Investigating the Use of Traveltime and Reflection Tomography for Deep Learning-Based Sound-Speed Estimation in Ultrasound Computed Tomography.

Ultrasound computed tomography (USCT) quantifies acoustic tissue properties such as the speed-of-sound (SOS). Although full-waveform inversion (FWI) is an effective method for accurate SOS reconstruction, it can be computationally challenging for large-scale problems. Deep learning-based image-to-image learned reconstruction (IILR) methods can offer computationally efficient alternatives. This study investigates the impact of the chosen input modalities on IILR methods for high-resolution SOS reconstruction in USCT. The selected modalities are traveltime tomography (TT) and reflection tomography (RT), which produce a low-resolution SOS map and a reflectivity map, respectively. These modalities have been chosen for their lower computational cost relative to FWI and their capacity to provide complementary information: TT offers a direct SOS measure, while RT reveals tissue boundary information. Systematic analyses were facilitated by employing a virtual USCT imaging system with anatomically realistic numerical breast phantoms. Within this testbed, a supervised convolutional neural network (CNN) was trained to map dual-channel (TT and RT images) to a high-resolution SOS map. Single-input CNNs were trained separately using inputs from each modality alone (TT or RT) for comparison. The accuracy of the methods was systematically assessed using normalized root mean squared error (NRMSE), structural similarity index measure (SSIM), and peak signal-to-noise ratio (PSNR). For tumor detection performance, receiver operating characteristic analysis was employed. The dual-channel IILR method was also tested on clinical human breast data. Ensemble average of the NRMSE, SSIM, and PSNR evaluated on this clinical dataset were 0.2355, 0.8845, and 28.33 dB, respectively.

2-D Slicewise Waveform Inversion of Sound Speed and Acoustic Attenuation for Ring Array Ultrasound Tomography Based on a Block LU Solver.

Ultrasound tomography is an emerging imaging modality that uses the transmission of ultrasound through tissue to reconstruct images of its mechanical properties. Initially, ray-based methods were used to reconstruct these images, but their inability to account for diffraction often resulted in poor resolution. Waveform inversion overcame this limitation, providing high-resolution images of the tissue. Most clinical implementations, often directed at breast cancer imaging, currently rely on a frequency-domain waveform inversion to reduce computation time. For ring arrays, ray tomography was long considered a necessary step prior to waveform inversion in order to avoid cycle skipping. However, in this paper, we demonstrate that frequency-domain waveform inversion can reliably reconstruct high-resolution images of sound speed and attenuation without relying on ray tomography to provide an initial model. We provide a detailed description of our frequency-domain waveform inversion algorithm with open-source code and data that we make publicly available.

Sound Speed Estimation for Distributed Aberration Correction in Laterally Varying Media.

Spatial variation in sound speed causes aberration in medical ultrasound imaging. Although our previous work has examined aberration correction in the presence of a spatially varying sound speed, practical implementations were limited to layered media due to the sound speed estimation process involved. Unfortunately, most models of layered media do not capture the lateral variations in sound speed that have the greatest aberrative effect on the image. Building upon a Fourier split-step migration technique from geophysics, this work introduces an iterative sound speed estimation and distributed aberration correction technique that can model and correct for aberrations resulting from laterally varying media. We first characterize our approach in simulations where the scattering in the media is known a-priori. Phantom and in-vivo experiments further demonstrate the capabilities of the iterative correction technique. As a result of the iterative correction scheme, point target resolution improves by up to a factor of 4 and lesion contrast improves by up to 10.0 dB in the phantom experiments presented.

Effect of perfluorocarbon composition on activation of phase-changing ultrasound contrast agents.

