Volume 51, Issue 5 pp. 1556-1567
Original Research

Qualitative and Quantitative Reporting of a Unique Biparametric MRI: Towards Biparametric MRI-Based Nomograms for Prediction of Prostate Biopsy Outcome in Men With a Clinical Suspicion of Prostate Cancer (IMPROD and MULTI-IMPROD Trials)

Ileana Montoya Perez MSc

Ileana Montoya Perez MSc

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Department of Future Technologies, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

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Ivan Jambor MD, PhD

Corresponding Author

Ivan Jambor MD, PhD

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

Address reprint requests to: I.J., Department of Diagnostic Radiology, University of Turku, Kiinamyllynkatu 4-8, P.O. Box 52, FI-20521 Turku, Finland. E-mail: [email protected]Search for more papers by this author
Tommi Kauko MSc

Tommi Kauko MSc

Auria Clinical Informatics, Turku University Hospital, Turku, Finland

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Janne Verho MD

Janne Verho MD

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

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Otto Ettala MD

Otto Ettala MD

Department of Urology, University of Turku and Turku University Hospital, Turku, Finland

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Ugo Falagario MD

Ugo Falagario MD

Department of Urology, University of Foggia, Foggia, Italy

Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA

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Harri Merisaari PhD

Harri Merisaari PhD

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Department of Future Technologies, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

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Aida Kiviniemi MD, PhD

Aida Kiviniemi MD, PhD

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

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Pekka Taimen MD, PhD

Pekka Taimen MD, PhD

Institute of Biomedicine, University of Turku and Department of Pathology, Turku University Hospital, Turku, Finland

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Kari T. Syvänen MD, PhD

Kari T. Syvänen MD, PhD

Department of Urology, University of Turku and Turku University Hospital, Turku, Finland

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Juha Knaapila MD

Juha Knaapila MD

Department of Urology, University of Turku and Turku University Hospital, Turku, Finland

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Marjo Seppänen MD

Marjo Seppänen MD

Department of Surgery, Satakunta Central Hospital, Pori, Finland

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Antti Rannikko MD

Antti Rannikko MD

Department of Urology, Helsinki University and Helsinki University Hospital, Helsinki, Finland

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Jarno Riikonen MD

Jarno Riikonen MD

Department of Urology, Tampere University Hospital and University of Tampere, Tampere, Finland

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Markku Kallajoki MD

Markku Kallajoki MD

Institute of Biomedicine, University of Turku and Department of Pathology, Turku University Hospital, Turku, Finland

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Tuomas Mirtti MD

Tuomas Mirtti MD

Department of Pathology, University of Helsinki, Helsinki, Finland

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Tarja Lamminen MD

Tarja Lamminen MD

Department of Urology, University of Turku and Turku University Hospital, Turku, Finland

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Jani Saunavaara PhD

Jani Saunavaara PhD

Department of Medical Physics, Turku University Hospital, Turku, Finland

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Tapio Pahikkala PhD

Tapio Pahikkala PhD

Department of Future Technologies, University of Turku, Turku, Finland

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Peter J. Boström MD, PhD

Peter J. Boström MD, PhD

Department of Urology, University of Turku and Turku University Hospital, Turku, Finland

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Hannu J. Aronen MD, PhD

Hannu J. Aronen MD, PhD

Department of Diagnostic Radiology, University of Turku, Turku, Finland

Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland

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First published: 21 November 2019
Citations: 26
Contract grant sponsor: Instrumentarium Research Foundation; Sigrid Jusélius Foundation; Turku University Hospital; TYKS-SAPA research fund; Finnish Cancer Society; Finnish Cultural Foundation; Orion Research Foundation; Clinical Researcher Funding from the Academy of Finland (to P.T.).

Abstract

Background

Multiparametric MRI of the prostate has been shown to improve the risk stratification of men with an elevated prostate-specific antigen (PSA). However, long acquisition time, high cost, and inter-center/reader variability of a routine prostate multiparametric MRI limit its wider adoption.

Purpose

To develop and validate nomograms based on unique rapid biparametric MRI (bpMRI) qualitative and quantitative derived variables for prediction of clinically significant cancer (SPCa).

Study Type

Retrospective analyses of single (IMPROD, NCT01864135) and multiinstitution trials (MULTI-IMPROD, NCT02241122).

Population

161 and 338 prospectively enrolled men who completed the IMPROD and MULTI-IMPROD trials, respectively.

Field Strength/Sequence

IMPROD bpMRI: 3T/1.5T, T2-weighted imaging, three separate diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm2; 2) b values 0, 1500 s/mm2; 3) values 0, 2000 s/mm2.

Assessment

The primary endpoint of the combined trial analysis was the diagnostic accuracy of the combination of IMPROD bpMRI and clinical variables for detection of SPCa.

Statistical Tests

Logistic regression models were developed using IMPROD trial data and validated using MULTI-IMPROD trial data. The model's performance was expressed as the area under the curve (AUC) values for the detection of SPCa, defined as ISUP Gleason Grade Group ≥2.

Results

A model incorporating clinical variables had an AUC (95% confidence interval) of 0.83 (0.77–0.89) and 0.80 (0.75–0.85) in the development and validation cohorts, respectively. The corresponding values for a model using IMPROD bpMRI findings were 0.93 (0.89–0.97), and 0.88 (0.84–0.92), respectively. Further addition of the quantitative DWI-based score did not improve AUC values (P < 0.05).

Data Conclusion

A prediction model using qualitative IMPROD bpMRI findings demonstrated high accuracy for predicting SPCa in men with an elevated PSA. Online risk calculator: http://petiv.utu.fi/multiimprod/

Level of Evidence: 1

Technical Efficacy Stage: 2

J. Magn. Reson. Imaging 2020;51:1556–1567.

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