Editorial for “Multi‐site concordance of diffusion weighted imaging quantification for assessing prostate cancer aggressiveness”
Abstract
Multiparametric magnetic resonance imaging (mpMRI) is playing an increasingly important role in the diagnosis of prostate cancer (PC). The development of Prostate Imaging-Reporting And Data System (PI-RADS) has greatly promoted standardization on the acquisition, interpretation, and reporting of mpMRI examinations. In the latest PI-RADS (v2.1), diffusion-weighted imaging (DWI) is the dominant sequence for PC diagnosis in the peripheral zone, which could be interpreted qualitatively on diffusionweighted images, or quantitatively on monoexponential apparent diffusion coefficient (MEADC) maps. Besides monoexponential DWI, advanced DWI models have been proposed for the characterization of non-Gaussian diffusion behaviors in PC, but all of them are still under research exploration and none has been integrated into clinical guidelines or protocols. A major concern on these advanced DWI models is their unestablished reliability as quantitative imaging biomarkers for clinical use. In this issue of JMRI, Obuchowski et al rigorously investigated inter-site concordance of diffusion-derived parametric maps on the same pathologically validated PC DWI dataset under a variety of site-specific parametric fitting implementations and post-processing conditions. The results across sites showed that K and DK in diffusion kurtosis imaging (DKI) and MEADC had significantly better quantitative reliability as compared to biexponential parameters in both noise-free digital reference object and real…
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.