骨小梁Micro-CT图像形态计量学参数计算方法综述

doi:10.3969/j.issn.0258-8021.2018.02.014

摘要
图/表
参考文献(79)
相关文章 (15)

全文: PDF (852 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要骨质疏松症是骨科领域的研究热点之一,研究发现,除骨密度(骨量)改变的因素外,骨小梁的结构变化也是患病的重要影响因素。骨小梁形态计量学分析是研究骨小梁结构形态变化的一种重要方法。基于骨小梁的Micro-CT图像介绍部分骨小梁形态学参数的计算方法,主要包括骨小梁各向异性、连通性、结构模型指数以及纹理等不同特征,同时列举部分相关研究实例,总结上述形态学参数的适用性以及优缺点,为更加有效地评价骨质疏松状态以及药物治疗效果提供依据。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	刘蓉
	郭新路
	张亚坤
	王永轩

关键词 ：骨质疏松症, 骨小梁, 形态计量学, 图像分析

Abstract：Osteoporosis is one of the hotspots in the orthopedic field. Some studies have revealed that not only the changes in bone mineral density (bone mass) but also changes of trabecular bone structure are pathogenic factors. The trabecular bone morphometric analysis is one kinds of important method to study trabecular bone structure change. In this paper, some methods to calculate the trabecular bone morphometric parameters based on Micro-CT images were introduced, such as trabecular anisotropy, connectivity, structure model index, texture and other trabecular bone characteristics. Meanwhile, some examples were given to summarize the applicability, pros and cons of the trabecular bone morphometric parameters to provide evidence for the effective evaluation of osteoporosis and drug treatment.

Key words： osteoporosis trabecular bone morphometric image analysis

收稿日期: 2017-05-20

PACS:

R318

基金资助:国家自然科学基金(61573079);大连大学博士启动项目(20151QL06);中央高校基本科研业务费专项资金(DUT15QY58)

通讯作者: wyx8904@mail.dlut.edu.cn

引用本文:

刘蓉, 郭新路, 张亚坤, 王永轩. 骨小梁Micro-CT图像形态计量学参数计算方法综述[J]. 中国生物医学工程学报, 2018, 37(2): 237-246.
Liu Rong, Guo Xinlu, Zhang Yakun, Wang Yongxuan. A Methodological Review on Morphometric Parameters of Micro-CT Trabecular Bone Images. Chinese Journal of Biomedical Engineering, 2018, 37(2): 237-246.

链接本文:

http://cjbme.csbme.org/CN/10.3969/j.issn.0258-8021.2018.02.014 或 http://cjbme.csbme.org/CN/Y2018/V37/I2/237

