Alain Coron

Three-Dimensional High-Frequency Backscatter and Envelope Quantification of Cancerous Human Lymph Nodes

Quantitative imaging methods using high-frequency ultrasound (HFU) offer a means of characterizing biological tissue at the microscopic level. Previously, high-frequency, 3-D quantitative ultrasound (QUS) methods were developed to characterize 46 freshly-dissected lymph nodes of colorectal-cancer patients. 3-D ultrasound radiofrequency data were acquired using a 25.6 MHz center-frequency transducer and each node was inked before tissue fixation to recover orientation after sectioning for 3-D histological evaluation. Backscattered echo signals were processed using 3-D 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 were also developed; they yielded four additional QUS estimates. The ability of these eight QUS estimates to classify lymph nodes and detect cancer was evaluated using receiver operating characteristics (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 3-D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

Three-dimensional High-frequency Characterization of Cancerous Lymph Nodes

High-frequency ultrasound (HFU) offers a means of investigating biologic tissue at the microscopic level. High-frequency, three-dimensional (3-D) quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. Three-dimensional 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 3-D histologic evaluation. Backscattered echo signals were processed using 3-D 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 microm) significantly larger (p < 0.05) than that in cancer-free nodes (i.e., 26 +/- 3.3 microm). Therefore, the 3-D 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.

Singular spectrum analysis applied to backscattered ultrasound signals from in vitro human cancellous bone specimens

Mean scatterer spacing (MSS) holds particular promise for the detection of changes in quasiperiodic tissue microstructures such as may occur during development of disease in the liver, spleen, or bones. Many techniques that may be applied for MSS estimation (temporal and spectral autocorrelation, power spectrum and cepstrum, higher order statistics, and quadratic transformation) characterize signals that contain a mixture of periodic and nonperiodic contributions. In contrast, singular spectrum analysis (SSA), a method usually applied in nonlinear dynamics, first identifies components of signals corresponding to periodic structures and, second, identifies dominant periodicity. Thus, SSA may better separate periodic structures from nonperiodic structures and noise. Using an ultrasound echo simulation model, we previously demonstrated SSAs potential to identify MSS of structures in quasiperiodic scattering media. The current work aims to observe the behavior of MSS estimation by SSA using ultrasound measurements in phantom materials (two parallel, nylon-line phantoms and four foam phantoms of different densities). The SSA was able to estimate not only the nylon-line distances but also nylon-line thickness. The method also was sensitive to the average pore-size differences of the four sponges. The algorithms then were applied to characterize human cancellous bone microarchitectures. Using 1-MHz center-frequency, radio-frequency ultrasound signals, MSS was measured in 24 in vitro bone samples and ranged front 1.0 to 1.7 mm. The SSA MSS estimates correlate significantly to MSS measured independently front synchrotron microtomography, r/sup 2/=0.68. Thus, application of SSA to backscattered ultrasound signals seems to be useful for providing information linked to tissue microarchitecture that is riot evident from clinical images.

A multiplicative model for improving microvascular flow estimation in dynamic contrast-enhanced ultrasound (DCE-US): theory and experimental validation

Perfusion parameter estimation from dynamic contrast-enhanced ultrasound (DCE-US) data relies on fitting parametric models of flow to curves describing linear echo power as a function of time. The least squares criterion is generally used to fit these models to data. This criterion is optimal in the sense of maximum likelihood under the assumption of an additive white Gaussian noise. In the current work, it is demonstrated that this assumption is not held for DCEUS. A better-adapted maximum likelihood criterion based on a multiplicative model is proposed. It is tested on simulated bolus perfusion data and on 11 sequences acquired in vivo during bolus perfusion of contrast agent in the cortex of healthy murine kidney, an area where the perfusion is expected to be approximately homogeneous. Results on simulated data show a significant improvement (p <; 0.05) of the precision and the accuracy for the estimations of perfusion parameters time to peak (TTP), wash-in rate (WiR), and mean transit time (MTT). On the 11 in vivo sequences, the new method leads to a significant reduction (p <; 0.05) in the variation of parametric maps for 9 sequences for TTP and 10 sequences for WiR and MTT. The mean percent decreases of the coefficient of variation are 40%, 25%, and 59% for TTP, WiR, and MTT, respectively. This method should contribute to a more robust and accurate estimation of perfusion parameters and an improved resolution of parametric imaging.

