Dataset Information

Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.

ABSTRACT: OBJECTIVES:To evaluate the use of super-resolution ultrasound (SR-US) imaging for quantifying microvascular changes in skeletal muscle using a mouse model of type 2 diabetes. METHODS:Study groups were young, standard chow-fed male C57BL/6J mice (lean group) and high fat diet-fed older mice (obese group). After an overnight fast, dynamic contrast-enhanced US imaging was performed on the proximal hind limb adductor muscle group for 10?minutes at baseline and again at 1 and 2?hours during administration of a hyperinsulinemic-euglycemic clamp. Dynamic contrast-enhanced US images were collected on a clinical US scanner (Acuson Sequoia 512; Siemens Healthcare, Mountain View, CA) equipped with a 15L8 linear array transducer. Dynamic contrast-enhanced US images were processed with a spatiotemporal filter to remove tissue clutter. Individual microbubbles were localized and counted to create an SR-US image. A frame-by-frame analysis of the microbubble count was generated (ie, time-microbubble count curve [TMC]) to estimate tissue perfusion and microvascular blood flow. The conventional time-intensity curve (TIC) was also generated for comparison. RESULTS:In vivo SR-US imaging could delineate microvascular structures in the mouse hind limb. Compared with lean animals, insulin-induced microvascular recruitment was attenuated in the obese group. The SR-US-based TMC analysis revealed differences between lean and obese animal data for select microvascular parameters (P?

SUBMITTER: Ghosh D

PROVIDER: S-EPMC6669112 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.

Ghosh Debabrata D Peng Jun J Brown Katherine K Sirsi Shashank S Mineo Chieko C Shaul Philip W PW Hoyt Kenneth K

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 20190131 10

<h4>Objectives</h4>To evaluate the use of super-resolution ultrasound (SR-US) imaging for quantifying microvascular changes in skeletal muscle using a mouse model of type 2 diabetes.<h4>Methods</h4>Study groups were young, standard chow-fed male C57BL/6J mice (lean group) and high fat diet-fed older mice (obese group). After an overnight fast, dynamic contrast-enhanced US imaging was performed on the proximal hind limb adductor muscle group for 10 minutes at baseline and again at 1 and 2 hours d ...[more]

PMID: 30706511

Similar Datasets

Project description:Ultrasound super-resolution (SR) microvessel imaging technologies are rapidly emerging and evolving. The unprecedented combination of imaging resolution and penetration promises a wide range of preclinical and clinical applications. This paper concerns spatial quantization error in SR imaging, a common issue that involves a majority of current SR imaging methods. While quantization error can be alleviated by the microbubble localization process (e.g., via upsampling or parametric fitting), it is unclear to what extent the localization process can suppress the spatial quantization error induced by discrete sampling. It is also unclear when low spatial sampling frequency will result in irreversible quantization errors that cannot be suppressed by the localization process. This paper had two goals: 1) to systematically investigate the effect of quantization in SR imaging and establish principles of adequate SR imaging spatial sampling that yield minimal quantization error with proper localization methods and 2) to compare the performance of various localization methods and study the level of tolerance of each method to quantization. We conducted experiments on a small wire target and on a microbubble flow phantom. We found that the Fourier analysis of an oversampled spatial profile of the microbubble signal could provide reliable guidance for selecting beamforming spatial sampling frequency. Among various localization methods, parametric Gaussian fitting and centroid-based localization on upsampled data had better microbubble localization performance and were less susceptible to quantization error than peak intensity-based localization methods. When spatial sampling resolution was low, parametric Gaussian fitting-based localization had the best performance in suppressing quantization error, and could produce acceptable SR microvessel imaging with no significant quantization artifacts. The findings from this paper can be used in practice to help intelligently determine the minimum requirement of spatial sampling for robust microbubble localization to avoid adding or even reduce the burden of computational cost and data storage that are commonly associated with SR imaging.

Dataset Information

Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.

Publications

Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets