Differential diagnosis of thyroid nodules with US elastography using carotid artery pulsation.

PURPOSE: To explore the sensitivity and specificity of ultrasonographic (US) elastography using carotid arterial pulsation as the compression source for differential diagnosis of thyroid nodules. MATERIALS AND METHODS: This HIPAA-compliant study was approved by the ethics committee of the institution, and all patients provided written informed consent. Fifty-eight patients (13 men and 45 women [mean age, 51 years; range, 20-76 years]) were enrolled. A short US examination and elastography with pulsation of the carotid artery used as the thyroid compression source were performed before fine-needle aspiration. Baseband US data were downloaded for off-line analysis. Elastographic maps and the thyroid stiffness index were calculated. The Kruskal-Wallis nonparametric rank sum test was used to assess equality of population medians among the different types of thyroid nodules; the R software environment was used for statistical computing and graphics (http://www.r-project.org/). RESULTS: Thyroid stiffness index calculated with elastography using carotid arterial pulsation as the compression source was effective in helping distinguish between papillary carcinomas (n = 10) and other lesions (n = 43) because papillary carcinomas were stiffer than other lesions (P < .0039). CONCLUSION: It is possible to distinguish between papillary carcinomas and other lesions with the thyroid stiffness index calculated from US elastography using carotid arterial pulsation.

Research interface on a programmable ultrasound scanner.

MOTIVATION: Commercial ultrasound machines in the past did not provide the ultrasound researchers access to raw ultrasound data. Lack of this ability has impeded evaluation and clinical testing of novel ultrasound algorithms and applications. OBJECTIVES: Recently, we developed a flexible ultrasound back-end where all the processing for the conventional ultrasound modes, such as B, M, color flow and spectral Doppler, was performed in software. The back-end has been incorporated into a commercial ultrasound machine, the Hitachi HiVision 5500. The goal of this work is to develop an ultrasound research interface on the back-end for acquiring raw ultrasound data from the machine. METHODS: The research interface has been designed as a software module on the ultrasound back-end. To increase the amount of raw ultrasound data that can be spooled in the limited memory available on the back-end, we have developed a method that can losslessly compress the ultrasound data in real time. RESULTS AND DISCUSSION: The raw ultrasound data could be obtained in any conventional ultrasound mode, including duplex and triplex modes. Furthermore, use of the research interface does not decrease the frame rate or otherwise affect the clinical usability of the machine. The lossless compression of the ultrasound data in real time can increase the amount of data spooled by approximately 2.3 times, thus allowing more than 6s of raw ultrasound data to be acquired in all the modes. The interface has been used not only for early testing of new ideas with in vitro data from phantoms, but also for acquiring in vivo data for fine-tuning ultrasound applications and conducting clinical studies. We present several examples of how newer ultrasound applications, such as elastography, vibration imaging and 3D imaging, have benefited from this research interface. Since the research interface is entirely implemented in software, it can be deployed on existing HiVision 5500 ultrasound machines and may be easily upgraded in the future. CONCLUSIONS: The developed research interface can aid researchers in the rapid testing and clinical evaluation of new ultrasound algorithms and applications. Additionally, we believe that our approach would be applicable to designing research interfaces on other ultrasound machines.

Ultrasound thyroid elastography using carotid artery pulsation: preliminary study.

