Evidence map›Paper›PMID 36659871›Full record

ArticleJournal of applied clinical medical physics2023

Evaluation of generalization ability for deep learning-based auto-segmentation accuracy in limited field of view CBCT of male pelvic region.

Hideaki Hirashima, Mitsuhiro Nakamura, Keiho Imanishi, Megumi Nakao, Takashi Mizowaki

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2023. 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
1.0field-weighted citation impact, top 23% of its field
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, 4 citations in OpenAlex.

  1. Organ-contour-driven auto-matching algorithm in image-guided radiotherapy.Journal of applied clinical medical physics · 2024
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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 at 2 institutions in 1 country.

Hideaki HirashimaDepartment of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Mitsuhiro NakamuraDepartment of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Keiho Imanishie-Growth Co., Ltd., Kyoto-shi, Kyoto, Japan.
Megumi NakaoDepartment of Advanced Medical Engineering and Intelligence, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Takashi MizowakiDepartment of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Kyoto University · JPShimadzu (Japan) · JP

Funding

Scientific Research B JP22H03021Scientific Research B JP22H03022the JSPS KAKENHI 22H03021the JSPS KAKENHI 22H03022the JSPS KAKENHI 22K15804the JSPS KAKENHI JP22K15804
6 · The paper itself

Abstract

purposeThe aim of this study was to evaluate generalization ability of segmentation accuracy for limited FOV CBCT in the male pelvic region using a full-image CNN. Auto-segmentation accuracy was evaluated using various datasets with different intensity distributions and FOV sizes.

methodsA total of 171 CBCT datasets from patients with prostate cancer were enrolled. There were 151, 10, and 10 CBCT datasets acquired from Vero4DRT, TrueBeam STx, and Clinac-iX, respectively. The FOV for Vero4DRT, TrueBeam STx, and Clinac-iX was 20, 26, and 25 cm, respectively. The ROIs, including the bladder, prostate, rectum, and seminal vesicles, were manually delineated. The U

resultsThe mean scores ± standard deviation of visual evaluation for bladder, prostate, rectum, and seminal vesicle in all treatment machines were 1.0 ± 0.7, 1.5 ± 0.6, 1.4 ± 0.6, and 2.1 ± 0.8 points, respectively. The median DSC values for all imaging devices were ≥0.94 for the bladder, 0.84-0.87 for the prostate and rectum, and 0.48-0.69 for the seminal vesicles. Although the DSC values for the bladder and seminal vesicles were significantly different among the three imaging devices, the DSC value of the bladder changed by less than 1% point. The median MSD values for all imaging devices were ≤1.2 mm for the bladder and 1.4-2.2 mm for the prostate, rectum, and seminal vesicles. The MSD values for the seminal vesicles were significantly different between the three imaging devices.

conclusionThe proposed method is effective for testing datasets with different intensity distributions and FOV from training datasets.

Indexed as

Deep LearningSpiral Cone-Beam Computed TomographyHumansImage Processing, Computer-AssistedMalePelvisRadiotherapy Planning, Computer-Assistedauto-segmentationintensity distributionlimited FOV CBCTU2-Net CNN

Identifiers

PMID36659871
PMCPMC10161011
OpenAlexW4317567930

What OpenQuestion holds

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Registered trials

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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.