From DQE to TRE: Image Science, Image Guidance, and Cone-Beam CT

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1 W task = F task C task Magnification Focal Spot Size Scatter-to-Primary Ratio kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling PW, PWE NPW, NPWE f J. H. Siewerdsen (Johns Hopkins University) From DQE to TRE: Image Science, Image Guidance, and Cone-Beam CT Jeff Siewerdsen, PhD Department of Biomedical Engineering Johns Hopkins University Johns Hopkins University Schools of Medicine and Engineering Overview Cone-Beam CT Principles and applications Task-based models for imaging performance 3D NPS 3D NEQ Detectability ROC Imaging Task System Geometry Detectability Index Observer Model NEQ Anatomical Background Quantum Noise k b System Design and Optimization Dedicated MSK scanner Physics-driven design Performance / advanced applications Clinical Translation and System Integration A mobile C-arm for intraop CBCT Spine, thoracic, skull base surgery Integration of Imaging + Registration + Tracking + Augmentation 1

2 Cone-Beam CT Projection data Multiple projections (~ ) over ~180 o -360 o Volume reconstruction Sub-mm spatial resolution + soft tissue visibility Cone-Beam CT 2

3 Cone-Beam CT Imaging Bench Flat-Panel Detector a-si:h PD + CsI:Tl (1536 x 2048 pixels, 1-30 fps) X-ray Tube kvp, Pulsed fluoro f cone ~5 o -15 o Optical Bench + Motion Control System 8-axis translation / rotation, 180 o +fan 360 o Repeat for ~360 o Projection Data Pre-Processing CBCT Reconstruction 3D Filtered Backprojection 3

4 Modeling the Imaging Chain Stage Physical Process 0 Incident quanta 1 Interacting quanta 2 Conversion to secondary quanta A: Complete absorption B: K x-ray escape C: K x-ray reabsorption 3 Spread of secondary quanta 4 Coupling of secondary quanta 5 Integration by pixel aperture 6 Sampling of pixel matrix 7 Readout with additive noise A B C Modeling the Imaging Chain Stage Physical Process 0 Incident quanta 1 Interacting quanta 2 Conversion to secondary quanta A: Complete absorption B: K x-ray escape C: K x-ray reabsorption 3 Spread of secondary quanta 4 Coupling of secondary quanta 5 Integration by pixel aperture 6 Sampling of pixel matrix 7 Readout with additive noise 4

5 Extension to Cone-Beam CT Stage Physical Process 0 Incident quanta 7 Projection readout Stage Mathematical Process 8 Ramp Filter 9 Apodization Filter 10 Interpolation 11 Backprojection 12 Sampling Projection T 8 T 9 T III 12 3D Noise-Power Spectrum S(f x, f y, f z ) Broken Sagittal Axial Symmetry NPS S(f x, f y z ) 5

6 3D Noise-Power Spectrum Axial Plane (x,y) NPS (m 2 mm 3 ) Axial NPS S(f x, f y ) 0.4 mas 1 mas 2 mas 4 mas Spatial Frequency, f x (mm -1 ) 3D Noise-Power Spectrum Sagittal Plane (x,z) NPS (m 2 mm 3 ) Sagittal NPS S(f x, f z ) 0.4 mas 1 mas 2 mas 4 mas Spatial Frequency, f z (mm -1 ) 6

7 Image Noise CT image noise depends on Dose Detector efficiency Voxel size Axial, a xy Slice thickness, a z Reconstruction filter 2 k K E 1 D a o xy 3 xy az D o a xy 1 a z Barrett, Gordon, and Hershel (1976) The 3-D NEQ and DQE NEQ Effective number of quanta used at each spatial frequency (Efficiency x Fluence) DQE Fraction of quanta used at each each frequency. Observations: 3D DQE(0) ~ Projection DQE(0) 3D DQE(f) dependent on reconstruction parameters 7

