Background: The incidences of premature coronary heart disease present a rising trend worldwide. The possible risk factors that may predict the incidence of repeat percutaneous coronary intervention (PCI) in premature acute coronary syndrome (ACS) remains unclear. Methods: A total of 203 patients ≤45 years with ACS from Chinese PLA General Hospital who have undergone angiography twice were included in this report. Data were collected from medical records of patients during hospitalization. Baseline characteristics which have significant differences in the univariate analysis were enrolled into the multiple logistic regression analysis. According to the odds ratio (OR) of these variables, different values were assigned to build a risk model to predict the possible risk of the premature ACS patients undergoing repeat PCI. Results: Of the 203 young patients, 88 patients (43.3%) underwent repeat PCI. The intermit time (OR 1.002, (95% CI [1.001–1.002])), diastolic blood pressure of second procedure (OR 0.967, (95% CI [0.938–0.996])), stent diameter (OR 0.352, (95% CI [0.148–0.840])), HbA1C of the first procedure (OR 1.835, (95% CI [1.358–2.479])), and Troponin T of the second procedure (OR 1.24, (95% CI [0.981–1.489])) were significantly associated with the incidence of repeat PCI in patients with premature ACS. An aggregate score between 0 and 6 was calculated based on these cutpoints. Conclusion: For young patients with premature ACS, risk of undergoing repeat PCI was high. HbA1C was a significant, independent predictor for the incidence of repeat revascularization, and weighed more than traditional lipid profile. The glucose metabolism and disorders in patients with premature ACS should be routinely screened.

Addressing conventional neurosurgical navigation systems’ high costs and complexity, this study explores the feasibility and accuracy of a simplified, cost-effective mixed reality navigation (MRN) system based on a laser crosshair simulator (LCS). A new automatic registration method was developed, featuring coplanar laser emitters and a recognizable target pattern. The workflow was integrated into Microsoft’s HoloLens-2 for practical application. The study assessed the system’s precision by utilizing life-sized 3D-printed head phantoms based on computed tomography (CT) or magnetic resonance imaging (MRI) data from 19 patients (female/male: 7/12, average age: 54.4 ± 18.5 years) with intracranial lesions. Six to seven CT/MRI-visible scalp markers were used as reference points per case. The LCS-MRN’s accuracy was evaluated through landmark-based and lesion-based analyses, using metrics such as target registration error (TRE) and Dice similarity coefficient (DSC). The system demonstrated immersive capabilities for observing intracranial structures across all cases. Analysis of 124 landmarks showed a TRE of 3.0 ± 0.5 mm, consistent across various surgical positions. The DSC of 0.83 ± 0.12 correlated significantly with lesion volume (Spearman rho = 0.813, p < 0.001). Therefore, the LCS-MRN system is a viable tool for neurosurgical planning, highlighting its low user dependency, cost-efficiency, and accuracy, with prospects for future clinical application enhancements.

Background: Glioblastoma (GBM), the most malignant form of gliomas, is a relatively common primary brain tumor in adults. Preoperative identification of isocitrate dehydrogenase 1 (IDH1) mutations in GBM is of critical prognostic importance. The aim of the present study was to explore the feasibility and diagnostic performance of basic patient information combined with conventional magnetic resonance imaging (MRI) findings for determination of the IDH1 status (mutant vs wild type) in patients with GBM. Methods: From January 1, 2016 to December 31, 2017, a consecutive series of 50 patients with GBM was retrospectively collected. The patients were divided into two group according to their IDH1 mutation status. Basic information and MRI features were analyzed for the establishment of a diagnostic prediction model using logistic regression. A receiver operating characteristic curve was used to evaluate the diagnostic performance. Results: Patients with IDH1-mutant tumors were younger than those with IDH1-wild type tumors, and exhibited a larger tumor volume. The diagnostic predictive model established by combining age and the tumor size exhibited a sensitivity and specificity of 70% and 93%, respectively. The area under the curve was 0.88, which indicated high diagnostic performance. Conclusion: Patient age and tumor volume can be used as indicators of IDH1 mutation status in patients with GBM, with high diagnostic performance for simple evaluations in clinical practice. The combined use of these two indicators can further enhance the diagnostic specificity.

Mixed Reality Navigation (MRN) is pivotal in augmented reality-assisted intelligent neurosurgical interventions. However, existing MRN registration methods face challenges in concurrently achieving low user dependency, high accuracy, and clinical applicability. This study proposes and evaluates a novel registration method based on a laser crosshair simulator, evaluating its feasibility and accuracy. A novel registration method employing a laser crosshair simulator was introduced, designed to replicate the scanner frame’s position on the patient. The system autonomously calculates the transformation, mapping coordinates from the tracking space to the reference image space. A mathematical model and workflow for registration were designed, and a Universal Windows Platform (UWP) application was developed on HoloLens-2. Finally, a head phantom was used to measure the system’s target registration error (TRE). The proposed method was successfully implemented, obviating the need for user interactions with virtual objects during the registration process. Regarding accuracy, the average deviation was 3.7 ± 1.7 mm. This method shows encouraging results in efficiency and intuitiveness and marks a valuable advancement in low-cost, easy-to-use MRN systems. The potential for enhancing accuracy and adaptability in intervention procedures positions this approach as promising for improving surgical outcomes.