Kai Ding, Kunlin Cao, Gary E. Christensen Eric A. Hoffman and Joseph M. Reinhardt

1. Registration-Based Regional Lung Mechanical Analysis: Retrospectively Reconstructed Dynamic Imaging versus Static Breath-hold Image Acquisition Kai Ding, Kunlin Cao, Gary E. Christensen Eric A. Hoffman and Joseph M. Reinhardt The University of Iowa, Iowa City, IA 52242

2. Motivation • Regional lung function depends on the mechanical relationships between the lungs, rib cage, diaphragm, and abdomen • Disease can change lung tissue material properties, e.g., • Emphysema (COPD) • Increased compliance • Idiopathic Pulmonary Fibrosis (IPF) • Decreased compliance

3. Motivation • Traditional pulmonary function measurements, such as spirometry, only give global information and are unable to show regional differences • Heterogeneity of lung function • New available technologies enable us to study pulmonary function in a regional level • Multi-detector-row CT (MDCT) • Dynamic volume CT imaging • Respiratory Gating methods

4. Previous Work – Imaging Methods • Nuclear medicine imaging (e.g. PET, SPECT) • Provides good functional information • Low spatial resolution • Hyperpolarized gas MR imaging • Provides dynamic ventilation and diffusion maps • Much less anatomical detail than MDCT • No radiation

5. Xe-CT vs. Volumetric CT • Xenon-enhanced CT (Xe-CT) • High temporal resolution • Provides regional ventilation maps • Limited axial coverage Apex Base

6. Previous work - Image Registration • MR images (Gee et al.) • Not much anatomical details • Limited landmark validation (22 landmarks) • 4D CT by optical-flow (Guerrero et al.) • Matched well with segmented volume change • No regional validation • Regional lung expansion from temporal CT (Christensen et al.) • Matched well with spirometry data • Only global validation

7. Our Work • Retrospectively reconstructed dynamic imaging and static breath-hold imaging • Using Jacobian which measures the regional volume change • Registration-based regional lung expansion vs. Xe-CT specific ventilation • Using semi-automatic reference standard to evaluate registration accuracy

8. Diagram Sheep 3D Image Registration Dynamic Imaging Regional Expansion Static Imaging 3D Image Registration Regional Expansion Compartment Model Xenon Imaging Regional Ventilation

9. Consistent Linear Elastic Registration • Inverse consistent linear elastic registration (Christensen et al.) • Jointly estimating h & g helps reduce the inverse consistency error • Cost minimization g h Template, T Target, S Christensen and Johnson, Consistent Image Registration, IEEE TMI 20(7), July 2001, pp. 568-582.

10. Consistent Linear Elastic Registration • Regional volume change • Output: Displacement field u(x,y,z) that maps image to image • Use the Jacobian determinant of the displacement field • Present our result in a natural way in Lagrangian Coordinate: • If Jacobian>1 local expansion • If Jacobian<1 local contraction • If Jacobian=1 no expansion or contraction

11. Xenon CT Analysis • Basic Model • During wash-in (wash-out), Xe increases (decreases) mean lung density(enhancement is roughly linear with Xe concentration) • Observed time-intensity data is fit to compartment model using least squares curve fit. • Time constant  describes WI and WO rates • Specific ventilation = 1/ D1 (t) = D0, t < t0 D2 (t) = D0+ ( Df - D0) exp(-[t-t0]/)t0 < t < tc D3 (t) = D0+ D2 (tc) exp(-[t- tc]/) t > tc

12. Xenon CT Analysis: PASS Pulmonary Analysis Software Suite Iowa Comprehensive Lung Imaging Center

13. Experimental Methods • Siemens Sensation 64 MDCT scanner • Four sheep at supine position • Anesthetized and mechanically ventilated • Siemens Sensation 64 MDCT scanner • Dual Harvard Piston Ventilators (Volume Controlled Ventilation)

14. Three types of data • Dynamic scans • 0, 25, 50, 75 and 100% phase points of inspiration portion and 75, 50 and 25% of the expiration portion, denoted as the T0, T1, T2 … and T7 images • Registration applied pairwise to estimate local expansion

15. Three types of data • Static scans • Acquired at 0, 5, 10, 15, 20 and 25 cm H2O airway pressure (We use P10, P15, P20 and P25 images) • Registration applied pairwise to estimate local expansion

16. Three types of data • Xenon CT scans • Acquired at the end expiratory point during the respiratory cycle (about 45 breaths) • Triggered at PEEP of 10 cm H2O • Slice thickness = 2.4 mm (about 3.2 times thicker than the volumetric CT slices) • 12 contiguous slices = 3 cm of coverage along the axial direction

17. Registration Accuracy • Automatic landmark detection (Murphy et al.) • Landmark projection-coronal view • Landmark projection-sagittal view • Note: 2D projection view. The landmarks are inside lung in 3D view. K. Murphy, B. van Ginneken, J. Pluim, S. Klein, and M. Staring, Semi-automatic reference standard construction for quantitative evaluation of lung CT registration, MICCAI 2008, 5242, pp. 1006-1013.

