Ultrasonic and elasticity imaging to model disease-induced changes in soft-tissue structure

doi:10.1016/S1361-8415(98)80014-5

Medical Image Analysis

Volume 2, Issue 4, December 1998, Pages 325-338

https://doi.org/10.1016/S1361-8415(98)80014-5 Get rights and content

Abstract

Ultrasonic techniques are presented for the study of soft biological tissue structure and function. Changes in echo waveforms caused by microscopic variations in the mechanical properties of tissue can reveal disease mechanism, in vivo. On a larger scale, elasticity imaging describes the macroscopic mechanical properties of soft tissues. We summarize the approach and present preliminary results for studying disease-induced changes in renal tissue using these two acoustic imaging techniques.

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Cited by (31)

RATE-iPATH: On the design of integrated ultrasonic biomarkers for breast cancer detection
2020, Biomedical Signal Processing and Control
Citation Excerpt :
QUS RATE parameters are measured directly from machine UB and UE images after the lesions have been traced out by expert radiologists [15]. These parameters provide macroscopic mechanical structure-related information as well as echo pattern and shape-based information of the tissue [31]. On the other hand, iPATH parameters are measured from the raw RF data using signal processing techniques and contain microscopic structural information of the tissue [31,32].
Multi-modal complementary information integrated noninvasive digital biomarkers are emerging with enormous potential for early detection of female breast cancer and reduction of mortality rate among women around the globe. The objective of this study is to design new quantitative ultrasound (QUS) biomarkers integrated from pathological information of tissue microstructure, conventional B-mode imaging-based acoustic and morphological features, and strain imaging-based tissue elasticity features for detecting cancer more effectively. We also develop simulation models to evaluate the estimation accuracy of effective scatterer diameter (ESD), a characteristic parameter of tissue pathology. The proposed biomarkers are designed by optimally integrating 2 QUS indirect pathology (iPATH) parameters with 27 QUS radiology and tissue elasticity (RATE) parameters. To determine effective biomarkers, several techniques are employed: a wrapper-based feature reduction technique in the original feature domain as well as in the empirical mode decomposition (EMD)-discrete wavelet transforms (DWT) domain, and a genetic algorithm-based feature weighting technique. Simulation phantoms determining the accuracy of the ESD estimation algorithm and explaining the increasing trend of ESD with the carcinogenic transformation of normal tissue are created in MATLAB and analyzed using Field II. The resulting average mean absolute percentage error of the ESD estimation algorithm on the simulation phantoms is 4.06%, proving its efficacy. On 139 in-vivo patient data, the three techniques yield accuracy, sensitivity, and specificity within the range of 97.84–99.28%, 97.84–100%, and 95.45–98.95%, respectively. The high values of these metrics indicate that the RATE-iPATH feature set can be used as non-invasive integrated biomarkers for computer-aided diagnosis of breast cancer.
Ultrasound Strain Elastography for Circumscribed Solid Thyroid Nodules without Malignant Features Categorized as Indeterminate by B-Mode Ultrasound
2016, Ultrasound in Medicine and Biology
The aim of this study was to evaluate the diagnostic performance of ultrasound strain elastography (USE) for circumscribed solid thyroid nodules without malignant or benign features seen on US. This retrospective study included 197 thyroid nodules in 196 patients who underwent USE with color mapping and strain ratio measurement between 2010 and 2014. Of the 197 nodules, 24 (12.2%) were malignant. No significant differences in color mapping or strain ratio were observed between benign and malignant nodules. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 29.2% (95% confidence interval [CI]: 13.8%–49.4%), 77.5% (95% CI: 75.3%–80.3%), 15.2% (95% CI: 7.2%–25.8%), 88.7% (95% CI: 86.3%–92.0%), and 71.6% (95% CI: 67.8%–76.5%) for color mapping and 50.0% (95% CI: 30.%–69.5%), 57.2% (95% CI: 54.5%–59.9%), 14.0% (95% CI: 8.5%–18.4%), 89.2% (95% CI: 85.0%–93.4%) and 56.3% (95% CI: 51.6%–61.1%) for strain ratio measurement, respectively. USE with color mapping and strain ratio measurement has a limited ability to differentiate benign from malignant nodules for circumscribed solid thyroid nodules without definite malignant features categorized as indeterminate by B-mode US.
The Journey of Elastography: Background, Current Status, and Future Possibilities in Breast Cancer Diagnosis
2015, Clinical Breast Cancer
Elastography is a promising way to assess tissue differences regarding stiffness or elasticity for what was historically assessed manually by palpation. Combined with conventional imaging modalities (eg, ultrasonography [US]), elastography can potentially evaluate the stiffness of a breast lesion and consequently help to detect malignant breast tumor from benign ones. Recent studies show that ultrasonographic elastography (USE) provides higher image quality compared with conventional B-mode US or mammography during breast cancer diagnosis, which eventually helps to reduce false-positive results (ie, increased specificity) and therefore is useful in avoiding breast biopsy. This article reviews the basics of elastography technique, classifications, diagnosis results obtained from clinical studies to date for differentiating malignant breast tumors from benign lesions, and its future possibilities. In addition, this article generalizes different elastography methods, modes, and associated imaging modalities in a simpler way and attempts to identify misconceptions and confusion related to existing elastography techniques. It also makes an effort to identify the gaps of information that need to be filled so that interested researchers can get an overall idea of elastography-based methods in a convenient way to carry out their research on breast elastography for prospective future applications, eg, breast cancer diagnosis or even in intraoperative breast tumor localization.
