Intraoperative augmented reality fiber tractography complements cortical and subcortical mapping

Augmented reality (AR) has been found to be advantageous in enhancing visualization of complex neuroanatomy intraoperatively and in neurosurgical education. Another key tool that allows neurosurgeons to have enhanced visualization, namely of white matter tracts, is diffusion tensor imaging (DTI) that is processed with high-definition fiber tractography (HDFT). There remains an enduring challenge in the structural–functional correlation of white matter tracts that centers on the difficulty in clearly assigning function to any given fiber tract when evaluating them through separated as opposed to integrated modalities. Combining the technologies of AR with fiber tractography shows promise in helping to fill in this gap between structural–functional correlation of white matter tracts. This novel study demonstrates through a series of three cases of awake craniotomies for glioma resections a technique that allows the first and most direct evidence of fiber tract stimulation and assignment of function or deficit in vivo through the intraoperative, real-time fusion of electrical cortical stimulation, AR, and HDFT. This novel technique has qualitatively shown to be helpful in guiding intraoperative decision making on extent of resection of gliomas. Future studies could focus on larger, prospective cohorts of glioma patients who undergo this methodology and further correlate the post-operative imaging results to patient functional outcomes

The use of Mixed Reality for the treatment planning of unruptured intracranial aneurysms

Background: A thorough comprehension of topographic neuroanatomy is paramount in neurosurgery. In recent years, great attention has been raised towards extended reality, which comprises virtual, augmented, and mixed reality (MR) as an aid for surgery. In this paper, we describe our preliminary experience with the use of a new MR platform, aiming to assess its reliability and usefulness in the planning of surgical treatment of unruptured intracranial aneurysms. Methods: We prospectively enrolled 5 patients, harboring a total of 8 intracranial unruptured aneurysms, undergoing elective surgical clipping. A wearable mixed-reality device (HoloLens) was used to display and interact with a holographic model during surgical planning. Afterward, a total of 10 among surgeons and residents filled in a 5-point Likert-scale evaluation questionnaire. Results: According to the participants' feedback, the main MR platform advantages were considered the educational value, its utility during patients positioning and craniotomy planning, as well as the anatomical and imaging interpretation during surgery. The graphic performance was also deemed very satisfactory. On the other hand, the device was evaluated as not easy to use and pretty uncomfortable when worn for a long time. Conclusions: We demonstrated that MR could play important role in planning the surgical treatment of intracranial aneurysms by enhancing the visualization and understanding of the patient-specific anatomy

Plasma 24-metabolite Panel Predicts Preclinical Transition to Clinical Stages of Alzheimer's Disease.

We recently documented plasma lipid dysregulation in preclinical late-onset Alzheimer's disease (LOAD). A 10 plasma lipid panel, predicted phenoconversion and provided 90% sensitivity and 85% specificity in differentiating an at-risk group from those that would remain cognitively intact. Despite these encouraging results, low positive predictive values limit the clinical usefulness of this panel as a screening tool in subjects aged 70-80 years or younger. In this report, we re-examine our metabolomic data, analyzing baseline plasma specimens from our group of phenoconverters (n = 28) and a matched set of cognitively normal subjects (n = 73), and discover and internally validate a panel of 24 plasma metabolites. The new panel provides a classifier with receiver operating characteristic area under the curve for the discovery and internal validation cohort of 1.0 and 0.995 (95% confidence intervals of 1.0-1.0, and 0.981-1.0), respectively. Twenty-two of the 24 metabolites were significantly dysregulated lipids. While positive and negative predictive values were improved compared to our 10-lipid panel, low positive predictive values provide a reality check on the utility of such biomarkers in this age group (or younger). Through inclusion of additional significantly dysregulated analyte species, our new biomarker panel provides greater accuracy in our cohort but remains limited by predictive power. Unfortunately, the novel metabolite panel alone may not provide improvement in counseling and management of at-risk individuals but may further improve selection of subjects for LOAD secondary prevention trials. We expect that external validation will remain challenging due to our stringent study design, especially compared with more diverse subject cohorts. We do anticipate, however, external validation of reduced plasma lipid species as a predictor of phenoconversion to either prodromal or manifest LOAD