Publications by authors named "F La Marca"

Background/objectives: Hidrocystomas, eccrine and apocrine, are rare cystic lesions that form benign tumors of the sweat glands. This study aimed to describe the clinical features of hidrocystomas and evaluate the role of non-invasive imaging techniques, including dermoscopy, Line-field Confocal Optical Coherence Tomography (LC-OCT), Reflectance Confocal Microscopy (RCM), and Ultra-High-Frequency Ultrasound (UHFUS), in their diagnosis.

Methods: In total, seven cases of hidrocystomas were collected from the Dermatologic Clinic of the University of Siena, Italy.

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Genital warts are the most frequent sexually transmitted disease. Their clinical diagnosis is not always easy, and invasive skin biopsies for histological examination should be performed in these cases. The aim of the study was to investigate the use of non-invasive imaging techniques for the diagnosis of genital warts and their imitators.

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Behçet's disease (BD) is a heterogeneous multifactorial autoinflammatory disease characterized by a plethora of clinical manifestations. Cutaneous lesions are considered hallmarks of the disease. However, their evolution over time and a thorough description are scarcely reported in non-endemic regions.

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Spinal instrumentation for adult spinal deformity dates back to the surgical correction of secondary complications from infectious processes, such as Pott's disease and poliomyelitis [1]. With the population aging at a longer life expectancy today, advanced degenerative spinal diseases and idiopathic scoliosis supersede as the most common causes of adult spinal deformity. Correction of the thoracolumbar malignment, specifically, has rapidly evolved with the burgeoning success of spinal instrumentation.

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Objective: Minimally invasive surgery (MIS) for spinal deformity uses interbody techniques for correction, indirect decompression, and arthrodesis. Selection criteria for choosing a particular interbody approach are lacking. The authors created the minimally invasive interbody selection algorithm (MIISA) to provide a framework for rational decision-making in MIS for deformity.

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