Evidence map›Paper›PMID 42014901›Full record

ArticleScientific reports2026

3D micro-CT and immunofluorescence-based characterization of Denonvilliers' fascia and its neurovascular structures.

So-Young In, Tae-Hyeon Cho, Hun-Mu Yang

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

3 authors.

So-Young InDepartment of Anatomy, Translational Laboratory for Clinical Anatomy, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
Tae-Hyeon Cho *Department of Anatomy, Wonkwang University School of Medicine, 460 Iksan-daero, Iksan, 54538, Republic of Korea. gods176@wku.ac.kr.
Hun-Mu Yang *Department of Anatomy, Translational Laboratory for Clinical Anatomy, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. yanghm@yuhs.ac.

Funding

Korea government (MSIT, Ministry of Sicence and ICT) RS-2023-00246638Korea Health Industry Development Institute RS-2024-00406488
6 · The paper itself

Abstract

This study provides a comprehensive anatomical and histological characterization of Denonvilliers’ fascia (DVF) and its associated neurovascular structures using manual dissection, histology, three-dimensional micro-CT imaging, and immunofluorescence (IF) analysis. Five embalmed and three fresh cadavers (All males; mean age, 77.9 years) were examined, All specimens without any medical history of pelvic cavity deformation, pelvic trauma, or surgical interventions. Micro-CT and resin-embedded sections demonstrated that the DVF originates from the peritoneal reflection and consistently exhibits a multilayered architecture with division, compression, and fusion patterns depending on pelvic level. Nerve branches from the inferior hypogastric plexus (IHP) coursed along the DVF, accompanying the vessels. In a cadaver with colorectal cancer, the DVF identified pathological thickening and separation of fascial laminae. IF analysis from two fresh cadavers revealed the axonal composition of the IHP: 53.2% sympathetic (TH-positive), 21.9% parasympathetic (nNOS-positive), 18.2% sensory (CGRP-positive), and 6.7% unlabeled fibers. Parasympathetic fibers observed extensive myelination, whereas sympathetic fibers observed minimal overlap with MBP. These findings clarify the neural distribution in the DVF region and provide mechanistic insight into postoperative dysfunction. This integrated anatomical framework supports improved nerve-sparing strategies in rectal surgery.

Indexed as

FasciaHypogastric PlexusX-Ray MicrotomographyAgedAged, 80 and overCadaverFluorescent Antibody TechniqueHumansImaging, Three-DimensionalMalePelvisDenonvilliers’ fasciaImmunofluorescenceInferior hypogastric plexusMicro-CTPelvic autonomic nerves

Identifiers

PMID42014901
PMCPMC13265767

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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.