Exploring the fragility of meta-analyses in ophthalmology: a systematic review.

OBJECTIVE: The fragility index (FI) of a meta-analysis evaluates the extent that the statistical significance can be changed by modifying the event status of individuals from included trials. Understanding the FI improves the interpretation of the results of meta-analyses and can help to inform changes to clinical practice. This review determined the fragility of ophthalmology-related meta-analyses. METHODS: Meta-analyses of randomized controlled trials with binary outcomes published in a journal classified as 'Ophthalmology' according to the Journal Citation Report or an Ophthalmology-related Cochrane Review were included. An iterative process determined the FI of each meta-analysis. Multivariable linear regression modeling evaluated the relationship between the FI and potential predictive factors in statistically significant and non-significant meta-analyses. RESULTS: 175 meta-analyses were included. The median FI was 6 (Q1-Q3: 3-12). This meant that moving 6 outcomes from one group to another would reverse the study's findings. The FI was 1 for 18 (10.2%) of the included meta-analyses and was ≤5 for 75 (42.4%) of the included meta-analyses. The number of events (p < 0.001) and the p-value (p < 0.001) were the best predictors of the FI in both significant and non-significant meta-analyses. CONCLUSION: The statistical significance of meta-analyses in ophthalmology often hinges on the outcome of a few patients. The number of events and the p-value are the most important factors in determining the fragility of the evidence. The FI is an easily interpretable measure that can supplement the reader's understanding of the strength of the evidence being presented. PROSPERO REGISTRATION: CRD42022377589.

Association of pre-residency publications with research productivity in residency, fellowship, and academic career choice among Canadian ophthalmologists.

OBJECTIVE: This study aimed to assess whether the research output of medical students who matched into a Canadian ophthalmology residency program influences their subsequent research productivity during residency, decision to pursue a fellowship, or engagement in academic practice. DESIGN: Retrospective database review. PARTICIPANTS: A total of 369 trainees commencing ophthalmology residency from 2004 to 2015 at 15 residency programs. METHODS: Each trainee's publication record was queried in Scopus before and after the date they started residency. Multiple public sources were searched to identify fellowship placement and the type of subsequent practice (i.e., academic or community). Predictors of research productivity during residency, fellowship, and practice setting were assessed using multivariable regression analyses. RESULTS: Trainees with pre-residency publications (n = 187) demonstrated significantly higher research productivity during residency than those without pre-residency publications (n = 182), with a mean of 5.17 ± 5.97 versus 1.60 ± 2.38 publications on any topic (p < 0.001). Pre-residency research output was a predictor of research productivity during residency (relative risk = 1.17; 95% CI, 1.09-1.27; p < 0.001), pursuing fellowship (odds ratio, 2.9; 95% CI, 1.74-4.83), and an academic career (odds ratio = 1.85; 95% CI, 1.07-3.2). CONCLUSION: Pre-residency research output is a significant predictor of research productivity during residency and subsequent career choices, suggesting that pre-residency publishing reflects a propensity toward an academic trajectory. Residency publication count moderates this association, underscoring the role of the residency program environment in fostering research productivity. Addressing barriers such as mentorship, funding, and curriculum may be key to incentivizing trainees to pursue academic medicine.

Perspectives on a virtual student-led research conference in ophthalmology.

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.

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.

Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.

