Differences in the angiographic evaluation of coiled cerebral aneurysms between a core laboratory reader and operators: results of the Cerecyte Coil Trial.

BACKGROUND AND PURPOSE: Independent evaluation of angiographic images is becoming widely applied in the assessment of treatment outcomes of cerebral aneurysms. In the current study, we assessed the agreement between an independent core laboratory and the operators regarding angiographic appearance in a recent randomized, controlled trial. MATERIALS AND METHODS: Data were derived from the Cerecyte Coil Trial. Angiographic images of each coiled aneurysm, taken immediately after embolization and at 5- to 7-month follow-up, were evaluated by the operator at the treating center and by an independent neuroradiologist at the core laboratory. For the purpose of this study, images were interpreted on a 3-point scale to provide uniformity for analysis; grade 1: complete occlusion, grade 2: neck remnant; and grade 3: sac filling. "Unfavorable angiographic appearance" was defined as grade 3 at follow-up or interval worsening of grade between the 2 time points. RESULTS: The study included 434 aneurysms. Immediately after embolization, grade 3 was reported by operators in 39 (9%) compared with 52 (12%) by the core laboratory (P = .159). On follow-up, grade 3 was reported by operators in 44 (10%) compared with 81 (19%) by the core laboratory (P < .0001). Overall, operators noted unfavorable angiographic appearance in 78 (18%) compared with 134 (31%) by the core laboratory (P < .0001). At every time point, agreement between the core laboratory and the operators was slight. CONCLUSIONS: Unfavorable angiographic appearance was noted almost twice as frequently by an independent core laboratory as compared with the operators. Planning of trials and interpretation of published studies should be done with careful attention to the mode of angiographic appearance interpretation.

Coil type does not affect angiographic follow-up outcomes of cerebral aneurysm coiling: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: Previous studies varied in their conclusions about the superiority of second-generation coils compared with bare platinum. In this systematic review and meta-analysis, we assessed differences in reported unfavorable angiographic outcomes of cerebral aneurysms treated with coil embolization as a function of coil type. MATERIALS AND METHODS: This systematic review covered 1999-2011 through the use of Ovid MEDLINE and EMBASE. Search terms were "subarachnoid hemorrhage," "intracranial aneurysms," "endovascular treatment," and "coiling." Inclusion criteria were studies reporting >50 aneurysms with imaging follow-up. We defined "unfavorable angiographic outcome" as either "recanalization," <90% occlusion, or "incomplete occlusion" at follow-up. Rates of unfavorable outcomes were pooled through the use of random effects models and compared across various coil types. Multivariate random effects meta-regression models were used to further explore the differences in outcomes related to coil type. RESULTS: We included 82 studies, comprising 90 patient cohorts, among which, 65 (72%) used bare platinum coils, 8 (8.9%) used Matrix, 11 (12%) used HydroCoil, and 6 (6.7%) used Cerecyte. The overall unfavorable outcome rate was 19% (95% CI: 17%,21%). Unfavorable outcome rates were 20% (95% CI: 17%, 22%) for bare platinum coils, 23% (95% CI: 16%, 29%) for Matrix, 15% (95% CI: 9%, 21%) for HydroCoil, and 15% (95% CI: 7%, 23%) for Cerecyte, respectively. The difference in unfavorable outcome rates among the various coil types was not statistically significant after adjusting for baseline characteristics, including aneurysm size, rupture status, and follow-up duration. CONCLUSIONS: The rate of unfavorable angiographic outcomes was not statistically different across the major approved coil types. The quality of the evidence, however, remains low because of high heterogeneity, small sample size, and potential publication bias.

