Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice
Introduction
Head and neck cancers comprise a wide range of histological types since they arise from different tissues in this complex region. Magnetic resonance (MR) imaging is more useful than other imaging techniques for anatomical assessment of these head and neck cancers, especially for mapping the primary tumor’s extent and identifying scar tissue post treatment. This anatomical information is complementary to computed tomography (CT) and 2-[18 F]-fluoro-2-deoxy-D-glucose (FDG) positron-emission tomography (PET) for oncological imaging of the head and neck. Moreover, MR imaging is a versatile technique that has the advantage of providing not only anatomical information but also molecular, metabolic, and physiological information. Therefore, head and neck MR imaging has been frequently used for various clinical purposes in routine clinical practice, although the resultant increase in examination time is considered one of the drawbacks [1,2]. For routine clinical practice, therefore, reducing examination time for certain sequences, especially MR imaging for obtaining anatomical information, might be essential.
Since the beginning of the 2000s, improving temporal and spatial resolution for MR imaging have been tested, not only by using image domain-based parallel imaging (PI) techniques, but also the k-space domain-based parallel imaging technique for 1.5 and 3 Tesla(T) MR systems [3]. However, it has been suggested that the advantages of a reduction in examination time and improvements in temporal and spatial resolution by using PI are limited due to the increase in the number of coil elements. Compressed sensing (CS) has recently been introduced as a new method for reducing the number of k-space samples by exploiting compressibility or sparsity in an appropriate transform domain [4]. However, it has been found that one of the drawbacks of simply reducing k-space sampling for CS may be relatively lower signal-to-noise ratio (SNR) than PI. This situation led to the recent development of new CS methods by a few MR vendors. These methods were combined PI with CS and clinically tested for body MR imaging in various organs. In routine clinical practice, T2 weighted image is one of key sequences for head and neck MR imaging in clinical practice because it shows good contrast of multiple fine structures in head and neck. Although a few investigators had tested the utility of CS accelerated T2 weighted sequences in the internal auditory canal and brain [5,6], no major studies have been reported for assessing the utility of PI with CS for T2 weighted image of head and neck MR imaging.
We hypothesized that a newly developed PI with CS could improve the image quality and shorten examination time for head and neck MR imaging as compared with PI. The purpose of this study was to directly compare the capability of compressed sensing (CS) and parallel imaging (PI) accelerated T2 FSE (Fast Spin Echo) sequence with PI for head and neck MR imaging.
Section snippets
Protocol, support, and funding
This retrospective study was approved by the Institutional Review Board of Fujita Health University School of Medicine, and technically and financially supported by Canon Medical Systems Corporation. Written informed consents was provided to all subjects in this study. One of the authors is an employee of Canon Medical Systems (K.Y) but did not have control over any of the data used in this study.
Subjects
During June and August 2019, 30 consecutive patients with various head and neck diseases (15 men
Results
Representative cases are shown in Fig. 3, Fig. 4. Mean examination time for PI with CS (83.5 ± 11.0 s) was significantly shorter than that for PI (173.0 ± 54.4 s, p < 0.0001).
