Preliminary clinical application of multimodal imaging combined with frameless robotic stereotactic biopsy in the diagnosis of primary central nervous system lymphoma.

Objective: To evaluate the clinical application of multimodal imaging combined with frameless robotic stereotactic biopsy in the diagnosis of primary central nervous system lymphoma (PCNSL). Methods: We retrospectively reviewed the clinical data of 8 patients who were considered suspected cases of PCNSL by multimodal imaging techniques. The final pathologic diagnosis were determined by the frameless robotic stereotactic biopsy. The postoperative related complications and pathological results were analyzed. Results: All patients underwent biopsies under general anesthesia with an average surgery time of 29.5 ± 4.5 min. The final pathological diagnostic accordant rate with the preoperative ones was 100%, and the pathologic examination of our patients showed features of diffuse large B-cell lymphoma. During the surgery, one patient suffered intratumoral hemorrhage without leading to serious cerebral edema, and conservative treatment was given. There was no death occurring during the study, and there were no significant differences in the Karnofsky Performance Scale Scores of all patients before and after surgery. Finally, they were transferred to the hematology department for standardized chemoradiotherapy according to the pathological results of PCNSL. Conclusion: This study shows that it may play a vital role in the early diagnosis of PCNSL with the technique of multimodal imaging. The technique of frameless robotic stereotactic biopsy for obtaining the pathology outcomes in suspected PCNSL patients has the advantages of safety, efficiency, and minimally invasiveness.

Predictive Factors and Nomogram to Evaluate the Risk of Symptomatic Intracerebral Hemorrhage for Stroke Patients Receiving Thrombectomy.

BACKGROUND: Symptomatic intracerebral hemorrhage (sICH) is a severe complication of mechanical thrombectomy (MT). This study is to identify predictive factors and create a nomogram to evaluate the risk of sICH after MT treatment. METHODS: We conducted a retrospective analysis on 127 consecutive stroke patients treated by MT therapy. We evaluated multiple predictive factors for the incidence of sICH using univariate and multivariate logistic regressions. Based on the identified and other possible factors, a nomogram was constructed to predict the risk of sICH. RESULTS: We identified several predictive factors for sICH in the univariate analysis, including thrombectomy maneuvers >3 (odds ratio [OR], 4.42; 95% confidence interval [CI], 1.25-15.6; P = 0.0211), admission blood glucose (OR, 1.29; 95% CI, 1.13-1.48; P = 0.0002), diabetes mellitus (OR, 4.44; 95% CI, 1.64-12.0; P = 0.0033), and admission National Institutes of Health Stroke Scale (NIHSS) score (OR, 1.05; 95% CI, 1.01-1.10; P = 0.0263). The multivariate analysis showed that admission NIHSS score and blood glucose significantly affected the prognosis. Moreover, the proposed nomogram showed reliable identification ability with an area under the curve of 0.82 (95% CI, 0.71-0.93), specificity of 0.745, sensitivity of 0.762, accuracy of 0.748, and negative predictive value of 0.941. CONCLUSIONS: Our study identified the admission NIHSS score and admission blood glucose level as predictive factors for sICH. Moreover, the proposed nomogram based on possible factors showed reliable predictive performance in evaluating the risk of sICH.