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Updated: Jul 5, 2025
Diffusion Imaging in the Rat Cervical Spinal Cord
Published on: April 7, 2015
Diffusion kurtosis imaging and standard diffusion imaging in the magnetic resonance imaging assessment of prostate
Pierpaolo Palumbo1, Andrea Martinese2, Maria Rosaria Antenucci2
1Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, Abruzzo Health Unit 1, L'Aquila, Italy.
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.
Insights
Diffusion kurtosis imaging (DKI) offers a more sophisticated analysis of prostate cancer (PCa) detection compared to standard diffusion-weighted imaging (DWI). While its advantages are still debated, DKI may improve the identification of clinically significant PCa with further research and understanding.
Area of Science:
- Radiology and Medical Imaging
- Oncology
- Biophysics
Background:
- Magnetic resonance imaging (MRI) is crucial for prostate cancer (PCa) detection and biopsy guidance.
- Biparametric MRI protocols show non-inferiority to multiparametric protocols for PCa detection.
- Diffusion-weighted imaging (DWI) is key, especially in the prostate's peripheral zone.
Purpose of the Study:
- To review the clinical applications and evidence for diffusion kurtosis imaging (DKI) in PCa detection.
- To compare the efficacy of DKI with conventional DWI.
Main Methods:
- A narrative review of literature from PubMed, including research articles, reviews, and meta-analyses.
- Analysis of findings related to DKI metrics (D app and K app ) and DWI-apparent diffusion coefficient (DWI-ADC).
Main Results:
- DKI analyzes non-Gaussian water diffusivity, offering insights beyond DWI-ADC's measure of water restriction.
- DKI metrics may reflect interactions between water molecules and cellular components.
- Evidence on DKI and DWI for PCa detection was collected and analyzed.
Conclusions:
- The advantages of DKI over conventional ADC analysis are currently debated.
- Wider adoption and technical understanding of DKI could validate its role in oncology, particularly for clinically significant PCa.
- Radiologists need a deeper understanding of DKI metrics (K app , D app ) for accurate PCa imaging interpretation.
