ArticleScientific reports2018
Automatic Detection of Prostate Tumor Habitats using Diffusion MRI.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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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.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- HRS Improves Active Surveillance for Prostate Cancer by Timely Identification of Progression.Academic radiology · 2025Trial
- Repeatability of an MRI protocol for generating habitats based on cellularity, perfusion, and hypoxia in a murine model of glioma.Magnetic resonance imaging · 2026Article
- mpMRI-Based Risk Estimation to Optimize Prostate Cancer Patient Selection for Active Surveillance.Cancers · 2026Article
- Article
- Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning.Cancers · 2022Article
- Prostate cancer GTV delineation with biparametric MRI andThe British journal of radiology · 2021Article
- A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors.Cancers · 2020Article
- Radiomics Improves Cancer Screening and Early Detection.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Review
- The role of radiomics in prostate cancer radiotherapy.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2020Review
- Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
A procedure for identification of optimal Apparent Diffusion Coefficient (ADC) thresholds for automatic delineation of prostatic lesions with restricted diffusion at differing risk for cancer was developed. The relationship between the size of the identified Volumes of Interest (VOIs) and Gleason Score (GS) was evaluated. Patients with multiparametric (mp)MRI, acquired prior to radical prostatectomy (RP) (n = 18), mpMRI-ultrasound fused (MRI-US) (n = 21) or template biopsies (n = 139) were analyzed. A search algorithm, spanning ADC thresholds in 50 µm
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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.