ArticlePhysical and engineering sciences in medicine2024
Dosiomics-based detection of dose distribution variations in helical tomotherapy for prostate cancer patients: influence of treatment plan parameters.
Article in Physical and engineering sciences in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The stability of dosiomics features (DFs) and dose-volume histogram (DVH) parameters for detecting disparities in helical tomotherapy planned dose distributions was assessed. Treatment plans of 18 prostate patients were recalculated using the followings: field width (WF) (2.5 vs. 5), pitch factor (PF) (0.433 vs. 0.444), and modulation factor (MF) (2.5 vs. 3). From each of the eight plans per patient, ninety-three original and 744 wavelet-based DFs were extracted, using 3D-Slicer software, across six regions including: target volume (PTV), pelvic lymph nodes (PTV-LN), PTV + PTV-LN (PTV-All), one cm rind around PTV-All (PTV-Ring), rectum, and bladder. For the resulting DFs and DVH parameters, the coefficient of variation (CV) was calculated, and using hierarchical clustering, the features were classified into low/high variability. The significance of parameters on instability was analyzed by a three-way analysis of variance. All DF's were stable in PTV, PTV-LN, and PTV-Ring (average CV (
Indexed as
Identifiers
39080209What OpenQuestion holds
Registered trials
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.