Renal transplant elasticity ultrasound imaging: Correlation between normalized strain and renal cortical fibrosis
2013, Ultrasound in Medicine and Biology
Citation Excerpt :
Elasticity ultrasound imaging (EUI) is an emerging non-invasive imaging technique for the assessment of internal organ and tissue biomechanical properties that may be useful in assessing pathologic changes that influence tissue mechanics (O'Donnell et al. 1993; Xu et al. 2012). In the kidney, EUI may provide information about the mechanical changes that accompany histologic changes useful for monitoring renal disease (Chaturvedi et al. 1998). Quasi-static ultrasound strain measurements of the renal cortex in renal transplant recipients may help detect and monitor tissue hardness changes in a chronic transplant allograft nephropathy (CTAN) (Weitzel et al. 2004).
After transplantation, over a widely variable time course, the cortex of the transplanted kidney becomes stiffer as interstitial fibrosis develops and renal function declines. Elasticity ultrasound imaging (EUI) has been used to assess biomechanical properties of tissue that change in hardness as a result of pathologic damage. We prospectively assessed the hardness of the renal cortex in renal transplant allograft patients using a normalized ultrasound strain procedure measuring quasi-static deformation, which was correlated with the grade of renal cortical fibrosis. To determine cortical strain, we used 2-D speckle-tracking software (EchoInsight, Epsilon Imaging, Ann Arbor, MI, USA) to perform offline analysis of stored ultrasound loops capturing deformation of renal cortex and its adjacent soft tissue produced by pressure applied using the scanning transducer. Normalized strain is defined as the mean developed strain in the renal cortex divided by the overall mean strain measured in the soft tissues from the abdominal wall to pelvic muscles. Using the Banff scoring criteria for renal cortical fibrosis as the gold standard, we classified 20 renal transplant allograft biopsy tissue samples into two groups: group 1 (n = 10) with mild (<25%) renal cortical fibrosis and group 2 (n = 10) with moderate (26%–50%) renal cortical fibrosis. An unpaired two-tailed t-test was used to determine the statistical difference in strains between patients with mild and those with moderate renal cortical fibrosis. Receiver operating characteristic curve analysis was performed to assess the accuracy of developed strain and normalized strain in predicting moderate renal cortical fibrosis. The reference strain did not significantly differ between the two groups (p = 0.10). However, the developed renal cortical strain in group 1 with mild fibrosis was higher than that in group 2 with moderate fibrosis (p = 0.025). The normalized strain in group 1 was also higher than that in group 2 (p = 0.0014). The areas under receiver operating characteristic curves for developed strain and normalized strain were 0.78 and 0.95, respectively. The optimal cutoff for distinguishing moderate renal cortical fibrosis was −0.08 for developed strain (sensitivity = 0.50, specificity = 1.0) and 2.5 for normalized strain (sensitivity = 0.80, specificity = 1.0). In summary, renal cortex strain is strongly correlated with grade of renal cortical fibrosis. Normalized strain is superior to developed strain in distinguishing moderate from mild renal cortical fibrosis. We conclude that free-hand real-time strain EUI may be useful in assessing the progression of cortical fibrosis in renal transplant allografts. Further prospective study using this method is warranted.
Role of ultrasound in thyroid disorders
2012, Ultrasound Clinics
Citation Excerpt :
In general, increased vascularity in a thyroid nodule is suggestive of malignancy but should not be considered a pathognomonic feature. Elastography is the ultrasound measurement of tissue elasticity, a mechanical property reflecting the deformation or distortion of the tissue in response to the application of external compression.35 In this method, pressure is applied with the ultrasound transducer and used to measure tissue stiffness.
Intravascular Ultrasound Area Strain Imaging Used to Characterize Tissue Components and Assess Vulnerability of Atherosclerotic Plaques in a Rabbit Model
2011, Ultrasound in Medicine and Biology
The purpose of this study was to investigate the association of area strain and tissue components and vulnerability of atherosclerotic plaques in a rabbit model. Forty purebred New Zealand rabbits underwent balloon-induced abdominal aorta endothelium injury, then a high-cholesterol diet for 24 weeks. Intravascular ultrasound (IVUS) images of abdominal aortas were acquired in situ and two consecutive frames near the end-diastole were used to construct an IVUS elastogram. Histologic slices matched with corresponding IVUS images were stained for fatty and collagen components, smooth muscle cells (SMCs) and macrophages. Regions-of-interest (ROIs) in plaques were classified as fibrous, fibro-fatty or fatty according to histologic study. Vulnerability indexes of ROIs were calculated as (fat + macrophage)/(collagen + SMCs). The area strain of these ROIs was calculated by use of an in-house–designed software system with a block-matching–based algorithm. Area strain was significantly higher in fatty ROIs (0.056 ± 0.003) than in fibrous (0.019 ± 0.002, p < 0.001) or fibro-fatty ROIs (0.033 ± 0.003, p < 0.001). The sensitivity and specificity of area strain for fatty ROIs characterization was 75.0% and 80.2% (area under the curve [AUC] 0.858, 95% confidence interval [CI] = 0.800–0.916, p < 0.001) and 75.0% and 75.3% (AUC 0.859, 95% CI = 0.801–0.917, p < 0.001) for fibrous ROIs, as demonstrated by receiver operating characteristic curve analysis. Area strain was positively correlated with vulnerability index (r² = 0.495, p < 0.001), fatty components (r² = 0.332, p < 0.001) and macrophage infiltration (r² = 0.406, p < 0.001); and negatively correlated with collagen and SMC composition (r² = 0.115 and r² = 0.169, p < 0.001, respectively). Area strain calculation with IVUS elastography based on digital B-mode analysis is feasible and can be useful for tissue characterization and plaque vulnerability assessment.

