Quantitative ultrasound assessment of fatty infiltration of the rotator cuff muscles using backscatter coefficient.

Background: To prospectively evaluate ultrasound backscatter coefficients (BSCs) of the supraspinatus and infraspinatus muscles and compare with Goutallier classification on magnetic resonance imaging (MRI).

Methods: Fifty-six participants had shoulder MRI exams and ultrasound exams of the supraspinatus and infraspinatus muscles. Goutallier MRI grades were determined and BSCs were measured.

Influences of Variability in Attenuation Compensation on the Estimation of Backscatter Coefficient of Median Nerves in Vivo.

Objective: Peripheral nerves remain a challenging target for medical imaging, given their size, anatomical complexity, and structural heterogeneity. Quantitative ultrasound (QUS) applies a set of techniques to estimate tissue acoustic parameters independent of the imaging platform. Many useful medical and laboratory applications for QUS have been reported, but challenges remain for deployment in vivo, especially for heterogeneous tissues.

Longitudinal Imaging of Injured Spinal Cord Myelin and White Matter with 3D Ultrashort Echo Time Magnetization Transfer (UTE-MT) and Diffusion MRI.

Quantitative MRI techniques could be helpful to noninvasively and longitudinally monitor dynamic changes in spinal cord white matter following injury, but imaging and postprocessing techniques in small animals remain lacking. Unilateral C5 hemisection lesions were created in a rat model, and ultrashort echo time magnetization transfer (UTE-MT) and diffusion-weighted sequences were used for imaging following injury. Magnetization transfer ratio (MTR) measurements and preferential diffusion along the longitudinal axis of the spinal cord were calculated as fractional anisotropy or an apparent diffusion coefficient ratio over transverse directions.

Neurovascular crossing patterns between leash of Henry and deep branch of radial nerve: implications for neurointervention and diagnostic imaging.

Objective: To detail the neurovascular crossing patterns between the leash of Henry (LoH) and the deep branch of the radial nerve (DBRN) in supination and pronation of the forearm, using imaging methods with anatomic correlation.

Materials And Methods: This cross-sectional study was performed ex vivo with HRUS and MRI with anatomic correlation on 6 samples and in vivo with HRUS with Doppler on 55 participants scanned bilaterally. The in vivo participants were enrolled over a 6-month period.

Post-mortem Tissue Degassing Using Positive Pressure Is Superior to Negative Pressure.

Objective: To compare the effectiveness of positive pressure (PP) and negative pressure (NP) for reducing gas inclusions in biological tissues in preparation for acoustic imaging.

Methods: Eighteen pieces of porcine liver in degassed saline were included in this study. For the PP group (n = 9 samples), a wristwatch waterproof tester was used to pressurize samples to 0.

Ultrasound attenuation of cortical bone correlates with biomechanical, microstructural, and compositional properties.

Background: We investigated the relationship of two commonly used quantitative ultrasound (QUS) parameters, speed of sound (SoS) and attenuation coefficient (α), with water and macromolecular contents of bovine cortical bone strips as measured with ultrashort echo time (UTE) magnetic resonance imaging (MRI).

Methods: SoS and α were measured in 36 bovine cortical bone strips utilizing a single-element transducer with nominal 5 MHz center frequency based on the time of flight principles after accommodating for reflection losses. Specimens were then scanned using UTE MRI to measure total, bound, and pore water proton density (TWPD, BWPD, and PWPD) as well as macromolecular proton fraction and macromolecular transverse relaxation time (T2-MM).

High-frequency Quantitative Ultrasound Imaging of Human Rotator Cuff Muscles: Assessment of Repeatability and Reproducibility.

This study evaluated the repeatability and reproducibility of using high-frequency quantitative ultrasound (QUS) measurement of backscatter coefficient (BSC), grayscale analysis, and gray-level co-occurrence matrix (GLCM) textural analysis, to characterize human rotator cuff muscles. The effects of varying scanner settings across two different operators and two US systems were investigated in a healthy volunteer with normal rotator cuff muscles and a patient with chronic massive rotator cuff injury and substantial muscle degeneration. The results suggest that BSC is a promising method for assessing rotator cuff muscles in both control and pathological subjects, even when operators were free to adjust system settings (depth, level of focus, and time-gain compensation).

Quantitative evaluation of rat sciatic nerve degeneration using high-frequency ultrasound.

In this study, we evaluated the utility of using high-frequency ultrasound to non-invasively track the degenerative process in a rat model of peripheral nerve injury. Primary analyses explored spatial and temporal changes in quantitative backscatter coefficient (BSC) spectrum-based outcomes and B-mode textural outcomes, using gray level co-occurrence matrices (GLCMs), during the progressive transition from acute to chronic injury. As secondary analyses, correlations among GLCM and BSC spectrum-based parameters were evaluated, and immunohistochemistry were used to suggest a structural basis for ultrasound outcomes.

Skeletal Muscle Assessment Using Quantitative Ultrasound: A Narrative Review.

