Semiautomated Software to Improve Stability and Reduce Operator-Induced Variation in Vascular Ultrasound Speckle Tracking.

OBJECTIVES: Ultrasound is useful in predicting arteriovenous fistula (AVF) maturation, which is essential for hemodialysis in end-stage renal disease patients. We developed ultrasound software that measures circumferential vessel wall strain (distensibility) using conventional ultrasound Digital Imaging and Communications in Medicine (DICOM) data. We evaluated user-induced variability in measurement of arterial wall distensibility and upon finding considerable variation we developed and tested 2 methods for semiautomated measurement. METHODS: Ultrasound scanning of arteries of 10 subjects scheduled for AVF surgery were performed. The top and bottom of the vessel wall were tracked using the Kanade-Lucas-Tomasi (KLT) feature-tracking algorithm over the stack of images in the DICOM cine loops. The wall distensibility was calculated from the change of vessel diameter over time. Two semiautomated methods were used for comparison. RESULTS: The location of points selected by users for the cine loops varied significantly, with a maximum spread of up to 120 pixels (7.8 mm) for the top and up to 140 pixels (9.1 mm) for the bottom of the vessel wall. This variation in users' point selection contributed to the variation in distensibility measurements (ranging from 5.63 to 41.04%). Both semiautomated methods substantially reduced variation and were highly correlated with the median distensibility values obtained by the 10 users. CONCLUSIONS: Minimizing user-induced variation by standardizing point selection will increase reproducibility and reliability of distensibility measurements. Our recent semiautomated software may help expand use in clinical studies to better understand the role of vascular wall compliance in predicting the maturation of fistulas.

Joint camera blur and pose estimation from aliased data.

A joint-estimation algorithm is presented that enables simultaneous camera blur and pose estimation from a known calibration target in the presence of aliasing. Specifically, a parametric maximum-likelihood (ML) point-spread function estimate is derived for characterizing a camera's optical imperfections through the use of a calibration target in an otherwise loosely controlled environment. The imaging perspective, ambient-light levels, target reflectance, detector gain and offset, quantum efficiency, and read-noise levels are all treated as nuisance parameters. The Cramér-Rao bound is derived, and simulations demonstrate that the proposed estimator achieves near optimal mean squared error performance. The proposed method is applied to experimental data to validate the fidelity of the forward models as well as to establish the utility of the resulting ML estimates for both system identification and subsequent image restoration.

Theoretical performance assessment and empirical analysis of super-resolution under unknown affine sensor motion.

This paper deals with super-resolution (SR) processing and associated theoretical performance assessment for under-sampled video data collected from a moving imaging platform with unknown motion and assuming a relatively flat scene. This general scenario requires joint estimation of the high-resolution image and the parameters that determine a projective transform that relates the collected frames to one another. A quantitative assessment of the variance in the random error as achieved through a joint-estimation approach (e.g., SR image reconstruction and motion estimation) is carried out via the general framework of M-estimators and asymptotic statistics. This approach provides a performance measure on estimating the fine-resolution scene when there is a lack of perspective information and represents a significant advancement over previous work that considered only the more specific scenario of mis-registration. A succinct overview of the theoretical framework is presented along with some specific results on the approximate random error for the case of unknown translation and affine motions. A comparison is given between the approximated random error and that actually achieved by an M-estimator approach to the joint-estimation problem. These results provide insight on the reduction in SR reconstruction accuracy when jointly estimating unknown inter-frame affine motion.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

BACKGROUND: A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. METHODS: Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. RESULTS: The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. CONCLUSIONS: The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

Development of open-source software for free-hand 3D vascular ultrasound: Dialysis fistula application.

BACKGROUND: The arteriovenous fistula (AVF) is the preferred vascular access for End Stage Renal Disease, having superior patency and lower infection risks than prosthetic graft and catheter access. When AVF dysfunction or delayed maturation does occur, the gold standard for diagnosis is the fistula angiogram (a.k.a. fistulogram). 3D ultrasound is available for obstetrical and other specialized uses, but it is cost prohibitive and has a field of view that is too small to cover the region of interest for the dialysis fistula application. We sought to develop a point of care 3D solution using freehand 2D ultrasound data acquisition. METHODS: We developed open-source software for 3D image reconstruction and projection of an angiogram-like image of the vascular access using a 2D freehand ultrasound scanner. We evaluated this software by comparing the ultrasound "sono-angiogram" images to fistulogram images in five subjects, using visual inspection and by applying the Percent of Exact Match (PEM) as a statistic test. RESULTS: The sono-angiograms showed identifiable characteristics that matched the fistulogram results in all five subjects. The PEM ranged between 42.8% and 77.0%, with Doppler and grayscale ultrasound data, showing complementary advantages and disadvantages when used for sono-angiogram image construction. Motion from freehand ultrasound acquisition was a significant source of mismatch. 3D image generation is a potential advantage with ultrasound data. CONCLUSIONS: While further work is needed to improve the accuracy with free hand scanning, fistulogram-like "sono-angiograms" can be generated using point of care 2D ultrasound. Methods such as these may be able to assist in point-of-care diagnosis in the future. The software is open-source, and importantly, the ultrasound data used are non-proprietary and available from any standard ultrasound machine. The simplicity and accessibility of this approach warrant further study.

