Ultrasound Tissue Characterization Research Articles

Evaluation of Patellar Tendon Structural Changes following Biological Treatments: Secondary Analysis of Double-Blinded Clinical Trial of Bone Marrow Mesenchymal Stromal Cells and Leukocyte-Poor Platelet-Rich Plasma.

Objective quantification of tendon structural changes through imaging is only achieved by evaluating tendon structure using ultrasound tissue characterization (UTC) technology. This study compares the effects of bone marrow mesenchymal stromal cells (BM-MSC) and leukocyte-poor platelet-rich plasma (Lp-PRP) on tendon structure and clinical outcomes in male patients with patellar tendinopathy measured with UTC at 3, 6, and 12 months after treatment. This is a double-blinded clinical trial with a randomized active control study with 20 male patients diagnosed with patellar tendinopathy who underwent BM-MSC and Lp-PRP. Bilateral ultrasound tissue characterization scans of the patellar tendon were carried out after 3, 6, and 12 months, as well as tests for strength and pain. UTC patellar tendon was analyzed at the insertion, proximal, and mid-tendon. BM-MSC showed a greater capacity to promote further positive changes than Lp-PRP. Lp-PRP presented higher disorganized echo-type II in the mid-tendon (p = 0.04; ES = 1.06) and III (p = 0.02; ES = -1.47) after 3 months in the Lp-PRP group. Similar results were seen after 6 and 12 months. Pain and strength data show improvement in the treated tendon. BM-MSC treatment demonstrates a superior capacity to promote tendon regeneration and organization, restore strength, and reduce pain compared to Lp-PRP, after 3, 6, and 12 months in male patients with patellar tendinopathy.

Ultrasound fuzzy entropy imaging based on time-series signal for tissue characterization

This study proposed a parametric imaging method of fuzzy entropy based on time-series signal, which can enhance the contrast and augment the accuracy of the detection of lesions in soft tissue. Fuzzy entropy assesses the irregularity of ultrasound time-series data through the detection of similarities within the signal waveform. Applying fuzzy entropy in ultrasound tissue characterization can provide more tissue information. The sliding windows are performed to traverse across the whole image with the step of one pixel. The signal in the sliding window calculates the fuzzy entropy (FE), and the FE value is assigned to the window’s center pixel. The entropy image will be constructed after obtaining all fuzzy entropies. The performance of the proposed FE imaging was compared with weighted Shannon entropy (WSE) imaging and B-mode imaging by simulations, ex vivo experiments, and clinical data. FE imaging got superior lesion area prediction with the AUC of 0.959 ± 0.042 (p < 0.0001), the accuracy of 99.88 ± 0.09 % (p < 0.0001), and the contrast-to-noise ratio of 7.806 ± 4.476 (p < 0.001) in the thyroid nodule diagnostic tests. The results show that FE imaging significantly increases the contrast of the images. Compared with WSE, the FE imaging method has better sensitivity to disorder degree and better recovery ability of tissue information when the amplitude of the signal decreases or the change of signal properties is small. FE imaging considers the characteristics of ultrasound time series. It has a better recovery ability for ultrasound signals, which is a promising technique for soft tissue diagnosis and thermal ablation monitoring.

Normative ultrasound values for Achilles tendon thickness in the general population and patients with Achilles tendinopathy: A large international cross-sectional study.

