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

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Title: Multi-parametric MRI zone-specific diagnostic model performance compared with experienced radiologists for detection of prostate cancer
Authors: Dikaios, N
Giganti, F
Sidhu, HS
Johnston, EW
Appayya, MB
Simmons, L
Freeman, A
Ahmed, HU
Atkinson, D
Punwani, S
Item Type: Journal Article
Abstract: OBJECTIVES: Compare the performance of zone-specific multi-parametric-MRI (mp-MRI) diagnostic models in prostate cancer detection with experienced radiologists. METHODS: A single-centre, IRB approved, prospective STARD compliant 3 T MRI test dataset of 203 patients was generated to test validity and generalisability of previously reported 1.5 T mp-MRI diagnostic models. All patients included within the test dataset underwent 3 T mp-MRI, comprising T2, diffusion-weighted and dynamic contrast-enhanced imaging followed by transperineal template ± targeted index lesion biopsy. Separate diagnostic models (transition zone (TZ) and peripheral zone (PZ)) were applied to respective zones. Sensitivity/specificity and the area under the receiver operating characteristic curve (ROC-AUC) were calculated for the two zone-specific models. Two radiologists (A and B) independently Likert scored test 3 T mp-MRI dataset, allowing ROC analysis for each radiologist for each prostate zone. RESULTS: Diagnostic models applied to the test dataset demonstrated a ROC-AUC = 0.74 (95% CI 0.67-0.81) in the PZ and 0.68 (95% CI 0.61-0.75) in the TZ. Radiologist A/B had a ROC-AUC = 0.78/0.74 in the PZ and 0.69/0.69 in the TZ. Radiologists A and B each scored 51 patients in the PZ and 41 and 45 patients respectively in the TZ as Likert 3. The PZ model demonstrated a ROC-AUC = 0.65/0.67 for the patients Likert scored as indeterminate by radiologist A/B respectively, whereas the TZ model demonstrated a ROC-AUC = 0.74/0.69. CONCLUSION: Zone-specific mp-MRI diagnostic models demonstrate generalisability between 1.5 and 3 T mp-MRI protocols and show similar classification performance to experienced radiologists for prostate cancer detection. Results also indicate the ability of diagnostic models to classify cases with an indeterminate radiologist score. KEY POINTS: • MRI diagnostic models had similar performance to experienced radiologists for classification of prostate cancer. • MRI diagnostic models may help radiologists classify tumour in patients with indeterminate Likert 3 scores.
Issue Date: 19-Nov-2018
Date of Acceptance: 24-Sep-2018
URI: http://hdl.handle.net/10044/1/65103
DOI: https://dx.doi.org/10.1007/s00330-018-5799-y
ISSN: 0938-7994
Publisher: Springer Verlag
Journal / Book Title: European Radiology
Copyright Statement: © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Sponsor/Funder: Wellcome Trust
University College London Hospitals Charity
Medical Research Council (MRC)
Funder's Grant Number: 204998/Z/16/Z
1348
WSST_P70374
Keywords: Computer-assisted
Diagnosis
Logistic models
Magnetic resonance imaging
Prostatic neoplasms
1103 Clinical Sciences
Nuclear Medicine & Medical Imaging
Publication Status: Published online
Conference Place: Germany
Online Publication Date: 2018-11-19
Appears in Collections:Division of Surgery
Faculty of Medicine



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