Evidence map›Paper›PMID 36615089›Full record

ReviewJournal of clinical medicine2022

In Search of an Imaging Classification of Adenomyosis: A Role for Elastography?

Sun-Wei Guo, Giuseppe Benagiano, Marc Bazot

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

3 authors at 3 institutions in 3 countries.

Sun-Wei GuoResearch Institute, Shanghai Obstetrics & Gynecology Hospital, Fudan University, Shanghai 200011, China.ORCID 0000-0002-8511-7624
Giuseppe BenagianoFaculty of Medicine and Dentistry, Sapienza, University of Rome, 00161 Rome, Italy.ORCID 0000-0002-3168-4594
Marc BazotDepartment of Radiology, Tenon University Hospital, Assistance Publique des Hôpitaux de Paris (AP-HP), Sorbonne Université, 75012 Paris, France.
Fudan University · CNSapienza University of Rome · ITSorbonne Université · FR

Funding

National Natural Science Foundation of China 82071623Science and Technology Commission of Shanghai Municipality 2017ZZ01016Shanghai Shenkang Center for Hospital Development SHDC2020CR2062B
6 · The paper itself

Abstract

Adenomyosis is a complex and poorly understood gynecological disease. It used to be diagnosed exclusively by histology after hysterectomy; today its diagnosis is carried out increasingly by imaging techniques, including transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI). However, the lack of a consensus on a classification system hampers relating imaging findings with disease severity or with the histopathological features of the disease, making it difficult to properly inform patients and clinicians regarding prognosis and appropriate management, as well as to compare different studies. Capitalizing on our grasp of key features of lesional natural history, here we propose adding elastographic findings into a new imaging classification of adenomyosis, incorporating affected area, pattern, the stiffest value of adenomyotic lesions as well as the neighboring tissues, and other pathologies. We argue that the tissue stiffness as measured by elastography, which has a wider dynamic detection range, quantitates a fundamental biologic property that directs cell function and fate in tissues, and correlates with the extent of lesional fibrosis, a proxy for lesional "age" known to correlate with vascularity and hormonal receptor activity. With this new addition, we believe that the resulting classification system could better inform patients and clinicians regarding prognosis and the most appropriate treatment modality, thus filling a void.

Indexed as

adenomyosiselastographyfibrosisimaging classificationmagnetic resonance imagingtransvaginal ultrasound

Identifiers

PMID36615089
PMCPMC9821156
OpenAlexW4313361154

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.