Using wildland fire smoke modeling data in gerontological health research (California, 2007-2018).

Widespread population exposure to wildland fire smoke underscores the urgent need for new techniques to characterize fire-derived pollution for epidemiologic studies and to build climate-resilient communities especially for aging populations. Using atmospheric chemical transport modeling, we examined air quality with and without wildland fire smoke PM2.5. In 12-km gridded output, the 24-hour average concentration of all-source PM2.5 in California (2007-2018) was 5.16 µg/m3 (S.D. 4.66 µg/m3). The average concentration of fire-PM2.5 in California by year was 1.61 µg/m3 (~30% of total PM2.5). The contribution of fire-source PM2.5 ranged from 6.8% to 49%. We define a "smokewave" as two or more consecutive days with modeled levels above 35 µg/m3. Based on model-derived fire-PM2.5, 99.5% of California's population lived in a county that experienced at least one smokewave from 2007 to 2018, yet understanding of the impact of smoke on the health of aging populations is limited. Approximately 2.7 million (56%) of California residents aged 65+ years lived in counties representing the top 3 quartiles of fire-PM2.5 concentrations (2007-2018). For each year (2007-2018), grid cells containing skilled nursing facilities had significantly higher mean concentrations of all-source PM2.5 than cells without those facilities, but they also had generally lower mean concentrations of wildland fire-specific PM2.5. Compared to rural monitors in California, model predictions of wildland fire impacts on daily average PM2.5 carbon (organic and elemental) performed well most years but tended to overestimate wildland fire impacts for high-fire years. The modeling system isolated wildland fire PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding exposures for aging population in health studies.

Ultrasound Measurement of Vascular Distensibility Based on Edge Detection and Speckle Tracking Using Ultrasound DICOM Data.

This study presents an edge detection and speckle tracking (EDST) based algorithm to calculate distensibility as percentage of change of vessel diameter during cardiac cycles. Canny edge detector, Vandermonde matrix representation, Kanade Lucas Tomasi algorithm with pyramidal segmentation, and penalized least squares technique identifies the vessel lumen edge, track the vessel diameter, detrend the signal and find peaks and valleys when the vessel is fully distended or contracted. An upper extremity artery from 10 patients underwent an ultrasound examination as part of preoperative evaluation before arteriovenous fistula surgery. Three studies were performed to evaluate EDST with automatic peak and valley selection versus manual speckle selection of expert users using manual peak and valley selection. Results demonstrate the effectiveness of the proposed methodology, to obtain comparable results as those obtained by expert-users, and considerably reducing the variability associated with external factors such as excessive motion, fluctuations in stroke volume, beat-to-beat blood pressure changes, breathing cycles, and arm-transducer pressure.

Ultrasound speckle tracking to detect vascular distensibility changes from angioplasty and branch ligation in a radio-cephalic fistula: Use of novel open source software.

We used novel open source software, based on an ultrasound speckle tracking algorithm, to examine the distensibility of the vessel wall of the inflow artery, anastomosis, and outflow vein before and after two procedures. An 83-year-old white man with a poorly maturing radio-cephalic fistula received an angioplasty at the anastomosis followed by branch ligation 28 days later. Duplex Doppler measurements corroborated the blood flow related changes anticipated from the interventions. The experimental distensibility results showed that it is technically feasible to measure subtle vessel wall motion changes with high resolution (sub-millimeter) using standard Digital Imaging and Communications in Medicine (DICOM) ultrasound data, which are readily available on conventional ultrasound scanners. While this methodology was originally developed using high resolution radiofrequency from ultrasound data, the goal of this study was to use DICOM data, which makes this technology accessible to a wide range of users.

Sono-angiography for dialysis vascular access based on the freehand 2D ultrasound scanning.

