Related Experiment Video
Updated: Sep 4, 2025

Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
Published on: December 9, 2010
Evaluating of the Quality of Hepatic Diffusion Weighted Imaging Using Multiband Imaging With Variable-Rate Selective
Naofumi Yoshida1, Takeshi Nakaura1, Kosuke Morita2
1From the Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University.
Objective:
To assess the image quality of diffusion-weighted imaging (DWI) using multiband (MB) imaging with variable-rate selective excitation (VERSE) and compare it to conventional DWI.
Methods:
We retrospectively evaluated hepatic DWI images of patients (n = 76) according to either the conventional method (SENSE, acceleration factor = 2) (n = 38) or fast scanning method (MB imaging with VERSE, acceleration factor = 2 × 2) (n = 38). We also conducted a volunteer study (n = 15) for those scanning methods. During quantitative analysis, the signal-to-noise ratio (SNR), apparent diffusion coefficient values, and contrast in the liver, spleen, and spinal cord were compared between the 2 groups. During qualitative analysis, all images were independently and blindly evaluated by 2 board-certified radiologists. The image contrast, noise, artifacts, and sharpness were assessed, and the performance of classification was measured using receiver operating characteristic curve analysis.
Results:
In the retrospective study, the SNRs of the hepatic parenchyma and spinal cord between the 2 protocols were significantly different (liver, 8.9 [interquartile range {IQR}, 7.6-12.2] vs 13.0 [IQR, 10.0-16.7]; P < 0.001 and spinal cord, 6.0 [IQR, 4.7-9.4] vs 4.3 [IQR, 3.8-6.8]; P < 0.02). No significant differences between the 2 protocols in the other retrospective analyses were noted. In the receiver operating characteristic curve analysis, area under the curve was 0.49 (95% confidence intervals, 0.40-0.58).
Conclusion:
Multiband VERSE reduced scan time and SNR of hepatic DWI; however, subjective image quality parameters were not significantly impacted.
More Related Videos
15:48Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
09:04In Vivo Tracking of Edema Development and Microvascular Pathology in a Model of Experimental Cerebral Malaria Using Magnetic Resonance Imaging
Published on: June 8, 2017