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Spatially resolved kinetics of skeletal muscle exercise response and recovery with multiple echo diffusion tensor imaging (MEDITI): a feasibility study

Sigmund, E E; Baete, S H; Patel, K; Wang, D; Stoffel, D; Otazo, R; Parasoglou, P; Bencardino, J
OBJECTIVES/OBJECTIVE:We describe measurement of skeletal muscle kinetics with multiple echo diffusion tensor imaging (MEDITI). This approach allows characterization of the microstructural dynamics in healthy and pathologic muscle. MATERIALS AND METHODS/METHODS:In a Siemens 3-T Skyra scanner, MEDITI was used to collect dynamic DTI with a combination of rapid diffusion encoding, radial imaging, and compressed sensing reconstruction in a multi-compartment agarose gel rotation phantom and within in vivo calf muscle. An MR-compatible ergometer (Ergospect Trispect) was employed to enable in-scanner plantar flexion exercise. In a HIPAA-compliant study with written informed consent, post-exercise recovery of DTI metrics was quantified in eight volunteers. Exercise response of DTI metrics was compared with that of T2-weighted imaging and characterized by a gamma variate model. RESULTS: = 0.303 ± 0.185). Diffusion and T2-weighted response magnitudes were correlated (e.g., r = 0.792, p = 0.019 for nMD vs. nT2w). CONCLUSION/CONCLUSIONS:We have demonstrated the feasibility of MEDITI for capturing spatially resolved diffusion tensor data in dynamic systems including post-exercise skeletal muscle recovery following in-scanner plantar flexion.
PMID: 29761414
ISSN: 1352-8661
CID: 3121362

Low Rank plus Sparse decomposition of ODFs for improved detection of group-level differences and variable correlations in white matter

Baete, Steven H; Chen, Jingyun; Lin, Ying-Chia; Wang, Xiuyuan; Otazo, Ricardo; Boada, Fernando E
A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF). Recent advances in MRI acquisition make it possible to use high quality diffusion weighted protocols (multi-shell, large number of gradient directions) for routine in vivo study of white matter architecture. The dimensionality of these data sets is however often reduced to simplify statistical analysis. While these approaches may detect large group differences, they do not fully capitalize on all acquired image volumes. Incorporation of all available diffusion information in the analysis however risks biasing the outcome by outliers. Here we propose a statistical analysis method operating on the ODF, either the diffusion ODF or fiber ODF. To avoid outlier bias and reliably detect voxelwise group differences and correlations with demographic or behavioral variables, we apply the Low-Rank plus Sparse (L+S) matrix decomposition on the voxelwise ODFs which separates the sparse individual variability in the sparse matrix S whilst recovering the essential ODF features in the low-rank matrix L. We demonstrate the performance of this ODF L+S approach by replicating the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset. The volume of positive findings (p<0.01, 227 cm3) agrees with and expands on the volume found by TBSS (17 cm3), Connectivity based fixel enhancement (15 cm3) and Connectometry (212 cm3). In the same dataset we further localize the correlations of brain structure with neurocognitive measures such as fluid intelligence and episodic memory. The presented ODF L+S approach will aid in the full utilization of all acquired diffusion weightings leading to the detection of smaller group differences in clinically relevant settings as well as in neuroscience applications.
PMCID:5949269
PMID: 29526742
ISSN: 1095-9572
CID: 2992472

RACER-GRASP: Respiratory-weighted, aortic contrast enhancement-guided and coil-unstreaking golden-angle radial sparse MRI

Feng, Li; Huang, Chenchan; Shanbhogue, Krishna; Sodickson, Daniel K; Chandarana, Hersh; Otazo, Ricardo
PURPOSE: To develop and evaluate a novel dynamic contrast-enhanced imaging technique called RACER-GRASP (Respiratory-weighted, Aortic Contrast Enhancement-guided and coil-unstReaking Golden-angle RAdial Sparse Parallel) MRI that extends GRASP to include automatic contrast bolus timing, respiratory motion compensation, and coil-weighted unstreaking for improved imaging performance in liver MRI. METHODS: In RACER-GRASP, aortic contrast enhancement (ACE) guided k-space sorting and respiratory-weighted sparse reconstruction are performed using aortic contrast enhancement and respiratory motion signals extracted directly from the acquired data. Coil unstreaking aims to weight multicoil k-space according to streaking artifact level calculated for each individual coil during image reconstruction, so that coil elements containing a high level of streaking artifacts contribute less to the final results. Self-calibrating GRAPPA operator gridding was applied as a pre-reconstruction step to reduce computational burden in the subsequent iterative reconstruction. The RACER-GRASP technique was compared with standard GRASP reconstruction in a group of healthy volunteers and patients referred for clinical liver MR examination. RESULTS: Compared with standard GRASP, RACER-GRASP significantly improved overall image quality (average score: 3.25 versus 3.85) and hepatic vessel sharpness/clarity (average score: 3.58 versus 4.0), and reduced residual streaking artifact level (average score: 3.23 versus 3.94) in different contrast phases. RACER-GRASP also enabled automatic timing of the arterial phases. CONCLUSIONS: The aortic contrast enhancement-guided sorting, respiratory motion suppression and coil unstreaking introduced by RACER-GRASP improve upon the imaging performance of standard GRASP for free-breathing dynamic contrast-enhanced MRI of the liver. Magn Reson Med, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.
PMCID:5876099
PMID: 29193260
ISSN: 1522-2594
CID: 2797952

