Sajan Goud Lingala Senior Research Scientist Medical Imaging Technology Siemens Healthineers Princeton, NJ 08540 E-mail: [email protected]Tel: (585) 208-6351 webpage: www.slingala.com Magnetic Resonance Imaging (MRI) acquisition and reconstruction design for rapid Research statement: imaging: The overall goal of my research is to develop innovative sparse sampling and constrained reconstruction strategies that push the limits of achievable resolution, signal-to-noise, coverage in multi-dimensional MRI. This will enable the next generation of MRI technology which a) allows for efficient extraction of quantitative information (eg. quantification of blood-brain barrier leakage for tumor characterization, quantification of myocardial perfusion) b) allows for new scientific ap- plications (eg. rapid real-time imaging of vocal tract dynamics for speech production), and c) also improves patient comfort and compliance during imaging (eg. enabling free breathing, more rapid examinations). Siemens Healthineers, Princeton, NJ Mar 2017 - current Employment Senior Research Scientist Area: Compressed sensing MRI product development University of Southern California, Los Angeles, CA Jan 2014 - Feb 2017 Postdoctoral Research Associate Magnetic Resonance Engineering Laboratory (mrel.usc.edu) Signal Analysis and Language Interpretation Laboratory (sail.usc.edu) Department of Electrical Engineering Viterbi School of Engineering Research area: Novel MRI acquisition and constrained reconstruction method design; Application areas include Real-Time upper-airway MRI, and Dynamic Contrast Enhanced MRI (brain, & heart). Mentors: Prof. Krishna S. Nayak, and Prof. Shrikanth Narayanan The University of Iowa, Iowa city, IA 2008 -2013 Education Ph.D., Biomedical Engineering Transferred from University of Rochester in Aug 2011 GPA: 4.3/4.3 Thesis: Novel adaptive reconstruction schemes for accelerated myocardial perfusion MRI Advisor: Prof. Mathews Jacob Indian Institute of Technology, Bombay, Mumbai, India 2006 - 2008 M. Tech., Biomedical Engineering Cumulative Performance Index, CPI : 9.58/10 Thesis: Signal and Image processing for MRI Advisor: Prof. Vikram Gadre Osmania University College of Engineering, Hyderabad, India 2002 - 2006 B. E., Biomedical Engineering Percentage: 77.98 Thesis: Design of a low cost ECG amplifier in a Central Monitoring Station Advisor: Prof. Satyanarayana Junior Fellow of the International Society of Magnetic Resonance in Medicine (ISMRM) Honors & Awards Recognition by the ISMRM society as an outstanding researcher at an early stage in the career, with an established and long-term commitment to ISMRM. May 2016
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Sajan Goud Lingala
Senior Research ScientistMedical Imaging TechnologySiemens HealthineersPrinceton, NJ 08540
Magnetic Resonance Imaging (MRI) acquisition and reconstruction design for rapidResearchstatement: imaging: The overall goal of my research is to develop innovative sparse sampling and constrained
reconstruction strategies that push the limits of achievable resolution, signal-to-noise, coverage inmulti-dimensional MRI. This will enable the next generation of MRI technology which a) allowsfor efficient extraction of quantitative information (eg. quantification of blood-brain barrier leakagefor tumor characterization, quantification of myocardial perfusion) b) allows for new scientific ap-plications (eg. rapid real-time imaging of vocal tract dynamics for speech production), and c) alsoimproves patient comfort and compliance during imaging (eg. enabling free breathing, more rapidexaminations).
� Siemens Healthineers, Princeton, NJ Mar 2017 - currentEmployment
Senior Research ScientistArea: Compressed sensing MRI product development
� University of Southern California, Los Angeles, CA Jan 2014 - Feb 2017Postdoctoral Research AssociateMagnetic Resonance Engineering Laboratory (mrel.usc.edu)Signal Analysis and Language Interpretation Laboratory (sail.usc.edu)Department of Electrical EngineeringViterbi School of EngineeringResearch area: Novel MRI acquisition and constrained reconstruction method design;
Application areas include Real-Time upper-airway MRI, and Dynamic Contrast Enhanced MRI (brain, &
heart).
Mentors: Prof. Krishna S. Nayak, and Prof. Shrikanth Narayanan
� The University of Iowa, Iowa city, IA 2008 -2013EducationPh.D., Biomedical EngineeringTransferred from University of Rochester in Aug 2011GPA: 4.3/4.3Thesis: Novel adaptive reconstruction schemes for accelerated myocardial perfusion MRI
Advisor: Prof. Mathews Jacob
� Indian Institute of Technology, Bombay, Mumbai, India 2006 - 2008M. Tech., Biomedical EngineeringCumulative Performance Index, CPI : 9.58/10Thesis: Signal and Image processing for MRI
Advisor: Prof. Vikram Gadre
� Osmania University College of Engineering, Hyderabad, India 2002 - 2006B. E., Biomedical EngineeringPercentage: 77.98Thesis: Design of a low cost ECG amplifier in a Central Monitoring Station
Advisor: Prof. Satyanarayana
� Junior Fellow of the International Society of Magnetic Resonance in Medicine (ISMRM)Honors &Awards Recognition by the ISMRM society as an outstanding researcher at an early stage in the career, with an
established and long-term commitment to ISMRM. May 2016
� IEEE-ISBI travel awards funded by NSF 2010, 2013
� Graduate student travel award, University of Rochester 2010
� Nitish Thakor award for excellence in M.Tech Biomedical Engineering,Indian Institute of Technology Bombay June 2008
� Best undergraduate thesis award, Biomedical Engineering, Osmania University June 2006
� Data-driven models for whole heart free breathing first pass myocardial perfusion MRIGrantsUniversity of Southern California, Los Angeles, CaliforniaPostdoctoral Provost’s grant, July 2015-May 2016 $ 25,000Role: Principal Investigator
� High resolution systolic free breathing perfusion MRI of the whole heartAmerican Heart Association (AHA) - Mid-West AffiliatePredoctoral Fellowship, July 2012 - Dec 2013 $ 26,000 per yearGrant number: AHA12PRE11920052Role: Principal Investigator
� Service:ProfessionalActivities · Annual meeting program committee (AMPC) member, International Society of Magnetic Resonance
in Medicine (ISMRM).
· Working committee member of ISMRM’s MR-Hub, a forum directed towards open source reproduciblesoftware sharing.
� Reviewer:
� Journals:
· Scientific Reports, Nature
· Magnetic Resonance in Medicine
· IEEE Transactions on Medical Imaging
· Journal of Magnetic Resonance Imaging
· IEEE Transactions on Biomedical Engineering
· IEEE Transactions on Image Processing
· Medical Physics
· IEEE Signal Processing Letters
· IEEE Transactions on Computational Imaging
· Medical Engineering and Biological Computing
Sajan Goud Lingala
· PLOS ONE
· Magnetic Resonance Imaging
� Conferences:
· IEEE-International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2010
· IEEE-International Symposia on Biomedical Imaging (ISBI) 2011
· IEEE-International Conference on Image Processing (ICIP) 2013
· International Society for Magnetic Resonance in Medicine (ISMRM) 2015
· International Society for Magnetic Resonance in Medicine (ISMRM) 2016
· IEEE-International Symposia on Biomedical Imaging (ISBI) 2015
· IEEE-International Symposia on Biomedical Imaging (ISBI) 2016
· IEEE-International Symposia on Biomedical Imaging (ISBI) 2017
� Membership:
· International Society for Magnetic Resonance in Medicine (ISMRM)
· Institute of Electrical and Electronics Engineers (IEEE)
· Radiological Society of North America (RSNA)
· Institute of Electrical and Electronics Engineers Communications Society
· Society of Cardiovascular Magnetic Resonance (SCMR)
· American Heart Association (AHA)
Patents
1. S.G. Lingala, M. Jacob, C. Chefd’hotel, M. Nadar, L. Zhang, “Unifying Reconstruction andMotion Estimation in First Pass Cardiac Perfusion MR Imaging”, United States Patent Appli-cation number: 20120148128, June 2012.