8 A Task-Based Model Detectability Index Imaging Task W task = F task C task Observer Model PW, PWE NPW, NPWE System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio NEQ Anatomical Background k b f NPS Q Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling A Task-Based Model Detectability Index Imaging Task W task = F task C task System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio NEQ Observer Model PW, PWE NPW, NPWE Anatomical Background k b f NPS Q 2 W task ( f ) Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling 8

9 A Task-Based Model Detectability Index Imaging Task Observer Model W task = F task C task PW, PWE NPW, NPWE NEQ NPS Q NPS B System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio Anatomical Background k b f Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling A Task-Based Model Detectability Index Imaging Task Observer Model W task = F task C task PW, PWE NPW, NPWE System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio NEQ Anatomical Background k b f NPS Q 2 2 MTF spot MTF scatter primary +NPS Q scatter Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling 1 1+SPR 2 MTF spot tot NPS Q 9

10 A Task-Based Model Detectability Index Imaging Task Observer Model W task = F task C task PW, PWE NPW, NPWE NEQ 1 1+SPR 2 MTF spot NPS + MTF 2 Q NPS B System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio Anatomical Background k b f Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling Application: Dose Reduction and Tomosynthesis Detectability Index (d ) Quantum Noise Limited q tot = 180 o 150 o 90 o 40 o Anatomical Noise Limited 10 o Anatomical noise typically dominates over quantum noise. Increasing dose Improved detectability! Including anatomical noise is essential to meaningful performance modeling Dose (mgy) 10

11 Human Observer Study 9AFC Tests Darkened reading room Diagnostic-quality display Fixed win / level [90%min, 110%max] 6 observers (physicists) Training set distinct from test set 5 repeats (distinct stimuli) Randomized reading order ~100 minutes for each observer Human Observer Study Uniform Background: Sphere detection Cluttered Background: Large sphere Small sphere Cube / sphere discrimination Encapsulated sphree 11

12 Human Observer Study z x Total Orbit (Tomo Angle) q: 360 o 90 o 40 o 10 o Human Observer Study Theoretical calculation (cascaded systems + task + model observer) 1 d ' A Z (1 erf ( )) 2 2 P corr A Z d' 2 1 ( x d) M 1 Pcorr ( d ', M ) exp f( x) dx 2 2 Measured directly from human observer MAFC tests 12

13 0.8 A z 0.7 B A z 0.7 B PW, PWEi, NPW, NPWE 1.0 NPWEi q tot 0.6 Uniform Background Sphere Detection Human Observer Cube vs. Sphere PW, PWEi, NPW, NPWE NPWEi Human Observer q tot and it Works! 0.8 A z NPW 0.7 NPWEi 0.6 Human Observer q tot B A z NPW 0.7 NPWEi 0.6 Human Observer q tot B Cluttered Background Small Sphere PW, PWEi, NPWE Encapsulated Sphere PW, PWEi, NPWE NPW A z 0.7 NPWEi 0.6 Human Observer q tot B Cluttered Background Large Sphere PW, PWEi NPWE Application to CBCT System Design 13

14 Clinical Motivation Extremities Imaging Musculoskeletal (MSK) / Orthopaedics CT high-resolution bone, ~soft tissue MR exquisite soft tissue; limited resolution CT ( Limitations and Challenges Imaging under load or tension Total knee replacement Longitudinal monitoring Cost, space, and workflow Impingement Subsidence Bone disintegration Fracture healing Therapy response MRI ( Scope of Applications Trauma (bone, joint, soft tissue); Osteoporosis Inflammation (arthritis, gout, lupus) Neoplasm / soft tissue (tendon, cartilage, vascular) A Dedicated Extremities Scanner Compact Self-shielded Upper / lower extremities Allows side entry Standing configuration (weight-bearing) Sitting configuration Standing Configuration Sitting Configuration 14

