Quantitative imaging methods using high-frequency ultrasound (HFU) offer a means of characterizing biological tissue at the microscopic level. Previously, high-frequency, threedimensional (3D) quantitative-ultrasound (QUS) methods were developed to characterize 46 freshly-dissected lymph nodes of colorectal-cancer patients. 3D ultrasound radio-frequency data were acquired using a 25.6-MHz center-frequency transducer and each node was inked prior to tissue fixation to recover orientation after sectioning for 3D histological evaluation. Backscattered echo signals were processed using 3D cylindrical regions-of-interest (ROIs) to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept, and slope). These QUS estimates, obtained by parameterizing the backscatter spectrum, showed great potential for cancer detection. In the present study, these QUS methods were applied to 112 lymph nodes from 77 colorectal and gastric cancer patients. Novel QUS methods parameterizing the envelope statistics of the ROIs using Nakagami and homodyned-K distributions also were developed; they yielded four additional QUS estimates. The ability of these eight QUS estimates to classify lymph nodes and detect cancer was evaluated using ROC curves. An area under the ROC curve of 0.996 with specificity and sensitivity of 95% were obtained by combining effective scatterer size and one envelope parameter based on the homodyned-K distribution. Therefore, these advanced 3D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

High-frequency ultrasound (HFU) offers a means of investigating biological tissue at the microscopic level. High-frequency, three-dimensional (3D) quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. 3D ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to tissue fixation to recover orientation after sectioning for 3D histological evaluation. Backscattered echo signals were processed using 3D cylindrical regions-of-interest to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept, and slope). QUS estimates were computed following established methods using two scattering models. In this study, 46 lymph nodes acquired from 27 patients diagnosed with colon cancer were processed. Results revealed that fully-metastatic nodes could be perfectly differentiated from cancer-free nodes using slope or scatterer-size estimates. Specifically, results indicated that metastatic nodes had an average effective scatterer size (i.e., 37.1 ± 1.7 um) significantly larger (p <0.05) than that in cancer-free nodes (i.e., 26 ± 3.3 um). Therefore, the 3D QUS methods could provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures.

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Ultrasound (US) scanners typically apply lossy, non-linear modifications to the US data for visualization purposes. The resulting images are then stored as compressed video data. Some system manufacturers provide dedicated software for quantification purposes to eliminate such processing distortions, at least partially. This is currently the recommended approach for quantitatively assessing changes in contrast-agent concentration from clinical data. However, the machine-specific access to US data and the limited set of analysis functionalities offered by each dedicated-software package make it difficult to perform comparable analyses with different US systems. The objective of this work was to establish if linearization of compressed video images obtained with an arbitrary US system can provide an alternative to dedicated-software analysis of machine-specific files for the estimation of echo-power. For this purpose, an Aplio 50 system (Toshiba Medical Systems, Tochigi, Japan), coupled with dedicated CHI-Q (Contrast Harmonic Imaging Quantification) software by Toshiba Medical Systems, was used. Results were compared with two approaches that apply algorithms to estimate relative echo-power from compressed video images: commercially available VueBox software by Bracco Suisse SA (Geneva, Switzerland) and in-laboratory software called PixPower. The echo-power estimated by CHI-Q analysis indicated a strong linear relationship versus agent concentration in vitro (R(2) ≥ 0.9996) for dynamic range (DR) settings of DR60 and DR80, with slopes between 9.22 and 9.57 dB/decade (p = 0.05). These values approach the theoretically predicted dependence of 10.0 dB/decade (equivalent to 3 dB for each concentration doubling). Echo-power estimations obtained from compressed video images with VueBox and PixPower also exhibited strong linear proportionality with concentration (R(2) ≥ 0.9996), with slopes between 9.30 and 9.68 dB/decade (p = 0.05). On an independent in vivo data set (N = 24), the difference in echo-power estimation between CHI-Q and each of the other two approaches was calculated after excluding regions that contain pixels affected by saturated or thresholded pixel values. The mean difference in estimates (expressed in decibels) was -0.25 dB between VueBox and CHI-Q (95% confidence interval: -0.75 to 0.26 dB) and -0.17 dB between PixPower and CHI-Q (95% confidence interval: -0.67 to 0.13 dB). To achieve linearization of data, one of the approaches (VueBox) requires calibration files provided by the software manufacturer for each machine type and setting. The other (PixPower) requires empirical correction of the imaging dynamic range based on ground truth data. These requirements could potentially be removed if US system manufacturers were willing to make relevant information on the applied processing publically available. Reliable echo-power estimation from linearized data would facilitate inclusion of different US systems in multicentric studies and more widespread implementation of emerging techniques for quantitative ...

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BACKGROUND Detection of metastases in lymph nodes (LNs) is critical for cancer management. Conventional histological methods may miss metastatic foci. Currently, no practical means of entire LN-volume evaluation exists. The aim of this study is to develop fast, reliable, operator-independent, high-frequency, quantitative-ultrasound (QUS) methods for evaluating LNs over their entire volumes for effectively detecting LN metastases. MATERIALS AND METHODS Freshly excised LNs were scanned at 26 MHz and echo-signal data were digitally acquired over the entire three-dimensional (3D) volume. 146 LNs of colorectal-, 26 LNs of gastric-, and 118 LNs of breast-cancer patients were enrolled. LNs were step-sectioned at 50-μm intervals and later compared to 13 QUS estimates associated with tissue microstructure. Linear-discriminant analysis classified LNs as metastatic or non-metastatic, and areas (Az) under receiver-operator characteristic (ROC) curves were computed to assess classification performance. QUS-estimates and cancer-probability values derived from discriminant analysis were depicted in 3D images for comparison with 3D histology. RESULTS 23/146 LNs of colorectal-cancer patients were metastatic; Az = 0.952 ± 0.021 (95% CI: 0.911 to 0.993); sensitivity 91.3% (specificity 87.0%); sensitivity 100% (specificity 67.5%). 5/26 LNs of gastric-cancer patients were metastatic; Az = 0.962 ± 0.039 (95% CI: 0.807 to 1.000); sensitivity 100% (specificity 95.3%). 17/118 LNs of breast-cancer patients were metastatic; Az = 0.833 ± 0.047 (95% CI: 0.741 to 0.926); sensitivity 88.2% (specificity 62.5%); sensitivity 100% (specificity 50.5%). 3D cancer-probability images showed good correlation with 3D histology. CONCLUSIONS These results suggest that operator- and system-independent QUS methods will allow reliable entire-volume LN evaluation for detecting metastases. 3D cancer-probability images can help pathologists identify metastatic foci that could be missed using conventional methods.