Inventors of CBMT validate accuracy of CBMT in leading journal, Bone. Bone. 2019 Mar;120:336-346. doi: 10.1016/j.bone.2018.11.018. Epub 2018 Nov 26.
High error rates in the prediction of fragility fractures by bone mineral density have motivated searches for better clinical indicators of bone strength, and the high incidence of non-hip, non-spine fractures has raised interest in cortical bone. The aim of this study was to assess the accuracy of Cortical Bone Mechanics Technology™. CBMT is a new non-invasive 3-point bending technique for measuring the mechanical properties of cortical bone in the ulnas of living humans.
35 cadaveric human arms were obtained from small women and large men ranging widely in age (17 < Age < 99 years) and body size (14 < BMI < 40 kg/m2). Noninvasive CBMT measurements of the flexural rigidity of the ulna bones within these arms (EICBMT) were compared to measurements of EI by Quasistatic Mechanical Testing in the ulnas excised from those arms (EIQMT). Ulna bending strength was also measured by QMT as the peak moment before fracture (Mpeak). The open source BoneJ plugin to ImageJ image processing software was used to calculate cortical porosity (CP) in micro-computed tomography images of a 2 mm length of the mid-shaft of each fractured ulna, and the interosseous diameter (IOD) of each ulna was also measured in those images.
EICBMT measurements (13 < EICBMT < 97 Nm2) explained 99% of the variance in QMT measurements of ulna bending strength (11 < Mpeak < 90 Nm), but EICBMT was biased high by 30% (p < 0.0001) relative to EIQMT (11 < EIQMT < 69 Nm2). After correcting this bias, EICBMT and EIQMT measurements lay along the identity line (y = 1.00x, R2 = 0.99, SEE = 3.1 Nm2). Predictions of Mpeak by EICBMT were less accurate than predictions by EIQMT (both R2 = 0.99; SEECBMT = 5.9 Nm vs SEEQMT = 4.5 Nm, F = 2.92, p = 0.001), but EICBMT predictions were substantially more accurate than those by IOD (R2 = 0.79; SEEIOD = 10.6 Nm, F = 3.30, p < 0.001) and CP (R2 = 0.35; SEECP = 18.9 Nm, F = 10.45, p < 10-9). Predictions by EICBMT were also more accurate than predictions by arm donor height (R2 = 0.63; SEE = 14.3 Nm, F = 5.87, p < 10-6), body weight (R2 = 0.77; SEE = 11.1 Nm, F = 3.54, p < 0.001) and BMI (R2 = 0.64; SEE = 14.1 Nm, F = 2.39, p < 0.01). In forward stepwise multiple regression beginning with EICBMT, only age explained any additional variance in ulna bending strength (ΔR2 = 0.3%, F = 8.03, p = 0.008).
Noninvasive CBMT measurements of ulna EI explain 99% of individual differences in QMT measurements of ulna bending strength in cadaveric human arms.
Copyright © 2018 Elsevier Inc. All rights reserved.
Bone fragility; Bone mechanics; Bone strength; Cortical bone; Cortical porosity; Ulna
- 2 Department of Biological Sciences, Ohio University, Athens, OH 45701, United States of America.
- 3 Honors Tutorial College, Ohio University, Athens, OH 45701, United States of America.
- 4 Department of Biological Sciences, Ohio University, Athens, OH 45701, United States of America; Ohio Musculoskeletal and Neurological Institute, Ohio University, Athens, OH 45701, United States of America. Electronic address: firstname.lastname@example.org.