Ultrasound (US) is an important imaging tool for skeletal muscle analysis. The advantages of US include point-of-care access, real-time imaging, cost-effectiveness, and absence of ionizing radiation. However, US can be highly dependent on the operator and/or US system, and a portion of the potentially useful information carried by raw sonographic data is discarded in image formation for routine qualitative US.

Regression analysis of logistic model with latent variables.

We propose a joint modeling approach to investigating the effects of social-psychological factors on the onset of depression. The proposed model comprises two components. The first one is a confirmatory factor analysis model that summarizes latent factors through multiple correlated observed variables.

Repeatability, Reproducibility and Sources of Variability in the Assessment of Backscatter Coefficient and Texture Parameters from High-Frequency Ultrasound Acquisitions in Human Median Nerve.

Ultrasound (US) is an increasingly prevalent and effective diagnostic modality for neuromuscular imaging. Gray-scale B-mode imaging has been the dominant US approach to evaluating nerves qualitatively or making morphometric measurements of nerves, providing important insights into pathological changes for conditions such as carpal tunnel syndrome. Among more recent ultrasound strategies, high-frequency ultrasound (often defined as >15 MHz for clinical applications), quantitative ultrasound and image textural analysis offer promising enhancements for improved and more objective approaches to nerve imaging.

Double bias correction for high-dimensional sparse additive hazards regression with covariate measurement errors.

We propose an inferential procedure for additive hazards regression with high-dimensional survival data, where the covariates are prone to measurement errors. We develop a double bias correction method by first correcting the bias arising from measurement errors in covariates through an estimating function for the regression parameter. By adopting the convex relaxation technique, a regularized estimator for the regression parameter is obtained by elaborately designing a feasible loss based on the estimating function, which is solved via linear programming.

Cox regression analysis for distorted covariates with an unknown distortion function.

We study inference for censored survival data where some covariates are distorted by some unknown functions of an observable confounding variable in a multiplicative form. An example of this kind of data in medical studies is normalizing some important observed exposure variables by patients' body mass index , weight, or age. Such a phenomenon also appears frequently in environmental studies where an ambient measure is used for normalization and in genomic studies where the library size needs to be normalized for the next generation sequencing of data.

Restricted mean survival time for interval-censored data.

Restricted mean survival time (RMST) evaluates the mean event-free survival time up to a prespecified time point. It has been used as an alternative measure of treatment effect owing to its model-free structure and clinically meaningful interpretation of treatment benefit for right-censored data. In clinical trials, another type of censoring called interval censoring may occur if subjects are examined at several discrete time points and the survival time falls into an interval rather than being exactly observed.

Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data.

Interval-censored data often arise naturally in medical, biological, and demographical studies. As a matter of routine, the Cox proportional hazards regression is employed to fit such censored data. The related work in the framework of additive hazards regression, which is always considered as a promising alternative, remains to be investigated.

Censored cumulative residual independent screening for ultrahigh-dimensional survival data.

For complete ultrahigh-dimensional data, sure independent screening methods can effectively reduce the dimensionality while retaining all the active variables with high probability. However, limited screening methods have been developed for ultrahigh-dimensional survival data subject to censoring. We propose a censored cumulative residual independent screening method that is model-free and enjoys the sure independent screening property.

Multiple imputation for cure rate quantile regression with censored data.

The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject.

Semiparametric inference for a 2-stage outcome-auxiliary-dependent sampling design with continuous outcome.

Two-stage design has long been recognized to be a cost-effective way for conducting biomedical studies. In many trials, auxiliary covariate information may also be available, and it is of interest to exploit these auxiliary data to improve the efficiency of inferences. In this paper, we propose a 2-stage design with continuous outcome where the second-stage data is sampled with an "outcome-auxiliary-dependent sampling" (OADS) scheme.

Statistical inference for a two-stage outcome-dependent sampling design with a continuous outcome.

The two-stage case-control design has been widely used in epidemiology studies for its cost-effectiveness and improvement of the study efficiency (White, 1982, American Journal of Epidemiology 115, 119-128; Breslow and Cain, 1988, Biometrika 75, 11-20). The evolution of modern biomedical studies has called for cost-effective designs with a continuous outcome and exposure variables. In this article, we propose a new two-stage outcome-dependent sampling (ODS) scheme with a continuous outcome variable, where both the first-stage data and the second-stage data are from ODS schemes.

Additive-multiplicative rates model for recurrent events.

Recurrent events are frequently encountered in biomedical studies. Evaluating the covariates effects on the marginal recurrent event rate is of practical interest. There are mainly two types of rate models for the recurrent event data: the multiplicative rates model and the additive rates model.

Multivariate Failure Times Regression with a Continuous Auxiliary Covariate.

How to take advantage of the available auxiliary covariate information when the primary covariate of interest is not measured is a frequently encountered question in biomedical study. In this paper, we consider the multivariate failure times regression analysis in which the primary covariate is assessed only in a validation set but a continuous auxiliary covariate for it is available for all subjects in the study cohort. Under the frame of marginal hazard model, we propose to estimate the induced relative risk function in the nonvalidation set through kernel smoothing method and then obtain an estimated pseudo-partial likelihood function.