Background: The integration of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT-4, is transforming healthcare. ChatGPT’s potential to assist in decision-making for complex cases, such as spinal metastasis treatment, is promising but widely untested. Especially in cancer patients who develop spinal metastases, precise and personalized treatment is essential. This study examines ChatGPT-4’s performance in treatment planning for spinal metastasis cases compared to experienced spine surgeons. Materials and Methods: Five spine metastasis cases were randomly selected from recent literature. Consequently, five spine surgeons and ChatGPT-4 were tasked with providing treatment recommendations for each case in a standardized manner. Responses were analyzed for frequency distribution, agreement, and subjective rater opinions. Results: ChatGPT’s treatment recommendations aligned with the majority of human raters in 73% of treatment choices, with moderate to substantial agreement on systemic therapy, pain management, and supportive care. However, ChatGPT’s recommendations tended towards generalized statements, with raters noting its generalized answers. Agreement among raters improved in sensitivity analyses excluding ChatGPT, particularly for controversial areas like surgical intervention and palliative care. Conclusions: ChatGPT shows potential in aligning with experienced surgeons on certain treatment aspects of spinal metastasis. However, its generalized approach highlights limitations, suggesting that training with specific clinical guidelines could potentially enhance its utility in complex case management. Further studies are necessary to refine AI applications in personalized healthcare decision-making.

Background: Hemodynamics during the growth process of cerebral aneurysms are incompletely understood. We developed a novel fluid–structure interaction analysis method for the identification of relevant scenarios of aneurysm onset. Method: This method integrates both fluid dynamics and structural mechanics, as well as their mutual interaction, for a comprehensive analysis. Patients with a single unruptured cerebral aneurysm were included. Results: Overall, three scenarios were identified. In scenario A, wall shear stress (WSS) was low, and the oscillatory shear index (OSI) was high in large areas within the region of aneurysm onset (RAO). In scenario B, the quantities indicated a reversed behavior, where WSS was high and OSI was low. In the last scenario C, a behavior in-between was found, with scenarios A and B coexisting simultaneously in the RAO. Structural mechanics demonstrated a similar but independent trend. Further, we analyzed the change in hemodynamics between the onset and a fully developed aneurysm. While scenarios A and C remained unchanged during aneurysm growth, 47% of aneurysms in scenario B changed into scenario A and 20% into scenario C. Conclusions: In conclusion, these findings suggest that WSS and the OSI are reciprocally regulated, and both low and high WSS/OSI conditions can lead to aneurysm onset.

The flow behavior of fluids can be characterized by rheology and is especially used in the field of polymeric materials. This study focused on characterizing cerebrospinal fluid (CSF) of patients who developed hydrocephalus after subarachnoid hemorrhage (SAH) with rheology. Samples were drawn from an external ventricular drainage (EVD) at four pre-defined time points after the initial hemorrhage. The CSF samples were analyzed using a rotational rheometer with a double gap geometry. In addition to the characterization of viscoelastic parameters, the cumulative storage factor was calculated to determine the interactions in the fluid. In order to investigate the temperature dependence of the CSF properties, the oscillatory measurements were implemented at certain temperatures that simulated specific conditions, such as 5 °C, at which temperature the CSF samples were stored; 35 °C for hypothermic conditions; 37 °C for physiologic conditions; and 40 °C for elevated body temperature. The overall goal was to evaluate whether rheology-based parameters may help in the prediction of shunt dependence for post-hemorrhagic hydrocephalus patients. For this aim, rheological parameters were correlated to certain laboratory parameters, such as erythrocyte and leukocyte count, glucose, lactate, and total protein concentration.