Multiparametric MRI in the diagnosis of prostate cancer

• Verfasst von: Wichtmann, Barbara [VerfasserIn]
• Verfasst von: Zöllner, Frank G. [VerfasserIn]
• Verfasst von: Attenberger, Ulrike [VerfasserIn]
• Verfasst von: Schönberg, Stefan [VerfasserIn]
• Titel: Multiparametric MRI in the diagnosis of prostate cancer
• Titelzusatz: physical foundations, limitations, and prospective advances of diffusion-weighted MRI
• Paralleltitel: Multiparametrische MRT in der Diagnose des Prostatakarzinoms
• Paralleltitelzusatz: physikalische Grundlagen, Limitationen und potenzielle Fortschritte der diffusionsgewichteten MRT
• Verf.angabe: authors: Barbara Daria Wichtmann, Frank Gerrit Zöllner, Ulrike Irmgard Attenberger, Stefan O. Schönberg
• Jahr: 2021
• Umfang: 11 S.
• Fussnoten: Artikel online veröffentlicht: 10. Dezember 2020 ; Gesehen am 17.01.2024
• Titel Quelle: Enthalten in: RöFo
• Ort Quelle: Stuttgart [u.a.] : Thieme, 1975
• Jahr Quelle: 2021
• Band/Heft Quelle: 193(2021), 4, Seite 399-409
• ISSN Quelle: 1438-9010
• DOI: doi:10.1055/a-1276-1773
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1878367358

Abstract

<p> <b>Background</b> Diffusion-weighted imaging (DWI) is an essential component of the multiparametric MRI exam for the diagnosis and assessment of prostate cancer (PCa). Over the last two decades, various models have been developed to quantitatively correlate the DWI signal with microstructural characteristics of prostate tissue. The simplest approach (ADC: apparent diffusion coefficient) - currently established as the clinical standard - describes monoexponential decay of the DWI signal. While numerous studies have shown an inverse correlation of ADC values with the Gleason score, the ADC model lacks specificity and is based on water diffusion dynamics that are not true in human tissue. This article aims to explain the biophysical limitations of the standard DWI model and to discuss the potential of more complex, advanced DWI models.</p> <p> <b>Methods</b> This article is a review based on a selective literature review.</p> <p> <b>Results</b> Four phenomenological DWI models are introduced: diffusion tensor imaging, intravoxel incoherent motion, biexponential model, and diffusion kurtosis imaging. Their parameters may potentially improve PCa diagnostics but show varying degrees of statistical significance with respect to the detection and characterization of PCa in current studies. Phenomenological model parameters lack specificity, which has motivated the development of more descriptive tissue models that directly relate microstructural features to the DWI signal. Finally, we present two of such structural models, i. e. the VERDICT (Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors) and RSI (Restriction Spectrum Imaging) model. Both have shown promising results in initial studies regarding the characterization and prognosis of PCa.</p> <p> <b>Conclusion</b> Recent developments in DWI techniques promise increasing accuracy and more specific statements about microstructural changes of PCa. However, further studies are necessary to establish a standardized DWI protocol for the diagnosis of PCa.</p> <p> <b>Key Points:</b> </p> <p> <b>Citation Format</b> </p>