Veterans Administration Medical Center San Francisco

San Francisco, CA, United States

Veterans Administration Medical Center San Francisco

San Francisco, CA, United States
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Lo R.,Loma Linda University | Chia K.K.M.,University of Sydney | Hsia H.H.,Veterans Administration Medical Center San Francisco
Cardiac Electrophysiology Clinics | Year: 2017

Ventricular arrhythmias are a significant cause of morbidity and mortality in patients with ischemic structural heart disease. Endocardial and epicardial mapping strategies include scar characterization channel identification, and recording and ablation of late potentials and local abnormal ventricular activities. Catheter ablation along with new technology and techniques of bipolar ablation, needle catheter, and autonomic modulation may increase efficacy in difficult to ablate ventricular arrhythmias. Catheter ablation of ventricular arrhythmias seem to confer mortality and morbidity benefits in patients with ischemic heart disease. © 2016


Tosun D.,University of California at San Francisco | Tosun D.,Veterans Administration Medical Center San Francisco | Joshi S.,University of Utah | Weiner M.W.,University of California at San Francisco | Weiner M.W.,Veterans Administration Medical Center San Francisco
Annals of Neurology | Year: 2013

Objective To identify a neuroimaging signature predictive of brain amyloidosis as a screening tool to identify individuals with mild cognitive impairment (MCI) that are most likely to have high levels of brain amyloidosis or to be amyloid-free. Methods The prediction model cohort included 62 MCI subjects screened with structural magnetic resonance imaging (MRI) and 11C-labeled Pittsburgh compound B positron emission tomography (PET). We identified an anatomical shape variation-based neuroimaging predictor of brain amyloidosis and defined a structural MRI-based brain amyloidosis score (sMRI-BAS). Amyloid beta positivity (Aβ+) predictive power of sMRI-BAS was validated on an independent cohort of 153 MCI patients with cerebrospinal fluid Aβ1-42 biomarker data but no amyloid PET scans. We compared the Aβ+ predictive power of sMRI-BAS to those of apolipoprotein E (ApoE) genotype and hippocampal volume, the 2 most relevant candidate biomarkers for the prediction of brain amyloidosis. Results Anatomical shape variations predictive of brain amyloidosis in MCI embraced a characteristic spatial pattern known for high vulnerability to Alzheimer disease pathology, including the medial temporal lobe, temporal-parietal association cortices, posterior cingulate, precuneus, hippocampus, amygdala, caudate, and fornix/stria terminals. Aβ+ prediction performance of sMRI-BAS and ApoE genotype jointly was significantly better than the performance of each predictor separately (area under the curve [AUC] = 0.88 vs AUC = 0.70 and AUC = 0.81, respectively) with >90% sensitivity and specificity at 20% false-positive rate and false-negative rate thresholds. Performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (AUC = 0.56). Interpretation As one of the first attempts to use an imaging technique that does not require amyloid-specific radioligands for identification of individuals with brain amyloidosis, our findings could lead to development of multidisciplinary/ multimodality brain amyloidosis biomarkers that are reliable, minimally invasive, and widely available. © 2013 American Neurological Association.

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