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Abstract Bone tissue, with its complex structure, often necessitates decalcification of the hard tissue for ex vivo morphological studies. The choice of a suitable decalcification method plays a crucial role in preserving desired features and ensuring compatibility with diverse imaging techniques. The search for a universal decalcification method that is suitable for a range of biophotonic analyses remains an ongoing challenge. In this study, we systematically assessed five standard bone decalcification protocols, encompassing strong mineralic acids (3% and 5% nitric acid), a commercially available formulation of hydrochloric and formic acid), as well as weak organic acids (5% trichloroacetic acid and 8% formic acid), and a chelating agent (25% ethylenediamine-tetraacetic acid) with varying decalcification durations, using mouse long bones as our experimental model. Our imaging analysis panel included classical histological staining (Hematoxylin and Eosin, H&E), immunofluorescence staining, and label-free Raman microspectroscopic imaging. We used cryosections instead of paraffin sections since paraffin interferes with tissue Raman signals. This approach is not as commonly used as it is more prone to handling artifacts, but is the preferred method for subsequent Raman analysis. Decalcification efficacy was evaluated based on various qualitative and some quantitative imaging parameters by 2–3 independent observers. Our systematic approach revealed that the chelating agent, when used for 24 h, optimally preserved bone features and, thus, would be the ideal decalcifying agent for comprehensive subsequent analysis. However, the choice of decalcifier and the ideal decalcification duration may vary depending on the type and thickness of bone, necessitating tailored adjustments to meet specific experimental requirements.

Staphylococcus aureus (S. aureus) is a facultative pathogenic bacterium that can cause infections in various tissue types in humans. Fluorescence imaging techniques have been employed to visualize the bacteria in ex-vivo samples mostly in research, aiding in the understanding of the etiology of the pathogen. However, the multispectral images generated from fluorescence microscopes are complex, making it difficult to locate bacteria across image files, especially in consecutive planes with different imaging depths. To address this issue, we present Findaureus, an open-source application specifically designed to locate and extract critical information about bacteria, especially S. aureus. Due to the limited availability of datasets, we tested the application on a dataset comprising fluorescence-labelled infected mouse bone tissue images, achieving an accuracy of 95%. We compared Findaureus with other state-of-the-art image analysis tools and found that it performed better, given its specificity toward bacteria localization. The proposed approach has the potential to aid in medical research of bone infections and can be extended to other tissue and bacteria types in the future.

The evolution of biomedical imaging technology is allowing the digitization of hundreds of glass slides at once. There are multiple microscope scanners available in the market including low-cost solutions that can serve small centers. Moreover, new technology is being researched to acquire images and new modalities are appearing in the market such as electron microscopy. This reality offers new diagnostics tools to clinical practice but emphasizes also the lack of multivendor system’s interoperability. Without the adoption of standard data formats and communications methods, it will be impossible to build this industry through the installation of vendor-neutral archives and the establishment of telepathology services in the cloud. The DICOM protocol is a feasible solution to the aforementioned problem because it already provides an interface for visible light and whole slide microscope imaging modalities. While some scanners currently have DICOM interfaces, the vast majority of manufacturers continue to use proprietary solutions. This article proposes an automated DICOMization pipeline that can efficiently transform distinct proprietary microscope images from CLSM, FIB-SEM, and WSI scanners into standard DICOM with their biological information maintained within their metadata. The system feasibility and performance were evaluated with fifteen distinct proprietary modalities, including stacked WSI samples. The results demonstrated that the proposed methodology is accurate and can be used in production. The normalized objects were stored through the standard communications in the Dicoogle open-source archive.