Evidence map›Paper›PMID 30809719›Full record

ArticleEuropean radiology2019

Longitudinal evolution of CT and MRI LI-RADS v2014 category 1, 2, 3, and 4 observations.

Cheng William Hong, Charlie C Park, Adrija Mamidipalli, Jonathan C Hooker, Soudabeh Fazeli Dehkordy, Saya Igarashi, Mohanad Alhumayed, Yuko Kono, Rohit Loomba, Tanya Wolfson and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Risk of Hepatocellular Carcinoma in Patients With Indeterminate (LI-RADS 3) Liver Observations.Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2023
    Article
  7. Article
  8. [Research progress of LI-RADS categories and imaging features in predicting the prognosis of liver tumors].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022
    Review
  9. [Radiologic Diagnosis of Hepatocellular Carcinoma].The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2021
    Review
  10. 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

13 authors.

Cheng William HongLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.ORCID http://orcid.org/0000-0002-5219-6039
Charlie C ParkSchool of Medicine, University of California San Diego, San Diego, CA, USA.
Adrija MamidipalliLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Jonathan C HookerLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Soudabeh Fazeli DehkordyLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Saya IgarashiLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Mohanad AlhumayedLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Yuko KonoComputational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA.
Rohit LoombaComputational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA.
Tanya WolfsonDivision of Gastroenterology, Department of Medicine, University of California San Diego, San Diego, CA, USA.
Anthony GamstDivision of Gastroenterology, Department of Medicine, University of California San Diego, San Diego, CA, USA.
Paul MurphyLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA.
Claude B SirlinLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA, USA. csirlin@ucsd.edu.

Funding

Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
NIBIB NIH HHS T32 EB005970NIBIB NIH HHS T32 EB005970-09
6 · The paper itself

Abstract

objectivesThis study assesses the risk of progression of Liver Imaging Reporting and Data System (LI-RADS) categories, and the effects of inter-exam changes in modality or radiologist on LI-RADS categorization.

methodsClinical LI-RADS v2014 CT and MRI exams at our institution between January 2014 and September 2017 were retrospectively identified. Untreated LR-1, LR-2, LR-3, and LR-4 observations with at least one follow-up exam were included. Three hundred and seventy-two observations in 214 patients (149 male, 65 female, mean age 61 ± 10 years) were included during the study period (715 exams total). Cumulative incidence curves for progression to malignant LI-RADS categories (LR-5 or LR-M) and to LR-4 or higher were generated for each index category and compared using log-rank tests with a resampling extension. Relationships between inter-exam changes in LI-RADS category and modality or radiologist, adjusted for inter-exam time intervals, were modeled using mixed effect logistic regressions.

resultsMedian inter-exam follow-up interval and total follow-up duration were 123 and 227 days, respectively. Index LR-1, LR-2, LR-3, and LR-4 differed significantly in their cumulative incidences of progression to malignant categories (p < 0.0001), which were 0%, 2%, 7%, and 32% at 6 months, respectively. Index LR-1, LR-2, and LR-3 differed significantly in cumulative incidences of progression to LR-4 or higher (p = 0.003). MRI-MRI exam pairs had more stable LI-RADS categorization compared to CT-CT (OR = 0.460, p = 0.0018).

conclusionsLI-RADS observations demonstrate increasing risk of progression to malignancy with increasing category ranging from 0% for LR-1 to 32% for LR-4 at 6 months. Inter-exam modality changes are associated with LI-RADS category changes. KEY POINTS: • While the majority of LR-2 observations remain stable over long-term follow-up, LR-3 and especially LR-4 observations have a higher risk for category progression. • Category transitions between sequential exams using different modalities (CT vs. MRI) may reflect modality differences rather than biological change. MRI, especially with the same type of contrast agent, may provide the most reproducible categorization, although this needs additional validation. • In a clinical practice setting, in which radiologists refer to prior imaging and reports, there was no significant association between changes in radiologist and changes in LI-RADS categorization.

Indexed as

Carcinoma, HepatocellularDisease ProgressionFemaleHumansLiverLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedMultidetector Computed TomographyRetrospective StudiesROC CurveHepatic neoplasmsHepatocellular carcinomaLiverLongitudinal studiesObserver variation

Identifiers

PMID30809719
PMCPMC7495398

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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.