The objective of the study was to obtain adjusted ultrasonographic reference values of the Achilles tendon thickness (maximum anterior-posterior distance) in adults without (previous) Achilles tendinopathy (AT) and to compare these reference values with AT patients. Six hundred participants were consecutively included, comprising 500 asymptomatic individuals and 100 patients with clinically diagnosed chronic AT. The maximum tendon thickness was assessed using Ultrasound Tissue Characterization. A multiple quantile regression model was developed, incorporating covariates (personal characteristics) that were found to have a significant impact on the maximum anterior-posterior distance of the Achilles tendon. A 95% reference interval (RI) was derived (50th, 2.5th-97.5th percentile). In asymptomatic participants median (95% RI) tendon thickness was 4.9 (3.8-6.9) mm for the midportion region and 3.7 (2.8-4.8) mm for the insertional region. Age, height, body mass index, and sex had a significant correlation with maximum tendon thickness. Median tendon thickness for the midportion region was calculated with the normative equation -2.1 + AGE × 0.021 + HEIGHT × 0.032+ BMI × 0.028 + SEX × 0.05. For the insertional region, the normative equation was -0.34 + AGE × 0.010+ HEIGHT × 0.018 + BMI × 0.022 + SEX × -0.05. In the equations, SEX is defined as 0 for males and 1 for females. Mean (95% CI) difference in tendon thickness compared to AT patients was 2.7 mm (2.3-3.2, p < 0.001) for the midportion and 1.4 mm (1.1-1.7, p < 0.001) for the insertional region. Compared to the asymptomatic population 73/100 (73%) AT patients exhibited increased tendon thickening, with values exceeding the 95% RI. This study presents novel reference values for the thickness of midportion and insertional region of the Achilles tendon, which were adjusted for personal characteristics. Our novel web-based openly accessible calculator for determining normative Achilles tendon thickness (www.achillestendontool.com) will be a useful resource in the diagnostic process. Trial registration number: This trial is registered in the Netherlands Trial Register (NL9010).

Appropriate indicator of modeling error for threshold-based model selection in statistics-based ultrasound tissue characterization

Analysis of the envelope statistics of ultrasound echo signals contributes to quantitative tissue characterization in medical ultrasound. Many probability distribution model functions have been studied, and the model function that should be used for tissue characterization depends on the type of disease, even in the same organ. Thus, an appropriate model selection is important for an accurate diagnosis. In this study, we aimed to select a model using threshold processing for modeling errors instead of a simple selection by minimizing the modeling error. For this purpose, we compared several indicators of modeling errors using random number simulations, ultrasonic simulation, and phantom experiment. The results validated that the Mahalanobis distance of moments is an appropriate indicator because it enables the use of a constant threshold value, regardless of the type of model function and data length.

High-resolution acoustic mapping of tunable gelatin-based phantoms for ultrasound tissue characterization.

Background: The choice of gelatin as the phantom material is underpinned by several key advantages it offers over other materials in the context of ultrasonic applications. Gelatin exhibits spatial and temporal uniformity, which is essential in creating reliable tissue-mimicking phantoms. Its stability ensures that the phantom's properties remain consistent over time, while its flexibility allows for customization to match the acoustic characteristics of specific tissues, in addition to its low levels of ultrasound scattering. These attributes collectively make gelatin a preferred choice for fabricating phantoms in ultrasound-related research. Methods: We developed gelatin-based phantoms with adjustable parameters and conducted high-resolution measurements of ultrasound wave attenuation when interacting with the gelatin phantoms. We utilized a motorized acoustic system designed for 3D acoustic mapping. Mechanical evaluation of phantom elasticity was performed using unconfined compression tests. We particularly examined how varying gelatin concentration influenced ultrasound maximal intensity and subsequent acoustic attenuation across the acoustic profile. To validate our findings, we conducted computational simulations to compare our data with predicted acoustic outcomes. Results: Our results demonstrated high-resolution mapping of ultrasound waves in both gelatin-based phantoms and plain fluid environments. Following an increase in the gelatin concentration, the maximum intensity dropped by 30% and 48% with the 5MHz and 1MHz frequencies respectively, while the attenuation coefficient increased, with 67% more attenuation at the 1MHz frequency recorded at the highest concentration. The size of the focal areas increased systematically as a function of increasing applied voltage and duty cycle yet decreased as a function of increased ultrasonic frequency. Simulation results verified the experimental results with less than 10% deviation. Conclusion: We developed gelatin-based ultrasound phantoms as a reliable and reproducible tool for examining the acoustic and mechanical attenuations taking place as a function of increased tissue elasticity and stiffness. Our experimental measurements and simulations gave insight into the potential use of such phantoms for mimicking soft tissue properties.

