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

USPTO Application #: 20060058621
Title: 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 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. (end of abstract)
Agent: Drinker Biddle & Reath Attn: Intellectual Property Group - Philadelphia, PA, US
Inventors: Felix W. Wehrli, Punam K. Saha, Bryan Roos Gomberg
USPTO Applicaton #: 20060058621 - Class: 600407000 (USPTO)
Related Patent Categories: Surgery, Diagnostic Testing, Detecting Nuclear, Electromagnetic, Or Ultrasonic Radiation
The Patent Description & Claims data below is from USPTO Patent Application 20060058621.
Brief Patent Description - Full Patent Description - Patent Application Claims  monitor keywords



CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 60/283,270 filed on Apr. 12, 2001.

FIELD OF THE INVENTION

[0003] This invention relates generally to the field of digital topological analysis (DTA) to derive structural parameters from trabecular bone images obtained by magnetic resonance imaging (MRI), computed tomography (CT), or other imaging technologies, and the use of these parameters to assess trabecular bone structure in patients at risk of developing fractures from osteoporosis or those suffering from metabolic bone disorders.

BACKGROUND OF THE INVENTION

[0004] Trabecular bone (TB) (also known as cancellous bone), which occurs in most of the axial skeleton and at locations toward the ends of the long bones, consists of a lattice of interconnected plates and rods that confer mechanical strength to the skeleton at minimum weight. In addition to the volume fraction of the trabecular bone (often quantified in terms of bone density), the three-dimensional (3D) arrangement of the trabecular network is a major determinant of elastic modulus (Odgaard et al., J. Biomechan. 30:487-495 (1997)) and ultimate strength.

[0005] In general, characterization of the strength of trabecular lattices from three-dimensional (3D) images can be divided into three major categories: material, scale and topology (DeHoff et al., J. Microscopy 95:69-91 (1972)). `Material properties` describe the bone material; `scale properties` describe the size and thickness (local volume properties) of the trabecular elements; and the `topological properties` describe the spatial arrangement of the bone material in the network. These parameters change characteristically with subject age. It is also widely accepted that the mechanical competence of trabecular bone (i.e., its resistance to fracturing) is a function of both mass density and architecture and that disease processes such as osteoporosis entail both loss in net bone mass and architectural deterioration (World Health Organization [WHO] Technical Report Series No. 843, 1994).

[0006] A common diagnostic screening method for osteoporosis is based on `dual-energy X-ray absorptiometry` (DEXA) (Wahner et al., The Evaluation of Osteoporosis: Dual Energy X-Ray Absorptiometry in Clinical Practice, Cambridge: University Press, 1994) to measure integral bone mineral density (BMD). This method, however, does not distinguish between trabecular and cortical bone and ignores the role of structure as a contributor to mechanical competence.

[0007] It has been shown that the 3D arrangement (Mosekilde, Bone 9:247-250 (1988)) and the nature of the trabeculae (e.g., plate-like versus rod-like) (Morita et al., Ann. Biomed. Eng. 22:532-539 (1994)) can help explain the variation in elastic moduli and ultimate strength of trabecular bone networks that is unaccounted for by density alone (Ciarelli et al., J. Orthopaedic Res. 9:674-682 (1991); Goulet et al., J. Biomechanics 27:375-389 (1994)). In models of trabecular bone, Jensen et al. (Bone 11:417-423 (1990)) demonstrated that the apparent stiffness can vary by a factor of 5-10 when the arrangement of the network goes from a perfect cubic lattice to maximum irregularity, even though trabecular bone volume remains almost constant. The independent role of architecture in conferring strength to the trabecular network is supported by a large number of experimental studies (Gordon et al. (Can. Assoc. Radiol. J. 49:390-397 (1998); Oden et al. (Calcif. Tissue Int. 63:67-73 (1998); Siffert et al., Bone 18:197-206 (1996); Hwang et al., Med. Phys. 24:1255-1261 (1997)). It is generally agreed that 50%-60% of the mechanical competence of the bone can be explained by variations in the apparent density (bone mass/tissue volume). The clinical evidence for an independent contribution from trabecular architecture is equally compelling.

[0008] In the past, studies concerned with the quantitative description of trabecular bone have used histomorphometry from sections in conjunction with stereology to reconstruct the third dimension (Parfitt, In Bone Histomorphometry: Techniques and Interpretation, Boca Raton, Fla.: CRC Press, 1981, pp. 53-87 (1981)). Several studies involving histomorphometry in patients with and without vertebral fractures, matched for gender and BMD, found the two groups of subjects to differ in histomorphometric indices. Kleerekoper et al. (Calcif. Tissue Int. 37:594-597 (1985)) first demonstrated that women with osteoporosis and vertebral compression deformities had a significantly lower mean trabecular plate density than did women without deformities, matched for age and BMD. Similarly, Recker (Calcif. Tissue Int. 53 Suppl. 1:S139-142 (1993)) showed that a subset of patients with vertebral crush fractures, matched to an equal number of controls for trabecular bone volume, had considerably decreased trabecular plate density and increased marrow star volume (Vesterby et al., Bone 12:219-224 (1989)). Legrand et al. (J. Bone Miner. Res. 15:13-19 (2000)) studied 108 men with osteoporosis, of whom 62 had at least one vertebral fracture, and determined that the patients with fractures did not differ in age, bone mineral density of the spine or hip from those without fractures. However, trabecular number was lower and trabecular separation greater in the fracture group. Other distinguishing histomorphometric parameters were found to relate to network connectivity.