18. Registration Accuracy • Semi-automatic system (Murphy et al.) • New landmark is added to a thin-plate-spline • System estimates the new landmark position for the user • 200 landmarks are matched by one observer across all image pairs • For each landmark, the actual landmark position was compared to the registration-derived landmark position • Dynamic scans mean landmark distance: • Before registration: on the order of 8 mm • After registration: on the order of 2 mm • Static scans mean landmark distance: • Before registration: on the order of 12 mm • After registration: on the order of 2 mm K. Murphy, B. van Ginneken, J. Pluim, S. Klein, and M. Staring, Semi-automatic reference standard construction for quantitative evaluation of lung CT registration, MICCAI 2008, 5242, pp. 1006-1013.

19. Registration Accuracy

20. Registration Jacobian • Registration-based estimates of regional expansion and contraction: Jacobian map (whole lung) • Inspiration phase: T0 to T1 Jacobian>1 local expansion • Expiration phase: T4 to T5 Jacobian<1 local contraction • Note: Color scale is different. Each color bar is set as the min & max J in the slice

21. Jacobian vs. Spec. Ventilation • Comparison between registration-based Jacobian map (whole lung) and Xe-CT estimates of specific ventilation (limited axial coverage) Apex Base • Affine transform is applied to find the axial location of Xe-CT scan in volumetric CT scan

22. Jacobian vs. Spec. Ventilation • Comparison between registration-based Jacobian map (whole lung) and Xe-CT estimates of specific ventilation (limited axial coverage) Lung Height 0%IN 100%IN • Deformed slabs

23. Jacobian vs. Spec. Ventilation • Linear regression of averaged Jacobian and the sV • Linear regression with 95% confidence interval for T0 T1of AS70078

24. Correlation • Correlation of the average Jacobian and the sV in dynamic scans • Correlation coefficient r square from the linear regression of J and sV for each phase change pair and for each animal, T2-T3 (50%IN-75%IN) r2 = 0.85

25. Correlation • Correlation of the average Jacobian and the sV in static scans • Correlation coefficient r square from the linear regression of J and sV for each phase change pair and for each animal, P20-P25 r2 = 0.84

26. Jacobian Change Across Phase • Different regions reach their maximum expansion at different points in respiratory cycle – coronal view Apex 0%IN-25%IN 25%IN-50%IN 50%IN-75%IN 75%IN-100%IN Base Apex 100%IN-75%EX 75%EX-50%EX 50%EX-25%EX Base AS70077 AS70078 AS70080 AS70079

27. Apex 0%IN-25%IN 25%IN-50%IN 50%IN-75%IN 75%IN-100%IN Base Jacobian Change Across Phase • Different regions reach their maximum expansion at different points in respiratory cycle – sagittal view Apex 100%IN-75%EX 75%EX-50%EX 50%EX-25%EX Base AS70077 AS70078 AS70080 AS70079

28. Discussion • Same level of correlation in both dynamic and static scans • Similar mouth pressure • Xe-CT measurements of sV have large  (30% of the mean) • Is measurement noisy? • Is underlying physiology variable? • Registration estimates of Jacobian: smooth • How small is the smallest abnormal tissue we can detect? • Registration model includes smoothness constraint • Application to human data • Works for human data in tidal breathing • Low dose screening scans?

29. Summary • Registration derived estimates of regional lung expansion • Both dynamic and static scans can be used for assessment • Registration J can be analyzed • Dynamic scans: reveal better heterogeneity, more dose, subjects need training • Static scans: improved spatial resolution, single pair of breath-hold images, lower radiation dose • Complementary to Xe-CT ventilation: provides local lung expansion information • Expansion, strain, lung-rib cage interaction, etc. • Fast, low-cost, functional lung imaging protocol • Method can provide information about lung mechanics

30. Thank you!