Evidence map›Paper›PMID 40626028›Full record

ArticlePolish journal of radiology2025

Differentiation of solid and cystic small renal masses: the role of multiphase CT markers in predicting malignant histology, subtype, and grade.

Yulian Mytsyk

Abstract read
In one paragraph

Article in Polish journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Yulian MytsykVoxel Medical Diagnostic Centre, Katowice, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to assess the diagnostic performance of multiphase contrast-enhanced computed tomography (MCECT) in differentiating benign and malignant solid and cystic small renal masses (SRMs), predicting histologic subtypes, and grading, using signal intensity (SI) and tumour-to-cortex signal intensity (TCSI) ratio. Material and methods: A retrospective analysis was conducted on 181 patients with solid and cystic SRMs (≤ 4 cm). MCECT imaging across 4 phases (non-contrast, corticomedullary, nephrographic, and excretory) was performed. SI and TCSI values were measured, and their diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis. Solid, Bosniak IIF, III, and IV SRMs underwent histopathological confirmation. Results: Among solid SRMs, excretory phase SI achieved an area under the curve (AUC) of 0.848 for differentiating RCC from other SRMs, with 100% sensitivity and 61.3% specificity. For distinguishing renal cell carcinoma (RCC) from benign SRMs, the most effective parameter was the TCSI ratio obtained from computed tomography excretory phase (88.6% sensitivity, 52.4% specificity, 0.763 AUC). For Bosniak IIF cysts, the corticomedullary phase SI provided an AUC of 0.902, with 93% sensitivity and 87.5% specificity. RCC subtyping showed distinct SI characteristics across phases, particularly for clear cell RCC. Nephrographic phase SI differentiated low- versus high-grade RCC, with an AUC of 0.901, 90.2% sensitivity, and 86.4% specificity. Conclusions: MCECT-derived imaging biomarkers, particularly SI and TCSI, are effective non-invasive tools for characterising SRMs, aiding in the differentiation of benign and malignant lesions, histological subtypes, and tumour grades. Their integration with advanced radiomics could further enhance diagnostic accuracy.

Indexed as

imaging markermultiphase contrast-enhanced CTradiomicsrenal cell carcinomasmall renal massestumour-to-cortex signal intensity ratio

Identifiers

PMID40626028
PMCPMC12232405

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.