INTRODUCTION: Dialysis vascular access, preferably an autogenous arteriovenous fistula, remains an end stage renal disease (ESRD) patient's lifeline providing a means of connecting the patient to the dialysis machine. Once an access is created, the current gold standard of care for maintenance of vascular access is angiography and angioplasty to treat stenosis. While point of care 2D ultrasound has been used to detect access problems, we sought to reproduce angiographic results comparable to the gold standard angiogram (fistulogram) using ultrasound data acquired from a conventional 2D ultrasound scanner. METHODS: A 2D ultrasound probe was used to acquire a series of cross sectional images of the vascular access including arteriovenous anastomosis of a subject with a radio-cephalic fistula. These 2D B-mode images were used for 3D vessel reconstruction by binary thresholding to categorize vascular versus non-vascular structures followed by standard image segmentation to select the structure representative of dialysis vascular access and morphologic filtering. Image processing was done using open source Python Software. RESULTS: The open source software was able to: (1) view the gold standard fistulogram images, (2) reconstruct 2D planar images of the fistula from ultrasound data as viewed from the top, analogous to computerized tomography images, and (3) construct a 2D representation of vascular access similar to the angiogram. CONCLUSION: We present a simple approach to obtain an angiogram-like representation of the vascular access from readily available, non-proprietary 2D ultrasound data in the point of care setting. While the sono-angiogram is not intended to replace angiography, it may be useful in providing 3D imaging at the point of care in the dialysis unit, outpatient clinic, or for pre-operative planning for interventional procedures. Future work will focus on improving the robustness and quality of the imaging data while preserving the straightforward freehand approach used for ultrasound data acquisition.

Detecting High-Resolution Intramural Vascular Wall Strain Signals Using DICOM Data.

Maintaining dialysis vascular access is a source of considerable morbidity in patients with end-stage renal disease (ESRD). High-resolution radiofrequency (RF) ultrasound vascular strain imaging has been applied experimentally in the vascular access setting to assist in diagnosis and management. Unfortunately, high-resolution RF data are not routinely accessible to clinicians. In contrast, the standard DICOM formatted B-mode ultrasound data are widely accessible. However, B-mode, representing the envelope of the RF signal, is of much lower resolution. If strain imaging could use open-source B-mode data, these imaging techniques could be more broadly investigated. We conducted experiments to detect wall strain signals with submillimeter tracking resolutions ranging from 0.2 mm (3 pixels) to 0.65 mm (10 pixels) using DICOM B-mode data. We compared this submillimeter tracking to the overall vascular distensibility as the reference measurements to see if high-strain resolution strain could be detected using open-source B-Mode data. We measured the best-fit coefficient of determination between signals, expressed as the percentage of strain waveforms that exhibited a correlation with a p value of 0.05 or less. The lowest percentage was 86.7%, and most were 90% and higher. This indicates high-resolution strain signals can be detected within the vessel wall using B-mode DICOM data.

Angioplasty Induced Changes in Dialysis Vascular Access Compliance.

Dialysis vascular access remains vitally important to maintain life and functional capacity with end stage renal disease. Angioplasty is an integral part of maintaining dialysis access function and patency. To understand the effect of angioplasty balloon dilation on vascular wall mechanics, we conducted a clinical study to evaluate the elastic modulus of the anastomosis in five subjects with anastomosis stenoses, before and after six angioplasty procedures, using B-mode ultrasound DICOM data. A novel and open source vascular ultrasound high-resolution speckle tracking software tool was used. The median lumen diameter increased from 3.4 to 5.5 mm after angioplasty. Meanwhile, the median elastic modulus of the 18 measurements at the anastomosis increased by 52.2%, from 2.24 × 103 to 3.41 × 103 mmHg. The results support our hypothesis that the structural changes induced in the vessel wall by balloon dilation lead to reduced vascular compliance and a higher elastic modulus of the vessel wall.

Sleep stage dynamics differ between children with and without obstructive sleep apnea.

