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del Álamo M, Li H, Munk A. Frame-constrained total variation regularization for white noise regression. Ann Stat 2021. [DOI: 10.1214/20-aos2001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
| | - Housen Li
- Institute for Mathematical Stochastics, University of Göttingen
| | - Axel Munk
- Institute for Mathematical Stochastics, University of Göttingen
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Burke CJ, Kaplan D, Block T, Chang G, Jazrawi L, Campbell K, Alaia M. Clinical Utility of Continuous Radial Magnetic Resonance Imaging Acquisition at 3 T in Real-time Patellofemoral Kinematic Assessment: A Feasibility Study. Arthroscopy 2018; 34:726-733. [PMID: 29273250 PMCID: PMC6080599 DOI: 10.1016/j.arthro.2017.09.020] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 09/05/2017] [Accepted: 09/06/2017] [Indexed: 02/02/2023]
Abstract
PURPOSE To compare patellar instability with magnetic resonance imaging analysis using continuous real-time radial gradient-echo (GRE) imaging in the assessment of symptomatic patients and asymptomatic subjects. METHODS Symptomatic patients with suspected patellofemoral maltracking and asymptomatic volunteers were scanned in real time by a radial 2-dimensional GRE sequence at 3 T in axial orientation at the patella level through a range of flexion-extension. The degree of lateral maltracking, as well as the associated tibial tubercle-trochlear groove distance and trochlea depth, was measured. Patellar lateralization was categorized as normal (≤2 mm), mild (>2 to ≤5 mm), moderate (>5 to ≤10 mm), or severe (>10 mm). The patellofemoral cartilage was also assessed according to the modified Outerbridge grading system. RESULTS The study included 20 symptomatic patients (13 women and 7 men; mean age, 36 ± 12.8 years) and 10 asymptomatic subjects (3 women and 7 men; mean age, 33.1 years). The mean time to perform the dynamic component ranged from 3 to 7 minutes. Lateralization in the symptomatic group was normal in 10 patients, mild in 1, moderate in 8, and severe in 1. There was no lateral tracking greater than 3 mm in the volunteer group. Lateral maltracking was significantly higher in symptomatic patients than in asymptomatic subjects (4.4 ± 3.7 mm vs 1.5 ± 0.71 mm, P = .007). Lateral tracking significantly correlated with tibial tubercle-trochlear groove distance (r = 0.48, P = .006). There was excellent agreement on lateral tracking between the 2 reviewers (intraclass correlation coefficient, 0.979; 95% confidence interval, 0.956-0.990). CONCLUSIONS The inclusion of a dynamic radial 2-dimensional GRE sequence is a rapid and easily performed addition to the standard magnetic resonance imaging protocol and allows dynamic quantitative assessment of patellar instability and lateral maltracking in symptomatic patients. With a paucity of reported data using this technique confirming that these results reach clinical significance, future work is required to determine how much lateral tracking is clinically significant. LEVEL OF EVIDENCE Level III, case control.
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Affiliation(s)
- Christopher J Burke
- Department of Radiology, NYU Hospital for Joint Diseases, New York, New York, U.S.A..