Measuring Ultrasonographic Thickness of the Achilles Tendon Insertion Is Less Reliable Than the Midportion in Healthy Tendons and Patients With Tendinopathy.

Ultrasound is the preferred imaging method in the diagnostic process of Achilles tendinopathy (AT). Ultrasound tissue characterization (UTC) is a frequently used, standardized and valid method to assess tendon geometry in AT patients. It is unknown whether UTC is reliable for measuring Achilles tendon thickness. The aim of the study was to assess intra- and inter-rater reliability of Achilles tendon thickness measurements using UTC in both asymptomatic individuals and patients with AT, and to evaluate if the reliability of thickness measurements differs between the midportion and insertional area. Exactly 50 patients with AT and 50 asymptomatic individuals were included. Using the conventional US and standardized UTC procedure maximum thickness was measured in the midportion and insertion region. To determine inter- and intra-rater reliabilities, the intraclass correlation coefficient (ICC) was used. The ICC values for inter- and intra-rater reliability were classified as "excellent," for the AT group (0.93 [95% CI: 0.88-0.96] and 0.95 [0.92-0.97]) and asymptomatic participants (0.91 [0.87-0.94] and 0.94 [0.92-0.96]). The reliability of measuring tendon thickness in the midportion region was "excellent," with both inter-rater (0.97 [0.95-0.98]) and intra-rater (0.98 [0.96-0.99]) ICC values indicating high levels of agreement. In the insertional region, ICC values for inter-rater (0.79 [0.69-0.87]) and intra-rater (0.89 [0.84-0.93]) reliability were "moderate to good." We showed excellent reliability for measuring the US thickness of the midportion and good reliability of measuring the insertional region in patients with AT. Significantly lower ICCs were observed for the reliability of thickness measurements in the insertional region when compared with the midportion.

Where is Your Pain? Achilles Tendinopathy Pain Location on Loading Is Different to Palpation, Imaging and Recall Location.

OBJECTIVE: To describe and compare pain maps reported during Achilles tendon loading exercises with recall pain location, in people with pain on palpation in their Achilles tendon and tendon pathology on imaging. DESIGN: Cross-sectional analysis of baseline RCT. METHOD: Participants were recruited from a larger Achilles tendinopathy clinical trial. Inclusion criteria were at least 2-month self-reported history of Achilles tendinopathy, midtendon palpation pain, and pathology on ultrasound tissue characterization. Participants were asked to identify their Achilles tendon pain location on a pain map with 8 prespecified locations while at rest prior to loading (recall pain), and subsequently during tendon loading exercises (loading pain). Participants could select multiple locations or select "other" if the locations did not represent their pain. RESULTS: Ninety-three participants were included (93% of participants from a clinical trial). The locations of pain on loading were diverse; all 8 pain locations (and an "other" option) were represented within this sample. Twenty-five percent of participants did not report pain with loading (n = 23 of 93). Of the 70 participants with loading pain, recall pain location differed to loading pain location in 40% (n = 28 of 70) of the participants. CONCLUSION: Palpation pain location, recall pain location, or location of pathology on imaging were not valid proxies for load-related pain in the Achilles tendon. How different pain locations respond to treatment is unknown. Some pathologies (eg, plantaris) have clear pain locations (eg, medial tendon), and assessing pain location may assist differential diagnosis. J Orthop Sports Phys Ther 2024;54(1):1-9. Epub 7 December 2023. doi:10.2519/jospt.2023.12131.

Quadriceps strength, patellar tendon quality, relative load exposure, and knee symptoms in male athletes before the anterior cruciate ligament reconstruction.

