Rhinosporidiosis is one of the granulomatous diseases endemic in Asia, Africa, and Europe, with Southern India and Sri Lanka having the greatest prevalence rates. It is typically understood to affect the upper respiratory system. Involvement of the lungs beyond the trachea is infrequent as compared to the upper respiratory tract. We revealed an uncommon case of disseminated rhinosporidiosis in a diabetic patient, who initially presented with shortness of breath associated with cough and fever. Two months prior to these symptoms, he was having oral ulcer and dysphagia and, subsequently, loss of weight. Chest radiograph and CT thorax revealed military nodules with multiple suppurative neck and mediastinal lymphadenopathy and bilateral adrenal lesions. He was initially investigated for tuberculosis, metastatic malignancy, or lymphangitic carcinomatosis before a biopsy revealed Rhinosporidiosis. Hence, histopathological or laboratory evidence is frequently crucial to back up imaging concerns so the appropriate treatment can be given.

Background: Tuberculosis (TB) and sarcoidosis are two common granulomatous diseases involving lymph nodes. Differential diagnosis is not always easy because pathogen demonstration in tuberculosis is not always possible and both diseases share clinical, radiological and histological patterns. The aim of our study was to identify factors associated with each diagnosis and set up a predictive score for TB. Methods: All cases of lymph node tuberculosis and sarcoidosis were retrospectively reviewed. Demographics, clinical characteristics, laboratory and imaging data, and microbiological and histological results were collected and compared. Results: Among 441 patients screened, 192 patients were included in the final analysis. The multivariate analysis showed that weight loss, necrotic granuloma, normal serum lysozyme level and hypergammaglobulinemia were significantly associated with TB. A risk score of TB was built based on these variables and was able to discriminate TB versus sarcoidosis with an AUC of 0.85 (95% CI: 0.79-0.91). Using the Youden\'s J statistic, its most discriminant value (-0.36) was associated with a sensitivity of 80% and a specificity of 75%. Conclusions: We developed a score based on weight loss, necrotic granuloma, normal serum lysozyme level and hypergammaglobulinemia with an excellent capacity to discriminate TB versus sarcoidosis. This score needs still to be validated in a multicentric prospective study.

Granulomatosis with polyangiitis is a rare disease with involvement of multiple organ system. It classically affects the upper respiratory tract, lower respiratory tract and kidneys. 90% of patients present with upper respiratory diseases like rhinosinusitis, nasal polyposis, nasal septal perforation, serous otitis media, impaired hearing and stridor due to subglottic stenosis. Disease manifests in two forms as limited disease i.e. without renal involvement and generalized disease i.e. with renal involvement. It needs to be differentiated from chronic granulomatous diseases like tuberculosis and delay in the treatment should be prevented. Here we present a case with disease limited to Nose and Paranasal sinuses.

BACKGROUND: We aimed to develop a diagnostic deep learning model using contrast-enhanced CT images and to investigate whether cervical lymphadenopathies can be diagnosed with these deep learning methods without radiologist interpretations and histopathological examinations.
METHODS: A total of 400 patients who underwent surgery for lymphadenopathy in the neck between 2010 and 2022 were retrospectively analyzed. They were examined in four groups of 100 patients: the granulomatous diseases group, the lymphoma group, the squamous cell tumor group, and the reactive hyperplasia group. The diagnoses of the patients were confirmed histopathologically. Two CT images from all the patients in each group were used in the study. The CT images were classified using ResNet50, NASNetMobile, and DenseNet121 architecture input.
RESULTS: The classification accuracies obtained with ResNet50, DenseNet121, and NASNetMobile were 92.5%, 90.62, and 87.5, respectively.
CONCLUSIONS: Deep learning is a useful diagnostic tool in diagnosing cervical lymphadenopathy. In the near future, many diseases could be diagnosed with deep learning models without radiologist interpretations and invasive examinations such as histopathological examinations. However, further studies with much larger case series are needed to develop accurate deep-learning models.

Sarcoidosis is a systemic inflammatory disorder characterized by tissue infiltration due to mononuclear phagocytes and lymphocytes and associated noncaseating granuloma formation. Pulmonary sarcoidosis (PS) shares a number of clinical, radiological, and histopathological characteristics with that of pulmonary tuberculosis (PTB). Due to this, clinicians face issues in differentiating between PS and PTB in a substantial number of cases. There is a lack of any specific biomarker that can diagnose PS distinctively from PTB. We compared T-cell-based signature cytokines in patients with PS and PTB. In this study, we proposed a serum biomarker panel consisting of cytokines from cells: T helper (Th) 1 [interferon-gamma (IFN-γ); tumor necrosis factor-alpha (TNF-α)], Th9 [interleukin (IL)-9], Th17 [IL-17], and T regulatory (Treg) [IL-10; transforming growth factor-beta (TGF-β)]. We performed the principal component analysis that demonstrated that our serum cytokine panel has a significant predictive ability to differentiate PS from PTB. Our results could aid clinicians to improve the diagnostic workflow for patients with PS in TB endemic settings where the diagnosis between PS and PTB is often ambiguous.