[1] Kanis JA. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group [J]. WHO Technical Report,1994,4(6):368-381.
[2] Weaver CM, Gordon CM, Janz KF, et al. The National Osteoporosis Foundation's position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations [J]. Osteoporosis International, 2016, 27(4):1281-1386.
[3] 张智海,刘忠厚,李娜,等.中国人骨质疏松症诊断标准专家共识(2014版) [J]. 中国骨质疏松杂志, 2014(9): 1007-1010.
[4] Liu Xiaowei Sherry, Cohen A, Shane E, et al. Bone density, geometry, microstructure, and stiffness: Relationships between peripheral and central skeletal sites assessed by DXA, HR-pQCT, and cQCT in premenopausal women [J]. Journal of Bone and Mineral Research, 2010,25(10):2229-2238.
[5] Erhart S, Zegg M, Kralinger F, et al. Fast and easy preoperative estimation of cancellous bone mineral density in patients with proximal femur fractures [J]. Archives of Orthopaedic & Trauma Surgery, 2015, 135(12):1683-1689.
[6] Raafat BM, Hassan NS, Aziz SW. Bone mineral density (BMD) and osteoporosis risk factor in Egyptian male and female battery manufacturing workers [J]. Toxicology & Industrial Health, 2011, 28(3): 245-252.
[7] 高飞,乔巨峰,高锋,等.骨代谢指标在骨质疏松患者椎体变形中的意义 [J]. 中国组织工程研究, 2014, 18(24):3803-3807.
[8] Mabilleau G, Mieczkowska A, Libouban H, et al. Comparison between quantitative X-ray imaging, dual energy X-ray absorptiometry and micro-CT in the assessment of bone mineral density in disuse-induced bone loss [J]. Journal of Musculoskeletal & Neuronal Interactions, 2015, 15(1):42.
[9] 李庆浩,万柏坤,明东,等.骨密度定量检测方法及性能比较 [J]. 国际生物医学工程杂志, 2010, 33(4):239-244.
[10] Xu Kailiang, Ta Dean, He Runxin, et al. Axial transmission method for long bone fracture evaluation by ultrasonic guided waves: simulation, phantom and in vitro, experiments [J]. Ultrasound in Medicine & Biology, 2014, 40(4):817-827.
[11] Baron C. Using the gradient of human cortical bone properties to determine age-related bone changes via ultrasonic guided waves [J]. Ultrasound in Medicine & Biology, 2012, 38(6):972-981.
[12] Wainwright SA, Marshall LM, Ensrud KE, et al. Hip fracture in women without osteoporosis [J]. Journal of Clinical Endocrinology & Metabolism,2005,90(5):2787-2793.
[13] Kanis JA, Mccloskey EV, Harvey NC, et al. Intervention thresholds and the diagnosis of osteoporosis [J]. Journal of Bone & Mineral Research, 2015, 30(10):1747-1753.
[14] 许江威. 股骨近端骨折发生机制的解剖学、影像学以及临床研究[D]. 大连: 大连医科大学,2013.
[15] Amstutz HC, Sissons HA. The structure of the vertebral spongiosa[J]. Journal of Bone & Joint Surgery British Volume, 1969, 51(3): 540-550.
[16] Hou Yang, Yuan Wen, Kang Jian, et al. Influences of endplate removal and bone mineral density on the biomechanical properties of lumbar spine [J]. PLoS ONE, 2013, 8(11):e76843.
[17] 万世勇, 雷伟, 吴子祥,等. 膨胀式椎弓根螺钉在骨螺钉界面的显微CT评价及组织学分析 [J]. 中华外科杂志, 2007, 45(18):1271-1273.
[18] 崔轶,徐永清,唐辉,等. 显微CT在骨质疏松研究领域的研究进 [J].中国骨质疏松杂志, 2012,18(1):87-89.
[19] 王江雪,高玉,李辉,等. 离子造影剂增强Micro-CT扫描对大鼠关节软骨形态的定量分析 [J]. 生物医学工程研究,2014,33 (3):157-161.
[20] 冯秀媛,王永福. 特发性青少年骨质疏松症 [J]. 中国骨质疏松杂志,2015(3):342-348.
[21] Barak MM, Lieberman DE, Hublin JJ. A Wolff in sheep's clothing: trabecular bone adaptation in response to changes in joint loading orientation [J]. Bone,2011,49(6):1141-1151.
[22] Whitehouse WJ, Dyson ED, Jackson CK. The scanning electron microscope in studies of trabecular bone from a human vertebral body [J]. Journal of Anatomy,1971,108(Pt 3):481-496.
