Magnetic Resonance Imaging of the Brain Using Compressed Sensing – Quality Assessment in Daily Clinical Routine

Mönch, Sebastian; Sollmann, Nico; Höck, A.; Zimmer, Claus; Kirschke, Jan S.; Hedderich, Dennis M.

doi:10.1007/s00062-019-00789-x

Cited by 27 publications

(24 citation statements)

References 22 publications

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“…Furthermore, compared with SPEEDER, Compressed SPEEDER can reduce image acquisition time without any degradation of diagnostic confidence. These findings are consistent with our quantitatively assessed image quality evaluations and previous reports [5,13,14,21,[23][24][25]27,[29][30][31]. This indicates that Compressed SPEEDER is useful for faster image acquisition without any degradation of diagnostic confidence level.…”

Section: Discussionsupporting

confidence: 93%

Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

Ueda

Ohno

Yamamoto

et al. 2021

European Journal of Radiology

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To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI. Method: Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test. Results: Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003). Conclusion: Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

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Section: Discussionsupporting

confidence: 93%

Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

Ueda

Ohno

Yamamoto

et al. 2021

European Journal of Radiology

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“…In this study, we applied CS to 3D volumetric T2-weighted brain imaging in children. Image quality improved using CS with 3D T2WI compared to conventional 3D T2WI and this was also observed in a previous study on adult brain imaging 22 . 3D volumetric imaging allows the retrospective analysis of brain structure along many axes which is an advantage over 2D images.…”

Section: Discussionsupporting

confidence: 82%

Accelerated 3D T2-Weighted SPACE Using Compressed Sensing for Paediatric Brain Imaging

Kim¹,

Oh²,

Han³

et al. 2021

Preprint

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The purpose of this study was to compare the image quality of the single-slab, 3D T2-weighted turbo-spin-eco sequence with high sampling efficiency (SPACE) with accelerated SPACE using compressed sensing (CS-SPACE) in paediatric brain imaging. A total of 116 brain MRI (53 in SPACE group and 63 in CS-SPACE group) were obtained from children aged 16 years old or younger. Quantitative image quality was evaluated using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The sequences were qualitatively evaluated for overall image quality, SNR, general artifact, cerebrospinal fluid (CSF)-related artifact and grey-white matter differentiation. The two sequences were compared for the total and for two age groups (< 24 months vs. ≥ 24 months). CS application in 3D T2-weighted imaging resulted in 8.5% reduction in scanning time. Quantitative image quality analysis showed higher SNR (Median [Interquartile range]; 29 [25] vs. 23 [14], P = .005) and CNR (0.231 [0.121] vs. 0.165 [0.120], P = .027) with CS-SPACE compared to SPACE. Qualitative image quality analysis showed better image quality with CS-SPACE for general artifact (P = .024) and CSF-related artifact (P < .001). CSF-related artifacts reduction was more prominent in the older age group (≥ 24 months). Overall image quality (P = .162), SNR (P = .726), and grey-white matter differentiation (P = .397) were comparable between SPACE and CS-SPACE. In conclusion, compressed sensing applied 3D T2-weighted images showed comparable or superior image quality compared to conventional images with reduced acquisition time for paediatric brain.

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“…11,13 Based on the large gradient hardware performance of the employed 3T scanner (Elition, Philips Healthcare) and due to the combination of compressed sensing (CS) with sensitivity encoding (SENSE) parallel imaging, a good signal-to-noise ratio and a short acquisition time can be achieved without the use of additional surface coils. 47,48 Although this study as well as some other recent studies show that MRI is suitable for bone depiction, there is another aspect that needs to be considered in the context of CAS, in particular for the manufacturing of tooth-supported devices like drilling guides, osteotomy guides, or occlusal splints. For this purpose, the occlusal surfaces must be visible at least well enough to be able to be aligned with highly precise virtual models derived from optical surface scans.…”

Section: Discussionmentioning

confidence: 79%

Geometric accuracy of magnetic resonance imaging–derived virtual 3‐dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study

Probst

Burian

Malenova

et al. 2021

Clin Implant Dent Rel Res

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Background: Providing accurate 3-dimensional virtual bone surface models is a prerequisite for virtual surgical planning and additive manufacturing in craniomaxillofacial surgery. For this purpose, magnetic resonance imaging (MRI) may be a radiation-free alternative to computed tomography (CT) and cone beam computed tomography (CBCT).Purpose: The aim of this study was to assess the geometric accuracy of 3-dimensional T1-weighted MRI-derived virtual bone surface models of the mandible in comparison to CT and CBCT.Materials and methods: Specimens of the mandible from porcine cadavers were scanned with (1) a 3-dimensional T1-weighted MRI sequence (0.6 mm isotropic voxel) optimized for bone imaging, (2) CT, and (3) CBCT. Cortical mandibular structures (n = 10) were segmented using semiautomated and manual techniques.Imaging-based virtual 3-dimensional models were aligned with a high-resolution optical 3-dimensional surface scan of the dissected bone (=ground truth) and global geometric deviations were calculated (mean surface distance [MSD]/root-mean-square distance [RMSD]). Agreement between the imaging modalities was assessed by equivalence testing and Bland-Altman analysis.Results: Intra-and inter-rater agreement was on a high level for all modalities. Global geometric deviations (MSD/RMSD) between optical scans and imaging modalities were 0.225 ± 0.020 mm/0.345 ± 0.074 mm for CT, 0.280 ± 0.067 mm/0.371 ± 0.074 mm for MRI, and 0.352 ± 0.076 mm/0.454 ± 0.071 mm for CBCT. All imaging modalities were statistically equivalent within an equivalence margin of ±0.3 mm, and Bland-Altman analysis indicated high agreement as well.

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Magnetic Resonance Imaging of the Brain Using Compressed Sensing – Quality Assessment in Daily Clinical Routine

Cited by 27 publications

References 22 publications

Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

Accelerated 3D T2-Weighted SPACE Using Compressed Sensing for Paediatric Brain Imaging

Geometric accuracy of magnetic resonance imaging–derived virtual 3‐dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study

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