The ratio between blood-forming cells (red color) and adipocytes (yellow color) is not constant. It changes with age, between different parts of the skeleton, and in various disease conditions or cancer treatments like chemo- and radio-therapy, which cause a condition called "bone marrow aplasia". Changes in the cells' ratio produce so-called "yellow-to-red" and "red-to-yellow" shifts in the color of the bone marrow, which is used for monitoring its condition.
This monitoring however is not entirely standardized, but relies on assessments by pathologists of histological images. In research, the relative health of bone marrow samples is also assessed qualitatively, through histological images. This subjectivity, although greatly compensated for, can still cause diagnostic and research limitations. Publishing in Frontiers Endocrinology, scientists led by Olaia Naveiras at EPFL, introduce MarrowQuant, a new digital pathology software that can "read" histological images of bone marrow and "describe" them quantitatively, building maps based on values to complement the images. The potential applications of this approach can revolutionize digital histology.
Its code already uploaded on GitHub, MarrowQuant is described as "a user-friendly algorithm for the quantification of H&E bone marrow tissue biopsies in whole slide images." In the paper, the researchers use MarrowQuant to build the first-ever quantitative map of the heterogeneity of bone marrow throughout the skeleton of mice suffering from age-induced and radiation-induced aplasia.
"The work was a massive effort only possible thanks to the long and fruitful collaboration with EPFL's BioImaging and Optics Platform [BIOP]," says Naveiras who is also the President of the International Bone Marrow Adiposity Society (BMAS). MarrowQuant, uses the open-source software QuPath, and can systematically quantify multiple bone components in histological images without bias. It does this by discerning and quantifying the areas occupied by various parts of the bone marrow - including the vasculature and the bone itself. One of the potential uses of MarrowQuant will be to re-examine historical sample collections of bone samples and even data from old clinical trials.
Source: Ecole Polytechnique Fédérale de Lausanne