[0009] As pointed out, most measurements of trabecular architecture are based on two-dimensional (2D) images (Gordon et al., Physics in Medicine and Biology 41:495-508 (1996); Parfitt, 1981; Parfitt et al., J. Clin. Invest. 72:1396-1409 (1983); Vesterby, Bone 11:149-155 (1990); Hahn et al., Bone 13:327-330 (1992); Garrahan et al., J. Microscopy. 142:341-349 (1986)). Yet, it is well known that connectivity analysis of 2D sections does not accurately define the 3D structures found in trabecular bone networks (Odgaard et al., Bone 14:173-182 (1993). For example, what appears to be a rod in a 2D section, may actually be a cross-section of a plate-like structure in the 3D network, or even a junction between two plates. A 3D analysis is thus essential to unambiguously establish the topology of the trabecular architecture (Wessels et al., Medical Physics 24:1409-20 (1997)).

[0010] In vivo assessment of trabecular bone architecture can be achieved by computed tomography (Gordon et al., 1996; Muller et al., J. Bone Mineral Res. 11:1745-1750 (1996); Laib et al., Bone 21(6):541-6 (1997); Laib et al., Tech. Health Care 6(5-6):329-337 (1998)), and magnetic resonance (MR) micro-imaging (Link et al., J. Bone Miner. Res. 13(7):1175-1182 (1998); Majumdar et al., Bone 22(5):445-454 (1998); Wehrli et al., Techn. Health Care 6:307-320 (1998A)). Studies performed in patients are usually conducted at peripheral skeletal locations, such as the wrist (Majumdar et al., J. Bone Mineral Res. 12:111-118 (1997); Gordon et al., Med. Phys. 24:585-593 (1997); Wehrli et al., Radiology 206:347-357 (1998B)) and have been shown useful in deriving trabecular structural quantities. Recent advances have permitted analysis of the resulting images by probability-based image processing techniques (Hwang et al., Internat'l J. Imaging Systems and Technol. 10:186-198 (1999)).

[0011] One potentially powerful approach toward characterizing and quantifying trabecular network architecture is based on topological evaluation of the structure. Topology is the branch of mathematics concerned with the geometric properties of deformable objects (that are invariant in scale, rotation and translation) (Maunder, Algebraic Topology, Cambridge, UK: Cambridge Univ. Press, 1980). For example, topological criteria allow a determination as to whether a particular point in the network is part of a surface, curve, or junction. To illustrate the difference between topology and scale, one can consider a trabecular bone network that undergoes slight uniform thickening. Topologically, the network remains unaltered, but the scale properties have changed, which will result in changes to the mechanical properties. Conversely, given two networks with identical `bone volume fraction` (BV/TV), one with more plate-like trabecular bone is assumed to be stronger than one that has trabeculae that are more rod-like. Here, the two networks differ in topology.

[0012] Feldkamp et al. (J. Bone Mineral Res. 4:3-11 (1989)) were among the first to use topological measures to describe trabecular lattices from 3D images obtained by micro-CT (.mu.-CT) images. The investigators reasoned that connectivity is impossible to derive from images of two-dimensional sections, hence they expressed connectivity in terms of a global network, referred to as the Euler characteristic or number. The Euler characteristic, derived from the Euler-Poincare formula, assumes the number of bone objects to be one, and that marrow cavities do not exist in the network. These assumptions make the Euler characteristics equivalent to the first Betti number (Feldkamp et al., 1989), which is a measure of the number of loops in the network. This approach permitted characterization of osteoporotic changes in laboratory animals, demonstrating that the reduction in connectivity following bone loss and recovery parallels the reduction in Young's modulus for loading (Kinney et al., J. Bone Mineral Res. 13:839-845 (1998)).

[0013] Lane et al. (J. Bone Miner. Res. 14(2):206-214 (1999)) showed that ovariectomized rats, when treated with estrogen, could restore their pre-ovariectomy bone volume, but not the lost connections, thus demonstrating the disparate behavior of bone volume fraction and network topology. Pothuaud et al. (J. Microsc. 199:149-161 (2000)), extended the classical approach toward establishing topological quantities, such as the Euler-Poincare number, with counts of branches and termini on the basis of skeleton graphs.

[0014] However, classical topology in terms of the Euler number ignores the existence of plates and rods, and fails to provide information on the spatial distribution of connectivity. Moreover, it may fail to detect the effect of osteoporotic erosion, as has been pointed out by Kinney et al., 1998. The first Betti number is inherently insensitive to trabecular erosion, which is known to result in perforation of trabecular bone plates and disconnection of rod-like trabecular bone (Amling et al., Arch. Orthop. Trauma Surg. 115:262-269 (1996); Parfitt, Bone 13:S4147 (1992)). The First Betti number cannot distinguish between perforation of trabecularbone plates and disconnection of rods. The first Betti number will decrease from loss of rods, causing a reduction in the number of loops. However, it would increase as a result of perforation of plates, which increases the number of loops. Therefore, the first Betti number can not necessarily detect osteoporotic bone erosion.