Anterior cruciate ligament (ACL) injuries cause knee instability, knee pain, weight-bearing adjustments, and functional deficits but their association to patellar tendon quality is unknown. Our purpose was to investigate quadriceps strength, patellar tendon quality, relative load exposure, perceived knee stability, knee pain, extension angle, and time from ACL injury; in addition to examining their relative associations. Injured and uninjured legs of 81 male athletes of different sports with a unilateral ACL injury (18-45 years) were examined. Participants reported location and intensity of knee pain and their perceived stability using a numerical rating scale (NRS 0-10). Strength was tested with an isokinetic device. Tendon quality was measured using ultrasound tissue characterization. Means ± standard deviation (SD) of perceived knee stability, knee extension angle, knee pain, isokinetic quadriceps strength in relation to body mass, proportion of echo-types (I-IV), tendon volume, and number of days from ACL injury to assessment are reported. Values of effect sizes (ES) and correlations (rs) were calculated. ACL injured leg demonstrated reduced reported knee stability (6.3 ± 2.5), decreased knee extension angle (-0.7 ± 3.1° vs. -2.7 ± 2.2°; ES = 0.7; P < 0.001), greater knee pain (NRS 3.1 ± 2.2 vs. 0.0 ± 0.1; ES = 2.0; P < 0.001), and 22% lower quadriceps strength (228.0 ± 65.0 vs. 291.2 ± 52.9 Nm/kg: ES = 1.2; P < 0.001) as compared to the uninjured leg. However, patellar tendons in both legs displayed similar quality. Quadriceps strength was associated with stability (rs = -0.54; P < 0.001), pain (rs = -0.47; P < 0.001), extension angle (rs = -0.39; P < 0.001), and relative load exposure (rs = -0.34; P < 0.004). Echo-types distribution was beneficially associated with time from ACL injury (rs range: -0.20/ -0.32; P < 0.05). ACL injured athletes displayed knee pain, extension deficit, and weaker quadriceps in the injured leg. While there were no differences in patellar tendon quality between legs, longer time from ACL injury showed better tendon quality.

Prognostic value of ultrasound tissue characterisation for a recurrence of mid-portion Achilles tendinopathy in military service members: a prospective cohort study

IntroductionTendon structure in mid-portion Achilles tendinopathy (mid-AT) appears poorly associated with symptoms. Yet, degenerative tendon changes on imaging have been associated with an increased risk of mid-AT. We aimed to...

Calibrating Data Mismatches in Deep Learning-Based Quantitative Ultrasound Using Setting Transfer Functions.

Deep learning (DL) can fail when there are data mismatches between training and testing data distributions. Due to its operator-dependent nature, acquisition-related data mismatches, caused by different scanner settings, can occur in ultrasound imaging. As a result, it is crucial to mitigate the effects of these mismatches to enable wider clinical adoption of DL-powered ultrasound imaging and tissue characterization. To address this challenge, we propose an inexpensive and generalizable method that involves collecting a large training set at a single setting and a small calibration set at each scanner setting. Then, the calibration set will be used to calibrate data mismatches by using a signals and systems perspective. We tested the proposed solution to classify two phantoms using an L9-4 array connected to a SonixOne scanner. To investigate generalizability of the proposed solution, we calibrated three types of data mismatches: pulse frequency mismatch, focus mismatch, and output power mismatch. Two well-known convolutional neural networks (CNNs), i.e., ResNet-50 and DenseNet-201, were trained using the ultrasound radio frequency (RF) data. To calibrate the setting mismatches, we calculated the setting transfer functions. The CNNs trained without calibration resulted in mean classification accuracies of around 52%, 84%, and 85% for pulse frequency, focus, and output power mismatches, respectively. By using the setting transfer functions, which allowed a matching of the training and testing domains, we obtained the mean accuracies of 96%, 96%, and 98%, respectively. Therefore, the incorporation of the setting transfer functions between scanner settings can provide an economical means of generalizing a DL model for specific classification tasks where scanner settings are not fixed by the operator.

A Study on a Parameter Estimator for the Homodyned K Distribution Based on Table Search for Ultrasound Tissue Characterization.

