Basha, Tamer A

Buehrer, Martin

Manning, Warren J

Nezafat, Reza

Roujol, Sébastien

Schülke, Christophe

Journal of Cardiovascular Magnetic Resonance

Harvard University - DASH 

 Low latency iterative reconstruction of first pass stress cardiacperfusion with physiological stress using graphical processingunit  (Article begins on next page)The Harvard community has made this article openly available.Please share how this access benefits you. Your story matters.Citation Roujol, Sébastien, Tamer A Basha, Christophe Schülke, MartinBuehrer, Warren J Manning, and Reza Nezafat. 2013. “Lowlatency iterative reconstruction of first pass stress cardiacperfusion with physiological stress using graphical processingunit.” Journal of Cardiovascular Magnetic Resonance 15 (Suppl1): E10. doi:10.1186/1532-429X-15-S1-E10.http://dx.doi.org/10.1186/1532-429X-15-S1-E10.Published Version doi:10.1186/1532-429X-15-S1-E10Accessed February 19, 2015 3:04:31 PM ESTCitable Link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879414Terms of Use This article was downloaded from Harvard University's DASHrepository, and is made available under the terms and conditionsapplicable to Other Posted Material, as set forth athttp://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAAPOSTER PRESENTATION Open AccessLow latency iterative reconstruction of first passstress cardiac perfusion with physiological stressusing graphical processing unitSébastien Roujol1*, Tamer A Basha1, Christophe Schülke1,3, Martin Buehrer3, Warren J Manning1,2, Reza Nezafat1From 16th Annual SCMR Scientific SessionsSan Francisco, CA, USA. 31 January - 3 February 2013BackgroundCardiac MR perfusion has been shown to provide highdiagnostic accuracy in detection of the coronary arterydisease [1]. We have recently installed an MR-compatiblesupine bicycle mounted on the scanner table, whichallows performing CMR perfusion immediately afterphysiologic stress. However, patients are unable tosustain a breathold after physical exercise, limiting thechoice of acceleration techniques such as k-t approaches.Additionally, due to subject motion during exercise, coilsensitivity map are inaccurate resulting in imagingartifacts in conventional parallel imaging reconstruction.Compressed sensing (CS) is an alternative accelerationtechnique that enables high acceleration even withoutexploiting temporal dimension or need for coil maps.However, iterative CS reconstruction of randomlyundersampled k-space is lengthy, performed off-line andis not usually integrated into the workflow of a clinicalscan which requires viewing and initial assessment onthe scanner console and storing the clinical images onthe hospital PACS system. In this proposal, we aim todevelop an accelerated iterative CS reconstructionworkflow for reconstruction of CS acquired perfusiondata using physical stress perfusion.MethodsFigure 1 shows the workflow of the accelerated CMRperfusion reconstruction. After completion of the CMRperfusion sequence, the reconstruction process ismanually started by CMR technologist using an in-house graphical user interface. All the subsequentreconstruction steps are then performed automaticallywithout any user interaction. The raw data are pre-processed on the scanner workstation and sent to adedicated computer for reconstruction (equipped withgraphic processing unit (GPU) NVIDIA Tesla) andfinally sent back to the scanner workstation and thePACS database. Pre- and post-processing are performedusing the ReconFrame platform (Gyrotools, Zurich,Switzerland). The GPU-based CS reconstruction isimplemented using a fast alternating minimizationapproach [2]. Since this reconstruction is iterative andvoxel-independent for each iteration, the parallelizationlevel of the GPU implementation was set to the voxellevel. The presented workflow has been tested duringbicycle ergometer stress CMR perfusion exams inhealthy subjects using a 1.5T Philips scanner and aprospective 4× CS-accelerated CMR perfusion sequence.Computation time and latency of each reconstructionstep was measured and compared to a non-parallelizedimplementation.ResultsThe proposed workflow allows reconstruction and view-ing of the CS accelerated perfusion on the scannerconsole. The GPU-based implementation provides a12-fold reduction in reconstruction time with an overalllatency of 5 min 15s (Table 1).ConclusionsGPU based CS-reconstruction significantly improved thereconstruction time and guarantee a minimal latencyrequired for optimized clinical MR protocol for CMRperfusion during physical stress.FundingNIH:R01EB008743-01A2.1Medecine, BIDMC / Harvard Medical School, Boston, MA, USAFull list of author information is available at the end of the articleRoujol et al. Journal of Cardiovascular MagneticResonance 2013, 15(Suppl 1):E10http://www.jcmr-online.com/content/15/S1/E10© 2013 Roujol et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.Figure 1 Workflow of the iterative CS reconstruction for CMR perfusion immediately after supine bicycle physiologic stress using a remoteworkstation equipped with GPU. The undersampled k-space data are sent to the GPU workstation using hospital network. After reconstruction,the data are sent back to the scanner workstation for final post-processing using the ReconFrame platform for viewing and storage in clinicalhospital PACS system and further analysis of images. This allows integration of CS-accelerated CMR perfusion into the clinical workflow withminimal user interaction.Roujol et al. Journal of Cardiovascular MagneticResonance 2013, 15(Suppl 1):E10http://www.jcmr-online.com/content/15/S1/E10Page 2 of 3Author details1Medecine, BIDMC / Harvard Medical School, Boston, MA, USA. 2Radiology,Beth Israel Deaconess Medical Center and Harvard Medical School, Boston,MA, USA. 3Institute for Biomedical Engineering, ETH Zurich, Zurich,Switzerland.Published: 30 January 2013References1. Greenwood:. The Lancet 2012.2. Yang:. IEEE JSTSP 2010.doi:10.1186/1532-429X-15-S1-E10Cite this article as: Roujol et al.: Low latency iterative reconstruction offirst pass stress cardiac perfusion with physiological stress usinggraphical processing unit. Journal of Cardiovascular Magnetic Resonance2013 15(Suppl 1):E10.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitTable 1 Computation time of the different reconstruction steps obtained for a complete CMR perfusion dataset.Load raw data on the scanner 10sPre-process raw data on the scanner 15sSave pre-processed raw data on the scanner 25sSend data to the GPU workstation 14sCompute the CS reconstruction 4 min, 5s (51 min)Transfer the data back to the scanner workstation 1sPost-process the reconstructed data and save to the scanner database 5sTotal 5 min, 15s (52 min, 10s)The reported times correspond to the treatment of the complete perfusion dataset (32 channels, 90 dynamics, 3 slices, image size=132x132, 100 iterations) foreach reconstruction step. Computation time obtained with the CPU only implementation is also reported (brackets). The proposed GPU reconstruction providesan acceleration factor > 12 compared to the CPU only implementation and provides an overall reconstruction time with a significantly reduced latency.Roujol et al. Journal of Cardiovascular MagneticResonance 2013, 15(Suppl 1):E10http://www.jcmr-online.com/content/15/S1/E10Page 3 of 3

Low latency iterative reconstruction of first pass stress cardiac perfusion with physiological stress using graphical processing unit

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Low latency iterative reconstruction of first pass stress cardiac perfusion with physiological stress using graphical processing unit

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