[0015] Various approaches have been described to distinguish rod-like from plate-like architectures. Hahn et al., 1992, found the proportion of trabecular plates to rods to be reflected by the ratio of concave to convex surfaces, expressed in terms of the `trabecular bone pattern factor.` An algorithm making use of the change in surface area for a differential change in radial expansion, led to the definition of a parameter denoted `structure-model index` (SMI) Hildebrand et al., Computer Meth. Biomech. Biomed. Engin. 1:15-23 (1997). This metric was subsequently applied to the quantitative characterization of 3D .mu.-CT trabecular bone images from multiple anatomic locations known to be predominantly plate-like (SMI 0-1) or rod-like (SMI 2-3) (Hildebrand et al., J. Bone Miner. Res. 14(7):1167-1174 (1999)).

[0016] Nevertheless, none of the existing methods provide a reliable and efficient method for quantitatively characterizing the 3D architecture of cancellous bone networks, which are highly dependent on structural organization. Nor does the prior art provide methods for assessing bone strength or for predicting fracture risk in vivo in patients suffering from osteoporosis or metabolic bone disorders. It is an object of the present invention to meet these needs.

SUMMARY OF THE INVENTION

[0017] The present invention comprises a method, system and device for noninvasively detecting bone structure. The method is based on digital topological analysis (DTA), which was first theoretically considered by one of the inventors (Saha et al., Computer Vision and Image Understanding 63:418-429 (1996)). DTA classifies each voxel in a 3D structure, based on the connectivity information of the neighboring voxels. In the present invention, however, DTA is shown to completely characterize trabecular bone networks by unambiguously establishing the topological class of each voxel in digital images of trabecular bone. Images suited for analysis by the present invention include those obtained by magnetic resonance (MRI), X-ray computed tomography (CT) or other imaging modalities, including 3D images reconstructed from serial sectioning of specimens.

[0018] The embodied method provides insight into the pathogenesis of osteoporosis, i.e., the conversion of plates to rods and the disruption of the rod-like trabecular elements. It also provides the reproducibility necessary to evaluate the progression of disease or its regression in response to treatment. Image-derived topological parameters have been shown to discriminate groups of patients with osteoporotic fractures, from those without fractures. Fractures refer to any fracture caused by compromised structure secondary to bone disease including but not limited to fractures of the femur, forearm, humerus, tibia, vertebrae and ribs. Rods and plates refer to the gray scale image representations of trabecular structures, and curves and surfaces refer to their surface skeleton counterparts.

[0019] Typically, structure is measured at a peripheral site in the appendicular skeleton (radius, tibia, calcaneus) serving as a `surrogate site` to predict structure at the fracture site but future embodiments will target the potential fracture site directly. The process entails imaging in three dimensions a region of trabecular bone (or using a pre-existing image); converting the 3D image, after binarization, into a skeletonized surface representation consisting of only 1- and 2-dimensional structures; and classifying each image voxel as a curve, a surface, or a junction; and deriving microarchitectural indices of trabecular bone to quantitatively characterize the trabecular bone network. In a preferred embodiment the method is combined with the measurement of scale parameters, such as trabecular bone volume fraction or thickness as a means to assess the network strength of the bone, and patients' risk of sustaining fractures. The method is applicable to, e.g., cadaver specimens or biopsies, or in vivo, in human subjects or laboratory animals.

[0020] The method has been validated with synthetic images and applied to a range of MR images of human trabecular bone obtained in two resolution regimens: (1) at high resolution in cadaveric specimens and (2) at lower resolution in vivo. The algorithm of the invention has been shown to be robust over a wide range of resolutions. Variations have been in good qualitative agreement with the visual appearance of the different morphologies, as long as image voxel size was sufficient to resolve the structures under investigation. Applications to 3D MR microimages of trabecular bone from the human distal radius indicate that the volume densities of topological parameters, such as the surface-to-curve ratio, are strong predictors of Young's modulus. Analysis of in vivo MR microimages from the human wrist further indicate that topological parameter densities vary substantially among subjects, even though bone mineral densities do not distinguish them.

[0021] Since each voxel is classified uniquely, a preferred embodiment of the invention topological classification of the distal radius, used as a surrogate site, offers a method for predicting the risk of potential fractures in patients predisposed toward osteoporosis. In another preferred embodiment, the steps for determining the structure of the patient's trabecular bone network are repeated at periodic intervals, and the resulting determinations are compared to measure the progression or regression of osteoporosis in the patient. Such longitudinal studies can be used to study disease etiology and therapy response, where a patient has to be examined repeatedly during the course of treatment. Drugs that might be studied in such a manner can include, but are not limited to, anabolic drugs (estrogen, testosterone, parathyroid hormone) or antiresorptives (osteoclast inhibitors).

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