Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Medical Imaging
Published in: BMC Medical Imaging 1/2020

Open Access 01-12-2020 | Parotid Gland Tumor | Research article

Feasibility study of using simultaneous multi-slice RESOLVE diffusion weighted imaging to assess parotid gland tumors: comparison with conventional RESOLVE diffusion weighted imaging

Authors: Jia-Suo Jiang, Liu-Ning Zhu, Qian Wu, Yi Sun, Wei Liu, Xiao-Quan Xu, Fei-Yun Wu

Published in: BMC Medical Imaging | Issue 1/2020

Login to get access

Abstract

Background

To evaluate the feasibility of using simultaneous multi-slice (SMS) readout segmentation of long variable echo-trains (RESOLVE) diffusion-weighted imaging (DWI) to assess parotid gland tumors, compared with conventional RESOLVE DWI.

Methods

From September 2018 to December 2018, 20 consecutive patients with parotid tumors who underwent MRI scan for pre-surgery evaluation were enrolled. SMS-RESOLVE DWI and conventional RESOLVE DWI were scanned with matched imaging parameters, respectively. The scan time of two DWI sequences was recorded. Qualitative (anatomical structure differentiation, lesion display, artifact, and overall image quality) and quantitative (apparent diffusion coefficient, ADC; ratio of signal-to-noise ratio, SNR ratio; ratio of contrast-to-noise ratio, CNR ratio) assessments of image quality were performed, and compared between SMS-RESOLVE DWI and conventional RESOLVE DWI by using Paired t-test. Two-sided P value less than 0.05 indicated significant difference.

Results

The scan time was 3 min and 41 s for SMS-RESOLVE DWI, and 5 min and 46 s for conventional RESOLVE DWI. SMS-RESOLVE DWI produced similar qualitative image quality with RESOLVE DWI (anatomical structure differentiation, P = 0.164; lesion display, P = 0.193; artifact, P = 0.330; overall image quality, P = 0.083). Meanwhile, there were no significant difference on ADCLesion (P = 0.298), ADCMasseter (P = 0.122), SNR ratio (P = 0.584) and CNR ratio (P = 0.217) between two DWI sequences.

