ArticleQuantitative imaging in medicine and surgery2025
Preliminary study on the ability of
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Radiomics-Based AI for the Diagnosis and Prognosis of Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- The diagnostic accuracy of imaging methods in preoperative prediction of vessels encapsulating tumor clusters in hepatocellular carcinoma in East Asian populations: a systematic review and meta-analysis.Quantitative imaging in medicine and surgery · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Recently, a novel vascular pattern characterized by vessels encapsulating tumor clusters (VETC) was reported to be related to poor clinical outcomes in patients with hepatocellular carcinoma (HCC). The objective of this study was to preliminarily assess the ability of metabolic parameters and radiomics features derived from Methods: A total of 149 patients diagnosed with HCC from two institutions (The Third Affiliated Hospital of Sun Yat-sen University and Sun Yat-sen Memorial Hospital) were retrospectively enrolled and subsequently divided into a training cohort (n=103) and a test cohort (n=46) as external validation. The correlation between traditional image features on computed tomography (CT)/magnetic resonance imaging (MRI) and Results: The difference in FDG parameter TLR between VETC-positive and VETC-negative HCC was found to be statistically significant (P<0.05), which was consistent with traditional CT/MRI imaging features. The Radscore was derived by calculating 13 selected radiomics features, comprising of six PET radiomics features and seven CT radiomics features. The nomogram model exhibited an area under the curve (AUC) of 0.908 [95% confidence interval (CI): 0.852-0.963; sensitivity: 0.855; specificity: 0.833] and 0.762 (95% CI: 0.624-0.900; sensitivity: 0.739; specificity: 0.739) in the training and test cohort, respectively. The disparity in the prediction of VETC status based on the nomogram model between DFS and OS was statistically comparable to that observed between VETC-positive and VETC-negative cases through pathological analysis (P<0.05). Conclusions: FDG metabolism is significantly associated with VETC status in HCC patients. A comprehensive nomogram model based on PET/CT radiomics and clinical indicators has potential for preoperative prediction of VETC as well as patient prognosis.
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.