ReviewMagma (New York, N.Y.)2026
Microstructure imaging of prostate cancer by diffusion MRI.
Review in Magma (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Prostate cancer remains one of the most prevalent malignancies in men worldwide, and early detection, accurate characterization, and staging are critical for optimal patient management. Diffusion magnetic resonance imaging (dMRI) has emerged as a powerful technique for non-invasive in vivo imaging of tissue microstructure, promising to enable unprecedented insights into the pathophysiology of prostate cancer. In this review, we examine the current state and future directions of dMRI techniques for microstructure MRI in prostate cancer applications. We describe the technical challenges of prostate imaging along with potential remedies, as well as techniques that go beyond measuring the conventional apparent diffusion coefficient. These include more sophisticated representations and models, such as intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), methods based on tensor-valued diffusion encoding such as q-space trajectory imaging (QTI), as well as time-dependent dMRI. Models, such as VERDICT (vascular, extracellular, and restricted diffusion for cytometry in tumors) and IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion), are highlighted for their ability to quantify the composition of prostatic tissues in the clinical setting. This review highlights the transformative potential of microstructure MRI in prostate cancer, while identifying key research priorities and technical developments needed to realize its clinical impact. Future directions include the adoption of high-performance MRI systems, improved image readout and processing techniques, integration of multiparametric and multidimensional approaches, development of parsimonious protocols, and standardization of robust biomarkers for personalized treatment stratification. Although there is yet to be a consensus of how microstructure MRI should be deployed, current evidence suggests that it can provide superior diagnostic performance compared to conventional measurements, with improved correlation to tumor aggressiveness and potential downstream advantages for prostate cancer diagnostics and treatment monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.