Hot Topics in Imaging Physics A Key Interdisciplinary Science for 21 st Century Medicine

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1 Hot Topics in Imaging Physics A Key Interdisciplinary Science for 21 st Century Medicine Jeff Siewerdsen, PhD FAAPM Department of Biomedical Engineering Department of Computer Science Russell H. Morgan Department of Radiology Armstrong Institute for Patient Safety and Quality Johns Hopkins University

2 Acknowledgments Contributions The I-STAR Lab ( JW Stayman, W Zbijewski (Hopkins BME) K Taguchi (Hopkins Radiology) R Taylor (Hopkins Computer Science) J Wong, J Lee (Hopkins Rad Onc) G Hugo and J Williamson (VCU) Disclosures NIH R01-CA , R01-EB R01-EB , U01-EB Carestream and Siemens Advisory Board (unpaid): Carestream and Siemens Licensing Agreements: Carestream, Elekta, and Siemens Research Systems / Off-Label Use This work includes systems that are not approved for clinical use.

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4 MBIR New Detectors Prior Information Reconstruction Low-Dose Imaging Task Speed 3D-2D Deformable Registration Multi-Modality Applications Image Analysis Dual-Energy Quantitation Population Models Big Data

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6 3D-2D Registration: LevelCheck T12 L1 S1 L2 L3 L4 L5 Optimization CMA-ES Multi-Starts Pre-Op CT Annotation and Mask DRR Generation Similarity Metric GO = 1 N w i i Ω: u I 1 > t 1 u I 2 > t 2 Intra-Op Radiograph w i = 2 ln cos 1 i Result

7 LevelCheck: Clinical Studies Spine Tech of the Year Otake et al., Phys Med Biol (2011, 2012, 2013) Lo et al., Spine (2014)

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9 Ultrasound-Fluoroscopy Guided Dynamic Dosimetry for Prostate Brachytherapy Registration Reconstructed seeds TRUS volume Real-time Dynamic Dosimetry / Guidance N. Kuo, E. Dehghan, A. Deguet, E. C. Burdette, G. Fichtinger, J. L. Prince, D. Y. Song, J. Lee, Med Phys 41(9) (2014)

10 Ultrasound-Fluoroscopy Guided Dynamic Dosimetry for Prostate Brachytherapy From prototype research platform (Matlab)... to FDA-approval (RadVision) to clinical studies (N = 80 patients) and N. Kuo, E. Dehghan, A. Deguet, E. C. Burdette, G. Fichtinger, J. L. Prince, D. Y. Song, J. Lee, Med Phys 41(9) (2014)

11 3D (Cone-Beam CT) to 2D (Video) for Robotic Surgery W. P. Liu, S. Reaugamornrat, A. Deguet, J. M. Sorger, J. H. Siewerdsen, J. Richmon, R. H. Taylor

12 Intraoperative Imaging: CBCT Daly et al. Med Phys (2006) Deformable Registration: Demons Reaungamornrat et al., Phys Med Biol (2013) CT to Robot Registration Mirota et al. IEEE-TMI (2013) Liu et al. Int J MRCAS (2014) 4. CT to Robot Registration W. P. Liu, S. Reaugamornrat, A. Deguet, J. M. Sorger, J. H. Siewerdsen, J. Richmon, R. H. Taylor

13 500,000 spine surgeries in the US each year 1 out of 30 surgeries exhibit breach Lehman, Spine % require revision (7500 / year) Gautschi, Neuro Focus 2011 D. A. Raley and R. J. Mobbs, Spine (2012)

14 3D-2D Registration: Known-Components Parametric Model Uneri et al. Phys Med Biol (2014) Uneri et al. Phys Med Biol (in press, 2015)

15 3D-2D Registration: KC-Reg Component Projector 2D Overlay Component Registration Radiographs Metric Optimizer 3D Overlay Patient Registration CT Projector Registration Error: e x ~1.4 mm e f ~0.6 o Uneri et al. Phys Med Biol (2014) Uneri et al. Phys Med Biol (2015)