Medical imaging data in the digital innovation age

Kesner, Adam; Laforest, Richard; Otazo, Ricardo; Jennifer, Kwak; Pan, Tinsu
As we reflect on decades of exponential advancements in electronic innovation, we can see the field of medical imaging eclipsed by a new digital landscape - one that is inexpensive, fast, and powerful. This new paradigm presents new opportunities to innovate in both research and clinical settings. In this article, we review the current role of data: the common perceptions around its valuation and the infrastructure currently in place for data-driven innovation. Looking forward, we consider what has already been achieved using modern data capacities, the opportunities we have for further expansion in this area, and the obstacles we will need to transcend.
PMID: 29405298
ISSN: 2473-4209
CID: 3055412

5D whole-heart sparse MRI

Feng, Li; Coppo, Simone; Piccini, Davide; Yerly, Jerome; Lim, Ruth P; Masci, Pier Giorgio; Stuber, Matthias; Sodickson, Daniel K; Otazo, Ricardo
PURPOSE: A 5D whole-heart sparse imaging framework is proposed for simultaneous assessment of myocardial function and high-resolution cardiac and respiratory motion-resolved whole-heart anatomy in a single continuous noncontrast MR scan. METHODS: A non-electrocardiograph (ECG)-triggered 3D golden-angle radial balanced steady-state free precession sequence was used for data acquisition. The acquired 3D k-space data were sorted into a 5D dataset containing separated cardiac and respiratory dimensions using a self-extracted respiratory motion signal and a recorded ECG signal. Images were then reconstructed using XD-GRASP, a multidimensional compressed sensing technique exploiting correlations/sparsity along cardiac and respiratory dimensions. 5D whole-heart imaging was compared with respiratory motion-corrected 3D and 4D whole-heart imaging in nine volunteers for evaluation of the myocardium, great vessels, and coronary arteries. It was also compared with breath-held, ECG-gated 2D cardiac cine imaging for validation of cardiac function quantification. RESULTS: 5D whole-heart images received systematic higher quality scores in the myocardium, great vessels and coronary arteries. Quantitative coronary sharpness and length were always better for the 5D images. Good agreement was obtained for quantification of cardiac function compared with 2D cine imaging. CONCLUSION: 5D whole-heart sparse imaging represents a robust and promising framework for simplified comprehensive cardiac MRI without the need for breath-hold and motion correction. Magn Reson Med, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.
PMCID:5681898
PMID: 28497486
ISSN: 1522-2594
CID: 2549232

Evaluation of SparseCT on patient data using realistic undersampling models

Chapter by: Chen, Baiyu; Muckley, Matthew; Sodickson, Aaron; O'Donnell, Thomas; Knoll, Florian; Sodickson, Daniel; Otazo, Ricardo
in: MEDICAL IMAGING 2018: PHYSICS OF MEDICAL IMAGING by ; Lo, JY; Schmidt, TG; Chen, GH
BELLINGHAM : SPIE-INT SOC OPTICAL ENGINEERING, 2018
pp. ?-?
ISBN: 978-1-5106-1636-3
CID: 3290392

Compressed sensing acceleration of biexponential 3D-T1rho relaxation mapping of knee cartilage

Zibetti, M V W; Sharafi, A; Otazo, R; Regatte, R R
Purpose: Use compressed sensing (CS) for 3D biexponential spin-lattice relaxation time in the rotating frame (T1rho) mapping of knee cartilage, reducing the total scan time and maintaining the quality of estimated biexponential T1rho parameters (short and long relaxation times and corresponding fractions) comparable to fully sampled scans. Methods: Fully sampled 3D-T1rho-weighted data sets were retrospectively undersampled by factors 2-10. CS reconstruction using 12 different sparsifying transforms were compared for biexponential T1rho-mapping of knee cartilage, including temporal and spatial wavelets and finite differences, dictionary from principal component analysis (PCA), k-means singular value decomposition (K-SVD), exponential decay models, and also low rank and low rank plus sparse models. Synthetic phantom (N = 6) and in vivo human knee cartilage data sets (N = 7) were included in the experiments. Spatial filtering before biexponential T1rho parameter estimation was also tested. Results: Most CS methods performed satisfactorily for an acceleration factor (AF) of 2, with relative median normalized absolute deviation (MNAD) around 10%. Some sparsifying transforms, such as low rank with spatial finite difference (L + S SFD), spatiotemporal finite difference (STFD), and exponential dictionaries (EXP) significantly improved this performance, reaching MNAD below 15% with AF up to 10, when spatial filtering was used. Conclusion: Accelerating biexponential 3D-T1rho mapping of knee cartilage with CS is feasible. The best results were obtained by STFD, EXP, and L + S SFD regularizers combined with spatial prefiltering. These 3 CS methods performed satisfactorily on synthetic phantom as well as in vivo knee cartilage for AFs up to 10, with median error below 15%.
EMBASE:623963118
ISSN: 0740-3194
CID: 3316832