The distinction between tuberculosis and sarcoidosis presents sometimes a clinical challenge. Their sequential occurrence in the same patient is uncommon. We present the case of a 42-year-old female with a proven diagnosis of tuberculous lymphadenitis who has developed successively nasal tuberculosis and pulmonary sarcoidosis respectively after 10 and 14 months of antituberculosis treatment. The patient presented with bilateral cervical lymphadenopathy. Tuberculin skin test was negative. Chest radiography was normal. An excision biopsy was taken and histopathological examination established tuberculosis diagnosis. Therapy with antituberculosis drugs was started, and cervical lymphadenopathy showed progressive resolution. Subsequently, nearly 10 months after, the patient developed new cervical lymphadenopathies and nasal obstruction. Tuberculosis of the nasal mucosa was confirmed by biopsy. Antituberclosis bitherapy was enhanced by ofloxacin and ethambutol. Thoracic CT scan showed several nodular elements in both lungs, with bilateral enlarged mediastinal adenopathy. Bronchoalveolar lavage showed a lymphocytic alveolitis with a CD4/CD8 ratio of 5, consistent with the diagnosis of pulmonary sarcoidosis. Corticosteroid treatment, in form of oral prednisolone was introduced, 3 months after sarcoidosis diagnosis have been setteled; because of pulmonary fibrosis noticed on thoracic CT. Systemic corticotherapy was continued for a further period of 3 years, until all the lesions cleared out. The present case emphasizes the possible association between tuberculosis and sarcoidosis.

A patient was referred to the oral medicine department with redness and swelling of the lips and cheek, and an intra-oral lesion. Biopsy and laboratory investigations suggested a diagnosis of sarcoidosis. In this study we discuss oral findings associated with sarcoidosis.

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Rationale: The Sarcoidosis Diagnostic Score (SDS) has been established to quantitate the clinical features consistent with sarcoidosis in a monocentric study. Objectives: We aimed to confirm the diagnostic value of SDS in a large, multicontinental study and to assess the utility of SDS in differentiating sarcoidosis from alternative diagnoses, including infectious and noninfectious granulomatous diseases. Methods: We included patients with biopsy-confirmed sarcoidosis at nine centers across the world. Patients without sarcoidosis seen at the same sites served as control patients. Using a modified World Association of Sarcoidosis and Other Granulomatous Disorders organ assessment instrument, we scored all patients for the presence of granuloma on biopsy, highly probable symptoms, and least probable symptoms for each area. Two sarcoidosis scores were generated: SDS Biopsy (with biopsy) and SDS Clinical (without biopsy). SDS Clinical and Biopsy were calculated for all patients. We calculated and compared the area under the curve (AUC) for SDS Clinical and Biopsy according to different diagnosis scenarios. Results: A total of 1,041 patients with sarcoidosis and 1,035 without sarcoidosis were included. The results for SDS Clinical (AUC, 0.888; 95% confidence interval [CI], 0.874-0.902) and SDS Biopsy (AUC, 0.979; 95% CI, 0.973-0.985) according to AUC were good to excellent for differentiating sarcoidosis from alternative diagnosis. SDS Clinical was less discriminatory in males (P = 0.01) and in high tuberculosis prevalence centers (P < 0.001). However, SDS Clinical (AUC, 0.684; 95% CI, 0.602-0.766) and SDS Biopsy (AUC, 0.754; 95% CI, 0.673-0.835) were not sufficiently discriminative for noninfectious granulomatous diseases, but both SDSs could differentiate sarcoidosis from infectious granulomatous diseases. Algorithms were proposed for the SDS Clinical and SDS Biopsy to assist the clinician in the diagnostic process, and cutoff values were proposed for the SDS Clinical and SDS Biopsy, allowing the diagnosis of sarcoidosis to be safely confirmed or rejected in most cases except for noninfectious granulomatous disease. Conclusions: This multicontinental study confirms that both SDS Clinical and SDS Biopsy have good to excellent performance in discriminating sarcoidosis from alternative diagnoses. Differences in the AUC were seen for high tuberculosis prevalence versus low tuberculosis prevalence centers and for males versus females. Both SDSs had good discriminatory function for infectious granulomatous disease but failed in cases of noninfectious granulomatous disease such as berylliosis.

There is a need to further characterize the antibody response to vimentin in relation to its possible involvement in pathogenicity of sarcoidosis and other lung disorders.
OBJECTIVE: We investigated serum samples from patients with sarcoidosis, healthy controls and controls with other non-infectious lung diseases., to evaluate levels and frequency of these antibodies.
METHODS: A retrospective-prospective comparative study was performed in the years 2015-2019. Sera from 93 patients with sarcoidosis, 55 patients with non-infectious lung diseases and 40 healthy subjects was examined for presence of autoantibodies to mutated citrullinated vimentin (anti-MCV). Patients with elevated anti-MCV levels were tested for antibodies to a cyclic citrullinated peptide (anti-CCP) and citrullinated vimentin (anti-Sa). In all cases ELISA assays was used. The results were considered statistically significant at p-value less than 0.05.
RESULTS: The high concentrations of anti-MCV antibodies were more frequent in patients with sarcoidosis (40.9% of the cases, 38/93), compared to the control groups (23.6% and 25.0% of cases, respectively). In sarcoidosis, clinical symptoms similar to the autoimmune pathology were described. A moderate positive correlation between the anti-MCV and anti-Sa antibodies (r = 0.66) was found in 13 patients with sarcoidosis. There was no significant difference between the levels of the anti-MCV and the anti-CCP in patients with non-infectious lung diseases and the healthy control group.
CONCLUSIONS: Antibodies to citrullinated cyclic peptides are not significant in the pathogenesis of sarcoidosis and other investigated pulmonary diseases (COPD, granulomatosis with polyangiitis, alveolitis) and based on their low concentration, it can be assumed that citrullination and modification of vimentin is not a key factor in the development of an autoimmune response in patients with sarcoidosis.