16 Imaging for OR QA Intraoperative Verification of Surgical Product QA Checklist Correct level Correct implant Correct placement Registration Overlay Acceptance Window LAT Oblique AP

17 MBIR New Detectors Prior Information Reconstruction Low-Dose Imaging Task Speed 3D-2D Deformable Registration Multi-Modality Applications Image Analysis Dual-Energy Quantitation Population Models Big Data

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19 Model-Based Image Reconstruction For example: Penalized Likelihood (PL) Estimation An objective function (L) with a roughness penalty (R) on noisy data: Measured Projections Log-Likelihood Balances data fidelity versus the penalty Regularization / Penalty Image Estimate Difference in voxel values Penalty function (e.g., linear, quadratic, Huber, ) Numerous iterative algorithms to solve the objective: Ordered subsets, paraboloidal surrogates,

20 CNR MBIR for C-Arm CBCT FBP PLH ESF width = 1 mm PLH 15 mas CNR ½ Dose FBP 30 mas mas 60 mas PLH Recon Time: 120 s Wang et al. PMB (2013, 2015) 120 mas

21 Noise (mm -1 ) 1000 mm 550 mm MBIR for CBCT of Brain Injury 2 x ⁰ Rotating Anode Tube FBP 15 kw, 30 sec scan 90 kvp, N proj = 720 FBP D 0 = 20 mgy FBP PWLS* PWLS* HU PWLS* ESF Width (mm) 4343CB Flat-Panel Detector Spatial resolution matched at e = 0.40 mm -50 Sisniega et al., Phys Med Biol (2014) Dang et al., Phys Med Biol (2015)

22 MBIR and Task-Driven Imaging Conventionally Ignored by Interventional Devices Interventional Imaging Conventional Intraoperative CT Diagnostic Imaging Preoperative Image Planning Data Flat-Panel Detector Task Definition Prior Information about Patient and Task Task-Driven Trajectory Traditional Circular Trajectory X-ray Source? Patient- and Task-Driven Intraoperative CT

23 Task-Driven Imaging Objective Optimizer Location, Contrast Spatial frequency f y Imaging Task W Task (f) d ' 2 Detectability Index d MTF 2 W 2 task argmax x d yω A, Ωz R Ω A,Ω R 2 NPS MTF W df df df 2 task 2 df df df x y z Ω A, Ω R Detector f x Anatomical Model System Model Ω A Ω R Task-Driven Acquisition Parameters (mas, kvp, ) Reconstruction Parameters (Kernel, Regularization) X-ray source Patient specific planning CT Previous intra-op CBCT Resolution: Noise: MTF Ω A, Ω R NPS Ω A, Ω R Stayman & Siewerdsen, Fully 3D Meeting (2013) Gang, Stayman, and Siewerdsen, Phys Med Biol (2015)

24 Task-Driven Imaging

25 Task-Driven Imaging Circular Scan Task-Driven Trajectory

26 MBIR New Detectors Prior Information Reconstruction Low-Dose Imaging Task Speed 3D-2D Deformable Registration Multi-Modality Applications Image Analysis Dual-Energy Quantitation Population Models Big Data

27 CBCT for Musculoskeletal Radiology Weight-bearing scans Lower extremities: Knee / Ankle / Foot Upper extremities: Hand / Wrist / Elbow Isotropic spatial resolution (~0.5 mm) Soft tissue approaching that of MDCT Low dose (~10 mgy) (cf mgy for high-resolution MDCT) Zbijewski et al. Med Phys 2011 Carrino et al. Radiology 2014 Demehri et al. Eur Radiol 2014 Thawait et al. Eur Radiol 2015