Book chapterPublications
1. S.G. Lingala, M. Jacob, “Accelerated Dynamic MRI using adaptive signal models”, (BookChapter), MRI: Physics, Image Reconstruction, and Analysis, CRC Press 2015.
Journal (IF: Impact Factor)
In review/ Submitted articles
1. Y. Lim, S.G. Lingala, A. Toutios, S. Narayanan, K.S. Nayak, “Improved depiction of Vocaltract articulators in spiral real-time MRI using automatic auto-focus off resonance correction”,Magnetic Resonance in Medicine, (in review), IF: 3.57.
2. S.G. Lingala, Y. Guo, Y. Zhu, R.M. Lebel, M. Law, K.S. Nayak, ”Accelerated dynamiccontrast enhanced MRI using contrast agent kinetic models as temporal constraints”, MedicalPhysics (in review) IF: 2.635
Published/ in-press articles
1. Y. Guo, S.G. Lingala, R.M. Lebel, Y. Zhu, K.S. Nayak, ”Joint estimation of arterial inputfunction and tracer kinetic parameters for under-sampled DCE-MRI”, Magnetic Resonance inMedicine, in press.
2. J. Toger, T. Sorensen, K. Somandepalli, A. Toutios, S.G. Lingala, S. Narayanan, K.S. Nayak,“Test-retest repeatability of human speech biomarkers from static and real-time dynamic mag-netic resonance imaging”, Journal of Acoustical Society of America (JASA), 141, pp. 3323-3336,2017
3. S.G.Lingala, Y. Zhu, Y. Lim, A. Toutios, Y. Ji, W-C. Lo, N. Seiberlich, S. Narayanan, K.S.Nayak, “Feasibility of spiral through-time GRAPPA for low latency accelerated real-time MRIof speech”, Magnetic Resonance in Medicine (early view). (IF: 3.57).
Sajan Goud Lingala
4. Y. Guo, S.G. Lingala, Y. Zhu, R.M. Lebel,, K.S. Nayak, “Direct estimation of pharmaco-kinetic parameters in highly accelerated DCE-MRI”, Magnetic Resonance in Medicine, earlyview, Nov 2016, doi: 10.1002/mrm.26540. (IF: 3.57).
5. X. Miao, S.G. Lingala Y. Guo, T. Jao, M. Usman, C. Prieto, K.S. Nayak, “Accelerated cardiaccine MRI using locally low rank and finite difference sparsity constraints” , 34(6), pp.707714,July 2016, Magnetic Resonance Imaging. (IF: 2.09).
6. Y. Guo, R.M Lebel, Y Zhu, S.G. Lingala, M.S Shiroishi, M. Law, K.S. Nayak, “High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evalu-ation in brain tumor patients”, Medical Physics, 43, 2016, early view: doi: 10.1118/1.4944736..(IF: 2.635).
7. S.G. Lingala, Y. Zhu, Y-C. Kim, A. Toutios, S. Narayanan, K.S. Nayak, “A fast and flexibleMRI based system for dynamic study of vocal production”, Magnetic Resonance in Medicine(early view, Jan 2016, doi: 10.1002/mrm.26090 ) (IF: 3.57).
8. Y.Q. Mohsin, S.G. Lingala, E. DiBella, M. Jacob, “Accelerated dynamic MRI using PatchRegularization for Implicit motion Compensation (PRICE)”, Magnetic Resonance in Medicine,Apr 2016 (early view), doi: 10.1002/mrm.26215.(IF: 3.57).
9. Y. Zhu, Y. Guo, S.G. Lingala, R.M. Lebel, M. Law, K.S. Nayak, “GOCART: GoLden AngleCartesIan Encoded Randomization for time-resolved 3D MRI”, Magnetic Resonance Imaging,34(7):940-50, Sep 2016.(IF: 2.090).
10. S. Bhave, S.G. Lingala, J. Newell, S. Nagle, M. Jacob, “Blind Compressed Sensing Enables3D Dynamic Free Breathing MR Imaging of the Respiratory Mechanics: A Feasibility Study”,Investigative Radiology, Special issue on Advances for Clinical Imaging involving DataSparsity in MRI and CT, 51(6):387-99, June 2016. (IF: 4.43).
11. S.G. Lingala, M. Miquel, B.P. Sutton, K.S. Nayak, “Recommendations for real time speechMRI”, Journal of Magnetic Resonance Imaging, vol. 43 (1), pp: 28-44, Jan 2016. (IF: 3.21).
13. S.G. Lingala, Y. Zhu, Y-C. Kim, A. Toutios, S. Narayanan, K.S. Nayak, “Towards High FrameRate Real-Time Magnetic Resonance Imaging of Speech Production”, SPIE News Room, doi:10.1117/2.1201505.005916.
14. S. Bhave, S.G. Lingala, C.P. Johnson, V.A. Magnotta, M. Jacob, “Accelerated whole-brainmulti-parameter mapping using blind compressed sensing”, Magnetic Resonance in Medicine,early view, doi: 10.1002/mrm.25722. (IF: 3.57).
15. S.G. Lingala, E. DiBella, M. Jacob, “Deformation corrected compressed sensing (DC-CS):a novel framework for accelerated dynamic MRI”, IEEE Transactions on Medical Imaging,vol.34(1), pp. 72-85, Jan 2015. (IF: 3.39).
16. S.G. Lingala, E. DiBella, G. Adluru, C. McGann, M. Jacob, “Accelerated free breathingmyocardial perfusion MRI using multi coil radial k-t SLR”, Physics in Medicine and Biology,vol.58(20),pp.7309-7327, Sep 2013.(IF: 3.39).
17. S.G. Lingala, M. Jacob, “Blind compressive sensing dynamic MRI”, IEEE Transactions onMedical Imaging, pp 1132-1145, vol.32(6), June 2013.(IF: 3.39).
18. Y. Hu, S.G. Lingala, M. Jacob, “A fast majorize-minimize algorithm for the recovery of sparseand low rank matrices, IEEE Transactions on Image Processing, vol.21 (2), pp.742-753, Feb2012.(IF: 3.625).
19. S.G. Lingala, Y. Hu, E. DiBella, M. Jacob, “Accelerated dynamic MRI using sparsity andlow-rank structure: k-t SLR”, IEEE Transactions on Medical Imaging, (Special issue on Com-pressive Biomedical Imaging), vol. 30 (5), pp. 1042-54, May 2011. (IF: 3.39).
Sajan Goud Lingala
Conference proceedings
1. S.G. Lingala, Y. Guo, N. Nallapareddy, Y. Bliesener, R. Marc Lebel, K.S. Nayak, ”Nestedtracer-kinetic model-based DCE-MRI reconstruction from under-sampled data”, Proceedingsof 25th International Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions,2017.
2. Y. Guo, S.G. Lingala, R. Marc Lebel, K.S. Nayak, ”Joint estimation of arterial input functionand tracer kinetic parameters from under-sampled data”, Proceedings of 25th InternationalSociety of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2017. Receipient ofan ISMRM Magna Cum Laude award
3. Y. Guo, S.G. Lingala, K.S. Nayak, ”Reconstruction of DCE tracer kinetic parameters fromunder-sampled data with a flexible model consistency constraint”, Proceedings of 25th Inter-national Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2017.
Y. Bliesener, S.G. Lingala, J.P. Haldar, K.S. Nayak, ”Comparison of (k,t) sampling schemesfor DCE-MRI pharmaco-kinetic parameter estimation”, Proceedings of 25th International So-ciety of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2017.
Y. Lim, S.G. Lingala, S. Narayanan, K.S. Nayak, ”Correction of dynamic off-resonance inspiral 2D real-time MRI of speech”, Proceedings of 25th International Society of MagneticResonance in Medicine (ISMRM) Scientific Sessions, 2017. (e-poster presentation)
4. J. Chen, S.G. Lingala, Y. Lim, A. Toutios, S. Narayanan, K.S. Nayak, ”Task-based Optimiza-tion of Regularization in highly accelerated speech RT-MRI”, Proceedings of 25th InternationalSociety of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2017.
