ArticleQuantitative imaging in medicine and surgery2026
Evaluation of MRI-based risk models versus PI-RADS version 2.1 and arterial spin labeling perfusion imaging strategy for clinically significant prostate cancer.
Article in Quantitative imaging in medicine and surgery, 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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Arterial spin labeling (ASL) is a non-invasive magnetic resonance imaging (MRI) technique that enables quantitative assessment of prostate blood flow (PBF). Although the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 is widely used for risk stratification of clinically significant prostate cancer (csPCa), whether combining ASL with the PI-RADS system can improve diagnostic accuracy remains to be explored. This study aimed to evaluate the risk of csPCa by integrating non-invasive ASL-derived PBF measurements with PI-RADS v2.1 scores in a clinical-imaging model. Methods: Of 233 patients with suspected prostate cancer (PCa) who underwent biparametric magnetic resonance imaging (bp-MRI) and ASL, 133 had pathologically confirmed benign or malignant lesions. The analysis included PBF measurements, PI-RADS v2.1 scores, and relevant clinical data from this cohort. This study employed both univariable and multivariable logistic regression to sequentially identify prognostic features. The diagnostic performance of PBF, PI-RADS v2.1 scores, and their combination in detecting csPCa was assessed using receiver operating characteristic (ROC) analysis. Bootstrap resampling was used for internal validation to ensure model stability. A nomogram was constructed to visualize the predictive model for csPCa risk, and decision curve analysis (DCA) was performed to evaluate its clinical utility. Results: Independent risk factors for csPCa included maximum prostate blood flow (PBF-max), PI-RADS v2.1 score, total prostate-specific antigen (tPSA), and prostate volume (PV). The diagnostic performance for csPCa, measured by the area under the curve (AUC), was 0.872 for PBF-max alone and 0.916 for the PI-RADS v2.1 score alone. Their combination significantly improved accuracy, yielding an AUC of 0.965. Furthermore, PI-RADS v2.1 scores demonstrated a strong positive correlation with PBF-max (r=0.62). Conclusions: The non-invasive quantification of PBF via ASL enhances the diagnostic capability of PI-RADS v2.1 scores for the detection of csPCa.
Indexed as
Identifiers
What OpenQuestion holds
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.