Conclusion

Compared with conventional RESOLVE DWI, SMS-RESOLVE DWI could provide comparable image quality using markedly reduced scan time. SMS could increase the clinical usability of RESOLVE technique for DWI of parotid gland.
Literature
1.
Yuan Y, Tang W, Tao X. Parotid gland lesions: separate and combined diagnostic value of conventional MRI, diffusion-weighted imaging and dynamic contrast-enhanced MRI. Br J Radiol. 2016;89(1060):20150912.PubMedPubMedCentralCrossRef
2.
Ma G, Zhu LN, Su GY, Hu H, Qian W, Bu SS, et al. Histogram analysis of apparent diffusion coefficient maps for differentiating malignant from benign parotid gland tumors. Eur Arch Otorhinolaryngol. 2018;275(8):2151–7.PubMedCrossRef
3.
Yabuuchi H, Kamitani T, Sagiyama K, Yamasaki Y, Hida T, Matsuura Y, et al. Characterization of parotid gland tumors: added value of permeability MR imaging to DWI and DCE-MRI. Eur Radiol. 2020; Online ahead of print..
4.
Jiang JS, Zhu LN, Chen W, Chen L, Su GY, Xu XQ, et al. Added value of susceptibility-weighted imaging to diffusion-weighted imaging in the characterization of parotid gland tumors. Eur Arch Otorhinolaryngol. 2020; Online ahead of print.
5.
Zhu L, Wang J, Shi H, Tao X. Multimodality fMRI with perfusion, diffusion-weighted MRI and 1H-MRS in the diagnosis of lympho-associated benign and malignant lesions of the parotid gland. J Magn Reson Imaging. 2019;49(2):423–32.PubMedCrossRef
6.
Tao X, Yang G, Wang P, Wu Y, Zhu W, Shi H, et al. The value of combining conventional, diffusion-weighted and dynamic contrast-enhanced MR imaging for the diagnosis of parotid gland tumours. Dentomaxillofac Radiol. 2017;46(6):20160434.PubMedPubMedCentralCrossRef
7.
Porter DA, Heidemann RM. High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator based reacquisition. Magn Reson Med. 2009;62(2):468–75.PubMedCrossRef
8.
Xu XQ, Liu J, Hu H, Su GY, Zhang YD, Shi HB, et al. Improve the image quality of orbital 3 T diffusion-weighted magnetic resonance imaging with readout-segmented echo-planar imaging. Clin Imaging. 2016;40(4):793–6.PubMedCrossRef
9.
Kim YJ, Kim SH, Kang BJ, Park CS, Kim HS, Son YH, et al. Readout-segmented echo-planar imaging in diffusion-weighted mr imaging in breast cancer: comparison with single-shot echo-planar imaging in image quality. Korean J Radiol. 2014;15(4):403–10.PubMedPubMedCentralCrossRef
10.
Bogner W, Pinker K, Zaric O, Baltzer P, Minarikova L, Porter D, et al. Bilateral diffusion-weighted MR imaging of breast tumors with submillimeter resolution using readout-segmented echo-planar imaging at 7 T. Radiology. 2015;274(1):74–84.PubMedCrossRef
11.
Xia CC, Liu X, Peng WL, Li L, Zhang JG, Meng WJ, et al. Readout-segmented echo-planar imaging improves the image quality of diffusion-weighted MR imaging in rectal cancer: comparison with single-shot echo-planar diffusion-weighted sequences. Eur J Radiol. 2016;85(10):1818–23.PubMedCrossRef
12.
Xu X, Wang Y, Hu H, Su G, Liu H, Shi H, et al. Readout-segmented echo-planar diffusion-weighted imaging in the assessment of orbital tumors: comparison with conventional single-shot echo-planar imaging in image quality and diagnostic performance. Acta Radiol. 2017;58(12):1457–67.PubMedCrossRef
13.
Setsompop K, Gagoski BA, Polimeni JR, Witzel T, Wedeen VJ, Wald LL. Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. Magn Reson Med. 2012;67(5):1210–24.PubMedCrossRef
14.
Filli L, Ghafoor S, Kenkel D, Liu W, Weiland E, Andreisek G, et al. Simultaneous multi-slice readout-segmented echo planar imaging for accelerated diffusion-weighted imaging of the breast. Eur J Radiol. 2016;85(1):274–8.PubMedCrossRef
15.
Ho M, Becker A, Ulbrich E, Manoliu A, Kuhn FP, Eberhard M, et al. Comparison of simultaneous multi-slice readout-segmented EPI and conventional single-shot EPI for diffusion tensor imaging of the ulnar nerve. Heliyon. 2018;4(10):e00853.PubMedPubMedCentralCrossRef
16.
Chakhoyan A, Leu K, Pope WB, Cloughesy TF, Ellingson BM. Improved spatiotemporal resolution of dynamic susceptibility contrast perfusion MRI in brain tumors using simultaneous multi-slice echo-planar imaging. AJNR Am J Neuroradiol. 2018;39(1):43–5.PubMedCrossRef
17.
Benali S, Johnston PR, Gholipour A, Dugan ME, Heberlein K, Bhat H, et al. Simultaneous multi-slice accelerated turbo spin echo of the knee in pediatric patients. Skelet Radiol. 2018;47(6):821–31.CrossRef
18.
19.
Zhang G, Sun H, Qian T, An J, Shi B, Zhou H, et al. Diffusion-weighted imaging of the kidney: comparison between simultaneous multi-slice and integrated slice-by-slice shimming echo planar sequence. Clin Radiol. 2019;74(4):325.e1–8.CrossRef
20.
Haraikawa M, Suzuki M, Inoue K, Kozawa E, Tanaka J, Niitsu M. Simultaneous multi-slice MR imaging of the hip at 3 T to reduce acquisition times and maintain image quality. BMC Musculoskelet Disord. 2018;19(1):440.PubMedPubMedCentralCrossRef
21.
Boss A, Barth B, Filli L, Kenkel D, Wurnig MC, Piccirelli M, et al. Simultaneous multi-slice echo planar diffusion weighted imaging of the liver and the pancreas: Optimization of signal-to-noise ratio and acquisition time and application to intravoxel incoherent motion analysis. Eur J Radiol. 2016;85(11):1948–55.PubMedCrossRef
22.
Bogner W, Pinker-Domenig K, Bickel H, Chmelik M, Weber M, Helbich TH, et al. Readout-segmented echo-planar imaging improves the diagnostic performance of diffusion-weighted MR breast examinations at 3.0 T. Radiology. 2012;263(1):64–76.PubMedCrossRef
23.
Connolly M, Srinivasan A. Diffusion-weighted Imaging in head and neck cancer: technique, limitations, and applications. Magn Reson Imaging Clin N Am. 2018;26(1):121–33.PubMedCrossRef
24.
Zhao M, Liu Z, Sha Y, Wang S, Ye X, Pan Y, et al. Readout-segmented echo-planar imaging in the evaluation of sinonasal lesions: a comprehensive comparison of image quality in single-shot echo-planar imaging. Magn Reson Imaging. 2016;34(2):166–72.PubMedCrossRef
25.
Zhang W, Zuo Z, Huang X, Jin G, Su D, et al. Value of Diffusion-weighted imaging combined with susceptibility-weighted imaging in differentiating benign from malignant parotid gland lesions. Med Sci Monit. 2018;24:4610–6.PubMedPubMedCentralCrossRef
Metadata
Title
Feasibility study of using simultaneous multi-slice RESOLVE diffusion weighted imaging to assess parotid gland tumors: comparison with conventional RESOLVE diffusion weighted imaging
Authors
Jia-Suo Jiang
Liu-Ning Zhu
Qian Wu
Yi Sun
Wei Liu
Xiao-Quan Xu
Fei-Yun Wu
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Medical Imaging / Issue 1/2020
Electronic ISSN: 1471-2342
DOI
https://doi.org/10.1186/s12880-020-00492-1

Other articles of this Issue 1/2020

BMC Medical Imaging 1/2020 Go to the issue

Research article

Comparison of three dimensional reconstruction and conventional computer tomography angiography in patients undergoing zero-ischemia laparoscopic partial nephrectomy

Case report

False positive finding from malignancy-like lesions on FDG PET/CT: case report of tuberculosis patients

Research article

Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging

Research article

Using CT texture analysis to differentiate between peripheral lung cancer and pulmonary inflammatory pseudotumor

Case report

Advanced hepatic vasculobiliary imaging segmentation and 3D reconstruction as an aid in the surgical management of high biliary stenosis

Technical advance

Deep semi-supervised learning for brain tumor classification