5. R. Marc Lebel, Y. Guo, S.G. Lingala, R. Frayne, K.S. Nayak, ”Highly accelerated DCEimaging with integrated T1 mapping”, Proceedings of 25th International Society of MagneticResonance in Medicine (ISMRM) Scientific Sessions, 2017.
6. J. Toger, T. Sorensen, K. Somandepalli, A. Toutios, S.G. Lingala, S. Narayanan, K.S. Nayak,”Test-retest repeatability of human speech biomarkers from static and real-time dynamic mag-netic resonance imaging”, Proceedings of 25th International Society of Magnetic Resonance inMedicine (ISMRM) Scientific Sessions, 2017.
7. R.M. Lebel, N. Nallapareddy, S.G. Lingala, L.B. Andersen, R. Frayne, K.S. Nayak, “Auto-matic bolus detection for dynamic contrast enhanced imaging with sparse sampling”, Societyof Magnetic Resonance Angiography, p. 76, (2016).
8. S.G. Lingala, A. Toutios, J. Toger, Y. Lim, Y. Zhu, Y-C. Kim, C. Vaz, S. Narayanan, K.S.Nayak, “State-of-the-art MRI Protocol for Comprehensive Assessment of Vocal Tract Structureand Function”, Interspeech, 2016.
9. A. Toutios, S.G. Lingala, C. Vaz, J. Kim, J. Esling, P. Keating, M. Gordon, D. Byrd, L.Goldstein, K. Nayak, S. Narayanan, “Illustrating the Production of the International PhoneticAlphabet Sounds using Fast Real-Time Magnetic Resonance Imaging”, Interspeech, 2016.
10. J. Toger, Y. Lim, S.G. Lingala, S. Narayanan, K. Nayak, “Sensitivity of quantitative RT-MRImetrics of vocal tract dynamics to image reconstruction settings”, Interspeech, 2016.
11. Y. Lim, S.G. Lingala, A. Toutios, S. Narayanan, K.S. Nayak, “Improved Depiction of TissueBoundaries in Vocal Tract Real-time MRI using Automatic Off-resonance Correction”, Inter-speech, 2016.
12. A. Kammen, B. Mordkin, S. Cen, S.G. Lingala, M. Law, K.S. Nayak, ”High resolution DCE-MRI permeability differentiates pseudoprogression from true disease progression in primaryhigh-grade gliomas and metastatic melanoma”, ASNR (American Society of Neuroradiology)54th Annual meeting, Washington, May 2016.
13. A. Kammen, B. Morkin, S. Cen, S.G. Lingala, J. Arevalo-Perez, A. Thomas, K. Peck, T.Kaley, M. Law, R. Young, K.S. Nayak, ”Multi-center study demonstrates dynamic contrastenhanced permeability MRI differentiates pseudo progression from true progression in primaryhigh-grade gliomas and metastatic melanoma”, ASNR (American Society of Neuroradiology)54th Annual meeting, Washington, May 2016.
Sajan Goud Lingala
14. N. Nallapareddy, S.G. Lingala, Y. Guo, R.M. Lebel, B. Driscoll, R.J. Bosca, C. Coolens, M.Shiroishi, C. Chung, M. Law, K.S. Nayak, ”Validation of highly accelerated DCE-MRI using aperfusion phantom”, Annual meeting of Radiological Society of North America (RSNA), 2016.
15. S.G. Lingala, S. Bhave, Y. Zhu, K.S. Nayak, M. Jacob, “Temporal point spread functioninterpretation of low rank, dictionary learning models in dynamic MRI”, Annual meeting ofthe International Society of the Magnetic Resonance in Medicine (ISMRM), May 2016 (e-posterpresentation).
16. S.G. Lingala, Y. Guo, Y. Zhu, R.M. Lebel, N. Nallapareddy, M. Law, K.S. Nayak, “Acceler-ated brain DCE-MRI using Contrast Agent Kinetic Models as Temporal Constraints”, Annualmeeting of the International Society of the Magnetic Resonance in Medicine (ISMRM), May2016 (oral presentation).
17. S.G. Lingala, Y. Zhu, Y. Ji, A. Toutios, W-C Lo, N. Seiberlich, S. Narayanan, K.S. Nayak,“Accelerating Real-time MRI of speech using spiral through-time GRAPPA”, Annual meetingof the International Society of the Magnetic Resonance in Medicine (ISMRM), May 2016 (e-poster presentation).
18. Y. Guo, S.G. Lingala, Y. Zhu, R.M. Lebel, K.S. Nayak, “Direct reconstruction of pharma-cokinetic parameter maps in accelerated brain DCE-MRI using the extended Tofts model”,Annual meeting of the International Society of the Magnetic Resonance in Medicine (ISMRM),May 2016 (oral presentation).
19. S. Bhave, S.G. Lingala, J. Newell, S. Nagle, M. Jacob, “Clinical evaluation of the respiratorymechanics using accelerated 3D dynamic free breathing MRI reconstruction”, IAnnual meetingof the International Society of the Magnetic Resonance in Medicine (ISMRM), May 2016 (oralpresentation). Recepient of an ISMRM summa cum Laude merit award
20. S.G. Lingala, Y. Mohsin, S. Bhave, X. Miao, Y. Guo, K.S. Nayak, E. DiBella, M. Jacob,“Data-driven adaptive reconstruction algorithms for accelerated dynamic MRI: an open sourceMATLAB package”. ISMRM Workshop on Data Sampling and Image Reconstruction, Sedona,Arizona, Jan 2016.
21. S.G. Lingala, Y. Guo, Y. Zhu, N. Nallapareddy, R.M. Lebel, M. Law, K.S. Nayak. “Acceler-ated brain DCE-MRI using Contrast Agent Kinetic Models as Temporal Constraints”. ISMRMWorkshop on Data Sampling and Image Reconstruction, Sedona, Arizona, Jan 2016.
22. Y. Guo, Y. Zhu, S.G. Lingala, R.M. Lebel, K.S. Nayak, “Direct Reconstruction of Tracer-Kinetic Parameter Maps from Prospective Highly Under-sampled DCE-MRI”. ISMRM Work-shop on Data Sampling and Image Reconstruction, Sedona, Arizona, Jan 2016.
23. K.S. Nayak, Y. Guo, Y. Zhu, S.G. Lingala, R.M. Lebel, N. Nallapareddy, M.S. Shiroishi, M.Law. “Improved clinical DCE-MRI pipeline for high resolution, whole brain imaging: applica-tion to brain tumor patients.” Radiological Society of North America (RSNA), 2015, Chicago.
24. S.G. Lingala, Y. Guo, Y. Zhu, S. Barnes, R.M. Lebel, K.S. Nayak, “Accelerated DCEMRI using constrained reconstruction based on pharmaco-kinetic model dictionaries”, Interna-tional Society for Magnetic Resonance in Medicine (ISMRM), 2015, p.196. Recipient of anISMRM Magna cum Laude Merit Award
25. S.G. Lingala, Y. Zhu, Y-C Kim, A. Toutios, S. Narayanan, K.S. Nayak, “High spatio-temporalresolution multi-slice real time MRI of speech using golden angle spiral imaging with constrainedreconstruction, parallel imaging, and a novel upper airway coil”, Proceedings of 23rd Interna-tional Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p. 689.Recipient of an ISMRM Magna cum Laude Merit Award
26. Y. Guo, Y. Zhu, S.G. Lingala, R.M. Lebel, K.S. Nayak, “Highly Accelerated Brain DCEMRI with Direct Estimation of Pharmacokinetic Parameter Maps”, Proceedings of 23rd In-ternational Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p.573. Recipient of an ISMRM Summa cum Laude Merit Award
Sajan Goud Lingala
27. X.Miao, S.G. Lingala, Y. Guo, T. Jao, K.S. Nayak, “Accelerated cardiac cine MRI usingLocally Low rank and Total variation Constraints”, Proceedings of 23rd International Societyof Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p. 571. Recipient ofan ISMRM Magna cum Laude Merit Award
28. Y. Zhu, Y. Guo, S.G. Lingala, R.M. Lebel, M. Law, K.S. Nayak, “Evaluation of GLACIER3DFT phase encode order for DCE-MRI”, Proceedings of 23rd International Society of MagneticResonance in Medicine (ISMRM) Scientific Sessions, 2015, pp. 2535.
