Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases.

Analysis of bone marrow aspirates (BMAs) is an essential step in the diagnosis of hematological disorders. This analysis is usually performed based on a visual examination of samples under a conventional optical microscope, which involves a labor-intensive process, limited by clinical experience and subject to high observer variability. In this work, we present a comprehensive digital microscopy system that enables BMA analysis for cell type counting and differentiation in an efficient and objective manner. This system not only provides an accessible and simple method to digitize, store, and analyze BMA samples remotely but is also supported by an Artificial Intelligence (AI) pipeline that accelerates the differential cell counting process and reduces interobserver variability. It has been designed to integrate AI algorithms with the daily clinical routine and can be used in any regular hospital workflow.

COVID-19 Severity and Survival over Time in Patients with Hematologic Malignancies: A Population-Based Registry Study.

Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February-June 2020; n = 769 (66%)) and later (July 2020-February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11-0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01-3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22-0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81-1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis.

Management of Persistent SARS-CoV-2 Infection in Patients with Follicular Lymphoma.

INTRODUCTION: There is no consensus on the management of the coronavirus disease (COVID-19) in patients with secondary immunosuppression due to either an underlying hematological disease or to the effects of immunochemotherapy (ICT). Some of them may present persistent infection with multiple relapses of COVID-19, requiring several admissions. This study evaluated the clinical characteristics and outcomes after treatment of 5 patients with follicular lymphoma (FL), previously treated with ICT, who developed several episodes of COVID-19. METHODS: We analyzed the clinical evolution and response to treatment with antiviral agent, steroids, and convalescent plasma in 5 patients with FL and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) persistent infection. Reverse transcriptase polymerase chain reaction tests and peripheral blood immunophenotype were performed for all patients. RESULTS: All patients required hospitalization due to pneumonia with severity criteria and were re-admitted after a median of 22 days (13-42) from the previous discharge. They all showed B-cell depletion by immunophenotyping, and no traces of immunoglobulin antibodies against SARS-CoV-2 were detected in any of the cases. The survival rate was 80%. CONCLUSION: The combination therapy evidenced clinical benefits, demonstrating its capacity to control infection in immunosuppressed FL patients treated with ICT.

Myocardial fibrosis in arrhythmogenic cardiomyopathy: a genotype-phenotype correlation study.

AIMS: Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is a life-threatening entity with a highly heterogeneous genetic background. Cardiac magnetic resonance (CMR) imaging can identify fibrofatty scar by late gadolinium enhancement (LGE). Our aim is to investigate genotype-phenotype correlation in ARVC/D mutation carriers, focusing on CMR-LGE and myocardial fibrosis patterns. METHODS AND RESULTS: A cohort of 44 genotyped patients, 33 with definite and 11 with borderline ARVC/D diagnosis, was characterized using CMR and divided into groups according to their genetic condition (desmosomal, non-desmosomal mutation, or negative). We collected information on cardiac volumes and function, as well as LGE pattern and extension. In addition, available ventricular myocardium samples from patients with pathogenic gene mutations were histopathologically analysed. Half of the patients were women, with a mean age of 41.6 ± 17.5 years. Next-generation sequencing identified a potential pathogenic mutation in 71.4% of the probands. The phenotype varied according to genetic status, with non-desmosomal male patients showing lower left ventricular (LV) systolic function. LV fibrosis was similar between groups, but distribution in non-desmosomal patients was frequently located at the posterolateral LV wall; a characteristic LV subepicardial circumferential LGE pattern was significantly associated with ARVC/D caused by desmin mutation. Histological analysis showed increased fibrillar connective tissue and intercellular space in all the samples. CONCLUSION: Desmosomal and non-desmosomal mutation carriers showed different morphofunctional features but similar LV LGE presence. DES mutation carriers can be identified by a specific and extensive LV subepicardial circumferential LGE pattern. Further studies should investigate the specificity of LGE in ARVC/D.