Automated resolution independent method for comparing in vivo and dry trabecular bone

Jaap P.P. Saers, Lily J. DeMars, Nicholas B. Stephens, Tea Jashashvili, Kristian J. Carlson, Adam D. Gordon, Timothy M. Ryan, Jay T. Stock

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: Variation in human trabecular bone morphology can be linked to habitual behavior, but it is difficult to investigate in vivo due to the radiation required at high resolution. Consequently, functional interpretations of trabecular morphology remain inferential. Here we introduce a method to link low- and high-resolution CT data from dry and fresh bone, enabling bone functional adaptation to be studied in vivo and results compared to the fossil and archaeological record. Materials and methods: We examine 51 human dry bone distal tibiae from Nile Valley and UK and two pig tibiae containing soft tissues. We compare low-resolution peripheral quantitative computed tomography (pQCT) parameters and high-resolution micro CT (μCT) in homologous single slices at 4% bone length and compare results to our novel Bone Ratio Predictor (BRP) method. Results: Regression slopes between linear attenuation coefficients of low-resolution pQCT images and bone area/total area (BA/TA) of high-resolution μCT scans differ substantially between geographical subsamples, presumably due to diagenesis. BRP accurately predicts BA/TA (R2 =.97) and eliminates the geographic clustering. BRP accurately estimates BA/TA in pigs containing soft tissues (R2 = 0.98) without requiring knowledge of true density or phantom calibration of the scans. Discussion: BRP allows automated comparison of image data from different image modalities (pQCT, μCT) using different energy settings, in archeological bone and wet specimens. The method enables low-resolution data generated in vivo to be compared with the fossil and archaeological record. Such experimental approaches would substantially improve behavioral inferences based on trabecular bone microstructure.

Original languageEnglish (US)
JournalAmerican Journal of Physical Anthropology
DOIs
StateAccepted/In press - 2020

All Science Journal Classification (ASJC) codes

  • Anatomy
  • Anthropology

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