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We have developed a wireless, wearable Doppler ultrasound system that continuously measures the common carotid artery Doppler pulse. A novel measure from this device, the Doppler shock index, accurately detected moderate-to-severe central blood volume loss in a human hemorrhage model generated by lower body negative pressure. In this analysis, we tested whether the wearable Doppler could identify only mild-to-moderate central blood volume loss.Eleven healthy volunteers were recruited and studied in a physiology laboratory at the Mayo Clinic. Each participant underwent a lower body negative protocol in duplicate. Carotid Doppler measures including Doppler shock indices were compared with blood pressure and the shock index for their ability to detect both 10% and 20% reductions in stroke volume.All carotid Doppler measures were better able to detect diminishing stroke volume than either systolic or mean arterial pressure. Falling carotid artery corrected flow time and rising heart rate/corrected flow time (DSI FTc ) were the most sensitive measures for detecting 10% and 20% stroke volume reductions, respectively. The area under the receiver operator curves (AUROCs) for all shock indices was at least 0.86; however, the denominators of the two Doppler shock indices (i.e., the corrected flow time and velocity time integral) had AUROCs ranging between 0.81 and 0.9, while the denominator of the traditional shock index (i.e., systolic blood pressure) had AUROCs between 0.54 and 0.7.The wearable Doppler ultrasound was able to continuously measure the common carotid artery Doppler pulse. Carotid Doppler measures were highly sensitive at detecting both 10% and 20% stroke volume reduction. All shock indices performed well in their diagnostic ability to measure mild-to-moderate central volume loss, although the denominators of both Doppler shock indices individually outperformed the denominator of the traditional shock index.Diagnostic test or criteria; Level III.

A hands-free continuous wave (CW) Doppler ultrasound patch has been developed for noninvasive assessment of carotid stroke volume. The patch enables easy, continuous monitoring, which is particularly useful in a fast-paced setting such as the intensive care unit. In vitro validation of the measurement of relative change in velocity was performed with a flow phantom for a maximum velocity range of 10–150 cm/s, showing good agreement, with average errors of 2.1% and 3.9% for constant and pulsatile flow, respectively. In a pilot clinical demonstration, a recording was made during on-pump coronary artery bypass surgery. The recorded maximum velocity trace was compared with the peristaltic pulsation frequency, showing that the patch tracked the large changes in pump flow rate. Notably, in the seconds following the changes in pump flow, clear differences were observed, consistent with cerebral autoregulation. Further investigations are ongoing into other metrics of carotid flow and stroke volume, and into the clinical utility of the device for assessing fluid responsiveness.

Purpose We describe the temporal concordance of 3 hemodynamic monitors. Materials and methods Healthy volunteers performed preload changes while simultaneously wearing a non-invasive, pulse-contour stroke volume (SV) monitor, a bioreactance SV monitor and a wireless, wearable Doppler ultrasound patch over the common carotid artery. The sensitivity and specificity for detecting preload change over 3 temporal windows (early, middle and late) was assessed. Results 40 preload changes were recorded in total (20 increase, 20 decrease). Immediately, the wearable Doppler had high sensitivity (100%) and specificity (100%) for detecting preload change with an area under the receiver operator curve (AUROC) of 0.98 for both velocity time integral (VTI, 10.5% threshold) and corrected flow time (FTc, 2.5% threshold). The sensitivity, specificity and AUROC for non-invasive pulse contour were equally good (9% SV threshold). For bioreactance, a 13% SV threshold immediately detected preload change with a sensitivity, specificity and AUROC of 60%, 95% and 0.75, respectively. After two SV outputs following preload change, the sensitivity, specificity and AUROC of bioreactance improved to 70%, 90% and 0.85, respectively. Conclusions Carotid Doppler ultrasound and non-invasive pulse contour detected rapid hemodynamic change with equal accuracy; bioreactance improved over time. Algorithm-lag should be considered when interpreting clinical studies.

