ArticleInsights into imaging2025
Repeatability and prognostic value of radiomic features: a study in esophageal cancer and nasopharyngeal carcinoma.
Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Deep learning-based CT slice synthesis improves radiomic feature reproducibility and discriminative performance in lung nodule assessment.Insights into imaging · 2026Article
- Targeting radiotherapy-induced inflammation in cancer metastasis: insights into immune modulation, therapeutic opportunities and radiogenomics.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
objectivesTo investigate whether radiomic features (RFs) repeatability and their prognostic value are study-specific. MATERIALS AND
methodsThis retrospective study included 234 esophageal cancer (EC) patients (contrast-enhanced computed tomography (CECT) and fluorine-18 fluorodeoxyglucose positron emission tomography (PET)), and 525 nasopharyngeal carcinoma (NPC) patients (CECT). Tumor, peritumor, and lymph node regions were defined as regions of interest. RF repeatability was assessed via perturbation analysis using intraclass correlation coefficients (ICC), with consistency and differences across cancer types, pathological regions, and modalities evaluated. The independent prognostic features common to both EC and NPC were screened from highly repeatable features using C-index and redundancy analysis.
resultsCT-based RFs in NPC and PET-based RFs in EC demonstrated significantly higher repeatability compared to CT-based RFs in EC (median ICC: 0.886 vs 0.806; 0.897 vs 0.806; p < 0.05). While CT-based peritumoral features showed comparable repeatability to tumor features in EC (0.824 vs 0.806, p > 0.05), PET-based peritumoral features exhibited significantly lower repeatability than tumor features (0.819 vs 0.897, p < 0.05). CT-based lymph node features demonstrated significantly lower repeatability than tumor features in NPC (0.863 vs 0.886, p < 0.05). Nevertheless, the effects of bin count, feature class, and filter on repeatability demonstrated consistent patterns across different cancer types, imaging modalities, and pathological regions. Moreover, four common independent prognostic features effectively stratified both EC and NPC patients into high- and low-risk groups with significant survival differences (p < 0.05).
conclusionsRF repeatability might be affected by cancer type, pathological region, and imaging modality, while certain features maintain consistent prognostic performance across different cancer types. CRITICAL RELEVANCE STATEMENT: The identification of high-repeatable pan-cancer prognostic radiomics features enables noninvasive patient risk stratification to guide personalized therapy, with cross-cancer consistency enhancing their applicability and convenience in clinical practice, thereby accelerating the integration of radiomics into precision oncology clinical workflows. KEY POINTS: This study examined RF repeatability and prognostic value specificity. RF repeatability varies across cancer types, regions, and modalities. The common highly repeatable RFs advance pan-cancer biomarker precision oncology.
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.