A comparison of quantitatively assessed image quality is shown in Fig. 5. Quantitative image indexes, SNR and CNR of PI with CS (SNR: mean ± standard deviation, 11.2 ± 3.6, CNR: median, 7.4 [interquartile range, 5.5–9.4]) were significantly better than those of PI (SNR: 8.9 ± 2.6, p < 0.0001; CNR: 6.1 [4.5–7.5],
Discussion
Our results demonstrate that PI with CS has the capability to reduce examination time while improving quantitative image quality indexes as compared with PI with CS and PI for head and neck MR examinations using a 3 T MR system. In addition, qualitative image quality indexes and diagnostic confidence level showed no significant differences between PI with CS and PI in this setting. Although a few investigators evaluated the utility of CS for T2-weighted imaging in different anatomical regions [5
CRediT authorship contribution statement
Hirotaka Ikeda: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Visualization, Writing - original draft, Writing - review & editing. Yoshiharu Ohno: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Visualization, Writing - original draft, Writing - review & editing. Kazuhiro Murayama: Data curation, Methodology, Project administration,
Declaration of Competing Interest
This study was technically and financially supported by Canon Medical Systems Corporation, Japan. Among the authors, Drs. Ohno, Murayama and Toyama got research grants from Canon Medical Systems Corporation, Japan. Ms. Yamamoto is an employee of Canon Medical System Corporation, but did not have control over any of the data and information submitted for publication or which data and information were to be included in this study. Mr. Iwase, Mr. Fukuba and I (i.e. Dr. Ikeda) have nothing to
Acknowledgements
The authors wish to thank Daiki Tabata, RT and Saki Takeda, RT (Department of Radiology, Fujita Health University Hospital), Yuichiro Sano, RT and Masato Ikedo, MEng (Canon Medical Systems Corporation) for their outstanding contributions to this work. This study was financially and technically supported by Canon Medical Systems Corporation.
References (27)
Measures of interrater agreement
J. Thorac. Oncol.
(2011)- et al.
Recent advances in MRI of the head and neck, skull base and cranial nerves: new and evolving sequences, analyses and clinical applications
Br. J. Radiol.
(2019) - et al.
Functional magnetic resonance imaging of head and neck cancer: performance and potential
Neuroradiol. J.
(2019) - et al.
Parallel MR imaging
J. Magn. Reson. Imaging
(2012) - et al.
Compressed sensing for body MRI
J. Magn. Reson. Imaging
(2017) - et al.
Magnetic resonance imaging of the brain using compressed sensing - quality assessment in daily clinical routine
Clin. Neuroradiol.
(2020) - et al.
Accelerated internal auditory canal screening magnetic resonance imaging protocol with compressed sensing 3-Dimensional T2-Weighted sequence
Invest. Radiol.
(2018) - et al.
SENSE: sensitivity encoding for fast MRI
Magn. Reson. Med.
(1999) - et al.
ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA
Magn. Reson. Med.
(2014) - et al.
Sparse MRI: The application of compressed sensing for rapid MR imaging
Magn. Reson. Med.
(2007)
Accuracy of the compressed sensing accelerated 3D-FLAIR sequence for the detection of MS plaques at 3T
AJNR Am. J. Neuroradiol.
Compressed sensing-sensitivity encoding (CS-SENSE) accelerated brain imaging: reduced scan time without reduced image quality
AJNR Am. J. Neuroradiol.
Effect of field strength on MR images: comparison of the same subject at 0.5, 1.0, and 1.5 T
Radiographics
Cited by (12)
Compressed sensing with deep learning reconstruction: Improving capability of gadolinium-EOB-enhanced 3D T1WI
2024, Magnetic Resonance ImagingMR imaging for shoulder diseases: Effect of compressed sensing and deep learning reconstruction on examination time and imaging quality compared with that of parallel imaging
2022, Magnetic Resonance ImagingCitation Excerpt :Therefore, the aforementioned threshold for the wavelet transformation in the case of CS may be considered significatively useful for reduction of examination time and should be used together with DLR in routine clinical practice. These conclusions are mostly compatible with those mentioned in previous literature [15,16,18]. For qualitative image quality assessments, we evaluated interobserver agreement for each index and determined that the qualitative evaluations in our study were moderate, substantial or almost perfect and can thus be considered reproducible becauseκranged from 0.50 to 0.83.
Echo planar imaging with compressed sensitivity encoding (EPICS): Usefulness for head and neck diffusion-weighted MRI
2022, European Journal of RadiologyMagnetic Resonance Imaging of Head and Neck Emergencies, a Symptom-Based Review, Part 1: General Considerations, Vision Loss, and Eye Pain
2022, Magnetic Resonance Imaging Clinics of North America