Background
The study was conducted to investigate the diagnostic performance of infrared (IR) imaging of the breast using an interpretive model derived from a scoring system.

Methods
The study was approved by the Institutional Review Board of our hospital. A total of 276 women (mean age = 50.8 years, SD 11.8) with suspicious findings on mammograms or ultrasound received IR imaging of the breast before excisional biopsy. The interpreting radiologists scored the lesions using a scoring system that combines five IR signs. The ROC (receiver operating characteristic) curve and AUC (area under the ROC curve) were analyzed by the univariate logistic regression model for each IR sign and an age-adjusted multivariate logistic regression model including 5 IR signs. The cut-off values and corresponding sensitivity, specificity, Youden's Index (Index = sensitivity+specificity-1), positive predictive value (PPV), negative predictive value (NPV) were estimated from the age-adjusted multivariate model. The most optimal cut-off value was determined by the one with highest Youden's Index.

Results
For the univariate model, the AUC of the ROC curve from five IR signs ranged from 0.557 to 0.701, and the AUC of the ROC from the age-adjusted multivariate model was 0.828. From the ROC derived from the multivariate model, the sensitivity of the most optimal cut-off value would be 72.4% with the corresponding specificity 76.6% (Youden's Index=0.49), PPV 81.3% and NPV 66.4%.

Conclusions
We established an interpretive age-adjusted multivariate model for IR imaging of the breast. The cut-off values and the corresponding sensitivity and specificity can be inferred from the model in a subpopulation for diagnostic purpose. Trial Registration: NCT00166998.

Background
Physiological experiments have shown that the mean arterial blood pressure (MAP) can not be regulated after chemo and cardiopulmonary receptor denervation. Neuro-physiological information suggests that the nucleus tractus solitarius (NTS) is the only structure that receives information from its rostral neural nuclei and from the cardiovascular receptors and projects to nuclei that regulate the circulatory variables.

Methods
From a control theory perspective, to answer if the cardiovascular regulation has a set point, we should find out whether in the cardiovascular control there is something equivalent to a comparator evaluating the error signal (between the rostral projections to the NTS and the feedback inputs). The NTS would function as a comparator if: a) its lesion suppresses cardiovascular regulation; b) the negative feedback loop still responds normally to perturbations (such as mechanical or electrical) after cutting the rostral afferent fibers to the NTS; c) perturbation of rostral neural structures (RNS) to the NTS modifies the set point without changing the dynamics of the elicited response; and d) cardiovascular responses to perturbations on neural structures within the negative feedback loop compensate for much faster than perturbations on the NTS rostral structures.

Results
From the control theory framework, experimental evidence found currently in the literature plus experimental results from our group was put together showing that the above-mentioned conditions (to show that the NTS functions as a comparator) are satisfied.

Conclusions
Physiological experiments suggest that long-term blood pressure is regulated by the nervous system. The NTS functions as a comparator (evaluating the error signal) between its RNS and the cardiovascular receptor afferents and projects to nuclei that regulate the circulatory variables. The mean arterial pressure (MAP) is regulated by the feedback of chemo and cardiopulmonary receptors and the baroreflex would stabilize the short term pressure value to the prevailing carotid MAP. The discharge rates of rostral neural projections to the NTS would function as the set point of the closed and open loops of cardiovascular control. No doubt, then, the RNS play a functional role not only under steady-state conditions, but also in different behaviors and pathologies.

Background
Arterial pressure waveforms contain important diagnostic and physiological information since their contour depends on a healthy cardiovascular system [1]. A sensor was placed at the measured artery and some contact pressure was used to measure the pressure waveform. However, where is the location of the sensor just about enough to detect a complete pressure waveform for the diagnosis? How much contact pressure is needed over the pulse point? These two problems still remain unresolved.