HYPOTHESIS The cochlear A-value measurement exhibits significant inter- and intraobserver variability, and its accuracy is dependent on the visualization method in clinical computed tomography (CT) images of the cochlea. BACKGROUND An accurate estimate of the cochlear duct length (CDL) can be used to determine electrode choice, and frequency map the cochlea based on the Greenwood equation. Studies have described estimating the CDL using a single A-value measurement, however the observer variability has not been assessed. METHODS Clinical and micro-CT images of 20 cadaveric cochleae were acquired. Four specialists measured A-values on clinical CT images using both standard views and multiplanar reconstructed (MPR) views. Measurements were repeated to assess for intraobserver variability. Observer variabilities were evaluated using intra-class correlation and absolute differences. Accuracy was evaluated by comparison to the gold standard micro-CT images of the same specimens. RESULTS Interobserver variability was good (average absolute difference: 0.77 ± 0.42 mm) using standard views and fair (average absolute difference: 0.90 ± 0.31 mm) using MPR views. Intraobserver variability had an average absolute difference of 0.31 ± 0.09 mm for the standard views and 0.38 ± 0.17 mm for the MPR views. MPR view measurements were more accurate than standard views, with average relative errors of 9.5 and 14.5%, respectively. CONCLUSION There was significant observer variability in A-value measurements using both the standard and MPR views. Creating the MPR views increased variability between experts, however MPR views yielded more accurate results. Automated A-value measurement algorithms may help to reduce variability and increase accuracy in the future.

Hypothesis Evaluation of cochlear duct length (CDL) using novel imaging techniques will help improve the accuracy of existing CDL equations. Background Various relationships relating A value measured from a patient's computed tomography scan and CDL have been proposed to aid in preoperative electrode selection and frequency mapping. Methods Ten cadaveric temporal bones were scanned using synchrotron radiation phase-contrast imaging. Reference CDL values were calculated by placing points representing the organ of Corti (OC), lateral wall (LW), and electrode location (I) on the synchrotron radiation phase-contrast imaging slices along the length of the cochlea. The CDL estimates from the existing three equations (OC, LW, I) in addition to two newly proposed equations (OC and LW) were compared with reference CDL values at each respective location. Results When compared with reference CDL values, the new OC equation improved the CDL estimates from a 6.2% error to a 5.1% error while the new LW equation improved the CDL estimate error from 3.9 to 3.6%. Bland-Altman plots revealed both new equations increased similarity to reference values and brought more samples to within clinically significant ranges. Validation of the original electrode location equation to the reference values showed a 4.6% difference. Conclusion The newly proposed equations for LW and OC provided an improvement over past equations for determining CDL from the A value by showing improved agreement with reference values. Therefore, these equations can provide quick and accurate preoperative estimates of CDL for improving customized frequency mapping.

High-resolution images of the cochlea are used to develop atlases to extract anatomical features from low-resolution clinical computed tomography (CT) images. We compare visualization and contrast of conventional absorption-based micro-CT to synchrotron radiation phase contrast imaging (SR-PCI) images of whole unstained, nondecalcified human cochleae. Three cadaveric cochleae were imaged using SR-PCI and micro-CT. Images were visually compared and contrast-to-noise ratios (CNRs) were computed from n = 27 regions-of-interest (enclosing soft tissue) for quantitative comparisons. Three-dimensional (3D) models of cochlear internal structures were constructed from SR-PCI images using a semiautomatic segmentation method. SR-PCI images provided superior visualization of soft tissue microstructures over conventional micro-CT images. CNR improved from 7.5 ± 2.5 in micro-CT images to 18.0 ± 4.3 in SR-PCI images (p < 0.0001). The semiautomatic segmentations yielded accurate reconstructions of 3D models of the intracochlear anatomy. The improved visualization, contrast and modelling achieved using SR-PCI images are very promising for developing atlas-based segmentation methods for postoperative evaluation of cochlear implant surgery.

Delivery of angiogenic growth factors lessens ischemia in preclinical models but has demonstrated little benefit in patients with peripheral vascular disease. Augmenting the wrapping of nascent microvessels by mural cells constitutes an alternative strategy to regenerating a functional microvasculature, particularly if integrated with a sustained delivery platform. Herein, electrospun poly(ester amide) (PEA) nanofiber mats are fabricated for delivering a mural cell-targeting factor, fibroblast growth factor 9 (FGF9). Proof-of-principle is established by placing FGF9/FGF2-loaded PEA fiber mats on the chick chorioallantoic membrane and identifying enhanced angiogenesis by 3D power Doppler micro-ultrasound imaging. To assess the delivery system in ischemic muscle, FGF9-loaded PEA fiber mats are implanted onto the surface of the tibialis anterior muscle of mice with hindlimb ischemia. The system supplies FGF9 into the tibialis anterior muscle and yields a neo-microvascular network with enhanced mural cell coverage up to 28 days after injury. The regenerating muscle that receives FGF9 display near-normal sized myofibers and reduced interstitial fibrosis. Moreover, the mice demonstrate improved locomotion. These findings of locally released FGF9 from PEA nanofibers raise prospects for a microvascular remodeling approach to improve muscle health in peripheral vascular disease.

Accurate estimates of the pars-tensa (PT) Young’s modulus (EPT) are required in finite-element (FE) modeling studies of the middle ear. Previously, we introduced an in-situ EPT estimation technique by optimizing a sample-specific FE model to match experimental eardrum pressurization data. This optimization process requires choosing some modeling assumptions such as PT thickness and boundary conditions. These assumptions are reported with a wide range of variation in the literature, hence affecting the reliability of the models. In addition, the sensitivity of the estimated EPT to FE modeling assumptions has not been studied. Therefore, the objective of this study is to identify the most influential modeling assumption on EPT estimates. The middle-ear cavity extracted from a cadaveric temporal bone was pressurized to 500 Pa. The deformed shape of the eardrum after pressurization was measured using a Fourier transform profilometer (FTP). A base-line FE model of the unpressurized middle ear was created. The EPT was estimated using golden section optimization method, which minimizes the cost function comparing the deformed FE model shape to the measured shape after pressurization. The effect of varying the modeling assumptions on EPT estimates were investigated. This included the change in PT thickness, pars flaccida Young’s modulus and possible FTP measurement error. The most influential parameter on EPT estimation was PT thickness and the least influential parameter was pars flaccida Young’s modulus. The results of this study provide insight into how different parameters affect the results of EPT optimization and which parameters’ uncertainties require further investigation to develop robust estimation techniques.

Background There has been renewed interest in the cochlear duct length (CDL) for preoperative cochlear implant electrode selection and postoperative generation of patient-specific frequency maps. The CDL can be estimated by measuring the A-value, which is defined as the length between the round window and the furthest point on the basal turn. Unfortunately, there is significant intra- and inter-observer variability when these measurements are made clinically. The objective of this study was to develop an automated A-value measurement algorithm to improve accuracy and eliminate observer variability. Method Clinical and micro-CT images of 20 cadaveric cochleae specimens were acquired. The micro-CT of one sample was chosen as the atlas, and A-value fiducials were placed onto that image. Image registration (rigid affine and non-rigid B-spline) was applied between the atlas and the 19 remaining clinical CT images. The registration transform was applied to the A-value fiducials, and the A-value was then automatically calculated for each specimen. High resolution micro-CT images of the same 19 specimens were used to measure the gold standard A-values for comparison against the manual and automated methods. Results The registration algorithm had excellent qualitative overlap between the atlas and target images. The automated method eliminated the observer variability and the systematic underestimation by experts. Manual measurement of the A-value on clinical CT had a mean error of 9.5 ± 4.3% compared to micro-CT, and this improved to an error of 2.7 ± 2.1% using the automated algorithm. Both the automated and manual methods correlated significantly with the gold standard micro-CT A-values (r = 0.70, p

Photoacoustic (PA) imaging has been proposed for cancer treatment monitoring. Tumor oxygen saturation (sO 2 ) should in principle be related to vascular parameters such as blood flow. In this work, in-vivo PA estimates of sO 2 were compared to power Doppler (pD) measures of vascularity hours after the administration of microbubbles (MB), radiation therapy (XRT), individually or combined (MB-XRT).

