Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI

Hammon M, Saake M, Laun FB, Heiß R, Seuss N, Janka RM, Cavallaro AJ, Uder M, Seuß H (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Diagnostics MDPI

Book Volume: 12

Journal Issue: 7

DOI: 10.3390/diagnostics12071592

Abstract

(1) Background: For the peripheral zone of the prostate, diffusion weighted imaging (DWI) is the most important MRI technique; however, a high b-value image (hbDWI) must always be evaluated in conjunction with an apparent diffusion coefficient (ADC) map. We aimed to unify the important contrast features of both a hbDWI and ADC in one single image, termed multichannel computed diffusion images (mcDI), and evaluate the values of these images in a retrospective clinical study; (2) Methods: Based on the 2D histograms of hbDWI and ADC images of 70 patients with histologically proven prostate cancer (PCa) in the peripheral zone, an algorithm was designed to generate the mcDI. Then, three radiologists evaluated the data of 56 other patients twice in three settings (T2w images +): (1) hbDWI and ADC; (2) mcDI; and (3) mcDI, hbDWI, and ADC. The sensitivity, specificity, and inter-reader variability were evaluated; (3) Results: The overall sensitivity/specificity were 0.91/0.78 (hbDWI + ADC), 0.85/0.88 (mcDI), and 0.97/0.88 (mcDI + hbDWI + ADC). The kappa-values for the inter-reader variability were 0.732 (hbDWI + ADC), 0.800 (mcDI), and 0.853 (mcDI + hbDWI + ADC). (4) Conclusions: By using mcDI, the specificity of the MRI detection of PCa was increased at the expense of the sensitivity. By combining the conventional diffusion data with the mcDI data, both the sensitivity and specificity were improved.

Authors with CRIS profile

Matthias Hammon Institute of Radiology Frederik Bernd Laun Professur für quantitative MR-Bildgebung (Heisenberg-Professur) Rafael Heiß Institute of Radiology Rolf Matthias Janka Institute of Radiology Alexander Josef Cavallaro Institute of Radiology Michael Uder Lehrstuhl für Diagnostische Radiologie Hannes Seuß Lehrstuhl für Diagnostische Radiologie

Involved external institutions

Klinikum Fürth DE Germany (DE)

How to cite

APA:

Hammon, M., Saake, M., Laun, F.B., Heiß, R., Seuss, N., Janka, R.M.,... Seuß, H. (2022). Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI. Diagnostics, 12(7). https://dx.doi.org/10.3390/diagnostics12071592

MLA:

Hammon, Matthias, et al. "Improved Visualization of Prostate Cancer Using Multichannel Computed Diffusion Images: Combining ADC and DWI." Diagnostics 12.7 (2022).

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