Computed Ultrasound Tomography in Echo mode (CUTE) of speed of sound for diagnosis and for aberration correction in pulse-echo sonography

Sound speed as a diagnostic marker for various diseases of human tissue has been of interest for a while. Up to now, mostly transmission ultrasound computed tomography (UCT) was able to detect spatially resolved sound speed, and its promise as a diagnostic tool has been demonstrated. However, UCT is limited to acoustically transparent samples such as the breast. We present a novel technique where spatially resolved detection of sound speed can be achieved using conventional pulse-echo equipment in reflection mode. For this purpose, pulse-echo images are acquired under various transmit beam directions and a two-dimensional map of the sound speed is reconstructed from the changing phase of local echoes using a direct reconstruction method. Phantom results demonstrate that a high spatial resolution (1 mm) and contrast (0.5 % of average sound speed) can be achieved suitable for diagnostic purposes. In comparison to previous reflection-mode based methods, CUTE works also in a situation with only diffuse echoes, and its direct reconstruction algorithm enables real-time application. This makes it suitable as an addition to conventional clinical ultrasound where it has the potential to benefit diagnosis in a multimodal approach. In addition, knowledge of the spatial distribution of sound speed allows full aberration correction and thus improved spatial resolution and contrast of conventional B-mode ultrasound. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Autologous hematopoietic stem cell transplantation vs intravenous pulse cyclophosphamide in diffuse cutaneous systemic sclerosis: a randomized clinical trial

IMPORTANCE High-dose immunosuppressive therapy and autologous hematopoietic stem cell transplantation (HSCT) have shown efficacy in systemic sclerosis in phase 1 and small phase 2 trials. OBJECTIVE To compare efficacy and safety of HSCT vs 12 successive monthly intravenous pulses of cyclophosphamide. DESIGN, SETTING, AND PARTICIPANTS The Autologous Stem Cell Transplantation International Scleroderma (ASTIS) trial, a phase 3, multicenter, randomized (1:1), open-label, parallel-group, clinical trial conducted in 10 countries at 29 centers with access to a European Group for Blood and Marrow Transplantation-registered transplant facility. From March 2001 to October 2009, 156 patients with early diffuse cutaneous systemic sclerosis were recruited and followed up until October 31, 2013. INTERVENTIONS HSCT vs intravenous pulse cyclophosphamide. MAIN OUTCOMES AND MEASURES The primary end point was event-free survival, defined as time from randomization until the occurrence of death or persistent major organ failure. RESULTS A total of 156 patients were randomly assigned to receive HSCT (n = 79) or cyclophosphamide (n = 77). During a median follow-up of 5.8 years, 53 events occurred: 22 in the HSCT group (19 deaths and 3 irreversible organ failures) and 31 in the control group (23 deaths and 8 irreversible organ failures). During the first year, there were more events in the HSCT group (13 events [16.5%], including 8 treatment-related deaths) than in the control group (8 events [10.4%], with no treatment-related deaths). At 2 years, 14 events (17.7%) had occurred cumulatively in the HSCT group vs 14 events (18.2%) in the control group; at 4 years, 15 events (19%) had occurred cumulatively in the HSCT group vs 20 events (26%) in the control group. Time-varying hazard ratios (modeled with treatment × time interaction) for event-free survival were 0.35 (95% CI, 0.16-0.74) at 2 years and 0.34 (95% CI, 0.16-0.74) at 4 years. CONCLUSIONS AND RELEVANCE Among patients with early diffuse cutaneous systemic sclerosis, HSCT was associated with increased treatment-related mortality in the first year after treatment. However, HCST conferred a significant long-term event-free survival benefit. TRIAL REGISTRATION isrctn.org Identifier: ISRCTN54371254.

