Registration of whole immunohistochemical slide images: an efficient way to characterize biomarker colocalization.

BACKGROUND AND OBJECTIVE: Extracting accurate information from complex biological processes involved in diseases, such as cancers, requires the simultaneous targeting of multiple proteins and locating their respective expression in tissue samples. This information can be collected by imaging and registering adjacent sections from the same tissue sample and stained by immunohistochemistry (IHC). Registration accuracy should be on the scale of a few cells to enable protein colocalization to be assessed. METHODS: We propose a simple and efficient method based on the open-source elastix framework to register virtual slides of adjacent sections from the same tissue sample. We characterize registration accuracies for different types of tissue and IHC staining. RESULTS: Our results indicate that this technique is suitable for the evaluation of the colocalization of biomarkers on the scale of a few cells. We also show that using this technique in conjunction with a sequential IHC labeling and erasing technique offers improved registration accuracies. DISCUSSION: Brightfield IHC enables to address the problem of large series of tissue samples, which are usually required in clinical research. However, this approach, which is simple at the tissue processing level, requires challenging image analysis processes, such as accurate registration, to view and extract the protein colocalization information. CONCLUSIONS: The method proposed in this work enables accurate registration (on the scale of a few cells) of virtual slides of adjacent tissue sections on which the expression of different proteins is evidenced by standard IHC. Furthermore, combining our method with a sequential labeling and erasing technique enables cell-scale colocalization.

Immunohistochemical toolkit for tracking and quantifying xenotransplanted human stem cells.

AIM: Biomarker-based tracking of human stem cells xenotransplanted into animal models is crucial for studying their fate in the field of cell therapy or tumor xenografting. MATERIALS & METHODS: Using immunohistochemistry and in situ hybridization, we analyzed the expression of three human-specific biomarkers: Ku80, human mitochondria (hMito) and Alu. RESULTS: We showed that Ku80, hMito and Alu biomarkers are broadly expressed in human tissues with no or low cross-reactivity toward rat, mouse or pig tissues. In vitro, we demonstrated that their expression is stable over time and does not change along the differentiation of human-derived induced pluripotent stem cells or human glial-restricted precursors. We tracked in vivo these cell populations after transplantation in rodent spinal cords using aforementioned biomarkers and human-specific antibodies detecting apoptotic, proliferating or neural-committed cells. CONCLUSION: This study assesses the human-species specificity of Ku80, hMito and Alu, and proposes useful biomarkers for characterizing human stem cells in xenotransplantation paradigms.

An automated blur detection method for histological whole slide imaging.

Whole slide scanners are novel devices that enable high-resolution imaging of an entire histological slide. Furthermore, the imaging is achieved in only a few minutes, which enables image rendering of large-scale studies involving multiple immunohistochemistry biomarkers. Although whole slide imaging has improved considerably, locally poor focusing causes blurred regions of the image. These artifacts may strongly affect the quality of subsequent analyses, making a slide review process mandatory. This tedious and time-consuming task requires the scanner operator to carefully assess the virtual slide and to manually select new focus points. We propose a statistical learning method that provides early image quality feedback and automatically identifies regions of the image that require additional focus points.