Combined dual-channel fluorescence depth sensing of indocyanine green and protoporphyrin IX kinetics in subcutaneous murine tumors.

Significance: Fluorescence sensing within tissue is an effective tool for tissue characterization; however, the modality and geometry of the image acquisition can alter the observed signal.

Aim: We introduce a novel optical fiber-based system capable of measuring two fluorescent contrast agents through 2 cm of tissue with simple passive electronic switching between the excitation light, simultaneously acquiring fluorescence and excitation data. The goal was to quantify indocyanine green (ICG) and protoporphyrin IX (PpIX) within tissue, and the sampling method was compared with wide-field surface imaging to contrast the value of deep sensing versus surface imaging.

Rapid wideband characterization of viscoelastic material properties by Bessel function-based time harmonic ultrasound elastography (B-THE).

Elastography is an emerging diagnostic technique that uses conventional imaging modalities such as sonography or magnetic resonance imaging to quantify tissue stiffness. However, different elastography methods provide different stiffness values, which require calibration using well-characterized phantoms or tissue samples. A comprehensive, fast, and cost-effective elastography technique for phantoms or tissue samples is still lacking.

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.

Integrating Learning-based Priors with Physics-based Models in Ultrasound Elasticity Reconstruction.

Ultrasound elastography images which enable quantitative visualization of tissue stiffness can be reconstructed by solving an inverse problem. Classical model-based methods are usually formulated in terms of constrained optimization problems. To stabilize the elasticity reconstructions, regularization techniques such as Tikhonov method are used with the cost of promoting smoothness and blurriness in the reconstructed images.

Brain elastography in aging relates to fluid/solid trendlines.

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury.

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.

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.

Probing Tissue Viscoelasticity With STL Ultrasound Shearwave Spectroscopy Using Cole-Cole Diagrams.

Objective: Viscoelasticity is mapped by dispersion in shearwave elastography. Incomplete spectral information of shearwaves is therefore used to estimate mechanical stiffness. We propose capturing the "full-waveform-information" of the shear wave spectra to better resolve complex shear modulus μ (ω).

Shear wave elastography can stratify rectal cancer response to short-course radiation therapy.

Rectal cancer is a deadly disease typically treated using neoadjuvant chemoradiotherapy followed by total mesorectal excision surgery. To reduce the occurrence of mesorectal excision surgery for patients whose tumors regress from the neoadjuvant therapy alone, conventional imaging, such as computed tomography (CT) or magnetic resonance imaging (MRI), is used to assess tumor response to neoadjuvant therapy before surgery. In this work, we hypothesize that shear wave elastography offers valuable insights into tumor response to short-course radiation therapy (SCRT)-information that could help distinguish radiation-responsive from radiation-non-responsive tumors and shed light on changes in the tumor microenvironment that may affect radiation response.

Stiffness pulsation of the human brain detected by non-invasive time-harmonic elastography.

Cerebral pulsation is a vital aspect of cerebral hemodynamics. Changes in arterial pressure in response to cardiac pulsation cause cerebral pulsation, which is related to cerebrovascular compliance and cerebral blood perfusion. Cerebrovascular compliance and blood perfusion influence the mechanical properties of the brain, causing pulsation-induced changes in cerebral stiffness.

Mapping estimates of vascular permeability with a clinical indocyanine green fluorescence imaging system in experimental pancreatic adenocarcinoma tumors.

Significance: Pancreatic cancer tumors are known to be avascular, but their neovascular capillaries are still chaotic leaky vessels. Capillary permeability could have significant value for therapy assessment, and its quantification might be possible with macroscopic imaging of indocyanine green (ICG) kinetics in tissue.

Aim: The capacity of using standard fluorescence surgical systems for ICG kinetic imaging as a probe for capillary leakage was evaluated using a clinical surgical fluorescence imaging system, as interpreted through vascular permeability modeling.

Artificial intelligence for diffusion MRI-based tissue microstructure estimation in the human brain: an overview.

Artificial intelligence (AI) has made significant advances in the field of diffusion magnetic resonance imaging (dMRI) and other neuroimaging modalities. These techniques have been applied to various areas such as image reconstruction, denoising, detecting and removing artifacts, segmentation, tissue microstructure modeling, brain connectivity analysis, and diagnosis support. State-of-the-art AI algorithms have the potential to leverage optimization techniques in dMRI to advance sensitivity and inference through biophysical models.

Reverberant magnetic resonance elastographic imaging using a single mechanical driver.

Reverberant elastography provides fast and robust estimates of shear modulus; however, its reliance on multiple mechanical drivers hampers clinical utility. In this work, we hypothesize that for constrained organs such as the brain, reverberant elastography can produce accurate magnetic resonance elastograms with a single mechanical driver. To corroborate this hypothesis, we performed studies on healthy volunteers (= 3); and a constrained calibrated brain phantom containing spherical inclusions with diameters ranging from 4-18 mm.

Functional ultrasound imaging reveals 3D structure of orientation domains in ferret primary visual cortex.

