Simultaneous multi-slice MR imaging of the hip at 3 T to reduce acquisition times and maintain image quality

Abstract Background Newly developed simultaneous multi-slice (SMS) scans are now being introduced as a clinical application in neuroimaging. We examined the feasibility of SMS scans for joint imaging. The purpose of the present study was to prospectively compare the resolution and specific absorption rate (SAR) obtained using SMS to those of conventional methods in hip joint magnetic resonance imaging (MRI) and establish whether imaging times may be reduced using SMS in 3 T MRI and if image quality is affected. Methods Twenty-one patients (4 men and 17 women, average age, 51.5 years, range: 22 to 76 years) with hip pain underwent MR examinations of the unilateral hip joint. Three board-certified radiologists independently and blindly evaluated the images obtained with and without SMS using window and level settings and magnification according to personal preferences. Individual SAR values were measured for each protocol. A Wilcoxon signed-rank test and a t-statistic test were used for statistical analyses. Signal-to-noise ratio (SNR) was also compared using a phantom. Results SMS imaging maintained equivalent image quality to conventional imaging for evaluating the morphology of the hip joint, and also reduced imaging times by approximately 40%. SMS images had significantly higher SAR values than conventional images. The rate of difference (SMS/conventional) in SNR ranged between 80 and 111%. Conclusions Based on its significantly lower acquisition times and the maintenance of similar image quality to conventional imaging, SMS may be applied to morphological evaluations of hip joint disorders without significantly increasing SAR

The annual rate of coronary artery calcification with combination therapy with a PCSK9 inhibitor and a statin is lower than that with statin monotherapy

Coronary artery calcification: entry to new frontier of PCSK9 inhibitors Today, rapid aging in society is making progress in developed countries. One of the most serious health problems in an aging society is atherosclerosis, of which final phase is coronary artery calcification (CAC). CAC could increase the risk of complications during coronary catheterization and coronary artery bypass surgery as well as ischemic heart disease (IHD). We, members in the aging society, would see much more patients with CAC in the near future. We, however, have no medications for CAC today. Moreover, statins that are used in the world have been known for CAC formation after long-term use. The team led by Yuichi Ikegami and Ikuo Inoue in Japan’s Saitama Medical University found that CAC in patients with atherosclerosis is improved by PCSK9 inhibitors compared to statins by using coronary computed tomographic angiography. This study shows us a hint that could lead us to new preventive therapies of IHD

The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network

Abstract We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comprised 100 participants with renal dysfunction (RD; eGFR < 45 mL/min/1.73 m2) and 70 without (non-RD; eGFR ≥ 45 mL/min/1.73 m2). The model was applied to the right, left, and both kidneys; it was first evaluated on the non-RD group data and subsequently on the combined data of the RD and non-RD groups. For bilateral kidney segmentation of the non-RD group, the best performance was obtained when using IP image, with a Dice score of 0.902 ± 0.034, average surface distance of 1.46 ± 0.75 mm, and a difference of − 27 ± 21 mL between ground-truth and automatically computed volume. Slightly worse results were obtained for the combined data of the RD and non-RD groups and for unilateral kidney segmentation, particularly when segmenting the right kidney from the OP images. Our 3D CNN-assisted automatic segmentation tools can be utilized in future studies on total kidney volume measurements and various image analyses of a large number of patients with CKD