Estimation of a mechanical property of anatomy from medical scan data
A mechanical property of anatomy is estimated from a patient in vivo, such as estimating a patient-specific material property of a valve. A morphological model is used to determine anatomy dynamics. A biomechanical model, using the anatomy dynamics, predicts the dynamics, based, at least in part, on one or more material properties. Using an inverse solution based on comparison of dynamics predicted by the biomechanical model and the dynamics determined from the morphological model, values for the material properties are determined.
1. A method for determining a mechanical property of anatomy, the method comprising:
determining, by a processor, first anatomy locations of a valve of a patient derived from first medical scan data of the patient at a first time;
determining, by the processor, second anatomy locations of the valve of the patient from second medical scan data of the patient at a second time different than the first time, the second anatomy locations being for a same anatomy of the valve as the first anatomy locations;
deriving, by the processor, an actual displacement between the first anatomy locations and the second anatomy locations;
modeling, by the processor, the valve with a biomechanical model, which is a function of the mechanical property and the actual displacement;
determining, by the processor based on the biomechanical model, first modeled anatomy locations and second modeled anatomy locations;
deriving, by the processor, a modeled displacement between the first modeled anatomy locations and the second modeled anatomy locations; and
inversely solving, by the processor, for a value of the mechanical property of the valve as a function of the biomechanical model and a comparison of the actual displacement with the modeled displacement.
2. The method of claim 1 wherein determining the first and second anatomy locations comprises determining from ultrasound data representing a volume including the valve over time.
3. The method of claim 1 wherein determining the first and second anatomy locations comprises determining by application of the first and second medical scan data, respectively, as input features to a machine-learning algorithm.
4. The method of claim 1 wherein determining the first and second anatomy locations comprises determining as a function of a discriminative probabilistic model.
5. The method of claim 1 wherein determining the first and second anatomy locations comprises determining locations for anterior and posterior papillary tips, mitral annulus, and anterior and posterior leaflets at the first and second times and determining a mesh for the valve at the first and second times.
6. The method of claim 1 wherein modeling comprises modeling with the biomechanical model comprising a finite element model.
7. The method of claim 1 wherein modeling comprises modeling with the biomechanical model comprising a dynamic system having mass, damping, stiffness, displacement, velocity, and acceleration terms.
8. The method of claim 1 wherein solving comprises solving for the value of a Young's modulus of the valve of the patient in-vivo from the first and second medical scan data of the patient.
9. The method of claim 1 wherein solving comprises solving for values of chordae lengths, respectively, of the valve of the patient in-vivo from the first and second medical scan data of the patient.
10. The method of claim 1 wherein solving for the value comprises solving for the value of the mechanical property and values of a plurality of other mechanical properties of the valve of the patient.
11. The method of claim 1 wherein solving for the value of the mechanical property of the valve of the patient comprises solving from the biomechanical model, the displacement from the first and second medical scan data of the patient and the modeled displacement.
12. The method of claim 1 wherein solving comprises solving as a non-linear function of the mechanical property to the first and second anatomy locations and with an extended Kalman filter.
13. The method of claim 1 wherein solving comprises solving as a function of a fluid-structure interaction model incorporating the biomechanical model, wherein the solving further comprises solving for a pressure with the fluid-structure interaction model.
14. The method of claim 1 further comprising categorizing a condition of the valve of the patient based on a comparison of the value of the mechanical property with a pre-determined value of the mechanical property.
15. The method of claim 1 further comprising displaying an image, the imaging being a function of the value of the mechanical property.
16. In a non-transitory computer readable storage medium having stored therein data representing instructions executable by a programmed processor for determining a mechanical property of anatomy, the storage medium comprising instructions for:
deriving an actual motion of the anatomy from scan data of a patient;
calculating a modeled motion of the anatomy from a biomechanical model, the biomechanical model being a function of the actual motion and at least one patient-specific material parameter;
comparing the modeled motion to the actual motion; and
solving, iteratively, for the patient-specific material parameter by repetition of the calculating and comparing.
17. The non-transitory computer readable storage medium of claim 16 wherein the anatomy comprises a heart valve, and wherein solving comprises solving for at least one Young's modulus of the heart valve and at least two chordae lengths of the heart valve.
18. The non-transitory computer readable storage medium of claim 16 wherein deriving the actual motion comprises deriving from ultrasound data input to a discriminative probabilistic model, wherein calculating with the biomechanical model comprises simulating biomechanics with finite element analysis, and wherein solving comprises solving with Kalman filtering.
19. A system for estimating a mechanical property of anatomy, the system comprising:
an ultrasound scanner configured to scan a heart volume of a patient, the scan providing medical diagnostic ultrasound data representing at least a part of the heart;
a processor configured to perform inverse analysis by deriving actual valve dynamics from the medical diagnostic ultrasound data, combining the actual valve dynamics with a biomechanical model, deriving modeled valve dynamics from the combination, estimating the mechanical property from the combination and the derived modeled valve dynamics, interpolating valve kinematics with the estimated mechanical property, and refining motion estimation with an alteration of the mechanical property; and
a display configured to generate a visualization of the mechanical property.
20. The system of claim 19 wherein the processor is configured to perform the refining with a Kalman filter.