Atrophy and cognitive profiles in older adults with temporal lobe epilepsy are similar to mild cognitive impairment.

Epilepsy incidence and prevalence peaks in older adults yet systematic studies of brain ageing and cognition in older adults with epilepsy remain limited. Here, we characterize patterns of cortical atrophy and cognitive impairment in 73 older adults with temporal lobe epilepsy (>55 years) and compare these patterns to those observed in 70 healthy controls and 79 patients with amnestic mild cognitive impairment, the prodromal stage of Alzheimer's disease. Patients with temporal lobe epilepsy were recruited from four tertiary epilepsy surgical centres; amnestic mild cognitive impairment and control subjects were obtained from the Alzheimer's Disease Neuroimaging Initiative database. Whole brain and region of interest analyses were conducted between patient groups and controls, as well as between temporal lobe epilepsy patients with early-onset (age of onset <50 years) and late-onset (>50 years) seizures. Older adults with temporal lobe epilepsy demonstrated a similar pattern and magnitude of medial temporal lobe atrophy to amnestic mild cognitive impairment. Region of interest analyses revealed pronounced medial temporal lobe thinning in both patient groups in bilateral entorhinal, temporal pole, and fusiform regions (all P < 0.05). Patients with temporal lobe epilepsy demonstrated thinner left entorhinal cortex compared to amnestic mild cognitive impairment (P = 0.02). Patients with late-onset temporal lobe epilepsy had a more consistent pattern of cortical thinning than patients with early-onset epilepsy, demonstrating decreased cortical thickness extending into the bilateral fusiform (both P < 0.01). Both temporal lobe epilepsy and amnestic mild cognitive impairment groups showed significant memory and language impairment relative to healthy control subjects. However, despite similar performances in language and memory encoding, patients with amnestic mild cognitive impairment demonstrated poorer delayed memory performances relative to both early and late-onset temporal lobe epilepsy. Medial temporal lobe atrophy and cognitive impairment overlap between older adults with temporal lobe epilepsy and amnestic mild cognitive impairment highlights the risks of growing old with epilepsy. Concerns regarding accelerated ageing and Alzheimer's disease co-morbidity in older adults with temporal lobe epilepsy suggests an urgent need for translational research aimed at identifying common mechanisms and/or targeting symptoms shared across a broad neurological disease spectrum.

The impact of cerebrovascular risk factors on postoperative memory decline in patients with left temporal lobe epilepsy.

Cerebrovascular risk factors (CVRFs) and comorbid cardiovascular and metabolic disease have been linked to accelerated cognitive aging and dementia in the general population; however, the contribution of these comorbidities to the risk of post anterior temporal lobectomy (ATL) memory decline has been unexamined. We explored the effects of CVRFs on postoperative verbal memory decline in a cohort of 22 patients with left temporal lobe epilepsy (LTLE) who completed pre- and one-year postsurgical neuropsychological testing. Diagnoses of interest included preoperative cardiovascular and metabolic disorders, as well as CVRFs [pulse pressure proxy, body mass index (BMI), and fasting glucose]. Twenty-three percent of patients had a history of cardiovascular disease, 9% of metabolic disorders, and 38% had a BMI indicating overweight or obese status. Higher preoperative BMI and glucose were associated with greater decline in verbal memory. The association between BMI and memory decline remained significant after controlling for age and left hippocampal volume. These findings suggest that modifiable health-related risk factors, including CVRFs, may impact the risk of postoperative cognitive decline, and that BMI in particular could be an important factor to consider and/or target for intervention early in clinical care to protect cognitive health.

Identifying the neural basis of a language-impaired phenotype of temporal lobe epilepsy.

