H-Scan Ultrasound Monitoring of Breast Cancer Response to Chemotherapy and Validation With Diffusion-Weighted Magnetic Resonance Imaging.

OBJECTIVES: H-scan ultrasound (US) imaging is a novel tissue characterization technique to detect apoptosis-induced changes in cancer cells after the initiation of effective drug treatment. The objective of the proposed research was to assess the sensitivity of 3-dimensional (3D) H-scan US technique for monitoring the response of breast cancer-bearing animals to neoadjuvant chemotherapy and correlate results to diffusion-weighted magnetic resonance imaging (DW-MRI) measurements of programmed cancer cell death. METHODS: Experimental studies used female mice (N = 18) implanted with human breast cancer cells. Animals underwent H-scan US and DW-MRI imaging on days 0, 1, 3, 7, and 10. After imaging at day 0, breast tumor-bearing nude mice were treated biweekly with an apoptosis-inducing drug. Texture analysis of H-scan US images explored spatial relationships between local US scattering. At day 10, H-scan measurements were compared with DW-MRI-derived apparent diffusion coefficient (ADC) values and histological findings. RESULTS: H-scan US imaging of low and high dose cisplatin-treated cancer-bearing animals revealed changes in image intensity suggesting a progressive decrease in aggregate US scatterer size that was not observed in control animals. Longitudinal trends discovered in H-scan US result matched with texture analysis and DW-MRI (P < .01). Further, analysis of the H-scan US image intensity and corresponding DW-MRI-derived ADC values revealed a strong linear correlation (R2  = .93, P < .001). These changes were due to cancer cell apoptotic activity and consider as early detectable biomarker during treatment. CONCLUSIONS: The 3D H-scan technique holds promise for assisting clinicians in monitoring the early response of breast cancer tumor to neoadjuvant chemotherapy and adding value to traditional diagnostic ultrasound examinations.

3-D H-scan ultrasound imaging of relative scatterer size using a matrix array transducer and sparse random aperture compounding.

H-scan ultrasound (US) is a high-resolution imaging technique for soft tissue characterization. By acquiring data in volume space, H-scan US can provide insight into subtle tissue changes or heterogenous patterns that might be missed using traditional cross-sectional US imaging approaches. In this study, we introduce a 3-dimensional (3-D) H-scan US imaging technology for voxel-level tissue characterization in simulation and experimentation. Using a matrix array transducer, H-scan US imaging was developed to evaluate the relative size of US scattering aggregates in volume space. Experimental data was acquired using a programmable US system (Vantage 256, Verasonics Inc, Kirkland, WA) equipped with a 1024-element (32 × 32) matrix array transducer (Vermon Inc, Tours, France). Imaging was performed using the full array in transmission. Radiofrequency (RF) data sequences were collected using a sparse random aperture compounding technique with 6 different data compounding approaches. Plane wave imaging at five angles was performed at a center frequency of 8 MHz. Scan conversion and attenuation correction were applied. To generate the 3-D H-scan US images, a convolution filter bank (N = 256) was then used to process the RF data sequences and measure the spectral content of the backscattered US signals before volume reconstruction. Preliminary experimental studies were conducted using homogeneous phantom materials embedded with spherical US scatterers of varying diameter, i.e., 27 to 45, 63 to 75, or 106-126 µm. Both simulated and experimental results revealed that 3-D H-scan US images have a low spatial variance when tested with homogeneous phantom materials. Furthermore, H-scan US is considerably more sensitive than traditional B-mode US imaging for differentiating US scatterers of varying size (p = 0.001 and p = 0.93, respectively). Overall, this study demonstrates the feasibility of 3-D H-scan US imaging using a matrix array transducer for tissue characterization in volume space.

Three-Dimensional H-Scan Ultrasound Imaging of Early Breast Cancer Response to Neoadjuvant Therapy in a Murine Model.

OBJECTIVES: Three-dimensional (3D) H-scan is a new ultrasound (US) technique that images the relative size of acoustic scatterers. The goal of this research was to evaluate use of 3D H-scan US imaging for monitoring early breast cancer response to neoadjuvant therapy using a preclinical murine model of breast cancer. MATERIALS AND METHODS: Preclinical studies were conducted using luciferase-positive breast cancer-bearing mice (n = 40). Anesthetized animals underwent US imaging at baseline before administration with an apoptosis-inducing drug or a saline control. Image data were acquired using a US scanner equipped with a volumetric transducer following either a shorter- or longer-term protocol. The later included bioluminescent imaging to quantify tumor cell viability. At termination, tumors were excised for ex vivo analysis. RESULTS: In vivo results showed that 3D H-scan US imaging is considerably more sensitive to tumor changes after apoptosis-inducing drug therapy as compared with traditional B-scan US. Although there was no difference at baseline (P > 0.99), H-scan US results from treated tumors exhibited progressive decreases in image intensity (up to 62.2% by day 3) that had a significant linear correlation with cancer cell nuclear size (R2 > 0.51, P < 0.001). Results were validated by histological data and a secondary longitudinal study with survival as the primary end point. DISCUSSION: Experimental results demonstrate that noninvasive 3D H-scan US imaging can detect an early breast tumor response to apoptosis-inducing drug therapy. Local in vivo H-scan US image intensity correlated with cancer cell nuclear size, which is one of the first observable changes of a cancer cell undergoing apoptosis and confirmed using histological techniques. Early imaging results seem to provide prognostic insight on longer-term tumor response. Overall, 3D H-scan US imaging is a promising technique that visualizes the entire tumor and detects breast cancer response at an early stage of therapy.

Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers.

The study of ultrasound tissue interactions in fatty livers has a long history with strong clinical potential for assessing steatosis. Recently we proposed alternative measures of first- and second-order statistics of echoes from soft tissues, namely, the H-scan, which is based on a matched filter approach, to quantify scattering transfer functions and the Burr distribution to model speckle patterns. Taken together, these approaches produce a multiparameter set that is directly related to the fundamentals of ultrasound propagation in tissue. To apply this approach to the problem of assessing steatotic livers, these analyses were applied to in vivo rat livers (N=21) under normal feeding conditions or after receiving a methionine- and choline-deficient diet that produces steatosis within a few weeks. Ultrasound data were acquired at baseline and again at weeks 2 and 6 before applying the H-scan and Burr analyses. Furthermore, a classification technique known as the support vector machine was then used to find clusters of the five parameters that are characteristic of the different steatotic liver conditions as confirmed by histologic processing of excised liver tissue samples. With the in vivo multiparametric ultrasound measurement approach and determination of clusters, steatotic can be discriminated from normal livers with 100% accuracy in a rat animal model.

Multiparametric ultrasound imaging for the assessment of normal versus steatotic livers.

Liver disease is increasing in prevalence across the globe. We present here a multiparametric ultrasound (mpUS) imaging approach for assessing nonalcoholic fatty liver disease (NALFD). This study was performed using rats (N = 21) that were fed either a control or methionine and choline deficient (MCD) diet. A mpUS imaging approach that includes H-scan ultrasound (US), shear wave elastography, and contrast-enhanced US measurements were then performed at 0 (baseline), 2, and 6 weeks. Thereafter, animals were euthanized and livers excised for histological processing. A support vector machine (SVM) was used to find a decision plane that classifies normal and fatty liver conditions. In vivo mpUS results from control and MCD diet fed animals reveal that all mpUS measures were different at week 6 (P < 0.05). Principal component analysis (PCA) showed that the H-scan US data contributed the highest percentage to the classification among the mpUS measurements. The SVM resulted in 100% accuracy for classification of normal and high fat livers and 92% accuracy for classification of normal, low fat, and high fat livers. Histology findings found considerable steatosis in the MCD diet fed animals. This study suggests that mpUS examinations have the potential to provide a comprehensive estimation of the main components of early stage NAFLD.

3-D H-Scan Ultrasound Imaging and Use of a Convolutional Neural Network for Scatterer Size Estimation.

H-Scan ultrasound (US) is a new imaging technology that estimates the relative size of acoustic scattering objects and structures. The purpose of this study was to introduce a three-dimensional (3-D) H-scan US imaging approach for scatterer size estimation in volume space. Using a programmable research scanner (Vantage 256, Verasonics Inc, Kirkland, WA, USA) equipped with a custom volumetric imaging transducer (4 DL7, Vermon, Tours, France), raw radiofrequency (RF) data was collected for offline processing to generate H-scan US volumes. A deep convolutional neural network (CNN) was modified and used to achieve voxel mapping from the input H-scan US image to underlying scatterer size. Preliminary studies were conducted using homogeneous gelatin-based tissue-mimicking phantom materials embedded with acoustic scatterers of varying size (15 to 250 µm) and concentrations (0.1 to 1%). Two additional phantoms were embedded with 63 or 125 µm-sized microspheres and used to test CNN estimation accuracy. In vitro results indicate that 3-D H-scan US imaging can visualize the spatial distribution of acoustic scatterers of varying size at different concentrations (R2 > 0.85, p < 0.03). The result of scatterer size estimation reveals that a CNN can achieve an average mapping accuracy of 93.3%. Overall, our preliminary in vitro findings reveal that 3-D H-scan US imaging allows the visualization of tissue scatterer patterns and incorporation of a CNN can be used to help estimate size of the acoustic scattering objects.

Adaptive attenuation correction during H-scan ultrasound imaging using K-means clustering.

H-scan ultrasound (US) imaging (where the 'H' stands for Hermite) is a novel non-invasive, low cost and real-time technology. Like traditional US, H-scan US suffers from frequency-dependent attenuation that must be corrected to have acceptable image quality for tissue characterization. The goal of this research was to develop a novel attenuation correction method based on adaptive K-means clustering. To properly isolate these signals, a lateral moving window approach applied to adaptively adjust GH filters based on the changing of RF vector spectrums. Then the signal isolated via the same filter will be combined together via overlap-add technology to keep the information loss minimum. Experimental data was collected using a Verasonics 256 US scanner equipped with a L11-4v linear array transducer. In vivo data indicates that H-scan US imaging after adaptive attenuation correction can optimally re-scale the GH kernels and match to the changing spectrum undergoing attenuation (i.e. high frequency shift). This approach produces H-scan US images with more uniform spatial intensity and outperforms global attenuation correction strategies. Overall, this approach will improve the ability of H-scan US imaging to estimate acoustic scatterer size and will improve its clinical use for tissue characterization when imaging complex tissues.