15 A Dedicated Extremities Scanner FPD Side Entry X-ray Tube Gantry: SDD 55 cm SAD 42 cm Up to 240 o rotation Flat-Panel Detector PaxScan FPD mm pixels 1-30 fps Dual/Dynamic gain X-ray source: Fixed anode 0.5 mm focal spot kvp ma (0.7 kw@100 kvp) Theoretical Basis for System Design Detectability Index 60 kvp Imaging Task Observer Model W task = F task C task PW, PWE NPW, NPWE NEQ d (Mag,kVp) System Geometry Magnification Focal Spot Size Scatter-to-Primary Ratio Anatomical Background k b f Quantum Noise kvp, Dose Scintillator, Detector Pixel Aperture, 2D Sampling Reconstruction Filter Backprojection Voxel Size 3D Sampling High-Frequency Task 3 (High Detection Frequency) Task kvp Magnification Beam Energy (kvp) 15

16 Theoretical Basis for System Design Pixel size (mm) High-Frequency Detection Task Beam Energy (kvp) Low-Frequency Detection Task x1 Binning a pix = mm 2x2 Binning a pix = mm Pixel size (mm) Beam Energy (kvp) CBCT for MSK Radiology and Orthopaedics Compact Self-shielded Upper / lower extremities Allows side entry Standing configuration (weight-bearing) Sitting configuration Standing Configuration Sitting Configuration 16

17 Cadaver Studies Hand Knee Qualitative Study Fresh cadavers Dose = ~4 mgy (~0.06 msv) (compare msv)* zoom Half resolution (0.388 mm) 0.25 mm isotropic voxels W/ and w/o scatter grid Simple scatter correction Elbow Ankle *Knee CT = 0.16 msv Biswas et al. J. Bone Joint Surg. Am. 91 (2009) Cadaver Studies Hand Knee Qualitative Study Fresh cadavers Dose = ~4 mgy (~0.06 msv) (compare msv)* zoom Half resolution (0.388 mm) 0.25 mm isotropic voxels W/ and w/o scatter grid Simple scatter correction Elbow Ankle *Knee CT = 0.16 msv Biswas et al. J. Bone Joint Surg. Am. 91 (2009) 17

18 Advanced Imaging Modes Multi-Mode Operation Radiography / Fluoroscopy Cone-Beam CT Single-Energy Dual-Energy (Ca-I) Dual-Energy Cone-Beam CT Exogenous Materials Iodine arthroplasty Vessels adjacent to bone Devices and implants Endogenous Tissue Contrasts Tendon / ligament collagen density Cartilage degeneration (Gd-proteoglycan) Arthritis (gout) Iodine basis Calcium basis Iterative Reconstruction Improved soft-tissue image quality Artifact correction Model-based reconstruction (implants) Applications in IGI 18

19 A Mobile C-Arm for Intraoperative Cone-Beam CT Multiple projection images acquired over ~180 o Image acquisition - Nominal: 60 s - High-speed: 20 s Image quality - Sub-mm spatial resolution - Soft-tissue visibility Radiation dose - ~1/10 th that of Dx CT 19

20 J. H. Siewerdsen (Johns Hopkins University) Applications in IG Surgery Orthopedic Surgery Spine Surgery Brachytherapy Ear Surgery Interventional Radiology Urology Lung Surgery Breast Surgery Head and Neck Surgery Maximal target ablation and critical structure avoidance Image-Guided Spine Surgery 20

21 100 kvp mas 1-2 mgy ( msv) Spine Protocols Task-Specific Imaging Techniques Bony Detail Soft-Tissue kvp mas 5-10 mgy ( msv) Example Intra-op Protocol Thoracic Scan 0 3D Fast 1 3D Fast 1 3D Hi-Q 5 3D Fast 1 3D Hi-Q 5 Total Fluoro 1 Lumbar 5 mgy Scan 0 10 mgy 3D Fast 2 3D Fast 2 3D Hi-Q 10 3D Fast 2 3D Hi-Q 10 Total Fluoro 1 TOTAL Typical Diagnostic CT Dose: 56 mgy >60 mgy Iterative Reconstruction Known-Component Reconstruction (KCR) Simultaneous Registration and PL Reconstruction of a Known Component (e.g., spine screw) in an Unknown Background T3 Iteration #0 #1 #2 #3 Comments R Awl Perforation 2.6mm X 2.6 mm square pyramid hole TRUTH FBP PL KCR 21

