Haemophagocytic lymphohistiocytosis and liver failure-induced massive hyperferritinaemia in a male COVID-19 patient

Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography

OBJECTIVES

This study aims to develop a deep learning algorithm, Pneumonia-Plus, based on computed tomography (CT) images for accurate classification of bacterial, fungal, and viral pneumonia.

METHODS

A total of 2763 participants with chest CT images and definite pathogen diagnosis were included to train and validate an algorithm. Pneumonia-Plus was prospectively tested on a nonoverlapping dataset of 173 patients. The algorithm's performance in classifying three types of pneumonia was compared to that of three radiologists using the McNemar test to verify its clinical usefulness.

RESULTS

Among the 173 patients, area under the curve (AUC) values for viral, fungal, and bacterial pneumonia were 0.816, 0.715, and 0.934, respectively. Viral pneumonia was accurately classified with sensitivity, specificity, and accuracy of 0.847, 0.919, and 0.873. Three radiologists also showed good consistency with Pneumonia-Plus. The AUC values of bacterial, fungal, and viral pneumonia were 0.480, 0.541, and 0.580 (radiologist 1: 3-year experience); 0.637, 0.693, and 0.730 (radiologist 2: 7-year experience); and 0.734, 0.757, and 0.847 (radiologist 3: 12-year experience), respectively. The McNemar test results for sensitivity showed that the diagnostic performance of the algorithm was significantly better than that of radiologist 1 and radiologist 2 (p < 0.05) in differentiating bacterial and viral pneumonia. Radiologist 3 had a higher diagnostic accuracy than the algorithm.

CONCLUSIONS

The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist and reduce the risk of misdiagnosis. The Pneumonia-Plus is important for appropriate treatment and avoiding the use of unnecessary antibiotics, and provide timely information to guide clinical decision-making and improve patient outcomes.

CLINICAL RELEVANCE STATEMENT

Pneumonia-Plus algorithm could assist in the accurate classification of pneumonia based on CT images, which has great clinical value in avoiding the use of unnecessary antibiotics, and providing timely information to guide clinical decision-making and improve patient outcomes.

KEY POINTS

• The Pneumonia-Plus algorithm trained from data collected from multiple centers can accurately identify bacterial, fungal, and viral pneumonia. • The Pneumonia-Plus algorithm was found to have better sensitivity in classifying viral and bacterial pneumonia in comparison to radiologist 1 (5-year experience) and radiologist 2 (7-year experience). • The Pneumonia-Plus algorithm is used to differentiate between bacterial, fungal, and viral pneumonia, which has reached the level of an attending radiologist.

COVID-19 vaccination-related hemophagocytic lymphohistiocytosis presenting as acute liver failure

Acute liver failure following COVID-19 infection and/or vaccination is very rare and can be secondary to hemophagocytic lymphohistiocytosis (HLH). Liver injury in such cases appears to be extrinsic and thus treatment hinges on prompt diagnosis and reversal of the primary disease. We describe a patient who developed acute liver failure secondary to HLH after receiving a second dose of the Pfizer COVID-19 vaccine. Persistently elevated liver function tests, fevers, and cytopenia following COVID-19 vaccination should prompt clinicians to calculate an H-score to evaluate for the presence of HLH.

Vascular Damage, Thromboinflammation, Plasmablast Activation, T-Cell Dysregulation and Pathological Histiocytic Response in Pulmonary Draining Lymph Nodes of COVID-19

Although initial immunophenotypical studies on peripheral blood and bronchoalveolar lavage samples have provided a glimpse into the immunopathology of COVID-19, analyses of pulmonary draining lymph nodes are currently scarce. 22 lethal COVID-19 cases and 28 controls were enrolled in this study. Pulmonary draining lymph nodes (mediastinal, tracheal, peribronchial) were collected at autopsy. Control lymph nodes were selected from a range of histomorphological sequelae [unremarkable histology, infectious mononucleosis, follicular hyperplasia, non-SARS related HLH, extrafollicular plasmablast activation, non-SARS related diffuse alveolar damage (DAD), pneumonia]. Samples were mounted on a tissue microarray and underwent immunohistochemical staining for a selection of immunological markers and in-situ hybridization for Epstein Barr Virus (EBV) and SARS-CoV-2. Gene expression profiling was performed using the HTG EdgeSeq Immune Response Panel. Characteristic patterns of a dysregulated immune response were detected in COVID-19: 1. An accumulation of extrafollicular plasmablasts with a relative paucity or depletion of germinal centers. 2. Evidence of T-cell dysregulation demonstrated by immunohistochemical paucity of FOXP3+, Tbet+ and LEF1+ positive T-cells and a downregulation of key genes responsible for T-cell crosstalk, maturation and migration as well as a reactivation of herpes viruses in 6 COVID-19 lymph nodes (EBV, HSV). 3. Macrophage activation by a M2-polarized, CD163+ phenotype and increased incidence of hemophagocytic activity. 4. Microvascular dysfunction, evidenced by an upregulation of hemostatic (CD36, PROCR, VWF) and proangiogenic (FLT1, TEK) genes and an increase of fibrin microthrombi and CD105+ microvessels. Taken together, these findings imply widespread dysregulation of both innate and adoptive pathways with concordant microvascular dysfunction in severe COVID-19.