[23] Chappard D, Legrand E, Pascaretti C, et al. Comparison of eight histomorphometric methods for measuring trabecular bone architecture by image analysis on histological sections [J]. Microscopy Research & Technique, 2015, 45(4-5):303-312.
[24] Niessen WJ, López AM, Enk WJV, et al. In Vivo Analysis Of Trabecular Bone Architecture [M]. Berlin: Springer Berlin Heidelberg, 1997:435-440.
[25] Dalle CL, Valenti MT, Bertoldo F, et al. Bone microarchitecture evaluated by histomorphometry [J]. Micron,2005,36(7-8):609-616.
[26] Dias DR, Leles CR, Batista AC, et al. Agreement between histomorphometry and microcomputedtomography to assess bone microarchitecture of dentalimplant sites [J]. Clinical Implant Dentistry & Related Research, 2015, 17(4):732-741.
[27] Parfitt AM, Drezner MK, Glorieux FH, et al. Bone histomo-rphometry: standardization of nomenclature, symbols, and units. Report of the ASBMR Histomorphometry Nomenclature Committee [J]. Journal of Bone and Mineral Research,1987, 2(6):595-610.
[28] Maquer G, Musy SN, Wandel J, et al. Bone volume fraction and fabric anisotropy are better determinants of trabecular bone stiffness than other morphological variables [J]. Journal of Bone & Mineral Research, 2015, 30(6):1000-1008.
[29] 邱明才.骨质疏松研究的现状与展望 [J].中华医学杂志, 2001,81(14):833-835.
[30] Dempster DW, Compston JE, Drezner MK, et al. Standardized nomenclature, symbols, and units for bone histomorphometry: A 2012 update of the report of the ASBMR Histomorphometry Nomenclature Committee [J]. Journal of Bone and Mineral Research, 2013,28(1):2-17.
[31] 于顺禄,魏学磊,熊光宜,等. 骨计量学方法在骨质疏松模型中的定量观察 [J]. 中国体视学与图像分析, 2012(3):207-214.
[32] Carbonare LD, Ballanti P, Bertoldo F, et al. Trabecular bone microarchitecture in mild primary hyperparathyroidism [J]. Journal of Endocrinological Investigation,2008,31(6):525-530.
[33] Negri AL, Valle EED, Zanchetta MB, et al. Evaluation of bone microarchitecture by high-resolution peripheral quantitative computed tomography (HR-pQCT) in hemodialysis patients [J]. Osteoporosis International, 2012, 23(10):2543-2550.
[34] 彭静,石锐,闵理,等. 骨质疏松髋部骨折区骨微结构变化研究 [J]. 中国骨质疏松杂志, 2014(10):1184-1188.
[35] Chappard D, Legrand E, Pascaretti C, et al. Comparison of eight histomorphometric methods for measuring trabecular bone architecture by image analysis on histological sections [J]. Microscopy Research & Technique, 2015, 45(4-5):303-312.
[36] Effendy NM, Khamis MF, Shuid AN. The effects of Labisia pumila extracts on bone microarchitecture of ovariectomized- induced osteoporosis rats: A micro-CT analysis [J]. Journal of X-Ray Science and Technology, 2016, 25(1):1-12.
[37] Hahn M, Vogel M, Pompesiuskempa M, et al. Trabecular bone pattern factor-a new parameter for simple quantification of bone microarchitecture [J]. Bone,1992,13(4):327-330.
[38] 温鑫鑫,雷伟,王法琪,等.松质骨显微结构参数与表观力学强度关系研究进展[J]. 中国骨质疏松杂志, 2014(12):1495-1500.
[39] Asa K, Kumasaka S, Sakurai T, et al. Evaluating two-dimensional skeletal structure parameters using radiological bone morphometric analysis [J]. Oral Radiology,2005,21(1):30-37.
[40] Silva AMHD, Alves JM, Silva OLD, et al. Two and three-dimensional morphometric analysis of trabecular bone using X-ray microtomography (μCT) [J]. Revista Brasileira De Engenharia Biomedica, 2014, 30(2):93-101.
[41] Wang Lei, Zhang Longzhen, Pan Haobo, et al. Abnormal subchondral bone microstructure following steroid administration is involved in the early pathogenesis of steroid-induced osteonecrosis [J]. Osteoporos Int, 2016, 27(1):153-159.
