Rapid Automated Quantification of Cerebral Leukoaraiosis on CT Images: A Multicenter Validation Study.

Purpose To validate a random forest method for segmenting cerebral white matter lesions (WMLs) on computed tomographic (CT) images in a multicenter cohort of patients with acute ischemic stroke, by comparison with fluid-attenuated recovery (FLAIR) magnetic resonance (MR) images and expert consensus. Materials and Methods A retrospective sample of 1082 acute ischemic stroke cases was obtained that was composed of unselected patients who were treated with thrombolysis or who were undergoing contemporaneous MR imaging and CT, and a subset of International Stroke Thrombolysis-3 trial participants. Automated delineations of WML on images were validated relative to experts' manual tracings on CT images, and co-registered FLAIR MR imaging, and ratings were performed by using two conventional ordinal scales. Analyses included correlations between CT and MR imaging volumes, and agreements between automated and expert ratings. Results Automated WML volumes correlated strongly with expert-delineated WML volumes at MR imaging and CT (r2 = 0.85 and 0.71 respectively; P < .001). Spatial-similarity of automated maps, relative to WML MR imaging, was not significantly different to that of expert WML tracings on CT images. Individual expert WML volumes at CT correlated well with each other (r2 = 0.85), but varied widely (range, 91% of mean estimate; median estimate, 11 mL; range of estimated ranges, 0.2-68 mL). Agreements (κ) between automated ratings and consensus ratings were 0.60 (Wahlund system) and 0.64 (van Swieten system) compared with agreements between individual pairs of experts of 0.51 and 0.67, respectively, for the two rating systems (P < .01 for Wahlund system comparison of agreements). Accuracy was unaffected by established infarction, acute ischemic changes, or atrophy (P > .05). Automated preprocessing failure rate was 4%; rating errors occurred in a further 4%. Total automated processing time averaged 109 seconds (range, 79-140 seconds). Conclusion An automated method for quantifying CT cerebral white matter lesions achieves a similar accuracy to experts in unselected and multicenter cohorts.

The assessment of headaches on the acute medical unit: is it adequate and how could it be improved? .

Neurological emergencies represent 15-25% of the medical take, second only to cardiac and respiratory cases. However, the UK's number of neurologists is lower than that of other developed nations. This quality improvement project aimed to develop a guideline to optimise acute headache management by non-specialists, informed by the findings of a survey and audit of doctors' knowledge and practice. In total, 62 doctors responded to our survey. 53/56 (94.6%) agreed a guideline would be useful. Knowledge of some important causes of headache was high, but was lower for others, including cerebral venous sinus thrombosis and cervical artery dissection. A consultant neurologist deemed 14/27 (51.9%) of acute headache presentations audited pre-guidelines to have had appropriate management. After guideline launch, a re-audit demonstrated this proportion was 18/22 (81.8%) (p=0.04). We conclude the investigation and management of acute headache requires optimisation and a guideline may help to achieve this.

Cost-Utility Analysis of Mechanical Thrombectomy Using Stent Retrievers in Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Recently, 5 randomized controlled trials demonstrated the benefit of endovascular therapy compared with intravenous tissue-type plasminogen activator in acute stroke. Economic evidence evaluating stent retrievers is limited. We compared the cost-effectiveness of intravenous tissue-type plasminogen activator alone versus mechanical thrombectomy and intravenous tissue-type plasminogen activator as a bridging therapy in eligible patients in the UK National Health Service. METHODS: A model-based cost-utility analysis was performed using a lifetime horizon. A Markov model was constructed and populated with probabilities, outcomes, and cost data from published sources, including 1-way and probabilistic sensitivity analysis. RESULTS: Mechanical thrombectomy was more expensive than intravenous tissue-type plasminogen activator, but it improved quality-adjusted life expectancy. The incremental cost per (quality-adjusted life year) gained of mechanical thrombectomy over a 20 year period was $11 651 (£7061). The probabilistic sensitivity analysis demonstrated that thrombectomy had a 100% probability of being cost-effective at the minimum willingness to pay for a quality-adjusted life year commonly used in United Kingdom. CONCLUSIONS: Although the upfront costs of thrombectomy are high, the potential quality-adjusted life year gains mean this intervention is cost-effective. This is an important factor for consideration in deciding whether to commission this intervention.

