SP0107 THE 4-D+ NANOSCOPE: THE RESOLUTION FOR BIOLOGICAL SAMPLES

Abstract

Background: In ageing societies all over the globe, the number of people suffering from bone disease, e.g. osteoporosis (OP) in the first place, has increased dramatically. OP considerably impairs patients’ life quality, and results in high societal costs. However, current understanding of OP is still insufficient due to the lack of appropriate high resolution tools that permit a thorough analysis of scale bridging bone architectures from macro to nano with statistical significance to support the development of better treatments by drugs or surgical intervention. Objectives: To revolutionize our knowledge of bone diseases based on an increase in understanding of the underlying bone anatomy, cutting-edge correlative high-resolution microscopy and spectroscopy together with advanced data analysis including machine learning approaches permit reaching the next, so far unprecedented level of understanding. Methods: Correlative workflows starting from X-ray microscopy (XRM) volume analysis, with voxel sizes of The present paper demonstrates novel findings related to various partly age related bone diseases using advanced correlative data acquisition (cf. Figure 2). Results: Figure 1 shows the different bone fine structures, composed of trabecular and vascular networks as well as a three-dimensional arrangement of osteo-lacunae that host osteocytes, as obtained by volume analysis in a new generation of lab-based x-ray microscope (Zeiss XRM Versa 520). These fine structures can be assessed quantitatively with statistical significance and can be correlated with additional modalities as shown in Figure 2. Elucidating examples demonstrating the power of such an approach will be given [ref 1, ref 2, ref 3, ref 4]. Figure 2 shows the an example correlative workflow from sample collection over sample preparation and the acquisition of various image modalities utilizing correlated data from electron-, ion-beam imaging and analytics, probes and focused laser light to study scale bridging bone architectures. We will demonstrate how these correlative workflows will permit to advance the current understanding of bone architectures and function substantially and will show some first systematic correlative microscopy and spectroscopy studies on mouse tibia and human bone [ref1, ref2, ref3, ref 4]. Conclusion: Based on our correlative analytics and the data availability, the advanced data interpretation using machine learning approaches will be discussed. Using this approach, all details of bone micro-/nano-architecture can be used to provide a novel clinical tool-set for future for early detection of bone diseases.