[42] Cieszko M, Szczepański Z, Gadzaa P. Determination of bone porosity based on histograms of 3D μCT images [J]. Journal of Materials Science, 2014, 50(2):1-12.
[43] Thomsen JS, Jensen MV, Niklassen AS, et al. Age-related changes in vertebral and iliac crest 3D bone microstructure differences and similarities [J]. Osteoporosis International, 2015, 26(1):219-228.
[44] 吴沛泽. 基于QCT影像的动物骨结构参数测量方法研究 [D]. 南京:东南大学, 2016.
[45] 樊立娜,刘素筠,孙栋,等. HRMRI对绝经后妇女骨质疏松症药物治疗效果的评价 [J].中国骨质疏松杂志,2010,16(2): 113-119.
[46] Ohser J, Redenbach C, Schladitz K. Mesh free estimation of the structure model index [J]. Image Analysis & Stereology,2009, 28(3):179-185.
[47] Nakada H, Sakae T, Watanabe T. Structure model index changes in the femoral epiphyseal region on micro-computed tomography caused by a supplement diet in ovariectomized rats [J]. Journal of Hard Tissue Biology, 2014, 23(2):169-176.
[48] 李国平. 自守函数与闵可夫斯基函数 [M]. 北京:科学出版社, 1979.
[49] Tabor Z. A novel method of estimating structure model index from gray-level images [J]. Medical Engineering & Physics, 2011, 33(33): 218-225.
[50] Salmon PL, Claes O, Shefelbine SJ, et al. Structure model index does not measure rods and plates in trabecular bone [J]. Frontiers in Endocrinology,2015,6:162.
[51] 李梦. 图像分割的结构张量几何活动轮廓模型 [J]. 计算机应用研究,2014,31(12):3890-3893.
[52] Marangalou JH, Ito K. A novel approach to estimate trabecular bone anisotropy from stress tensors [J]. Biomechanics and Modeling in Mechanobiology,2015,14(1):39-48.
[53] Bishop PJ, Clemente CJ, Hocknull SA, et al. The effects of cracks on the quantification of the cancellous bone fabric tensor in fossil and archaeological specimens: a simulation study [J]. Journal of Anatomy,2016.230:461-470.
[54] Whitehouse WJ. The quantitative morphology of anisotropic trabecular bone [J]. Journal of Microscopy,1974,101(2):153-168.
[55] Tabor Z. Equivalence of mean intercept length and gradient fabric tensors-3d study [J]. Medical Engineering & Physics,2012,34(5): 598-604.
[56] Moreno R, Borga M, Smedby . Generalizing the mean intercept length tensor for gray-level images [J]. Medical Physics,2012, 39(7): 4599-4612.
[57] Nazemi SM, Cooper DML, Johnston JD. Quantifying trabecular bone material anisotropy and orientation using low resolution clinical CT images: A feasibility study [J]. Medical Engineering & Physics,2016,38(9): 978-987.
[58] Allison SJ, Poole KE, Treece GM, et al. The influence of high-impact exercise on cortical and trabecular bone mineral content and 3d distribution across the proximal femur in older men: A randomized controlled unilateral intervention [J]. Journal of Bone & Mineral Research,2015,30(9):1709-1716.
[59] Odgaard A, Jensen EB, Gundersen HJG. Estimation of structural anisotropy based on volume orientation. A new concept [J]. Journal of Microscopy,1990,157(Pt 2):149-162.
[60] Fields AJ, Keaveny TM. Trabecular Architecture and Vertebral Fragility in Osteoporosis [J]. Current Osteoporosis Reports, 2012, 10(2):132-140.
[61] Tabor Z, Lataa Z. 3D gray-level histomorphometry of trabecular bone-A methodological review [J]. Image Analysis & Stereology, 2014,33(1):1-12.
[62] D’Souza MS, Isac C, Venkatesaperumal R, et al. Exploring fracture risk factors among Omani women: Implications for risk assessment[J]. Open Journal of Nursing, 2012, 2(4):365-371.
[63] Permuy M, Guede D, López-Pea M, et al. Comparison of various SYSADOA for the osteoarthritis treatment: an experimental study in rabbits [J]. BMC Musculoskeletal Disorders,2015,16(1):120.
