Gaucher-like cells in myelodysplastic syndrome with ring sideroblasts

Khoury, Christelle El; Farhat, Hussein

doi:10.1016/j.htct.2020.08.011

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Bone marrow smears show Gaucher-like cells with the use of May Grunwald-Giemsa (MGG) stain. They have been described in various hemolytic and myeloproliferative disorders, in hematologic malignancies and in infectious diseases such as hemoglobinopathies, some subtypes of congenital dyserythropoietic anemia, chronic myeloid leukemia, Waldenstrom macroglobulinemia, multiple myeloma, Hodgkin's lymphoma and tuberculosis [5][6][7][8][9][10][11][12][13][14]. Gaucher-like cells are difficult to differentiate from true Gaucher cells using morphology alone; cytochemistry and electron microscopic findings aid in definitive differentiation.…”

Section: Discussionmentioning

confidence: 99%

Gaucher-like Cells in Thalassemia Intermedia: Is It a Challenge?

Komninaka,

Flevari,

Karkaletsis

et al. 2023

Diseases

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We describe two cases of thalassemia intermedia (TI) patients with the presence of Gaucher-like cells in hematopoietic tissue biopsies, raising diagnostic dilemmas. The first is a 56-year-old female with bone lesions, splenomegaly, hypochromic microcytic anemia and Gaucher-like cells in the bone marrow, with a final diagnosis of TI, and the second is a 69-year-old male with TI, monoclonal gammopathy of undetermined significance (MGUS) that accelerated to multiple myeloma (MM) requiring treatment, bone disease and Gaucher-like cells in the bone marrow and the spleen, and heterozygoty of Gaucher disease (GD). Gaucher-like cells are difficult to differentiate from true Gaucher cells, that are the hallmark of GD suspicion. These cells are usually reported in the lymphohematopoietic system. They have been described in myeloproliferative disorders, hematological malignancies, infectious diseases, hemoglobinopathies and other hemolytic anemias. The presence of Gaucher-like cells in patients with thalassemia major has been well documented, whereas there are limited references regarding cases with thalassemia intermedia. The identification of these cells in thalassemia probably reflects the high cell turnover. The bony complications in GD and TIare not yet fully explained in the literature, and this raises the question of whether Gaucher-like cells could play a pathogenetic role in the bone disease of thalassemia, as Gaucher cells are considered to play a similar role in bone complications of GD. Moreover, given the rarity and similarity of Gaucher and Gaucher-like cells, we would like to highlight that the presence of Gaucher-like cells in the bone marrow should not be overlooked, as they might be obscuring an underlying pathology, in order to ensure that hematologists, internists and hematopathologists will be promptly and accurately diagnosed.

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Section: Discussionmentioning

confidence: 99%

Gaucher-like Cells in Thalassemia Intermedia: Is It a Challenge?

Komninaka,

Flevari,

Karkaletsis

et al. 2023

Diseases

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Naïve Bayes classifier assisted automated detection of cerebral microbleeds in susceptibility-weighted imaging brain images

Ateeq,

Faheem,

Ghoneimy

et al. 2023

Biochem. Cell Biol.

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Cerebral microbleeds (CMBs) in the brain are the essential indicators of critical brain disorders such as dementia and ischemic stroke. Generally, CMBs are detected manually by experts, which is an exhaustive task with limited productivity. Since CMBs have complex morphological nature, manual detection is prone to errors. This paper presents a machine learning-based automated CMB detection technique in the brain susceptibility-weighted imaging (SWI) scans based on statistical feature extraction and classification. The proposed method consists of three steps: (1) removal of the skull and extraction of the brain; (2) thresholding for the extraction of initial candidates; and (3) extracting features and applying classification models such as random forest and naïve Bayes classifiers for the detection of true positive CMBs. The proposed technique is validated on a dataset consisting of 20 subjects. The dataset is divided into training data that consist of 14 subjects with 104 microbleeds and testing data that consist of 6 subjects with 63 microbleeds. We were able to achieve 85.7% sensitivity using the random forest classifier with 4.2 false positives per CMB, and the naïve Bayes classifier achieved 90.5% sensitivity with 5.5 false positives per CMB. The proposed technique outperformed many state-of-the-art methods proposed in previous studies.

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Gaucher-like cells in myelodysplastic syndrome with ring sideroblasts

Cited by 2 publications

References 6 publications

Gaucher-like Cells in Thalassemia Intermedia: Is It a Challenge?

Gaucher-like Cells in Thalassemia Intermedia: Is It a Challenge?

Naïve Bayes classifier assisted automated detection of cerebral microbleeds in susceptibility-weighted imaging brain images

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