Signal-to-noise ratio assessment of muscle diffusion tensor imaging using single image set and validation by the difference image method

• Published in: British journal of radiology Vol. 92; no. 1102; p. 20190133
• Main Authors: Wang, Zhiyue J., Yamamura, Jin, Keller, Sarah
• Format: Journal Article
• Language: English
• Published: England The British Institute of Radiology 01.10.2019
• Subjects: Adult; Anisotropy; Diffusion Tensor Imaging - methods; Female; Healthy Volunteers; Humans; Male; Muscle, Skeletal - diagnostic imaging; Reproducibility of Results; Signal-To-Noise Ratio; Thigh - diagnostic imaging
• ISSN: 0007-1285; 1748-880X; 1748-880X
• DOI: 10.1259/bjr.20190133

Signal-to-noise ratio (SNR) assessment is essential for accurate quantification of diffusion tensor imaging (DTI) metrics and usually requires the use of a difference image method using duplicate images. We aimed to estimate the SNR of DTI of thigh muscles using a single image set without duplicate images. DTI of one thigh were acquired on a 3 T scanner from 15 healthy adults, and scans with number of signal averages (NSA) = 4 and 8 were repeatedly acquired. SNR were evaluated for six thigh muscles. For SNR calculation from a single image set, diffusion-weighted images with similar diffusion encoding directions were grouped into pairs. The difference image of each pair was high-pass filtered in k-space to yield noise images. Noise images were also calculated with a difference method using two image sets as a reference. Subjects were divided into two groups for filter optimization and validation, respectively. The coefficient of repeatability (CR) of the SNR obtained from the two methods was also evaluated separately. Bland Altman analysis comparing the single image set method and the reference showed 95% limits of agreement of -9.2 to 9.2% for the optimization group and -12.5 to 12.6% for the validation group. The SNR measurement had a CR of 21.1% using the reference method, and 13.8% using the single image set method. The single image method can be used for DTI SNR assessment and offers better repeatability. SNR of skeletal muscle DTI can be assessed for any data set without duplicate images.