Multi-parametric MRI zone-specific diagnostic model performance compared with experienced radiologists for detection of prostate cancer-Reference-Cited by-同舟云学术

Multi-parametric MRI zone-specific diagnostic model performance compared with experienced radiologists for detection of prostate cancer

Published:2018-11-19 Issue:8 Volume:29 Page:4150-4159
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Dikaios Nikolaos,Giganti Francesco,Sidhu Harbir S.,Johnston Edward W.,Appayya Mrishta B.,Simmons Lucy,Freeman Alex,Ahmed Hashim U.,Atkinson David,Punwani Shonit^ORCID

Funder

University College London

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s00330-018-5799-y.pdf

Reference30 articles.

1. National Prostate Cancer Audit Fourth Year Annual Report – Results of the NPCA Prospective Audit in England and Wales for men diagnosed 1 April 2015–March 2016. Available via https://www.npca.org.uk . Accessed 01 Aug 2018

2. Renard-Penna R, Mozer P, Cornud F et al (2015) Prostate imaging reporting and data system and Likert scoring system: multiparametric MR imaging validation study to screen patients for initial biopsy. Radiology 275:458–468

3. Brizmohun Appayya M, Sidhu HS, Dikaios N et al (2018) Characterizing indeterminate (Likert-score 3/5) peripheral zone prostate lesions with PSA density, PI-RADS scoring and qualitative descriptors on multiparametric MRI. Br J Radiol 91:20170645

4. Simmons LA, Ahmed HU, Moore CM et al (2014) The PICTURE study -- prostate imaging (multi-parametric MRI and Prostate HistoScanning™) compared to transperineal ultrasound guided biopsy for significant prostate cancer risk evaluation. Contemp Clin Trials 37:69–83

5. Dikaios N, Alkalbani J, Abd-Alazeez M et al (2015) Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI. Eur Radiol 25:2727–2737

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A radiomics based method for prediction of prostate cancer Gleason score using enlarged region of interest;BMC Medical Imaging;2023-12-08

2. A radiomics based method for prediction of prostate cancer Gleason score using enlarged region of interest;2023-08-03

3. Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: How accurate are they when tested on independent cohorts? – A systematic review;Diagnostic and Interventional Imaging;2023-05

4. Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology;Magnetic Resonance Imaging;2022-01

5. Utility of diffusion MRI characteristics of cervical lymph nodes as disease classifier between patients with head and neck squamous cell carcinoma and healthy volunteers;NMR in Biomedicine;2021-07-08