Real-time ultra-high optical coherence tomography monitoring of optical tissue effects caused by selective retina therapy

Purpose: Selective retina therapy (SRT) has shown great promise compared to conventional retinal laser photocoagulation as it avoids collateral damage and selectively targets the retinal pigment epithelium (RPE). Its use, however, is challenging in terms of therapy monitoring and dosage because an immediate tissue reaction is not biomicroscopically discernibel. To overcome these limitations, real-time optical coherence tomography (OCT) might be useful to monitor retinal tissue during laser application. We have thus evaluated a proprietary OCT system for its capability of mapping optical changes introduced by SRT in retinal tissue. Methods: Freshly enucleated porcine eyes, covered in DMEM upon collection were utilized and a total of 175 scans from ex-vivo porcine eyes were analyzed. The porcine eyes were used as an ex-vivo model and results compared to two time-resolved OCT scans, recorded from a patient undergoing SRT treatment (SRT Vario, Medical Laser Center Lübeck). In addition to OCT, fluorescin angiography and fundus photography were performed on the patient and OCT scans were subsequently investigated for optical tissue changes linked to laser application. Results: Biomicroscopically invisible SRT lesions were detectable in OCT by changes in the RPE / Bruch's complex both in vivo and the porcine ex-vivo model. Laser application produced clearly visible optical effects such as hyperreflectivity and tissue distortion in the treated retina. Tissue effects were even discernible in time-resolved OCT imaging when no hyper-reflectivity persisted after treatment. Data from ex-vivo porcine eyes showed similar to identical optical changes while effects visible in OCT appeared to correlate with applied pulse energy, leading to an additional reflective layer when lesions became visible in indirect ophthalmoscopy. Conclusions: Our results support the hypothesis that real-time high-resolution OCT may be a promising modality to obtain additional information about the extent of tissue damage caused by SRT treatment. Data shows that our exvivo porcine model adequately reproduces the effects occurring in-vivo, and thus can be used to further investigate this promising imaging technique.

A comprehensive discussion of HMBC pulse sequences. III. Solving the problem of missing and weakly observed long-range correlations

The intensity of long-range correlations observed with the classical HMBC pulse sequence using static optimization of the long-range coupling delay is directly related to the size of the coupling constant and is often set as a compromise. As such, some long-range correlations might appear with a reduced intensity or might even be completely absent from the spectra. After a short introduction, this third manuscript will give a detailed review of some selected HMBC variants dedicated to improve the detection of long-range correlations, such as the ACCORD-HMBC, CIGAR-HMBC, and Broadband HMBC experiments. Practical details about the accordion optimization, which affords a substantial improvement in both the number and intensity of the long-range correlations observed, but introduces a modulation in F1, will be discussed. The incorporation of the so-called constant time variable delay in the CIGAR-HMBC experiment, which can trigger or even completely suppress 1H–1H coupling modulation inherent to the utilization of the accordion principle, will be also discussed. The broadband HMBC scheme, which consists of recording a series of HMBC spectra with different delays set as a function of the long-range heteronuclear coupling constant ranges and transverse relaxation times T2, is also examined.

Time-Resolved Ultra–High Resolution Optical Coherence Tomography for Real-Time Monitoring of Selective Retina Therapy

Purpose: Selective retina therapy (SRT) is a novel treatment for retinal pathologies, solely targeting the retinal pigment epithelium (RPE). During SRT, the detection of an immediate tissue reaction is challenging as tissue effects remain limited to intracellular RPE photodisruption. Time-resolved ultra-high axial resolution optical coherence tomography (OCT) is thus evaluated for the monitoring of dynamic optical changes at and around the RPE during SRT. Methods: An experimental OCT system with an ultra-high axial resolution of 1.78 µm was combined with an SRT system and time-resolved OCT M-scans of the target area were recorded from four patients undergoing SRT. OCT scans were analyzed and OCT morphology was correlated with findings in fluorescein angiography, fundus photography and cross-sectional OCT. Results: In cases where the irradiation caused RPE damage proven by fluorescein angiography, the lesions were well discernible in time-resolved OCT images but remained invisible in fundus photography and cross-sectional OCT acquired after treatment. If RPE damage was introduced, all applied SRT pulses led to detectable signal changes in the time-resolved OCT images. The extent of optical signal variation seen in the OCT data appeared to scale with the applied SRT pulse energy. Conclusion: The first clinical results proved that successful SRT irradiation induces detectable changes in the OCT M-scan signal while it remains invisible in conventional ophthalmoscopic imaging. Thus, real-time high-resolution OCT is a promising modality to monitor and analyze tissue effects introduced by selective retina therapy and may be used to guide SRT in an automatic feedback mode.

Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

Time-domain ptychography

Through dedicated measurements in the optical regime we demonstrate that ptychography can be applied to reconstruct complex-valued object functions that vary with time from a sequence of spectral measurements. A probe pulse of approximately 1 ps duration, time delayed in increments of 0.25 ps, is shown to recover dynamics on a ten times faster time scale with an experimental limit of approximately 5 fs.

Ptychographic ultrafast pulse reconstruction

We demonstrate a new ultrafast pulse reconstruction modality that is somewhat reminiscent of frequency-resolved optical gating but uses a modified setup and a conceptually different reconstruction algorithm that is derived from ptychography. Even though it is a second-order correlation scheme, it shows no time ambiguity. Moreover, the number of spectra to record is considerably smaller than in most other related schemes which, together with a robust algorithm, leads to extremely fast convergence of the reconstruction.

Pulse-shaping assisted multidimensional coherent electronic spectroscopy

Understanding nuclear and electronic dynamics of molecular systems has advanced considerably by probing their nonlinear responses with a suitable sequence of pulses. Moreover, the ability to control crucial parameters of the excitation pulses, such as duration, sequence, frequency, polarization, slowly varying envelope, or carrier phase, has led to a variety of advanced time-resolved spectroscopic methodologies. Recently, two-dimensional electronic spectroscopy with ultrashort pulses has become a more and more popular tool since it allows to obtain information on energy and coherence transfer phenomena, line broadening mechanisms, or the presence of quantum coherences in molecular complexes. Here, we present a high fidelity two-dimensional electronic spectroscopy setup designed for molecular systems in solution. It incorporates the versatility of pulse-shaping methods to achieve full control on the amplitude and phase of the individual exciting and probing pulses. Selective and precise amplitude- and phase-modulation is shown and applied to investigate electronic dynamics in several reference molecular systems.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Iodine speciation at time series station DYFAMED

Iodine speciation analysis was carried out upon seawater samples collected in July 1993 at the DYFAMED station (43 °25?N, 7 °52?E) located in the northwestern Mediterranean Sea. Dissolved iodate and iodide were directly determined by differential pulse polarography and cathodic stripping square wave voltammetry, respectively, and organically bound iodine was estimated by wet-chemical oxidation with sodium hypochlorite. Iodate is the predominant species ranging from 416 nM in surface waters to 480 nM in bottom waters. Iodide is present in significant concentrations up to 60 nM in surface waters, undetectable between 500 and 1000 m depth and present in very low but measurable concentrations (about 6 nM) in deep waters. The vertical profile of total free iodine demonstrates observable removal from surface waters, slight enrichment at about 200 m depth and constant there below. Up to 40 nM of organically bound iodine has been estimated between 20 to 30 m. Factorial analysis of different iodine species with biologically relevant parameters provided strong evidence for iodine biophilic features.

(Table 1) Sea-surface temperatures, intermediate-water temperatures, and latitudinal gradient at three time slices at the end of the Cretaceous

Climatic and oceanographic variations during the last 2 m.y. of the Maastrichtian inferred from high-resolution (10 k.y.) stable isotope analysis of the mid-latitude South Atlantic Deep Sea Drilling Project Site 525 reveal a major warm pulse followed by rapid cooling prior to the Cretaceous-Tertiary boundary. Between 66.85 and 65.52 Ma, cool but fluctuating temperatures average 9.9 and 15.4°C in intermediate and surface waters, respectively. This interval is followed by an abrupt short-term warming between 65.45 and 65.11 Ma, which increased temperatures by 2-3°C in intermediate waters, and decreased the vertical thermal gradient to an average of 2.7°C. This warm pulse may be linked to increased atmospheric pCO2, increased poleward heat transport, and the switch of an intermediate water source from high to low-middle latitudes. During the last 100 k.y. of the Maastrichtian, intermediate and surface temperatures decreased by an average of 2.1 and 1.4°C, respectively, compared to the maximum temperature between 65.32 and 65.24 Ma.