Photoacoustic (PA) imaging of tumor oxygenation can be used to monitor vascular-targeted novel therapies. This study examines how a combination treatment, ultrasound-microbubbles (USMB)/radiation-therapy (XRT) alters oxygen saturation (sO2) estimates, which are then compared to power Doppler (PD) assessments of tumor vascularity. SCID mice were inoculated with subcutaneous, hind-leg PC3 tumors. The treatment consisted of XRT/MB (XRT: 8Gy/single-fraction; USMB: 3%/500 kHz/570kPa; n=3), USMB (n=3) and XRT (n=5) alone and untreated control (n=5). PA/PD imaging was acquired pre-treatment and 2h/24h post-treatment using the VevoLAZR (21 MHz, 750/850 nm). The volumetric tumor sO2 was quantified using histogram distributions and the average mode was computed. The vascularization index (VI), a PD metric of tumor vessel density, was studied along with the sO2 mode by comparing changes at 2h with pre-treatment. Mice whose pre-treatment sO2 levels were over 65%, exhibited a 15% drop in oxygenation at 2h, remaining unchanged by 24h. Examining the sO2 and VI relationships revealed differences between the groups. All groups (except control) exhibited a positive correlation when the ∆VI was plotted as a function of ∆sO2 (r2≥0.85). Mice in the XRT/MB group had the largest slope (11.7) suggesting that a change in sO2 was accompanied by the largest change in vessel density. The slope of the USMB and XRT treatments was 5.6 and 2.9, respectively. The combination treatment induced the largest changes in vessel density and sO2. Early PA estimates of tumor oxygenation appear to correlate with the treatment-induced vascular changes. Such measure could potentially be used for predicting treatment outcome.

High resolution images are used as a basis for finite-element modeling of the middle-ear structures to study their biomechanical function. Commonly used imaging techniques such as micro-computed tomography (CT) and optical microscopy require extensive sample preparation, processing or staining using contrast agents to achieve sufficient soft-tissue contrast. We compare imaging of middle-ear structures in unstained, non-decalcified human temporal bones using conventional absorption-contrast micro-CT and using synchrotron radiation phase-contrast imaging (SR-PCI). Four cadaveric temporal bones were imaged using SR-PCI and conventional micro-CT. Images were qualitatively compared in terms of visualization of structural details and soft-tissue contrast using intensity profiles and histograms. In order to quantitatively compare SR-PCI to micro-CT, three-dimensional (3D) models of the ossicles were constructed from both modalities using a semi-automatic segmentation method as these structures are clearly visible in both types of images. Volumes of the segmented ossicles were computed and compared between the two imaging modalities and to estimates from the literature. SR-PCI images provided superior visualization of soft-tissue microstructures over conventional micro-CT images. Intensity profiles emphasized the improved contrast and detectability of soft-tissue in SR-PCI in comparison to absorption-contrast micro-CT. In addition, the semi-automatic segmentations of SR-PCI images yielded accurate 3D reconstructions of the ossicles with mean volumes in accord with volume estimates from micro-CT images and literature. Sample segmentations of the ossicles and soft tissue structures were provided on an online data repository for benefit of the research community. The improved visualization, modeling accuracy and simple sample preparation make SR-PCI a promising tool for generating reliable FE models of the middle-ear structures, including both soft tissues and bone.

