Publications by authors named "S Cappabianca"

Sarcopenia, a syndrome characterized by age-related loss of muscle mass and function, lacks universally accepted diagnostic criteria, particularly for its role as a prognostic factor in elderly patients with non-small-cell lung cancer (NSCLC). This study aimed to evaluate the prognostic significance of sarcopenia, assessed by psoas muscle size on baseline CT scans, in patients over 70 years of age with metastatic NSCLC. We retrospectively analyzed 85 elderly patients undergoing palliative radiation therapy between August 2022 and July 2024.

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: The aim of this study was to assess the diagnostic performance of contrast-enhanced ultrasound (CEUS) in characterizing small renal masses (SRMs) measuring less than 3 cm and in distinguishing between malignant and benign SRMs. : A retrospective study was conducted between January 2022 and January 2023 at the Radiology Department of (Anonymized data), with a total of 43 patients assessed via CT and MRI scans, which were subsequently studied by experienced radiologists who were blinded to the pathology results. The CEUS findings were then compared with histopathological examination outcomes or follow-up imaging results.

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Squamous cell carcinoma of the head and neck (SCCHN) is among the ten most common cancers worldwide, with advanced SCCHN presenting with a 5-year survival of 34% in the case of nodal involvement and 8% in the case of metastatic disease. Disease-free survival at 2 years is 67% for stage II and 33% for stage III tumors, whereas 12-30% of patients undergo distant failures after curative treatment. Previous treatments often hinder the success of salvage surgery and/or reirradiation, while the standard of care for the majority of metastatic SCCHN remains palliative chemo- and immuno-therapy, with few patients eligible for locoregional treatments.

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The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-art cancer treatment, facilitating collaborative diagnosis and management by a diverse team of specialists. Despite the clear benefits in personalized patient care and improved outcomes, the increasing burden on MTBs due to rising cancer incidence and financial constraints necessitates innovative solutions. The advent of artificial intelligence (AI) in the medical field offers a promising avenue to support clinical decision-making.

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Background: The retromolar canal (RMC) is an anatomical structure of the mandibular bone located distal to the last molar. The frequency of anatomical variation in human anatomy is approximately 30-35%. This study aimed to evaluate the prevalence of the retromolar canal in a population subjected to cone beam computed tomography (CBCT).

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