Introduction: The biokinetics of radioiodine (RAI) in thyroid cancer patients are complex. This study aims to develop a practical approach for assessing RAI biokinetics to predict patient discharge time and estimate radiation exposure to caregivers. Methods: We retrospectively reviewed data from patients with differentiated thyroid carcinoma undergoing RAI treatment. Serial radiation dose rates were dynamically collected during hospitalization and fitted to a biexponential model to assess the biokinetic features: RAI uptake fraction of thyroid tissue (F_t) and effective half-life of extra-thyroid tissue (T_et). Correlations with ^99mTc thyroid uptake ratio (TcUR), radiation retention ratio (RR), renal function, and body mass index (BMI) were analyzed. Results: Thirty-five patients were enrolled. The derived F_t was 0.08 ± 0.06 and T_et was 7.57 ± 1.45 h. Pearson’s correlation analysis revealed a significant association between F_t and both TcUR and RR (p < 0.05), while T_et correlated with renal function and BMI (p < 0.05). Conclusion: This novel and practical method assessing RAI biokinetics demonstrates consistency with other parameters and related studies, enhancing the model reliability. It shows promise in predicting an appropriate discharge time and estimating radiation exposure to caregivers, allowing for modifications to radiation protection precautions to follow ALARA principle and minimize the potential risks from radiation exposure.

Chemotherapy-induced cognitive impairment (CICI) is a frequently reported complication in lung cancer patients, yet the underlying cerebral metabolic changes remain poorly characterized. This study aimed to evaluate chemotherapy-related alterations in brain glucose metabolism in patients with non-small cell lung cancer (NSCLC) using a longitudinal, within-subject voxel-based ¹⁸F-FDG PET approach. Forty NSCLC patients who underwent both pre- and post-chemotherapy FDG PET imaging were retrospectively enrolled. Voxel-wise comparisons were performed using SPM12 to identify regional metabolic changes. Patients were stratified based on chemotherapy intensity (standard: ≥4 cycles; short-course: 1-3 cycles) and recovery interval (short: <6 months; long: ≥6 months), with subgroup and interaction analyses conducted accordingly. Compared with baseline, post-treatment scans revealed regional metabolic reductions, predominantly in the right thalamus, left frontal lobe, and bilateral temporal regions. Patients receiving standard chemotherapy exhibited more extensive metabolic reductions than those receiving short-course treatment, particularly in the bilateral temporal and cingulate regions. Furthermore, patients scanned within six months post-chemotherapy showed more pronounced reductions than those with longer recovery intervals, suggesting a potential trend of metabolic recovery over time. In contrast, patients with limited initial metabolic changes (i.e., short-course group) exhibited minimal changes across intervals. This within-subject FDG PET study provides longitudinal evidence that chemotherapy independently contributes to brain metabolic alterations in NSCLC patients, predominantly involving the frontal, temporal, and limbic regions. These findings highlight vulnerable neural substrates and underscore the clinical value of functional neuroimaging in cancer survivorship research.