Shaping the risk for late-life neurodegenerative disease: A systematic review on prenatal risk factors for Alzheimer's disease-related volumetric brain biomarkers.

Environmental exposures including toxins and nutrition may hamper the developing brain in utero, limiting the brain's reserve capacity and increasing the risk for Alzheimer's disease (AD). The purpose of this systematic review is to summarize all currently available evidence for the association between prenatal exposures and AD-related volumetric brain biomarkers. We systematically searched MEDLINE and Embase for studies in humans reporting on associations between prenatal exposure(s) and AD-related volumetric brain biomarkers, including whole brain volume (WBV), hippocampal volume (HV) and/or temporal lobe volume (TLV) measured with structural magnetic resonance imaging (PROSPERO; CRD42020169317). Risk of bias was assessed using the Newcastle Ottawa Scale. We identified 79 eligible studies (search date: August 30th, 2020; Ntotal=24,784; median age 10.7 years) reporting on WBV (N = 38), HV (N = 63) and/or TLV (N = 5) in exposure categories alcohol (N = 30), smoking (N = 7), illicit drugs (N = 14), mental health problems (N = 7), diet (N = 8), disease, treatment and physiology (N = 10), infections (N = 6) and environmental exposures (N = 3). Overall risk of bias was low. Prenatal exposure to alcohol, opioids, cocaine, nutrient shortage, placental dysfunction and maternal anemia was associated with smaller brain volumes. We conclude that the prenatal environment is important in shaping the risk for late-life neurodegenerative disease.

Mediterranean-Type Diet and Brain Structural Change from 73 to 79 Years in the Lothian Birth Cohort 1936.

OBJECTIVES: To test whether Mediterranean-type Diet (MeDi) at age 70 years is associated with longitudinal trajectories of total brain MRI volume over a six-year period from age 73 to 79. DESIGN: Cohort study which uses a correlational design. SETTING: Participants residing in the Lothian region of Scotland and living independently in the community. PARTICIPANTS: A relatively healthy Scottish sample drawn from the Lothian Birth Cohort 1936. MEASUREMENTS: Total brain volume measurements were available at ages 73, 76 and 79 (N ranged 332 to 563). Adherence to the MeDi was based on food frequency questionnaire data collected three years before the baseline imaging scans, and was used in growth curve models to predict the trajectory of total brain volume change. RESULTS: No association was found (p>.05) between adherence to the MeDi at age 70 and total brain volume change from 73 to 79 years in minimally-adjusted (sex) or fully adjusted models controlling for additional health confounders. CONCLUSIONS: Variation in adherence to the MeDi was not predictive of total brain atrophy over a six-year period. This suggests that previous findings of dietary associations with brain volume are not long lasting or become less important as ageing-related conditions account for greater variation in brain volume change. More frequent collection of dietary intake data is needed to clarify these findings.

Cerebral small vessel disease burden and longitudinal cognitive decline from age 73 to 82: the Lothian Birth Cohort 1936.

Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD's association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised ß: -0.201; 95% CI: [-0.36, -0.04]; pFDR = 0.022) and processing speed (-0.222; [-0.40, -0.04]; pFDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD's association with greater decline in general cognitive ability remained significant, prior to FDR correction (-0.222; [-0.39, -0.06]; p = 0.008; pFDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.

Roadmap Consensus on Carotid Artery Plaque Imaging and Impact on Therapy Strategies and Guidelines: An International, Multispecialty, Expert Review and Position Statement.

Current guidelines for primary and secondary prevention of stroke in patients with carotid atherosclerosis are based on the quantification of the degree of stenosis and symptom status. Recent publications have demonstrated that plaque morphology and composition, independent of the degree of stenosis, are important in the risk stratification of carotid atherosclerotic disease. This finding raises the question as to whether current guidelines are adequate or if they should be updated with new evidence, including imaging for plaque phenotyping, risk stratification, and clinical decision-making in addition to the degree of stenosis. To further this discussion, this roadmap consensus article defines the limits of luminal imaging and highlights the current evidence supporting the role of plaque imaging. Furthermore, we identify gaps in current knowledge and suggest steps to generate high-quality evidence, to add relevant information to guidelines currently based on the quantification of stenosis.

Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort.

Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized ß: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.

Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life.

Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the eighth decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study.

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (ß = 0.132, pFDR = 0.040), arcuate (ß = 0.291, pFDR = 0.040), anterior thalamic radiations (ß = 0.215, pFDR = 0.040) and cingulum (ß = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (ß = -0.039, pFDR = 0.048) and strength (ß = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus.

Objective To investigate brain structural connectivity in relation to cognitive abilities and systemic damage in systemic lupus erythematosus (SLE). Methods Structural and diffusion MRI data were acquired from 47 patients with SLE. Brains were segmented into 85 cortical and subcortical regions and combined with whole brain tractography to generate structural connectomes using graph theory. Global cognitive abilities were assessed using a composite variable g, derived from the first principal component of three common clinical screening tests of neurological function. SLE damage ( LD) was measured using a composite of a validated SLE damage score and disease duration. Relationships between network connectivity metrics, cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiple linear regression, adjusting for covariates, was employed to model the outcomes g and LD as a function of network metrics. Results The network measures of density (standardised ß = 0.266, p = 0.025) and strength (standardised ß = 0.317, p = 0.022) were independently related to cognitive abilities. Strength (standardised ß = -0.330, p = 0.048), mean shortest path length (standardised ß = 0.401, p = 0.020), global efficiency (standardised ß = -0.355, p = 0.041) and clustering coefficient (standardised ß = -0.378, p = 0.030) were independently related to systemic damage. Network metrics were not related to current disease activity. Conclusion Better cognitive abilities and more SLE damage are related to brain topological network properties in this sample of SLE patients, even those without neuropsychiatric involvement and after correcting for important covariates. These data show that connectomics might be useful for understanding and monitoring cognitive function and white matter damage in SLE.

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks.

White matter hyperintensities (WMH) are a feature of sporadic small vessel disease also frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The accurate assessment of WMH burden is of crucial importance for epidemiological studies to determine association between WMHs, cognitive and clinical data; their causes, and the effects of new treatments in randomized trials. The manual delineation of WMHs is a very tedious, costly and time consuming process, that needs to be carried out by an expert annotator (e.g. a trained image analyst or radiologist). The problem of WMH delineation is further complicated by the fact that other pathological features (i.e. stroke lesions) often also appear as hyperintense regions. Recently, several automated methods aiming to tackle the challenges of WMH segmentation have been proposed. Most of these methods have been specifically developed to segment WMH in MRI but cannot differentiate between WMHs and strokes. Other methods, capable of distinguishing between different pathologies in brain MRI, are not designed with simultaneous WMH and stroke segmentation in mind. Therefore, a task specific, reliable, fully automated method that can segment and differentiate between these two pathological manifestations on MRI has not yet been fully identified. In this work we propose to use a convolutional neural network (CNN) that is able to segment hyperintensities and differentiate between WMHs and stroke lesions. Specifically, we aim to distinguish between WMH pathologies from those caused by stroke lesions due to either cortical, large or small subcortical infarcts. The proposed fully convolutional CNN architecture, called uResNet, that comprised an analysis path, that gradually learns low and high level features, followed by a synthesis path, that gradually combines and up-samples the low and high level features into a class likelihood semantic segmentation. Quantitatively, the proposed CNN architecture is shown to outperform other well established and state-of-the-art algorithms in terms of overlap with manual expert annotations. Clinically, the extracted WMH volumes were found to correlate better with the Fazekas visual rating score than competing methods or the expert-annotated volumes. Additionally, a comparison of the associations found between clinical risk-factors and the WMH volumes generated by the proposed method, was found to be in line with the associations found with the expert-annotated volumes.

Brain age predicts mortality.

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

Fourth European stroke science workshop.

