MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology

Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematologic and nonhematologic disorders. Clinical assessment is based on a semiquantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient, user-friendly digital hematopathology workflow integrated within QuPath software, which serves as BM quantifier for 5 mutually exclusive compartments (bone, hematopoietic, adipocytic, and interstitial/microvasculature areas and other) and derives the cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized through the adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of hematoxylin and eosin images obtained from 250 bone specimens, from control subjects and patients with acute myeloid leukemia or myelodysplastic syndrome, at diagnosis and follow-up, and measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from 4 hematopathologists. The algorithm was capable of robust BM compartment segmentation with an average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%), and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R² = 0.92-0.98, intraclass correlation coefficient [ICC] = 0.98; interobserver ICC = 0.96). BM compartment segmentation quantitatively confirmed the reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R² = 0.86, n = 42). Thus, we conclude that these validation experiments establish MarrowQuant 2.0 as a reliable tool for BM cellularity assessment. We expect this workflow will serve as a clinical research tool to explore novel biomarkers related to BM stromal components and may contribute to further validation of future digitalized diagnostic hematopathology workstreams.

MarrowQuant Across Aging and Aplasia: A Digital Pathology Workflow for Quantification of Bone Marrow Compartments in Histological Sections

The bone marrow (BM) exists heterogeneously as hematopoietic/red or adipocytic/yellow marrow depending on skeletal location, age, and physiological condition. Mouse models and patients undergoing radio/chemotherapy or suffering acute BM failure endure rapid adipocytic conversion of the marrow microenvironment, the so-called "red-to-yellow" transition. Following hematopoietic recovery, such as upon BM transplantation, a "yellow-to-red" transition occurs and functional hematopoiesis is restored. Gold Standards to estimate BM cellular composition are pathologists' assessment of hematopoietic cellularity in hematoxylin and eosin (H&E) stained histological sections as well as volumetric measurements of marrow adiposity with contrast-enhanced micro-computerized tomography (CE-μCT) upon osmium-tetroxide lipid staining. Due to user-dependent variables, reproducibility in longitudinal studies is a challenge for both methods. Here we report the development of a semi-automated image analysis plug-in, MarrowQuant, which employs the open-source software QuPath, to systematically quantify multiple bone components in H&E sections in an unbiased manner. MarrowQuant discerns and quantifies the areas occupied by bone, adipocyte ghosts, hematopoietic cells, and the interstitial/microvascular compartment. A separate feature, AdipoQuant, fragments adipocyte ghosts in H&E-stained sections of extramedullary adipose tissue to render adipocyte area and size distribution. Quantification of BM hematopoietic cellularity with MarrowQuant lies within the range of scoring by four independent pathologists, while quantification of the total adipocyte area in whole bone sections compares with volumetric measurements. Employing our tool, we were able to develop a standardized map of BM hematopoietic cellularity and adiposity in mid-sections of murine C57BL/6 bones in homeostatic conditions, including quantification of the highly predictable red-to-yellow transitions in the proximal section of the caudal tail and in the proximal-to-distal tibia. Additionally, we present a comparative skeletal map induced by lethal irradiation, with longitudinal quantification of the "red-to-yellow-to-red" transition over 2 months in C57BL/6 femurs and tibiae. We find that, following BM transplantation, BM adiposity inversely correlates with kinetics of hematopoietic recovery and that a proximal to distal gradient is conserved. Analysis of in vivo recovery through magnetic resonance imaging (MRI) reveals comparable kinetics. On human trephine biopsies MarrowQuant successfully recognizes the BM compartments, opening avenues for its application in experimental, or clinical contexts that require standardized human BM evaluation.

Correlation study between osteoporosis and hematopoiesis in the context of adjuvant chemotherapy for breast cancer

This retrospective study attempts to establish if a correlation exists between osteoporosis and hematopoiesis before and after adjuvant chemotherapy in the context of non-metastatic breast cancer. Osteoporosis is interpreted both as a direct marker of osteoblastic decline and as an indirect marker of increased bone marrow adiposity within the hematopoietic microenvironment. Patients from the “Centre du Sein” at CHUV (Centre Hospitalier Universitaire Vaudois) undergoing adjuvant chemotherapy were included in this study. Evolution of blood counts was studied in correlation with the osteoporosis status. Toxicity of chemotherapy was coded according to published probability of febrile neutropenia. One hundred forty-three women were included: mean age 52.1 ± 12.5 years, mean BMI (body mass index) 24.4 ± 4.1. BMD (bone mineral density) scored osteoporotic in 32% and osteopenic in 45%. Prior to chemotherapy, BMD was positively correlated with neutrophil (p < 0.001) and thrombocyte (p = 0.01) count; TBS (trabecular bone score) was not correlated with blood count. After the first cycle of chemotherapy, an increase of one point in TBS correlated with a decrease of 57% on the time to reach leucocyte nadir (p = 0.004). There was a positive correlation between BMD and risk of infection (p < 0.001). Our data demonstrates an association between osteoporosis and lower blood counts in a younger cohort than previously published, extending it for the first time to neutrophil counts in females. Our results suggest that the healthier the bone, the earlier the lowest leucocyte count value, prompting further research on this area.