OBJECTIVE: To identify neuroimaging and clinical biomarkers associated with a language-impaired phenotype in refractory temporal lobe epilepsy (TLE). METHODS: Eighty-five patients with TLE were characterized as language-impaired (TLE-LI) or non-language-impaired (TLE-NLI) based on comprehensive neuropsychological testing. Structural magnetic resonance imaging (MRI), diffusion tensor imaging, and functional MRI (fMRI) were obtained in patients and 47 healthy controls (HC). fMRI activations and cortical thickness were calculated within language regions of interest, and fractional anisotropy (FA) was calculated within deep white matter tracts associated with language. Analyses of variance were performed to test for differences among the groups in imaging measures. Receiver operator characteristic curves were used to determine how well different clinical versus imaging measures discriminated TLE-LI from TLE-NLI. RESULTS: TLE-LI patients showed significantly less activation within left superior temporal cortex compared to HC and TLE-NLI, regardless of side of seizure onset. TLE-LI also showed decreased FA in the inferior longitudinal fasciculus and arcuate fasciculus compared to HC. Cortical thickness did not differ between groups in any region. A model that included language-related fMRI activations within the superior temporal gyrus, age at onset, and demographic variables was the most predictive of language impairment (area under the curve = 0.80). SIGNIFICANCE: These findings demonstrate a unique imaging signature associated with a language-impaired phenotype in TLE, characterized by functional and microstructural alterations within the language network. Reduced left superior temporal activation combined with compromise to language association tracts underlies this phenotype, extending our previous work on cognitive phenotypes that could have implications for treatment-planning or cognitive progression in TLE.

Longitudinal change in fine motor skills after brain radiotherapy and in vivo imaging biomarkers associated with decline.

BACKGROUND: We explored fine motor skills (FMS) before and after brain radiotherapy (RT), analyzing associations between longitudinal FMS and imaging biomarkers of cortical and white matter (WM) integrity in motor regions of interest (ROIs). METHODS: On a prospective trial, 52 primary brain tumor patients receiving fractionated brain RT underwent volumetric brain MRI, diffusion tensor imaging, and FMS assessments (Delis-Kaplan Executive Function System Trail Making Test Motor Speed [DKEFS-MS], Grooved Pegboard Dominant Hands [PDH], and Grooved Pegboard Nondominant Hands [PNDH]) at baseline and 3-, 6-, and 12-month post-RT. Motor ROIs autosegmented included: sensorimotor cortices and superficial WM, corticospinal tracts, cerebellar cortices and WM, and basal ganglia. Volume (cc) was measured in all ROIs at each timepoint. Diffusion biomarkers (FA [fractional anisotropy] and MD [mean diffusivity]) were additionally measured in WM ROIs. Linear mixed-effects models assessed biomarkers as predictors of FMS scores. P values were corrected for multiple comparisons. RESULTS: Higher RT dose was associated with right paracentral cortical thinning (ß = -2.42 Gy/(month × mm), P = .03) and higher right precentral WM MD (ß = 0.69 Gy/(month × µm2/ms), P = .04). Higher left (ß = 38.7 points/(month × µm2/ms), P = .004) and right (ß = 42.4 points/(month × µm2/ms), P = .01) cerebellar WM MD, left precentral cortical atrophy (ß = -8.67 points/(month × mm), P = .02), and reduced right cerebral peduncle FA (ß = -0.50 points/month, P = .01) were associated with worse DKEFS-MS performance. Left precentral cortex thinning was associated with worse PDH scores (ß = -17.3 points/(month × mm), P = .02). Left (ß = -0.87 points/(month × cm3), P = .001) and right (ß = -0.64 points/(month × cm3), P = .02) cerebellar cortex, left pons (ß = -19.8 points/(month × cm3), P = .02), and right pallidum (ß = -10.8 points/(month × cm3), P = .02) atrophy and reduced right internal capsule FA (ß = -1.02 points/month, P = .03) were associated with worse PNDH performance. CONCLUSIONS: Biomarkers of microstructural injury in motor-associated brain regions were associated with worse FMS. Dose avoidance in these areas may preserve FMS.

Quality of Life Is Independently Associated With Neurocognitive Function in Patients With Brain Tumors: Analysis of a Prospective Clinical Trial.