29. Y. Zhu, Y. Guo, S.G. Lingala, S. Barnes, R.M. Lebel, M. Law, K.S. Nayak, “Evaluation ofDCE-MRI data sampling, reconstruction and model fitting using digital brain phantom”, Pro-ceedings of 23rd International Society of Magnetic Resonance in Medicine (ISMRM) ScientificSessions, 2015, pp. 3052.
30. R.M. Lebel, Y. Guo, Y. Zhu, S.G. Lingala, R. Frayne, L.B. Andersen, J. Easaw, K.S. Nayak,“The Comprehensive Contrast-enhanced Neurovascular Exam”, Proceedings of 23rd Interna-tional Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, pp. 3705.
31. Y.Q. Mohsin, S.G. Lingala, E. DiBella, M. Jacob, “Motion Compensated Free BreathingMyocardial Perfusion MRI Using Iterative Non Local Shrinkage”, Proceedings of 23rd Inter-national Society of Magnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p.2684.
32. S. Bhave, S.G. Lingala, C.P. Johnson, V.A.Magnotta, M. Jacob, “Whole Brain multi-parameter mapping using dictionary learning”, Proceedings of 23rd International Society ofMagnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p. 1675.
33. S. Bhave, S.G. Lingala, J. Newell, A. Comellas, M. Jacob, “Dynamic 3D MRI Of the wholeLung using Constrained Reconstruction with learned dictionaries”, Proceedings of InternationalSociety ofMagnetic Resonance in Medicine (ISMRM) Scientific Sessions, 2015, p 1466.
34. S. Bhave, S.G. Lingala, M. Jacob, “A variable splitting based algorithm for Fast multi-coilBlind compressed sensing MRI reconstruction”, IEEE International conference of the IEEEEngineering in Medicine and Biology Society (IEEE-EMBS), 2014. Finalist, Student papercompetition.
35. S. Poddar, S.G. Lingala, M. Jacob, “Joint recovery of undersampled signals on a manifold:application to free breathing cardiac MRI”, IEEE International Conference on Acoustics,Speech, and Signal Processing (ICASSP), 2014. Best student paper award in the categoryof Bio Imaging and Signal processing.
36. S.G. Lingala, Y. Mohsin, J. Newell, J. Sieren, D. Wang, D. Thedens, M. Jacob, “Towards 3Ddynamic MRI of the lung using blind compressed sensing”, International Society for MagneticResonance in Medicine (ISMRM), 2014. p0298. Recipient of an ISMRM Magna cumLaude Merit Award
37. Y. Mohsin, Z. Yang, S.G. Lingala, M. Jacob, “Motion compensated dynamic imaging with-out explicit motion estimation”, International Society for Magnetic Resonance in Medicine(ISMRM), 2014.
38. S. Poddar, S.G. Lingala, M. Jacob, “Real Time Cardiac MRI using Manifold Sensing”, In-ternational Society for Magnetic Resonance in Medicine (ISMRM), 2014.
39. S.G. Lingala, E. DiBella, M. Jacob, “A generalized motion compensated compressed sens-ing scheme for highly accelerated myocardial perfusion MRI”, (SCMR)-ISMRM workshop onAccelerated CMR: Towards Comprehensive Clinical Cardiovascular Imaging, 2014.
40. S.G. Lingala, Y. Mohsin, J. Newell, J. Sieren, D. Thedens, P. Kollasch, M. Jacob, “Accelerateddynamic imaging of the lung using blind compressive sensing”, (SCMR)-ISMRM workshop onAccelerated CMR: Towards Comprehensive Clinical Cardiovascular Imaging, 2014.
41. S.G. Lingala, E. DiBella and M. Jacob, “Accelerated myocardial perfusion MRI using motioncompensated compressed sensing (MC-CS)”, International Society for Magnetic Resonance inMedicine (ISMRM), 2013.
Sajan Goud Lingala
42. S.G. Lingala, and M. Jacob, “Blind compressed sensing dynamic MRI with sparse dictionar-ies”, International Society for Magnetic Resonance in Medicine (ISMRM), 2013.
43. S.G. Lingala, M. Jacob, “Accelerated dynamic MRI using sparse dictionary learning”, Waveletsand Sparsity IV, Proceedings of SPIE, 8858, Aug 2013.
44. S.G. Lingala and M. Jacob, “Blind compressed sensing with sparse dictionaries for accelerateddynamic MRI” , IEEE-International Symposia on Biomedical Imaging, ISBI, 2013.
45. S.G. Lingala and M. Jacob, “Blind Compressed Sensing dynamic MRI”, International Societyfor Magnetic Resonance in Medicine (ISMRM), 2012. Recipient of an ISMRM MagnaCum Laude Merit award.
46. S.G. Lingala and M. Jacob, “A Blind compressive sensing frame work for accelerated dynamicMRI” , IEEE-International Symposia on Biomedical Imaging, ISBI, 2012.
47. S.G. Lingala, E. DiBella, M. Nadar, C. Chefd’hotel and M. Jacob, “Motion compensated re-construction for myocardial perfusion MRI”, Society for Cardiac Magnetic Resonance (SCMR),2012.
48. S.G. Lingala, E. DiBella and M. Jacob, “Accelerated imaging of rest and stress myocardialperfusion imaging using multi-coil k-t SLR: A feasibility study”, Society for Cardiac MagneticResonance (SCMR), 2012.
49. S.G. Lingala, Y. Hu, E. DiBella, M. Jacob, “Highly accelerated myocardial perfusion MRIusing k-t SLR with parallel imaging”, International Society for Magnetic Resonance in Medicine(ISMRM) 2011.
50. Y. Hu, S.G. Lingala, M. Jacob, “High resolution structural free breathing cardiac MRI enabledby k-t SLR”, International Society for Magnetic Resonance in Medicine (ISMRM) 2011.
51. S.G. Lingala, Y. Hu, and M. Jacob, “Blind linear models for the recovery of dynamic MRIdata”, IV conference on Wavelets and Sparsity, SPIE, Aug 2011.
52. S.G. Lingala, Y. Hu, E. DiBella, M. Jacob, “Accelerated first pass perfusion cardiac perfusionMRI using improved k-t SLR”, IEEE-International symposium on Biomedical Imaging (ISBI)2011.
53. S.G. Lingala, M. Nadar, C. Chefd’hotel, L. Zhang, M. Jacob, “Unified reconstruction andmotion estimation in first pass cardiac perfusion imaging”, IEEE-International symposium onBiomedical Imaging (ISBI) 2011.
54. S.G. Lingala , M. Jacob, “Free Breathing Cardiac Perfusion MR Reconstruction using a sparseand low rank model: Validation with the Physiologically Improved NCAT phantom”, (in press)IEEE-International conference on Communications and Signal Processing (ICCSP) 2011.
55. S.G. Lingala, Y. Hu, M. Jacob, “Real time Cardiac MRI using low rank and sparsity penal-ties”, IEEE-International symposium on Biomedical Imaging (ISBI) 2010.
56. R.K. Bhatt, S.G. Lingala, A.V. Deshmukh, V.M. Gadre,“Quantification of cardiac motion inCardiac Magnetic Resonance Imaging”, in the proceedings of the International Conference onSensors, Signal Processing, Communication, Control and Instrumentation (SSPCCIN), 2008.
