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April 26, 2026Physics and Imaging in Radiation Oncology0 citationsOpen Access

Comparative Assessment of Deep Learning and Knowledge-Based Dose Prediction Models in Prostate...

A comparative assessment of deep learning and knowledge-based dose prediction models for advanced radiotherapy planning of prostate cancer with focal boosting

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Authors

MPMaria A. PilieroAAAntonio AngrisaniDBDavide G. Bosetti

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Overview

Randomized trial compares dose prediction models in prostate cancer, highlighting optimization needs.

Key Points

  • This study aims to evaluate the effectiveness of deep learning versus knowledge-based dose prediction models for prostate radiotherapy planning with focal boosting.
  • Compared knowledge-based and deep-learning dose prediction models against clinically approved plans for prostate radiotherapy.
  • Assessed dose variations for bladder and rectum in high-dose regions and mean doses for femoral heads, pudendal artery, and urethra.
  • Knowledge-based model accurately reproduced clinical plans.
  • Deep-learning showed median dose variations of 5% for bladder and rectum, and a mean dose of 3.8 Gy higher for femoral heads.
  • Pudendal artery doses were 15 Gy higher than constraints, indicating training dataset limitations.

Cite This Study

Piliero et al. (2026) studied this question.

synapsesocial.com/papers/69edab424a46254e215b351ehttps://doi.org/10.1016/j.phro.2026.100977
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