| | - Daniel Kaplan
- Department of Orthopedic Surgery, NYU Hospital for Joint Diseases, New York, New York, U.S.A
| | - Tobias Block
- NYU Center for Biomedical Imaging, New York, New York, U.S.A
| | - Gregory Chang
- NYU Center for Biomedical Imaging, New York, New York, U.S.A
| | - Laith Jazrawi
- Department of Orthopedic Surgery, NYU Hospital for Joint Diseases, New York, New York, U.S.A
| | - Kirk Campbell
- Department of Orthopedic Surgery, NYU Hospital for Joint Diseases, New York, New York, U.S.A
| | - Michael Alaia
- Department of Orthopedic Surgery, NYU Hospital for Joint Diseases, New York, New York, U.S.A
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Fu M, Barlaz MS, Holtrop JL, Perry JL, Kuehn DP, Shosted RK, Liang ZP, Sutton BP. High-frame-rate full-vocal-tract 3D dynamic speech imaging. Magn Reson Med 2016; 77:1619-1629. [PMID: 27099178 DOI: 10.1002/mrm.26248] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Revised: 03/25/2016] [Accepted: 03/28/2016] [Indexed: 11/08/2022]
Abstract
PURPOSE To achieve high temporal frame rate, high spatial resolution and full-vocal-tract coverage for three-dimensional dynamic speech MRI by using low-rank modeling and sparse sampling. METHODS Three-dimensional dynamic speech MRI is enabled by integrating a novel data acquisition strategy and an image reconstruction method with the partial separability model: (a) a self-navigated sparse sampling strategy that accelerates data acquisition by collecting high-nominal-frame-rate cone navigator sand imaging data within a single repetition time, and (b) are construction method that recovers high-quality speech dynamics from sparse (k,t)-space data by enforcing joint low-rank and spatiotemporal total variation constraints. RESULTS The proposed method has been evaluated through in vivo experiments. A nominal temporal frame rate of 166 frames per second (defined based on a repetition time of 5.99 ms) was achieved for an imaging volume covering the entire vocal tract with a spatial resolution of 2.2 × 2.2 × 5.0 mm3 . Practical utility of the proposed method was demonstrated via both validation experiments and a phonetics investigation. CONCLUSION Three-dimensional dynamic speech imaging is possible with full-vocal-tract coverage, high spatial resolution and high nominal frame rate to provide dynamic speech data useful for phonetic studies. Magn Reson Med 77:1619-1629, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Maojing Fu
- Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Marissa S Barlaz
- Linguistics, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Joseph L Holtrop
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jamie L Perry
- Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina, USA
| | - David P Kuehn
- Speech and Hearing Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Ryan K Shosted
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Linguistics, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Zhi-Pei Liang
- Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Bradley P Sutton
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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Hartmann A, Huckemann S, Dannemann J, Laitenberger O, Geisler C, Egner A, Munk A. Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy. J R Stat Soc Series B Stat Methodol 2015. [DOI: 10.1111/rssb.12128] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | | | | | | | | | | | - Axel Munk
- Georg-August-Universität; Göttingen Germany
- Max Planck Institute for Biophysical Chemistry; Göttingen Germany
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Contijoch F, Witschey WRT, Rogers K, Rears H, Hansen M, Yushkevich P, Gorman J, Gorman RC, Han Y. User-initialized active contour segmentation and golden-angle real-time cardiovascular magnetic resonance enable accurate assessment of LV function in patients with sinus rhythm and arrhythmias. J Cardiovasc Magn Reson 2015; 17:37. [PMID: 25994390 PMCID: PMC4440288 DOI: 10.1186/s12968-015-0146-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2014] [Accepted: 05/08/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Data obtained during arrhythmia is retained in real-time cardiovascular magnetic resonance (rt-CMR), but there is limited and inconsistent evidence to show that rt-CMR can accurately assess beat-to-beat variation in left ventricular (LV) function or during an arrhythmia. METHODS Multi-slice, short axis cine and real-time golden-angle radial CMR data was collected in 22 clinical patients (18 in sinus rhythm and 4 patients with arrhythmia). A user-initialized active contour segmentation (ACS) software was validated via comparison to manual segmentation on clinically accepted software. For each image in the 2D acquisitions, slice volume was calculated and global LV volumes were estimated via summation across the LV using multiple slices. Real-time imaging data was reconstructed using different image exposure times and frame rates to evaluate the effect of temporal resolution on measured function in each slice via ACS. Finally, global volumetric function of ectopic and non-ectopic beats was measured using ACS in patients with arrhythmias. RESULTS ACS provides global LV volume measurements that are not significantly different from manual quantification of retrospectively gated cine images in sinus rhythm patients. With an exposure time of 95.2 ms and a frame rate of > 89 frames per second, golden-angle real-time imaging accurately captures hemodynamic function over a range of patient heart rates. In four patients with frequent ectopic contractions, initial quantification of the impact of ectopic beats on hemodynamic function was demonstrated. CONCLUSION User-initialized active contours and golden-angle real-time radial CMR can be used to determine time-varying LV function in patients. These methods will be very useful for the assessment of LV function in patients with frequent arrhythmias.
