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Palumbo P, Martinese A, Antenucci MR, Granata V, Fusco R, De Muzio F, Brunese MC, Bicci E, Bruno A, Bruno F, Giovagnoni A, Gandolfo N, Miele V, Di Cesare E, Manetta R. Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate cancer. Gland Surg 2023; 12:1806-1822. [PMID: 38229839 PMCID: PMC10788566 DOI: 10.21037/gs-23-53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 11/09/2023] [Indexed: 01/18/2024]
Abstract
Background and Objective In recent years, magnetic resonance imaging (MRI) has shown excellent results in the study of the prostate gland. MRI has indeed shown to be advantageous in the prostate cancer (PCa) detection, as in guiding targeting biopsy, improving its diagnostic yield. Although current acquisition protocols provide for multiparametric acquisition, recent evidence has shown that biparametric protocols can be non-inferior in PCa detection. Diffusion-weighted imaging (DWI) sequence, in particular, plays a key role, particularly in the peripheral zone which accounts for the larger part of the prostate. High b-values are generally recommended, although with the possibility of obtaining non-Gaussian diffusion effects, which requires a more sophisticated model for the analysis, namely through the diffusion kurtosis imaging (DKI). Purpose of this narrative review was to analyze the current applications and clinical evidence regarding the use of DKI with a main focus on PCa detection, also in comparison with DWI. Methods This narrative review synthesized the findings of literature retrieved from main researches, narrative and systematic reviews, and meta-analyses obtained from PubMed. Key Content and Findings DKI analyses the non-Gaussian water diffusivity and describe the effect of signal intensity decay related to high b-value through two main metrics (Dapp and Kapp). Differently from DWI-apparent diffusion coefficient (DWI-ADC) which reflects only water restriction outside of cells, DKI metrics are supposed to represent also the direct interaction of water molecules with cell membranes and intracellular compounds. This review describes current evidence on ADC and DKI metrics in clinical imaging, and finally collect the results derived from the main articles focused on DWI and DKI models in detecting PCa. Conclusions DKI advantages, compared to conventional ADC analysis, still remain controversial. Wider application and greater technical knowledge of DKI, however, may help in proving its intrinsic validity in the field of oncology and therefore in the study of clinically significant PCa. Finally, a deep understanding of DKI is important for radiologists to better understand what Kapp and Dapp mean in the context of different cancer and how these metrics may vary specifically in PCa imaging.
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Affiliation(s)
- Pierpaolo Palumbo
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, L’Aquila, Italy
| | - Andrea Martinese
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy
| | - Maria Rosaria Antenucci
- Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy
| | - Vincenza Granata
- Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale-IRCCS di Napoli”, Naples, Italy
| | | | - Federica De Muzio
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, Campobasso, Italy
| | - Maria Chiara Brunese
- Diagnostic Imaging Section, Department of Medical and Surgical Sciences & Neurosciences, University of Molise, Campobasso, Italy
| | - Eleonora Bicci
- Department of Emergency Radiology, University Hospital Careggi, Florence, Italy
| | - Alessandra Bruno
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Ancona, Italy
| | - Federico Bruno
- Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, L’Aquila, Italy
| | - Andrea Giovagnoni
- Department of Clinical, Special and Dental Sciences, University Politecnica delle Marche, Ancona, Italy
- Department of Radiology, University Hospital “Azienda Ospedaliera Universitaria delle Marche”, Ancona, Italy
| | - Nicoletta Gandolfo
- Diagnostic Imaging Department, Villa Scassi Hospital-ASL 3, Genoa, Italy
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, Milan, Italy
| | - Vittorio Miele
- Department of Emergency Radiology, University Hospital Careggi, Florence, Italy
| | - Ernesto Di Cesare
- Department of Life, Health and Environmental Sciences, University of L’Aquila, L’Aquila, Italy
| | - Rosa Manetta
- Radiology Unit, San Salvatore Hospital, Abruzzo Health Unit 1, L’Aquila, Italy
- Prostate Unit, San Salvatore Hospital, Abruzzo Health Unit 1, L’Aquila, Italy
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