22 J. H. Siewerdsen (Johns Hopkins University) Image-Guided Head and Neck Surgery C-Spine Facial Nerve Cochlea Stapes Crura C-Arm Trials: Mandibulectomy Scan 4 Scan 3 Scan 2 Scan 1 Fibula Reconstruction Target (Radionecrosis) Resection Plates 22

23 C-Arm Trials: Skull Base Scan 4 Scan 3 Scan 2 Scan 1 Craniotomy Tumor margins Tumor Packing resection Chondrosarcoma Closure CBCT Guidance: Endoscopic Skull Base 23

24 Image-Guided Thoracic Surgery Low-dose CT screening Early detection Stage Ia tumors Reduced mortality Video-assisted thoracic surgery (VATS): a growing challenge Localization and resection of subpalpable lung tumors Intraoperative CBCT Direct localization of tumors and critical structures Deformable registration (inflated deflated) Real-time video augmentation Motion imaging Image-Guided Thoracic Surgery Goal: Direct visualization / localization of nodules in the deflated lung Inflated Deflated Porcine Study: Implanted Lung Nodules 24

25 Image-Guided Thoracic Surgery Goal: Direct visualization / localization of nodules in the deflated lung (B) 0.9 mm 1.5 mm Inflated Deflated 2.95 msv 1.63 msv 0.41 msv Inflated 1.63 msv Collapsed Image-Guided Thoracic Surgery Goal: Direct visualization / localization of nodules in the deflated lung Inflated Deflated 25

26 Segmentation and Registration Goal: Deformable registration from inhale to deflated lung Segmentation Inhaled Deflated Semi-Automatic Seeding + Region Growing Segmentation and Registration Goal: Deformable registration from inhale to deflated lung Segmentation Inhaled Deflated Semi-Automatic Seeding + Region Growing 26

27 Medial Line and Bifurcations Inhaled Deflated Segmentation Medial Line Junctions Corresponding Points Goal: Deformable registration from inhale to deflated lung Inhaled Deflated REG 27

28 Corresponding Points + Surfaces Goal: Deformable registration from inhale to deflated lung Inhaled Deflated REG Preliminary Results: Segmentation Surface Mesh Bifurcations Inflated-Deflated (nodule in wedge) Correspondences Inflated-Deflated (mm-precision critical structures) Thoracoscopic Video-CBCT Fusion PA Fissure Target Video Overlay Sagittal Axial Coronal 28

29 J. H. Siewerdsen (Johns Hopkins University) Summary and Conclusions CBCT entering a broad scope of applications Diagnostic imaging (breast, dental, ENT, MSK, orthopaedics) Image guidance (e.g., MI interventions, IGRT) Image science foundation for CBCT Spatial resolution Noise, NEQ Dose Artifacts (e.g., x-ray scatter) System geometry System configuration Acquisition techniques Reconstruction techniques Accelerates system development, translation, and system integration Improved system configurations (detector, speed, electronics) New applications (e.g. MSK imaging and DE-CBCT) Streamlined system integration (esp. for IGI and IGRT) Advanced reconstruction techniques, artifact reduction Acknowledgments I-STAR Laboratory JW Stayman, W Zbijewski S Schafer, P DeJean, Y Otake J Lee, A Uneri, S Nithiananthan D Mirota, P Prakash, GJ Gang Y Ding, W Liu, H Dang Hopkins Collaborators J Carrino (MSK Radiology) J Prince (Electrical Engineering) R Taylor, G Hager (Comp. Science) D Reh (Head and Neck Surgery) G Gallia (Neurosurgery) J Khanna (Spine Surgery) M Sussman (Thoracic Surgery) Funding Support / Disclosures National Institutes of Health Siemens Healthcare (SP, Erlangen) Carestream Health Elekta Oncology Systems 29