Compressed SENSitivity Encoding (SENSE): Qualitative and Quantitative Analysis.

BACKGROUND: This study aimed to qualitatively and quantitatively evaluate T1-TSE, T2-TSE and 3D FLAIR sequences obtained with and without Compressed-SENSE technique by assessing the contrast (C), the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR). METHODS: A total of 142 MRI images were acquired: 69 with Compressed-SENSE and 73 without Compressed-SENSE. All the MRI images were contoured, spatially aligned and co-registered using 3D Slicer Software. Two radiologists manually drew 12 regions of interests on three different structures of CNS: white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF). RESULTS: C values were significantly higher in Compressed-SENSE T1-TSE compared to No Compressed-SENSE T1-TSE for three different structures of the CNS. C values were also significantly lower for Compressed-SENSE 3D FLAIR and Compressed-SENSE T2-TSE compared to the corresponding No Compressed-SENSE scans. While CNR values did not significantly differ in GM-WM between Compressed-SENSE and No Compressed-SENSE for the 3D FLAIR and T1-TSE sequences, the differences in GM-CSF and WM-CSF were always statistically significant. CONCLUSION: Compressed-SENSE for 3D T2 FLAIR, T1w and T2w sequences enables faster MRI acquisition, reducing scan time and maintaining equivalent image quality. Compressed-SENSE is very useful in specific medical conditions where lower SAR levels are required without sacrificing the acquisition of helpful diagnostic sequences.

Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS).

PURPOSE: High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers. METHODS: Thirty-seven patients with pathologically confirmed breast cancer underwent DWIBS, and images were reconstructed using both conventional SENSE (SENSE-DWIBS) and EPICS (EPICS-DWIBS). Two board-certified radiologists independently evaluated lesion conspicuity (LC) and noise using a 5-point grading scale. The same 2 radiologists independently measured SNR, contrast-to-noise ratio (CNR), and the mean cancer ADC. The Pearson coefficient and Bland-Altman plot were applied to assess the accuracy of ADCs. RESULTS: LC scores were higher with EPICS than with SENSE, reaching significance for one reviewer but not the other reviewer. Noise ratings on visual evaluation were significantly lower with EPICS than with SENSE (P < 0.001 for both reviewers). SNR was significantly higher with EPICS than with SENSE (P < 0.005 for both reviewers). CNR was significantly higher with EPICS than with SENSE (P < 0.001 for both reviewers). Bland-Altman plots of cancer ADCs using EPICS-DWIBS and SENSE-DWIBS showed excellent concordance, with a bias of 0.026 × 10-3 mm2/s and limits of agreement ranging 0.054 × 10-3 mm2/s; the Pearson's correlation coefficient was 0.997 (P < 0.0001). CONCLUSION: EPICS enhances breast DWIBS image quality, with improved SNR and CNR and reduced noise levels. The ADCs of breast cancers obtained using EPICS were almost perfectly correlated with those obtained using conventional SENSE.

Acceleration of uterine 3D T2-weighted imaging by compressed SENSE-a multicentre study.

OBJECTIVES: To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI). METHODS: A total of 91 female volunteers from the First Affiliated Hospital of Dalian Medical University, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, and The Fourth Hospital of Harbin were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a 3-point scoring system. Junction zone signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and myometrial SNR were also calculated. Intraclass correlation coefficients were used to analyse the consistency of the measurement results by 2 observers. Analysis of variance test or Friedman rank sum test was used to compare the differences in subjective scores, SNR, and CNR under different AFs/different degrees of fat suppression. RESULTS: Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores. CONCLUSION: The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan. ADVANCES IN KNOWLEDGE: The CS5 has the highest image quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for a female pelvic 3D-ISO-T2WI scan.

Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding.

BACKGROUND: Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues. PURPOSE: To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI. STUDY TYPE: Prospective. POPULATION: Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis). FIELD STRENGTH/SEQUENCE: 3-T, M2C EPICS DWI, and M2C DWI. ASSESSMENT: The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated using aSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale. STATISTICAL TESTS: Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05. RESULTS: In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts. DATA CONCLUSION: Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Feasibility of Artificial Intelligence Constrained Compressed SENSE Accelerated 3D Isotropic T1 VISTA Sequence For Vessel Wall MR Imaging: Exploring the Potential of Higher Acceleration Factors Compared to Traditional Compressed SENSE.