Method
In this study, we propose a quantitative analysis to evaluate the pressure waveform for locating the position and applying the appropriate force between the sensor and the radial artery. The two-axis mechanism and the modified sensor have been designed to estimate the radial arterial width and detect the contact pressure. The template matching method was used to analyze the pressure waveform. In the X-axis scan, we found that the arterial diameter changed waveform (ADCW) and the pressure waveform would change from small to large and then back to small again when the sensor was moved across the radial artery. In the Z-axis scan, we also found that the ADCW and the pressure waveform would change from small to large and then back to small again when the applied contact pressure continuously increased.

Results
In the X-axis scan, the template correlation coefficients of the left and right boundaries of the radial arterial width were 0.987 +/- 0.016 and 0.978 +/- 0.028, respectively. In the Z-axis scan, when the excessive contact pressure was more than 100 mm Hg, the template correlation was below 0.983. In applying force, when using the maximum amplitude as the criteria level, the lower contact pressure (r = 0.988 +/- 0.004) was better than the higher contact pressure (r = 0.976 +/- 0.012). Conclusions: Although, the optimal detective position has to be close to the middle of the radial arterial, the pressure waveform also has a good completeness with a template correlation coefficient of above 0.99 when the position was within +/-1 mm of the middle of the radial arterial range. In applying force, using the maximum amplitude as the criteria level, the lower contact pressure was better than the higher contact pressure.

Background
Interruption of cardiopulmonary resuscitation (CPR) impairs the perfusion of the fibrillating heart, worsening the chance for successful defibrillation. Therefore ECG-analysis during ongoing chest compression could provide a considerable progress in comparison with standard analysis techniques working only during "hands-off" intervals.

Methods
For the reduction of CPR-related artefacts in ventricular fibrillation ECG we use a localized version of the coherent line removal algorithm developed by Sintes and Schutz. This method can be used for removal of periodic signals with sufficiently coupled harmonics, and can be adapted to specific situations by optimal choice of its parameters (e.g., the number of harmonics considered for analysis and reconstruction). Our testing was done with 14 different human ventricular fibrillation (VF) ECGs, whose fibrillation band lies in a frequency range of [1 Hz, 5 Hz]. The VF-ECGs were mixed with 12 different ECG-CPR-artefacts recorded in an animal experiment during asystole. The length of each of the ECG-data was chosen to be 20 sec, and testing was done for all 168=14x12 pairs of data. VF-to-CPR ratio was chosen as -20 dB, -15 dB, -10 dB, -5 dB, 0 dB, 5 dB and 10 dB. Here -20 dB corresponds to the highest level of CPR-artefacts.

Results
For non-optimized coherent line removal based on signals with a VF-to-CPR ratio of -20 dB, -15 dB, -10 dB, -5 dB and 0 dB, the signal-to-noise gains (SNR-gains) were 9.3 +/- 2.4 dB, 9.4 +/- 2.4 dB, 9.5 +/- 2.5 dB, 9.3 +/- 2.5 dB and 8.0 +/- 2.7 (mean +/- std, n=168), respectively. A typical example would be an original VF-to-CPR ratio of -10 dB, corresponding to a variance ratio var(VF):var(CPR)= 1:10. An improvement by 9.5 dB would result in a restored VF-to-CPR ratio of -0.5 dB, corresponding to a variance ratio var(VF):var(CPR)= 1:1.1, the variance of the CPR in the signal being reduced by a factor of 8.9.

Discussion
The localized coherent line removal algorithm uses the information in the ECG only, in contrast to multi-channel algorithms, which need additional information such as thorax impedance, blood pressure, or pressure exerted on the sternum during CPR. Predictors of defibrillation success such as mean and median frequency of VF-ECGs containing CPR-artefacts are prone to being governed by the harmonics of the artefacts. Reduction of CPR-artefacts is therefore necessary for determining reliable values for estimators of defibrillation success.

Conclusions
The localized coherent line removal algorithm reduces CPR-artefacts in VF-ECG, but does not eliminate them. It uses the ECG-channel only, without any additional information (like blood pressure). Our SNR-improvements are in the same range as offered by multichannel methods of Rheinberger et al., Husoy et al. and Aase et al. Additional developments are necessary before the algorithm can be tested in real CPR situations.

Background
Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.

Methods
This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.

Results
The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.

Conclusions
The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.