Patients’ Perceptions of Memory Functioning Before and After Surgical Intervention to Treat Medically Refractory Epilepsy.

Purpose:One risk associated with epilepsy surgery is memory loss, but perhaps more important is how patients perceive changes in their memories. This longitudinal study evaluated changes in memory self-reports and investigated how self-reports relate to changes on objective memory measures in temporal or extratemporal epilepsy patients who underwent surgery. Methods: Objective memory (Wechsler Memory Scale–Revised) and subjective memory self-reports (Memory Assessment Clinics Self-Rating Scale) were individually assessed for 136 patients ∼6 months before and 6 months after surgery. A measure of depressive affect (Beck Depression Inventory–2nd Edition) was used to control variance attributable to emotional distress. Results: Despite a lack of significant correlational relationships between objective and subjective memory for the entire sample, significant correlations between objective memory scores and self-reports did emerge for a subset of patients who evidenced memory decline. Differences also were found in the subjective memory ratings of temporal lobe versus extratemporal patients. Temporal lobe patients rated their memories more negatively than did extratemporal patients and were more likely to report significant improvements in their memory after surgery. Conclusions: In general, patients were not accurate when rating their memories compared to other adults. However, patients with significant declines in their memories were sensitive to actual changes in their memories over time relative to their own personal baselines

A deep learning pipeline for automatized assessment of spinal MRI

Background This work evaluates the feasibility, development, and validation of a machine learning pipeline that includes all tasks from MRI input to the segmentation and grading of the intervertebral discs in the lumbar spine, offering multiple different radiological gradings of degeneration as quantitative objective output. Methods The pipelines’ performance was analysed on 1′000 T2-weighted sagittal MRI. Binary outputs were assessed with the harmonic mean of precision and recall (DSC) and the area under the precision-recall curve (AUC-PR). Multi-class output scores were averaged and complemented by the Top-2 categorical accuracy. The processing success rate was evaluated on 10′053 unlabelled MRI scans of lumbar spines. Results The midsagittal plane selection achieved an DSC of 74,80% ± 2,99% and an AUC-PR score of 81.71% ± 2.72% (96.91% Top-2 categorical accuracy). The segmentation network obtained a DSC of 91.80% ± 0.44%. The Pfirrmann grading of intervertebral discs in the midsagittal plane was classified with a DSC of 64.08% ± 3.29% and an AUC-PR score of 68.25% ± 6.00% (91.65% Top-2 categorical accuracy). Disc herniations achieved a DSC of 61.57% ± 3.39% and an AUC-PR score of 66.86% ± 5.03%. The cranial endplate defects reached a DSC of 49.76% ± 3.45% and 52.36% ± 1.98% AUC-PR (slightly superior predictions of caudal endplate defect). The binary classifications for the caudal Schmorl's nodes obtained a DSC of 91.58% ± 2.25% with an AUC-PR metric of 96.69% ± 1.58% (similar performance for cranial Schmorl's nodes). Spondylolisthesis was classified with a DSC of 89.03% ± 2.42% and an AUC-PR score of 95.98% ± 1.82%. Annular Fissures were predicted with a DSC of 78.09% ± 7.21% and an AUC-PR score of 86.31% ± 7.45%. Intervertebral disc classifications in the parasagittal plane achieved an equivalent performance. The pipeline successfully processed 98.53% of the provided sagittal MRI scans. Conclusions The present deep learning framework has the potential to aid the quantitative evaluation of spinal MRI for an array of clinically established grading systems. + Graphical abstrac

A Comparative Study of Social Cognition in Epilepsy, Brain Injury, and Parkinson's Disease