Should magnetic resonance imaging or computed tomography be the primary brain imaging modality in the transient ischemic attack clinic?

OBJECTIVE: The Royal College of Physicians and National Institute of Clinical Excellence have recommended that magnetic resonance imaging should be the modality of choice for cerebral imaging in transient ischemic attack patients. However, implementation of this is often difficult. Therefore, it is important to know whether magnetic resonance imaging contributes significantly to early clinical management in transient ischemic attack patients. DESIGN: A retrospective case-notes review of 65 consecutive patients seen by one neurology trainee (with consultant review), in a neurovascular service where computed tomography has been the primary cerebral imaging modality. SETTING: Outpatient TIA/Neurovascular clinic at Imperial College hospital. PARTICIPANTS: 65 consecutive patients seen by one neurology trainee (with consultant review). MAIN OUTCOME MEASURE: We recorded the preliminary clinical diagnosis, details of investigations performed and whether or not patients had a magnetic resonance imaging brain scan subsequently, the number followed up in clinic and the final diagnosis. RESULTS: Of the 65 cases seen, 55% were classified initially as transient ischemic attack/stroke mimics. Of the 29 cases (45%) that were classified as transient ischemic attack, all had computed tomography scans, 12 had magnetic resonance imaging scans subsequently and 14 were followed up several weeks later. Of the 36 cases classified as stroke mimics, 27 had computed tomography scans immediately and 31 had carotid Dopplers, six subsequently had magnetic resonance imaging scans and 14 were followed up in clinic. Only two patients had their diagnosis revised on the basis of the magnetic resonance imaging. CONCLUSIONS: Our study suggests that magnetic resonance imaging brain changes the diagnosis in a relatively small percentage of cases. A good history and examination remain paramount in the assessment of patients presenting to the transient ischemic attack clinic, particularly when more than 50% of cases referred are transient ischemic attack/stroke mimics.

Sequential strokes in a hyperacute stroke unit.

Vasculitis is a rare, but treatable condition that can present to hyperacute stroke units. Thrombolysis does not treat the underlying pathology, and a rapidly evolving clinical picture drives clinical decision often before all the investigation results are available.

Prediction of stroke thrombolysis outcome using CT brain machine learning.

A critical decision-step in the emergency treatment of ischemic stroke is whether or not to administer thrombolysis - a treatment that can result in good recovery, or deterioration due to symptomatic intracranial haemorrhage (SICH). Certain imaging features based upon early computerized tomography (CT), in combination with clinical variables, have been found to predict SICH, albeit with modest accuracy. In this proof-of-concept study, we determine whether machine learning of CT images can predict which patients receiving tPA will develop SICH as opposed to showing clinical improvement with no haemorrhage. Clinical records and CT brains of 116 acute ischemic stroke patients treated with intravenous thrombolysis were collected retrospectively (including 16 who developed SICH). The sample was split into training (n = 106) and test sets (n = 10), repeatedly for 1760 different combinations. CT brain images acted as inputs into a support vector machine (SVM), along with clinical severity. Performance of the SVM was compared with established prognostication tools (SEDAN and HAT scores; original, or after adaptation to our cohort). Predictive performance, assessed as area under receiver-operating-characteristic curve (AUC), of the SVM (0.744) compared favourably with that of prognostic scores (original and adapted versions: 0.626-0.720; p < 0.01). The SVM also identified 9 out of 16 SICHs, as opposed to 1-5 using prognostic scores, assuming a 10% SICH frequency (p < 0.001). In summary, machine learning methods applied to acute stroke CT images offer automation, and potentially improved performance, for prediction of SICH following thrombolysis. Larger-scale cohorts, and incorporation of advanced imaging, should be tested with such methods.

pNfH is a promising biomarker for ALS.

