Evidence map›Paper›PMID 39220116›Full record

ArticlePhysics and imaging in radiation oncology2024

Optimizing volumetric modulated arc therapy prostate planning using an automated Fine-Tuning process through dynamic adjustment of optimization parameters.

Hasan Cavus, Thierry Rondagh, Alexandra Jankelevitch, Koen Tournel, Marc Orlandini, Philippe Bulens, Laurence Delombaerde, Kenny Geens, Wouter Crijns, Brigitte Reniers

Abstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Hasan CavusDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Thierry RondaghDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Alexandra JankelevitchDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Koen TournelDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Marc OrlandiniDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Philippe BulensDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Laurence DelombaerdeDepartment Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Belgium.
Kenny GeensDepartment of Radiation Oncology, Jessa Hospital, 3500 Hasselt, Belgium.
Wouter CrijnsDepartment Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Belgium.
Brigitte ReniersFaculty of Engineering Technology, Hasselt University, B- 3590, Diepenbeek, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In radiotherapy treatment planning, optimization is essential for achieving the most favorable plan by adjusting optimization criteria. This study introduced an innovative approach to automatically fine-tune optimization parameters for volumetric modulated arc therapy prostate planning, ensuring all constraints were met. A knowledge-based planning model was invoked, and the fine-tuning process was applied through an in-house developed script. Among 25 prostate plans, this fine-tuning increased the number of plans meeting all constraints from 10/25 to 22/25, with a reduction in mean monitor units per gray without increasing plan's complexity. This automation improved efficiency by saving time and resources in treatment planning.

Indexed as

AutomationAuto-PlanningEclipse Scripting APIKnowledge-Based Planning

Identifiers

PMID39220116
PMCPMC11363496

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.