Three-dimensional segmentation of high-frequency ultrasound echo signals from dissected lymph nodes

Quantitative high-frequency ultrasound (QHFU) imaging methods are under investigation to evaluate their ability to detect small nodal metastases in lymph nodes freshly dissected from cancer patients. To apply these methods, a critical preprocessing step is 3D segmentation of the lymph-node ultrasound echo-signal dataset. Segmenting the residual fat layer and the lymph node is critical in order to avoid bias in the QHFU estimates (e.g., scatterer size and acoustic concentration) due to attenuation and to exclude estimates obtained from the fat regions. Segmentation also provides absolute measurements of lymph-node dimensions that are necessary to match 3D ultrasound with 3D histology. In this study, a 3D region-based segmentation algorithm was developed and compared quantitatively using Dices mutual-overlap criterion with 2D manual segmentation of 9 representative cross sections. The method was tested on 13 lymph nodes, and resulting Dice scores had mean values of 0.81 and 0.78 for lymph node and fat segmentation, respectively.

ECHO-POWER ESTIMATION FROM LOG-COMPRESSED VIDEO DATA IN DYNAMIC CONTRAST-ENHANCED ULTRASOUND IMAGING

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 analysis of contrast ultrasound.

Ultrasonic Backscatter and Attenuation (11–27 MHz) Variation with Collagen Fiber Distribution in Ex Vivo Human Dermis

This ex vivo study explores the relationship of ultrasonic attenuation and backscatter to dermal microarchitecture by comparing ultrasonic measurements of these parameters (11–27 MHz) to a microscopic analysis of three parameters describing the collagen distribution (mean thickness and spacing of collagen bundles along the insonification direction and the percent area occupied by collagen). Skin samples (N = 31) were obtained from patients undergoing breast or abdominal reduction surgery. Radio-frequency (rf) signals were acquired in a B-scan format using an ultrasound system developed for skin imaging (Ultrasons Technologies, Tours, France). Ultrasonic data were analyzed to calculate average integrated backscatter (IBS in dB) and frequency dependence of backscatter (n, dimensionless) of each specimen at depths centered approximately 370, 620 and 880 μm beneath the skin surface. Average integrated attenuation coefficient (IA in dB.cm−1) and frequency dependence of attenuation coefficient (β in dB.cm−1.MHz−1) were estimated across the depth between 240 and 1,000 μm. The three collagen distribution parameters were estimated using digitized microcopic fields from matched regions of histological sections stained with hematoxylin-eosin-saffron. No significant correlation was identified between collagen distribution parameters and IA or β. For the most superficial depth studied in abdominal skin, n was inversely correlated to collagen bundle thickness (r = −0.67, p = 0.002) and percent area (r = −0.65, p = 0.003). At the same depth, IBS was inversely correlated to percent area of collagen (r = −0.51, p = 0.03). The rather high collagen packing (48 to 82% area) measured in histological sections and the inverse relationship observed between IBS and percent area of collagen suggest that a packing factor should be included in models relating skin collagen distribution to ultrasound spectral parameters. A better understanding of the relationship between ultrasound parameters and the microarchitecture of the dermis should help to interpret changes in ultrasonic parameters observed during in vivo ultrasonic skin examinations.

Optimization of attenuation estimation in reflection for in vivo human dermis characterization at 20 MHz

In vivo skin attenuation estimators must be applicable to backscattered radio frequency signals obtained in a pulse-echo configuration. This work compares three such estimators: short-time Fourier multinarrowband (MNB), short-time Fourier centroid shift (FC), and autoregressive centroid shift (ARC). All provide estimations of the attenuation slope (/spl beta/, dB.cm/sup -1/.MHz/sup -1/); MNB also provides an independent estimation of the mean attenuation level (IA, dB.cm/sup -1/). Practical approaches are proposed for data windowing, spectral variance characterization, and bandwidth selection. Then, based on simulated data, FC and ARC were selected as the best (compromise between bias and variance) attenuation slope estimators. The FC, ARC, and MNB were applied to in vivo human skin data acquired at 20 MHz to estimate /spl beta//sub FC/, /spl beta//sub ARC/, and IA/sub MNB/, respectively (without diffraction correction, between 11 and 27 MHz). Lateral heterogeneity had less effect and day-today reproducibility was smaller for IA than for /spl beta/. The IA and /spl beta//sub ARC/ were dependent on pressure applied to skin during acquisition and IA on room and skin-surface temperatures. Negative values of IA imply that IA and /spl beta/ may be influenced not only by skins attenuation but also by structural heterogeneity across dermal depth. Even so, IA was correlated to subject age and IA, /spl beta//sub FC/, and /spl beta//sub ARC/ were dependent on subject gender. Thus, in vivo attenuation measurements reveal interesting variations with subject age and gender and thus appeared promising to detect skin structure modifications.

Three-dimensional quantitative ultrasound for detecting lymph node metastases

PURPOSE Detection of metastases in lymph nodes (LNs) is critical for cancer management. Conventional histological methods may miss metastatic foci. To date, no practical means of evaluating the entire LN volume exists. The aim of this study was to develop fast, reliable, operator-independent, high-frequency, quantitative ultrasound (QUS) methods for evaluating LNs over their entire volume to effectively detect LN metastases. METHODS We scanned freshly excised LNs at 26 MHz and digitally acquired echo-signal data over the entire three-dimensional (3D) volume. A total of 146 LNs of colorectal, 26 LNs of gastric, and 118 LNs of breast cancer patients were enrolled. We step-sectioned LNs at 50-μm intervals and later compared them with 13 QUS estimates associated with tissue microstructure. Linear-discriminant analysis classified LNs as metastatic or nonmetastatic, and we computed areas (Az) under receiver-operator characteristic curves to assess classification performance. The QUS estimates and cancer probability values derived from discriminant analysis were depicted in 3D images for comparison with 3D histology. RESULTS Of 146 LNs of colorectal cancer patients, 23 were metastatic; Az = 0.952 ± 0.021 (95% confidence interval [CI]: 0.911-0.993); sensitivity = 91.3% (specificity = 87.0%); and sensitivity = 100% (specificity = 67.5%). Of 26 LNs of gastric cancer patients, five were metastatic; Az = 0.962 ± 0.039 (95% CI: 0.807-1.000); sensitivity = 100% (specificity = 95.3%). A total of 17 of 118 LNs of breast cancer patients were metastatic; Az = 0.833 ± 0.047 (95% CI: 0.741-0.926); 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 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.

High-Frequency Quantitative Ultrasound Imaging of Cancerous Lymph Nodes

High-frequency ultrasound (HFU) offers a means of investigating biological tissue at the microscopic level. High-frequency, quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. Three-dimensional (3D) ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to 3D histological fixation to recover orientation after sectioning. Backscattered echo signals were processed to yield two QUS estimates associated with tissue microstructure: scatterer size and acoustic concentration. The QUS estimates were computed following established methods using a Gaussian scattering model. Four lymph nodes from a patient with stage-3 colon cancer were evaluated as an illustrative case. QUS images were generated for this patient by expressing QUS estimates as color-encoded pixels and overlaying them on conventional gray-scale B-mode images. The single metastatic node had an average scatterer size that was significantly larger than the average scatterer size of the other nodes, and the statistics of both QUS estimates in the metastatic node showed greater variance than the statistics of the other nodes. Results indicate that the methods may provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures.