Evidence map›Paper›PMID 40453307›Full record

ArticleCureus2025

Investigation of Knowledge-Based Planning Models for Intensity-Modulated Proton Therapy With Limited Data for Brain Targets.

Robert Kaderka, Yihang Xu, Gregory Azzam, Nesrin Dogan, Michael P Butkus

Abstract read
In one paragraph

Article in Cureus, 2025. 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

5 authors.

Robert KaderkaDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, USA.
Yihang XuDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, USA.
Gregory AzzamDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, USA.
Nesrin DoganDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, USA.
Michael P ButkusDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Knowledge-based planning (KBP) in radiation therapy aims to improve the plan quality and planning efficiency. Limited training data complicate the development of KBP models for intensity-modulated proton therapy (IMPT). Clinicians face questions such as whether KBP validation is feasible on the training set and if small data sets substantially impact the resulting plan quality. This work describes the development of KBP models for brain IMPT while focusing on these key questions. Materials and methods A hundred and twenty brain IMPT plans were identified and 31 were selected for validation. Three KBP models were trained (a) KBP

Indexed as

automated treatment planningbrain imptbrain tumour radiotherapyknowledge-based planningradiotherapy treatment planning

Identifiers

PMID40453307
PMCPMC12126691

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.