The brain regions involved in social cognition and the regulation of social behavior form a widely distributed cortico‐subcortical network. Therefore, many neurological disorders could affect social cognition and behavior. A persistent lack of valid tests and a rigid neuropsychological focus on language, attention, executive function, and memory have contributed to a long‐standing neglect of social cognition in clinical diagnostics, although the DSM‐5 recognizes it as one of the six core dimensions in neurocognitive disorders. To assess for the first time the diagnostic yield of a comprehensive social cognition battery (Networks of Emotion Processing [NEmo]), we administered several emotion recognition and theory of mind tests to three incidental clinical samples with different neurological conditions: temporal lobe epilepsy (n = 30), acquired brain injury (n = 24), Parkinson's disease (n = 19), and a healthy control group (n = 67). A multivariate analysis of covariance was performed to test the effect of group on subscales of the NEmo test battery, controlling for age and performance IQ. The results showed statistically significant differences between clinical groups and healthy controls. No differences were found for gender and lateralization of the predominant lesion side. In our incidental samples, 86% of individuals with temporal lobe epilepsy, 57% of individuals with acquired brain lesion, and 14% of individuals with Parkinson's disease underperformed on tests of social cognition compared with controls. These findings suggest a differential impact of neurological disorders on the risk of impaired social cognition and highlight the need to consider social cognition in diagnostics, counselling, therapy, and rehabilitation

Anatomical landmark detection on bi-planar radiographs for predicting spinopelvic parameters

INTRODUCTION: Accurate landmark detection is essential for precise analysis of anatomical structures, supporting diagnosis, treatment planning, and monitoring in patients with spinal deformities. Conventional methods rely on laborious landmark identification by medical experts, which motivates automation. The proposed deep learning pipeline processes bi-planar radiographs to determine spinopelvic parameters and Cobb angles without manual supervision. METHODS: The dataset used for training and evaluation consisted of 555 bi-planar radiographs from un-instrumented patients, which were manually annotated by medical professionals. The pipeline performed a pre-processing step to determine regions of interest, including the cervical spine, thoracolumbar spine, sacrum, and pelvis. For each ROI, a segmentation network was trained to identify vertebral bodies and pelvic landmarks. The U-Net architecture was trained on 455 bi-planar radiographs using binary cross-entropy loss. The post-processing algorithm determined spinal alignment and angular parameters based on the segmentation output. We evaluated the pipeline on a test set of 100 previously unseen bi-planar radiographs, using the mean absolute difference between annotated and predicted landmarks as the performance metric. The spinopelvic parameter predictions of the pipeline were compared to the measurements of two experienced medical professionals using intraclass correlation coefficient (ICC) and mean absolute deviation (MAD). RESULTS: The pipeline was able to successfully predict the Cobb angles in 61% of all test cases and achieved mean absolute differences of 3.3 degrees (3.6 degrees ) and averaged ICC of 0.88. For thoracic kyphosis, lumbar lordosis, sagittal vertical axis, sacral slope, pelvic tilt, and pelvic incidence, the pipeline produced reasonable outputs in 69%, 58%, 86%, 85%, 84%, and 84% of the cases. The MAD was 5.6 degrees (7.8 degrees ), 4.7 degrees (4.3 degrees ), 2.8 mm (3.0 mm), 4.5 degrees (7.2 degrees ), 1.8 degrees (1.8 degrees ), and 5.3 degrees (7.7 degrees ), while the ICC was measured at 0.69, 0.82, 0.99, 0.61, 0.96, and 0.70, respectively. CONCLUSION: Despite limitations in patients with severe pathologies and high BMI, the pipeline automatically predicted coronal and sagittal spinopelvic parameters, which has the potential to simplify clinical routines and large-scale retrospective data analysis

