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Clinical, biochemical, molecular and radiomic approach in the search for prognostic factors for the management of adrenal incidentalomas.

Grant number: 23/17774-0
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2024
Effective date (End): March 31, 2025
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Margaret de Castro
Grantee:Guilherme Henrique Pereira dos Santos
Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

The project addresses adrenal incidentalomas, lesions discovered incidentally during abdominal exams, commonly detected in assessments for lower back pain and motor vehicle accidents. The prevalence, especially in the elderly, has increased due to population aging and advancements in medical technologies. These lesions, classified as non-functioning benign, functioning benign, and malignant, require systematization in investigation to optimize costs and avoid unnecessary procedures.Clinical assessment covers signs of neoplasms and hormonal imbalances. Tests, such as dexamethasone suppression, are used to diagnose syndromes like MACS. Complications associated with MACS include cardiometabolic problems. The study emphasizes the overlap of clinical features between MACS and Cushing's Syndrome.Screening for hyperaldosteronism and pheochromocytoma, through biochemical and imaging tests, is crucial. Contrast-free computed tomography (CT) is the primary imaging modality. Lesions with attenuation coefficient >10 HU in CT indicate the need for further investigation.Imaging diagnosis includes evaluating the size and attenuation of the lesion. Contrast-enhanced CT washout and magnetic resonance imaging (MRI), which detects microscopic fat, complement the investigation. The study highlights challenges in differentiating between benign and malignant lesions.TP53, a tumor suppressor gene, and the p.R337H mutation are relevant in adrenocortical carcinomas. Molecular studies are necessary to assess the prevalence of this mutation in patients with adrenal incidentalomas in Brazil.The heterogeneity of the lesions motivates the use of machine learning and radiomics to identify hidden patterns. The study aims to create a more effective patient care flow using artificial intelligence parameters.Objectives include evaluating clinical, laboratory, molecular, and radiological characteristics of patients with adrenal incidentalomas, creating a more effective care flow with artificial intelligence, and analyzing TP53 and the p.R337H mutation.The retrospective study will evaluate records of 200 patients with adrenal incidentalomas, considering demographic, clinical, biochemical, and imaging characteristics. Management and follow-up will be analyzed, and sequencing of TP53 exon 10 may be conducted.Statistical analysis will be performed, and data management will follow ethical standards. The project will contribute to understanding the heterogeneity of these lesions and improving clinical and diagnostic approaches.

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