Lake Eibsee, Garmisch-Partenkirchen, 16 to 18 November, 2017: The European Stroke Organisation convened >120 stroke experts from 21 countries to discuss latest results and hot topics in clinical, translational and basic stroke research. Since its inception in 2011, the European Stroke Science Workshop has become a cornerstone of European Stroke Organisation's academic activities and a major highlight for researchers in the field. Participants include stroke researchers at all career stages and with different backgrounds, who convene for plenary lectures and discussions. The workshop was organised in seven scientific sessions focusing on the following topics: (1) acute stroke treatment and endovascular therapy; (2) small vessel disease; (3) opportunities for stroke research in the omics era; (4) vascular cognitive impairment; (5) intracerebral and subarachnoid haemorrhage; (6) alternative treatment concepts and (7) neural circuits, recovery and rehabilitation. All sessions started with a keynote lecture providing an overview on current developments, followed by focused talks on a timely topic with the most recent findings, including unpublished data. In the following, we summarise the key contents of the meeting. The program is provided in the online only Data Supplement. The workshop started with a key note lecture on how to improve the efficiency of clinical trial endpoints in stroke, which was delivered by Craig Anderson (Sydney, Australia) and set the scene for the following discussions.

Dietary Iodine Exposure and Brain Structures and Cognition in Older People. Exploratory Analysis in the Lothian Birth Cohort 1936.

BACKGROUND: Iodine deficiency is one of the three key micronutrient deficiencies highlighted as major public health issues by the World Health Organisation. Iodine deficiency is known to cause brain structural alterations likely to affect cognition. However, it is not known whether or how different (lifelong) levels of exposure to dietary iodine influences brain health and cognitive functions. METHODS: From 1091 participants initially enrolled in The Lothian Birth Cohort Study 1936, we obtained whole diet data from 882. Three years later, from 866 participants (mean age 72 yrs, SD±0.8), we obtained cognitive information and ventricular, hippocampal and normal and abnormal tissue volumes from brain structural magnetic resonance imaging scans (n=700). We studied the brain structure and cognitive abilities of iodine-rich food avoiders/low consumers versus those with a high intake in iodine-rich foods (namely dairy and fish). RESULTS: We identified individuals (n=189) with contrasting diets, i) belonging to the lowest quintiles for dairy and fish consumption, ii) milk avoiders, iii) belonging to the middle quintiles for dairy and fish consumption, and iv) belonging to the middle quintiles for dairy and fish consumption. Iodine intake was secured mostly though the diet (n=10 supplement users) and was sufficient for most (75.1%, median 193 µg/day). In individuals from these groups, brain lateral ventricular volume was positively associated with fat, energy and protein intake. The associations between iodine intake and brain ventricular volume and between consumption of fish products (including fish cakes and fish-containing pasties) and white matter hyperintensities (p=0.03) the latest being compounded by sodium, proteins and saturated fats, disappeared after type 1 error correction. CONCLUSION: In this large Scottish older cohort, the proportion of individuals reporting extreme (low vs. high)/medium iodine consumption is small. In these individuals, low iodine-rich food intake was associated with increased brain volume shrinkage, raising an important hypothesis worth being explored for designing appropriate guidelines.

Ageing causes prominent neurovascular dysfunction associated with loss of astrocytic contacts and gliosis.

AIMS: Normal neurovascular coupling, mediated by the fine interplay and communication of cells within the neurovascular unit, is critical for maintaining normal brain activity and cognitive function. This study investigated whether, with advancing age there is disruption of neurovascular coupling and specific cellular components of the neurovascular unit, and whether the effects of increasing amyloid (a key feature of Alzheimer's disease) would exacerbate these changes. METHODS: Wild-type mice, in which amyloid deposition is absent, were compared to transgenic amyloid precursor protein (APP) littermates (TgSwDI) which develop age-dependent increases in amyloid. Baseline cerebral blood flow and responses to whisker stimulation were measured. Components of the neurovascular unit (astrocytes, end-feet, pericytes, microglia) were measured by immunohistochemistry. RESULTS: Neurovascular coupling was progressively impaired with increasing age (starting at 12 months) but was not further altered in TgSwDI mice. Aged mice showed reduced vascular pericyte coverage relative to young but this was not related to neurovascular function. Aged mice displayed significant reductions in astrocytic end-feet expression of aquaporin-4 on blood vessels compared to young mice, and a prominent increase in microglial proliferation which correlated with neurovascular function. CONCLUSIONS: Strategies aimed to restore the loss of astrocytic end feet contact and reduce gliosis may improve neurovascular coupling.