57. B.K. Errangi, S.G. Lingala, “Diffusion Tensor Magnetic Resonance Imaging”, proceedings ofIEEE North East Bioengineering conference, pp. 67-68, 2006.
� Invited speaker, Annual meeting of the International Society of Magnetic Resonancein Medicine (ISMRM) April 2017TeachingInvited to deliver an educational talk on “Motion Compensated Reconstruction” in the weekendeducational session track on “Image Acquisition and Reconstruction”
� EE 591: Magnetic Resonance Imaging and ReconstructionPrimary Instructor: Prof. Krishna NayakUniversity of Southern CaliforniaSpring 2015
Sajan Goud Lingala
· Assisted Prof. Krishna Nayak in designing innovative learning methods in this class taught ina “flipped class room” format, including design of in-class group activities, quizzes, assistancein on-line forums for question and answer discussions, and conduction of on-line quizzes.
· Independently delivered a 45-minute video-taped lecture, and conducted a 3-hour in class lec-ture and learning activity on the topic of “Dynamic MRI imaging”.
� EE 591: Magnetic Resonance Imaging and ReconstructionPrimary instructor: Prof. Justin HaldarUniversity of Southern CaliforniaFall 2016
· Independently lectured a 80 minute class on the topic of “Spin echo and Gradient echo”
� Teaching Assistants for courses:
� Signals and Measurements in BME,University of RochesterSpring 2010
� Biomedical Computation,University of RochesterFall 2009
� Biostatistics,Indian Institute of Technology BombaySpring 2008
� Virtual Instrumentation in BME,Indian Institute of Technology BombayFall 2007
� Co-mentored the below trainees along with Prof. Krishna Nayak at University of Southern CaliforniaMentoring(USC)
– Area: Free breathing cardiac 3D cine imaging, Free breathing myocardial 3D first passperfusion imaging, Motion correction, Data adaptive transform design for dynamic MRI
– Area: Design of k-space based digital reference objects for whole-brain DCE-MRI.
· Naren Nallapareddy, M.S student Jan 2015-June 2016
– Area: Validation of sparse DCE-MRI methods using a physical flow phantom.
· Jieshen Chen, M.S student May 2016-current
– Area: Advanced constrained reconstruction methods for improved real-time MRI of thevocal tract.
· Arjun Viswanathan, High school student June 2015-July 2015
– Area: Basics of Fourier Transforms, Introduction to MRI image formation.
Sajan Goud Lingala
1. Analytical Foundations in BMERelevantCourseWork
2. Medical Imaging3. Biostatistics 4. Introduction to Neuro-engineering5. Random Process 6. Wavelets7. Digital signal processing and its Applications 8. Magnetic Resonance Imaging: from spins to brains
9. Pathways to Human Disease
� Operating Systems: Windows 98 or higher, Mac OS, LinuxSkills
� Languages : English(fluent), Telugu(native), Hindi(fluent)
� Born: April 13, 1985 Hyderabad, IndiaPersonalInfo � Legal status: Permanent Resident of the United States
� Prof. Krishna NayakReferencesProfessorDepartment of Electrical EngineeringUniversity of Southern [email protected]
� Prof. Mathews JacobAssociate ProfessorDepartment of Electrical and Computer EngineeringUniversity of [email protected]
� Prof. Edward DiBellaProfessorDepartment of RadiologyUniversity of [email protected]
� Prof. Shrikanth NarayananProfessorDepartment of Electrical EngineeringUniversity of Southern [email protected]
SajanGoudLingala,PhD
LETTER OF INTENT Dear members of search committee, Please find attached herein my research and teaching statements for a possible tenure track faculty position in Biomedical Engineering, University of Iowa, Iowa city. I am very excited on this potential opportunity, and look forward to being a part of the dynamic environment within Univ of Iowa, and continue my research on advancing magnetic resonance imaging methods for improved healthcare, and also lead campus and professional service activities. In my prior research (7 months of industry research experience at Siemens Healthineers, 3 years post-doctorate work at Univ. of Southern California, 5.5 years doctorate work at Univ. of Iowa), I have made significant contributions in the area of accelerated MRI. I have developed novel sparse sampling and constrained reconstruction methods to enable efficient reconstruction from highly undersampled data. I have contributed to the area of data-adaptive compressive sensing, where I developed methods based on advances in compressed sensing, low rank matrix recovery, machine learning, motion compensation, model-based reconstruction, parallel imaging, and non-Cartesian MRI. I have focused all my technological research developments towards translating them to both clinical and basic science applications. My work so far has resulted in 19 published and 2 in review journal publications, and 57 peer reviewed conference papers/abstracts. These are published in leading medical imaging journals including IEEE Transactions on Medical Imaging, Magnetic Resonance in Medicine, Investigative Radiology, Medical Physics, and Journal of Magnetic Resonance Imaging, and presented at annual meetings of International Society of Magnetic Resonance in Medicine, and International Symposium on Biomedical Imaging. I have released my developments as open source software, which lead to its wide adaption across several sites to advance dynamic MRI exams. It has resulted in a citation count of 685 (as per google scholar, accessed on 09/10/2017). My planned research projects use new ideas from signal and image processing, compressive sensing, MR physics, and applied mathematics, and are described in detail in the attached research plan. I am excited to continue to develop innovative methods for next-generation MRI technology and collaborate with several of faculty within Iowa to expand its potential. As listed in my research plan, I will look to submit grant proposals to various funding agencies in the first one to two years of my faculty timeline. The tools I will develop will considerably improve the state-of-the-art in dynamic contrast enhanced imaging, real time MRI of speech and swallowing MRI, free breathing cardio-pulmonary MRI, thus enabling several new clinical and basic science applications. These include improved cancer therapy planning, improved imaging of vocal tract dynamics, comprehensive and improved workflow based ungated free breathing imaging of the cardio-pulmonary system. During my graduate training, I was also fortunate to have served as a teaching assistant to four courses including Bio- statistics, Signals and Measurements, Biomedical Computation, Virtual Instrumentation in BME. In my post-doc training, I have contributed significantly to a graduate course on Magnetic Resonance Imaging and Reconstruction, which was taught in a flipped class room format. I have delivered an educational lecture on Motion Compensated Image Reconstruction as a part of an educational session at annual meeting of International Society of Magnetic Resonance in Medicine in 2017. I have provided more details on my teaching experiences and philosophy in the attached teaching statement. These experiences have built my confidence and an interest in teaching and I look forward to the opportunity to not only teach existing courses in Engineering but also develop new courses. Given an opportunity, I would enjoy discussing my interests in person in the coming days. In the meantime, I am enclosing my curriculum vitae and statements of research and teaching interests. Thank you very much again for your consideration. Sincerely, Sajan Goud Lingala
SajanGoudLingala,PhD
RESEARCH STATEMENT My research interests are in developing non-invasive imaging methods that provide new insights into understanding of the human body, and disease mechanisms. My research to date has been focused on magnetic resonance imaging (MRI), which is a powerful modality with incredible untapped potential due to its flexibility and availability of several contrast mechanisms. My research is motivated by addressing the slow nature of MRI acquisitions, which has severely limited its utility in several multi-dimensional applications. The overall goal of my research is to develop innovative sparse sampling and constrained reconstruction strategies that push the limits of achievable resolution, signal-to-noise, coverage in multi-dimensional MRI. This will enable the next generation of MRI technology which a) enables efficient extraction of quantitative information (eg. quantification of blood-brain barrier leakage, quantification of myocardial perfusion, etc.), and also b) improves patient comfort and compliance during imaging (eg. enabling free breathing, more rapid examinations). I plan to capitalize on all of my industry experience, and post-doctoral and doctoral work, where I have made significant contributions in the area of accelerated MRI, where the goal is to efficiently recover the underlying imaging object from limited number of measurements. The central philosophy is to efficiently exploit inherent redundancies in the multi-dimensional data by utilizing data-driven, and/or model-driven constraints. I have contributed towards innovative data-adaptive, model-driven methods for accelerated dynamic MRI including a) k-t SLR (exploiting sparsity and low rank structure of dynamic data) [1-2]; b) blind compressed sensing (BCS) [3-5]; c) deformation corrected compressed sensing (DC-CS) [6]; d) tracer-kinetic model based dynamic contrast enhanced MRI [7-8]; and e) a fast and flexible MRI system for real-time imaging of vocal tract dynamics during speech [9-10]. My contributions have resulted in 19 journal publications (8 first author), and 2 in review in the leading medical imaging journals including IEEE Transactions on Medical Imaging (impact factor-3.39), Magnetic Resonance in Medicine (impact factor-3.57), Investigative Radiology (impact factor-4.43), Journal of Magnetic Resonance Imaging (impact factor-3.21), IEEE Transactions on Image Processing (impact factor-3.625), and Medical Physics (impact factor: 2.635). These have also resulted in 57 peer-reviewed conference proceedings and abstracts at various international society meetings including International Society of Magnetic Resonance in Medicine (ISMRM), IEEE-International Symposia on Biomedical Imaging (IEEE-ISBI), Society of Cardiovascular Magnetic Resonance (SCMR).