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Affiliation(s)
- Francisco Contijoch
- Department of Bioengineering, University of Pennsylvania, Smilow Center for Translational Research, 3400 Civic Center Blvd, Bldg 421, 7th Floor, Rm 103, Philadelphia, PA, 1903, USA.
| | | | - Kelly Rogers
- Cardiovascular Division, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
| | - Hannah Rears
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Paul Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Joseph Gorman
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, 1903, USA.
| | - Robert C Gorman
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, 1903, USA.
| | - Yuchi Han
- Cardiovascular Division, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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Fu M, Zhao B, Carignan C, Shosted RK, Perry JL, Kuehn DP, Liang ZP, Sutton BP. High-resolution dynamic speech imaging with joint low-rank and sparsity constraints. Magn Reson Med 2015; 73:1820-32. [PMID: 24912452 PMCID: PMC4261062 DOI: 10.1002/mrm.25302] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Revised: 04/11/2014] [Accepted: 05/05/2014] [Indexed: 11/11/2022]
Abstract
PURPOSE To enable dynamic speech imaging with high spatiotemporal resolution and full-vocal-tract spatial coverage, leveraging recent advances in sparse sampling. METHODS An imaging method is developed to enable high-speed dynamic speech imaging exploiting low-rank and sparsity of the dynamic images of articulatory motion during speech. The proposed method includes: (a) a novel data acquisition strategy that collects spiral navigators with high temporal frame rate and (b) an image reconstruction method that derives temporal subspaces from navigators and reconstructs high-resolution images from sparsely sampled data with joint low-rank and sparsity constraints. RESULTS The proposed method has been systematically evaluated and validated through several dynamic speech experiments. A nominal imaging speed of 102 frames per second (fps) was achieved for a single-slice imaging protocol with a spatial resolution of 2.2 × 2.2 × 6.5 mm(3) . An eight-slice imaging protocol covering the entire vocal tract achieved a nominal imaging speed of 12.8 fps with the identical spatial resolution. The effectiveness of the proposed method and its practical utility was also demonstrated in a phonetic investigation. CONCLUSION High spatiotemporal resolution with full-vocal-tract spatial coverage can be achieved for dynamic speech imaging experiments with low-rank and sparsity constraints.
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Affiliation(s)
- Maojing Fu
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Bo Zhao
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | | | - Ryan K. Shosted
- Department of Linguistics, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Jamie L. Perry
- Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
| | - David P. Kuehn
- Department of Speech and Hearing Science, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Zhi-Pei Liang
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Bradley P. Sutton
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois
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Zhang S, Joseph AA, Voit D, Schaetz S, Merboldt KD, Unterberg-Buchwald C, Hennemuth A, Lotz J, Frahm J. Real-time magnetic resonance imaging of cardiac function and flow-recent progress. Quant Imaging Med Surg 2014; 4:313-29. [PMID: 25392819 DOI: 10.3978/j.issn.2223-4292.2014.06.03] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2014] [Accepted: 05/30/2014] [Indexed: 11/14/2022]
Abstract
Cardiac structure, function and flow are most commonly studied by ultrasound, X-ray and magnetic resonance imaging (MRI) techniques. However, cardiovascular MRI is hitherto limited to electrocardiogram (ECG)-synchronized acquisitions and therefore often results in compromised quality for patients with arrhythmias or inabilities to comply with requested protocols-especially with breath-holding. Recent advances in the development of novel real-time MRI techniques now offer dynamic imaging of the heart and major vessels with high spatial and temporal resolution, so that examinations may be performed without the need for ECG synchronization and during free breathing. This article provides an overview of technical achievements, physiological validations, preliminary patient studies and translational aspects for a future clinical scenario of cardiovascular MRI in real time.
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Affiliation(s)
- Shuo Zhang
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Arun A Joseph
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Dirk Voit
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Sebastian Schaetz
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Klaus-Dietmar Merboldt
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Christina Unterberg-Buchwald
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Anja Hennemuth
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Joachim Lotz
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
| | - Jens Frahm
- 1 Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen 37070, Germany ; 2 DZHK (German Cardiovascular Research Center), partner site Göttingen, Göttingen, Germany ; 3 Diagnostische und Interventionelle Radiologie, 4 Kardiologie und Pneumologie, Universitätsmedizin Göttingen, Göttingen 37075, Germany ; 5 Fraunhofer MEVIS Institute for Medical Image Computing, Bremen, Germany
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