RATIONALE AND OBJECTIVES: Investigate the feasibility of using deep learning-based accelerated 3D T1-weighted volumetric isotropic turbo spin-echo acquisition (VISTA) for vessel wall magnetic resonance imaging (VW-MRI), compared to traditional Compressed SENSE and optimize acceleration factor (AF) to obtain high-quality clinical images. METHODS: 40 patients with atherosclerotic plaques in the intracranial or carotid artery were prospectively enrolled in our study from October 1, 2022 to October 31, 2023 underwent high-resolution vessel wall imaging on a 3.0 T MR system using variable Compressed SENSE (CS) AFs and reconstructed by an optimized artificial intelligence constrained Compressed SENSE (CS-AI). Images were reconstructed through both traditional CS and optimized CS-AI. Two radiologists qualitatively assessed the image quality scores of CS and CS-AI across different segments and quantitatively evaluated SNR (signal-to-noise ratio) and CNR (contrast-to-noise ratio) metrics. Paired t-tests, ANOVA, and Friedman tests analyzed image quality metrics. Written informed consent was obtained from all patients in this study. RESULTS: CS-AI groups demonstrated good image quality scores compared to reference scans until AF up to 12 (P < 0.05). The CS-AI 10 protocol provided the best images in the lumen of both normal and lesion sites (P < 0.05). The plaque SNR was significantly higher in CS-AI groups compared to CS groups until the AF increased to 12 (P < 0.05). CS-AI protocols had higher CNR compared to CS with whichever AF on both pre-and post-contrast T1WI (P < 0.05), The CNR was highest in the CS-AI 10 protocol on pre-contrast T1WI and in CS-AI 12 on post-contrast T1WI (P < 0.05). CONCLUSION: The study demonstrated the feasibility of using CS-AI technology to diagnose arteriosclerotic vascular disease with 3D T1 VISTA sequences. The image quality and diagnostic efficiency of CS-AI images were comparable or better than traditional CS images. Higher AFs are feasible and have potential for use in VW-MRI. The determination of standardized AFs for clinical scanning protocol is expected to help for empirical evaluation of new imaging technology.

Electrophysiological cardiovascular MR: procedure-ready mesh model generation for interventional guidance based on non-selective excitation compressed sensing whole heart imaging.

Fully CMR-guided electrophysiological interventions (EP-CMR) have recently been introduced but data on the optimal CMR imaging protocol are scarce. This study determined the clinical utility of 3D non-selective whole heart steady-state free precession imaging using compressed SENSE (nsWHcs) for automatic segmentation of cardiac cavities as the basis for targeted catheter navigation during EP-CMR cavo-tricuspid isthmus ablation. Fourty-two consecutive patients with isthmus-dependent right atrial flutter underwent EP-CMR radiofrequency ablations. nsWHcs succeeded in all patients (nominal scan duration, 98 ± 10 s); automatic segmentation/generation of surface meshes of right-sided cavities exhibited short computation times (16 ± 3 s) with correct delineation of right atrium, right ventricle, tricuspid annulus and coronary sinus ostium in 100%, 100%, 100% and 95%, respectively. Point-by-point ablation adhered to the predefined isthmus line in 62% of patients (26/42); activation mapping confirmed complete bidirectional isthmus block (conduction time difference, 136 ± 28 ms). nsWHcs ensured automatic and reliable 3D segmentation of targeted endoluminal cavities, multiplanar reformatting and image fusion (e.g. activation time measurements) and represented the basis for precise real-time active catheter navigation during EP-CMR ablations of isthmus-dependent right atrial flutter. Hence, nsWHcs can be considered a key component in order to advance EP-CMR towards the ultimate goal of targeted substrate-based ablation procedures.

Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study.

PURPOSE: To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC). METHODS: This single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test. RESULTS: 67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001-0.039). For clinically-relevant liver lesions, the detection rates (91.4%-93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%-89.8%, p = 0.230-0.231) but were superior to PI-DWI (82.7%-85.8%, p = 0.015-0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%-97.4% vs 76.9%-79.5% vs 64.1%-69.2%, p = 0.002-0.045) among the three DWI sequences. CONCLUSION: In patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome.

Evaluation of Compressed SENSE on Image Quality and Reduction of MRI Acquisition Time: A Clinical Validation Study.

RATIONALE AND OBJECTIVES: To evaluate the effect of compressed SENSE (CS) in clinical settings on scan time reduction and image quality. MATERIALS AND METHODS: Ninety-five magnetic resonance imaging (MRI) scans from different anatomical regions were acquired, consisting of a standard protocol sequence (SS) and sequence accelerated with CS. Anonymized paired sequences were randomly displayed and rated by six blinded subspecialty radiologists. Side-by-side evaluation on perceived sharpness, perceived signal-to-noise-ratio (SNR), lesion conspicuity, and artifacts were compared and scored on a five-point Likert scale, and individual image quality was evaluated on a four-point Likert scale. RESULTS: CS reduced overall scan time by 32% while maintaining acceptable MRI quality for all regions. The largest time savings were seen in the spine (mean = 68 seconds, 44% reduction) followed by the brain (mean = 86 seconds, 37% reduction). The sequence with maximum time savings was intracranial 3D-time-of-flight magnetic resonance angiography (202 seconds, 56% reduction). CS was mildly inferior to SS on perceived sharpness, perceived SNR, and lesion conspicuity (mean scores = 2.32-2.96, P < .001 [1: SS superior; 3: equivalent; 5: CS superior]). CS was equivalent to SS for joint and body scans on overall image quality (CS = 3.02-3.37, SS = 3.04-3.68, P > .05, [1: lowest quality and 4: highest quality]). The overall image quality of CS was slightly less for brain and spine scans (mean CS = 2.79-3.05, mean SS = 3.13-3.43, P = .021) but still diagnostic. Good overall clinical acceptance for CS (88%) was noted with full clinical acceptance for body scans (100%) and high acceptance for other regions (68%-95%). CONCLUSION: CS significantly reduced MR acquisition time while maintaining acceptable image quality. The implementation of CS may improve departmental workflows and enhance patient care.

Accelerated Cine Cardiac MRI Using Deep Learning-Based Reconstruction: A Systematic Evaluation.

BACKGROUND: Breath-holding (BH) for cine balanced steady state free precession (bSSFP) imaging is challenging for patients with impaired BH capacity. Deep learning-based reconstruction (DLR) of undersampled k-space promises to shorten BHs while preserving image quality and accuracy of ventricular assessment. PURPOSE: To perform a systematic evaluation of DLR of cine bSSFP images from undersampled k-space over a range of acceleration factors. STUDY TYPE: Retrospective. SUBJECTS: Fifteen pectus excavatum patients (mean age 16.8 ± 5.4 years, 20% female) with normal cardiac anatomy and function and 12-second BH capability. FIELD STRENGTH/SEQUENCE: 1.5-T, cine bSSFP. ASSESSMENT: Retrospective DLR was conducted by applying compressed sensitivity encoding (C-SENSE) acceleration to systematically undersample fully sampled k-space cine bSSFP acquisition data over an acceleration/undersampling factor (R) considering a range of 2 to 8. Quality imperceptibility (QI) measures, including structural similarity index measure, were calculated using images reconstructed from fully sampled k-space as a reference. Image quality, including contrast and edge definition, was evaluated for diagnostic adequacy by three readers with varying levels of experience in cardiac MRI (>4 years, >18 years, and 1 year). Automated DL-based biventricular segmentation was performed commercially available software by cardiac radiologists with more than 4 years of experience. STATISTICAL TESTS: Tukey box plots, linear mixed effects model, analysis of variance (ANOVA), weighted kappa, Kruskal-Wallis test, and Wilcoxon signed-rank test were employed as appropriate. A P-value <0.05 was considered statistically significant. RESULTS: There was a significant decrease in the QI values and edge definition scores as R increased. Diagnostically adequate image quality was observed up to R = 5. The effect of R on all biventricular volumetric indices was non-significant (P = 0.447). DATA CONCLUSION: The biventricular volumetric indices obtained from the reconstruction of fully sampled cine bSSFP acquisitions and DLR of the same k-space data undersampled by C-SENSE up to R = 5 may be comparable. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Evaluation of Artifact Appearance and Burden in Pediatric Brain Tumor MR Imaging with Compressed Sensing in Comparison to Conventional Parallel Imaging Acceleration.

