Evidence map›Paper›PMID 37222836›Full record

ArticleInsights into imaging2023

Differentiation of placenta percreta through MRI features and diffusion-weighted magnetic resonance imaging.

Hang Li, Tao Lu, Mou Li, Yishuang Wang, Feng Zhang, Yi Yuan, Meilin Zhu, Xinyi Zhao

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Insights into imaging, 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
1.7field-weighted citation impact, top 15% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  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

8 authors at 1 institution in 1 country.

Hang LiDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Tao LuDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China. 345248302@qq.com.
Mou LiDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Yishuang WangDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Feng ZhangDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Yi YuanDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Meilin ZhuDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
Xinyi ZhaoDepartment of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, 32 West Second Section, First Ring Road, Chengdu, 610072, China.
University of Electronic Science and Technology of China · CN

Funding

Sichuan Province Science and Technology Support Program 2021YJ0237
6 · The paper itself

Abstract

objectivesTo identify whether parameters measured from diffusion kurtosis and intravoxel incoherent motion help diagnose placenta percreta.

methodsWe retrospectively enrolled 75 patients with PAS disorders including 13 patients with placenta percreta and 40 patients without PAS disorders. Each patients underwent diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC), perfusion fraction (f), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), mean diffusion kurtosis (MK) and mean diffusion coefficient (MD) were measured by the volumetric analysis and compared. MRI features were also analyzed and compared. The receiver operating characteristic (ROC) curve and logistic regression analysis were used to evaluate the diagnostic efficiency of different diffusion parameters and MRI features for distinguishing placental percreta.

resultsD* was an independent risk factor from DWI for predicting placenta percreta with sensitivity of 73% and specificity of 76%. Focal exophytic mass remained as independent risk factor from MRI features for predicting placenta percreta with sensitivity of 72.7% and specificity of 88.1%. When the two risk factors were combined together, the AUC was the highest, 0.880 (95% CI 0.8-0.96).

conclusionD* and focal exophytic mass were associated with placenta percreta. A combination of the 2 risk factors can be used to predict placenta percreta. CRITICAL RELEVANCE STATEMENT: A combination of D* and focal exophytic mass can be used to differentiate placenta percreta.

Indexed as

Diffusion kurtosis imagingDiffusion-weighted MRIIntravoxel incoherent motionPlacenta accreta spectrum disorders

Identifiers

PMID37222836
PMCPMC10209373
OpenAlexW4377940164

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.