ArticleFrontiers in oncology2020
Radiomics of Multiparametric MRI to Predict Biochemical Recurrence of Localized Prostate Cancer After Radiation Therapy.
Open access · goldAbstract read
In one paragraph
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 6% of its field
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
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 49 citations in OpenAlex.
- Magnetic Resonance Imaging-Based Artificial Intelligence in Predicting Prostate Cancer Biochemical Recurrence: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Radiomics in prostate cancer imaging for a personalized treatment approach - current aspects of methodology and a systematic review on validated studies.Theranostics · 2021Pooled it
- MRI-guided focal boost to dominant intraprostatic lesion using volumetric modulated arc therapy in prostate cancer. Results of a phase II trial.The British journal of radiology · 2022Trial
- Evaluating Risk Factors Associating With Late Recurrence After Low-Dose-Rate Brachytherapy for Prostate Cancer Using Machine Learning.The Prostate · 2026Article
- Development and Validation of a Multimodal AI-Based Model for Predicting Post-Prostatectomy Treatment Outcomes from Baseline Biparametric Prostate MRI.medRxiv : the preprint server for health sciences · 2026Article
- An AI-Based Radiomics Model Using MRI ADC Maps for Accurate Prediction of Advanced Prostate Cancer Progression.Current oncology (Toronto, Ont.) · 2026Article
- Integrating biparametric MRI radiomics with clinical variables improves pre-treatment prediction of prostate cancer recurrence.Frontiers in oncology · 2026Article
- Computed Tomography-Based Radiomics Prediction of Biochemical Failure and Distant Metastasis in Patients With High- and Very High-Risk Localized Prostate Cancer.Advances in radiation oncology · 2025Article
- Next-Generation Advances in Prostate Cancer Imaging and Artificial Intelligence Applications.Journal of imaging · 2025Review
- MRMS-CNNFormer: A Novel Framework for Predicting the Biochemical Recurrence of Prostate Cancer on Multi-Sequence MRI.Bioengineering (Basel, Switzerland) · 2025Article
- Prediction of bone metastasis of prostate cancer based on intratumoral and peritumoral radiomics of MRI T2WI combined with ADC images.Frontiers in oncology · 2025Article
- Investigation of radiomics models for predicting biochemical recurrence of advanced prostate cancer on pretreatment MR ADC maps based on automatic image segmentation.Journal of applied clinical medical physics · 2024Article
- Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.Frontiers in oncology · 2024Article
- Robustness of magnetic resonance imaging and positron emission tomography radiomic features in prostate cancer: Impact on recurrence prediction after radiation therapy.Physics and imaging in radiation oncology · 2024Article
- Computed Tomography-Based Radiomics for Long-Term Prognostication of High-Risk Localized Prostate Cancer Patients Received Whole Pelvic Radiotherapy.Journal of personalized medicine · 2023Article
- T2-Weighted MRI Radiomic Features Predict Prostate Cancer Presence and Eventual Biochemical Recurrence.Cancers · 2023Article
- MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer.Journal of Zhejiang University. Science. B · 2023Review
- Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy.European journal of nuclear medicine and molecular imaging · 2023Article
- What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?Military Medical Research · 2023Review
- An artificial neural network-based radiomics model for predicting the radiotherapy response of advanced esophageal squamous cell carcinoma patients: a multicenter study.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 4 institutions in 2 countries.
Qiu-Zi ZhongDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Liu-Hua LongKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education / Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China.
An LiuDepartment of Radiation Oncology, City of Hope Medical Center, Duarte, CA, United States.
Chun-Mei LiDepartment of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China.
Xia XiuDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Xiu-Yu HouDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Qin-Hong WuDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Hong GaoDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Yong-Gang XuDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Ting ZhaoDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Dan WangDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Hai-Lei LinDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Xiang-Yan ShaDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Wei-Hu WangKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education / Beijing), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China.
Min ChenDepartment of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China.
Gao-Feng LiDepartment of Radiation Oncology, National Center of Gerontology, Beijing Hospital, Beijing, China.
Beijing Hospital · CNCity Of Hope National Medical Center · USPeking University · CNPeking University Cancer Hospital · CN
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
imagingprognosisprostate neoplasmradiomicsradiotherapy
Identifiers
What OpenQuestion holds
Textmetadata
LicenceCC BY
Read underepoch 390
Registered trials
None linked
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.