A diagnostic biomarker for ALS would permit early intervention with disease-modifying therapies while a biomarker for disease activity could accelerate the pace of drug discovery by facilitating shorter, and less costly, drug trials to be conducted with a smaller number of patients. Neurofilaments are the most abundant neuronal cytoskeletal protein. We set out to determine whether pNfH was a credible biomarker for ALS. pNfH levels were determined using an ELISA for 150 ALS subjects and 140 controls. We demonstrated a seven-fold elevation in the cerebrospinal fluid (CSF) levels of phosphorylated neurofilament heavy subunit (pNfH) in ALS (median = 2787 pg/ml, n = 150), compared to headache and other benign controls (394 pg/ml, n = 100, p = < 0.05). There was a 10-fold elevation of pNfH compared to ALS mimics (266 pg/ml, n = 20) and other neurodegenerative and inflammatory conditions (279 pg/ml for n = 20) which was also highly significant (p = < 0.05). pNfH achieved a diagnostic sensitivity of 90% and specificity of 87% in distinguishing ALS from all controls. We also detected an inverse correlation between CSF pNfH levels and disease duration (time from symptom onset to death, r(2 = )0.1247, p = 0.001). In conclusion, pNfH represents a promising candidate for inclusion in a panel of diagnostic and prognostic biomarkers.

Low index-to-ring finger length ratio in sporadic ALS supports prenatally defined motor neuronal vulnerability.

BACKGROUND: The aetiology of apparently sporadic amyotrophic lateral sclerosis (ALS) is unknown, but prenatal factors are known to influence disease development. In both men and women, motor neurons require testosterone for survival and axonal regeneration after injury, and androgen insensitivity leads to a form of motor neuron degeneration in men. Reduction in the ratio of index to ring finger length (2D:4D ratio) is considered a surrogate marker for high prenatal testosterone levels in both men and women. The authors therefore tested the hypothesis that prenatal testosterone irrespective of gender is an independent risk factor for the development of ALS later in life, and that this would be reflected in a lower 2D:4D ratio in both men and women with ALS. METHODS: Patients and unrelated control individuals attending a specialist tertiary referral centre for ALS were studied. A digital camera was used to photograph hands. Finger lengths were measured by four independent scorers blind to case-control status, and the mean 2D:4D ratio derived. Analysis was by linear regression and receiver-operator-curve analysis. RESULTS: Controlling for differences in sex ratio between groups, the 2D:4D ratio was lower for people with ALS (n=47) than for controls (n=63) (r=-0.25, two-tailed p=0.009). CONCLUSIONS: Patients with ALS have a lower 2D:4D ratio, consistent with higher prenatal circulating levels of testosterone, and possibly a prenatal influence of testosterone on motor-neuron vulnerability in later life.

Combination of neurofilament heavy chain and complement C3 as CSF biomarkers for ALS.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive and ultimately fatal neurodegenerative disease with an average survival of 3 years from symptom onset. Rapid and conclusive early diagnosis is essential if interventions with disease-modifying therapies are to be successful. Cytoskeletal modification and inflammation are known to occur during the pathogenesis of ALS. We measured levels of cytoskeletal proteins and inflammatory markers in the CSF of ALS, disease controls and healthy subjects. We determined threshold values for each protein that provided the optimal sensitivity and specificity for ALS within a training set, as determined by receiver operating characteristic analysis. Interestingly, the optimal assay was a ratio of the levels for phosphorylated neurofilament heavy chain and complement C3 (pNFH/C3). We next applied this assay to a separate test set of CSF samples to verify our results. Overall, the predictive pNFH/C3 ratio identified ALS with 87.3% sensitivity and 94.6% specificity in a total of 71 ALS subjects, 52 disease control subjects and 40 healthy subjects. In addition, the level of CSF pNFH correlated with survival of ALS patients. We also detected increased pNFH in the plasma of ALS patients and observed a correlation between CSF and plasma pNFH levels within the same subjects. These findings support large-scale prospective biomarker studies to determine the clinical utility of diagnostic and prognostic signatures in ALS.

The association between ALS and population density: A population based study.

