An Automated Histologic System for 3D Histomorphometry of the Mouse Knee

Abstract

Osteoarthritis (OA) is a degenerative joint disease that is a leading cause of adult pain and disability in Western countries1. Clinically, several structural features of the joint are important in diagnosis, prognosis and evaluation of treatment efficacy, e.g. cartilage volume, homogeneity and joint space narrowing2,3. In animal models of OA, structural features such as bone defects and cartilage changes are commonly investigated using histomorphometry, a technique that uses stereological point counting and manual tracing of regions of interest to extract 3-dimensional (3D) geometrical properties from 2D histology slides. This is time-consuming and subject to inter-observer variations, hence limiting precision 4,5. Therefore, a technique for rapidly imaging joint structures in 3D at high resolution, including articular cartilage and subchondral bone, is currently needed in pre-clinical OA research.

Application of autofluorescence robotic histology for quantitative evaluation of the 3‐dimensional morphology of murine articular cartilage

“…In this study, we sought to image mouse articular cartilage in 3D and obtain morphological information on this tissue using a customized device for high‐throughput robotic histology. The use of automated systems for high‐resolution, 3D histological imaging is becoming increasingly important to assess experimental models of pathology (Tsuchiya & Yamada, ) and newer systems can now achieve full automation on serial sectioning and imaging (Kazakia et al, ; Murienne et al, ; Wilson et al, ) which previous systems did only by semi‐automated approaches (Hashimoto, Kusakabe, & Ishikawa, ). Using the 3D histocutter, we successfully demonstrated that, in the absence of any staining and purely based on tissue autofluorescence, articular cartilage and subchondral bone can be imaged in 3D at high‐resolution.…”

“…While the rotary microtome in the cutting unit removes thin sections that are discarded by air puffers, the high‐resolution camera images the surface. A sequential stack of images is recorded in the computer and acquisition using multiple fluorescent channels is also possible (Andrikakou et al, ; Murienne et al, ; Tang et al, ).…”

“…We used a robotic imaging system with high‐resolution capability, termed “3D histocutter” (Department of Bioengineering, Imperial College London), that automatically sections embedded tissue samples and serially acquires fluorescence microscopy images (Burgoyne, Downs, Bellezza, & Hart, ). Preliminary studies have demonstrated its ability to image decalcified mouse knee joints (Murienne et al, ) and, subsequently, its applicability on soft tissue imaging, namely in brain (Tang, Ardila Jimenez, Chakraborty, & Schultz, ) and lung (Andrikakou, Vickraman, & Arora, ) samples from experimental models. Furthermore, analogous automated systems have successfully imaged mouse embryos (Tsuchiya & Yamada, ) and rat trabecular bone (Matheny et al, ; Slyfield, Tkachenko, Wilson, & Hernandez, ) in 3D using fluorescence.…”