Bone marrow biopsy in geriatric patients above the age of 85 years: invaluable or unnecessary? A retrospective analysis.

Bone marrow biopsy (BMB) is a well-established diagnostic tool for various hematological, oncological, and other medical conditions. However, treatment options for geriatric patients (pts) facing these diseases are often constrained. In this single-center, retrospective analysis we assessed the diagnostic value of BMB in geriatric pts aged ≥ 85 years and examined its impact on therapeutic decisions. We examined 156 BMB procedures in 129 pts, extracting data from the electronic patient records and applying descriptive statistical methods. Nearly half of the primary diagnostic procedures (26; 44.1%) resulted in a modification of the initially suspected diagnosis. Notably, 15 (25.4%) of these procedures, led to changes in both the diagnosis and planned interventional treatment. Among the 15 follow-up procedures (36.6%), disease progression was initially suspected based on symptoms, but BMB results excluded such progression. In lymphoma staging biopsies, only 2 (3.6%) prompted a change in therapeutic intervention. Importantly, no BMB-related complications, such as bleeding, infection or nerve damage, were reported. Median survival after BMB was 16.1 months across all pts, yet it varied based on the diagnosis and comorbidity score. The survival of pts with a change in therapy based on BMB results did not significantly differ from those who did not undergo a therapy change. In conclusion, BMB proved to be generally safe and beneficial in this geriatric cancer patient cohort beyond the age of 85 years. However, the advantages of lymphoma staging in this patient population warrant further consideration.

Leukocyte Counts Based on DNA Methylation at Individual Cytosines.

BACKGROUND: White blood cell counts are routinely measured with automated hematology analyzers, by flow cytometry, or by manual counting. Here, we introduce an alternative approach based on DNA methylation (DNAm) at individual CG dinucleotides (CpGs). METHODS: We identified candidate CpGs that were nonmethylated in specific leukocyte subsets. DNAm levels (ranging from 0% to 100%) were analyzed by pyrosequencing and implemented into deconvolution algorithms to determine the relative composition of leukocytes. For absolute quantification of cell numbers, samples were supplemented with a nonmethylated reference DNA. RESULTS: Conventional blood counts correlated with DNAm at individual CpGs for granulocytes (r = -0.91), lymphocytes (r = -0.91), monocytes (r = -0.74), natural killer (NK) cells (r = -0.30), T cells (r = -0.73), CD4+ T cells (r = -0.41), CD8+ T cells (r = -0.88), and B cells (r = -0.66). Combination of these DNAm measurements into the "Epi-Blood-Count" provided similar precision as conventional methods in various independent validation sets. The method was also applicable to blood samples that were stored at 4 °C for 7 days or at -20 °C for 3 months. Furthermore, absolute cell numbers could be determined in frozen blood samples upon addition of a reference DNA, and the results correlated with measurements of automated analyzers in fresh aliquots (r = 0.84). CONCLUSIONS: White blood cell counts can be reliably determined by site-specific DNAm analysis. This approach is applicable to very small blood volumes and frozen samples, and it allows for more standardized and cost-effective analysis in clinical application.

Cup-like blasts in acute myeloid leukemia.

A patient with AML with normal karyotype and the cytological pattern of cup-like blasts (CLB) is reported. The typical morphology on Pappenheim stained blood smears is shown. In addition transmission electron microscopy pictures demonstrate impressively the invaginated nuclear pocket compressing the chromatin. Cup-like blasts usually do not express CD34. There is a close relationship of CLB-AML with the molecular aberrations of NPM1 and/or FLT3-ITD.

State of the Art Cell Detection in Bone Marrow Whole Slide Images.

CONTEXT: Diseases of the hematopoietic system such as leukemia is diagnosed using bone marrow samples. The cell type distribution plays a major role but requires manual analysis of different cell types in microscopy images. AIMS: Automated analysis of bone marrow samples requires detection and classification of different cell types. In this work, we propose and compare algorithms for cell localization, which is a key component in automated bone marrow analysis. SETTINGS AND DESIGN: We research fully supervised detection architectures but also propose and evaluate several techniques utilizing weak annotations in a segmentation network. We further incorporate typical cell-like artifacts into our analysis. Whole slide microscopy images are acquired from the human bone marrow samples and annotated by expert hematologists. SUBJECTS AND METHODS: We adapt and evaluate state-of-the-art detection networks. We further propose to utilize the popular U-Net for cell detection by applying suitable preprocessing steps to the annotations. STATISTICAL ANALYSIS USED: Evaluations are performed on a held-out dataset using multiple metrics based on the two different matching algorithms. RESULTS: The results show that the detection of cells in hematopoietic images using state-of-the-art detection networks yields very accurate results. U-Net-based methods are able to slightly improve detection results using adequate preprocessing - despite artifacts and weak annotations. CONCLUSIONS: In this work, we propose, U-Net-based cell detection methods and compare with state-of-the-art detection methods for the localization of hematopoietic cells in high-resolution bone marrow images. We show that even with weak annotations and cell-like artifacts, cells can be localized with high precision.