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Purpose: Patients with hematological malignancies are at an increased risk of severe infection with coronavirus disease 2019 (COVID-19). However, developing an adequate immune response after vaccination is difficult, especially in patients with lymphoid neoplasms. Since the long-term effects of the BNT162b2 vaccine are unclear, the humoral immune response 5 months after the two vaccinations in patients with hematological disorders was analyzed., Materials and Methods: Samples were collected from 96 patients vaccinated twice with BNT162b2 and treated with at least one line of an antitumor or immunosuppressive drug in our hospital from November 2021 to February 2022. Serum anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) spike (S) antibody titers were analyzed. Patients were age- and sex-matched using propensity matching and compared with a healthy control group. Patients with serum anti-SARS-CoV-2 S antibodies were defined as 'responder' if >50 U/mL. The patients had B-cell non-Hodgkin lymphoma (B-NHL), multiple myeloma, chronic myeloid leukemia, etc., Results: Patients had significantly low antibody levels (median, 55.3 U/mL vs. 809.8 U/mL; p<0.001) and a significantly low response rate (p<0.001). Multivariate analysis showed that patients with B-NHL, aged >72 years, were associated with a low response to vaccination. There were no significant differences between patients with chronic myeloid leukemia and healthy controls., Conclusion: Our study shows that patients with hematological disorders are at risk of developing severe COVID-19 infections because of low responsiveness to vaccination. Moreover, the rate of antibody positivity differed between the disease groups. Further studies are warranted to determine an appropriate preventive method for these patients, especially those with B-NHL., Competing Interests: No potential conflict of interest relevant to this article was reported., (© Korean Vaccine Society.)

In recent years, medical disciplines have moved closer together and rigid borders have been increasingly dissolved. The synergetic advantage of combining multiple disciplines is particularly important for radiology, nuclear medicine, and pathology to perform integrative diagnostics. In this review, we discuss how medical subdisciplines can be reintegrated in the future using state-of-the-art methods of digitization, data science, and machine learning. Integration of methods is made possible by the digitalization of radiological and nuclear medical images, as well as pathological images. 3D histology can become a valuable tool, not only for integration into radiological images but also for the visualization of cellular interactions, the so-called connectomes. In human pathology, it has recently become possible to image and calculate the movements and contacts of immunostained cells in fresh tissue explants. Recording the movement of a living cell is proving to be informative and makes it possible to study dynamic connectomes in the diagnosis of lymphoid tissue. By applying computational methods including data science and machine learning, new perspectives for analyzing and understanding diseases become possible., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)