Assessment of Diffusion Tensor Imaging Parameters of Hepatic Parenchyma for Differentiation of Biliary Atresia from Alagille Syndrome.

OBJECTIVE: To assess diffusion tensor imaging (DTI) parameters of the hepatic parenchyma for the differentiation of biliary atresia (BA) from Alagille syndrome (ALGS). MATERIALS AND METHODS: This study included 32 infants with BA and 12 infants with ALGS groups who had undergone DTI. Fractional anisotropy (FA) and mean diffusivity (MD) of the liver were calculated twice by two separate readers and hepatic tissue was biopsied. Statistical analyses were performed to determine the mean values of the two groups. The optimum cut-off values for DTI differentiation of BA and ALGS were calculated by receiver operating characteristic (ROC) analysis. RESULTS: The mean hepatic MD of BA (1.56 ± 0.20 and 1.63 ± 0.2 × 10-3 mm²/s) was significantly lower than that of ALGS (1.84 ± 0.04 and 1.79 ± 0.03 × 10-3 mm²/s) for both readers (r = 0.8, p = 0.001). Hepatic MD values of 1.77 and 1.79 × 10-3 mm²/s as a threshold for differentiating BA from ALGS showed accuracies of 82 and 79% and area under the curves (AUCs) of 0.90 and 0.91 for both readers, respectively. The mean hepatic FA of BA (0.34 ± 0.04 and 0.36 ± 0.04) was significantly higher (p = 0.01, 0.02) than that of ALGS (0.30 ± 0.06 and 0.31 ± 0.05) for both readers (r = 0.80, p = 0.001). FA values of 0.30 and 0.28 as a threshold for differentiating BA from ALGS showed accuracies of 75% and 82% and AUCs of 0.69 and 0.68 for both readers, respectively. CONCLUSION: Hepatic DTI parameters are promising quantitative imaging parameters for the detection of hepatic parenchymal changes in BA and ALGS and may be an additional noninvasive imaging tool for the differentiation of BA from ALGS.

Assessment of paraspinal neurogenic tumors with diffusion-weighted MR imaging.

PURPOSE: To assess paraspinal neurogenic tumors with diffusion-weighted MR imaging. METHODS: Retrospective analysis was done upon 34 patients with paraspinal neurogenic tumors that underwent diffusion-weighted MR imaging. The ADC values of the mediastinal neurogenic tumors were calculated and correlated with biopsy results. RESULTS: The ADC of benign paraspinal neurogenic tumors (1.5 ± 0.28 × 10-3 mm2/s) was significantly higher (P = 0.001) than that of malignant peripheral nerve sheath tumors (0.995 ± 0.198 × 10-3 mm2/s). Selection of 1.15 × 10-3 mm2/s as a cut-off point for differentiating malignant from benign neurogenic tumors revealed an area under the curve of 0.885, an accuracy of 91.1%, a sensitivity of 90.9%, and specificity of 91.3%. There was significant difference (P = 0.04) in the ADC of schwannomas (1.55 ± 0.29 × 10-3 mm2/s) from neurofibromas (1.33 ± 0.08 × 10-3 mm2/s). The cut-off ADC value of 1.44 × 10-3 mm2/s was used to differentiate schwannomas and neurofibromas with an area under the curve of 0.86, an accuracy of 82.6%, a sensitivity of 100%, and a specificity of 76.5%. CONCLUSION: Diffusion-weighted MR imaging is imaging parameter that can be used for differentiation of benign from malignant paraspinal neurogenic tumors.

Characterization of Parotid Tumors With Dynamic Susceptibility Contrast Perfusion-Weighted Magnetic Resonance Imaging and Diffusion-Weighted MR Imaging.

PURPOSE: To characterize parotid tumors with dynamic susceptibility contrast perfusion-weighted magnetic resonance (MR) imaging and diffusion-weighted MR imaging. MATERIAL AND METHODS: Prospective study was conducted upon 48 consecutive patients (27 men, 21 women; aged 15-75 years; mean, 45 years) with parotid tumors that underwent dynamic susceptibility contrast perfusion-weighted MR imaging was performed after bolus injection of gadopentate dimeglumine and diffusion-weighted MR imaging. The dynamic susceptibility contrast percentage (DSC%) and apparent diffusion coefficient (ADC) values of parotid tumors were calculated and correlated with histopathological findings. RESULTS: The DSC% of malignant parotid tumors (33.53% ± 3.99%) was significantly different (P = 0.001) from that of benign parotid tumors (22.29% ± 4.13%). The threshold values of DSC% and ADC used in differentiating malignant from benign parotid tumors were 26.5% and 1.07 × 10 mm/s, respectively, with area under the curve (AUC) of 0.96 and 0.81, respectively. The DSC% of malignant parotid tumors was significantly different from that of Warthin tumors (P = 0.001). The cutoff DSC% used to differentiate malignancy from Warthin tumors was 26.9% with an AUC of 0.99. There was a significant difference in DSC% and ADC values between pleomorphic adenomas and Warthin tumors (P = 0.001). The threshold values of DSC% and ADC used in differentiating pleomorphic adenomas from Warthin tumors was 22.5% and 0.99 × 10 mm/s, respectively, with AUC of 0.88 and 0.98, respectively. CONCLUSIONS: Dynamic susceptibility contrast-enhanced perfusion-weighted MR imaging and diffusion-weighted MR imaging are noninvasive promising methods that are used for differentiation of malignant from benign parotid tumors and for characterization of some benign parotid tumors.

Pilot study of ultrasound parotid imaging reporting and data system (PIRADS): Inter-observer agreement.

AIM: To establish proposal ultrasound parotid imaging reporting and data system (PIRADS) for classification and prediction of malignancy of parotid lesions and to assess the inter-observer agreement of this system. SUBJECTS AND METHODS: Retrospective analysis of ultrasound and power Duplex images of 142 patients with parotid lesions by two reviewers. Parotid focal lesions were classified into nine patterns and then categorized into five groups: PIRADS 1, definitively benign; PIRADS 2, probably benign; PIRADS 3, indeterminate; PIRADS 4, probably malignant; and PIRADS 5, highly suggestive malignant. THE RESULTS: There was excellent interobserver agreement of both reviewers for patterns and PIRADS (K=0.84, P=0.001) with 92% percent agreement. There was excellent agreement of PIRADS 1 (K=1.00, P=0.001), PIRADS 2 (K=0.97, P=0.001), PIRADS 3 (K=0.86, P=0.001) and PIRADS 5 (K=0.88, P=0.001) and good agreement of PIRADS 4 (K=0.67, P=0.001). The Odds ratio of PIRADS 3, 4 and 5 were 1.36 (95% CI=0.39-4.55), 7.11 (95% CI=3.02-11.15) and 8.27 (95% CI=3.49-10.27) respectively. The accuracy was 92% and 90%, sensitivity was 79% and 65%, specificity was 94% and 96% of PIRADS of both reviewers respectively. CONCLUSION: The proposed PIRADS is a reliable non-invasive imaging modality that can be used for categorizing parotid lesions and prediction of malignancy.