AIMC Topic: Adrenal Gland Neoplasms

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Correspondence regarding "Clinical parameters-based machine learning models for predicting intraoperative hemodynamic instability in hypertensive pheochromocytomas and paragangliomas patients".

World journal of urology
Zhao et al. present machine-learning models to predict intraoperative hemodynamic instability in hypertensive pheochromocytoma and paraganglioma surgery. The clinical motivation is sound and the reported discrimination and decision-curve metrics indi...

Robotic adrenalectomy: a comprehensive review of perioperative outcomes, comparative efficacy, and technological advancements.

Journal of robotic surgery
The adrenal glands are small but vital endocrine organs responsible for hormone production, which is essential for stress response, fluid balance, and blood pressure regulation. Adrenalectomy, the surgical removal of one or both adrenal glands, is in...

Clinical parameters-based machine learning models for predicting intraoperative hemodynamic instability in hypertensive pheochromocytomas and paragangliomas patients.

World journal of urology
PURPOSE: To create machine learning (ML) models based on inflammatory markers and coagulation parameters for predicting intraoperative hemodynamic Instability (HI) in sustained hypertensive patients with pheochromocytomas and paragangliomas (PPGLs).

Combined nomogram for differentiating adrenal pheochromocytoma from large-diameter lipid-poor adenoma using multiphase CT radiomics and clinico-radiological features.

BMC medical imaging
BACKGROUND AND OBJECTIVE: Adrenal incidentalomas (AIs) are predominantly adrenal adenomas (80%), with a smaller proportion (7%) being pheochromocytomas(PHEO). Adenomas are typically non-functional tumors managed through observation or medication, wit...

Interpretable bioinformatics approaches for pheochromocytoma bioactivity and protein interaction analysis.

Computers in biology and medicine
Pheochromocytoma (PCC) is a rare neuroendocrine tumor driven by complex molecular mechanisms, notably involving the oncogenic c-Myc/Max and c-Myc/c-Max protein complexes. Despite their pivotal role in tumor progression, the molecular interactions and...

Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.

JCO clinical cancer informatics
PURPOSE: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evalu...

Genotype-negative multiple endocrine neoplasia type 1 with prolactinoma, hyperparathyroidism, and subclinical Cushing's syndrome accompanied by hyperglycemia: a case report.

Frontiers in endocrinology
BACKGROUND: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant disorder, accompanied by multiple endocrine neoplasms of the parathyroid, pancreas, pituitary, and other neoplasms in the adrenal glands. However, in some cases, pati...

A natural language processing-informed adrenal gland incidentaloma clinic improves guideline-based care.

World journal of surgery
INTRODUCTION: Adrenal gland incidentalomas (AGIs) are found in up to 5% of cross-sectional images. However, rates of guideline-based workup for AGIs are notoriously low. We sought to determine if a natural language processing (NLP)-informed AGI clini...

Utilization of artificial intelligence in minimally invasive right adrenalectomy: recognition of anatomical landmarks with deep learning.

Acta chirurgica Belgica
BACKGROUND: The primary surgical approach for removing adrenal masses is minimally invasive adrenalectomy. Recognition of anatomical landmarks during surgery is critical for minimizing complications. Artificial intelligence-based tools can be utilize...