The homodyned K (HK) distribution is considered to be the most suitable distribution in the context of tissue characterization; therefore, the search for a rapid and reliable parameter estimator for HK distribution is important. We propose a novel parameter estimator based on a table search (TS) for HK parameter estimates. The TS estimator can inherit the strength of conventional estimators by integrating various features and taking advantage of the TS method in a rapid and easy operation. Performance of the proposed TS estimator was evaluated and compared with that of XU (the estimation method based on X and U statistics) and artificial neural network (ANN) estimators. The simulation results revealed that the TS estimator is superior to the XU and ANN estimators in terms of normalized standard deviations and relative root mean squared errors of parameter estimation, and is faster. Clinical experiments found that the area under the receiver operating curve for breast lesion classification using the parameters estimated by the TS estimator could reach 0.871. The proposed TS estimator is more accurate, reliable and faster than the state-of-the-art XU and ANN estimators and has great potential for ultrasound tissue characterization based on the HK distribution.

Parallelized ultrasound homodyned-K imaging based on a generalized artificial neural network estimator

The homodyned-K (HK) distribution model is a generalized backscatter envelope statistical model for ultrasound tissue characterization, whose parameters are of physical meaning. To estimate the HK parameters is an inverse problem, and is quite complicated. Previously, we proposed an artificial neural network (ANN) estimator and an improved ANN (iANN) estimator for estimating the HK parameters, which are fast and flexible. However, a drawback of the conventional ANN and iANN estimators consists in that they use Monte Carlo simulations under known values of HK parameters to generate training samples, and thus the ANN and iANN models have to be re-trained when the size of the test sets (or of the envelope samples to be estimated) varies. In addition, conventional ultrasound HK imaging uses a sliding window technique, which is non-vectorized and does not support parallel computation, so HK image resolution is usually sacrificed to ensure a reasonable computation cost. To this end, we proposed a generalized ANN (gANN) estimator in this paper, which took the theoretical derivations of feature vectors for network training, and thus it is independent from the size of the test sets. Further, we proposed a parallelized HK imaging method that is based on the gANN estimator, which used a block-based parallel computation method, rather than the conventional sliding window technique. The gANN-based parallelized HK imaging method allowed a higher image resolution and a faster computation at the same time. Computer simulation experiments showed that the gANN estimator was generally comparable to the conventional ANN estimator in terms of HK parameter estimation performance. Clinical experiments of hepatic steatosis showed that the gANN-based parallelized HK imaging could be used to visually and quantitatively characterize hepatic steatosis, with similar performance to the conventional ANN-based HK imaging that used the sliding window technique, but the gANN-based parallelized HK imaging was over 3 times faster than the conventional ANN-based HK imaging. The parallelized computation method presented in this work can be easily extended to other quantitative ultrasound imaging applications.

Tissue Characterization of Puborectalis Muscle From 3-D Ultrasound.

Pelvic floor (PF) muscles have the role of preventing pelvic organ descent. The puborectalis muscle (PRM), which is one of the female PF muscles, can be damaged during child delivery. This damage can potentially cause irreversible muscle trauma and even lead to an avulsion, which is disconnection of the muscle from its insertion point, the pubic bone. Ultrasound imaging allows diagnosis of such trauma based on comparison of geometric features of a damaged muscle with the geometric features of a healthy muscle. Although avulsion, which is considered severe damage, can be diagnosed, microdamage within the muscle itself leading to structural changes cannot be diagnosed by visual inspection through imaging only. Therefore, we developed a quantitative ultrasound tissue characterization method to obtain information on the state of the tissue of the PRM and the presence of microdamage in avulsed PRMs. The muscle was segmented as the region of interest (ROI) and further subdivided into six regions of interest (sub-ROIs). Mean echogenicity, entropy and shape parameter of the statistical distribution of gray values were analyzed on two of these sub-ROIs nearest to the bone. The regions nearest to the bones are also the most likely regions to exhibit damage in case of disconnection or avulsion. This analysis was performed for both the muscle at rest and the muscle in contraction. We found that, for PRMs with unilateral avulsion compared with undamaged PRMs, the mean echogenicity (p=0.02) and shape parameter (p < 0.01) were higher, whereas the entropy was lower (p < 0.01). This method might be applicable to quantification of PRM damage within the muscle.