My work has been cited 685 times (as per google scholar accessed on 09/10/2017). To promote reproducible research, I have released all my developments as open-source software at various stages of my career (www.slingala.com/software.html). My work has been adapted at various sites to improve dynamic MRI applications including high-frame real time MRI of speech [9-10] (Univ. of Southern California), free breathing whole-lung imaging (Univ. of Iowa), free breathing abdominal perfusion imaging (Stanford University), high resolution myocardial perfusion imaging (Univ. of Utah, Univ. of Virginia). Portions of my prior work have been recognized by student awards at international conferences (6 ISMRM Magna cum Laude, 2 ISMRM Summa cum Laude), and have received other accolades including 2016 ISMRM Junior Fellow distinction, 2012-13 American Heart Association pre-doctoral fellowship, 2015 University of Iowa Rex Montgomery best doctoral dissertation prize for highest clinical translational value across all disciplines, and 2015 Univ. of Southern California Provost’s post-
SajanGoudLingala,PhD
doctoral research grant.
My planned research projects use new ideas from signal and image processing, compressive sensing, MR physics, and applied mathematics, and are described in detail below. My immediate goal in the next two years is to develop each of these projects into independent grant proposals for the NSF CAREER award, American Cancer Society Research Scholar grant, American Heart Association scientists development grant, and a NIH R21 proposal. The tools I will develop will considerably improve the state-of-the-art in dynamic contrast enhanced imaging, speech and swallowing MRI, and free breathing cardio-pulmonary exams, thus enabling several new research and clinical applications. These include improved cancer therapy planning, improved assessment of neurological conditions including multiple sclerosis, Alzheimer’s disease, and aging, assessing vocal tract dynamics in speech and swallowing disorders, and improved imaging of cardiac abnormalities including ischemia, and myocardial infarction. As I have done throughout my research career, I will collaborate closely with clinical and basic science researchers in pursuing these challenging applications. Project 1: Data-adaptive reconstruction schemes for multi-dimensional MRI
I am interested in the recovery of image data from sub-sampled measurements using constrained image models. I feel that this is an extremely promising approach to improve MRI, which directly translates to improvements in image quality in terms of resolution, signal to noise, and coverage. This approach has tremendous potential to change the paradigm of MRI acquisition, reconstruction by enabling efficient extraction of quantitative information with reduced imaging errors, improved signal to noise, and also improving patient comfort and compliance. Its application to other imaging modalities such as low-dose CT also has tremendous promise. Current constrained reconstruction techniques predominantly use pre-determined transform bases (eg. Fourier, wavelet bases), which are problematic because there is a potential misfit between the model representation and the data. Many transform coefficients are often required to accurately represent the signal at hand. This limits the maximum achievable acceleration rate. Moreover, this model makes it difficult to customize the scheme developed for one particular application to another. For example, the use of an algorithm designed for breath-held cardiac cine MRI will be sub-optimal if applied to free breathing MRI.
I will develop new frameworks based on data-driven transforms, which will provide efficient representation of multi-dimensional data. This approach will adapt the signal model to the measured data. I expect to obtain unbiased reconstructions from far fewer of measurements than that is possible with existing Nyquist sampling based schemes (~10-30 fold improvement in imaging speed). I will utilize the acceleration in imaging towards prospectively improving several factors including improving spatio-temporal resolutions, improving signal to noise, and enabling whole organ coverage (some example applications shown in Figure 1). I shall also tailor these developments to novel MRI sampling schemes, which offer complementary acceleration capabilities. These include multi-band excitation, non-Cartesian sampling, parallel imaging. In contrast to current data-adaptive algorithms, which rely on two-step strategies of first estimating the model bases using training data, and then performing reconstruction, my proposed research formulates the joint estimation of the representation and the signal from the entire undersampled data as a single optimization problem [eg. 1-6]. I plan to specifically focus on the following developments:
(a) Novel development of data-driven spatio-temporal constraints with multi-band excitation,
SajanGoudLingala,PhD
non-Cartesian imaging, and parallel imaging. (b) Novel sparse optimization algorithms for non-convex minimization in the context of
multi-dimensional MRI. (c) Application to range of multi-dimensional MRI problems, including but not limited to
dynamic contrast enhanced MRI, free breathing MRI, real-time MRI (eg. of speech and swallowing), myocardial perfusion MRI, functional MRI, diffusion tensor MRI, magnetic resonance spectroscopy, relaxation parameter mapping. Specific details for three of these applications are listed in projects 2, 3, and 4. The proposed data-adaptive framework is a significant departure from classical
approaches of using pre-determined dictionaries a.k.a. compressed sensing. The proposed research allows for the development of efficient optimization algorithms, performance enhancement using tailored cost functions, and novel integration with advances in MRI sampling This will enable a new imaging paradigm with fewer imaging errors (due to improved spatio-temporal resolutions, signal to noise), enables efficient extraction of quantitative information (eg. quantitation of perfusion/permeability over the whole-organ with reduced partial voluming errors (high-resolution), and also enables free breathing exams to improve patient comfort and compliance (eg. elimination of cumbersome repeated breath-holds during stress exams, and while imaging patients with respiratory insufficiency, pediatric subjects). My immediate motivation is to use the novel framework to considerably improve the state of the art in multi-dimensional MRI considered in projects 2-4 which facilitates clinical applications of very high significance; the proposed research is truly transformative.
Project 2: Rapid real-time MRI of the vocal tract with simultaneous audio recordings for speech science, swallowing, and speech disorders applications Speech production involves a complex spatio-temporal co-ordination of various upper-airway articulators (lips, tongue, glottis, epiglottis, velum, teeth, hard palate). During my postdoctoral training, I was involved with the with the Speech Production and Articulation Knowledge Group (SPAN) group at University of Southern California (sail.usc.edu/span). The SPAN group has pioneered the development, and application of real time MRI techniques to noninvasively visualize the vocal tract dynamics. I have contributed toward advancing the state of art rapid imaging for speech MRI. I have developed a new-imaging framework to combine custom upper-airway coil design, spiral acquisition, multi-slice time-interleaving, constrained reconstruction, parallel imaging, and enable higher frame-rate real-time imaging for assessment of speech. This frame-work which achieves images at the rate of 90+frames/second is currently set up as the sequence of choice at USC, and is being routinely used in data-collection pertaining to numerous speech science studies. I have also contributed towards developing a “Recommendations for real-time speech MRI” review article where I have provided in depth discussion of imaging trade-offs in real-time MRI of speech in terms of achievable image quality, model assumptions, artifacts. This article finally provides a set of four recommended protocols in terms of best-practices to perform a speech MRI experiment. I plan to capitalize all my significant experience in speech imaging at USC in this project, and plan to build a fast and flexible real-time MRI framework with simultaneous audio recordings to image the vocal tract dynamics on the MRI magnet at Univ. of Iowa. The goal of this research
SajanGoudLingala,PhD
will be highly interdisciplinary where I will look to collaborate with speech scientists, linguists, head and neck clinicians, and faculty in the department of Communications Sciences and Disorders at Univ of Iowa. I am very excited about the strong presence of potential end-users of this technology within the university, and greatly look forward to the opportunities and the impact the proposed system for upper-airway imaging would create – which include but not limited to answering open questions in speech science, language production, evaluating swallowing disorders, speech disorders, evaluating speech post oro-pharyngeal cancer treatment. This technology and system will also have a seamless translation to various other real-time MRI applications, including but not limited to real-time cardiac MRI, real-time MRI of flow, real-time MRI of joint movements, real-time MRI of the gastro intestinal system. I will proactively look to explore relevant collaborative avenues with various clinical faculty within the school of medicine.