We aimed to assess whether rural residence is associated with amyotrophic lateral sclerosis in the south-east of England using a population based register. Previous studies in different populations have produced contradictory findings. Residence defined by London borough or non-metropolitan district at time of diagnosis was recorded for each incident case in the South-East England ALS Register between 1995 and 2005. Each of the 26 boroughs or districts of the catchment area of the register was classified according to population density. Age- and sex-adjusted incidence of ALS was calculated for each region and the relationship with population density tested by linear regression, thereby controlling for the underlying population structure. We found that population density in region of residence at diagnosis explained 25% of the variance in ALS rates (r = 0.5, p < 0.01). Thus, in this cohort in the south-east of England, people with ALS were more likely to be resident in areas of high population density at diagnosis.

The application of biomarkers in clinical trials for motor neuron disease.

The interest and research into disease-related biomarkers has greatly accelerated over the last 10 years. The potential clinical benefits for disease-specific biomarkers include a more rapid and accurate disease diagnosis, and potential reduction in size and duration of clinical drug trials, which would speed up drug development. The application of biomarkers into the clinical arena of motor neuron disease should both determine if a drug hits its proposed target and whether the drug alters the course of disease. This article will highlight the progress made in discovering suitable biomarker candidates from a variety of sources, including imaging, neurophysiology and proteomics. For biomarkers to have clinical utility, specific criteria must be satisfied. While there has been tremendous effort to discover biomarkers, very few have been translated to the clinic. The bottlenecks in the biomarker pipeline will be highlighted as well as lessons that can be learned from other disciplines, such as oncology.

The sex ratio in amyotrophic lateral sclerosis: A population based study.

Replicable risk factors for ALS include increasing age, family history and being male. The male: female ratio has been reported as being between 1 and 3. We tested the hypothesis that the sex ratio changes with age in a population register covering the south-east of England. The sex ratio before and after the age of 51 years was compared using a Z-test for proportions. Kendall's tau was used to assess the relationship between age group and sex ratio using incidence and prevalence data. Publicly available data from Italian and Irish population registers were compared with results. There was a significant difference in the proportion of females with ALS between those in the younger group (30.11%) and those in the older group (43.66%) (p = 0.013). The adjusted male: female ratio dropped from 2.5 in the younger group to 1.4 in the older group using prevalence data (Kendall's tau = -0.73, p = 0.039). Similar ratios were found in the Italian but not the Irish registry. We concluded that sex ratios in ALS may change with age. Over-representation of younger patients in clinic registers may explain the variation in sex ratios between studies. Menopause may also play a role.

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS: Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS: The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION: The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

Mutations in FUS, an RNA processing protein, cause familial amyotrophic lateral sclerosis type 6.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that is familial in 10% of cases. We have identified a missense mutation in the gene encoding fused in sarcoma (FUS) in a British kindred, linked to ALS6. In a survey of 197 familial ALS index cases, we identified two further missense mutations in eight families. Postmortem analysis of three cases with FUS mutations showed FUS-immunoreactive cytoplasmic inclusions and predominantly lower motor neuron degeneration. Cellular expression studies revealed aberrant localization of mutant FUS protein. FUS is involved in the regulation of transcription and RNA splicing and transport, and it has functional homology to another ALS gene, TARDBP, which suggests that a common mechanism may underlie motor neuron degeneration.

A longitudinal study of diffusion tensor MRI in ALS.

In this study, we investigated whether diffusion tensor MRI (DTI) could detect progressive corticospinal tract degeneration in amyotrophic lateral sclerosis (ALS) and whether changes in diffusion variables reflected clinical deterioration. Twenty-three ALS patients and 25 healthy volunteers underwent whole brain DTI. Patients and a subset (n = 12) of controls returned for a second scan. Clinical measures of disease severity were assessed in the ALS group. Changes in fractional anisotropy (FA) and mean diffusivity (MD) were measured along the corticospinal tract using a region of interest approach. Adequate DTI data were available in 11 ALS patients and 11 controls at two time points. FA and MD differed significantly between ALS patients and controls at both time points, but neither changed significantly over time, while global measures of disease severity in patients increased with time. Although we confirmed that DTI detects corticospinal tract damage in ALS, there were no significant changes in diffusion measures over time. The sensitivity of DTI may be improved by advanced data analysis techniques, although the high dropout rate suggests that use of MRI as a biomarker in ALS may be restricted to earlier stages of disease.