Evidence map›Paper›PMID 37859989›Full record

ArticleFrontiers in endocrinology2023

Value of three-dimensional visualization of preoperative prostatic magnetic resonance imaging based on measurements of anatomical structures in predicting positive surgical margin after radical prostatectomy.

Bo Fan, Luxin Zhang, Yuchao Wang, Zhihong Dai, Heming Pan, Jiaxin Xie, Hao Wang, Zihan Xin, Yutong Wang, Xu Duan and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in endocrinology, 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
–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

13 authors.

Bo FanDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Luxin ZhangDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Yuchao WangDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Zhihong DaiDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Heming PanDepartment of Scientific Research, Dalian Neusoft University of Information, Dalian, Liaoning, China.
Jiaxin XieInstitute of Urology, Peking University, Beijing, China.
Hao WangDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, Liaoning, China.
Zihan XinDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, Liaoning, China.
Yutong WangDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, Liaoning, China.
Xu DuanDepartment of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, Liaoning, China.
Jiawen LuoDepartment of Radiology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Liang WangDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Zhiyu LiuDepartment of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Positive surgical margin (PSM) or apical positive surgical margin (APSM) is an established predictive factor of biochemical recurrence or disease progression in prostate cancer (PCa) patients after radical prostatectomy. Since there are limited usable magnetic resonance imaging (MRI)-based models, we sought to explore the role of three-dimensional (3D) visualization for preoperative MRI in the prediction of PSM or APSM. Methods: From December 2016 to April 2022, 149 consecutive PCa patients who underwent radical prostatectomy were retrospectively selected from the Second Affiliated Hospital of Dalian Medical University. According to the presence of PSM or APSM, patients were divided into a PSM group (n=41) and a without PSM group (n=108) and into an APSM group (n=33) and a without APSM group (n=116). Twenty-one parameters, including prostate apical shape, PCa distance to the membranous urethra, and pubic angle, were measured on 3D visualization of MRI. The development of the nomogram models was built by the findings of multivariate logistic regression analysis for significant factors. Results: To predict the probability of PSM, a longer PCa distance to the membranous urethra (OR=0.136, p=0.019) and the distance from the anterior peritoneum to the anterior border of the coccyx (work space AP, OR=0.240, p=0.030) were independent protective factors, while a type 3 prostate apical shape (OR=8.262, p=0.025) and larger pubic angle 2 (OR=5.303, p=0.029) were identified as independent risk factors. The nomogram model presented an area under the curve (AUC) of the receiver operating characteristic curve (ROC) of PSM of 0.777. In evaluating the incidence of APSM, we found that the distance to the membranous urethra (OR=0.135, p=0.014) was associated with a low risk of APSM, while larger pubic angle 1 (OR=4.666, p=0.043) was connected to a higher risk of APSM. The nomogram model showed that the AUC of APSM was 0.755. Conclusion: As 3D visualization for preoperative MRI showed good performance in predicting PSM or APSM, the tool might be potentially valuable, which also needs to be validated by multicenter, large-scale, prospective studies.

Indexed as

ProstateProstatic NeoplasmsHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleMargins of ExcisionProspective StudiesProstatectomyRetrospective StudiesRisk Factorsmagnetic resonance imagingpositive surgical marginprostate cancerradical prostatectomythree-dimensional visualization

Identifiers

PMID37859989
PMCPMC10582708

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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.