Fatigue and cognitive function in systemic lupus erythematosus: associations with white matter microstructural damage. A diffusion tensor MRI study and meta-analysis.

Objective The objective of this study was to investigate fatigue and cognitive impairments in systemic lupus erythematous (SLE) in relation to diffuse white matter microstructural brain damage. Methods Diffusion tensor MRI, used to generate biomarkers of brain white matter microstructural integrity, was obtained in patients with SLE and age-matched controls. Fatigue and cognitive function were assessed and related to SLE activity, clinical data and plasma biomarkers of inflammation and endothelial dysfunction. Results Fifty-one patients with SLE (mean age 48.8 ± 14.3 years) were included. Mean diffusivity (MD) was significantly higher in all white matter fibre tracts in SLE patients versus age-matched healthy controls ( p < 0.0001). Fatigue in SLE was higher than a normal reference range ( p < 0.0001) and associated with lower MD ( ß = -0.61, p = 0.02), depression ( ß = 0.17, p = 0.001), anxiety ( ß = 0.13, p = 0.006) and higher body mass index ( ß = 0.10, p = 0.004) in adjusted analyses. Poorer cognitive function was associated with longer SLE disease duration ( p = 0.003) and higher MD ( p = 0.03) and, in adjusted analysis, higher levels of IL-6 ( ß = -0.15, p = 0.02) but not with MD. Meta-analysis (10 studies, n = 261, including the present study) confirmed that patients with SLE have higher MD than controls. Conclusion Patients with SLE have more microstructural brain white matter damage for age than the general population, but this does not explain increased fatigue or lower cognition in SLE. The association between raised IL-6 and worse current cognitive function in SLE should be explored in larger datasets.

Cytomegalovirus infection is associated with an increase in systolic blood pressure in older individuals.

BACKGROUND: Cytomegalovirus (CMV) is a chronic infection that is widely distributed in the population. CMV infects a range of tissues, including endothelium, and viral replication is suppressed by the host immune system. Infection is associated with increased risk of mortality from vascular disease in older people, but the mechanisms behind this have not been determined. AIM: We investigated the association between CMV infection and cardiovascular phenotype in a cohort of healthy elderly donors. DESIGN: CMV serostatus and cardiovascular parameters were determined in the Lothian Birth cohort, which comprises 1091 individuals aged 70 years in whom many environmental, biochemical and radiological correlates of vascular function have been determined. METHODS: CMV serostatus was determined by enzyme-linked immunosorbant assay and correlated with a range of biochemical and phenotypic measures. RESULTS: Sixty-five percent of participants were CMV seropositive, which indicates chronic infection. The mean sitting systolic blood pressure (SBP) was 149.2 mmHg in CMV seropositive individuals compared with 146.2 mmHg in CMV seronegative subjects (SD 18.7 vs. 19.7; P < 0.017). This association between CMV infection and SBP was not attenuated after adjustment for a wide range of biological and socio-economic factors. CONCLUSIONS: These data show that CMV infection is associated with an increase in SBP in individuals at age 70 years. The magnitude is comparable to environmental variables such as obesity, diabetes or high salt intake. This is the first evidence to show that a chronic infection may be an important determinant of blood pressure and could have significant implications for the future management of hypertension.

Do white matter hyperintensities mediate the association between brain iron deposition and cognitive abilities in older people?

