Evidence map›Paper›PMID 28811845›Full record

ArticlePolish journal of radiology2017

Role of Contrast Enhancement and Corrected Attenuation Values of Renal Tumors in Predicting Renal Cell Carcinoma (RCC) Subtypes: Protocol for a Triphasic Multi-Slice Computed Tomography (CT) Procedure.

Ersen Ertekin, Akın Soner Amasyalı, Bulent Erol, Saim Acikgozoglu, Faruk Kucukdurmaz, Alaaddin Nayman, Haluk Erol

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Article in Polish journal of radiology, 2017. 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

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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.

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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.

Ersen ErtekinDepartment of Radiology, Adnan Menderes University, Faculty of Medicine, Aydın, Turkey.
Akın Soner AmasyalıDepartment of Urology, Adnan Menderes University, Faculty of Medicine, Aydın, Turkey.
Bulent ErolDepartment of Urology, Medeniyet University, School of Medicine, Istanbul, Turkey.
Saim AcikgozogluDepartment of Radiology, Necmettin Erbakan University, School of Medicine, Konya, Turkey.
Faruk KucukdurmazDepartment of Urology, Sutcu Imam University, School of Medicine, Kahramanmaras, Turkey.
Alaaddin NaymanDepartment of Radiology, Selcuk University, School of Medicine, Konya, Turkey.
Haluk ErolDepartment of Urology, Adnan Menderes University, Faculty of Medicine, Aydın, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo distinguish RCC subtypes based on contrast enhancement features of CT images. MATERIAL/

methodsIn total, 59 lesions from 57 patients were included. All patients underwent multi-slice CT imaging with a triphasic protocol, which included non-contrast, corticomedullary, nephrographic and urographic phases. Contrast enhancement features of renal masses were evaluated in terms of CT attenuation values (AV) and differences in contrast density; the aorta or renal parenchyma were evaluated based on corrected or relative values.

resultsClear cell RCC (ccRCC) showed more intense contrast enhancement than other RCC subtypes. When differentiating ccRCC from other RCC subtypes, a cut-off AV of 86-89 HU, aorta-based corrected AV of 89-95 HU and renal parenchyma-based corrected AV of 87-95 HU showed a diagnostic accuracy of 81-86%, 86-88% and 74-78%, respectively, in the corticomedullary phase. Furthermore, a cutoff of 2.42-2.72 for the relative contrast enhancement ratio, a cutoff of 2.59-2.74 for the aorta-based corrected relative contrast enhancement ratio and a cutoff of 2.63-2.76 for the renal parenchyma-based attenuation ratio showed a diagnostic accuracy of 83-88%, 88-90% and 81%, respectively.

conclusionsThe most reliable parameters for differentiating ccRCC from other RCC subtypes are aorta-based corrected AV and aorta-based corrected relative contrast enhancement values in the corticomedullary phase.

Indexed as

Carcinoma, Renal CellContrast MediaMultidetector Computed Tomography

Identifiers

PMID28811845
PMCPMC5530140

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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.