PURPOSE: We conducted the first prospective longitudinal study examining the independent association between patient-reported health-related quality of life (hrQoL) (physical, social/family, emotional, functional, and brain cancer-specific) and neurocognitive function (NCF), while controlling for mood symptoms in patients with primary brain tumors. METHODS AND MATERIALS: Patients with primary brain tumors (n = 59) receiving brain radiation therapy underwent hrQOL (Functional Assessment of Cancer Therapy-Brain), mood (Beck Depression and Anxiety Inventories), and neurocognitive evaluation at baseline and 3, 6, and 12 months postradiation therapy in a prospective clinical trial. Neurocognitive assessments measured attention/processing speed, memory, and executive function, including the Delis-Kaplan Executive Function System Verbal Fluency, Hopkins Verbal Learning Test Revised (HVLT-R), and Brief Visuospatial Memory Test. Subjects underwent neurocognitive, mood, and hrQoL assessments in the same testing session. Multivariable linear mixed-effects models assessed associations between hrQOL and NCF over time, controlling for patient, tumor, and treatment characteristics as well as timepoint-specific patient-reported mood (ie, anxiety and depression symptoms). P values were adjusted for multiple comparisons. RESULTS: Higher physical hrQoL was associated with better verbal memory (HVLT-R Total Recall, P = .047), and higher functional hrQoL was associated with better executive function (Delis-Kaplan Executive Function System Verbal Fluency Switching Total, P = .009) and verbal memory (HVLT-R Delayed Recall, P = .006). Higher brain tumor-specific hrQoL was associated with better verbal and nonverbal memory (HVLT-R Total, P = .004 and Delayed Recall, P = .030; Brief Visuospatial Memory Test Total, P = .049 and Delayed Recall, P = .049). There was no association between social/family or emotional hrQoL and NCF after controlling for mood. CONCLUSIONS: Higher physical, functional, and brain tumor-specific hrQoL were associated with better executive function and memory among patients with primary brain tumors. Physical and functional impairments are correlated with cognitive performance. Interventions to maximize quality of life after treatment may influence neurocognition and vice versa.

Microstructural Injury to Corpus Callosum and Intrahemispheric White Matter Tracts Correlate With Attention and Processing Speed Decline After Brain Radiation.

PURPOSE: The corpus callosum (CC) and intrahemispheric white matter tracts (IHWM) subserve critical aspects of attention and processing speed. We analyzed imaging biomarkers of microstructural injury within these regions and association with attention and processing speed performance before and after radiation therapy in primary brain tumor patients. METHODS AND MATERIALS: In a prospective clinical trial, 44 primary brain tumor patients underwent cognitive testing and magnetic resonance imaging/diffusion-weighted imaging at baseline (pre-radiation therapy) and 3-, 6-, and 12-months post-radiation therapy. CC (subregions, total) and IHWM tracts (left/right without CC, total) were autosegmented; tumor, tumor bed, and edema were censored. Biomarkers included volume changes (cm3), mean diffusivity ([MD]; higher values indicate white matter injury), fractional anisotropy ([FA]; lower values indicate white matter injury). Reliable-change indices measured changes in attention (Weschler Adult Intelligence Scale [WAIS-IV] digits-forward; Delis-Kaplan Executive Function System Trail Making [D-KEFS-TM] visual-scanning), and processing speed (WAIS-IV coding; D-KEFS-TM number-sequencing, letter-sequencing), accounting for practice effects. Linear mixed-effects models evaluated associations between mean radiation dose and biomarkers (volume, MD, FA) and imaging biomarkers and neurocognitive performance. Statistics were corrected for multiple comparisons. RESULTS: Processing speed declined at 6 months following radiation therapy (number sequencing, letter sequencing; P < .04). Seizures and antiepileptic drug therapy were associated with lower visual-scanning attention reliable-change indices at 6 months (P = .039). Higher radiation dose correlated with smaller midanterior CC volume (P = .023); lower FA in posterior CC, anterior CC, and total CC (all P < .03); and higher MD in anterior CC (P = .012). Smaller midanterior CC and left IHWM volume correlated with worse processing speed (coding, letter-sequencing, number-sequencing; all P < .03). Higher FA in right, left, and total IHWM correlated with better coding scores (all P < .01). Lower FA in total IHWM (P = .009) was associated with worse visual-scanning attention scores. Higher FA in midposterior CC (P = .029) correlated with better digits-forward attention scores. CONCLUSIONS: The CC demonstrated radiation dose-dependent atrophy and WM injury. Microstructural injury within the CC and IHWM was associated with attention and processing speed decline after radiation therapy. These areas represent possible avoidance regions for preservation of attention and processing speed.

Microstructural Injury to Left-Sided Perisylvian White Matter Predicts Language Decline After Brain Radiation Therapy.

PURPOSE: Our purpose was to investigate the association between imaging biomarkers of radiation-induced white matter (WM) injury within perisylvian regions and longitudinal language decline in patients with brain tumors. METHODS AND MATERIALS: Patients with primary brain tumors (n = 44) on a prospective trial underwent brain magnetic resonance imaging, diffusion-weighted imaging, and language assessments of naming (Boston Naming Test [BNT]) and fluency (Delis-Kaplan Executive Function System Category Fluency [DKEFS-CF]) at baseline and 3, 6, and 12 months after fractionated radiation therapy (RT). Reliable change indices of language function (0-6 months), accounting for practice effects (RCI-PE), evaluated decline. Bilateral perisylvian WM regions (superficial WM subadjacent to Broca's area and the superior temporal gyrus [STG], inferior longitudinal fasciculus [ILF], inferior fronto-occipital fasciculus [IFOF], and arcuate fasciculus) were autosegmented. We quantified volume and diffusion measures of WM microstructure: fractional anisotropy (FA; lower values indicate disruption) and mean diffusivity (MD; higher values indicate injury). Linear mixed-effects models assessed mean dose as predictor of imaging biomarker change and imaging biomarkers as longitudinal predictors of language scores. RESULTS: DKEFS-CF scores declined at 6 months post-RT (RCI-PE, -0.483; P = .01), whereas BNT scores improved (RCI-PE, 0.262; P = .04). Higher mean dose to left and right regions was predictive of decreased volume (left-STG, P = .02; right-ILF and IFOF, P = .03), decreased FA (left-WM tracts, all P < .01; right-STG and IFOF, P < .02), and increased MD of left-WM tracts (all P < .03). Volume loss within left-Broca's area (P = .01), left-ILF (P = .01), left-IFOF (P = .01), and left-arcuate fasciculus (P = .04) was associated with lower BNT scores. Lower FA correlated with poorer DKEFS-CF and BNT scores within left-ILF (P = .02, not significant), left-IFOF (P = .02, .04), and left-arcuate fasciculus (P = .01, .01), respectively. Poorer DKEFS-CF scores correlated with increased MD values within the left-arcuate fasciculus (P = .03). Right-sided biomarkers did not correlate with language scores. CONCLUSIONS: Patients with primary brain tumors experience language fluency decline post-RT. Poorer fluency and naming function may be explained by microstructural injury to left-sided perisylvian WM, representing potential dose-avoidance targets for language preservation.

Clinical utility of structural connectomics in predicting memory in temporal lobe epilepsy.

