Perspectives d'une conférence virtuelle de recherche en ophtalmologie dirigée par des étudiants

Implication Statement We share our experience of organizing a one-day virtual educational event, the first Canadian national student ophthalmology conference, in response to the need for ophthalmology career exploration. The conference included mentorship with residents, research presentations, keynote speakers, and more. Following the event, students expressed some improvement in accessing ophthalmology mentorship and research opportunities, along with a modest enhancement in their understanding of the specialty. We provide insights into the organizational framework and quality improvement results, aiming to assist students in adapting similar events for various specialities.Énoncé des implications de la recherche Nous partageons notre expérience portant sur l'organisation d'un événement éducatif virtuel d'une journée : la première conférence nationale canadienne des étudiants en ophtalmologie. Cette initiative a été prise en réponse au besoin d'exploration des carrières en ophtalmologie. La conférence comprenait des séances de mentorat avec des résidents, des présentations de recherche, des conférenciers d'honneur, entre autres. Suite à cet événement, les étudiants ont exprimé une amélioration dans l'accès au mentorat et aux opportunités de recherche en ophtalmologie, ainsi qu'une modeste amélioration de leur compréhension de la spécialité. Nous offrons un aperçu du cadre organisationnel et des résultats de l'amélioration de la qualité, dans le but d'aider d’autres étudiants à organiser des événements similaires pour diverses spécialités

Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or BOLDSD , is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan

Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or “BOLDSD,” is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan

Presurgical brain mapping of the language network in pediatric patients with epilepsy using resting-state fMRI

Objective: Epilepsy affects neural processing and often causes intra- or interhemispheric language reorganization, rendering localization solely based on anatomical landmarks (e.g., Broca\u27s area) unreliable. Preoperative brain mapping is necessary to weigh the risk of resection with the risk of postoperative deficit. However, the use of conventional mapping methods (e.g., somatosensory stimulation, task-based functional MRI [fMRI]) in pediatric patients is technically difficult due to low compliance and their unique neurophysiology. Resting-state fMRI (rs-fMRI), a task-free technique based on the neural activity of the brain at rest, has the potential to overcome these limitations. The authors hypothesized that language networks can be identified from rs-fMRI by applying functional connectivity analyses. Methods: Cases in which both task-based fMRI and rs-fMRI were acquired as part of the preoperative clinical protocol for epilepsy surgery were reviewed. Task-based fMRI consisted of 2 language tasks and 1 motor task. Resting-state fMRI data were acquired while the patients watched an animated movie and were analyzed using independent component analysis (i.e., data-driven method). The authors extracted language networks from rs-fMRI data by performing a similarity analysis with functionally defined language network templates via a template-matching procedure. The Dice coefficient was used to quantify the overlap. Results: Thirteen children underwent conventional task-based fMRI (e.g., verb generation, object naming), rs-fMRI, and structural imaging at 1.5T. The language components with the highest overlap with the language templates were identified for each patient. Language lateralization results from task-based fMRI and rs-fMRI mapping were comparable, with good concordance in most cases. Resting-state fMRI-derived language maps indicated that language was on the left in 4 patients (31%), on the right in 5 patients (38%), and bilateral in 4 patients (31%). In some cases, rs-fMRI indicated a more extensive language representation. Conclusions: Resting-state fMRI-derived language network data were identified at the patient level using a template- matching method. More than half of the patients in this study presented with atypical language lateralization, emphasizing the need for mapping. Overall, these data suggest that this technique may be used to preoperatively identify language networks in pediatric patients. It may also optimize presurgical planning of electrode placement and thereby guide the surgeon\u27s approach to the epileptogenic zone

Video Context Improves Performance in Identifying Operative Planes on Static Surgical Images

BACKGROUND: Correct identification of the surgical tissue planes of dissection is paramount at the operating room, and the needed skills seem to be improved with realistic dynamic models rather than mere still images. The objective is to assess the role of adding video prequels to still images taken from operations on the precision and accuracy of tissue plane identification using a validated simulation model, considering various levels of surgeons’ experience. METHODS: A prospective observational study was conducted involving 15 surgeons distributed to three equal groups, including a consultant group [C], a senior group [S], and a junior group [J]. Subjects were asked to identify and draw ideal tissue planes in 20 images selected at suitable operative moments of identification before and after showing a 10- second videoclip preceding the still image. A validated comparative metric (using a modified Hausdorff distance [%Hdu] for object matching) was used to measure the distance between lines. A precision analysis was carried out based on the difference in %Hdu between lines drawn before and after watching the videos, and between-group comparisons were analyzed using a one-way analysis of variance (ANOVA). The analysis of accuracy was done on the difference in %Hdu between lines drawn by the subjects and the ideal lines provided by an expert panel. The impact of videos on accuracy was assessed using a repeated-measures ANOVA. RESULTS: The C group showed the highest preciseness as compared to the S and J groups (mean Hdu 9.17±11.86 versus 12.1±15.5 and 20.0±18.32, respectively, p \u3c0.001) and significant differences between groups were found in 14 images (70%). Considering the expert panel as a reference, the interaction between time and experience level was significant ( F (2, 597) = 4.52, p \u3c0.001). Although the subjects of the J group were significantly less accurate than other surgeons, only this group showed significant improvements in mean %Hdu values after watching the lead-in videos ( F (1, 597) = 6.04, p = 0.014). CONCLUSIONS: Adding video context improved the ability of junior trainees to identify tissue planes of dissection. A realistic model is recommended considering experience-based differences in precision in training programs