AIMC Topic: Radiotherapy Dosage
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Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.
Journal of applied clinical medical physics
Dec 20, 2024
PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential...
Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 19, 2024
BACKGROUND AND PURPOSE: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct ...
Validating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.
Physical and engineering sciences in medicine
Dec 18, 2024
This study examined the characteristics of the broad model (KBP) through a complete open-loop evaluation of volumetric modulated arc therapy (VMAT) plans for prostate cancer in 30 patients at two institutions. KBP, trained using 561 prostate cancer V...
Towards U-Net-based intraoperative 2D dose prediction in high dose rate prostate brachytherapy.
Brachytherapy
Dec 11, 2024
BACKGROUND: Poor needle placement in prostate high-dose-rate brachytherapy (HDR-BT) results in sub-optimal dosimetry and mentally predicting these effects during HDR-BT is difficult, creating a barrier to widespread availability of high-quality prost...
Automatic plan selection using deep network-A prostate study.
Medical physics
Dec 10, 2024
BACKGROUND: Recently, high-dose-rate (HDR) brachytherapy treatment plans generation was improved with the development of multicriteria optimization (MCO) algorithms that can generate thousands of pareto optimal plans within seconds. This brings a shi...
[Application of artificial intelligence-based organ contouring software and comparison of results in treatment planning for radiotherapy].
Orvosi hetilap
Dec 8, 2024
An assessment of the influence of trade-off optimization in commercial knowledge based planning library creation for tongue cancer patients.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Dec 6, 2024
This article aims to compare the dosimetric performance between knowledge-based plan (KBP) libraries with and without trade-off (TO) exploration using multicriterial optimization (MCO) for tongue cancer patients. The trade-off optimized library (KBP_...
Federated learning for enhanced dose-volume parameter prediction with decentralized data.
Medical physics
Dec 6, 2024
BACKGROUND: The widespread adoption of knowledge-based planning in radiation oncology clinics is hindered by the lack of data and the difficulty associated with sharing medical data.
Deep learning dose prediction to approach Erasmus-iCycle dosimetric plan quality within seconds for instantaneous treatment planning.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 6, 2024
BACKGROUND AND PURPOSE: Fast, high-quality deep learning (DL) prediction of patient-specific 3D dose distributions can enable instantaneous treatment planning (IP), in which the treating physician can evaluate the dose and approve the plan immediatel...
Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.
Journal of applied clinical medical physics
Dec 6, 2024
BACKGROUND AND OBJECTIVE: The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get bene...
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