BACKGROUND AND PURPOSE: Several studies have reported associations between brain iron deposits (IDs), white matter hyperintensities (WMHs) and cognitive ability in older individuals. Whether the association between brain IDs and cognitive abilities in older people is mediated by or independent of total brain tissue damage represented by WMHs visible on structural magnetic resonance imaging (MRI) was examined. METHODS: Data from 676 community-dwelling individuals from the Lothian Birth Cohort 1936, with Mini-Mental State Examination scores >24, who underwent detailed cognitive testing and multimodal brain MRI at mean age 72.7 years were analysed. Brain IDs were assessed automatically following manual editing. WMHs were assessed semi-automatically. Brain microbleeds were visually counted. Structural equation modelling was used to test for mediation. RESULTS: Overall, 72.8% of the sample had IDs with a median total volume of 0.040 ml (i.e. 0.004% of the total brain volume). The total volume of IDs, significantly and negatively associated with general cognitive function (standardized ß = -0.17, P < 0.01), was significantly and positively associated with WMH volume (std ß = 0.13, P = 0.03). WMH volume had a significant negative association with general cognitive function, independent of IDs (std ß = -0.13, P < 0.01). The association between cognition and IDs in the brain stem (and minimally the total brain iron load) was partially and significantly mediated by WMH volume (P = 0.03). CONCLUSIONS: The negative association between brain IDs and cognitive ability in the elderly is partially mediated by WMHs, with this mediation mainly arising from the iron deposition load in the brain stem. IDs might be an indicator of small vessel disease that predisposes to white matter damage, affecting the neuronal networks underlying higher cognitive functioning.

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (N=112 151) and 24 GWAS consortia.

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular-metabolic, neuropsychiatric, physiological-anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer's disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples.

HydroCoils Are Associated with Lower Angiographic Recurrence Rates Than Are Bare Platinum Coils in Treatment of "Difficult-to-Treat" Aneurysms: A Post Hoc Subgroup Analysis of the HELPS Trial.

BACKGROUND AND PURPOSE: The HydroCoil Endovascular Aneurysm Occlusion and Packing Study was a randomized controlled trial that compared HydroCoils to bare platinum coils. Using data from this trial, we performed a subgroup analysis of angiographic and clinical outcomes of patients with "difficult-to-treat" aneurysms, defined as irregularly shaped and/or having a dome-to-neck ratio of <1.5. MATERIALS AND METHODS: Separate subgroup analyses comparing outcomes of treatment with HydroCoils to that of bare platinum coils were performed for the following: 1) irregularly shaped aneurysms, 2) regularly shaped aneurysms, 3) aneurysms with a dome-to-neck ratio of <1.5, and 4) aneurysms with a dome-to-neck ratio of ≥1.5. For each subgroup analysis, the following outcomes were studied at the last follow-up (3-18 months): 1) any recurrence, 2) major recurrence, 3) re-treatment, and 4) an mRS score of ≤2. Multivariate logistic regression analysis was performed to determine if the HydroCoil was independently associated with improved outcomes in these subgroups. RESULTS: Among the patients with an irregularly shaped aneurysm, the HydroCoil was associated with lower major recurrence rates than the bare platinum coils (17 of 66 [26%] vs 30 of 69 [44%], respectively; P = .046). Among the patients with an aneurysm with a small dome-to-neck ratio, the HydroCoil was associated with lower major recurrence rates than the bare platinum coils (18 of 73 [24.7%] vs 32 of 76 [42.1%], respectively; P = .02). No difference in major recurrence was seen between HydroCoils and bare platinum coils for regularly shaped aneurysms (42 of 152 [27.6%] vs 52 of 162 [32.1%], respectively; P = .39) or aneurysms with a large dome-to-neck ratio (41 of 145 [28.3%] vs 50 of 155 [32.3%], respectively; P = .53). CONCLUSIONS: This unplanned post hoc subgroup analysis found that HydroCoils are associated with improved angiographic outcomes in the treatment of irregularly shaped aneurysms and aneurysms with a dome-to-neck ratio of <1.5. Because this was a post hoc analysis, these results are not reliable and absolutely should not alter clinical practice but, rather, may inform the design of future randomized controlled trials.