ReviewAbdominal radiology (New York)2022
Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques.
Review in Abdominal radiology (New York), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 21 citations in OpenAlex.
- Randomized trial of biopsy needle sandblasting in coaxial core-needle liver biopsy: no significant improvement in ultrasound visibility, pain, or tissue yield.Abdominal radiology (New York) · 2026Trial
- Mapping fibrosis in colorectal liver metastases (CRLM) with gadobenate dimeglumine-enhanced MRI: prognostic implications and imaging biomarkers.International journal of colorectal disease · 2026Article
- Radiomics-based automated machine learning for differentiating focal liver lesions on unenhanced computed tomography.Abdominal radiology (New York) · 2025Article
- Fully Automated and Explainable Measurement of Liver Surface Nodularity in CT: Utility for Staging Hepatic Fibrosis.Academic radiology · 2025Article
- Revolutionising portal hypertension diagnosis: the rise of non-invasive techniques in liver cirrhosis.Frontiers in medicine · 2025Review
- Progress and prospects of elastography techniques in the evaluation of fibrosis in chronic liver disease.Archives of medical science : AMS · 2024Article
- Tungsten-based nanoparticles as contrast agents for liver tumor detection using dual-energy computed tomography.Biomaterials science · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver fibrosis features excessive protein accumulation in the liver interstitial space resulting from repeated tissue injury due to chronic liver disease. Liver fibrosis eventually proceeds to cirrhosis and associated complications. So, early diagnosis and staging of liver fibrosis are of vital importance for clinical treatment. Liver biopsy remains the gold standard for the diagnosing and staging of fibrosis, but it is suboptimal due to various limitations. Recently, efforts have been made to migrate toward noninvasive techniques for assessing liver fibrosis. CT is relatively easy to perform, relatively standardized for different scanners, and does not require additional hardware in liver fibrosis staging. MRI is frequently performed to characterize indeterminate liver lesions. Because it does not use ionizing radiation and features high image contrast, its role has increased in the staging of liver fibrosis. More recently, several studies on liver fibrosis staging using deep learning algorithms in CT or MRI have been proposed and have shown meaningful results. In this review, we summarize the basic concept, diagnostic performance, and advantages and limitations of each technique to noninvasively stage liver fibrosis.
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Registered trials
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 Socratic graph.