[64] Zehani S, Mimi M, Taleb-Ahmed A, et al. Anisotropy analysis of textures using wavelets transform and fractal dimension[C]// Ahmed B H, Basel S, eds. Advanced Technologies for Signal and Image Processing (ATSIP 2016). Monastir: Curran Associates, 2016: 341-347.
[65] Moreno R, Borga M, Klintstrm E, et al. Anisotropy estimation of trabecular bone in gray-scale: Comparison between cone beam and micro computed tomography data [M]//Developments in Medical Image Processing and Computational Vision. Berlin: Springer International Publishing, 2015: 207-220.
[66] Zeytinogˇlu M, B, Dündar N, et al. Fractal analysis for the assessment of trabecular peri-implant alveolar bone using panoramic radiographs [J]. Clinical Oral Investigations,2015, 19(2): 519-524.
[67] Wu Yuchin, Adeeb S, Doschak MR. Using micro-CT derived bone microarchitecture to analyze bone stiffness-a case study on osteoporosis rat bone [J]. Frontiers in Endocrinology,2015,6:80.
[68] El Hassani ASEB, El Hassouni M, Jennane R, et al. Texture analysis for trabecular bone x-ray images using anisotropic morlet wavelet and Rényi entropy [M]// Image and Signal processing. Berlin: Springer International Publishing, 2012:290-297.
[69] Pustelnik N, Wendt H, Abry P, et al. Combining local regularity estimation and total variation optimization for scale-free texture segmentation [J]. IEEE Transactions on Computational Imaging, 2016, 2(4):468-479.
[70] 郑磊斌,嵇鸣,庄天戈. 活体磁共振图像分析对骨质疏松的初步评估 [J]. 中国医疗器械杂志,2005,29(4):244-246.
[71] 陈树越,李颖,邹凌. 基于Micro-CT的小鼠骨小梁LBF模型提取及特征分析 [J]. 生物医学工程研究,2016,35(2):65-70.
[72] Padma A, Sukanesh R. Automatic classification and segmentation of brain tumor in CT images using optimal dominant gray ievel run iength texture features [J]. International Journal of Advanced Computer Science & Applications, 2011, 2(10):53-59.
[73] Brodic' D, Amelio A, Milivojevic' ZN. Classification of the scripts in medieval documents from balkan region by run-length texture analysis [M]// Neural Information Processing. Berlin: Springer International Publishing, 2015:262-262.
[74] Rocha SVD, Junior GB, Silva AC, et al. Texture analysis of masses malignant in mammograms images using a combined approach of diversity index and local binary patterns distribution [J]. Expert Systems with Applications, 2016, 66:7-19.
[75] Leijenaar RTH, Nalbantov G, Carvalho S, et al. The effect of SUV discretization in quantitative FDG-PET Radiomics: The need for standardized methodology in tumor texture analysis [J]. Scientific Reports,2015,5:11075.
[76] Molina D, Pérez-Beteta J, Martínez-González A, et al. Influence of gray level and space discretization on brain tumor heterogeneity measures obtained from magnetic resonance images [J]. Computers in Biology & Medicine, 2016, 78:49-57.
[77] Sassi OB, Sellami L, Slima MB, et al. Improved spatial gray level dependence matrices for texture analysis [J]. International Journal of Computer Science & Information Technolo, 2012, 4(6):209-219.
[78] Padma A, Sukanesh R. SVM based classification of soft tissues in brain CT images using wavelet based dominant gray level run length texture features [J]. Middle East Journal of Scientific Research, 2013, 13(7):883-888.
[79] Padma A, Giridharan N. Performance comparison of texture feature analysis methods using PNN classifier for segmentation and classification of brain CT images [J]. International Journal of Imaging Systems & Technology, 2016, 26(2):97-105.