BACKGROUND: While microbubble contrast agents (MCAs) are commonly used in ultrasound (US), they are inherently limited to vascular targets due to their size. Alternatively, phase-changing nanodroplet contrast agents (PNCAs) can be delivered as nanoscale agents (i.e., small enough to extravasate), but when exposed to a US field of sufficient mechanical index (MI), they convert to MCAs, which can be visualized with high contrast using nonlinear US. PURPOSE: To investigate the effect of perfluorocarbon (PFC) core composition and presence of cholesterol in particle coatings on stability and image contrast generated from acoustic activation of PNCAs using high-frequency US suitable for clinical imaging. METHODS: PNCAs with varied core compositions (i.e., mixtures of perfluoropentane [C5] and/or perfluorohexane [C6]) and two coating formulations (i.e., with and without cholesterol) were characterized and investigated for thermal/temporal stability and postactivation, nonlinear US contrast in phantom and in vivo environments. Through hydrophone measurements and nonlinear numerical modeling, MI was estimated for pulse sequences used for PNCA activation. RESULTS: All PNCA compositions were characterized to have similar diameters (249-267 nm) and polydispersity (0.151-0.185) following fabrication. While PNCAs with majority C5 core composition showed higher levels of spontaneous signal (i.e., not due to US activation) in phantoms than C6-majority PNCAs, all compositions were stable during imaging experiments. When activating PNCAs with a 12.3-MHz US pulse (MI = 1.1), C6-core particles with cholesterol-free coatings (i.e., CF-C6-100 particles) generated a median contrast of 3.1, which was significantly higher (p < 0.001) than other formulations. Further, CF-C6-100 particles were activated in a murine model, generating US contrast ≥ $ \ge $ 3.4. CONCLUSION: C6-core PNCAs can provide high-contrast US imaging with minimal nonspecific activation in phantom and in vivo environments.

Projection-based stereolithography for direct 3D printing of heterogeneous ultrasound phantoms.

Modern ultrasound (US) imaging is increasing its clinical impact, particularly with the introduction of US-based quantitative imaging biomarkers. Continued development and validation of such novel imaging approaches requires imaging phantoms that recapitulate the underlying anatomy and pathology of interest. However, current US phantom designs are generally too simplistic to emulate the structure and variability of the human body. Therefore, there is a need to create a platform that is capable of generating well-characterized phantoms that can mimic the basic anatomical, functional, and mechanical properties of native tissues and pathologies. Using a 3D-printing technique based on stereolithography, we fabricated US phantoms using soft materials in a single fabrication session, without the need for material casting or back-filling. With this technique, we induced variable levels of stable US backscatter in our printed materials in anatomically relevant 3D patterns. Additionally, we controlled phantom stiffness from 7 to >120 kPa at the voxel level to generate isotropic and anisotropic phantoms for elasticity imaging. Lastly, we demonstrated the fabrication of channels with diameters as small as 60 micrometers and with complex geometry (e.g., tortuosity) capable of supporting blood-mimicking fluid flow. Collectively, these results show that projection-based stereolithography allows for customizable fabrication of complex US phantoms.

Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.

As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO2) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO2) and in vivo rat arteries. Estimation error of absolute SO2 and change in SO2 reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO2 with PA imaging.

A tumor vessel-targeting fusion protein elicits a chemotherapeutic bystander effect in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease characterized by a prominent desmoplastic stroma that may constrain tumor progression but also limit the access of therapeutic drugs. In this study, we explored a tumor-targeting strategy that enlists an engineered anti-angiogenic protein consisting of endostatin and cytosine deaminase linked to uracil phosphoribosyltransferase (EndoCD). This protein selectively binds to tumor vessels to compromise tumor angiogenesis and converts the non-toxic 5-fluorocytosine (5-FC) to the cytotoxic 5-fluorouracil to produce a chemotherapeutic bystander effect at the pancreatic tumor site. We found that resveratrol increased the protein stability of EndoCD through suppression of chymotrypsin-like proteinase activity and synergistically enhances EndoCD-mediated 5-FC-induced cell killing. In various PDAC mouse models, the EndoCD/5-FC/resveratrol regimen decreased intratumoral vascular density and stroma formation and enhances apoptosis in tumors cells as well as in surrounding endothelial, pancreatic stellate, and immune cells, leading to reduced tumor growth and extended survival. Thus, the EndoCD/5-FC/resveratrol combination may be an effective treatment option for PDAC.

Croconaine rotaxane for acid activated photothermal heating and ratiometric photoacoustic imaging of acidic pH.

Absorption of 808 nm laser light by liposomes containing a pH sensitive, near-infrared croconaine rotaxane dye increases dramatically in weak acid. A stealth liposome composition permits acid activated, photothermal heating and also acts as an effective nanoparticle probe for ratiometric photoacoustic imaging of acidic pH in deep sample locations, including a living mouse.

Fluorinated graphene oxide; a new multimodal material for biological applications.

Fluorinated graphene oxide (FGO) is reported for the first time as a magnetically responsive drug carrier that can serve both as a magnetic resonance imaging (MRI) and photoacoustic contrast agent, under preclinical settings, and as a type of photothermal therapy. Its hydrophilic nature facilitates biocompatibility. FGO as a broad wavelength absorber, with high charge transfer and strong non-linear scattering is optimal for NIR laser-induced hyperthermia.