• It is difficult to diagnose transition zone (TZ) cancer. • We performed quantitative image analysis in multi-parametric MRI. • Standardized-T2WI and mean-ADC were independent factors for diagnosing TZ cancer. • We developed logistic-regression analysis to diagnose TZ cancer accurately. • The performance of the logistic-regression analysis was higher than PIRADSv2.
Purpose To evaluate the image quality and interobserver reproducibility of unenhanced lumbar spinal computed tomography (CT) images reconstructed with iterative model reconstruction (IMR). Materials and Methods This prospective study was approved by the local ethics committee, and written informed consent was obtained from all patients. The study included 34 patients scanned with unenhanced CT and magnetic resonance (MR) imaging for lumbar canal spinal stenosis. The CT images were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR), and IMR. Image noise and contrast-to-noise ratio (CNR) were compared among the three reconstruction techniques with the repeated one-way analysis of variance. The interobserver agreement of the dural sac on all CT image sets and T2-weighted images was also compared. Qualitative analysis of the three reconstruction techniques was performed by using Friedman test and the Wilcoxon signed-rank test with Holm correction. Results The image noise of IMR was significantly lower than that of FBP or HIR (P < .001 and P < .001). Pearson correlation analysis showed that the highest correlation coefficient with interobserver agreement was with IMR (r = 0.98) followed by MR imaging (r = 0.88), FBP (r = 0.41), and HIR (r = 0.33). It also showed that the narrowest Bland-Altman limit of agreement was achieved with IMR followed by MR imaging, FBP, and HIR. The qualitative image score using IMR was significantly higher than that using FBP or HIR (P < .001 and P < .001). Conclusion IMR offers excellent noise reduction, higher interobserver reproducibility of canal stenosis, and improved image quality compared with FBP and HIR. RSNA, 2017 Online supplemental material is available for this article.
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