Spatiotemporal Dynamics and Prognostic Value of the 18F-FDG PET Neuro-Metabolic Network

This observational clinical study aims to investigate the spatiotemporal changes of the 18F-FDG PET neuro-metabolic network in patients with lung, gastrointestinal, or endocrine diseases. The study seeks to clarify : 1. the dynamic metabolic alterations of specific brain regions, 2. the spatiotemporal associations between cerebral metabolism and systemic disease progression, 3. the prognostic value of neuro-metabolic parameters. Participants will undergo 18F-FDG PET/CT imaging, clinical assessments, and longitudinal follow-up to evaluate outcomes such as tumor recurrence, metastasis, and survival.

The brain-organ axis, including the brain-lung, brain-heart, brain-gut, and brain-endocrine pathways, has emerged as a critical research field for systemic disease pathophysiology. 18F-FDG PET/CT provides a unique noninvasive tool to quantify neural metabolic activity and to reveal central-peripheral interactions in cross-axis disorders. Previous studies have demonstrated that chronic hypoxia in lung diseases can lead to global cerebral metabolic suppression, with prominent hypometabolism in the frontal cortex and hippocampus, directly correlating with cognitive decline. Similarly, brain-heart axis dysfunction in heart failure is characterized by hypothalamic-amygdala hypermetabolism and hippocampal hypometabolism, linked to higher rehospitalization risk. Inflammatory bowel disease demonstrates abnormal hypermetabolism in the insula and anterior cingulate cortex, correlated with intestinal mucosal damage. Moreover, 18F-FDG PET can sensitively detect pituitary microadenomas and predict postoperative recurrence in Cushing's disease. Despite these advances, three major limitations remain: 1. most studies focus on single organ axes, lacking integrative dynamic network analyses across multiple axes; 2. conventional static SUV metrics cannot capture the spatiotemporal evolution of metabolic pathways, while advanced dynamic PET approaches remain underutilized in clinical practice; 3. prognostic models often rely on single-modality parameters, ignoring the added value of multimodal integration, as shown by recent evidence combining DWI-derived ADC values with PET metabolic parameters to enhance prognostic accuracy in NSCLC. Therefore, this prospective cohort study will systematically map neuro-metabolic remodeling patterns of brain-organ axis diseases using 18F-FDG PET imaging, and establish metabolism-based prognostic stratification models. Objectives: To characterize the dynamic cerebral metabolic alterations in patients with lung, gastrointestinal, or endocrine diseases. To explore the spatiotemporal associations between specific brain region metabolism and disease progression. To assess the prognostic value of cerebral metabolic parameters for clinical outcomes. Primary Outcomes: The primary outcomes include tumor recurrence, metastasis, and death. All events will be adjudicated by at least two independent clinicians based on comprehensive clinical information and professional expertise. The number and timing of outcome events will be recorded at the end of follow-up for each participant.