Measurement of trabecular bone thickness in the limited resolution regime of in vivo MRI by fuzzy distance transform

Trabecular or cancellous bone, the type of bone found in the vertebrae and near the joints of long bones, consists of a network of plates and struts. Accurate measurement of trabecular thickness is of significant interest, for example, to assess the effectiveness of anabolic (bone forming) agents of patients with osteoporosis. Here, we introduce a new fuzzy distance transform (FDT)-based thickness computation method that obviates binary segmentation and that can effectively deal with images acquired at a voxel size comparable to the typical trabecular bone thickness. The method's robustness is shown on the basis of /spl mu/-CT images of human trabecular bone, resampled at progressively coarser resolution and after application of rotation and addition of noise as a means to simulate the in vivo situation. Reproducibility of the method is demonstrated with /spl mu/-CT images by comparing histograms of thickness within and between data sets and with /spl mu/-MRI volume data sets of human volunteers imaged repeatedly. Finally, with in vivo /spl mu/-MR images from a prior study in rabbits subjected to corticosteroid exposure, it is demonstrated that short-term treatment resulting in trabecular thinning can be quantified with the new method.

[1]  Scott N. Hwang,et al.  In vivo NMR microscopy allows short-term serial assessment of multiple skeletal implications of corticosteroid exposure , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[2]  P. Rüegsegger,et al.  A microtomographic system for the nondestructive evaluation of bone architecture , 2006, Calcified Tissue International.

[3]  P. Levitz,et al.  A new method for three-dimensional skeleton graph analysis of porous media: application to trabecular bone microarchitecture. , 2000, Journal of microscopy.

[4]  Supun Samarasekera,et al.  Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation , 1996, CVGIP Graph. Model. Image Process..

[5]  A. Wright,et al.  Role of Magnetic Resonance for Assessing Structure and Function of Trabecular Bone , 2002, Topics in magnetic resonance imaging : TMRI.

[6]  Azriel Rosenfeld,et al.  Digital Picture Processing, Volume 1 , 1982 .

[7]  Bidyut Baran Chaudhuri,et al.  3D Digital Topology under Binary Transformation with Applications , 1996, Comput. Vis. Image Underst..

[8]  Punam K. Saha,et al.  Fuzzy Distance Transform: Theory, Algorithms, and Applications , 2002, Comput. Vis. Image Underst..

[9]  P. Rüegsegger,et al.  A new method for the model‐independent assessment of thickness in three‐dimensional images , 1997 .

[10]  H. Song,et al.  In vivo micro‐imaging using alternating navigator echoes with applications to cancellous bone structural analysis , 1999, Magnetic resonance in medicine.

[11]  M. Kleerekoper,et al.  Relationships between surface, volume, and thickness of iliac trabecular bone in aging and in osteoporosis. Implications for the microanatomic and cellular mechanisms of bone loss. , 1983, The Journal of clinical investigation.

[12]  Jayaram K. Udupa,et al.  Scale-Based Fuzzy Connected Image Segmentation: Theory, Algorithms, and Validation , 2000, Comput. Vis. Image Underst..

[13]  Azriel Rosenfeld,et al.  Digital Picture Processing , 1976 .

[14]  J. P. Jones,et al.  Foundations of Medical Imaging , 1993 .

[15]  Punam K. Saha,et al.  Novel theory and algorithm for fuzzy distance transform and its applications , 2002, SPIE Medical Imaging.

[16]  P. Meunier,et al.  Comparison of Trabecular Bone Microarchitecture and Remodeling in Glucocorticoid‐Induced and Postmenopausal Osteoporosis , 2001, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[17]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[18]  P. Meunier,et al.  Clinical Use of Bone Biopsy , 2001 .

[19]  Scott N. Hwang,et al.  Estimating voxel volume fractions of trabecular bone on the basis of magnetic resonance images acquired in vivo , 1999 .

[20]  Milan Sonka,et al.  Image processing analysis and machine vision [2nd ed.] , 1999 .

[21]  Jonathan Reeve,et al.  Treatment of osteoporosis with parathyroid peptide (hPTH 1–34) and oestrogen: increase in volumetric density of iliac cancellous bone may depend on reduced trabecular spacing as well as increased thickness of packets of newly formed bone , 1992, Clinical endocrinology.

[22]  Bidyut Baran Chaudhuri,et al.  Detection of 3-D Simple Points for Topology Preserving Transformations with Application to Thinning , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Bidyut Baran Chaudhuri,et al.  A new shape preserving parallel thinning algorithm for 3D digital images , 1997, Pattern Recognit..

[24]  Jayaram K. Udupa,et al.  Shell rendering , 1993, IEEE Computer Graphics and Applications.

[25]  Felix W. Wehrli,et al.  Estimating voxel volume fractions of trabecular bone on the basis of magnetic resonance images acquired in vivo , 1999, Int. J. Imaging Syst. Technol..

[26]  G. Herman,et al.  3D Imaging In Medicine , 1991 .

[27]  Dewey Odhner,et al.  3DVIEWNIX: an open, transportable, multidimensional, multimodality, multiparametric imaging software system , 1994, Medical Imaging.

[28]  H. Song,et al.  Fast 3D large‐angle spin‐echo imaging (3D FLASE) , 1996, Magnetic resonance in medicine.