Digital topological analysis of trabecular bone MR images and prediction of osteoporosis fractures

• US 20020191823A1
• Filed: 04/11/2002
• Published: 12/19/2002
• Est. Priority Date: 04/12/2001
• Status: Active Grant

• Current Assignee: Trustees Of The University Of Pennsylvania (University of Pennsylvania)
• Original Assignee: Trustees Of The University Of Pennsylvania (University of Pennsylvania)
• Inventors: Wehrli, Felix W., Saha, Punam K., Gomberg, Bryon Roos
• Granted Patent: US 6,975,894 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/417 the bone marrow
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 6/505 for diagnosis of bone
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/20044 Skeletonization; Medial axis transform
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The invention provides method, system and device for determining trabecular bone structure and strength by digital topological analysis, and offers, for the first time, a demonstration of superior associations between vertebral deformity and a number of architectural indices measured in the distal radius, thus permitting reliable and noninvasive detection and determination of the pathogenesis of osteoporosis. A preferred embodiment provides imaging in three dimension of a region of trabecular bone, after which the 3D image is converted into a skeletonized surface representation. Digital topological analysis is applied to the converted image, and each image voxel is identified and classified as a curve, a surface, or a junction; and then associated with microarchitectural indices of trabecular bone to quantitatively characterize the trabecular bone network. The invention is applicable in vivo, particularly on human subjects, or ex vivo.

Claims

1. The method for noninvasively detecting bone structure, comprising:

imaging in 3D a region of trabecular bone;

converting the 3D image into a skeletonized surface representation;

analyzing the converted image by digital topological analysis;

classifying each image voxel as a curve, a surface, or a junction; and

calculating microarchitectural indices from the classified image.

2. The method of claim 1, further comprising calculating the scale and orientation information needed for normalization.

3. The method of claim 2, further comprising combining trabecular orientation and scale information with the step of classifying each voxel to characterize local bone network.

4. The method of claim 1, wherein the classified image shows a conversion of plates to rods and disruption of the rod-like trabecular elements.

5. The method of claim 1, wherein the bone is in vivo.

6. The method of claim 1, wherein the bone is ex vivo.

7. The method for noninvasively determining bone structure of a patient, comprising:

imaging in 3D a region of trabecular bone of the patient;

converting the 3D image into a skeletonized surface representation;

analyzing the converted image by digital topological analysis;

classifying each image voxel as a curve, a surface, or a junction; and

calculating microarchitectural indices of from the classified image of the patient'"'"'s trabecular bone.

8. The method of claim 7, further comprising calculating the scale and orientation information needed for normalization.

9. The method of claim 8, further comprising combining trabecular orientation and scale information with the step of classifying each voxel to characterize local bone network.

10. The method of claim 7, wherein the classified image shows a conversion of plates to rods and disruption of the rod-like trabecular elements.

11. The method of claim 7, wherein condition of the patient'"'"'s trabecular bone network provides an index of bone disease in the patient.

12. The method of claim 7, wherein steps for determining the structure of the patient'"'"'s trabecular bone network are repeated at periodic intervals and the resulting determinations compared to measure the progression or regression of osteoporosis in the patient.

13. A method for predicting the risk of fracture or vertebral deformity in a patient according to claim 7.

14. The method of claim 7, wherein the imaged bone region in a patient is selected from a surrogate site selected from the group consisting of the distal radius, distal tibia, mandible or calcaneus.

15. The method of claim 14, wherein microarchitectural imaging and digital topological analysis of trabecular volume densities and bone network of the surrogate site provides an indicia of bone structure throughout the axial skeleton of the patient.

16. A method for predicting the risk of osteoporosis in the patient according to claim 14.

17. The method of claim 14, wherein steps for determining the structure of the patient'"'"'s trabecular bone network, based upon noninvasive imaging of the patient'"'"'s surrogate site, are repeated at periodic intervals and the resulting determinations compared to measure the progression or regression of osteoporosis in the patient.

18. A system for noninvasively determining bone structure and strength by digital topological analysis, comprising:

means for acquiring or reading a 3D image of a region of trabecular bone;

means for converting the 3D image into a skeletonized surface representation;

means analyzing the converted image by digital topological analysis;

means for classifying each image voxel as a curve, a surface, or a junction; and

means for calculating microarchitectural indices from the classified image to quantitatively characterize the trabecular bone.

19. A device for noninvasively determining bone structure and strength by digital topological analysis, comprising:

a computer-readable signal-bearing medium;

means in the medium for acquiring or reading a 3D image of a region of trabecular bone;

means in the medium for converting the 3D image into a skeletonized surface representation;

means in the medium for analyzing the converted image by digital topological analysis;

means in the medium for classifying each image voxel as a curve, a surface, or a junction; and

means in the medium calculating microarchitectural indices from the classified image to quantitatively characterize the trabecular bone.