Clinical magnetic resonance imaging (MRI) aims for the highest possible image quality, while balancing the need for acceptable examination time, reasonable signal-to-noise ratio (SNR), and lowest artifact burden. With a recently introduced imaging acceleration technique, compressed sensing, the acquisition speed and image quality of pediatric brain tumor exams can be improved. However, little attention has been paid to its impact on method-related artifacts in pediatric brain MRI. This study assessed the overall artifact burden and artifact appearances in a standardized pediatric brain tumor MRI by comparing conventional parallel imaging acceleration with compressed sensing. This showed that compressed sensing resulted in fewer physiological artifacts in the FLAIR sequence, and a reduction in technical artifacts in the 3D T1 TFE sequences. Only a slight difference was noted in the T2 TSE sequence. A relatively new range of artifacts, which are likely technique-related, was noted in the 3D T1 TFE sequences. In conclusion, by equipping a basic pediatric brain tumor protocol for 3T MRI with compressed sensing, the overall burden of common artifacts can be reduced. However, attention should be paid to novel compressed-sensing-specific artifacts.

Diagnostic ability of diffusion-weighted imaging using echo planar imaging with compressed SENSE (EPICS) for differentiating hepatic hemangioma and liver metastasis.

PURPOSE: To assess the diagnostic abilities of diffusion-weighted imaging (DWI) with parallel imaging (PI-DWI) and that with Compressed SENSE (EPICS-DWI) for differentiating hepatic hemangiomas (HHs) and liver metastases (LMs). METHOD: This prospective study included 30 participants with HH and/or LM who underwent PI-DWI and EPICS-DWI. Two radiologists assessed the DWI images and assigned confidence scores for hepatic lesions conspicuity using 4-point scale. One of the radiologists additionally calculated the contrast-to-noise ratio (CNR) and measured ADC value of the hepatic lesions. The conspicuity, CNR, and ADC values were compared between the two sequences. A receiver operating characteristic (ROC) analysis was performed to assess the diagnostic abilities of the two sequences for differentiating HHs and LMs. RESULTS: The conspicuity of LMs was better in EPICS-DWI than in PI-DWI (P < .05 in both radiologists). The CNR of LMs was higher in EPICS-DWI than in PI-DWI (P = .008). No difference was found in the CNR of HHs (P = .52), ADC values for HHs (P = .79), and LMs (P = .29) between the two sequences. To differentiate between HHs and LMs, the cutoff ADC values were 1.38 × 10-3 mm2/s in PI-DWI and 1.37 × 10-3 mm2/s in EPICS-DWI. The area under the ROC curve (P = .86), sensitivity (P > .99), and specificity (P > .99) did not vary. CONCLUSIONS: The LMs were more visible in EPICS-DWI than in PI-DWI. However, the cutoff ADC values and diagnostic abilities for differentiating HHs and LMs were almost comparable between the two sequences.

Repeatability of brain phase-based magnetic resonance electric properties tomography methods and effect of compressed SENSE and RF shimming.

