD) and beam profiles by predicting beam data from sparse single-field measurements, th...

Rule-based AI automated adaptive treatment planning for image guided cervical cancer brachytherapy.

Brachytherapy
BACKGROUND AND PURPOSE: A rule-based AI system for automated adaptive treatment planning for image guided adaptive brachytherapy (IGABT) of locally advanced cervical cancer (LACC) was developed at Erasmus MC, and internally and externally validated b...

Beam orientation optimization in IMRT using sparse mixed integer programming and non-convex fluence map optimization.

Physics in medicine and biology
Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, non-convex problem traditionally addressed with heuristic methods.This work demonstrates the potential improvement of the proposed BOO, providing a math...

Multiomic based Bayesian network toxicity modeling for simultaneous prediction of multiple toxicity outcomes in NSCLC.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Radiation Pneumonitis (RP) and Radiation Esophagitis (RE) are two prominent dose limiting toxicities from NSCLC radiotherapy. This study aimed to develop a multi-objective Bayesian network (BN) model to predict multiple NSCLC outcomes simult...

Deep learning dosiomics in grade 4 radiation-induced lymphopenia prediction in radiotherapy for esophageal cancer: a multi-center study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, as well as their combination with dose-volume histogram (DVH) parameters and clinical factors to predict grade 4 radiation-induced lymphopenia (G4RIL)...

Deep learning-based automatic dose optimization for brachytherapy.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
PURPOSE: The purpose of this study is to determine the best dose processing method for deep learning-based dose prediction in brachytherapy (BT), as well as to investigate the feasibility of using the inverse dose optimization algorithm to improve tr...

Cone-beam computed tomography-based online adaptive radiotherapy of esophageal cancer in the neoadjuvant setting: Dosimetric analysis, toxicity and treatment response.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Chemoradiotherapy (CRT) followed by surgery is a treatment option for esophageal cancer (EC). However, concerns persist regarding cardiopulmonary toxicity and inconsistent daily target coverage due to anatomical changes. To ad...

Deep learning-based applicator selection between Syed and T&O in high-dose-rate brachytherapy for locally advanced cervical cancer: a retrospective study.

Physics in medicine and biology
High-dose-rate (HDR) brachytherapy is integral to the standard-of-care for locally advanced cervical cancer (LACC). Currently, selection of brachytherapy applicators relies on physician's clinical experience, which can lead to variability in treatmen...

Study on the relationship between vaginal dose and radiation-induced vaginal injury following cervical cancer radiotherapy, and model development.

Frontiers in public health
OBJECTIVE: This study investigates the relationship between vaginal radiation dose and radiation-induced vaginal injury in cervical cancer patients, with the aim of developing a risk prediction model to support personalized treatment strategies.

Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

Scientific reports
This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic cancer using a prototype DL-based automated planning support system, named RatoGuide, to evaluate it...