1 LIRIS Laboratory, Lyon, France 2 Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA 3 Radiotherapy Department, Léon Bérard Cancer Center,

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1 LIRIS Laboratory, Lyon, France 2 Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA 3 Radiotherapy Department, Léon Bérard Cancer Center, Lyon, France 4 CREATIS Laboratory, Lyon, France ICCR 2007, June 04, 2007, MO-T BR 1-5 Lung motion modeling with deformable registration: nonlinearity and hysteresis estimation and analysis V. Boldea 1,3, G.C. Sharp 2, S.B. Jiang 2, D. Sarrut 3,4

ICCR 2007, June 04, 2007, MO-T BR Introduction Goal: follow lung and tumor displacements and deformations during free breathing  Introduce patient specific lung motion model  Propose automatic techniques to quantify motion nonlinearity and hysteresis  Useful ? Margin definition, automatic contour propagation, image guidance procedures 4D-CT  MGH Boston acquisition protocol  10 3D-CT over the free breathing cycle  voxel size : 0.977x 0.977x 2.5 mm³  5 NSCLC patients time amplitude I0I0 I1I1 I2I2 I3I3 I4I4 I6I6 I7I7 I8I8 I9I9 I5I5

ICCR 2007, June 04, 2007, MO-T BR Plan I. Lung motion model II. Lung motion nonlinearity III. Lung motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR D-CT motion model Deformable registration (“demons” based) Evaluation  Accuracy: ≈ 60 landmarks / 3D-CT identified – 3 experts ≈ 2.3 mm  Consistency: symmetry and transitivity of deformations 1.0 mm (SD: 1.1 mm) – ideally 0.0 mm End-exhale End-inhale Lagrangian approach – v ector fields (U 5X, U X5 ) between I 5 and I X (X {0,1,..., 9} - {5}) 18 vector fields ≈2.5 h computation time / patient model on a P4 (3.2 GHz, 2 Go Ram) I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Lung point trajectories piecewise linear trajectory: straight line trajectory between two successive phases of the 4D-CT p x, q x - point positions at 4D-CT phases I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Plan I. Lung motion model II. Lung motion nonlinearity III. Lung motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Nonlinearity computation Distance to straight line trajectory  motion can be approximated with a straight line ? p x – point positions at 4D-CT phases δ x (p) – distance to straight line trajectory I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Nonlinearity results Majority of lung points - nonlinearity < 2.5 mm  Exhalation: 80.33% %  Inhalation: 70.39% %  GTV: 91.8% % Two groups of patients  patients 2, 5 - non-significant ≠ exhal. ↔ inhal. ( p-value: 0.34/0.25 )  patients 1, 3, 4 – significant ≠ exhal. ↔ inhal. ( p-value: 0.04/0.1/0.001 ) Pooled data analysis  significant ≠ inhal. ↔ exhal. ( p-value: ) consistent with respiration mechanism I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Nonlinearity results R1R1 R2R2 R3R3 R4R4 R5R5 R6R6 6 cranio-caudal regions evaluation I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Nonlinearity results Upper lung - nearly linear motion Middle-lower regions - less linear motion I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Plan I. Lung motion model II. Lung motion nonlinearity III. Lung motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Hysteresis Exhalation trajectory ≠ Inhalation trajectory Hysteresis – maximum distance between inhalation and exhalation trajectory Assumption: uniform motion over exhalation and inhalation Our approach : inhalation and exhalation trajectories - non-planar polygonal curves Hysteresis measure - Fréchet distance-based criterion I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Trajectory descriptions: sets of equidistant points  inhalation: p ΨX, x {0,1,..., n}  exhalation: p ΦX, x {0,1,..., n} Hysteresis computation I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Trajectory descriptions: sets of equidistant points Distances between each couple of points (p ΦX, p ΨX ) Hysteresis computation I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Hysteresis results Higher hysteresis in middle-lower regions of lung Longer trajectory length → higher hysteresis R 1, R 2, R 3, R 4, R 5, R 6 - cranio-caudal regions I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Hysteresis results Hysteresis vs relative hysteresis R 1, R 2, R 3, R 4, R 5, R 6 - cranio-caudal regions I. Motion modelII. Motion nonlinearityIII. Motion hysteresis

ICCR 2007, June 04, 2007, MO-T BR Discussion and conclusion Method limitations:  Dependent on image quality and resolution  Deformable registration still an active area of research Nonlinearity and hysteresis  patient specific  vary across regions within the lung during respiration Integrate physiological information in a general lung atlas with different clinical applications