Fig.3: Example real-time MRI data from the fast MRI system to study vocal tract dynamics and its relationship of articulatory dynamics to the acoustic information. Shown here is an example of a subject producing consonant and vowel sounds as captured by rapid real-time MRI at 12 ms/frame. Note that the high time resolution depicts the formation of all the sounds with excellent fidelity and correlates well with the simultaneously acquired audio signal. This frame-work enables simultaneous assessment of articulatory and acoustic dynamics and their interplay while producing speech.
SajanGoudLingala,PhD
Project 3: High spatio-temporal resolution, whole-organ coverage dynamic contrast enhanced MRI Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a potentially powerful quantitative technique to non-invasively characterize tumor/cancer biology, and its response to treatment. It has applications in cancer therapy planning in several body parts including the brain, breast, liver, and prostate, where the response to treatment may be longitudinally assessed. In the brain, DCE-MRI characterizes the blood brain barrier leakiness, which has important implications as a potential early biomarker in the evaluation of neuro-degenerative diseases such as Alzhemier’s disease, multiple sclerosis, and vascular dementia.
DCE-MRI involves intravenous administration of a paramagnetic contrast agent and continuous MRI acquisition of images to track the passage of the contrast through the volume of interest. Pharmaco-kinetic (PK) modeling of the enhancement kinetics of the contrast agent enables quantification of PK parameters such as Ktrans: a volume transfer coefficient across the capillary endothelium, and fractional volumes such as ve (fractional volume of the extravascular extracellular space). These parameters give a direct and quantitative measure of capillary leakiness, which is an important early functional biomarker for characterizing tumor biology, and assessing their response to treatment. Although DCE-MRI was proposed over 20 years ago, the technique has several remaining technical challenges: poor reproducibility, low spatio-temporal resolution, difficulties with arterial input function measurement, selection of an appropriate pharmacokinetic model, and inability to provide large slice coverage. The proposed research aims to tackle these problems through the use of sparse-sampling and constrained reconstruction algorithms tailored to DCE-MRI for specific body-part and application under consideration. In my post-doctoral work, I have made significant contributions in the development of sparse-sampling techniques, and novel model based tracer-kinetic reconstruction algorithms to enable highly accelerated brain DCE-MRI [7-8]. I will capitalize on these developments and adapt it accordingly to various body parts, and applications including choice of appropriate tracer kinetic model, incorporation of motion-estimation into the reconstruction, pre-clinical feasibility
Fig.2: Improved acquisition and reconstruction methods for DCE-MRI. (a) demonstrates a novel pharmaco-kinetic model based reconstruction that efficiently exploits contrast agent kinetic models as temporal constraints to accelerate DCE-MRI. This frame-work does not rely on tuning of parameters (eg. regularization parameters as required by compressed sensing algorithms). Note the improved accuracy in quantifying Ktrans with model-based reconstruction in comparison to compressed sensing. (b) demonstrates an example of prospectively applying model-based reconstruction with novel golden angle Cartesian randomization 3D sampling scheme at an acceleration of R=30 fold to enable whole brain pharmaco-kinetic parameter mapping.
SajanGoudLingala,PhD
studies for reproducibility of the new technique, followed by clinical translation of the technique. This project will greatly improve the accuracy, and reproducibility of DCE-MRI,
allowing generation of high quality PK maps, including permeability mapping across the whole organ. In the brain, blood brain barrier leakage/permeability provides a unique window to assess progression of several neuro-degenerative diseases, and may be an earlier marker than structural abnormalities. Whole-brain mapping enables assessment of differential blood brain barrier leakage patterns in brain diseases, which will further enable understanding of disease mechanisms and may become a diagnostic tool and marker for treatment efficacy. In general, the technical development and translation of sparse-sampling and constrained reconstruction based DCE-MRI will stimulate innovation, drive scientific discovery, and improve health. Project 4: Robust free breathing, high resolution cardio-pulmonary MRI Dynamic imaging forms a key component of several exams in cardio-pulmonary MRI (eg. dynamic cardiac cine MRI, dynamic cardiac perfusion MRI, dynamic MRI of respiratory mechanics). Current clinical protocols based on parallel imaging face a challenging trade-off amongst the spatio-temporal resolutions, coverage, motion artifact reduction, and signal-to-noise. In cardiac MRI, the scans require consistent gating, a great deal of patient co-operation to produce multiple, consistent breath-holds, which can be challenging during stress exams, while imaging patients with significant heart rate variability (eg. atrial fibrillation), and for a wide range of patient population (eg. respiratory insufficiency, pediatrics). The goal of this project is to develop novel dynamic imaging frame-works that enables robust free breathing exams that can provide the characterization of the cardio-pulmonary system with high resolution and whole-organ coverage. I will capitalize on my prior expertise in utilizing data driven models for free breathing myocardial perfusion MRI, and free breathing dynamic lung MRI, and synergistically combine it with other recent advances including simultaneous multi slice imaging, use of multi-element coil arrays, use of efficient non-Cartesian sparse sampling techniques. This project will also be highly translational where I am excited on collaborating with cardiologists, and pulmonologists to identify patient cohorts where the proposed free breathing, and ungated exams will have an immediate translational impact. Summary As a faculty member, I intend to establish a multi-disciplinary research program dedicated to the development of “next generation” MRI technology for quantitative multi-dimensional MRI. I believe my strong background in signal processing and computational science, combined with my clinical translational research experience, provides me with unique skills to bridge the gap between MR physics, engineering, signal processing, and clinical translational research communities. References: 1. S.G. Lingala, Y. Hu, E. DiBella, M. Jacob, "Accelerated dynamic MRI by exploiting low
rank and sparse properties: k-t SLR", IEEE Transactions on Medical Imaging, (Special Issue on Compressive sensing for Biomedical Imaging), pp: 1042-1054, vol.30, May 2011.
2. S.G. Lingala, E. DiBella, G. Adluru, M. Jacob, "Accelerated free breathing myocardial perfusion MRI using multi coil radial k-t SLR", Physics in Medicine and Biology,
SajanGoudLingala,PhD
vol.58(20),pp.7309-7327, Sep 2013. 3. S.G. Lingala, M. Jacob, "Blind compressed sensing dynamic MRI", IEEE Transactions on
Medical Imaging, pp 1132-1145, vol.32(6), June 2013. 4. S. Bhave, S.G. Lingala, C.P. Johnson, V.A. Magnotta, M. Jacob, "Accelerated whole-brain
multi-parameter mapping using blind compressed sensing", Magnetic Resonance in Medicine, (early view, Apr 2015, doi: 10.1002/mrm.25722).
5. S. Bhave, S.G. Lingala, S. Nagle, J. Newell, M. Jacob, "Blind Compressed Sensing Enables 3D Dynamic Free Breating MR Imaging of Lung Volumes and Diaphragm Motion", Investigative Radiology, Special issue on Advances for Clinical Imaging involving Data Sparsity in MRI and CT, in press.
6. S.G. Lingala, E. DiBella, M. Jacob, "Deformation corrected compressed sensing: a novel framework for accelerated dynamic MRI", IEEE Transactions on Medical Imaging, vol.34(1), pp. 72-85, Jan 2015.
