ArticleFrontiers in oncology2021
Personalized Treatment Planning Automation in Prostate Cancer Radiation Oncology: A Comprehensive Dosimetric Study.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 18 citations in OpenAlex.
- Multimodal multitask deep learning for grading management system in non-small cell lung cancer.Nature communications · 2026Article
- Artificial intelligence applications in prostate cancer.Prostate cancer and prostatic diseases · 2024Review
- Estimation of the risk of secondary cancer in rectum and bladder after radiation therapy for prostate cancer using a feasibility dose-volume histogram.Physics and imaging in radiation oncology · 2023Article
- The effect of integrating knowledge-based planning with multicriteria optimization in treatment planning for prostate SBRT.Journal of applied clinical medical physics · 2023Article
- Knowledge-based planning for the radiation therapy treatment plan quality assurance for patients with head and neck cancer.Journal of applied clinical medical physics · 2022Article
- Personalized Automation of Treatment Planning for Linac-Based Stereotactic Body Radiotherapy of Spine Cancer.Frontiers in oncology · 2022Article
- Evaluation of two independent dose prediction methods to personalize the automated radiotherapy planning process for prostate cancer.Physics and imaging in radiation oncology · 2022Article
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn radiation oncology, automation of treatment planning has reported the potential to improve plan quality and increase planning efficiency. We performed a comprehensive dosimetric evaluation of the new Personalized algorithm implemented in Pinnacle MATERIAL AND
methodsThirteen low-risk prostate (without lymph-nodes irradiation) and 13 high-risk prostate (with lymph-nodes irradiation) treatments were retrospectively taken from our clinical database and re-optimized using two different automated engines implemented in the Pinnacle treatment system. These two automated engines, the currently used Autoplanning and the new Personalized are both template-based algorithms that use a wish-list to formulate the planning goals and an iterative approach able to mimic the planning procedure usually adopted by experienced planners. In addition, the new Personalized module integrates a new engine, the Feasibility module, able to generate an "
resultsFor similar targets coverage, Pers plans reported a significant increase of dose conformity and less irradiation of healthy tissue, with significant dose reduction for rectum, bladder, and femurs. On average, Pers plans decreased rectal mean dose by 11.3 and 8.3 Gy for low-risk and high-risk cohorts, respectively. Similarly, the Pers plans decreased the bladder mean doses by 7.3 and 7.6 Gy for low-risk and high-risk cohorts, respectively. The integral dose was reduced by 11-16% with respect to MP plans. Overall planning times were dramatically reduced to about 7 and 15 min for Pers plans. Despite the increased complexity, all plans passed the 3%/2 mm γ-analysis for dose verification.
conclusionsThe Personalized engine provided an overall increase of plan quality, in terms of dose conformity and sparing of normal tissues for prostate cancer patients. The Feasibility "
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