OBJECTIVE: To determine the predictive power of white matter neuronal networks (i.e., structural connectomes [SCs]) in discriminating memory-impaired patients with temporal lobe epilepsy (TLE) from those with normal memory. METHODS: T1- and diffusion MRI (dMRI), clinical variables, and neuropsychological measures of verbal memory were available for 81 patients with TLE. Prediction of memory impairment was performed with a tree-based classifier (XGBoost) for 4 models: (1) a clinical model including demographic and clinical features, (2) a hippocampal volume (HCV) model, (3) a tract model including 5 temporal lobe white matter association tracts derived from a dMRI atlas, and (4) an SC model based on dMRI. SCs were derived by extracting cortical-cortical connections from a temporal lobe subnetwork with probabilistic tractography. Principal component (PC) analysis was then applied to reduce the dimensionality of the SC, yielding 10 PCs. Multimodal models were also tested combining SCs and tracts with HCV. Each model was trained on 48 patients from 1 epilepsy center and tested on 33 patients from a different center. RESULTS: Multimodal models that included the SC + HCV model yielded the highest classification accuracy (81%; 0.90 sensitivity; 0.67 specificity), outperforming the clinical model (61%; p < 0.001) and HCV model (66%; p < 0.001). In addition, the unimodal SC model (76% accuracy) and tract model (73% accuracy) outperformed the clinical model (p < 0.001) and HCV model (p < 0.001) for classifying patients with TLE with and without memory impairment. Furthermore, the SC identified that short-range temporal-temporal connections were important contributors to memory performance. CONCLUSION: SCs and tract-based models are stronger predictors of memory impairment in TLE than HCVs and clinical variables. However, SCs may provide additional information about local cortical-cortical connectivity contributing to memory that is not captured in large association tracts.

Longitudinal Analysis of Depression and Anxiety Symptoms as Independent Predictors of Neurocognitive Function in Primary Brain Tumor Patients.

PURPOSE: Primary brain tumor patients are vulnerable to depression and anxiety symptoms, which may affect their neurocognitive functioning. We performed a prospective longitudinal analysis to examine the association between depression and anxiety symptoms and domain-specific neurocognitive functioning in primary brain tumor patients receiving radiation therapy (RT). METHODS AND MATERIALS: On a prospective trial, 54 primary brain tumor patients receiving RT underwent comprehensive neurocognitive evaluation at baseline (pre-RT), and 3, 6, and 12 months post-RT. Neurocognitive assessments measured attention/processing speed, verbal and visuospatial memory, and executive functioning, including Delis-Kaplan Executive Function System Trail-Making Test (DKEFS-TMT), DKEFS Verbal Fluency, and Brief Visuospatial Memory Test-Revised. Depression and anxiety symptoms were also assessed at each time point with Beck Depression and Anxiety Inventories (BDI-II and BAI), respectively. Higher scores reflect more numerous or severe depression or anxiety symptoms. Univariable and multivariable linear mixed-effects models assessed associations between BDI-II and BAI scores and domain-specific neurocognitive scores over time, controlling for pre-existing depression or anxiety disorders and other patient, tumor, and treatment characteristics. RESULTS: Higher BAI scores were associated with worse attention and processing speed in univariable analyses: DKEFS-TMT visual scanning (P = .003), number sequencing (P = .011), and letter sequencing (P <.001). On multivariable analyses, these associations remained significant (all P ≤ .01). Higher BDI-II scores were also associated with poorer attention/processing speed (DKEFS-TMT Letter Sequencing) in univariable (P = .002) and multivariable (P = .013) models. Higher BAI scores were associated with worse visuospatial memory (Brief Visuospatial Memory Test-Revised Delayed Recall) on univariable (P = .012) but not multivariable analyses (P = .383). Similarly, higher BDI-II scores were associated with poorer executive functioning (DKEFS Verbal Fluency Category Switching) on univariable (P = .031) but not multivariable analyses (P = .198). CONCLUSIONS: Among primary brain tumor patients receiving RT, increased depression and anxiety were independently associated with worsened neurocognition, particularly in attention/processing speed. Depression and anxiety symptoms should be controlled for in prospective clinical trials and managed in the clinical setting to optimize neurocognitive functioning.

The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy.

OBJECTIVE: The distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment. METHODS: T1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results. RESULTS: The SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance. CONCLUSION: The SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance.