Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer.

Multiparametric prostate MRI Prostate cancer Quantitative imaging T2 mapping

Journal

Journal of imaging informatics in medicine
ISSN: 2948-2933
Titre abrégé: J Imaging Inform Med
Pays: Switzerland
ID NLM: 9918663679206676

Informations de publication

Date de publication:
26 Jun 2024
Historique:
received: 16 11 2023
accepted: 23 05 2024
revised: 21 05 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 26 6 2024
Statut: aheadofprint

Résumé

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.

Identifiants

pubmed: 38926263
doi: 10.1007/s10278-024-01150-6
pii: 10.1007/s10278-024-01150-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121
Organisme : Bundesministerium für Bildung und Forschung
ID : FKZ: 01KX2121

Informations de copyright

© 2024. The Author(s).

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Auteurs

Andreas Michael Bucher (AM)

Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Jan Egger (J)

Institute for AI in Medicine, University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany. jan.egger@uk-essen.de.

Julia Dietz (J)

Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Ralph Strecker (R)

Siemens Healthineers AG, (EMEA Scientific Partnerships), Henkestraße 127, 91052, Erlangen, Germany.

Tom Hilbert (T)

Advanced Clinical Imaging Technology, Siemens Healthineers International AG, EPFL, QI E, 1015, Lausanne, Lausanne, Switzerland.
Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Eric Frodl (E)

Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Mike Wenzel (M)

Department of Urology, Goethe University Hospital, Goethe University Frankfurt, Frankfurt, Germany, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Tobias Penzkofer (T)

Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
Berlin Institute of Health, Berlin, Germany.

Bernd Hamm (B)

Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Felix Kh Chun (FK)

Department of Urology, Goethe University Hospital, Goethe University Frankfurt, Frankfurt, Germany, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Thomas Vogl (T)

Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.

Jens Kleesiek (J)

Institute for AI in Medicine, University Hospital Essen, Girardetstraße 2, 45131, Essen, Germany.
Department of Physics, TU Dortmund University, Otto-Hahn-Straße 4, 44227, Dortmund, Germany.
Cancer Research Center Cologne Essen (CCCE), West German Cancer Center Essen (WTZ), 45122, Essen, Germany.
German Cancer Research Center (DKFZ), Partner site University Hospital Essen, German Cancer Consortium (DKTK), 45122, Essen, Germany.
Medical Faculty, University of Duisburg-Essen, 45122, Essen, Germany.

Martin Beeres (M)

Institute for Diagnostic and Interventional Radiology, Goethe University Frankfurt, University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt, Germany.
Departement of Neuroradiology, University-Hospital of Giessen and Marburg Campus Marburg, Baldingerstraße 1, 35043, Marburg, Germany.

Classifications MeSH