ArticleOncotarget2018
Predicting clinically significant prostate cancer using DCE-MRI habitat descriptors.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 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
14 citing papers in PubMed.
- Perioperative Complications and In-Hospital Mortality in Paraplegic Radical Cystectomy Patients.Annals of surgical oncology · 2025Article
- Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation.Cancer management and research · 2025Review
- Tumour habitat-based radiomics analysis enhances the ability to predict prostate cancer aggressiveness with biparametric MRI-derived features.Frontiers in oncology · 2025Article
- Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.International journal of molecular sciences · 2021Review
- Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data.Cancers · 2021Article
- Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images.Archives of gynecology and obstetrics · 2021Article
- Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature.Contrast media & molecular imaging · 2021Article
- A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors.Cancers · 2020Article
- Article
- Machine and deep learning methods for radiomics.Medical physics · 2020Review
- The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study.PloS one · 2019Article
- Mri-based cancer lesion analysis with 3d printed patient specific prostate cutting guides.American journal of clinical and experimental urology · 2019Article
- Quantitative DCE Dynamics on Transformed MR Imaging Discriminates Clinically Significant Prostate Cancer.Cancer control : journal of the Moffitt Cancer CenterArticle
- Radiomics in prostate cancer: an up-to-date review.Therapeutic advances in urologyReview
Corrections and comments
- Erratum issuedErratum: Predicting clinically significant prostate cancer using DCE-MRI habitat descriptors.2019 · Parra, Andres N [corrected to Parra, N Andres]
Authors and funding
15 authors.
Funding
Abstract
Prostate cancer diagnosis and treatment continues to be a major public health challenge. The heterogeneity of the disease is one of the major factors leading to imprecise diagnosis and suboptimal disease management. The improved resolution of functional multi-parametric magnetic resonance imaging (mpMRI) has shown promise to improve detection and characterization of the disease. Regions that subdivide the tumor based on Dynamic Contrast Enhancement (DCE) of mpMRI are referred to as
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.