28 CBCT for Musculoskeletal Radiology Three-Source Dual-Energy CBCT Marrow frac.=0.88±0.08 Bone frac.=0.064±0.005 LE: 60 kvp, 7 mgy HE: 105 kvp, 7 mgy PL reconstruction Weight-bearing scans Lower extremities: Knee / Ankle / Foot Upper extremities: Hand / Wrist / Elbow Isotropic spatial resolution (~0.5 mm) Soft tissue approaching that of MDCT Low dose (~10 mgy) (cf mgy for high-resolution MDCT) Marrow frac.=0.85±0.09 Bone frac.=0.029± /mm Fat vol. frac Bone vol. frac Zbijewski et al. SPIE 2015

29 Trabecular Thickness (mm) Structure Model Index Trabecular Volume Fraction Quantitative CBCT: Microarchitecture % MDCT (Siemens Somatom) In Situ a vox = 0.36 mm Micro CT (mct) (Johns Hopkins Univ) Ex Vivo a vox = 0.1 mm 50 CBCT (Dedicated Prototype) 1.0 In Situ a vox = 0.1 mm % 3 % % 1 % 2 % 0.2 MDCT 0 mct CBCT MDCT mct CBCT MDCT (In Situ) MCCT (Ex Vivo) CBCT (In Situ) MDCT (In Situ) MCCT (Ex Vivo) CBCT (In Situ) 0.0 MDCT mct CBCT MDCT (In Situ) MCCT (Ex Vivo) CBCT (In Situ) Muhit et al. SPIE 2013

30 Photon Counting Spectral CT Photon-Counting Detector Characteristic coefficients w Tissue type z Sinogram y Nakada, et al., IEEE MIC (2013) Nakada et al., Med Phys (2015) E Projection noise w pe blood 0.00 Iodine-mixed blood lung fat Geometry Statistical relationship muscle liver muscle location z i = z j = blood α w i w j 2 rib Smooth z i z j β Discontinuous spine w cs

31 Truth FBP PML K. Nakada, CERN Workshop (2015) JE-MAP

32 Dual-Energy CT for RT Treatment Planning E 1 = 90 kvp m( x, E ) w ( x) m ( E ) w ( x) m ( E ) m( x, E ) w ( x) m ( E ) w ( x) m ( E ) E 2 = 140 kvp Z eff w PE w Compt r 20% difference D 90 : MC vs. TG43 Williamson Med Phys: 4115 (2006) Evans Med Phys: (2013) Sampson Med Phys 1058 (2012)

33 Dual-Energy CT for RT Treatment Planning Proton Therapy Range uncertainty: ~3-5 mm Requires 4-5 mm planning marging distal to SOBP Proton topping power depends on both r e and composition via I-value Slide courtesy of J. Williamson

34 MR-to-CT Synthesis Find patches in the atlas image that match that patch Find the patches in the same positions as the best matches Consider an image patch in the source image Combine these patches and retain the central pixel Slide courtesy of J. L. Prince

35 CT is needed for: Surgical planning PET reconstruction Sometimes not acquired: Avoid dose Not standard of care PET/MR scanners Acquire two ultrashort TE MR (UTE) scans; atlas also has CT Compared to other methods, GENESIS is far superior MR-to-CT Synthesis Roy et al., J. Nucl. Med. 2014

36 Imaging Physics Vibrant field of medical physics research Foundation for technology development Accelerates clinical translation Key interdisciplinary science for MANY questions in precision medicine Hot Topics Summary and Discussion Image registration: 3D2D, 3D deformable, multi-modality Image reconstruction: Model-based statistical image reconstruction Image analysis: quantitative imaging Medical physicists ideally situated for impactful research Highly translational clinical / research environment Access to physicians: identify unmet clinical needs Access to patients: first clinical studies Access to data: quality, standards, and curation of big data Unique expertise: science / research integral to daily work and training

37 Thanks and Acknowledgments The I-STAR Lab W Zbijewski Hopkins BME J Wong Hopkins Rad Onc J. Lee Hopkins Rad Onc K Taguchi Hopkins Radiology G Hugo VCU Rad Onc R. Taylor Hopkins Comp Sci J Williamson VCU Rad Onc M Miller Hopkins BME W Stayman Hopkins BME J Prince Hopkins ECE

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39 Images are Numbers