Pituitary neuroendocrine tumors (PitNETs) represent approximately 16% of primary brain tumors. Tumor consistency, whether soft or hard, directly affects surgical strategy, extent of resection, and risk of complications. This study aimed to perform a ...
This study aimed to determine the optimized scan time and injected activity regimen for clinical Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.A NEMA PET body phantom was...
OBJECTIVES: This study aimed to investigate the impact of primary tumor resection (PTR) on survival outcomes for patients with metastatic non-small cell neuroendocrine tumors (mNSCLC-NETs), develop a predictive model to identify which patients may be...
BACKGROUND: Small intestinal neuroendocrine neoplasms (SI-NENs), a subgroup of neuroendocrine tumors originating from neuroendocrine cells in the small intestine, present significant therapeutic challenges, and their relationship with ferroptosis-a r...
The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessment is labor-intensive, requiring the counting of 500-2,000 cells in hotspots. Digital image analysis could streamline this process, yet few comprehensi...
Neuroendocrine neoplasms (NENs) exemplify the challenges and opportunities inherent in managing rare cancers. Their rarity, biological heterogeneity, and diagnostic complexity necessitate a highly structured and multidisciplinary approach to patient ...
This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point kernels (DPKs) alongside the integration of artificial intelligence (AI) for accurate dose prediction w...
Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This study aimed to differentiate PPTs from PitNET and craniopharyngioma using a machine learning method b...
INTRODUCTION: Large Language Models (LLMs) are increasingly used in oncology, but their application in neuroendocrine neoplasms (NENs) is still unexplored.
BACKGROUND: Some nonfunctioning pituitary neuroendocrine tumor (NFPitNET) can show invasive growth, which increases the difficulty of surgery and indicates a poor prognosis. However, the molecular mechanism related to invasiveness remains to be furth...
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