A5046264610- Advanced Radiotherapy Techniques
- Statistical Methods in Clinical Trials
- Radiation Therapy and Dosimetry
- Radiomics and Machine Learning in Medical Imaging
- Head and Neck Cancer Studies
- Prostate Cancer Diagnosis and Treatment
- Prostate Cancer Treatment and Research
- Colorectal Cancer Surgical Treatments
- Health Systems, Economic Evaluations, Quality of Life
- Nuclear reactor physics and engineering
- Medical Imaging Techniques and Applications
- Radiation Dose and Imaging
- Effects of Radiation Exposure
- Healthcare Operations and Scheduling Optimization
- Advances in Oncology and Radiotherapy
- Immunodeficiency and Autoimmune Disorders
- Lung Cancer Diagnosis and Treatment
- Medical Imaging and Analysis
- Head and Neck Surgical Oncology
- Colorectal Cancer Treatments and Studies
- Radiation Effects and Dosimetry
- Colorectal and Anal Carcinomas
- Manufacturing Process and Optimization
- Cancer Treatment and Pharmacology
- Endometrial and Cervical Cancer Treatments
Erasmus MC Cancer Institute
2017-2022
IntroductionMany approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to ‘manual’ trial-and-error planning, decrease routine workload. A few implemented in commercial systems (TPSs). We performed a pre-clinical validation of new system (‘NovelATP’) that is based on fully-automated multi-criterial optimization (MCO). The aim NovelATP automatically generate each patient single high-quality, Pareto-optimal...
Proton therapy is becoming increasingly available, so it important to apply objective and individualized patient selection identify those who are expected benefit most from proton compared conventional intensity modulated radiation (IMRT). Comparative treatment planning using normal tissue complication probability (NTCP) evaluation has recently been proposed. This work investigates the impact of NTCP model dose uncertainties on model-based selection.We used IMRT (IMPT) plans 78 oropharyngeal...
Background and purpose: In this study we developed a workflow for fully-automated generation of deliverable IMRT plans 1.5 T MR-Linac (MRL) based on contoured CT scans, evaluated automated MRL planning rectal cancer.Methods: The Monte Carlo dose calculation engine used in the clinical TPS (Monaco, Elekta AB, Stockholm, Sweden), suited high accuracy calculations magnetic field, was coupled to our in-house Erasmus-iCycle optimizer. Clinically 23 cancer patients were automatically generated...
Background: Currently, radiation-oncologists generally evaluate a single treatment plan for each patient that is possibly adapted by the planner prior to final approval. There no systematic exploration of patient-specific trade-offs between planning aims, using set plans with a-priori defined (slightly) different balances. To this purpose, we developed an automated workflow and explored its use prostate cancer. Materials Methods: For fifty study patients, seven were generated, including...
Background With the large-scale introduction of volumetric modulated arc therapy (VMAT), selection optimal beam angles for coplanar static-beam IMRT has increasingly become obsolete. Due to unavailability VMAT in current MR-linacs, problem re-gained importance. An application automated treatment planning with integrated, patient-specific computer-optimization (BAO) was used systematically investigate computer-aided generation angle class solutions (CS) replacement computationally expensive...
Complexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated angle optimization was used to define VMAT class solutions (CSs), each consisting a coplanar arc additional 1 or 2 fixed, partial arcs.Automated generate plan 5 complementary computer-optimized IMRT beams (VMAT+5) 20 included patients. Subsequently, frequency distribution 100...
ConclusionThe novel method for automatic configuration of the LRPM resulted in clinically favourable Pareto-optimal treatment plans.Due to vast reduction workload, a major obstacle introducing large-scale automated multi-criterial planning with has been overcome.