Review of Envelope Statistics Models for Quantitative Ultrasound Imaging and Tissue Characterization.

The homodyned K-distribution and the K-distribution, viewed as a special case, as well as the Rayleigh and the Rice distributions, viewed as limit cases, are discussed in the context of quantitative ultrasound (QUS) imaging. The Nakagami distribution is presented as an approximation of the homodyned K-distribution. The main assumptions made are (1) the absence of log-compression or application of nonlinear filtering on the echo envelope of the radiofrequency signal and (2) the randomness and independence of the diffuse scatterers. We explain why other available models are less amenable to a physical interpretation of their parameters. We also present the main methods for the estimation of the statistical parameters of these distributions. We explain why we advocate the methods based on the X-statistics for the Rice and the Nakagami distributions and the K-distribution. The limitations of the proposed models are presented. Several new results are included in the discussion sections, with proofs in the appendix.

Disorganised patellar tendon structure remains inert despite continued exposure to high loading environments

Introduction: Ultrasound tissue characterisation (UTC) is a unique imaging modality used to investigate structural changes of the patellar tendon. Adolescent athletes who load their knees may be susceptible to patellar tendon abnormality(s) (PTA), characterised by areas of structural disorganisation. Presence of a PTA is a risk factor for the development of pain and dysfunction. This longitudinal study aimed to investigate patellar tendon structural changes in adolescent athletes with PTA.

Poor association between tendon structure and self-reported symptoms following conservative management in active soldiers with mid-portion Achilles tendinopathy

IntroductionMid-portion Achilles tendinopathy (mid-AT) is currently the preferred term for persistent Achilles tendon pain, defined as located 2–7 cm proximal to the calcaneus, and with loss of function related to...

Liver Fibrosis Assessment Using Radiomics of Ultrasound Homodyned-K imaging Based on the Artificial Neural Network Estimator.

The homodyned-K distribution is an important ultrasound backscatter envelope statistics model of physical meaning, and the parametric imaging of the model parameters has been explored for quantitative ultrasound tissue characterization. In this paper, we proposed a new method for liver fibrosis characterization by using radiomics of ultrasound backscatter homodyned-K imaging based on an improved artificial neural network (iANN) estimator. The iANN estimator was used to estimate the ultrasound homodyned-K distribution parameters k and α from the backscattered radiofrequency (RF) signals of clinical liver fibrosis (n = 237), collected with a 3-MHz convex array transducer. The RF data were divided into two groups: Group I corresponded to liver fibrosis with no hepatic steatosis (n = 94), and Group II corresponded to liver fibrosis with mild to severe hepatic steatosis (n = 143). The estimated homodyned-K parameter values were then used to construct k and α parametric images using the sliding window technique. Radiomics features of k and α parametric images were extracted, and feature selection was conducted. Logistic regression classification models based on the selected radiomics features were built for staging liver fibrosis. Experimental results showed that the proposed method is overall superior to the radiomics method of uncompressed envelope images when assessing liver fibrosis. Regardless of hepatic steatosis, the proposed method achieved the best performance in staging liver fibrosis ≥F1, ≥F4, and the area under the receiver operating characteristic curve was 0.88, 0.85 (Group I), and 0.85, 0.86 (Group II), respectively. Radiomics has improved the ability of ultrasound backscatter statistical parametric imaging to assess liver fibrosis, and is expected to become a new quantitative ultrasound method for liver fibrosis characterization.

Intra- and Inter-Rater Reliability of Processing Ultrasound Tissue Characterization Scans in Midportion Achilles Tendinopathy.

