Purpose: To compare the diagnostic accuracy of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) for prostate cancer (PCa) and clinically significant prostate cancer (csPCa) and to explore the application value of dynamic contrast-enhanced (DCE) MRI in prostate imaging. Methods and materials: This study retrospectively enrolled 235 patients with suspected PCa in our hospital from January 2016 to December 2017, and all lesions were histopathologically confirmed. The lesions were scored according to the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2). The bpMRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC]) and mpMRI (T2WI, DWI/ADC and DCE) scores were recorded to plot the receiver operating characteristic (ROC) curves. The area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) for each method were calculated and compared. The patients were further stratified according to bpMRI scores (bpMRI ≥3, and bpMRI = 3, 4, 5) to analyse the difference in DCE MRI between PCa and non-PCa lesions (as well as between csPCa and non-csPCa). Results: The AUC values for the bpMRI and mpMRI protocols for PCa were comparable (0.790 [0.732–0.840] and 0.791 [0.733–0.841], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for PCa were 76.2, 79.5, 72.6, 75.8, and 76.6%, respectively, and the values for mpMRI were 77.4, 84.4, 69.9, 75.2, and 80.6%, respectively. The AUC values for the bpMRI and mpMRI protocols for the diagnosis of csPCa were similar (0.781 [0.722–0.832] and 0.779 [0.721–0.831], respectively). The accuracy, sensitivity, specificity, PPV and NPV of bpMRI for csPCa were 74.0, 83.8, 66.9, 64.8, and 85.0%, respectively; and 73.6, 87.9, 63.2, 63.2, and 87.8%, respectively, for mpMRI. For patients with bpMRI scores ≥3, positive DCE results were more common in PCa and csPCa lesions (both P = 0.001). Further stratification analysis showed that for patients with a bpMRI score = 4, PCa and csPCa lesions were more likely to have positive DCE results (P = 0.003 and P < 0.001, respectively). Conclusion: The diagnostic accuracy of bpMRI is comparable with that of mpMRI in the detection of PCa and the identification of csPCa. DCE MRI is helpful in further identifying PCa and csPCa lesions in patients with bpMRI ≥3, especially bpMRI = 4, which may be conducive to achieving a more accurate PCa risk stratification. Rather than omitting DCE, we think further comprehensive studies are required for prostate MRI.

Pathological examination combined with tumor markers has become a standard for the diagnosis of intracranial germ cell tumors (ICGCTs), but the current concept of ‘secreting germ cell tumors’ and three empirically highly specific diagnostic criteria (β-hCG ≥ 50 IU/L or αFP ≥ 10 ng/mL; β-hCG ≥ 100 IU/L or αFP ≥ 50 ng/mL; β-hCG > 50 IU/L or αFP > 25 ng/mL) are not based upon pathology examination or CSF cytology. Further investigation is needed to re-evaluate their value. A multidisciplinary diagnostic team was created. Valid β-hCG/αFP data were collected from cases of ICGCTs confirmed by pathology and CSF cytology (n = 58) between 1991 and 2012, and from suspected ICGCTs cases (n = 17) between 2011 and 2012 as controls [Langerhans cell histiocytosis (LCH), n = 12; and other intracranial tumor (ICT), n = 5]. The cut-off points for β-hCG and αFP were calculated using receiver operating characteristic (ROC) curves. This study clarifies the relative rationality of one criteria (β-hCG > 50 IU/L and αFP > 25 ng/mL); confirms new β-hCG diagnostic cut-off points: CSF β-hCG ≥ 8.2 IU/L and serum β-hCG ≥ 2.5 IU/L (sensitivity of 47 and 34 %, respectively, specificity of 100 %, both; P < 0.05); and empirically adjusts the criteria for αFP to ≥ 3.8 ng/mL in CSF and to ≥ 25 ng/mL in serum. The total diagnostic sensitivity for ICGCTs finally increased from 34.6 to 65.4 % (P < 0.05, diagnostic value of CSF β-hCG exceeds 90 %). Subtype diagnosis improved with αFP in 16.7 % of non-geminomatous germ cell tumor cases. New evidence-based criteria of β-hCG and αFP can help improving early and formal diagnosis of ICGCTs, and is of great clinical significance.

Background: The inter-scanner reproducibility of brain volumetry is important in multi-site neuroimaging studies, where the reliability of automated brain segmentation (ABS) tools plays an important role. This study aimed to evaluate the influence of ABS tools on the consistency and reproducibility of the quantified brain volumetry from different scanners. Methods: We included fifteen healthy volunteers who were scanned with 3D isotropic brain T1-weighted sequence on three different 3.0 Tesla MRI scanners (GE, Siemens and Philips). For each individual, the time span between image acquisitions on different scanners was limited to 1 h. All the T1-weighted images were processed with FreeSurfer v6.0, FSL v5.0 and AccuBrain^® with default settings to obtain volumetry of brain tissues (e.g. gray matter) and substructures (e.g. basal ganglia structures) if available. Coefficient of variation (CV) was calculated to test inter-scanner variability in brain volumetry of various structures as quantified by these ABS tools. Results: The mean inter-scanner CV values per brain structure among three MRI scanners ranged from 6.946 to 12.29% (mean, 9.577%) for FreeSurfer, 7.245 to 20.98% (mean, 12.60%) for FSL and 1.348 to 8.800% (mean value, 3.546%) for AccuBrain^®. In addition, AccuBrain^® and FreeSurfer achieved the lowest mean values of region-specific CV between GE and Siemens scanners (from 0.818 to 5.958% for AccuBrain^®, and from 0.903 to 7.977% for FreeSurfer), while FSL-FIRST had the lowest mean values of region-specific CV between GE and Philips scanners (from 2.603 to 16.310%). AccuBrain^® also had the lowest mean values of region-specific CV between Siemens and Philips scanners (from 1.138 to 6.615%). Conclusion: There is a large discrepancy in the inter-scanner reproducibility of brain volumetry when using different processing software. Image acquisition protocols and selection of ABS tool for brain volumetry quantification have impact on the robustness of results in multi-site studies.