OBJECTIVE: The purpose of this study was to evaluate the feasibility of ultrasound thyroid elastography using carotid artery pulsation as the compression source and its potential for differential diagnosis of thyroid nodules. METHODS: Baseband sonographic data were acquired for 16 thyroid nodules from 12 patients. The natural pulsation of the carotid artery was used as the compression source, and thyroid strain was estimated offline. For quantitative assessment of thyroid tissue stiffness, a new metric called the thyroid stiffness index (TSI) was computed as the ratio of strain near the carotid artery (high-strain region) to that of a stiff region (low-strain region) inside a thyroid nodule. The stiffness information from elastography was correlated with histopathologic findings. RESULTS: The TSI for papillary carcinoma (n = 9) was higher than the TSI for a benign nodular goiter (n = 6), indicating that papillary carcinoma is stiffer than a benign nodular goiter (P < .05). In 1 patient, we were able to distinguish a papillary carcinoma nodule and a benign nodular goiter located in the same thyroid lobe based on the stiffness information obtained from elastography. This suggests that elastography could be used for guiding fine-needle aspiration biopsy to a thyroid nodule with a high probability of cancer. CONCLUSIONS: The results from this preliminary study indicate the feasibility of the pulsation-induced thyroid elastography. Ultrasound thyroid elastography using carotid artery pulsation appears to have the potential for noninvasively differentiating papillary carcinoma from benign nodular goiter. Future studies are needed to evaluate the efficacy of elastography in detecting thyroid cancer and guiding thyroid biopsies.

Angular strain estimation method for elastography.

In the conventional cross-correlation-based strain estimation, there is a trade-off between the interpolation accuracy and the computational requirement. On the other hand, the autocorrelation-based method does not need interpolation, but it cannot estimate the wide range of displacements for elastography. We have developed a new strain estimator, called the angular strain estimation method, which does not need any interpolation and can estimate strain without restricting the range of displacements. The new method estimates strain utilizing complex correlation between correlated ultrasound signals from pre-and post-compression frames. From simulation and experiments, we found that the angular strain estimation method improves the accuracy and strain image quality compared to the conventional strain estimator using cross correlation with interpolation. Furthermore, it is computationally efficient and can be readily incorporated in ultrasound machines for rea -time elastography.

Direct phase-based strain estimator for ultrasound tissue elasticity imaging.

Palpation has been widely used to detect hard tumorous tissues surrounded by softer normal tissues. The goal of ultrasound tissue elasticity imaging is to extract information regarding tissue stiffness that is closely related to pathology. For this tissue elasticity imaging, compression is applied first, and the amount of resulting tissue deformation or strain needs to be estimated. Traditionally, strain estimators aim to accurately derive tissue displacements between pre- and post-compression and compute strain from the displacements. However, the displacement can be as large as a thousand times of strain for typical compression levels used in ultrasound elasticity imaging. Error in displacement estimation leads to a large variance in strain, thus resulting in poor signal to noise ratio for the estimated strain. We have developed a novel strain estimator that directly estimates strain from the phase of temporal and spatial correlation instead of estimating small strain from large displacements. SNRe (signal to noise ratio of elastogram) and CNRe (contrast to noise ratio of elastogram) using the direct strain estimator are at least three times and six times larger than that using conventional displacement-based strain estimators, respectively. These results indicate that the direct strain estimator can significantly improve accuracy and lesion detectability in ultrasound elasticity imaging. In addition, the direct strain estimator is computationally efficient compared to conventional estimators, thus enabling the realtime implementation and clinical use of this new ultrasound imaging mode.

Fast adaptive unsharp masking with programmable mediaprocessors.

Unsharp masking is a widely used image-enhancement method in medical imaging. Hardware-based solutions can be developed to support high computational demand for unsharp masking, but they suffer from limited flexibility. Software solutions can easily incorporate new features and modify key parameters, such as filtering kernel size, but they have not been able to meet the fast computing requirement. Modern programmable mediaprocessors can meet both fast computing and flexibility requirements, which will benefit medical image computing. In this article, we present fast adaptive unsharp masking on two leading mediaprocessors or high-end digital signal processors, Hitachi/Equator Technologies MAP-CA and Texas Instruments TMS320C64x. For a 2k x 2k 16-bit image, our adaptive unsharp masking with a 201 x 201 boxcar kernel takes 225 ms on a 300-MHz MAP-CA and 74 ms on a 600-MHz TMS320C64x. This fast unsharp masking enables technologists and/or physicians to adjust parameters interactively for optimal quality assurance and image viewing.