Evidence map›Paper›PMID 35697856›Full record

ArticleAbdominal radiology (New York)2022

Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics.

Taek Min Kim, Hyungwoo Ahn, Hyo Jeong Lee, Min Gwan Kim, Jeong Yeon Cho, Sung Il Hwang, Sang Youn Kim

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Article in Abdominal radiology (New York), 2022. 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
1.7field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Taek Min Kim *Department of Radiology, Seoul National University Hospital, Seoul, Korea.
Hyungwoo Ahn *Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
Hyo Jeong LeeDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.
Min Gwan KimDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.
Jeong Yeon ChoDepartment of Radiology, Seoul National University Hospital, Seoul, Korea.
Sung Il HwangDepartment of Radiology, Seoul National University College of Medicine, Seoul, Korea.
Sang Youn KimDepartment of Radiology, Seoul National University Hospital, Seoul, Korea. iwishluv@empas.com.
Seoul National University Hospital · KRSeoul National University · KRSeoul National University Bundang Hospital · KRThe Seoul Institute · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aims to assess the computed tomography (CT) findings of renal epithelioid angiomyolipoma (EAML) and develop a radiomics-based model for differentiating EAMLs and clear cell renal cell carcinomas (RCCs).

methodThis two-center retrospective study included 28 histologically confirmed EAMLs and 56 size-matched clear cell RCCs with preoperative three-phase kidney CTs. We conducted subjective image analysis to determine the CT parameters that can distinguish EAMLs from clear cell RCCs. Training and test sets were divided by chronological order of CT scans, and radiomics model was built using ten selected features among radiomics and CT features. The diagnostic performance of the radiomics model was compared with that of the three radiologists using the area under the receiver-operating characteristic curve (AUC).

resultsThe mean size of the EAMLs was 6.2 ± 5.0 cm. On multivariate analysis, a snowman or ice cream cone tumor shape (OR 16.3; 95% CI 1.7-156.9, P = 0.02) and lower tumor-to-cortex (TOC) enhancement ratio in the corticomedullary phase (OR 33.4; 95% CI 5.7-197, P < 0.001) were significant independent factors for identifying EAMLs. The diagnostic performance of the radiomics model (AUC 0.89) was similar to those of genitourinary radiologists (AUC 0.78 and 0.81, P > 0.05) and superior to that of a third-year resident (AUC 0.63, P = 0.04).

conclusionsA snowman or ice cream cone shape and lower TOC ratio were more closely associated with EAMLs than with clear cell RCCs. A CT radiomics model was useful for differentiating EAMLs from clear cell RCCs with better diagnostic performance than an inexperienced radiologist.

Indexed as

Adenocarcinoma, Clear CellAngiomyolipomaCarcinoma, Renal CellHamartomaKidney NeoplasmsDiagnosis, DifferentialHumansRetrospective StudiesTomography, X-Ray ComputedAngiomyolipomaClear cell renal cell carcinomaComputed tomographyEpithelioid angiomyolipomaPerivascular epithelioid cell neoplasmRadiomics

Identifiers

PMID35697856
OpenAlexW4282565315

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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.