VARIATIONAL DEEP LEARNING FOR LOW-DOSE COMPUTED TOMOGRAPHY [Meeting Abstract]

Kobler, Erich; Muckley, Matthew; Chen, Baiyu; Knoll, Florian; Hammernik, Kerstin; Pock, Thomas; Sodickson, Daniel; Otazo, Ricardo
ISI:000446384606169
ISSN: 1520-6149
CID: 4533932

Sparse-SEMAC: rapid and improved SEMAC metal implant imaging using SPARSE-SENSE acceleration

Otazo, Ricardo; Nittka, Mathias; Bruno, Mary; Raithel, Esther; Geppert, Christian; Gyftopoulos, Soterios; Recht, Michael; Rybak, Leon
PURPOSE: To develop an accelerated SEMAC metal implant MRI technique (Sparse-SEMAC) with reduced scan time and improved metal distortion correction. METHODS: Sparse-SEMAC jointly exploits the inherent sparsity along the additional phase-encoding dimension and multicoil encoding capabilities to significantly accelerate data acquisition. A prototype pulse sequence with pseudorandom ky -kz undersampling and an inline image reconstruction was developed for integration in clinical studies. Three patients with hip implants were imaged using the proposed Sparse-SEMAC with eight-fold acceleration and compared with the standard-SEMAC technique used in clinical studies (three-fold GRAPPA acceleration). Measurements were performed with SEMAC-encoding steps (SES) = 15 for Sparse-SEMAC and SES = 9 for Standard-SEMAC using high spatial resolution Proton Density (PD) and lower-resolution STIR acquisitions. Two expert musculoskeletal (MSK) radiologists performed a consensus reading to score image-quality parameters. RESULTS: Sparse-SEMAC enables up to eight-fold acceleration of data acquisition that results in two-fold scan time reductions, compared with Standard-SEMAC, with improved metal artifact correction for patients with hip implants without degrading spatial resolution. CONCLUSION: The high acceleration enabled by Sparse-SEMAC would enable clinically feasible examination times with improved correction of metal distortion. Magn Reson Med, 2016. (c) 2016 Wiley Periodicals, Inc.
PMCID:5266741
PMID: 27454003
ISSN: 1522-2594
CID: 2191422

Comparison of conventional DCE-MRI and a novel golden-angle radial multicoil compressed sensing method for the evaluation of breast lesion conspicuity

Heacock, Laura; Gao, Yiming; Heller, Samantha L; Melsaether, Amy N; Babb, James S; Block, Tobias K; Otazo, Ricardo; Kim, Sungheon G; Moy, Linda
PURPOSE: To compare a novel multicoil compressed sensing technique with flexible temporal resolution, golden-angle radial sparse parallel (GRASP), to conventional fat-suppressed spoiled three-dimensional (3D) gradient-echo (volumetric interpolated breath-hold examination, VIBE) MRI in evaluating the conspicuity of benign and malignant breast lesions. MATERIALS AND METHODS: Between March and August 2015, 121 women (24-84 years; mean, 49.7 years) with 180 biopsy-proven benign and malignant lesions were imaged consecutively at 3.0 Tesla in a dynamic contrast-enhanced (DCE) MRI exam using sagittal T1-weighted fat-suppressed 3D VIBE in this Health Insurance Portability and Accountability Act-compliant, retrospective study. Subjects underwent MRI-guided breast biopsy (mean, 13 days [1-95 days]) using GRASP DCE-MRI, a fat-suppressed radial "stack-of-stars" 3D FLASH sequence with golden-angle ordering. Three readers independently evaluated breast lesions on both sequences. Statistical analysis included mixed models with generalized estimating equations, kappa-weighted coefficients and Fisher's exact test. RESULTS: All lesions demonstrated good conspicuity on VIBE and GRASP sequences (4.28 +/- 0.81 versus 3.65 +/- 1.22), with no significant difference in lesion detection (P = 0.248). VIBE had slightly higher lesion conspicuity than GRASP for all lesions, with VIBE 12.6% (0.63/5.0) more conspicuous (P < 0.001). Masses and nonmass enhancement (NME) were more conspicuous on VIBE (P < 0.001), with a larger difference for NME (14.2% versus 9.4% more conspicuous). Malignant lesions were more conspicuous than benign lesions (P < 0.001) on both sequences. CONCLUSION: GRASP DCE-MRI, a multicoil compressed sensing technique with high spatial resolution and flexible temporal resolution, has near-comparable performance to conventional VIBE imaging for breast lesion evaluation. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2016.
PMCID:5538366
PMID: 27859874
ISSN: 1522-2586
CID: 2311022