Magnetic resonance electrical properties tomography (MREPT) is an emerging imaging modality to noninvasively measure tissue conductivity and permittivity. Implementation of MREPT in the clinic requires repeatable measurements at a short scan time and an appropriate protocol. The aim of this study was to investigate the repeatability of conductivity measurements using phase-based MREPT and the effects of compressed SENSE (CS), and RF shimming on the precision of conductivity measurements. Conductivity measurements using turbo spin echo (TSE) and three-dimensional balanced fast field echo (bFFE) with CS factors were repeatable. Conductivity measurement using bFFE phase showed smaller mean and variance that those measured by TSE. The conductivity measurements using bFFE showed minimal deviation with CS factors up to 8, with deviation increasing at CS factors > 8. Subcortical structures produced less consistent measurements than cortical parcellations at higher CS factors. RF shimming using full slice coverage 2D dual refocusing echo acquisition mode (DREAM) and full coverage 3D dual TR approaches further improved measurement precision. BFFE is a more optimal sequence than TSE for phase-based MREPT in brain. Depending on the area of the brain being measured, the scan can be safely accelerated with compressed SENSE without sacrifice of precision, offering the potential to employ MREPT in clinical research and applications. RF shimming with better field mapping further improves precision of the conductivity measures.

3D whole-heart noncontrast coronary MR angiography based on compressed SENSE technology: a comparative study of conventional SENSE sequence and coronary computed tomography angiography.

OBJECTIVE: The relatively long scan time has hampered the clinical use of whole-heart noncontrast coronary magnetic resonance angiography (NCMRA). The compressed sensitivity encoding (SENSE) technique, also known as the CS technique, has been found to improve scan times. This study aimed to identify the optimal CS acceleration factor for NCMRA. METHODS: Thirty-six participants underwent four NCMRA sequences: three sequences using the CS technique with acceleration factors of 4, 5, and 6, and one sequence using the conventional SENSE technique with the acceleration factor of 2. Coronary computed tomography angiography (CCTA) was considered as a reference sequence. The acquisition times of the four NCMRA sequences were assessed. The correlation and agreement between the visible vessel lengths obtained via CCTA and NCMRA were also assessed. The image quality scores and contrast ratio (CR) of eight coronary artery segments from the four NCMRA sequences were quantitatively evaluated. RESULTS: The mean acquisition time of the conventional SENSE was 343 s, while that of CS4, CS5, and CS6 was 269, 215, and 190 s, respectively. The visible vessel length from the CS4 sequence showed good correlation and agreement with CCTA. The image quality score and CR from the CS4 sequence were not statistically significantly different from those in the other groups (p > 0.05). Moreover, the image score and CR showed a decreasing trend with the increase in the CS factor. CONCLUSIONS: The CS technique could significantly shorten the acquisition time of NCMRA. The CS sequence with an acceleration factor of 4 was generally acceptable for NCMRA in clinical settings to balance the image quality and acquisition time.

Evaluation of a deep learning-based reconstruction method for denoising and image enhancement of shoulder MRI in patients with shoulder pain.

OBJECTIVES: To evaluate the diagnostic performance of an automated reconstruction algorithm combining MR imaging acquired using compressed SENSE (CS) with deep learning (DL) in order to reconstruct denoised high-quality images from undersampled MR images in patients with shoulder pain. METHODS: Prospectively, thirty-eight patients (14 women, mean age 40.0 ± 15.2 years) with shoulder pain underwent morphological MRI using a pseudo-random, density-weighted k-space scheme with an acceleration factor of 2.5 using CS only. An automated DL-based algorithm (CS DL) was used to create reconstructions of the same k-space data as used for CS reconstructions. Images were analyzed by two radiologists and assessed for pathologies, image quality, and visibility of anatomical landmarks using a 4-point Likert scale. RESULTS: Overall agreement for the detection of pathologies between the CS DL reconstructions and CS images was substantial to almost perfect (κ 0.95 (95% confidence interval 0.82-1.00)). Image quality and the visibility of the rotator cuff, articular cartilage, and axillary recess were overall rated significantly higher for CS DL images compared to CS (p < 0.03). Contrast-to-noise ratios were significantly higher for cartilage/fluid (CS DL 198 ± 24.3, CS 130 ± 32.2, p = 0.02) and ligament/fluid (CS DL 184 ± 17.3, CS 141 ± 23.5, p = 0.03) and SNR values were significantly higher for ligaments and muscle of the CS DL reconstructions (p < 0.04). CONCLUSION: Evaluation of shoulder pathologies was feasible using a DL-based algorithm for MRI reconstruction and denoising. In clinical routine, CS DL may be beneficial in particular for reducing image noise and may be useful for the detection and better discrimination of discrete pathologies. Assessment of shoulder pathologies was feasible with improved image quality as well as higher SNR using a compressed sensing deep learning-based framework for image reconstructions and denoising. KEY POINTS: • Automated deep learning-based reconstructions showed a significant increase in signal-to-noise ratio and contrast-to-noise ratio (p < 0.04) with only a slight increase of reconstruction time of 40 s compared to CS. • All pathologies were accurately detected with no loss of diagnostic information or prolongation of the scan time. • Significant improvements of the image quality as well as the visibility of the rotator cuff, articular cartilage, and axillary recess were detected.

