University of Oulu

Movahedi, P., Merisaari, H., Perez, I.M. et al. Prediction of prostate cancer aggressiveness using 18F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI. Sci Rep 10, 9407 (2020).

Prediction of prostate cancer aggressiveness using ¹⁸F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI

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Author: Movahedi, Parisa1,2; Merisaari, Harri1,2; Perez, Ileana Montoya1,2;
Organizations: 1Department of Future Technologies, University of Turku, Turku, Finland
2Department of Diagnostic Radiology, University of Turku, Turku, Finland
3Institute of Biomedicine, University of Turku and Department of Pathology, Turku
4University, Hospital, Turku, Finland
5Turku PET Centre, Turku University and Turku University Hospital, Turku, Finland
6Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
7Department of Oncology and Radiotherapy, Turku University Hospital, Turku, Finland
8Department of Medical Physics, Turku University Hospital, Turku, Finland
9Department of Urology, University of Turku and Turku University hospital, Turku, Finland
10A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
11Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland
12Department of Clinical Radiology, Oulu University Hospital, Oulu, Finland
13Medical Imaging Centre of Southwest Finland, Turku University Hospital, Turku, Finland
14Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
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Language: English
Published: Springer Nature, 2020
Publish Date: 2020-10-19


The aim of this prospective single-institution clinical trial (NCT02002455) was to evaluate the potential of advanced post-processing methods for ¹⁸F-Fluciclovine PET and multisequence multiparametric MRI in the prediction of prostate cancer (PCa) aggressiveness, defined by Gleason Grade Group (GGG). 21 patients with PCa underwent PET/CT, PET/MRI and MRI before prostatectomy. DWI was post-processed using kurtosis (ADCₖ, K), mono- (ADCₘ), and biexponential functions (f, Dₚ, Df) while Logan plots were used to calculate volume of distribution (VT). In total, 16 unique PET (VT, SUV) and MRI derived quantitative parameters were evaluated. Univariate and multivariate analysis were carried out to estimate the potential of the quantitative parameters and their combinations to predict GGG 1 vs >1, using logistic regression with a nested leave-pair out cross validation (LPOCV) scheme and recursive feature elimination technique applied for feature selection. The second order rotating frame imaging (RAFF), monoexponential and kurtosis derived parameters had LPOCV AUC in the range of 0.72 to 0.92 while the corresponding value for VT was 0.85. The best performance for GGG prediction was achieved by K parameter of kurtosis function followed by quantitative parameters based on DWI, RAFF and ¹⁸F-FACBC PET. No major improvement was achieved using parameter combinations with or without feature selection. Addition of ¹⁸F-FACBC PET derived parameters (VT, SUV) to DWI and RAFF derived parameters did not improve LPOCV AUC.

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Series: Scientific reports
ISSN: 2045-2322
ISSN-E: 2045-2322
ISSN-L: 2045-2322
Volume: 10
Issue: 1
Article number: 9407
DOI: 10.1038/s41598-020-66255-8
Type of Publication: A1 Journal article – refereed
Field of Science: 3121 General medicine, internal medicine and other clinical medicine
Funding: This study was financially supported by grants from Instrumentarium Research Foundation, Sigrid Jusélius Foundation, Turku University Hospital, TYKS-SAPA research fund, Finnish Cancer Society, Finnish Cultural Foundation, and Orion Research Foundation. PT was supported by a Clinical Researcher Funding from the Academy of Finland. HM was supported by a grant from Orion Research Foundation. The study was conducted within the Finnish Center of Excellence in Molecular Imaging in Cardiovascular and Metabolic Research supported by the Academy of Finland, University of Turku, Turku University Hospital and Åbo Akademi University.
Copyright information: © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit