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The detection of metastases in freshly-excised lymph nodes from cancer patients during lymphadenectomy is critically important for cancer staging, treatment, and optimal patient management. Currently, conventional histologic methods suffer a high rate of false-negative determinations because pathologists cannot evaluate each excised lymph nodes in its entirety. Therefore, lymph nodes are undersampled and and small but clinically relevant metastatic regions can be missed. In this study, quantitative ultrasound (QUS) methods using high-frequency transducers (i.e., > 20 MHz) were developed and evaluated for their ability to detect and guide pathologists towards suspicious regions in lymph nodes. A custom laboratory scanning system was used to acquire radio-frequency (RF) data in 3D from excised lymph nodes using a 26-MHz center-frequency transducer. Overlapping 1-mm cylindrical regions-of-interest (ROIs) of the RF data were processed to yield 13 QUS estimates quantifying tissue microstructure and organization. These QUS methods were applied to more than 260 nodes from more than 160 colorectal-, gastric-, and breast-cancer patients. Cancer-detection performance was assessed for individual estimates and linear combinations of estimates. ROC results demonstrated excellent classification. For colorectal- and gastric-cancer nodes, the areas under the ROC curves (AUCs) were greater than 0.95. Slightly poorer results (AUC=0.85) were obtained for breast-cancer nodes. Images based on QUS parameters also permitted localization of cancer foci in some micrometastatic cases.

We have developed quantitative descriptors to provide an objective means of noninvasive identification of cancerous breast lesions. These descriptors include quantitative acoustic features assessed using spectrum analysis of ultrasonic radiofrequency (rf) echo signals and morphometric properties related to lesion shape. Acoustic features include measures of echogenicity, heterogeneity and shadowing, computed by generating spectral-parameter images of the lesion and surrounding tissue. Spectral-parameter values are derived from rf echo signals at each pixel using a sliding-window Fourier analysis. We derive quantitative acoustic features from spectral-parameter maps of the lesion and adjacent areas. We quantify morphometric features by geometric and fractal analysis of traced lesion boundaries. Initial results on biopsy-proven cases show that although a single parameter cannot reliably discriminate cancerous from noncancerous breast lesions, multi-feature analysis provides excellent discrimination for this data set. We have processed data for 130 biopsy-proven patients, acquired during routine ultrasonic examinations at three clinical sites and produced an area under the receiver-operating-characteristics (ROC) curve of 0.947 +/- 0.045. Among the quantitative descriptors, lesion-margin definition, spiculation and border irregularity are the most useful; some additional morphometric features (such as border irregularity) also are particularly effective in lesion classification. Our findings are consistent with many of the BI-RADS (Breast Imaging Reporting and Data System) breast-lesion-classification criteria in use today.

Axillary lymph node status is an important factor for staging and treatment planning in breast cancer. Our study was performed in vitro on a node-by-node basis to evaluate the ability of B-mode ultrasonographic images to distinguish metastatic from nonmetastatic nodes. Immediately prior to histologic examination, individual dissected axillary nodes were scanned in a water bath using a 10 MHz B-mode ultrasonographic transducer. Four B-mode features (size, circularity, border demarcation, and internal echo) were evaluated for their ability to distinguish metastatic from nonmetastatic lymph nodes. Lymph node metastasis was indicated by (1) a large size (i.e., a length of the longest axis of 10 mm or greater); (2) a circular shape (i.e., the ratio of the shortest axis to the longest axis between 0.5 and 1.0); (3) a sharply demarcated border compared with surrounding fatty tissue; and (4) a hypoechoic internal echo, with obliteration of the fatty hilum. The sensitivity and specificity were compared for all combinations of features. We examined 84 histologically characterized axillary nodes from 27 breast cancer patients, including 64 nonmetastatic and 20 metastatic nodes. Of the criteria cited, circular shape was the best single feature for distinguishing metastatic from nonmetastatic nodes (sensitivity, 65%; specificity, 73%). The best combination of sensitivity (85%) and specificity (73%) was obtained using the criterion that a lymph node contained cancer when at least three positive features were present. The present in vitro study demonstrated that the sensitivity and specificity of B-mode ultrasonography for diagnosing lymph node metastasis were lower than 90%. Therefore, B-mode ultrasonography may not be an optimal noninvasive screening method for diagnosing axillary lymph node metastasis in breast cancer patients, particularly under in vivo clinical conditions.

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.

The ability of ultrasonic tissue characterization to differentiate and classify benign and malignant breast tissues in vivo in patients with palpable breast masses and in vitro in excised breast tissue was evaluated. One-hundred and twenty-four in vivo and 89 in vitro studies were performed using a technique of UTC based on parameters from the power spectrum of backscattered echoes. Sensitivities and specificities for diagnosing carcinoma were 86 and 84% for in vivo studies and 94 and 92% for in vitro studies. These UTC parameters provided threshold values for color-coding breast lesion images. The results of this preliminary investigation suggest that UTC provides a basis for assessing more accurately lesions suspected of being malignant prior to biopsy and possibly for evaluating breast lesions noninvasively.