Determining the acuteness and stability of deep venous thrombosis by ultrasonic tissue characterization

Shear Wave Elastography and Quantitative Ultrasound as Biomarkers to Characterize Deep Vein Thrombosis In Vivo

OBJECTIVE

Investigate shear wave elastography (SWE) and quantitative ultrasound (QUS) parameters in patients hospitalized for lower limb deep vein thrombosis (DVT).

METHOD

Sixteen patients with DVT were recruited and underwent SWE and radiofrequency data acquisitions for QUS on day 0, day 7, and day 30 after the beginning of symptoms, in both proximal and distal zones of the clot identified on B-mode scan. SWE and QUS features were computed to differentiate between thrombi at day 0, day 7, and day 30 following treatment with heparin or oral anticoagulant. The Young's modulus from SWE was computed, as well as QUS homodyned K-distribution (HKD) parameters reflecting blood clot structure. Median and interquartile range of SWE and QUS parameters within clot were taken as features.

RESULTS

In the proximal zone of the clot, the HKD ratio of coherent-to-diffuse backscatter median showed a significant decrease from day 7 to day 30 (P = .036), while the HKD ratio of diffuse-to-total backscatter median presented a significant increase from day 7 to day 30 (P = .0491). In the distal zone of the clot, the HKD normalized intensity of the echo envelope median showed a significant increase from day 0 to day 30 (P = .0062). No SWE features showed statistically significant differences over time. Nonetheless, a trend of lower median of Young's modulus within clot for patients who developed a pulmonary embolism was observed.

CONCLUSION

QUS features may be relevant to characterize clot's evolution over time. Further analysis of their clinical interpretation and validation on a larger dataset would deserve to be studied.

Analysis of Two Quantitative Ultrasound Approaches

There are two well-known ultrasonic approaches to extract sets of quantitative parameters: Lizzi-Feleppa (LF) parameters: slope, intercept, and midband; and quantitative ultrasound (QUS)-derived parameters: effective scatterer diameter (ESD) and effective acoustic concentration (EAC). In this study, the relation between the LF and QUS-derived parameters is studied theoretically and experimentally on ex vivo mouse livers. As expected from the theory, LF slope is correlated to ESD ([Formula: see text]), and from experimental data, LF midband is correlated to EAC ([Formula: see text]). However, LF intercept is not correlated to ESD ([Formula: see text]) nor EAC ([Formula: see text]). The unexpected correlation observed between LF slope and EAC ([Formula: see text]) results likely from the high correlation between ESD and EAC due to the inversion process. For a liver fat percentage estimation, an important potential medical application, the parameters presenting the better correlation are EAC ([Formula: see text]) and LF midband ([Formula: see text]).

Computer aided diagnosis of parotid gland lesions using ultrasonic multi-feature tissue characterization

In this article, an ultrasound based system for computer aided characterization of biologic tissue and its application to differential diagnosis of parotid gland lesions is proposed. Aiming at an automated differentiation between malignant and benign cases, the system is based on a supervised classification using tissue-describing features derived from ultrasound radio-frequency (RF) echo signals and image data. Standard diagnostic ultrasound equipment was employed to acquire ultrasound RF echo data from parotid glands of 138 patients. Lesions were manually demarcated as regions-of-interest (ROIs) in the B-mode images. Spectral ultrasound backscatter and attenuation parameters are estimated from diffraction corrected RF data, yielding spatially resolved parameter images. Histogram based statistical measures derived from the parameters distributions inside the ROI are used as tissue describing features. In addition, texture features and shape descriptors are extracted from demodulated ultrasound image data. The features are processed by a maximum likelihood classifier. An optimal set of 10 features was chosen by a sequential forward selection algorithm. The classifier's performance is evaluated using total cross validation and receiver operating characteristic (ROC) analysis. As a reference method, postoperative pathohistologic analysis was conducted and proved malignancy or prospective malignancy in 51 patients. The classification using the proposed system yielded an area under the ROC curve of 0.91, proving significant potential for differentiating between malignant and benign parotid gland lesions.

In vitro diagnosis of axillary lymph node metastases in breast cancer by spectrum analysis of radio frequency echo signals

Axillary lymph node status is of particular importance for staging and managing breast cancer. Currently, axillary lymph node dissection is performed routinely in cases of invasive breast cancer because of the lack of accurate noninvasive methods for diagnosing lymph node metastasis. We investigated the diagnostic ability of ultrasonic tissue characterization based on spectrum analysis of backscattered echo signals to detect axillary lymph node metastasis in breast cancer in vitro compared with in vitro B-mode imaging. Immediately after surgery, individual lymph nodes were isolated from axillary tissue. Each lymph node was scanned in a water bath using a 10-MHz instrument, and radio frequency data and B-mode images were acquired. Spectral parameter values were calculated, and discriminant analysis was performed to classify metastatic and nonmetastatic lymph nodes. Forty histologically characterized axillary lymph nodes were enrolled in this study, including 25 nonmetastatic and 15 metastatic lymph nodes. A significant difference existed in the spectral parameter values (slope and intercept) for metastatic and nonmetastatic lymph nodes. Spectral parameter-based discriminant function classification of metastatic vs. nonmetastatic lymph nodes provided a sensitivity of 93.3%, specificity of 92.0%, and overall accuracy of 92.5%. In comparison, B-mode ultrasound images of in vitro lymph nodes provided a sensitivity of 73.3%, specificity of 84.0%, and overall accuracy of 80.0%. Receiver operating characteristic (ROC) analysis comparing the efficacy of both methods gave an ROC curve area of 0.9888 for spectral methods, which was greater than the area of 0.8980 for B-mode ultrasound. Hence, this in vitro study suggests that the diagnostic ability of spectrum analysis may prove to be markedly superior to that of B-mode ultrasound in detecting axillary lymph node metastasis in breast cancer. Because of these encouraging results, we intend to conduct an investigation of the ability of spectral methods to classify metastatic axillary lymph nodes in vivo.