Evidence map›Paper›PMID 38329565›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Detection support of lesions in patients with prostate cancer using

Naoki Tsuchiya, Koichiro Kimura, Ukihide Tateishi, Tadashi Watabe, Koji Hatano, Motohide Uemura, Norio Nonomura, Akinobu Shimizu

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 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

8 authors.

Naoki TsuchiyaInstitute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan. s228382t@st.go.tuat.ac.jp.ORCID http://orcid.org/0009-0001-0986-9533
Koichiro KimuraDepartment of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo City, Tokyo, Japan.
Ukihide TateishiDepartment of Diagnostic Radiology, Tokyo Medical and Dental University, Bunkyo City, Tokyo, Japan.
Tadashi WatabeDepartment of Nuclear Medicine and Tracer Kinetics, Graduate School of Medicine, Osaka University, Osaka, Japan.
Koji HatanoDepartment of Urology, Graduate School of Medicine, Osaka University, Osaka, Japan.
Motohide UemuraDepartment of Urology, Graduate School of Medicine, Osaka University, Osaka, Japan.
Norio NonomuraDepartment of Urology, Graduate School of Medicine, Osaka University, Osaka, Japan.
Akinobu ShimizuInstitute of Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan. simiz@cc.tuat.ac.jp.ORCID https://orcid.org/0000-0002-2719-5923

Funding

the Ministry of Health, Labour and Welfare Grants and Japan Agency for Medical Research and Development Grants 22ck0106577h0003the QiSS program of the OPERA from the Japan Science and Technology Agency JPMJOP1721
6 · The paper itself

Abstract

purposeThis study proposes a detection support system for primary and metastatic lesions of prostate cancer using

methodsA convolutional neural network with condition generators and feature-wise linear modulation (FiLM) layers was employed to allow input of not only PET/CT images but also non-image information, namely, Gleason score, flag of pre- or post-prostatectomy, and normalized z-coordinate of an input slice. We explored the insertion position of the FiLM layers to optimize the conditioning of the network using non-image information.

results

conclusionThis study demonstrated the effectiveness of the use of non-image information, including metadata of the patient and location information of the input slice image, in the detection of prostate cancer from

Indexed as

Positron Emission Tomography Computed TomographyProstatic NeoplasmsHumansMaleProstatectomyMetadataPET/CTProstate cancerSegmentation

Identifiers

PMID38329565

What OpenQuestion holds

Textmetadata
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.