Evidence map›Paper›PMID 39031902›Full record

ArticleJournal of applied clinical medical physics2024

Evaluation of knowledge-based planning models for male pelvic CBCT-based online adaptive radiotherapy on conventional linear accelerators.

Riley C Tegtmeier, Edward L Clouser, Brady S Laughlin, Diego A Santos Toesca, Mattison J Flakus, Sara Bashir, Christopher J Kutyreff, Dean Hobbis, Daniel P Harrington, Jennifer L Smetanick and 5 more

Abstract readEvaluation Study
In one paragraph

Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Riley C TegtmeierDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0002-8339-7845
Edward L ClouserDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Brady S LaughlinDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Diego A Santos ToescaDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Mattison J FlakusDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Sara BashirDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Christopher J KutyreffDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Dean HobbisDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0001-8932-2097
Daniel P HarringtonDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Jennifer L SmetanickDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Nathan Y YuDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Carlos E VargasDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Sarah E JamesDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Jean-Claude M RwigemaDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Yi RongDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0002-2620-1893

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the practicality of employing a commercial knowledge-based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone-beam computed tomography (iCBCT) datasets. METHODS AND MATERIALS: Intact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose-volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan-generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow.

resultsModel testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09 ± 02:06 (intact) and 07:12 ± 01:04 (bed).

conclusionThis study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach.

Indexed as

Cone-Beam Computed TomographyOrgans at RiskParticle AcceleratorsProstatic NeoplasmsRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedAlgorithmsHumansImage Processing, Computer-AssistedKnowledge BasesMalePelvisRetrospective Studiesadaptive radiotherapyCBCTknowledge‐based planningprostate radiotherapyRapidPlan

Identifiers

PMID39031902
PMCPMC11492302

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.