Evidence map›Paper›PMID 38461432›Full record

ArticleAbdominal radiology (New York)2024

Intravoxel incoherent motion assessment of liver fibrosis staging in MASLD.

Hao Ren, Hui Xu, Dawei Yang, Xiaofei Tong, Xinyan Zhao, Qianyi Wang, Yameng Sun, Xiaojuan Ou, Jidong Jia, Hong You and 2 more

Abstract read
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In one paragraph

Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. [Advances and challenges in new technologies for imaging evaluation of liver fibrosis].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025
    Review
  6. Review
  7. Article
  8. 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

12 authors.

Hao RenDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Hui XuDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Dawei YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Xiaofei TongLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Xinyan ZhaoLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Qianyi WangLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Yameng SunLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Xiaojuan OuLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Jidong JiaLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Hong YouLiver Research Center, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, West District, Beijing, 100050, China.
Zhenchang WangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China.
Zhenghan YangDepartment of Radiology, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing, 100050, China. yangzhenghan@vip.163.com.ORCID http://orcid.org/0000-0003-3986-1732

Funding

Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support ZYLX202101Beijing Natural Science Foundation No.7184199Capital's Funds for Health Improvement and Research No.2018-2-2023National Natural Science Foundation of China 62171298National Natural Science Foundation of China 82071876National Natural Science Foundation of China No. 61871276
6 · The paper itself

Abstract

purposePartial correlation analysis was performed to account for the interference of steatosis changes and inflammatory factors, to determine the true correlation between fibrosis and IVIM parameters (Dfast, Dslow, and F), and to evaluate the diagnostic efficacy of IVIM for liver fibrosis.

methodsA total of 106 patients with metabolic dysfunction-associated steatotic liver disease (MASLD) examined by IVIM from November 2016 to November 2023 at our hospital were retrospectively included. Preliminary analysis of each IVIM parameter and correlations with pathological findings were performed using Spearman correlation analysis, and partial correlation analysis was used to exclude the interference of other pathological factors, thus yielding the true correlations between IVIM parameters (Dfast, Dslow, and F) and pathology. The diagnostic efficacy of IVIM parameters for diagnosing MASLD was assessed via receiver operating characteristic (ROC) curve analysis.

resultsSpearman correlation analysis of all the IVIM parameters revealed correlations with steatosis, lobular inflammation, and ballooning. Partial correlation analysis indicated that Dfast was correlated with the pathological fibrosis stage (r = - 0.593, P < 0.001), Dslow was correlated with the pathological steatosis score (r = - 0.313, P < 0.05), and F was correlated with the pathological fibrosis stage and steatosis score (r = - 0.456 and 0.255, P < 0.001 and P < 0.05). In the diagnosis of hepatic fibrosis, significant hepatic fibrosis, advanced liver fibrosis and cirrhosis, Dfast achieved areas under the ROC curve of 0.763, 0.801, 0.853, and 0.897, respectively. The threshold values for diagnosing different fibrosis stages using Dfast (10

conclusionAccording to our partial correlation analysis, there was a moderate correlation between Dfast and F according to fibrosis stage, and Dfast was not influenced by inflammation or steatosis when diagnosing fibrosis in MASLD patients. A relatively close Dfast threshold is insufficient for accurately and noninvasively assessing various stages of MASLD fibrosis. In clinical practice, this approach can be considered an alternative method for the preliminary assessment of fibrosis in MASLD patients.

Indexed as

Liver CirrhosisAdultAgedFatty LiverFemaleHumansLiverMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesIVIMLiver fibrosisMASLD

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Registered trials

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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.