Histomorphological patterns of regional lymph nodes in COVID-19 lungs

BACKGROUND

A dysregulated immune response is considered one of the major factors leading to severe COVID-19. Previously described mechanisms include the development of a cytokine storm, missing immunoglobulin class switch, antibody-mediated enhancement, and aberrant antigen presentation.

OBJECTIVES

To understand the heterogeneity of immune response in COVID-19, a thorough investigation of histomorphological patterns in regional lymph nodes was performed.

MATERIALS AND METHODS

Lymph nodes from the cervical, mediastinal, and hilar regions were extracted from autopsies of patients with lethal COVID-19 (n = 20). Histomorphological characteristics, SARS-CoV‑2 qRT-PCR, and gene expression profiling on common genes involved in immunologic response were analyzed.

RESULTS

Lymph nodes displayed moderate to severe capillary stasis and edema, an increased presence of extrafollicular plasmablasts, mild to moderate plasmacytosis, a dominant population of CD8⁺ T‑cells, and CD11c/CD68⁺ histiocytosis with hemophagocytic activity. Out of 20 cases, 18 presented with hypoplastic or missing germinal centers with a decrease of follicular dendritic cells and follicular T‑helper cells. A positive viral load was detected by qRT-PCR in 14 of 20 cases, yet immunohistochemistry for SARS-CoV-2 N-antigen revealed positivity in sinus histiocytes of only one case. Gene expression analysis revealed an increased expression of STAT1, CD163, granzyme B, CD8A, MZB1, and PAK1, as well as CXCL9.

CONCLUSIONS

Taken together, our findings imply a dysregulated immune response in lethal COVID-19. The absence/hypoplasia of germinal centers and increased presence of plasmablasts implies a transient B‑cell response, implying an impaired development of long-term immunity against SARS-CoV‑2 in such occasions.

[Histomorphological patterns of regional lymph nodes in COVID-19 lungs]

Hintergrund

Eine dysregulierte Immunantwort, z. B. in der Form eines Zytokinsturmes, einer Störung des Immunglobulinklassenwechsels, eines sog. antikörpervermitteltem Enhancements oder einer aberranten Antigenpräsentation wurde bereits in schweren Krankheitsverläufen von COVID-19 beschrieben.

Ziel der Arbeit

Zur Charakterisierung der COVID-19-Immunantwort wurde die Histomorphologie der Lymphknoten des pulmonalen Abflussgebietes untersucht.

Material und Methoden

Regionale Lymphknoten des pulmonalen Abflussgebiets wurden bei COVID-19-Autopsien asserviert (n = 20). Deren Histomorphologie, SARS-CoV-2-qRT-PCR sowie Genexpressionsanalysen von gängigen Genen der Immunantwort wurden berücksichtigt.

Ergebnisse

Histologisch zeigten sich ein mäßig- bis schwergradiges Ödem mit Kapillarostase, eine erhöhte Anzahl von extrafollikulären Plasmablasten, milde bis mäßige Plasmazytose, vermehrte CD8⁺-T-Zellen und CD11c/CD68⁺-Histiozyten mit Hämophagozytoseaktivität. Von 20 Fällen wiesen 18 hypoplastische oder fehlende Keimzentren sowie eine Verminderung der follikulären dendritischen Zellen und follikulären T‑Helferzellen auf. In 14 von 20 Fällen war der qRT-PCR-Nachweis von SARS-CoV‑2 positiv, jedoch zeigte sich nur bei einem einzigen Fall eine immunhistochemische Positivität für SARS-CoV-2-N-Antigene in Sinushistiozyten. In Genexpressionsanalysen war eine erhöhte Expression von STAT1, CD163, Granzym B, CD8A, MZB1 und PAK1, neben CXCL9 zu beobachten.

Diskussion

Die Befunde in den Lymphknoten deuten auf eine dysregulierte Immunantwort bei schweren COVID-19-Krankheitsverläufen hin. Insbesondere impliziert das Ausbleiben der Keimzentrumsreaktion und die vermehrte Präsenz von Plasmablasten eine nur transiente B‑Zellreaktion, welche die Entwicklung einer Langzeitimmunität infrage stellt.