Free-breathing contrast-enhanced multiphase MRI of the liver in patients with a high risk of breath-holding failure: comparison of compressed sensing-accelerated radial and Cartesian acquisition techniques

Background Knowing the advantages and disadvantages of each magnetic resonance (MR) technique, would allow us to choose a sequence better suited in patients with a high risk of breath-holding failure. Purpose To compare the image quality of free-breathing contrast-enhanced multiphase MR imaging (MRI) using incoherent Cartesian k-space sampling combined with a motion-resolved compressed sensing reconstruction (XD-VIBE) and Golden-Angle Radial Sparse Parallel MRI (GRASP). Material and Methods A total of 67 patients were included. Overall image quality, motion artifacts, and liver edge sharpness on arterial and portal-venous phase were evaluated by two radiologists. We evaluated the signal intensity ratio between liver in the late arterial phase to aorta at peak enhancement and the detection rate of hypervascular lesions. Results Overall image quality, artifact, and liver edge sharpness scores of XD-VIBE and GRASP were not significantly different ( P = 0.070–0.397). Four (reviewer 1, 12.1%) and seven patients (reviewer 2, 21.2%) received non-diagnostic quality in the XD-VIBE group whereas one patient (reviewer 2, 2.9%) received non-diagnostic quality in the GRASP group. The ratio between the aorta and liver signal for GRASP was significantly higher than that of XD-VIBE (0.32 ± 0.10 vs. 0.47 ± 0.13; P < 0.001). The hypervascular lesion detection rate of XD-VIBE (86.7%) was higher than that of GRASP (57.1%) in the arterial phase without a statistically significant difference ( P = 0.081). Conclusion Overall image quality of XD-VIBE and GRASP were not significantly different. More XD-VIBE examinations were rated non-diagnostic. On the other hand, the relative liver parenchymal enhancement to the aorta in the late arterial phase of GRASP was higher than that of XD-VIBE, which potentially leads to lower detectability of hypervascular lesions on arterial phase images.

Edge Detection Algorithm Based on BEMD for Liver CT Images

Liver edge identification requires for its volume estimation from CT image and this process is a prerequisite for liver diagnosis and treatment planning. In this article, an edge detection algorithm proposed based on Bi-dimensional Empirical Mode Decomposition (BEMD) and Fourier Transform. Intrinsic mode function (IMF) extracted from BEMD and mixed with the Fourier phase of the original image to get edge profile. The proposed method extensively evaluated on Berkeley Segmentation Data Set (BSDS-500) and compared with Sobel and Canny operators. Results achieved Mean Square error 0.04±0.01 and PSNR 62.27±1.1. In conclusion, The BEMD approach capable of identifying image edges with high accuracy compared with state of the art.

Accuracy of Routine Clinical Ultrasound for Staging of Liver Fibrosis

Objective: To determine the diagnostic accuracy of routine clinical ultrasound in the staging of liver fibrosis in chronic viral hepatitis. Materials and Methods: A retrospective evaluation of the ultrasound images of 156 patients with chronic viral hepatitis who underwent liver biopsy was performed. Two radiologists in consensus, blind to the biopsy results and clinical details, evaluated the ultrasound images for liver fibrosis. The readers specifically assessed three features — surface nodularity, liver edge, and parenchymal echotexture — with scores of 0 to 3 (0 = normal, 1 = mild, 2 = moderate, 3 = severe). Accuracies of each sonographic feature for the detection of mild fibrosis and above (≥F1), significant fibrosis (≥F2), severe fibrosis (≥F3), and cirrhosis (F4) were determined with histopathology as the reference standard. Results: Fibrosis was present in 99 patients (F1=34, F2=20, F3=22, and F4=23) and absent in 57 patients. The sensitivities for the detection of significant fibrosis with surface nodularity, liver edge, and parenchymal echotexture were 57%, 15%, and 41%, respectively. The accuracies for the detection of ≥F1, ≥F2, ≥F3, and F4 stages were 50.5%, 59%, 59%, and 65% for liver surface, 51%, 53%, 54%, and 55% for liver edge, and 58%, 59%, 63%, and 63% for parenchyma echotexture, respectively. The combined scores from all three features had accuracies of 56%, 59%, 62%, and 66% for the detection of ≥F1, ≥F2, ≥F3, and F4, respectively. Conclusion: Routine clinical ultrasound is a not a sensitive predictor of early fibrosis in chronic viral hepatitis. Surface nodularity is the most sensitive sonographic feature for the detection of significant fibrosis and routine clinical ultrasound is the most useful for the detection of cirrhosis.

Clinical Estimation of Liver Size in Newborn Infants

In Reply.— Brion and Avni have compared the clinical estimation of liver size by the liver span and the size of its edge below the right costal margin. Some of their results are in accordance with ours, such as the lack of differences between the measurements immediately after birth and a few days later, and the reduced size of liver edge found in our preliminary measurements in infants who were small for gestational age (Table). It seems to us that the practical approach to the clinical estimation of liver size in the newborn should include routine measurement of liver edge in every healthy newborn infant.