Evidence map›Paper›PMID 39291281›Full record

ArticleOpen medicine (Warsaw, Poland)2024

Application value of multi-parameter magnetic resonance image-transrectal ultrasound cognitive fusion in prostate biopsy.

Haichuan Yuan, Min Huang, Tao Liu, Wu Song, Chengpeng Luo

Abstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 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

5 authors.

Haichuan YuanDepartment of Urology, Renhe Hospital, Shanghai, 200431, People Republic of China.
Min HuangPreventive Health Care Section, Gaojing Town Community Health Service Center, Shanghai, 200435, People Republic of China.
Tao LiuDepartment of Urology, Youyi Street Community Health Service Center, Shanghai, 201999, People Republic of China.
Wu SongDepartment of Urology, Renhe Hospital, Shanghai, 200431, People Republic of China.
Chengpeng LuoDepartment of Urology, Renhe Hospital, Baoshan District, 1999 West Changjiang Road, Shanghai, 200431, People Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the effect of three-dimensional (3D) reconstruction-assisted cognitive fusion in targeted prostate biopsy. Results: There was no significant difference in the detection rate of prostate cancer (PCa) between targeted biopsy and systematic biopsy, and there was significant difference in the detection rate of clinically significant prostate cancer (csPCa) between targeted biopsy and systematic biopsy. In the low prostate total specific antigen (tPSA) group, there was no statistically significant difference in the detection rate of prostate cancer between the two biopsy modalities. However, compared with systematic puncture, targeted puncture had a higher detection rate for csPCa and a lower detection rate for clinically insignificant prostate cancer (ciPCa), and the difference was statistically significant. In the high tPSA group, there was no significant difference in the detection rate of PCa, csPCa, and ciPCa between the two biopsy types. Single needle positive rate of targeted puncture (29.77%) was significantly higher than that of systematic puncture (10.28%). Conclusions: The detection rate of csPCa in 3D reconstruction-assisted cognitive fusion targeted prostate biopsy is better than that of 12-needle systematic biopsy, which markedly improved the positive rate of prostate biopsy.

Indexed as

cognitive fusionprostate cancersystematic biopsytargeted biopsythree-dimensional reconstruction

Identifiers

PMID39291281
PMCPMC11406436

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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.