Office of Technology Transfer – University of Michigan

Methods for the detection and diagnosis of osteoporosis and osteogenesis imperfecta using atomic force microscopy

Technology #5466

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Mark M. Banaszak Holl
Managed By
Tiefei Dong
Senior Licensing Specialist, Life Sciences 734-763-5332
Patent Protection
US Patent Pending

This technology utilizes atomic force microscopy (AFM) imaging and two-dimensional fast Fourier transform (2D FFT) analysis to examine collagen fibril D-spacing in collagenous tissues. Collagen is the major building block of many human tissues, including skin, tendons, and bone. Structurally, collagen molecules are arranged into fibrils that contain repeating staggered gaps termed D-periodic gap/overlap spacing or “D-spacing”. Studies have shown that collagen fibril D-spacing is altered in certain human diseases including estrogen deprivation induced osteoporosis and osteogenesis imperfecta (brittle bone disease). The measurement of D-spacing in collagenous tissues using AFM and 2D FFT represents a powerful potential tool to detect and diagnose these human diseases.

Detection and diagnosis of prevalent bone diseases by visualizing collagen structure

The most prevalent bone disease in the United States is osteoporosis. Approximately 60 million Americans have osteoporosis or osteopenia (early stage osteoporosis) and the incidence of the disease, which is characterized by accelerated bone loss resulting in brittle and weak bones, is expected to increase in the future due to aging populations. Currently, osteoporosis is diagnosed via bone mineral density tests that do not take into account changes in collagen structure associated with the disease. Previously, direct characterization of collagen structure was limited to qualitative means and included electron and light microscopy. This technology utilizes AFM and 2D FFT to provide an accurate and quantitative measurements of collagen D-spacing.

Appliations and Advantages

  • Quantitative method to detect collagen ultrastructure in various tissues
  • Detection and diagnosis of osteoporosis and osteogenesis imperfecta

  • Limited sample processing improves accuracy and reduces artifacts