Dexmedetomidine - Commonly Used in Functional Imaging Studies - Increases Susceptibility to Seizures in Rats But Not in Wild Type Mice.

Functional MRI (fMRI) utilizes changes in metabolic and hemodynamic signals to indirectly infer the underlying local changes in neuronal activity. To investigate the mechanisms of fMRI responses, spontaneous fluctuations, and functional connectivity in the resting-state, it is important to pursue fMRI in animal models. Animal studies commonly use dexmedetomidine sedation. It has been demonstrated that potent sensory stimuli administered under dexmedetomidine are prone to inducing seizures in Sprague-Dawley (SD) rats. Here we combined optical imaging of intrinsic signals and cerebral blood flow with neurophysiological recordings to measure responses in rat area S1FL to electrical forepaw stimulation administered at 8 Hz. We show that the increased susceptibility to seizures starts no later than 1 h and ends no sooner than 3 h after initiating a continuous administration of dexmedetomidine. By administering different combinations of anesthetic and sedative agents, we demonstrate that dexmedetomidine is the sole agent necessary for the increased susceptibility to seizures. The increased susceptibility to seizures prevails under a combination of 0.3-0.5% isoflurane and dexmedetomidine anesthesia. The blood-oxygenation and cerebral blood flow responses to seizures induced by forepaw stimulation have a higher amplitude and a larger spatial extent relative to physiological responses to the same stimuli. The epileptic activity and the associated blood oxygenation and cerebral blood flow responses stretched beyond the stimulation period. We observed seizures in response to forepaw stimulation with 1-2 mA pulses administered at 8 Hz. In contrast, responses to stimuli administered at 4 Hz were seizure-free. We demonstrate that such seizures are generated not only in SD rats but also in Long-Evans rats, but not in C57BL6 mice stimulated with similar potent stimuli under dexmedetomidine sedation. We conclude that high-amplitude hemodynamic functional imaging responses evoked by peripheral stimulation in rats sedated with dexmedetomidine are possibly due to the induction of epileptic activity. Therefore, caution should be practiced in experiments that combine the administration of potent stimuli with dexmedetomidine sedation. We propose stimulation paradigms that elicit seizure-free, well detectable neurophysiological and hemodynamic responses in rats. We further conclude that the increased susceptibility to seizures under dexmedetomidine sedation is species dependent.

Proximal femur segmentation in conventional pelvic x ray.

A solid and accurate proximal femur segmentation technique using the popular active shape model (ASM) is proposed. For generating an optimal shape prior, the minimum description length, based on 200 supervised manual segmented proximal femur shapes, is used. The segmentation is based on a coarse to fine scaling technique including a profile scale space method. The segmentation results are compared using an optimal defined initial pose and a pose based on a registration technique. Using ideal template initialization, 95% of the shapes have been recovered exactly (average point-to-point error approximately 13 pixels, average point-to-boundary error approximately 7 pixels). Using a template-based initialization based on a registration technique, a successful segmentation rate of approximately 89% is achieved, with an average point-to-point error approximately 12 pixels, and an average point-to-boundary error approximately 8 pixels. With an adequate template initialization and an improved ASM, this method seems to provide an accurate tool for segmentation of the proximal femur shapes on conventional hip overview x-ray images.

Knowledge-based femur detection in conventional radiographs of the pelvis.

In this paper we present a knowledge-based femur detection algorithm. The algorithm uses femur corpus constraints, Canny edge detection and Hough lines. For optimal femur template placement in the local area we use cross-correlation. The segmentation itself is done with an optimized active shape modeling technique. Using the knowledge-based technique we have located 95% of the femur shapes of N=117 X-rays. From those 83% of the target femur shapes have been segmented successfully (point-to-point error: approximately 14 pixels, point-to-boundary error = approximately 9 pixels).

Electrocardiologic and related methods of non-invasive detection and risk stratification in myocardial ischemia: state of the art and perspectives.

BACKGROUND: Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia. OBJECTIVES: To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. METHODS: In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology. RESULTS: Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients. CONCLUSIONS: There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine.

Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution.

Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.