ArticleBMC medical imaging2025
Development and validation of a nomogram for diabetic tibial neuropathy based on ultrasound radiomics: a multicenter study.
Article in BMC medical 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.
- Radiomics Applied to the Diagnosis of Peripheral Nerve Disorders: A Systematic Review and Meta-Analysis of the Existing Literature.Journal of clinical medicine · 2026Review
- CT-based intratumoral habitat and peritumoral radiomics model to predict spread through air spaces in solid lung adenocarcinoma with diameter ≤ 2 cm: a dual-center study.Frontiers in oncology · 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
Abstract
objectiveDiabetic tibial nerve neuropathy (DTN), a severe subtype of diabetic peripheral neuropathy, is often underdiagnosed in the early stages. This significantly raises the risks of foot ulcers and amputations. This study aims to develop and validate a novel nomogram prediction model integrating clinical characteristics and ultrasound radiomics features for early identification of DTN patients.
methodsFrom January 2024 to April 2025, 300 patients with type 2 diabetes who visited the Second Affiliated Hospital of Fujian Medical University were prospectively collected and randomly divided into training and validation cohorts at a ratio of 7:3. The study collected 134 patients from two other tertiary hospitals as the external validation set. The differences among the three cohorts were evaluated by single-factor ANOVA analysis of variance or χ² test. Tibial nerve ultrasound cross-sectional images were analyzed to extract radiomics features. Optimal features were selected using t-tests and least absolute shrinkage and selection operator (LASSO) regression, generating a weighted ultrasound radiomics score (Rad-score). A nomogram integrating clinical variables and Rad-score was developed through univariate and multivariate logistic regression. Performance was evaluated using AUC, calibration curves, decision/clinical impact curves.
resultsThe nomogram incorporated three clinical variables (age, smoking history, and hypertension history) and Rad-score derived from seven optimal ultrasound radiomics features. The model demonstrated AUCs of 0.947 (training set), 0.910 (internal validation set) and 0.887 (external validation set). Calibration and decision curves indicated strong consistency and clinical utility.
conclusionThe clinical-ultrasound radiomics nomogram effectively predicts DTN risk, potentially serving as a reference tool for early diagnosis.
Indexed as
Identifiers
What Socratic 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 Socratic graph.