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

Dual-modal Photoacoustic and Ultrasound Imaging: from preclinical to clinical applications

Photoacoustic imaging is a novel biomedical imaging modality that has emerged over the recent decades. Due to the conversion of optical energy into the acoustic wave, photoacoustic imaging offers high-resolution imaging in depth beyond the optical diffusion limit. Photoacoustic imaging is frequently used in conjunction with ultrasound as a hybrid modality. The combination enables the acquisition of both optical and acoustic contrasts of tissue, providing functional, structural, molecular, and vascular information within the same field of view. In this review, we first described the principles of various photoacoustic and ultrasound imaging techniques and then classified the dual-modal imaging systems based on their preclinical and clinical imaging applications. The advantages of dual-modal imaging were thoroughly analyzed. Finally, the review ends with a critical discussion of existing developments and a look toward the future.

Hermite-scan imaging for differentiating glioblastoma from normal brain: Simulations and ex vivo studies for applications in intra-operative tumor identificationa)

Hermite-scan (H-scan) imaging is a tissue characterization technique based on the analysis of raw ultrasound radio frequency (RF) echoes. It matches the RF echoes to Gaussian-weighted Hermite polynomials of various orders to extract information related to scatterer diameter. It provides a color map of large and small scatterers in the red and blue H-scan image channels, respectively. H-scan has been previously reported for characterizing breast, pancreatic, and thyroid tumors. The present work evaluated H-scan imaging to differentiate glioblastoma tumors from normal brain tissue ex vivo. First, we conducted 2-D numerical simulations using the k-wave toolbox to assess the performance of parameters derived from H-scan images of acoustic scatterers (15-150 μm diameters) and concentrations (0.2%-1% w/v). We found that the parameter intensity-weighted percentage of red (IWPR) was sensitive to changes in scatterer diameters independent of concentration. Next, we assessed the feasibility of using the IWPR parameter for differentiating glioblastoma and normal brain tissues (n = 11 samples per group). The IWPR parameter estimates for normal tissue (44.1% ± 1.4%) were significantly different (p < 0.0001) from those for glioblastoma (36.2% ± 0.65%). These findings advance the development of H-scan imaging for potential use in differentiating glioblastoma tumors from normal brain tissue during resection surgery.

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.

Optimized Simultaneous Axial Multifocal Imaging via Frequency Multiplexed Focusing

Simultaneous axial multifocal imaging (SAMI) using a single acoustical transmission was developed to enhance the depth of field. This technique transmits a superposition of axial multifoci waveforms in a single transmission, thus increasing the frame rate. However, since all the waveforms are transmitted at a constant center frequency, there is a tradeoff between attenuation and lateral resolution when choosing a constant frequency for all the axial depths. In this work, we developed an optimized SAMI method by adding frequency dependence to each axial multifocus. By gradually increasing the frequency as a function of the focal depth, this method makes it possible to compensate for the gradually increasing F-number in order to achieve constant lateral resolution across the entire field of view. Alternatively, by gradually decreasing the axial multifoci frequencies as a function of depth, enhanced penetration depth and contrast are obtained. This method, termed frequency multiplexed SAMI (FM-SAMI), is described analytically and validated by resolution and contrast experiments performed on resolution targets, tissue-mimicking phantoms, and ex vivo biological samples. This is the first real-time implementation of a frequency multiplexing approach for axial multifoci imaging that facilitates high-quality imaging at an increased frame rate.

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.

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.

Fine-tuning the H-scan for discriminating changes in tissue scatterers

The H-scan approach ('H' denoting hue, or Hermite) is a recent matched filter methodology that aims to add information to the traditional ultrasound B-scan. The theory is based on the differences in the echoes produced by different classes of reflectors or scatterers. Matched filters can be created for different types of scatterers, whereby the maximum output indicates a match, and color schemes can be used to indicate the class of scatterer responsible for echoes, providing a visual interpretation of the results. However, within the theory of weak scattering from a variety of shapes, small changes in the size of the inhomogeneous objects will create shifts in the scattering transfer function. In this paper, we argue for a general power law transfer function as the canonical model for transfer functions from most normal soft vascularized tissues, at least over some bandpass spectrum illuminated by the incident pulse. In cases where scatterer size and distributions change, this produces a corresponding shift in center frequency, along with time and frequency domain characteristics of echoes, and these are captured by matched filters to distinguish and visualize in color the major characteristics of scattering types. With this general approach, the H-scan matched filters can be set to elicit more fine grain shifts in scattering types, commensurate with more subtle changes in tissue morphology. Compensation for frequency-dependent attenuation is helpful for avoiding beam softening effects with increasing depths. Examples from phantoms and normal and pathological tissues are provided to demonstrate that the H-scan analysis and displays are sensitive to scatterer size and morphology, and can be adapted to conventional imaging systems.

Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging

Breast cancer is one of the most common cancers among women worldwide. Ultrasound imaging has been widely used in the detection and diagnosis of breast tumors. However, due to factors such as limited spatial resolution and speckle noise, classification of benign and malignant breast tumors using conventional B-mode ultrasound still remains a challenging task. H-scan is a new ultrasound technique that images the relative size of acoustic scatterers. However, the feasibility of H-scan ultrasound imaging in the classification of benign and malignant breast tumors has not been investigated. In this paper, we proposed a new method based on H-scan ultrasound imaging to classify benign and malignant breast tumors. Backscattered ultrasound radiofrequency signals of 100 breast tumors were used (48 benign and 52 malignant cases). H-scan ultrasound images were constructed with the radiofrequency signals by matched filtering using Gaussian-weighted Hermite polynomials. Experimental results showed that benign breast tumors had more red components, while malignant breast tumors had more blue components in H-scan ultrasound images. There were significant differences between the RGB channels of H-scan ultrasound images of benign and malignant breast tumors. We conclude H-scan ultrasound imaging can be used as a new method for classifying benign and malignant breast tumors.