ArticleFrontiers in oncology2025
Prediction of bone metastasis of prostate cancer based on intratumoral and peritumoral radiomics of MRI T2WI combined with ADC images.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- An interpretable biparametric MRI habitat radiomics model for predicting bone metastasis in prostate cancer: a dual-center study.Translational andrology and urology · 2026Article
- Development and validation of an MRI radiomics-based model for predicting progression risk in prostate cancer after endocrine therapy.Translational andrology and urology · 2026Article
- A multimodal fusion model integrating Vision Transformer, radiomics, and clinical features for predicting bone metastasis in prostate cancer.Frontiers in oncology · 2026Article
- Dual-region deep learning model integrating prostate and peri-prostatic adipose tissue MRI features for bone metastasis prediction in prostate cancer.Frontiers in oncology · 2026Article
- Diagnostic value of whole-tumor ADC histogram parameters combined with ISUP grade and MRI-EPE score for predicting extracapsular extension in PI-RADS 4-5 prostate cancer.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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To investigate the value of intratumoral and peritumoral MRI radiomic models in predicting bone metastasis of prostate cancer patients using T2WI combined with ADC images. Materials and method: A total of 144 patients with prostate cancer who underwent preoperative MRI (T2WI and DWI) were retrospectively included. All patients were categorized into two groups based on the presence of bone metastasis. The radiomics features were calculatd for the entire tumor and 3mm-peritumoral components on pre-processed T2WI combined with ADC images. The radiomics models based on intratumoral features, peritumoral features as well as their merged features were respectively constructed. The independent risk factors of bone metastasis of prostate cancer were used to constructed clinical prediction model. The performance of the clincal model, radiomics models and clinic-imaging combined models was evaluated by the receiver operating characteristic curve and compared with the bootstrap methods. T-test was used to compare the evaluation indicators of different prediction models. Results: The clinic-imaging combined model had the best predictive efficacy among all models. The area under the curve (AUC) of the clinic-imaging combined model for predicting bone metastasis of prostate cancer in the training dataset and test dataset were 0.937 and 0.893, respectively. The accuracy, sensitivity and specificity of this model in predicting bone metastasis of prostate cancer in the training dataset were 84.2%, 91.2% and 80.6%, respectively; the accuracy, sensitivity and specificity of the testing dataset were 76.7%, 73.3% and 78.6%, respectively. Conclusions: T2WI and ADC intratumoral and peritumoral radiomic models can be used to noninvasively predict the primary diagnosis of PCa BM, and peritumoral radiomic model can add independent predictive value. And the clinic-imaging combined model has the better predictive value.
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.