Publications by authors named "L Regli"
Objective: To scrutinize and compare the accuracy of measurements obtained from photogrammetric models against direct measurements taken on dry skulls, with the aim to verify the feasibility of photogrammetry for quantitative analysis in microsurgical neuroanatomy.
Methods: Two dry human skulls were used. Each was scanned using the dual camera system of a smartphone The selected photos were separately processed two different software to create 3D models.
Cerebral cavernous malformations are benign vascular anomalies of the central nervous system (CNS). The clinical presentation of a cavernoma depends on its location. The majority of patients with cavernomas are asymptomatic.
View Article and Find Full Text PDFBackground And Purpose: Identifying and assessing hemodynamic and flow status in patients with symptomatic internal carotid artery (ICA) occlusion is crucial for evaluating recurrent stroke risk. The aim of this study was to analyze the correlation between two quantitative imaging modalities: (1) blood oxygenation level-dependent (BOLD) cerebrovascular reactivity (CVR) and (2) quantitative magnetic resonance angiography (qMRA) with non-invasive optimal vessel analysis (NOVA), measuring volume flow rate (VFR). Comparing these modalities is relevant for assessing collateral circulation and hemodynamic impairment.
View Article and Find Full Text PDFBackground: Gliomas, the most frequent malignant primary brain tumors, lack curative treatments. Understanding glioma-specific molecular alterations is crucial to develop novel therapies. Among them, the biological consequences of the isocitrate dehydrogenase 1 gene mutation ( ) remain inconclusive despite its early occurrence and widespread expression.
View Article and Find Full Text PDFArticle Synopsis
- - The study aimed to create a machine-learning algorithm to automatically identify cerebral arteries and unruptured intracranial aneurysms using a dataset of manually segmented MRI-TOF scans.
- - The nnUNet algorithm was trained on 62 MRITOF scans, showing strong performance metrics with a median Dice Similarity Coefficient of 0.86 and an 80% sensitivity for detecting aneurysms.
- - The results indicate that the algorithm can effectively and quickly extract relevant anatomical features, with future plans to enhance its training dataset and apply it to 3D imaging tools for better treatment predictions.