Ultrasound tissue characterization (UTC) is used to visualize and quantify the Achilles tendon structure. We investigated the intra-rater and inter-rater reliability of UTC for quantifying the midportion tendon structure and the area of maximum degeneration (AoMD) in military personnel with midportion Achilles tendinopathy. UTC scans of 50 patients (16-60 years) were processed twice by rater 1 and once by rater 2. First, the midportion tendon structure was quantified and subsequently the AoMD. The intraclass correlation coefficient (ICC) was calculated for echo-types I, II, III, IV, aligned fibrillar structure (echo-types I + II), and disorganized tendon structure (echo-types III + IV). For midportion tendon structure, all ICC values were excellent for intra-rater reliability (range: 0.97 to 0.99) and inter-rater reliability (range: 0.98 to 0.99). Regarding the AoMD, intra-rater reliability showed excellent ICC values for all echo-types (range: 0.94 to 0.98) except for echo-type II (0.85). Inter-rater reliability showed excellent ICC values for all echo-types (range: 0.92 to 0.98). Processing of UTC scans is highly reliable in quantifying the midportion Achilles tendon structure and the AoMD.

An Improved Parameter Estimator of the Homodyned K Distribution Based on the Maximum Likelihood Method for Ultrasound Tissue Characterization.

The homodyned K distribution (HK) can generally describe the ultrasound backscatter envelope statistics distribution with parameters that have specific physical meaning. However, creating robust and reliable HK parameter estimates remains a crucial concern. The maximum likelihood estimator (MLE) usually yields a small variance and bias in parameter estimation. Thus, two recent studies have attempted to use MLE for parameter estimation of HK distribution. However, some of the statements in these studies are not fully justified and they may hinder the application of parameter estimation of HK distribution based on MLE. In this study, we propose a new parameter estimator for the HK distribution based on the MLE (i.e., MLE1), which overcomes the disadvantages of conventional MLE of HK distribution. The MLE1 was compared with other estimators, such as XU estimator (an estimation method based on the first moment of the intensity and tow log-moments) and ANN estimator (an estimation method based on artificial neural networks). We showed that the estimations of parameters α and k are the best overall (in terms of the relative bias, normalized standard deviation, and relative root mean squared errors) using the proposed MLE1 compared with the others based on the simulated data when the sample size was N = 1000. Moreover, we assessed the usefulness of the proposed MLE1 when the number of scatterers per resolution cell was high (i.e., α up to 80) and when the sample size was small (i.e., N = 100), and we found a satisfactory result. Tests on simulated ultrasound images based on Field II were performed and the results confirmed that the proposed MLE1 is feasible and reliable for the parameter estimation from the ultrasonic envelope signal. Therefore, the proposed MLE1 can accurately estimate the HK parameters with lower uncertainty, which presents a potential practical value for further ultrasonic applications.

Observation of plaque behavior and tissue characterization of coronary plaque using speckle tracking intravascular ultrasound (ST-IVUS) and iMap imaging system.

Tissue characterization plays an important role in the development of acute coronary syndromes. iMap is an intravascular ultrasound (IVUS) tissue characterization system that provides useful information by reconstructing color-coded maps. Mechanical properties due to dynamic mechanical stress during a cardiac cycle may also trigger vulnerable plaque. Speckle tracking IVUS (ST-IVUS) has been introduced to observe plaque behavior in relation to mechanical properties. We report the case of an 84-year-old woman with stable coronary artery disease who underwent percutaneous coronary intervention, at which time IVUS demonstrated mainly three low echoic areas like lipid pools with thick fibrous caps. Pathological evaluation with iMap revealed that one low echoic area was occupied with necrotic tissue and that the other two areas occupied fibrotic. Although those tissue characterizations were different, they showed similar stretching behavior at systole by ST-IVUS which depicted plaque behavior from IVUS images using a color mapping. The mechanical properties of individual coronary plaques may differ depending on the tissue disposition. It is necessary to consider mechanical properties using ST-IVUS as well as to evaluate tissue characterization in plaque risk stratification.