Publications by authors named "Vasilis C Pezoulas"
Objectives: To assess if isolated mouth or eye dryness constitutes distinct clinical phenotypes in Sjögren's disease (SjD).
Methods: We analysed 1765 patients meeting the 2016 ACR-EULAR SjD criteria, followed up at four centres in Greece and Italy (Universities of Pisa, Italy, and Athens, Harokopion, and Ioannina, Greece). Patients with isolated mouth or eye dryness were identified and matched 1:2 with those experiencing both symptoms, according to age at SjD diagnosis, gender, and disease duration.
Article Synopsis
- This study investigates the link between non-Hodgkin lymphomas, specifically MALT lymphomas, and Sjögren's disease, aiming to find predictors for lymphoma development in patients with this autoimmune condition.
- Researchers conducted a case-control study with patients from three universities in Italy and Greece, comparing those with Sjögren's disease-associated MALT lymphoma to matched controls without lymphoma.
- By analyzing data at three key timepoints related to lymphomagenesis progression, the study sought to establish reliable predictors for the onset of lymphoma in patients already diagnosed with Sjögren's disease.
Objectives: Previous cohort studies have shown that around 10% of patients with primary Sjögren's syndrome (pSS) develop lymphadenopathy during their disease course. However, no studies have described their clinical phenotype. The present study aims to describe the clinical manifestations and laboratory findings of pSS patients presenting long-standing lymphadenopathy.
View Article and Find Full Text PDFObjectives: Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease characterised by oral and eye dryness. A minority of patients can present without dryness but studies on their clinico-laboratory manifestations are scarce. Our purpose was to describe the clinical phenotype of pSS patients lacking sicca symptoms.
View Article and Find Full Text PDFComparison of three U-Net family architectures for left ventricular myocardial wall automatic segmentation.
Annu Int Conf IEEE Eng Med Biol Soc
November 2021
Article Synopsis
- Left ventricular (LV) segmentation is crucial for measuring heart health metrics like volume and wall thickness, but it’s challenging due to individual differences in heart shape.
- This study evaluates three Deep Learning models from the U-Net family (custom 2-D U-Net, ResU-Net++, DenseU-Net) for accurately segmenting the LV wall in cardiac CT images of patients with hypertrophic cardiomyopathy.
- The models showed high segmentation performance, with Dice scores of 0.81, 0.82, and 0.84, indicating effective differentiating capabilities among the architectures used.
Primary Sjögren's syndrome (pSS) is a chronic, systemic autoimmune disease with diverse clinical picture and outcome. The disease affects primarily middle-aged females and involves the exocrine glands leading to dry mouth and eyes. When the disease extends beyond the exocrine glands (systemic form), certain extraglandular manifestations involving liver, kidney, lungs, peripheral nervous system and the skin may occur.
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