Effect of core laboratory and multiple-reader interpretation of angiographic images on follow-up outcomes of coiled cerebral aneurysms: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: Reported rates of recanalization following coil embolization vary widely across studies. Some confounders are known to affect outcomes but others remain questionable. In the current study, we assess differences in reported angiographic outcomes for cerebral aneurysms treated with coil embolization as a function of single vs multiple readers and site investigator vs core laboratory settings. MATERIALS AND METHODS: Our systematic review covered 1999-2011 by using Ovid MEDLINE and EMBASE. Search terms were subarachnoid hemorrhage, intracranial aneurysms, endovascular treatment, and coiling. Inclusion criteria were >50 aneurysms and available imaging follow-up. Study characteristics of interest were readers at the treating site(s) or at an independent core imaging facility, single vs multiple readers, number of aneurysms treated, mean aneurysm size, mean follow-up time, coil type, initial rupture status, and angiographic follow-up. We defined "unfavorable angiographic outcome" as either "recanalization," <90% occlusion, or "incomplete occlusion." RESULTS: There were 104 (2.6%) of 4022 studies that fulfilled our inclusion criteria, comprising a total of 22,134 treated aneurysms, of which 15,969 (72.1%) had reported angiographic follow-up. The overall unfavorable outcome rate was 17.8% (2955/15,969 aneurysms). Eight (7.7%) of 104 studies reported core laboratory readings in which the pooled rate of unfavorable outcomes was 0.23 (95% CI, 0.19-0.28) compared with 0.16 (95% CI, 0.14-0.18) in readings from the treating sites (P < .001). The multivariate meta-regression suggested that core laboratory interpretation was significant for unfavorable outcomes (OR, 5.60; 95% CI, 2.01-15.60; P = .001), after adjustment for initial rupture status, aneurysm size, follow-up duration, and coil type. No significant association was found with use of multiple readers. CONCLUSIONS: Core laboratory studies tend to report higher rates of unfavorable outcomes compared with self-reported studies.

Signal quality indices and data fusion for determining clinical acceptability of electrocardiograms.

A completely automated algorithm to detect poor-quality electrocardiograms (ECGs) is described. The algorithm is based on both novel and previously published signal quality metrics, originally designed for intensive care monitoring. The algorithms have been adapted for use on short (5-10 s) single- and multi-lead ECGs. The metrics quantify spectral energy distribution, higher order moments and inter-channel and inter-algorithm agreement. Seven metrics were calculated for each channel (84 features in all) and presented to either a multi-layer perceptron artificial neural network or a support vector machine (SVM) for training on a multiple-annotator labelled and adjudicated training dataset. A single-lead version of the algorithm was also developed in a similar manner. Data were drawn from the PhysioNet Challenge 2011 dataset where binary labels were available, on 1500 12-lead ECGs indicating whether the entire recording was acceptable or unacceptable for clinical interpretation. We re-annotated all the leads in both the training set (1000 labelled ECGs) and test dataset (500 12-lead ECGs where labels were not publicly available) using two independent annotators, and a third for adjudication of differences. We found that low-quality data accounted for only 16% of the ECG leads. To balance the classes (between high and low quality), we created extra noisy data samples by adding noise from PhysioNet's noise stress test database to some of the clean 12-lead ECGs. No data were shared between training and test sets. A classification accuracy of 98% on the training data and 97% on the test data were achieved. Upon inspection, incorrectly classified data were found to be borderline cases which could be classified either way. If these cases were more consistently labelled, we expect our approach to achieve an accuracy closer to 100%.

Temporal and spatial complexity measures for electroencephalogram based brain-computer interfacing.

There has been much interest recently in the concept of using information from the motor cortex region of the brain, recorded using non-invasive scalp electrodes, to construct a crude interface with a computer. It is known that movements of the limbs, for example, are accompanied by desynchronisations and synchronisations within the scalp-recorded electroencephalogram (EEG). These event-related desynchronisations and synchronisations (ERD and ERS), however, appear to be present when volition to move a limb occurs, even when actual movement of the limb does not in fact take place. The determination and classification of the ERD/S offers many exciting possibilities for the control of peripheral devices via computer analysis. To date most effort has concentrated on the analysis of the changes in absolute frequency content of signals recorded from the motor cortex. The authors present results which tackle the issues of both the interpretation of changes in signals with time and across channels with simple methods which monitor the temporal and spatial 'complexity' of the data. Results are shown on synthetic and real data sets.

Stochastic complexity measures for physiological signal analysis.

Traditional feature extraction methods describe signals in terms of amplitude and frequency. This paper takes a paradigm shift and investigates four stochastic-complexity features. Their advantages are demonstrated on synthetic and physiological signals; the latter recorded during periods of Cheyne-Stokes respiration, anesthesia, sleep, and motor-cortex investigation.