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. 2020 Dec;21(12):1367-1373.
doi: 10.3348/kjr.2019.0824. Epub 2020 Jul 27.

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

Affiliations

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

Ahmed Abdel Khalek Abdel Razek et al. Korean J Radiol. 2020 Dec.

Abstract

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.

Keywords: Biliary atresia; Diffusion tensor imaging; Infant; Jaundice.

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Conflict of interest statement

The authors have no potential conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1. Localization of ROIs.
MD map showing localization of three ROIs within hepatic parenchyma. MD = mean diffusivity, ROIs = regions of interest
Fig. 2
Fig. 2. Liver biopsy of 2 infants with cholestasis.
A. Case of BA showing portal tract expansion by loose fibrous tissue containing irregularly anastomosing bile ductules at the periphery, some being dilated with inspissated bile in their lumen. B. Case of ALGS with portal area containing vessels but no ducts “unpaired artery” without cholangiolar proliferation (both are H & E stain, with magnification × 10). ALGS = Alagille syndrome, BA = biliary atresia
Fig. 3
Fig. 3. ROC of MD used to differentiate BA from ALGS.
MD of 1.77 and 1.79 × 10−3 mm2/s as threshold value for differentiating BA from ALGS shows accuracies of 82% and 79%, sensitivities of 91% and 83%, specificities of 80% and 83%, and AUCs of 0.90 and 0.91 for both reviewers, respectively. AUC = area under the curve, ROC = receiver operating characteristic
Fig. 4
Fig. 4. ROC of FA used to differentiate BA from ALGS.
FA of 0.30, 0.28 as threshold value for differentiating BA from ALGS shows accuracies of 79% and 82%, sensitivities of 81% and 93%, specificities of 58% and 50%, and AUCs of 0.69 and 0.68 for both readers, respectively. FA = fractional anisotropy

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