PURPOSE: This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and their predictive accuracies. We also evaluate the integration of bioinformatics with AI tools. METHODS: This scoping review was conducted across five electronic databases including EMBASE, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics were included. RESULTS: A total of 10,262 articles were retrieved from all databases and 177 studies met the inclusion criteria. The most commonly studied ocular diseases were diabetic eye diseases, with 50 papers (28%), while glaucoma was explored in 25 studies (14%), age-related macular degeneration in 20 (11%), dry eye disease in 10 (6%), and uveitis in 9 (5%). Supervised learning was used in 91 papers (51%), unsupervised AI in 83 (46%), and bioinformatics in 85 (48%). Ninety-eight papers (55%) used more than one class of AI (e.g. > 1 of supervised, unsupervised, bioinformatics, or statistical techniques), while 79 (45%) used only one. Supervised learning techniques were often used to predict disease status or prognosis, and demonstrated strong accuracy. Unsupervised AI algorithms were used to bolster the accuracy of other algorithms, identify molecularly distinct subgroups, or cluster cases into distinct subgroups that are useful for prediction of the disease course. Finally, bioinformatic tools were used to translate complex biomarker profiles or findings into interpretable data. CONCLUSION: AI analysis of biofluid markers displayed diagnostic accuracy, provided insight into mechanisms of molecular etiologies, and had the ability to provide individualized targeted therapeutic treatment for patients. Given the progression of AI towards use in both research and the clinic, ophthalmologists should be broadly aware of the commonly used algorithms and their applications. Future research may be aimed at validating algorithms and integrating them in clinical practice.

Strabismus outcomes in pediatric patients undergoing disconnective hemispheric surgery for intractable epilepsy: a systematic review.

BACKGROUND: Children undergoing hemispheric surgery for intractable seizures are susceptible to visual complications including strabismus. This systematic review aims to investigate the rates and characteristics of strabismus development after hemispheric surgery and evaluate clinical implications for ophthalmologic care. METHODS: A systematic search of MEDLINE, EMBASE, Cochrane, PsychINFO, and Web of Science databases was performed from database inception to May 2022. Included articles referred to strabismus outcomes in pediatric populations after hemispherectomy or hemispherotomy. Reviews and non-English-language publications were excluded. Risk of bias was assessed using Joanna Briggs Institute critical appraisal tools. Demographic data and characteristics of strabismus were extracted and tabulated. RESULTS: Of 41 articles identified, 10 studies consisting of 384 pediatric participants (48% females) and age at surgery between 6 months and 16 years were included. Preoperative strabismus rates ranged between 3% and 56%, whereas postoperative rates ranged between 38% and 100%. With respect to the site of hemispheric surgery, contralateral exodeviation was the most common (16%-67%; n = 7) and then ipsilateral exodeviation (16%-56%; n = 2), whereas ipsilateral esodeviation was infrequent (4%-9%; n = 3). CONCLUSIONS: Contralateral exotropia and ipsilateral esotropia may occur after hemispheric surgery and may have the potential to be field expanding. Concerns regarding negative social reactions should be balanced with the risk of visual field reduction and (or) diplopia by strabismus surgery. Higher-quality articles with large, homogeneous, and well-described populations (i.e., complete pre- and postoperative ophthalmologic assessments) are required to establish the risks and rates of strabismus development after hemispheric surgery.

Evaluation of commitment to equity, diversity, and inclusion on Canadian ophthalmology residency program websites.

OBJECTIVE: Program websites play a crucial role in providing information to prospective residency applicants. This research assesses the extent to which Canadian ophthalmology residency programs demonstrate their commitment to equity, diversity, and inclusion (EDI) through their websites and identifies areas for potential improvement. METHODS: A cross-sectional analysis of websites affiliated with 15 accredited Canadian ophthalmology residency training programs was performed. A score was assigned based on 16 EDI elements derived from recent literature. The relationship between program website EDI elements with language, geography, and regional population diversity was explored. RESULTS: Of the 15 Canadian ophthalmology residency programs, 12 (80%) met at least 1 of 16 EDI elements, with a mean program score of 2.4 (SD = 1.92). The program that attained the highest score met 7 of 16 EDI elements. Anglophone programs had a higher mean score (2.92; SD = 1.78) when compared with their Francophone counterparts (0.33; SD = 0.58; p = 0.023). No significant difference was found between programs in western, central, and eastern Canada (p = 0.86). The regional minorities proportion associated with each program was not found to influence scores (p = 0.088). CONCLUSIONS: EDI elements were seldom addressed on Canadian ophthalmology residency program affiliated websites. We propose recommendations in 4 domains: showcasing team diversity, clear discourse in recruitment, inclusive resources, and program organization. Improving EDI visibility on program websites through revisions of existing websites or through creation of new promotional websites may foster recruitment of a diverse resident body.

Research productivity of first-year Canadian ophthalmology residents: a 12-year trend.

OBJECTIVE: Research experience is one criterion of the selection process for applicants to residency training programs. We aim to quantify temporal trends in research productivity of medical students who matched into a canadian ophthalmology residency program. DESIGN: Retrospective database review. PARTICIPANTS: A total of 465 residents commencing ophthalmology training from 2010 to 2022 in 15 Canadian ophthalmology residency programs. METHODS: The names of all residents commencing training in ophthalmology in all Canadian programs from 2010 to 2022 were identified. Bibliometric data including publication count and type, authorship position, and H-index corresponding to the match year were extracted from the Scopus database. Descriptive and univariate statistics were used to characterize and assess trends in research productivity. RESULTS: A total of 461 ophthalmology residents (99% complete data set) from all 15 residency programs representing 1179 publications, including 679 ophthalmology-related publications, were identified. Most publications were original research (676; 58%), followed by case reports and letters (324; 27%) and reviews (162; 14%). Overall, 62% of residents had at least 1 publication at the time of the match, with a mean of 2.56 ± 3.49 publications and a mean H-index of 1.03 ± 1.48 publications. There was a significant increase (p < 0.001) in all research productivity metrics except senior authorship in the period 2019-2022 compared with 2010-2018. Notably, 91% of residents had ≥1 publication in 2022 compared with 38% in 2010. CONCLUSION: First-year ophthalmology resident publication productivity doubled from 2010-2016 to 2017-2022 suggesting a greater emphasis on scholarly work from medical trainees, a trend similar to that reported in other specialties.

Management of Congenital Dacryocystocele: A Case Series and Literature Review.

Congenital dacryocystocele presents with a distinct bluish swelling in the medial canthal region in neonates. The authors present four illustrative cases with differing courses and a literature review on dacryocystocele management to raise awareness of the importance of prompt diagnosis, initiation of conservative management, and appropriate referral for surgical assessment. [J Pediatr Ophthalmol Strabismus. 2023;60(3):e31-e34.].

The use of augmented reality and virtual reality for visual field expansion and visual acuity improvement in low vision rehabilitation: a systematic review.

INTRODUCTION: Developments in image processing techniques and display technology have led to the emergence of augmented reality (AR) and virtual reality (VR)-based low vision devices (LVDs). However, their promise and limitations in low vision rehabilitation are poorly understood. The objective of this systematic review is to appraise the application of AR/VR LVDs aimed at visual field expansion and visual acuity improvement in low vision rehabilitation. METHODS: A systematic search of the literature was performed using MEDLINE, Embase, PsychInfo, HealthStar, and National Library of Medicine (PubMed) from inception to March 6, 2022. Articles were eligible if they included an AR or VR LVD tested on a sample of individuals with low vision and provided visual outcomes such as visual acuity, visual fields, and object recognition. RESULTS: Of the 652 articles identified, 16 studies comprising 382 individuals with a mean age of 52.17 (SD = 18.30) years, and with heterogeneous low vision etiologies (i.e., glaucoma, age-related macular degeneration, retinitis pigmentosa) were included in this systematic review. Most articles used AR (53%), VR (40%), and one article used both AR and VR. The main visual outcomes evaluated were visual fields (67%), visual acuity (65%), and contrast sensitivity (27%). Various visual enhancement techniques were employed including variable magnification using digital zoom (67%), contrast enhancements (53%), and minification (27%). AR LVDs were reported to expand the visual field from threefold to ninefold. On average, individuals using AR/VR LVDs experienced an improved in visual acuity from 0.9 to 0.2 logMAR. Ten articles were classified as high or moderate risk of bias. CONCLUSION: AR/VR LVDs were found to afford visual field expansion and visual acuity improvement in low vision populations. Even though the results of this review are promising, the lack of controlled studies with well-defined populations, use of small, convenience samples, and incomplete reporting of inclusion and exclusion criteria among included studies makes it challenging to judge the true impact of these devices. Future studies should address these limitations and compare various AR/LVDs to determine what is the ideal LVD type and vision enhancement combination based on the user's level of visual ability and lifestyle.

The role of artificial intelligence in analysis of biofluid markers for diagnosis and management of glaucoma: A systematic review.

PURPOSE: This review focuses on utility of artificial intelligence (AI) in analysis of biofluid markers in glaucoma. We detail the accuracy and validity of AI in the exploration of biomarkers to provide insight into glaucoma pathogenesis. METHODS: A comprehensive search was conducted across five electronic databases including Embase, Medline, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science. Studies pertaining to biofluid marker analysis using AI or bioinformatics in glaucoma were included. Identified studies were critically appraised and assessed for risk of bias using the Joanna Briggs Institute Critical Appraisal tools. RESULTS: A total of 10,258 studies were screened and 39 studies met the inclusion criteria, including 23 cross-sectional studies (59%), nine prospective cohort studies (23%), six retrospective cohort studies (15%), and one case-control study (3%). Primary open angle glaucoma (POAG) was the most commonly studied subtype (55% of included studies). Twenty-four studies examined disease characteristics, 10 explored treatment decisions, and 5 provided diagnostic clarification. While studies examined at entire metabolomic or proteomic profiles to determine changes in POAG, there was heterogeneity in the data with over 175 unique, differentially expressed biomarkers reported. Discriminant analysis and artificial neural network predictive models displayed strong differentiating ability between glaucoma patients and controls, although these tools were untested in a clinical context. CONCLUSION: The use of AI models could inform glaucoma diagnosis with high sensitivity and specificity. While insight into differentially expressed biomarkers is valuable in pathogenic exploration, no clear pathogenic mechanism in glaucoma has emerged.

Patient perspective on the participation of ophthalmology residents in their cataract surgery.

OBJECTIVE: To determine the proportion of patients consenting to resident participation in cataract surgery and to identify factors predictive of consent. DESIGN: Prospective cross-sectional study. PARTICIPANTS: The 330 consecutive patients referred for cataract evaluation from February-April 2021 to 3 surgeons at a tertiary care referral centre in London, Ontario. METHODS: Using a standardized disclosure script, individuals were asked about resident participation in their cataract surgery. A phone survey and medical record review were conducted to obtain clinical and demographic information. Predictors of consent were assessed using logistic regression modelling. RESULTS: Responses were received from 279 individuals (85% response rate), with a mean age of 71.7 ± 8.6 years, and 113 were female. The consent rate was 71%. Prior negative experience with any medical trainee was an independent predictor for refusing resident participation (odds ratio [OR] = 3.10; 95% CI, 1.32-7.28; p = 0.009). Nonconsenters also had more prior negative experiences with other physicians (35% vs 23%; p = 0.031) and knew someone who had had a problem after eye surgery (36% vs 22%; p = 0.016). Individuals with an occupation involving apprenticeship (OR = 2.87; 95% CI, 1.08-7.67; p = 0.035) and those with a preoperative acuity of 20/200 or worse (OR = 2.78; 95% CI, 1.03-7.14; p = 0.043) were more likely to consent. CONCLUSIONS: Patients should be explicitly asked about resident involvement. Negative experiences can make individuals reluctant to have learners involved in their future care. Patient education describing the apprenticeship model in medicine may increase consent.

Anesthesia for ophthalmic surgery: an educational review.

