Background: Reactive stroma is recognized as one of the independent prognostic factors in prostate cancer (PCa). Intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) may be useful for assessing the reactive stromal grade (RSG). Purpose: To investigate whether IVIM and DKI models can evaluate RSG in PCa patients. Study Type: Retrospective. Subjects: A total of 56 PCa patients aged 73 years on average confirmed by MRI and transrectal ultrasound (MRI/TRUS) fusion biopsy divided into two subgroups (18 high RSG and 38 low RSG).

Objective. To evaluate the different pharmacokinetic parameters of the DCE-MRI method on diagnosing and staging of rabbits’ liver fibrosis. Methods. We had performed DCE-MRI for rabbits that had been divided into the experiment group and the control group. Then, rabbits’ images were transferred to a work station to get three parameters such as Ktrans, Kep, and Ve, which had been measured to calculate. After data were analyzed, ROC analyses were performed to assess the diagnostic performance of Ktrans, Kep, and Ve to judge liver fibrosis. Results. The distribution of the different liver fibrosis group was as follows: F1, n = 8; F2, n = 9; F3, n = 6; F4, n = 5. No fibrosis was deemed as F0, n = 6. Kep is statistically significant P < 0.05 for F0 and mild liver fibrosis stage, and the Kep shows AUC of 0.814. Three parameters are statistically significant for F0 and advanced liver fibrosis stage (Ktrans and Kep, P < 0.01 ; Ve, P < 0.05 ), and the Ktrans shows AUC of 0.924; the Kep shows AUC of 0.909; the Ve shows AUC of 0.848; Ktrans and Kep are statistically significant for mild and advanced liver fibrosis stages (Ktrans, P < 0.01 ; Kep, P < 0.05 ), and the Ktrans shows AUC of 0.840; the Kep shows AUC of 0.765. Both Ktrans and Kep are negatively correlated with the liver fibrosis stage. Ve is positively correlated with the liver fibrosis stage. Conclusion. Ktrans is shown to be the best DCE parameter to distinguish the fibrotic liver from the normal liver and mild and advanced fibrosis. On the contrary, Kep is moderate and Ve is worst. And Kep is a good DCE parameter to differentiate mild fibrosis from the normal liver.

Background: This study aimed to evaluate the diagnostic accuracy of diffusion kurtosis imaging (DKI) in differentiating early hepatic fibrosis (HF) from normal liver and advanced HF in rabbits.Methods: A total of 35 healthy New Zealand white rabbits were included in the study. A model of HF was established in 30 rabbits through subcutaneous injections of 50% carbon tetrachloride (CCl 4 )/olive oil, while 5 rabbits received saline injections. The gradually increased doses of CCl 4 were 0.1, 0.2, and 0.3 mL/kg in weeks 1 to 3, weeks 4 to 6, and weeks 7 to 10, respectively. Two injections were given each week. Two rabbits in the experimental group died. All rabbits underwent DKI with three b values (0, 500, and 1,000 s/mm 2 ) at week 5 (n=8), week 6 (n=9), week 7 (n=8), and week 10 (n=8). Approximately 2 liver lobes per rabbit were selected for histopathology. Mean diffusivity (MD) and mean kurtosis (MK) were calculated. Discrimination capacities of DKI parameters were analyzed and compared by receiver operating characteristic (ROC) analysis. Results:The meta-analysis of histological data in viral hepatitis (METAVIR) scoring system was used to classify liver lobes into the control group (F0, n=0), early HF group (F1-F2, n=28), and advanced HF group (F3-F4, n=28). MD and MK values were significantly different among the three groups (all P<0.05). MD value was negatively correlated with increased fibrosis level, while MK value was positively correlated with increased fibrosis level (ρ=−0.540, 0.614; P<0.05). The area under ROC curves (AUCs) for MD and MK were 0.886 and 0.875, respectively, for characterization of F0 and F1-F2, and 0.975 and 0.957 for F0 and F3-F4. AUC for MK was 0.751 for characterization of F1-F2 and F3-F4. MD performed better than MK for characterization of F0 and F1-F2 as well as F0 and F3-F4. MK showed good differentiation performance between F1-F2 and F3-F4.Conclusions: Our results showed that DKI contributed to discriminating reversible early HF from normal liver and advanced HF and as a result, showed promise for use in HF diagnosis.

Levothyroxine is a common prescribed drug. Many medications and food, however, can interfere with its bioavailability. The aim of this review was to summarize the medications, food and beverages that interact with levothyroxine and to assess their effects, mechanisms and treatments. Methods: A systematic review on interfering substances that interact with levothyroxine was performed. Web of Science, Embase, PubMed, the Cochrane library, grey literature from other sources and the lists of references were searched for human studies comparing the levothyroxine efficacy with and without interfering substances. The patient characteristics, drug classes, effects and mechanism were extracted. The NHLBI study quality assessment tools and the JBI critical appraisal checklist were used to assess the quality of included studies. Results: A total of 107 articles with 128 studies were included. Drugs interactions were revealed in calcium and iron supplements, proton pump inhibitors, bile acid sequestrants, phosphate binders, sex hormones, anticonvulsants and other drugs. Some food and beverage could also induce malabsorption. Proposed mechanisms included direct complexing, alkalization, alteration of serum thyroxine-binding globulin levels and acceleration of levothyroxine catabolism via deiodination. Dose adjustment, administration separation and discontinuation of interfering substances can eliminate the interactions. Liquid solutions and soft-gel capsules could eliminate the malabsorption due to chelation and alkalization. The qualities of most included studies were moderate. Conclusion: Lots of medications and food can impair the bioavailability of levothyroxine. Clinicians, patients and pharmaceutical companies should be aware of the possible interactions. Further well-designed studies are needed to provide more solid evidence on treatment and mechanisms.

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