Cargando…

Current Value of Biparametric Prostate MRI with Machine-Learning or Deep-Learning in the Detection, Grading, and Characterization of Prostate Cancer: A Systematic Review

Prostate cancer detection with magnetic resonance imaging is based on a standardized MRI-protocol according to the PI-RADS guidelines including morphologic imaging, diffusion weighted imaging, and perfusion. To facilitate data acquisition and analysis the contrast-enhanced perfusion is often omitted...

Descripción completa

Detalles Bibliográficos
Autores principales:	Michaely, Henrik J., Aringhieri, Giacomo, Cioni, Dania, Neri, Emanuele
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027206/ https://www.ncbi.nlm.nih.gov/pubmed/35453847 http://dx.doi.org/10.3390/diagnostics12040799

Ejemplares similares

Short review of biparametric prostate MRI
por: Steinkohl, Fabian, et al.
Publicado: (2018)

Biparametric versus multiparametric MRI in the diagnosis of prostate cancer
por: Thestrup, Karen Cecilie Duus, et al.
Publicado: (2016)

Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers
por: Cipollari, Stefano, et al.
Publicado: (2022)

A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics
por: Bleker, Jeroen, et al.
Publicado: (2022)

Semisupervised Learning with Report-guided Pseudo Labels for Deep Learning–based Prostate Cancer Detection Using Biparametric MRI
por: Bosma, Joeran S., et al.
Publicado: (2023)

Biparametric Quantitative MRI for Prostate Cancer Detection
por: Uyanik, Meltem, et al.
Publicado: (2023)

Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature
por: Zhang, Li, et al.
Publicado: (2021)

Assessment of the Diagnostic Accuracy of Biparametric Magnetic Resonance Imaging for Prostate Cancer in Biopsy-Naive Men: The Biparametric MRI for Detection of Prostate Cancer (BIDOC) Study
por: Boesen, Lars, et al.
Publicado: (2018)

Comparison of biparametric and multiparametric MRI in the diagnosis of prostate cancer
por: Xu, Lili, et al.
Publicado: (2019)

Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis
por: Belue, Mason James, et al.
Publicado: (2022)

Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer?
por: Iacob, Roxana, et al.
Publicado: (2023)

AI-assisted biparametric MRI surveillance of prostate cancer: feasibility study
por: Roest, C., et al.
Publicado: (2022)

Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI
por: Hötker, Andreas M., et al.
Publicado: (2021)

Diagnostic value of integrated (18)F-PSMA-1007 PET/MRI compared with that of biparametric MRI for the detection of prostate cancer
por: Zeng, Yuping, et al.
Publicado: (2022)

Cancer Detection Rates of Systematic and Targeted Prostate Biopsies after Biparametric MRI
por: Gayet, Maudy C. W., et al.
Publicado: (2020)

Endometrial Cancer Staging: Is There Value in ADC?
por: Moreira, Ana Sofia Linhares, et al.
Publicado: (2023)

Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks
por: Lai, Chih-Ching, et al.
Publicado: (2021)

Added Value of Biparametric MRI and TRUS-Guided Systematic Biopsies to Clinical Parameters in Predicting Adverse Pathology in Prostate Cancer
por: Liu, Hailang, et al.
Publicado: (2020)

The Role of Radiomics in Salivary Gland Imaging: A Systematic Review and Radiomics Quality Assessment
por: Aringhieri, Giacomo, et al.
Publicado: (2022)

Head-to-head comparison of biparametric versus multiparametric MRI of the prostate before robot-assisted transperineal fusion prostate biopsy
por: Thaiss, Wolfgang M., et al.
Publicado: (2022)

Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities
por: Li, Huanye, et al.
Publicado: (2022)

A narrative review of biparametric MRI (bpMRI) implementation on screening, detection, and the overall accuracy for prostate cancer
por: Greenberg, Jacob W., et al.
Publicado: (2022)

Comparison of Sensitivity and Specificity of Biparametric versus Multiparametric Prostate MRI in the Detection of Prostate Cancer in 431 Men with Elevated Prostate-Specific Antigen Levels
por: Pesapane, Filippo, et al.
Publicado: (2021)

An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study
por: Hiremath, Amogh, et al.
Publicado: (2021)

Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI
por: Bertelli, Elena, et al.
Publicado: (2022)

Assessment of prostate cancer prognostic Gleason grade group using zonal‐specific features extracted from biparametric MRI using a KNN classifier
por: Jensen, Carina, et al.
Publicado: (2019)

Concordance between biparametric MRI, transperineal targeted plus systematic MRI-ultrasound fusion prostate biopsy, and radical prostatectomy pathology
por: Noh, Tae Il, et al.
Publicado: (2022)

Validation of IMPROD biparametric MRI in men with clinically suspected prostate cancer: A prospective multi-institutional trial
por: Jambor, Ivan, et al.
Publicado: (2019)

Outcomes of a Diagnostic Pathway for Prostate Cancer Based on Biparametric MRI and MRI-Targeted Biopsy Only in a Large Teaching Hospital
por: Paulino Pereira, Leonor J., et al.
Publicado: (2023)

Single-center versus multi-center biparametric MRI radiomics approach for clinically significant peripheral zone prostate cancer
por: Bleker, Jeroen, et al.
Publicado: (2021)

AutoProstate: Towards Automated Reporting of Prostate MRI for Prostate Cancer Assessment Using Deep Learning
por: Mehta, Pritesh, et al.
Publicado: (2021)

MRI Based Radiomics Compared With the PI-RADS V2.1 in the Prediction of Clinically Significant Prostate Cancer: Biparametric vs Multiparametric MRI
por: Chen, Tong, et al.
Publicado: (2022)

Added value of systematic biopsy in men with a clinical suspicion of prostate cancer undergoing biparametric MRI-targeted biopsy: multi-institutional external validation study
por: Falagario, Ugo, et al.
Publicado: (2020)

Cardiac Magnetic Resonance in Fabry Disease: Morphological, Functional, and Tissue Features
por: Aquaro, Giovanni Donato, et al.
Publicado: (2022)

Development and validation of a nomogram for predicting prostate cancer based on combining contrast-enhanced transrectal ultrasound and biparametric MRI imaging
por: Nong, Wanxian, et al.
Publicado: (2023)

Autonomous Detection and Classification of PI-RADS Lesions in an MRI Screening Population Incorporating Multicenter-Labeled Deep Learning and Biparametric Imaging: Proof of Concept
por: Winkel, David J., et al.
Publicado: (2020)

MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer
por: Qiao, Xiaofeng, et al.
Publicado: (2023)

Outcome of 5-year follow-up in men with negative findings on initial biparametric MRI
por: Kortenbach, Karen-Cecilie, et al.
Publicado: (2021)

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL
por: Lu, Yangbai, et al.
Publicado: (2022)

Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction
por: Gassenmaier, Sebastian, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_qcfnfnhol91rqv6dpotck2g684