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We observed liver failure with a presumed etiology of echinococcosis in an 89-year-old woman. Our patient had been born and then resided on Rebun Island until she was 12 years old. At 46 years old, she had been referred to our hospital due to right abdominal pain. Ultrasound had revealed multilocular cysts in the right lobe of the liver. At 84 years old, the hepatic cyst occupied nearly the entire liver with ring-shaped calcification along the cyst wall. The patient was diagnosed with decompensated cirrhosis and hepatic hydatid disease based on typical imaging and the long-term natural clinical course.

Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = −0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.

This research was aimed at making a robot that can go and get an object designated by the user. We produced a robot control system that uses pointing and voice control. This control system is composed of two systems. One system is the object instruction system that uses pointing, and the other is the object instruction system that uses voice. The approximate position of a designated object is recognized by the object instruction system that uses pointing, and information about the object and instructions about the operation are conveyed by the object instruction system that uses voice. This time, the object instruction system that uses pointing has been designed and verified as the first step. A calculation resource to calculate the approximate position of the designated object is obtained when the user points directly at the object. A robot can be moved around a designated object by using this system. The object instruction system that uses voice will be constructed in future work.