7. S.G. Lingala, Y. Guo, Y. Zhu, S. Barnes, R.M. Lebel, K.S. Nayak, Accelerated DCE MRI using constrained reconstruction based on pharmaco-kinetic model dictionaries, International Society for Magnetic Resonance in Medicine (ISMRM)}, 2015, p.196.
8. Y. Guo, Y. Zhu, S.G. Lingala, R.M. Lebel, K.S. Nayak, “Direct estimation of pharmacokinetic parameters from under-sampled DCE-MRI", Magnetic Resonance in Medicine, 2017, early view.
9. Y. Zhu, Y. Guo, S.G. Lingala, R.M. Lebel, M. Law, K.S. Nayak, “GOCART: Golden Angle Cartesian encoded Randomization for Time Resolved 3D MRI”, Magnetic Resonance Imaging, early view, Dec 2015, doi: 10.1016/j.mri.2015.12.030.
10. S.G. Lingala, Y. Zhu, Y.C. Kim, A. Toutios, S. Narayanan, K.S. Nayak, "A fast and flexible MRI system for the dynamic study of vocal tract shaping", Magnetic Resonance in Medicine, early view, Jan 2016, doi: 10.1002/mrm.26090.
11. S.G. Lingala, B.P. Sutton, M.E. Miquel, K.S. Nayak, "Recommendations for real-time speech MRI", Journal of Magnetic Resonance Imaging, vol. 43 (1), pp: 28-44, Jan 2016.
SajanGoudLingala,PhD
DIVERSITY STATEMENT I strongly believe education is for one and for all. Throughout my journey from pursuing home schooling in Iran, schooling and undergraduate education in India, graduate studies in the USA, I have learnt through a fairly diverse type of teaching mechanisms. I strongly recognize that students are very diverse and come from different cultural backgrounds, upbringing, schooling and it is important to provide them the highest quality education regardless of any form of bias. During my time as a postdoc at University of Southern California, I have advised graduate students from very diverse backgrounds such as students from Germany, China, India, South Korea, Vietnam, and USA. I realize that while some students are comfortable in expressing their views, some others are shy and require careful attention. I feel it important to have constant one-on-one discussions to hear the students and their inhibitions and concerns. I also realize that the more diverse a research group or a class room is, the more vibrant, and the more energetic is the knowledge flow and transfer. I will actively work to avoid unconscious preferences in my own interactions with everyone in the department. As an advisor, I will work to recruit diverse graduate and under-graduate students. As an instructor, I will encourage all students to recognize that this beautiful field of biomedical engineering—both in industry and continuing in academics is welcoming and supportive, even when they feel the stress of being in the minority. Above all, I recognize that I do not have all the answers, I will keep listening to other perspectives to understand on this important issue of diversity. Sajan Goud Lingala
SajanGoudLingala,PhD
TEACHING STATEMENT
Experience: The primary reason of me to pursue an academic path back in a university setting is the opportunity it offers to groom the development of under-graduate and graduate students. I find one-on-one mentorship of student research and class-room teaching to be extremely rewarding. I greatly enjoy the challenge of expressing abstract concepts by relating them to what the students already know and by taking “baby steps”, leading them towards deeper understanding. During my masters studies at the Indian Institute of Technology Bombay, I have been a teaching assistant to two courses: (a) Biostatistics; and (b) Virtual Instrumentation in Biomedical Engineering. I have been responsible in designing problems in the homeworks, computer exercises, quizzes, and a final project in both the courses. My overall contributions at IIT Bombay including performance in courses, research, and teaching assistantship were recognized by an award for excellence in masters studies. During my doctoral studies in University of Rochester, and University of Iowa, I was a teaching assistant to two under-graduate courses: (a) Biomedical Computation; and (b) Signals and Measurements in Biomedical Engineering. My responsibilities included conducting weekly lab exercises, class-room teaching, and designing a final project. During my post-doc experience at the University of Southern California (USC), I helped my mentor Prof. Krishna Nayak in conducting the graduate course on “Magnetic resonance imaging and reconstruction”. The course was offered in a “flipped class-room style”, where the students listened to audio/video-taped lectures off-line and the in- class activity was used for deep understanding of the topics. I helped Prof. Nayak in designing innovative learning methods in this class including traditional chalkboard work/problem solving, in-class group work, quizzes, use of on-line tools (eg. Piazza) for question and answer discussions, and conduction of on-line quizzes. In this course, I have independently contributed towards a 45- minute video-taped lecture, and a 3-hour in class activity on the topic of Dynamic MRI imaging. In the subsequent year, the same course was taught by Prof. Justin Haldar. I volunteered and independently lectured a 3 hour class on the topic of Spin echo and gradient echo. More recently at the annual meeting of the International Society of Magnetic Resonance Medicine (ISMRM 2017), I have had the opportunity to deliver a 30 minute educational lecture on Motion compensated image reconstruction. The goal of this lecture was to introduce the topic to physicists and engineers who wish to acquire advanced understanding of MR physics and reconstruction. These teaching experiences as well as the graduate and undergraduate education in India and United States have exposed me to both the teacher and student facets of education as well as strikingly different modes, philosophies, and environments of education.
Philosophy: I strongly believe that teaching should be a core requirement for faculties within leading universities. It is a very rewarding task, both for the students and the instructor; it enables the instructor to strengthen her/hisʼs basics and organize the knowledge. My philosophy is to maximize student involvement in the lessons and concepts being taught. When lecturing to a group, I present topics systematically using everyday analogies to enable the students appreciate the larger context before being absorbed in the details. I also keep the students excited by illustrating the relevance of the abstract concepts
SajanGoudLingala,PhD
to highly relevant practical problems. For example, while teaching Fourier Transforms, I illustrate practical utility in applications such as audio processing, and Magnetic Resonance Imaging. During individual mentoring sessions at office hours, I often reverse roles and allow the student to ʻteachʼ the topic. This typically exposes gaps in understanding and pinpoints any areas of misunderstanding. Aside from scientific and engineering concepts, students also need to develop communication, teamwork, and critical- thinking skills, which is cultivated through writing assignments, presentations, and working in teams on in-depth projects. I am committed towards incorporating new learning techniques and seeking advice from senior faculty in providing high quality teaching. With my strong background in biomedical engineering, signal and image processing, inverse problems, and magnetic resonance imaging, I will be able to teach several core undergraduate and graduate courses as well as related interdisciplinary courses.
Specifically, I am interested in teaching the following Biomedical Engineering courses:
• BME 2200 Systems, Instrumentation and Data acquisition • BME 2210 Bioimaging and Bioinformatics • BME 5210: Medical Imaging Physics • BME 5220 Digital Image Processing • BME 5230 Multi dimensional Medical Imaging Process • BME 5200 Biomedical Signal Processing
Research Mentoring: As a post-doctoral researcher in the Magnetic Resonance Engineering Laboratory, Univ. of Southern California, I have co-mentored five highly motivated PhD students (Yinghua Zhu, Xin Miao, Yi Guo, Yongwan Lim, Yannick Bleisner), 1 Masters student (Naren Nallapareddy), and 1 undergraduate student (Jieshen Chen). I have mentored them in various projects on MRI imaging related to compressed sensing, image reconstruction, rapid imaging, cardiac imaging, dynamic contrast enhanced imaging of the brain, speech imaging. I have also run regular team meetings and journal clubs for in-depth and critical discussion of concepts and ideas, literature review, and helped students in manuscript preparation, and practice for conference presentations. I enjoy to work closely with enthusiastic minds and to help them solve challenging problems in biomedical imaging. It is very gratifying to see them mature and become independent over time.
Summary: I consider teaching to be a crucial component of my academic career. Since I derive great pleasure in explaining things that I understand to others, teaching always had been a gratifying experience to me. I am looking forward to interact with bright new engineers and researchers. I am really confident and excited about supervising and working with a team of graduate and undergraduate students.