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Medical Image Analysis

Abstract

References (25)

A mathematical model for progression of renal diseases

J. Theor. Biol.

Diagnostic spectrum analysis in ophthalmology: a physical perspective

Ultrasound Med. Biol.

Is focal segmental glomerulosclerosis really focal? Distribution of lesions in adults and children

Kidney Int.

Imaging of the elastic properties of tissue—a review

Ultrasound Med. Biol.

Parametric ultrasound imaging from backscatter coefficient measurements: image formation and interpretation

Ultrasonic Imaging

Identifying acoustic scattering sources in normal renal parenchyma in vivo by varying arterial and ureteral pressures

Ultrasound Med. Biol.

Elastography: a quantitative method for imaging the elasticity of biological tissue

Ultrason. Imaging

Tissue response to mechanical vibrations for sonoelasticity imaging

Ultrasound Med. Biol.

Effects of antihypertensive drugs on glomerular morphology

Kidney Int.

Deformation models and correlation analysis in elastography

J. Acoust. Soc. Am.

Ultrasonic scattering properties of three random media with implications for tissue characterization

J. Acoust. Soc. Am.

Bayesian and least squares approaches to ultrasonic scatterer size image formation

IEEE Trans. Ultrason. Ferroelect. Freq. Control

Cited by (31)

RATE-iPATH: On the design of integrated ultrasonic biomarkers for breast cancer detection

Ultrasound Strain Elastography for Circumscribed Solid Thyroid Nodules without Malignant Features Categorized as Indeterminate by B-Mode Ultrasound

The Journey of Elastography: Background, Current Status, and Future Possibilities in Breast Cancer Diagnosis

Renal transplant elasticity ultrasound imaging: Correlation between normalized strain and renal cortical fibrosis

Role of ultrasound in thyroid disorders

Intravascular Ultrasound Area Strain Imaging Used to Characterize Tissue Components and Assess Vulnerability of Atherosclerotic Plaques in a Rabbit Model