Clinical application of 3.0 T MR imaging without contrast in coronary artery based on compressed SENSE technology / 中华放射学杂志

Objective:To explore the optimal acceleration factor and feasibility of the compressed SENSE (CS) technique in non-contrast MR coronary angiography (NMRCA) for clinical practice.Methods:The image data of completed coronary CTA and 3.0 T NMRCA sequence in 31 patients with suspected coronary heart disease were prospectively recruited at Fuyang People′s Hospital from August 2021 to November 2021. NMRCA sequences included conventional SENSE2 sequence and CS sequences with acceleration factors of 4, 5, and 6, respectively. The subjective scores of image quality and the objective scores, the contrast ratios between assessed coronaries and myocardium (CMCR) were compared among the 4 groups using the Friedman and Wilcoxon rank sum test.Results:Compared with the conventional SENSE2 [(343±46)s], the scan time of CS4 (269±36), CS5 (214±29) and CS6 (178±26) s were shortened by 21.5%, 37.5% and 48.0%, respectively. There was a good consistency between the subjective scores of the four groups (Kappa=0.769, 95% Cl 0.738-0.800). There was no significant difference in subjective score and CMCR value between CS4 and SENSE2 ( P>0.05). The coronary artery segments of CS5 and CS6 were significantly different from SENSE2 group ( P<0.05). Conclusions:For 3.0 T NMRCA, CS technology shows high feasibility. The CS4 can reduce imaging time while ensuring high-quality coronary arterial images, which has a well-established clinical application value for NMRCA.

Motion-robust MR imaging of the shoulder using compressed SENSE MultiVane.

Purpose: Motion artifacts caused by breathing or involuntary motion of patients, which may lead to reduced image quality and a loss of diagnostic information, are a major problem in shoulder magnetic resonance imaging (MRI). The MultiVane (MV) technique decreases motion artifacts; however, it tends to prolong the acquisition time. As a parallel imaging technique, SENSitivity Encoding (SENSE) can be combined with the compressed sensing method to produce compressed SENSE (C-SENSE), resulting in a markedly reduced acquisition time. This study aimed to evaluate the use of C-SENSE MV for MRI of the shoulder joint. Methods: Thirty-one patients who were scheduled to undergo MRI of the shoulder were included. This prospective study was approved by our institution's medical ethics committee, and written informed consent was obtained from all 31 patients. Two sets of oblique coronal images derived from the standard protocol were acquired without (standard) or with C-SENSE MV: proton-density weighted imaging (PDWI), PDWI with C-SENSE MV, T2-weighted imaging (T2WI) with fat suppression (fs), and T2WI fs with C-SENSE MV. Two radiologists graded motion artifacts and the detectability of anatomical shoulder structures on a 4-point scale (3, no artifacts/excellent delineation; 0, severe artifacts/difficulty with delineation). The Wilcoxon signed-rank test was used to compare the data for the standard and C-SENSE MV images. Results: Motion artifacts were significantly reduced on the C-SENSE MV images (p < 0.001). Regarding the detectability of anatomical structures, the ratings for the C-SENSE MV sequences were significantly better (p < 0.001).In conclusion, in shoulder MRI the newly developed C-SENSE MV technique reduces motion artifacts and increases the detectability of anatomical structures compared with standard sequences.

Evaluating Compressed SENSE (CS) MRI Metal Artifact Reduction Using Pig L-Spine Phantom and Transplant Patients: Focused on the CS-SEMAC (SPIR), mDixon(O-MAR) and STIR Techniques.

This study evaluates the clinical usefulness of the images obtained after applying mDixon (O-MAR), CS-SEMAC (SPIR), and STIR techniques to Pig L-Spine Phantom and transplant patients according to the difference in the reduction in metal artifacts and provides the optimal MAR image technique. This study was conducted with Phantom and 30 transplant patients who had an implant on the L-Spine (22 men, 8 women, mean age: 64.2 ± 12.98). All data analyzed were evaluated, using Philips Ingenia 3.0T CX. As pulse sequences, applied to the analysis, mDixon (O-MAR), CS-SEMAC (SPIR), and STIR were used. As the coil used to obtain data, the dStream Head Spine Coil was used. When tested directly applying to the transplant patients in the conditions the same as for the Phantom, as for the MAR effect of T1 and T2 images, the SNR value showed the highest effect on the increase in the signal in T1, T2 CS-SEMAC (SPIR), followed by mDixon (O-MAR) and STIR, which was the same result as the Phantom (p < 0.05). In addition, in the results of the histogram measurement in both of the subjects, Phantom and transplant patients, the count of T1, the T2 Sagittal image was the highest in T1, T2 STIR, followed by T1, T2 mDixon (O-MAR) and T1, and T2 CS-SEMAC (SPIR). As a result of the qualitative analysis, the quality was the best in T2 CS-SEMAC(SPIR) (c), followed by mDixon (O-MAR) (b) and T2 STIR (a). In conclusion, when the MAR effect on the Pig L-spine Phantom and Transplant patients was compared, it was noted that the CS-SEMAC (SPIR) technique was the most excellent in the following order: STIR < mDixon (O-MAR) < CS-SEMAC (SPIR).

Deep learning-based acceleration of Compressed Sense MR imaging of the ankle.

OBJECTIVES: To evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle. METHODS: Thirty patients were scanned at 3T. Axial T2-w, coronal T1-w, and coronal/sagittal intermediate-w scans with fat saturation were acquired using compressed sensing only (12:44 min, CS), CSAI with an acceleration factor of 4.6-5.3 (6:45 min, CSAI2x), and CSAI with an acceleration factor of 6.9-7.7 (4:46 min, CSAI3x). Moreover, a high-resolution axial T2-w scan was obtained using CSAI with a similar scan duration compared to CS. Depiction and presence of abnormalities were graded. Signal-to-noise and contrast-to-noise were calculated. Wilcoxon signed-rank test and Cohen's kappa were used to compare CSAI with CS sequences. RESULTS: The correlation was perfect between CS and CSAI2x (κ = 1.0) and excellent for CS and CSAI3x (κ = 0.86-1.0). No significant differences were found for the depiction of structures between CS and CSAI2x and the same abnormalities were detected in both protocols. For CSAI3x the depiction was graded lower (p ≤ 0.001), though most abnormalities were also detected. For CSAI2x contrast-to-noise fluid/muscle was higher compared to CS (p ≤ 0.05), while no differences were found for other tissues. Signal-to-noise and contrast-to-noise were higher for CSAI3x compared to CS (p ≤ 0.05). The high - resolution axial T2-w sequence specifically improved the depiction of tendons and the tibial nerve (p ≤ 0.005). CONCLUSIONS: Acquisition times can be reduced by 47% using CSAI compared to CS without decreasing diagnostic image quality. Reducing acquisition times by 63% is feasible but should be reserved for specific patients. The depiction of specific structures is improved using a high-resolution axial T2-w CSAI scan. KEY POINTS: • Prospective study showed that CSAI enables reduction in acquisition times by 47% without decreasing diagnostic image quality. • Reducing acquisition times by 63% still produces images with an acceptable diagnostic accuracy but should be reserved for specific patients. • CSAI may be implemented to scan at a higher resolution compared to standard CS images without increasing acquisition times.

3D Amide Proton Transfer Weighted Brain Tumor Imaging With Compressed SENSE: Effects of Different Acceleration Factors.

Objectives: The aim of the current study was to evaluate the performance of compressed SENSE (CS) for 3D amide proton transfer weighted (APTw) brain tumor imaging with different acceleration factors (AFs), and the results were compared with those of conventional SENSE. Methods: Approximately 51 patients with brain tumor (22 males, 49.95 ± 10.52 years) with meningiomas (n = 16), metastases (n = 12), or gliomas (n = 23) were enrolled. All the patients received 3D APTw imaging scans on a 3.0 T scanner with acceleration by CS (AFs: CS2, CS3, CS4, and CS5) and SENSE (AF: S1.6). Two readers independently and subjectively evaluated the APTw images relative to image quality and measured confidence concerning image blur, distortion, motion, and ghosting artifacts, lesion recognition, and contour delineation with a 5-point Likert scale. Mean amide proton transfer (APT) values of brain tumors (APT tumor ), the contralateral normal-appearing white matter (APT CNAWM ), and the peritumoral edema area (if present, APT edema ) and the tumor volume (V APT ) were measured for objective evaluation and determination of the optimal AF. The Ki67 labeling index was also measured by using standard immunohistochemical staining procedures in samples from patients with gliomas, and the correlation between tumor APT values and the Ki67 index was analyzed. Results: The image quality of AF = CS5 was significantly lower than that of other groups. V APT showed significant differences among the six sequences in meningiomas (p = 0.048) and gliomas (p = 0.023). The pairwise comparison showed that the V APT values of meningiomas measured from images by CS5 were significantly lower, and gliomas were significantly larger than those by SENSE1.6 and other CS accelerations, (p < 0.05). APT tumor (p = 0.191) showed no significant difference among the three types of tumors. The APT tumor values of gliomas measured by APTw images with the SENSE factor of 1.6 and the CS factor of 2, 3, and 4 (except for CS5) were all positively correlated with Ki67. Conclusion: Compressed SENSE could be successfully extended to accelerated 3D APTw imaging of brain tumors without compromising image quality using the AF of 4.

Evaluating the Quality of Optimal MRCP Image Using RT-2D-Compressed SENSE(CS)Turbo Spin Echo: Comparing Respiratory Triggering(RT)-2D-SENSE Turbo Spin Echo and Breath Hold-2D-Single-Shot Turbo Spin Echo.

This study aimed to select the pulse sequence providing the optimal MRCP image quality by applying various reduction and denoising level parameters­which could improve image quality and shorten examination time­to BH-2D-SSh TSE, RT- 2D-SENSE TSE, and RT-2D-Compressed SENSE(CS) TSE and then comparing and analyzing the obtained images. This study was carried out using 30 subjects (15 men and 15 women with a mean age of 53 ± 8.76 years) who underwent an MRCP test using 3.0T MRI equipment. These 30 subjects were composed of 20 patients (CHDD: 7; LC: 6; and IPMN: 7) and 10 volunteers without a disease. When the CS technique was used, five reduction values (1.1, 1.2, 1.3, 1.4, and 1.5) were used and four denoising levels (No, Weak, Medium, and Strong) were used. The existing SENSE method was based on a reduction value of 1, and other parameters were set the same. The image data of BH-2D-SSh TSE, RT-2D-SENSE TSE, and RT-CS-2D TSE used for the analysis were acquired in the coronal plane, and the acquired data underwent MIP post-processing for analysis. To compare these techniques, SNR and CNR were measured for six biliary duct images for the purpose of quantitative analysis, and qualitative analysis was performed on the sharpness of the duct, the overall quality of the image, and the motion artifact. The results of the quantitative and standard analyses showed that the RT-2D-CS TSE technique had the highest results for all IPMN, LC, and CHDD diseases (p < 0.05). Moreover, SNR and CNR were the highest when the reduction value was set to 1.3 and the denoising level was set to medium as the CS setting values (p < 0.05). Compared with the conventional RT-2D-SENSE TSE, the test time decreased by 20% and SNR and CNR increased by 14% on average. When conducting RT-2D-CS TSE, we found that it shortened the examination time and improved the image quality compared to the existing RT-2D-SENSE TSE. Unlike previous studies, this study using the RT technique shows that it is a useful MRI Pulse Sequence technique able to replace the BH-2D-SSh TSE and BH-3D-SENSE GRASE techniques, which require the patient to hold their breath during the test.