ArticleCureus2022
The Role of Computed Tomography Perfusion in Various Focal Liver Lesions.
Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Lower diffusion-derived vessel density (DDVD) measure of liver focal nodular hyperplasia than those of hepatocellular carcinoma and liver metastasis allows potential differential diagnosis: quantitative and semi-quantitative analyses of two-center data.Journal of gastrointestinal oncology · 2025Article
- Evaluating the role of quantitative computed tomography perfusion parameters in differentiating hepatocellular carcinoma from other hepatic neoplasms.Abdominal radiology (New York) · 2025Article
- Influences of the second motion probing gradientQuantitative imaging in medicine and surgery · 2025Article
- Underestimation of liver hemangioma perfusion fraction by standard intravoxel incoherent motion diffusion magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background This study aims to identify the potential advantages of quantitative determination of various focal liver pathologies, identify lesion hemodynamics, and distinguish benign and malignant pathologies based on CT perfusion (CTP) parameters. Methodology In this study, we examined 36 patients using contrast-enhanced CT (CECT) and proposed inclusion and exclusion criteria. Of the 36 patients, 18 had malignant lesions and 14 had benign lesions. CTP was performed on patients comprising cases of hepatocellular carcinoma (HCC), metastasis, hemangiomas, hepatic cysts, and hepatic abscess. Images were post-processed and analyzed to calculate various perfusion parameters such as blood flow (BF), blood volume (BV), permeability surface (PS), mean transit time (MTT), the hepatic arterial fraction (HAF), and induced residue fraction time of onset (IRFTO). Parameters were compared between benign and malignant lesions, and descriptive analysis was performed for individual lesions. Results Data were analyzed with IBM SPSS Statistics (IBM Corp., Armonk, NY, USA). IRFTO showed the area of the curve (AOC) = 0.659,
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.