It is possible to distinguish between papillary carcinomas and other lesions with the thyroid stiffness index calculated from US elastography using carotid arterial pulsation.

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. Key words: carotid artery pulsation; elastography; thyroid; thyroid stiffness index; ultrasound.Received February 5, 2007,

For ultrasound thyroid elastography, hand-induced freehand compression is typically applied on the neck area to induce strain in the thyroid. In contrast to this conventional approach, we have utilized natural pulsation of the carotid artery as the compression source for thyroid elastography. We have developed strain processing techniques to aid interpretation of strain induced by internal compression. Furthermore, we have developed a metric called thyroid stiffness index (TSI) to provide a more quantitative measure of thyroid tissue stiffness. From 18 patients with thyroid nodules and 5 healthy volunteers, the pulsation-induced thyroid strain was estimated and analyzed. We have found that pulsation of the carotid artery can serve as a repeatable and operator-independent compression source for thyroid elastography. TSI results from 23 subjects indicate that papillary carcinoma is stiffer than other thyroid lesions and normal thyroid glands (p<0.001), thus TSI may be useful in differentiating papillary carcinoma, the most prevalent thyroid cancer, from other lesions. With high quality strain images and a quantitative stiffness measure, thyroid elastography using natural carotid artery pulsation has good potential to provide non-invasive differential diagnosis of thyroid nodules.

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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.

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.

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.