STUDY OBJECTIVES: Analysis of sleep dynamics--distributions of contiguous sleep and sleep stage durations--reveal exponential distributions and potential clinical utility in adults. We sought to examine these polysomnographic variables for the first time in children, and in the context of childhood sleep disordered breathing (SDB). DESIGN AND SETTING: Analysis of polysomnographic data available from the Washtenaw County Adenotonsillectomy Cohort. PARTICIPANTS: Selected subjects were 48 children aged 5-12 years with SDB (pediatric apnea/hypopnea index > or = 1.5) who were scheduled for adenotonsillectomy and 20 control subjects of similar ages without SDB. Subjects were studied at enrollment and again one year later in almost all cases. RESULTS: Durations of sleep and specific sleep stage bouts generally followed exponential distributions. At baseline, the number of sleep stage changes, proportion of total sleep time occupied by stage 1 sleep, proportion stage 2 sleep, mean stage 2 duration, and mean stage REM duration each distinguished subjects with and without SDB (P < 0.05), but only mean stage 2 duration did so independently after accounting for the other variables (P = 0.03). At one-year follow-up, changes in total sleep time, mean stage 2 duration, and mean stage REM duration distinguished SDB from control subjects, but again only changes in mean stage 2 duration did so independently (P = 0.01). CONCLUSIONS: Durations of uninterrupted sleep and specific sleep stages appear to follow exponential distributions in children with or without SDB. Parameters that describe these distributions--particularly mean duration of stage 2 sleep periods--may provide useful additions to standard sleep stage analyses.

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California.

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-h average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007-2013) was 4.91 µg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 µg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 µg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California's population lived in a county that experienced at least one episode of high smoke exposure ("smokewave") from 2007-2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (-2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts.

Identifying the time of occurrence of a hamstring strain injury during treadmill running: a case study.

BACKGROUND: While hamstring strain injuries are common during sprinting, the mechanisms of injury are not well understood. In this study, we analyzed the running kinematics of an athlete obtained at the time of an acute hamstring strain injury. The purpose was to identify the period of the gait cycle during which the hamstring was likely injured, as well as to characterize the biomechanical conditions associated with the injury. METHODS: A male professional skier injured his right biceps femoris long head while running at 5.36 m/s on a treadmill with a 15% incline. Whole body kinematics were recorded at the time of injury. A linear periodic prediction model was used to determine when individual marker trajectories deviated from a cyclic periodic pattern, indicating the mechanical response to injury. A three-dimensional musculoskeletal model was used to compute joint angles and hamstring musculotendon lengths during the injurious running trial. These data were used with estimates of neuromuscular latencies and electromechanical delays to identify the most likely time period of injury. FINDINGS: Based upon the earliest indications in marker trajectories, a 130 ms period during the late swing phase of the gait cycle was identified as the period of injury. During this period, the biceps femoris reached a peak musculotendon length that was estimated to be 12% beyond the length seen in an upright posture and exceeded the normalized peak length of the medial hamstrings. INTERPRETATION: This case provides quantitative data suggesting that the biceps femoris muscle is susceptible to an lengthening contraction injury during the late swing phase of the running gait cycle.

Method for detection of respiratory cycle-related EEG changes in sleep-disordered breathing.

STUDY OBJECTIVES: In sleep-disordered breathing (SDB), visual or computerized analysis of electroencephalogram (EEG) signals shows that disruption of sleep architecture occurs in association with apneas and hypopneas. We developed a new signal analysis algorithm to investigate whether brief changes in cortical activity can also occur with individual respiratory cycles. DESIGN: Retrospective. SETTING: University sleep laboratory. PARTICIPANTS: A 6 year-old boy with SDB. INTERVENTION: Polysomnography before and after clinically indicated adenotonsillectomy. MEASUREMENTS: For the first 3 hours of nocturnal sleep, a computer algorithm divided nonapneic respiratory cycles into 4 segments and, for each, computed mean EEG powers within delta, theta, alpha, sigma, and beta frequency ranges. Differences between segment-specific EEG powers were tested by analysis of variance. Respiratory cycle-related EEG changes (RCREC) were quantified. RESULTS: Preoperative RCREC were statistically significant in delta (P < .0001), theta (P < .001), and sigma (P < .0001) but not alpha or beta (P > .01) ranges. One year after the operation, RCREC in all ranges showed statistical significance (P < .01), but delta, theta, and sigma RCREC had decreased, whereas alpha and beta RCREC had increased. Preoperative RCREC also were demonstrated in a sequence of 101 breaths that contained no apneas or hypopneas (P < .0001). Several tested variations in the signal-analysis approach, including analysis of the entire nocturnal polysomnogram, did not meaningfully improve the significance of RCREC. CONCLUSIONS: In this child with SDB, the EEG varied with respiratory cycles to a quantifiable extent that changed after adenotonsillectomy. We speculate that RCREC may reflect brief but extremely numerous microarousals.

Correlates of respiratory cycle-related EEG changes in children with sleep-disordered breathing.

