Drawing as a Way of Knowing : How a Mapping Model Assists Preoperative Evaluation of Patients with Thyroid Carcinoma.
Marco BiffoniGiorgio GraniRossella MelcarneValerio GeronziFabrizio ConsortiGiuseppe De RuggieriAlessia GalvanoMaryam Hosseinpour RazlighiEva IannuzziTal Deborah EngelDaniela PaceCira Rosaria Tiziana di GioiaMarco BoniardiCosimo DuranteLaura GiacomelliPublished in: Journal of clinical medicine (2024)
Background : Effective pre-surgical planning is crucial for achieving successful outcomes in endocrine surgery: it is essential to provide patients with a personalized plan to minimize operative and postoperative risks. Methods: Preoperative lymph node (LN) mapping is a structured high-resolution ultrasonography examination performed in the presence of two endocrinologists and the operating surgeon before intervention to produce a reliable "anatomical guide". Our aim was to propose a preoperative complete model that is non-invasive, avoids overdiagnosis of thyroid microcarcinomas, and reduces medical expenses. Results: The use of 'preoperative echography mapping' has been shown to be successful, particularly in patients with suspected or confirmed neoplastic malignancy. Regarding prognosis, positive outcomes have been observed both post-surgery and in terms of recurrence rates. We collected data on parameters such as biological sex, age, BMI, and results from cytologic tests performed with needle aspiration, and examined whether these parameters predict tumor malignancy or aggressiveness, calculated using a multivariate analysis (MVA). Conclusions: A standard multidisciplinary approach for evaluating neck lymph nodes pre-operation has proven to be an improved diagnostic and preoperative tool.
Keyphrases
- lymph node
- high resolution
- patients undergoing
- minimally invasive
- healthcare
- coronary artery bypass
- high density
- ultrasound guided
- magnetic resonance imaging
- sentinel lymph node
- body mass index
- mass spectrometry
- radiation therapy
- electronic health record
- adipose tissue
- insulin resistance
- coronary artery disease
- machine learning
- quality improvement
- risk assessment
- climate change
- tandem mass spectrometry