Oravec Daniel, Yaldo Omar, Bolton Carrie, Flynn Michael J, van Holsbeeck Marnix, Yeni Yener N
Department of Orthopaedics, Bone and Joint Center, Henry Ford Health System, HFH/WSU Integrative Biosciences (iBio) Research Bldg, 6135 Woodward Ave, Detroit, MI 48202.
Spectrum Health, Michigan State University, Grand Rapids, MI.
AJR Am J Roentgenol. 2019 Jul;213(1):W38-W44. doi: 10.2214/AJR.18.20700. Epub 2019 Apr 11.
The objective of this study was to investigate the association of fractal-derived bone microstructural parameters with vertebral fracture status using in vivo digital tomosynthesis images of the spine. Digital tomosynthesis images of the thoracic and lumbar spine from T1 to L5 were acquired from 36 patients with newly diagnosed multiple myeloma or monoclonal gammopathy of uncertain significance (age range, 39-85 years old). Scans were performed with patients in the supine position with reconstructed planes formed in the coronal direction. Bone mineral density (BMD) was recorded for 10 patients who had recently undergone dual x-ray absorptiometry. Vertebral fracture and lytic lesion status was determined by a radiologist from digital radiographs. Radiologist interpretation was reviewed to identify levels with a minimum number of fractures or lesions. For fractal analysis, the largest possible cuboid volume of interest within the cancellous bone was cropped from T7 and T11 images. Mean and SD of fractal variables between slices of fractal dimension (FD, a measure of self-similarity in the texture), mean lacunarity (λ, a measure of heterogeneity) and the slope of lacunarity versus box size relationship (S, a measure of sensitivity of heterogeneity to size scale) were calculated using a box-counting method. A generalized estimating equation (GEE) platform was used to examine fractal variables as predictors of fracture status. Fracture status was not significantly associated with sex, race, age, stage of myeloma, presence of lesion in the spine, or BMD. In light of these results, no correction was made for these variables in further analyses of fractal variables. No interaction was found between vertebral level and any of the fractal variables ( = 0.12-0.77). Therefore, vertebral level was not considered further as an independent variable. Logistic regression analysis within GEE indicated that probability of fracture decreased with increasing mean FD ( = 0.02). In contrast, probability of fracture increased with increasing mean λ ( = 0.03). Although not to a statistically significant degree, probability of fracture increased with increasing mean S ( = 0.08), SD of FD ( = 0.07), SD of λ ( = 0.07), and SD of S ( = 0.06). We found FD and lacunarity calculated within the cancellous centrum of T7 and T11 vertebrae to be significantly associated with the presence of a vertebral fracture in this cohort. The decreased probability of fracture with increasing fractal dimension and increased probability of fracture with increasing lacunarity are consistent with the idea that cancellous bone with a better organized trabecular architecture is mechanically more competent. To our knowledge, this is the first in vivo evidence that fractal analysis of vertebral bone from tomosynthesis images may be useful in assessing vertebral fracture risk in patients with multiple myeloma.
本研究的目的是利用脊柱的体内数字断层合成图像,探讨分形衍生的骨微观结构参数与椎体骨折状态之间的关联。从36例新诊断的多发性骨髓瘤或意义未明的单克隆丙种球蛋白病患者(年龄范围39 - 85岁)获取了从T1至L5的胸腰椎数字断层合成图像。扫描时患者处于仰卧位,重建平面沿冠状方向形成。记录了10例近期接受双能X线吸收测定的患者的骨密度(BMD)。由放射科医生根据数字X线片确定椎体骨折和溶骨性病变状态。对放射科医生的解读进行了复查,以确定骨折或病变最少的节段。对于分形分析,从T7和T11图像中裁剪出松质骨内最大可能的长方体感兴趣体积。使用盒计数法计算分形维数(FD,纹理自相似性的度量)、平均孔隙率(λ,异质性的度量)以及孔隙率与盒大小关系的斜率(S,异质性对大小尺度敏感性的度量)在各切片间的均值和标准差。使用广义估计方程(GEE)平台来检验分形变量作为骨折状态的预测指标。骨折状态与性别、种族、年龄、骨髓瘤分期、脊柱病变的存在或骨密度均无显著关联。鉴于这些结果,在分形变量的进一步分析中未对这些变量进行校正。未发现椎体节段与任何分形变量之间存在相互作用(P = 0.12-0.77)。因此,未将椎体节段进一步视为独立变量。GEE内的逻辑回归分析表明,骨折概率随平均FD的增加而降低(P = 0.02)。相反,骨折概率随平均λ的增加而增加(P = 0.03)。虽然未达到统计学显著程度,但骨折概率随平均S(P = 0.08)、FD的标准差(P = 0.07)、λ的标准差(P = 0.07)和S的标准差(P = 0.06)的增加而增加。我们发现,在该队列中,T7和T11椎体松质骨中心计算得到的FD和孔隙率与椎体骨折的存在显著相关。骨折概率随分形维数增加而降低以及随孔隙率增加而增加,这与小梁结构组织更好的松质骨在力学上更具优势的观点一致。据我们所知,这是首个体内证据,表明从断层合成图像对椎体骨进行分形分析可能有助于评估多发性骨髓瘤患者的椎体骨折风险。