STUDY OBJECTIVES: To explore newly-identified respiratory cycle-related electroencephalographic changes (RCREC), which may represent microarousals, as correlates of neurobehavioral outcomes in children with sleep-disordered breathing (SDB). DESIGN: Retrospective. SETTING: University sleep laboratory. PARTICIPANTS: Ten research subjects, aged 6 to 10 years, with and without SDB. INTERVENTION: Polysomnography, Multiple Sleep Latency Tests, and tests of auditory attention before and after clinically-indicated tonsillectomy (n = 9) or hernia repair (n = 1, control). MEASUREMENTS: For the first 3 hours of nocturnal sleep, a computer algorithm quantified the degree to which delta, theta, and alpha electroencephalographic power varied within non-apneic respiratory cycles. Correlations between the RCREC and standard objective measures of SDB, sleepiness, and attention were explored. RESULTS: Five children had SDB (> 1 obstructive apnea per hour of sleep). Preoperative delta, theta, or alpha RCREC were statistically significant (P < .01) in all subjects except 1 without SDB and the 1 control. Theta RCREC correlated with rates of apneas and hypopneas (P = .01) and decreased after the apnea was treated. Postoperative changes in delta and theta RCREC predicted changes in Multiple Sleep Latency Test scores (rho = -0.84, P = .002; rho = -0.64, P = .05), whereas changes in rates of apneas and hypopneas did not (rho = -0.24, P = .50). Postoperative changes in attention tended to correlate with changes in delta RCREC (rho = -0.54, P = .11) more strongly than with changes in rates of apneic events (rho = -0.07, P = .84). CONCLUSIONS: The RCREC may reflect brief but numerous microarousals that could help to explain neurobehavioral consequences of SDB.

Limited short-term prognostic utility of cerebral NIRS during neonatal therapeutic hypothermia.

OBJECTIVE: We evaluated the utility of amplitude-integrated EEG (aEEG) and regional oxygen saturation (rSO2) measured using near-infrared spectroscopy (NIRS) for short-term outcome prediction in neonates with hypoxic ischemic encephalopathy (HIE) treated with therapeutic hypothermia. METHODS: Neonates with HIE were monitored with dual-channel aEEG, bilateral cerebral NIRS, and systemic NIRS throughout cooling and rewarming. The short-term outcome measure was a composite of neurologic examination and brain MRI scores at 7 to 10 days. Multiple regression models were developed to assess NIRS and aEEG recorded during the 6 hours before rewarming and the 6-hour rewarming period as predictors of short-term outcome. RESULTS: Twenty-one infants, mean gestational age 38.8 ± 1.6 weeks, median 10-minute Apgar score 4 (range 0-8), and mean initial pH 6.92 ± 0.19, were enrolled. Before rewarming, the most parsimonious model included 4 parameters (adjusted R(2) = 0.59; p = 0.006): lower values of systemic rSO2 variability (p = 0.004), aEEG bandwidth variability (p = 0.019), and mean aEEG upper margin (p = 0.006), combined with higher mean aEEG bandwidth (worse discontinuity; p = 0.013), predicted worse short-term outcome. During rewarming, lower systemic rSO2 variability (p = 0.007) and depressed aEEG lower margin (p = 0.034) were associated with worse outcome (model-adjusted R(2) = 0.49; p = 0.005). Cerebral NIRS data did not contribute to either model. CONCLUSIONS: During day 3 of cooling and during rewarming, loss of physiologic variability (by systemic NIRS) and invariant, discontinuous aEEG patterns predict poor short-term outcome in neonates with HIE. These parameters, but not cerebral NIRS, may be useful to identify infants suitable for studies of adjuvant neuroprotective therapies or modification of the duration of cooling and/or rewarming.

Overcoming turbulence-induced space-variant blur by using phase-diverse speckle.

Space-variant blur occurs when imaging through volume turbulence over sufficiently large fields of view. Space-variant effects are particularly severe in horizontal-path imaging, slant-path (air-to-ground or ground-to-air) geometries, and ground-based imaging of low-elevation satellites or astronomical objects. In these geometries, the isoplanatic angle can be comparable to or even smaller than the diffraction-limited resolution angle. We report on a postdetection correction method that seeks to correct for the effects of space-variant aberrations, with the goal of reconstructing near-diffraction-limited imagery. Our approach has been to generalize the method of phase-diverse speckle (PDS) by using a physically motivated distributed-phase-screen model. Simulation results are presented that demonstrate the reconstruction of near-diffraction-limited imagery under both matched and mismatched model assumptions. In addition, we present evidence that PDS could be used as a beaconless wavefront sensor in a multiconjugate adaptive optics system when imaging extended scenes.