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ArticleEuropean radiology experimental2021

Material decomposition using iodine quantification on spectral CT for characterising nodules in the cirrhotic liver: a retrospective study.

Shalini Thapar Laroia, Komal Yadav, Senthil Kumar, Archana Rastogi, Guresh Kumar, Shiv Kumar Sarin

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In one paragraph

Article in European radiology experimental, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 47% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 1 institution in 1 country.

Shalini Thapar LaroiaDepartment of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India. thaparshalini@gmail.com.ORCID 0000-0002-2459-7927
Komal YadavDepartment of Radiology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
Senthil KumarDepartment of HPB Surgery and Liver Transplantation, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
Archana RastogiDepartment of Clinical and Hepato-pathology, Institute of Liver and Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
Guresh KumarDepartment of Biostatistics and Research, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110070, India.
Shiv Kumar SarinDepartment of Hepatology, Institute of Liver & Biliary Sciences, Sector D-1, Vasant Kunj, New Delhi, 110 070, India.
Institute of Liver and Biliary Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is limited scientific evidence on the potential of spectral computed tomography (SCT) for differentiation of nodules in the cirrhotic liver. We aimed to assess SCT-generated material density (MD) parameters for nodule characterisation in cirrhosis.

methodsDynamic dual-energy SCT scans of cirrhotic patients performed over 3 years were retrospectively reviewed. They were classified as hepatocellular carcinoma (HCC), regenerative or indeterminate, according to the European Association for the Study of the Liver criteria. MD maps were generated to calculate the area under the curve (AUC) and cutoff values to discriminate these nodules in the hepatic arterial phase (HAP) and portal venous phase (PVP). MD maps included iodine concentration density (ICD) of the liver and nodule, lesion-to-normal liver ICD ratio (LNR) and difference in nodule ICD between HAP and PVP.

resultsThree hundred thirty nodules belonging to 300 patients (age 53.0 ± 12.7 years, mean ± standard deviation) were analysed at SCT (size 2.3 ± 0.8 cm, mean ± SD). One hundred thirty-three (40.3%) nodules were classified as HCC, 147 (44.5%) as regenerative and 50 (15.2%) as indeterminate. On histopathology, 136 (41.2%) nodules were classified as HCC, 183 (55.5%) as regenerative and 11 (3.3%) as dysplastic. All MD parameters on HAP and the nodule  difference in ICD could discriminate pathologically proven HCC or potentially malignant nodules from regenerative nodules (p < 0.001). The AUC was 82.4% with a cutoff > 15.5 mg/mL for nodule ICD, 81.3% > 1.8 for LNR-HAP and 81.3% for difference in ICD > 3.5 mg/mL.

conclusionSCT-generated MD parameters are viable diagnostic tools for differentiating malignant or potentially malignant from benign nodules in the cirrhotic liver.

Indexed as

Carcinoma, HepatocellularIodineLiver NeoplasmsAdultAgedContrast MediaHumansLiver CirrhosisMiddle AgedRetrospective StudiesTomography, X-Ray ComputedContrast MediaIodineCarcinoma (hepatocellular)computed)IodineLiver cirrhosisLiver neoplasmsTomography (x-ray

Identifiers

PMID34046753
PMCPMC8160046
OpenAlexW3164869738

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LicenceCC BY
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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.