Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by electrical neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-Blinks (EB) and Cardiac Activity (CA) are two of the most common types of non-neuronal artifacts. They can be measured by affixing eye proximal electrodes, as in electrooculography (EOG) and chest electrodes, as in electrocardiography (EKG), however this complicates imaging setup, decreases patient comfort, and often induces further artifacts from facial twitching and postural muscle movement. We propose an EOG- and EKG-free approach to identify eye-blink, cardiac, or neuronal signals for automated artifact suppression. Our contributions are two-fold. First, we combine a data driven, multivariate decomposition approach based on Independent Component Analysis (ICA) and a highly accurate classifier constructed as a deep 1-D Convolutional Neural Network. Second, we visualize the features learned to reveal what features the model uses and to bolster user confidence in our model’s training and potential for generalization. We train and test three variants of our method on resting state MEG data from 49 subjects. Our cardiac model achieves a 96% sensitivity and 99% specificity on the set-aside test-set. Our eye-blink model achieves a sensitivity of 85% and specificity of 97%. This work facilitates automated MEG processing for both, clinical and research use, and can obviate the need for EOG or EKG electrodes.
Magnetoencephelography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from muscle activity often corrupts the data. Eye-blinks are one of the most common types of muscle artifact. They can be recorded by affixing eye proximal electrodes, as in electrooculography (EOG), however this complicates patient preparation and decreases comfort. Moreover, it can induce further muscular artifacts from facial twitching. We propose an EOG free, data driven approach. We begin with Independent Component Analysis (ICA), a well-known preprocessing approach that factors observed signal into statistically independent components. When applied to MEG, ICA can help separate neuronal components from non-neuronal ones, however, the components are randomly ordered. Thus, we develop a method to assign one of two labels, non-eye-blink or eye-blink, to each component. Our contributions are two-fold. First, we develop a 10-layer Convolutional Neural Network (CNN), which directly labels eye-blink artifacts. Second, we visualize the learned spatial features using attention mapping, to reveal what it has learned and bolster confidence in the method’s ability to generalize to unseen data. We acquired 8-min, eyes open, resting state MEG from 44 subjects. We trained our method on the spatial maps from ICA of 14 subjects selected randomly with expertly labeled ground truth. We then tested on the remaining 30 subjects. Our approach achieves a test classification accuracy of 99.67%, sensitivity: 97.62%, specificity: 99.77%, and ROC AUC: 98.69%. We also show the learned spatial features correspond to those human experts typically use which corroborates our model’s validity. This work (1) facilitates creation of fully automated processing pipelines in MEG that need to remove motion artifacts related to eye blinks, and (2) potentially obviates the use of additional EOG electrodes for the recording of eye-blinks in MEG studies.
Ischemic stroke is a rare yet devastating complication that may occur following cardiothoracic surgery. Fibrinolytic treatment is contraindicated due to elevated risk for hemorrhage. Mechanical thrombectomy entails a catheterized approach wherein the thrombus is physically removed from the vessel without the use of fibrinolytics, minimizing the possibility of intracranial hemorrhage. Here, we present two original cases of mechanical thrombectomy as treatment for patients experiencing emergent large vessel occlusion following cardiothoracic surgery. A literature review was conducted to determine current treatment guidelines, risk factors, and complications resulting from recanalization due to mechanical thrombectomy versus fibrinolytic therapy. One patient was admitted due to chronic, American College of Cardiology/American Heart Association stage D, New York Heart Association functional class IV heart failure and required complete, artificial hemodynamic support for two weeks and on the 19th day experienced neurologic decline secondary to a supraclinoid left internal carotid artery (ICA) occlusion. Mechanical thrombectomy resulted in distal reperfusion and neurologic improvement. The second patient presented with coronary artery disease and underwent triple coronary artery bypass grafting and endovein harvesting. On post-operative day 2, the patient experienced a left ICA occlusion extending to the cavernous ICA resulting in speech impairment and right-sided weakness. The patient was heparinized and underwent mechanical thrombectomy, resulting in immediate speech and muscle strength recovery. Medical advances allow mechanical thrombectomy to be performed in a timely and effective manner at specialized treatment centers. It offers endovascular treatment modalities to a unique patient population with postoperative stroke. In such patients, thrombectomy can safely provide reperfusion while reducing the risk of complications associated with conventional thrombolytics.
Carotid cavernous fistulae (CCF) are defined as abnormal connections between the carotid circulation and cavernous sinus. CCFs can be categorized as being direct or indirect. Direct CCFs are usually associated with trauma, whereas indirect CCFs are associated with revascularization following cavernous sinus thrombosis. We present a case of a 53-year-old male who presented with tinnitus, proptosis, conjunctivitis, and blurry vision. The patient had a recent endovascular transvenous embolization that was only partially successful, with a residual carotid cavernous fistula draining to the left superior ophthalmic vein and multiple cortical veins. A physical examination of the patient showed elevated intraocular pressures bilaterally. The patient had a high-flow indirect carotid cavernous fistula with bilateral superior ophthalmic vein (SOV) and retrograde cortical vein drainage. The SOV was punctured with a micropuncture needle and was used to successfully gain access to the cavernous sinus. Multiple coils were placed in the posterior aspect of the sinus until there was complete occlusion of venous flow. Coils were packed up to the posterior aspect of the orbit near the junction of the cavernous sinus with the SOV, and the embolization was successful. Indirect CCFs have gradual onset and are usually low-flow. Low-flow CCFs might improve with medical management.Some CCFs may cause ocular manifestations and can be symptomatically managed with prism therapy or ocular patching for diplopia, lubrication for keratopathy, or topical agents for elevated intraocular pressures. However, patients presenting with persistent ocular morbidity may require surgical or endovascular intervention.
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