The wall-filter selection curve method is proposed to objectively identify a cut-off velocity that minimizes artifacts in power Doppler images. A selection curve, which is constructed by plotting the color pixel density (CPD) as a function of the cut-off velocity, exhibits characteristic intervals hypothesized to include the optimum cut-off velocity. This article presents an improved implementation of the method that automatically detects characteristic intervals in a selection curve and selects an operating point cut-off velocity along a characteristic interval. The method is applied to subregions within the Doppler image to adapt the cut-off velocity to local variations in vascularity. The method's performance is evaluated in 30-MHz power Doppler images of a four-vessel flow phantom. At high (>5 mm/s) flow velocities, qualitative improvements in vessel delineation are achieved and the CPD in the resulting images is accurate to within 3% of the vascular volume fraction of the phantom.

Operator-dependent settings such as the wall filter cut-off frequency control the incidence of artifacts in Doppler images and limit the reliability of comparisons of Doppler vascular indices across longitudinal studies. To address this problem, the wall filter selection curve (WFSC) method was developed to objectively select the cut-off frequency. This paper reports the first evaluation of the effectiveness of the WFSC method for imaging a tumor model. 3-D power Doppler data were acquired from murine breast cancer tumors over a six-week study and the WFSC method was applied to select a cut-off frequency for the wall filter. Images reconstructed using the WFSC method were compared to images processed using a fixed cut-off frequency. Selection curves for tumor images were consistent with flow-phantom data from previous studies. The mean WFSC-selected cut-off showed significant variation among images acquired at different time points from each tumor (two-way ANOVA, p < 0.0001), which demonstrates the relevance of adjusting the cut-off frequency to match changing flow conditions. 3-D images processed using the WFSC method depicted additional vascular structures compared to volumes processed using a fixed cut-off frequency. Therefore, the WFSC method can facilitate acquisition of reliable Doppler images by inexperienced or time-sensitive operators.

The wall-filter selection curve (WFSC) method was developed to automatically select cut-off velocities for high-frequency power Doppler imaging. Selection curves are constructed by plotting color pixel density (CPD) as a function of wall filter cut-off velocity. A new three-component mathematical model is developed to guide the design of an online implementation of the method for in vivo imaging. The model treats Doppler imaging as a signal detection task in which the scanner must distinguish intravascular pixels from perivascular and extravascular pixels and includes a cost function to identify the optimum cut-off velocity that provides accurate vascular quantification and minimizes the effect of color pixel artifacts on visualization of vascular structures. The goodness of fit of the three-component model to flow-phantom data is significantly improved compared to a previous two-component model (F test, p < 0:005). Simulations using the new model indicate that selection curves should be sampled using at least 100 cut-off velocities to ensure robust performance of the automated WFSC method and determine an upper bound on CPD variability that ensures reliable vascular quantification accuracy, defined as CPD within 5% of the reference vascular volume fraction. Results of the simulations also provide evidence that limiting the selection of the cut-off velocity to a binary choice between the middle and right end of the characteristic interval is sufficient to meet the quantification accuracy goal. The model provides an intuitive, empirical description of the relationship between system settings and blood-flow detection performance in power Doppler imaging.

The wall‐filter selection curve method has been enhanced to improve detection and interpretation of color pixel density (CPD) plateaus. The improved algorithm was developed by analyzing data acquired from three fields of view in a four‐vessel flow phantom using a 30‐MHz swept‐scan transducer. An N‐point maximum envelope peak search applied to the first difference of CPD detects selection curve plateaus by incorporating criteria that identify intervals of minimum variation in CPD. Selection curves for regions of interest (ROIs) containing multiple vessels can be difficult to interpret, so the algorithm subdivides the image into small ROIs, constructs selection curves for each ROI, and sums the resulting vascularity estimates. The lower limit on ROI size is constrained by a need to avoid ROIs that are completely filled by blood. A multiple‐step decision algorithm was designed that considers the number, length, and slope of each plateau to identify the cutoff velocity that yields the best vascularity estimate. At high (> 5 mm/s) flow velocities, the decision algorithm yielded a summed CPD that was within 5% of the vascular volume fraction in each field of view. These improvements are an initial step toward automating wall‐filter cutoff settings in a power Doppler system.