Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Using a knowledge-based planning solution to select patients for proton therapy.

Alexander R Delaney1, Max Dahele1, Jim P Tol1

  • 1Department of Radiation Oncology, VU University Medical Center, Amsterdam, The Netherlands.

Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology
|April 17, 2017
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The survival impact of combining radiotherapy and immune checkpoint inhibitors in patients with solid tumors: A systematic review and living meta-analysis of randomized controlled trials.

European journal of cancer (Oxford, England : 1990)·2026
Same author

ESTRO-EORTC expert guideline on target delineation and radiotherapy details for stage I-III small cell lung cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026
Same author

Clinical outcomes of stereotactic MRI-guided adaptive radiotherapy for renal tumors in patients with a solitary kidney.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2026
Same author

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

Clinical and translational radiation oncology·2026
Same author

Cone beam computed tomography-guided online adaptive radiation therapy: Clinical implementation in breast and axillary target volumes.

Clinical and translational radiation oncology·2025
Same author

ESTRO-ISRS clinical practice recommendations for re-irradiation of spinal metastases with Stereotactic Body Radiotherapy: Delphi consensus supported by a systematic review and meta-analysis.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2025

Knowledge-based planning accurately predicts organ-at-risk doses for proton therapy, enabling efficient patient selection. A proton-specific solution could further enhance these predictions.

Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Patient selection for proton therapy is complex and time-consuming.
  • Knowledge-based planning (KBP) solutions like RapidPlan™ model organ-at-risk (OAR) dose-volume histograms (DVHs).

Purpose of the Study:

  • To investigate if RapidPlan, using a photon-based algorithm, can predict proton DVHs.
  • To assess if these predictions can accurately identify patients suitable for proton therapy.

Main Methods:

  • Developed proton (ModelPROT) and photon (ModelPHOT) KBP models using 30 head-and-neck cancer plans.
  • Generated KBP plans for 10 evaluation patients and analyzed DVH prediction accuracy.
  • Compared KBP and manual plans for OAR mean doses, using a 6Gy difference in predicted doses to select patients for proton therapy.
Keywords:
Head and neck cancerKnowledge-based planningPatient selectionProton therapy

Related Experiment Videos

Main Results:

  • High accuracy for predicted vs. achieved mean OAR doses (R²=0.95 for ModelPROT, R²=0.98 for ModelPHOT).
  • KBP plans showed minimal average dose changes (<2Gy) compared to manual plans for critical structures.
  • The prediction difference (ΔPrediction) correctly identified 4 out of 5 patients for proton therapy.

Conclusions:

  • Knowledge-based DVH predictions offer an efficient method for patient-specific proton therapy selection.
  • A dedicated proton-specific RapidPlan solution may further improve selection accuracy.