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning

PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol but is usually acquired for preoperative planning purposes only. Additionally, it is costly, exposes the patients to high doses of radiation and is acquired in a non-weight-bearing position. METHODS: In this study, we develop a deep-learning based pipeline to facilitate 3D preoperative planning for high tibial osteotomies, based on 3D models reconstructed from low-dose biplanar standing EOS radiographs. Using digitally reconstructed radiographs, we train networks to localize the clinically required landmarks, separate the two legs in the sagittal radiograph and finally reconstruct the 3D bone model. Finally, we evaluate the accuracy of the reconstructed 3D models for the particular application case of preoperative planning, with the aim of eliminating the need for a CT scan in specific cases, such as high tibial osteotomies. RESULTS: The mean Dice coefficients for the tibial reconstructions were 0.92 and 0.89 for the right and left tibia, respectively. The reconstructed models were successfully used for clinical-grade preoperative planning in a real patient series of 52 cases. The mean differences to ground truth values for mechanical axis and tibial slope were 0.52 degrees and 4.33 degrees , respectively. CONCLUSIONS: We contribute a novel framework for the 2D-3D reconstruction of bone models from biplanar standing EOS radiographs and successfully use them in automated clinical-grade preoperative planning of high tibial osteotomies. However, achieving precise reconstruction and automated measurement of tibial slope remains a significant challenge

Carbamazepine reduces memory induced activation of mesial temporal lobe structures: a pharmacological fMRI-study

BACKGROUND AND PURPOSE: It is not known whether carbamazepine (CBZ; a drug widely used in neurology and psychiatry) influences the blood oxygenation level dependent (BOLD) contrast changes induced by neuronal activation and measured by functional MRI (fMRI). We aimed to investigate the influence of CBZ on memory induced activation of the mesial temporal lobes in patients with symptomatic temporal lobe epilepsy (TLE). MATERIAL AND METHODS: Twenty-one individual patients with refractory symptomatic TLE with different CBZ serum levels and 20 healthy controls were studied using BOLD fMRI. Mesial temporal lobe (MTL) activation was induced by a task that is based on the retrieval of individually familiar visuo-spatial knowledge. The extent of significant MTL fMRI activation was measured and correlated with the CBZ serum level. RESULTS: In TLE patients, the extent of significant fMRI activation over both MTL was negatively correlated to the CBZ serum level (Spearman r = -0.654, P < 0.001). Activation over the supposedly normal MTL, i.e. contralateral to the seizure onset of TLE patients, was smaller than the averaged MTL activation in healthy controls (P < 0.005). Age, duration of epilepsy, side of seizure onset, and intelligence were not correlated to the extent of the significant BOLD-response over both MTL in patients with TLE. CONCLUSIONS: In TLE patients, carbamazepine reduces the fMRI-detectable changes within the mesial temporal lobes as induced by effortful memory retrieval. FMRI appears to be suitable to study the effects of chronic drug treatment in patients with epilepsy

Neuropsychologische Begutachtungen in der Schweiz – aktuelle Beiträge

Die vorliegende Publikation befasst sich mit den Aufgaben und der Rolle der Neuropsychologie als gutachtliche Disziplin. Beleuchtet werden unter anderem formale und inhaltliche Aspekte eines neuropsychologischen Gutachtens, das sogenannte «informierte Einverständnis», Instrumente der Performanz- und Beschwerdenvalidierung, Verfahren der Konsistenz- und Plausibilitätsprüfung, konzeptuelle Unterschiede zwischen der Verdeutlichung, der Aggravation und der Simulation, die Problematik des «Coachings», die Einschätzung der Arbeitsfähigkeit und des Integritätsschadens aus neuropsychologischer Sicht sowie Aspekte der Fahreignung. Die Publikation soll klare Handlungsempfehlungen – mit dem Ziel einer möglichst einheitlichen Vorgehensweise sowohl bei der Durchführung neuropsychologischer Begutachtungen wie auch im Rahmen der Berichterstattung – vermitteln. Die folgenden Ausführungen beziehen sich auf das Schweizer Rechtssystem. Folglich sind diese nicht einfach auf den Rechtsrahmen anderer Länder übertragbar

Diagnostic accuracy of functional magnetic resonance imaging, Wada test, magnetoencephalography, and functional transcranial Doppler sonography for memory and language outcome after epilepsy surgery: A systematic review

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