In:
Journal of Computer Assisted Tomography, Ovid Technologies (Wolters Kluwer Health), Vol. 46, No. 5 ( 2022-9), p. 815-822
Abstract:
This study systematically compared the images from readout-segmented echo-planar diffusion-weighted imaging (RESOLVE-DWI [RS-DWI]) and simultaneous multislice accelerated RESOLVE-DWI (SMS-RS-DWI) in patients with nasopharyngeal carcinoma (NPC) in qualitative and quantitative aspects. Method Forty-four patients with NPC were included. The RS-DWI and prototypic SMS-RS-DWI sequences were performed on all patients. Images were qualitatively evaluated by 4 independent radiologists using a 5-point Likert scale. For quantitative evaluation, the maximum and minimum diameters and the maximum tumor areas were determined for both DWI sequences and compared with the T2-weighted imaging (T2WI) to evaluate image distortions. The apparent diffusion coefficient was measured in the slice with the maximum tumor profile. Results The SMS-RS-DWI was superior to RS-DWI with respect to overall image quality (3.40 ± 0.53 vs 2.71 ± 0.48, P 〈 0.0001) and tumor edge sharpness (3.29 ± 0.65 vs 2.64 ± 0.47, P 〈 0.0001). Susceptibility artifacts were significantly less severe in SMS-RS-DWI than in RS-DWI (0.85 ± 0.57 vs 1.36 ± 0.57, P 〈 0.0001). There was no significant overestimation or underestimation of the tumor geometry using the SMS-RS-DWI or RS-DWI compared with T2WI. The quantitative analysis showed a slightly higher agreement for SMS-RS-DWI with T2WI than RS-DWI for maximum diameter, minimum diameter, and maximum tumor area. The apparent diffusion coefficient values showed no significant differences between the 2 DWI techniques ( P 〉 0.05). Conclusions At 3 T, SMS-RS-DWI is a useful technique for diagnosing NPC. It substantially improves different aspects of image quality by providing higher spatial resolution and fewer susceptibility artifacts with more extensive anatomic coverage compared with RS-DWI.
Type of Medium:
Online Resource
ISSN:
1532-3145
,
0363-8715
DOI:
10.1097/RCT.0000000000001327
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2022
detail.hit.zdb_id:
2039772-0
