Temporal and spectral properties of esophageal mucosal blood perfusion: a comparison between normal subjects and nutcracker esophagus patients.

BACKGROUND: The mechanism of esophageal pain in patients with nutcracker esophagus (NE) and other esophageal motor disorders is not known. Our recent study shows that baseline esophageal mucosal perfusion, measured by laser Doppler perfusion monitoring, is lower in NE patients compared to controls. The goal of our current study was to perform a more detailed analysis of esophageal mucosal blood perfusion (EMBP) waveform of NE patients and controls to determine the optimal EMBP biomarkers that combined with suitable statistical learning models produce robust discrimination between the two groups. METHODS: Laser Doppler recordings of 10 normal subjects (mean age 43 ± 15 years, 8 males) and 10 patients (mean age 47 ± 5.5 years., 8 males) with NE were analyzed. Time and frequency domain features were extracted from the first twenty-minute recordings of the EMBP waveforms, statistically ranked according to four independent evaluation criterions, and analyzed using two statistical learning models, namely, logistic regression (LR) and support vector machines (SVM). KEY RESULTS: The top three ranked predictors between the two groups were the 0.5 and 0.75 perfusion quantile values followed by the surface of the EMBP power spectrum in the frequency domain. ROC curve ranking produced a cross-validated AUC (area under the curve) of 0.93 for SVM and 0.90 for LR. CONCLUSIONS & INFERENCES: We show that as a group NE patients have lower perfusion values compared to controls, however, there is an overlap between the two groups, suggesting that not all NE patients suffer from low mucosal perfusion levels.

Measurement of peak esophageal luminal cross-sectional area utilizing nadir intraluminal impedance.

BACKGROUND: Multichannel intraluminal impedance (MII) is currently used to monitor gastroesophageal reflux and esophageal bolus clearance. We describe a novel methodology to measure maximal luminal cross-sectional area (CSA) during bolus transport from MII measurements. METHODS: Studies were conducted in-vitro (test tubes) and in-vivo (healthy subjects). Concurrent MII, high resolution manometry, and intraluminal ultrasound (US) images were recorded 7-cm above the lower esophageal sphincter. Swallows with two concentrations of saline, 0.1 and 0.5 N, of bolus volumes 5, 10, and 15 cc were performed. The CSA was estimated by solving two algebraic Ohm's law equations, resulting from the two saline solutions. The CSA calculated from impedance method was compared with the CSA measured from the intraluminal US images. KEY RESULTS: The CSA measured in duplicate from B-mode US images showed a mean difference between the two manual delineations to be near zero, and the repeatability coefficient was within 7.7% of the mean of the two CSA measurements. The calculated CSA from the impedance measurements strongly correlated with the US measured CSA (R(2) ≅ 0.98). A detailed statistical analysis of the impedance and US measured CSA data indicated that the 95% limits of agreement between the two methods ranged from -9.1 to 13 mm(2) . The root mean square error of the two measurements was 4.8% of the mean US-measured CSA. CONCLUSIONS & INFERENCES: We describe a novel methodology to measure peak esophageal luminal CSA from the nadir impedance during peristalsis. Further studies are needed to determine if it is possible to measure patterns of luminal distension during peristalsis across the entire length of the esophagus from the MII recordings.

The use of the Kalman filter in the automated segmentation of EIT lung images.

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging.

Simulation of cardiac motion on non-Newtonian, pulsating flow development in the human left anterior descending coronary artery.

This study aimed at investigating the effect of myocardial motion on pulsating blood flow distribution of the left anterior descending coronary artery in the presence of atheromatous stenosis. The moving 3D arterial tree geometry has been obtained from conventional x-ray angiograms obtained during the heart cycle and includes a number of major branches. The geometry reconstruction model has been validated against projection data from a virtual phantom arterial tree as well as with CT-based reconstruction data for the same patient investigated. Reconstructions have been obtained for a number of temporal points while linear interpolation has been used for all intermediate instances. Blood has been considered as a non-Newtonian fluid. Results have been obtained using the same pulse for the inlet blood flow rate but with fixed arterial tree geometry as well as under steady-state conditions corresponding to the mean flow rate. Predictions indicate that myocardial motion has only a minor effect on flow distribution within the arterial tree relative to the effect of the blood pressure pulse.