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

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 3 D 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.

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.