Sarcoidosis is a granulomatous disorder of unknown etiology characterized by noncaseating granulomas virtually in every organ and tissue. This finding represents the most important diagnostic clue to reach a correct definition of sarcoidosis, although the biopsy is invasive and has several risk procedures. Several efforts are made to suspect the diagnosis of sarcoidosis by combining noninvasive elements, in particular from imaging, though these findings are often nonspecific and reflect the wide multifactorial pathogenesis. Every effort should be made to obtain a detailed radiological picture that, if associated with a suggestive clinical picture, could avoid the need of biopsy in some specific cases. In this narrative review, we aim to describe main computed tomography (CT) features of pulmonary and abdominal sarcoidosis, by reporting strengths and limits of this technique, in particular for the identification of extrapulmonary, isolated disease.

Sarcoidosis is a rare unknown etiology multisystem inflammatory disease in which noncaseating granulomas (a collection of inflammatory cells) forms and growth in various organs, involving predominantly lungs, intrathoracic lymph node, skin, and eyes. Most commonly, affecting patients between 20 and 40 years old of age, although could be observed at any age (female predominance; rare in Asians). The areas of the body usually affected by sarcoidosis are lungs, skin, or lymph nodes; pulmonary and mediastinal involvement is seen in over 90% of patients. Less commonly eyes, liver, heart, and brain are involved. Any organ, however, can be affected. Early diagnosis of sarcoidosis can be difficult due to few signs and symptoms in its early stages, and when disease does occur, it may mimic other pathologies, and it is achieved through chest X-ray, computed tomography (CT)-high resolution CT (HRCT), gallium scans. Fluoro-deoxy glucose-positron emission tomography (FDG-PET) is another useful tool to assess the extent of disease and has a potential to evaluate the clinical management of patients responding or not to the treatment. Imaging gives, moreover, an important contribution to the evaluation of prognosis and follow-up.

Background/Objectives: Polycystic Ovary Syndrome (PCOS) is characterized by reproductive and metabolic disturbances, including insulin resistance and altered ovarian morphology. The clinical manifestations of PCOS include metabolic, reproductive, and psychological issues that negatively affect quality of life, making PCOS a significant public health concern. The relationship between follicle number and metabolic alterations across PCOS phenotypes still remains unclear. Methods: We conducted a retrospective cross-sectional study of 289 PCOS patients and 50 controls, assessing insulin resistance, lipid profiles, ovarian volume, and follicle count across phenotypes A, B, and C. We compared the three PCOS phenotypes and identified differences in follicle number, ovarian volume, insulin-related biomarkers, androgens, and LH and FSH. Results: Phenotype A exhibited higher insulin resistance and adverse lipid profiles compared to controls. The follicle number significantly discriminated between phenotypes and is associated with insulin-related alterations, one of the most clinically relevant aspects of PCOS. It is also correlated negatively with insulin resistance, most notably in phenotype B. Ovarian volume even differed among phenotypes but showed weaker metabolic associations. There is also a significant relevance of ovarian dysmorphology in PCOS and its association with hyperinsulinemia and insulin resistance. Conclusions: There is a complex interplay among the ovarian morphology, androgen and metabolic patterns in the different PCOS phenotypes. Follicle number is a relevant marker linked to insulin resistance in PCOS, particularly in phenotype B, supporting its role in clinical phenotyping and potential for guiding personalized management strategies.