Evidence map›Paper›PMID 37064354›Full record

ArticleQuantitative imaging in medicine and surgery2023

Value of susceptibility-weighted imaging in differentiating benign from malignant portal vein thrombosis.

Chengling Huang, Xixi Xiao, Man Guo, Xianling Hu, Chen Liu, Jian Wang, Huarong Zhang, Xiaoming Li, Ping Cai

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2023. 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
–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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chengling Huang *Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xixi Xiao *Department of Oncology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Man GuoDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xianling HuCommunication Sergeant School, Army Engineering University of PLA, Chongqing, China.
Chen LiuDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Jian WangDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Huarong ZhangInstitute of Pathology and Southwest Cancer Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xiaoming LiDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Ping CaiDepartment of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Many diseases are accompanied by portal vein thrombosis (PVT), and its nature is closely related to its prognosis and treatment. It is important to evaluate magnetic resonance imaging (MRI) parameters, including susceptibility-weighted imaging (SWI) and qualitative diffusion-weighted imaging (DWI), in the differentiation between benign and malignant PVT. Methods: In this retrospective study, we collected clinical imaging data from 140 patients with PVTs characterized as benign or malignant based on enhanced MRI between January 2011 and April 2016 and retrospectively analyzed PVTs using SWI and DWI. There were 37 benign and 103 malignant PVTs. Image review was performed by 2 radiologists blinded to clinical information. The signal intensity (SI) of PVTs was recorded on SWI. The apparent diffusion coefficient (ADC) and the ratio of signal intensity (SIR) on SWI (SIR Results: On SWI and DWI, 100.0% (36/36) and 80.5% (29/36) of benign PVTs were hypointense, respectively. For malignant PVTs on SWI and DWI, 99.0% (103/104) and 89.4% (93/104) were hyperintense, respectively. The SIR Conclusions: The diagnostic performance of SWI is superior to that of DWI in the differentiation of benign and malignant PVTs.

Indexed as

Benigndiffusion-weighted imaging (DWI)malignantportal vein thrombosis (PVT)susceptibility-weighted imaging (SWI)

Identifiers

PMID37064354
PMCPMC10102778

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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.