Search

Selective amygdalohippocampectomy (SelAH) is one of the most common surgical treatments for mesial temporal sclerosis. Microsurgical approaches are associated with the risk of cognitive and visual deficits due to damage to the cortex and white matter (WM) pathways. Our objective is to test the feasibility of an endoscopic approach through the anterior middle temporal gyrus (aMTG) to perform a SelAH.Virtual simulation with MRI scans of ten patients (20 hemispheres) was used to identify the endoscopic trajectory through the aMTG. A cadaveric study was performed on 22 specimens using a temporal craniotomy. The anterior part of the temporal horn was accessed using a tubular retractor through the aMTG after performing a 1.5 cm corticectomy at 1.5 cm posterior to the temporal pole. Then, an endoscope was introduced. SeIAH was performed in each specimen. The specimens underwent neuronavigation-assisted endoscopic SeIAH to confirm our surgical trajectory. WM dissection using Klingler's technique was performed on five specimens to assess WM integrity.This approach allowed the identification of collateral eminence, lateral ventricular sulcus, choroid plexus, inferior choroidal point, amygdala, hippocampus, and fimbria. SelAH was successfully performed on all specimens, and CT neuronavigation confirmed the planned trajectory. WM dissection confirmed the integrity of language pathways and optic radiations.Endoscopic SelAH through the aMTG can be successfully performed with a corticectomy of 15 mm, presenting a reduced risk of vascular injury and damage to WM pathways. This could potentially help to reduce cognitive and visual deficits associated with SelAH.

Standard DSC-PWI analyses are based on concrete parameters and values, but an approach that contemplates all points in the time-intensity curves and all voxels in the region-of-interest may provide improved information, and more generalizable models. Therefore, a method of DSC-PWI analysis by means of normalized time-intensity curves point-by-point and voxel-by-voxel is constructed, and its feasibility and performance are tested in presurgical discrimination of glioblastoma and metastasis.In this retrospective study, patients with histologically confirmed glioblastoma or solitary-brain-metastases and presurgical-MR with DSC-PWI (August 2007-March 2020) were retrieved. The enhancing tumor and immediate peritumoral region were segmented on CE-T1wi and coregistered to DSC-PWI. Time-intensity curves of the segmentations were normalized to normal-appearing white matter. For each participant, average and all-voxel-matrix of normalized-curves were obtained. The 10 best discriminatory time-points between each type of tumor were selected. Then, an intensity-histogram analysis on each of these 10 time-points allowed the selection of the best discriminatory voxel-percentile for each. Separate classifier models were trained for enhancing tumor and peritumoral region using binary logistic regressions.A total of 428 patients (321 glioblastomas, 107 metastases) fulfilled the inclusion criteria (256 men; mean age, 60 years; range, 20-86 years). Satisfactory results were obtained to segregate glioblastoma and metastases in training and test sets with AUCs 0.71-0.83, independent accuracies 65-79%, and combined accuracies up to 81-88%.This proof-of-concept study presents a different perspective on brain MR DSC-PWI evaluation by the inclusion of all time-points of the curves and all voxels of segmentations to generate robust diagnostic models of special interest in heterogeneous diseases and populations. The method allows satisfactory presurgical segregation of glioblastoma and metastases.• An original approach to brain MR DSC-PWI analysis, based on a point-by-point and voxel-by-voxel assessment of normalized time-intensity curves, is presented. • The method intends to extract optimized information from MR DSC-PWI sequences by impeding the potential loss of information that may represent the standard evaluation of single concrete perfusion parameters (cerebral blood volume, percentage of signal recovery, or peak height) and values (mean, maximum, or minimum). • The presented approach may be of special interest in technically heterogeneous samples, and intrinsically heterogeneous diseases. Its application enables satisfactory presurgical differentiation of GB and metastases, a usual but difficult diagnostic challenge for neuroradiologist with vital implications in patient management.

Becoming aware of one's own states is a fundamental aspect for self-monitoring, allowing us to adjust our beliefs of the world to the changing context. Previous evidence points out to the key role of the anterior insular cortex (aIC) in evaluating the consequences of our own actions, especially whenever an error has occurred. In the present study, we propose a new multimodal protocol combining electrical stimulation mapping (ESM) and functional magnetic resonance imaging (fMRI) to explore the functional role of the aIC for self-monitoring in patients undergoing awake brain surgery. Our results using a modified version of the Stroop task tackling metacognitive abilities revealed new direct evidence of the involvement of the aIC in monitoring our performance, showing increased difficulties in detecting action-outcome mismatches when stimulating a cortical site located at the most posterior part of the aIC as well as significant BOLD activations at this region during outcome incongruences for self-made actions. Based on these preliminary results, we highlight the importance of assessing the aIC's functioning during tumor resection involving this region to evaluate metacognitive awareness of the self in patients undergoing awake brain surgery. In a similar vein, a better understanding of the aIC's role during self-monitoring may help shed light on action/outcome processing abnormalities reported in several neuropsychiatric disorders such as schizophrenia, anosognosia for hemiplegia or major depression.