PURPOSE: Selecting an anesthetic agent for ophthalmic surgery has crucial implications for the surgeon, anesthesiologist, and patient. This educational review explores the common classes of anesthesia used in ophthalmology. Additionally, we discuss the considerations unique to cataract, glaucoma, strabismus, orbital, oculoplastic, and ocular trauma surgeries. METHODS: A comprehensive Embase search was performed using combinations of the subject headings "anesthesia", "eye surgery", "ophthalmology" and "cataract extraction", "glaucoma", "strabismus", "vitreoretinal surgery", "retina surgery", "eye injury", and "eyelid reconstruction". RESULTS: Topical anesthetics are the most commonly used form of ocular anesthesia, used in both an office and surgical setting, and carry a minimal side effect profile. Notably, topical anesthetics offer analgesia, but do not provide akinesia or amnesia. Regional blocks, such as are sub-Tenon's, peribulbar, and retrobulbar blocks, are used when akinesia is required in addition to analgesia. Recently, sub-Tenon's blocks have recently gained popularity due to their improved safety profile compared to other regional blocks. General anesthesia is considered for long, complex surgery, surgery in patients with multiple comorbidities, surgery in young pediatric patients, or surgery in patients intolerant to local or regional anesthetic. CONCLUSION: Anesthetizing the eye has rapidly evolved in recent years, supporting the safety, efficacy and comfort of ocular surgery. Since there are many viable options of anesthetics available for ophthalmic surgery, a robust understanding of the patients needs, the skill of the surgical team, and surgery-specific factors ought to be considered when creating an anesthetic plan for surgery.

The Application of Artificial Intelligence in the Analysis of Biomarkers for Diagnosis and Management of Uveitis and Uveal Melanoma: A Systematic Review.

Purpose: This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases. Methods: A comprehensive literature search was conducted in 5 electronic databases, finding studies relating to AI and uveal diseases. Results: After screening 10,258 studies,18 studies met the inclusion criteria. Uveal melanoma (44%) and uveitis (56%) were the two uveal diseases examined. Ten studies (56%) used complex AI, while 13 studies (72%) used regression methods. Lactate dehydrogenase (LDH), found in 50% of studies concerning uveal melanoma, was the only biomarker that overlapped in multiple studies. However, 94% of studies highlighted that the biomarkers of interest were significant. Conclusion: This study highlights the value of using complex and simple AI tools as a clinical tool in uveal diseases. Particularly, complex AI methods can be used to weigh the merit of significant biomarkers, such as LDH, in order to create staging tools and predict treatment outcomes.

Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review.

This systematic review explores the use of artificial intelligence (AI) in the analysis of biofluid markers in age-related macular degeneration (AMD). We detail the accuracy and validity of AI in diagnostic and prognostic models and biofluid markers that provide insight into AMD pathogenesis and progression. This review was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines. A comprehensive search was conducted across 5 electronic databases including Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, EMBASE, Medline, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics in AMD were included. Identified studies were assessed for risk of bias and critically appraised using the Joanna Briggs Institute Critical Appraisal tools. A total of 10,264 articles were retrieved from all databases and 37 studies met the inclusion criteria, including 15 cross-sectional studies, 15 prospective cohort studies, five retrospective cohort studies, one randomized controlled trial, and one case-control study. The majority of studies had a general focus on AMD (58%), while neovascular AMD (nAMD) was the focus in 11 studies (30%), and geographic atrophy (GA) was highlighted by three studies. Fifteen studies examined disease characteristics, 15 studied risk factors, and seven guided treatment decisions. Altered lipid metabolism (HDL-cholesterol, total serum triglycerides), inflammation (c-reactive protein), oxidative stress, and protein digestion were implicated in AMD development and progression. AI tools were able to both accurately differentiate controls and AMD patients with accuracies as high as 87% and predict responsiveness to anti-VEGF therapy in nAMD patients. Use of AI models such as discriminant analysis could inform prognostic and diagnostic decision-making in a clinical setting. The identified pathways provide opportunity for future studies of AMD development and could be valuable in the advancement of novel treatments.

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 <0.001) 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 <0.001). 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.

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's 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's approach to the epileptogenic zone.

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.