Background And Purpose: The sensory cortex is organized into "maps" that represent sensory space across cortical space. In primary visual cortex (V1) of highly visual mammals, multiple visual feature maps are organized into a functional architecture anchored by orientation domains: regions containing neurons preferring the same stimulus orientation. Although the pinwheel-like structure of orientation domains is well-characterized in the superficial cortical layers in dorsal regions of V1, the 3D shape of orientation domains spanning all 6 cortical layers and across dorsal and ventral regions of V1 has never been revealed.

Separation of mainlobe and sidelobe contributions to B-mode ultrasound images based on the aperture spectrum.

Purpose: Isolating the mainlobe and sidelobe contribution to the ultrasound image can improve imaging contrast by removing off-axis clutter. Previous work achieves this separation of mainlobe and sidelobe contributions based on the covariance of received signals. However, the formation of a covariance matrix at each imaging point can be computationally burdensome and memory intensive for real-time applications.

Volumetric tri-modal imaging with combined photoacoustic, ultrasound, and shear wave elastography.

Photoacoustic imaging is a hybrid imaging approach that combines the advantages of optical and ultrasonic imaging in one modality. However, for comprehensive tissue characterization, optical contrast alone is not always sufficient. In this study, we combined photoacoustic imaging with high-resolution ultrasound and shear wave elastography.

Imaging the Local Nonlinear Viscoelastic Properties of Soft Tissues: Initial Validation and Expected Benefits.

Imaging tissue mechanical properties has shown promise in noninvasive assessment of numerous pathologies. Researchers have successfully measured many linear tissue mechanical properties in laboratory and clinical settings. Currently, multiple complex mechanical effects such as frequency-dependence, anisotropy, and nonlinearity are being investigated separately.

Second-Generation Dual Scan Mammoscope With Photoacoustic, Ultrasound, and Elastographic Imaging Capabilities.

We recently developed the photoacoustic dual-scan mammoscope (DSM), a system that images the patient in standing pose analog to X-ray mammography. The system simultaneously acquires three-dimensional photoacoustic and ultrasound (US) images of the mildly compressed breast. Here, we describe a second-generation DSM (DSM-2) system that offers a larger field of view, better system stability, higher ultrasound imaging quality, and the ability to quantify tissue mechanical properties.

Enabling quantitative robot-assisted compressional elastography via the extended Kalman filter.

Compressional or quasi-static elastography has demonstrated the capability to detect occult cancers in a variety of tissue types, however it has a serious limitation in that the resulting elastograms are generally qualitative whereas other forms of elastography, such as shear-wave, can produce absolute measures of elasticity for histopathological classification. We address this limitation by introducing a stochastic method using an extended Kalman filter and robot-assistance to obtain quantitative elastograms which are resilient to measurement noise and system uncertainty. In this paper, the probabilistic framework is described, which utilizes many ultrasound acquisitions obtained from multiple palpations, to fuse data and uncertainty from a robotic manipulator's joint encoders and force/torque sensor directly into the inverse reconstruction of the elastogram.

Single-shell NODDI using dictionary-learner-estimated isotropic volume fraction.

Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular, and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize brain tissue microstructure. Single-shell reconstruction for NODDI parameters has been discouraged in previous studies caused by failure when fitting, especially for the neurite density index (NDI).

A Robust and Fast Method for 2-D Shear Wave Speed Calculation.

We developed a new method, called the tangent plane method (TPM), for more efficiently and accurately estimating 2-D shear wave speed (SWS) from any direction of wave propagation. In this technique, we estimate SWS by solving the Eikonal equation because this approach is more robust to noise. To further enhance the performance, we computed the tangent plane of the arrival time surface.

H-scan, Shear Wave and Bioluminescent Assessment of the Progression of Pancreatic Cancer Metastases in the Liver.

The non-invasive quantification of tumor burden and the response to therapies remain an important objective for imaging modalities. To characterize the performance of two newly optimized ultrasound-based analyses, we applied shear wave and H-scan scattering analyses to repeated trans-abdominal ultrasound scans of a murine model of metastatic pancreatic cancer. In addition, bioluminescence measurements were obtained as an alternative reference.

Parallel Receive Beamforming Improves the Performance of Focused Transmit-Based Single-Track Location Shear Wave Elastography.

Single-track location shear wave elastography (STL-SWEI) is robust against speckle-induced noise in shear wave speed (SWS) estimates; however, it is not immune to other incoherent sources of noise (such as electronic noise) that increases the variance in SWS estimates. Although estimation averaging enabled by parallel receive beamforming adequately suppresses these noise sources, these beamforming techniques often rely on broad transmit beams (plane or diverging). While broad beam approaches, such as plane-wave imaging, are becoming ubiquitous in research ultrasound systems, clinical systems usually employ focused transmit beams due to compatibility with hardware beamforming and deeper penetration.

Shear Induced Non-Linear Elasticity Imaging: Elastography for Compound Deformations.

The goal of non-linear ultrasound elastography is to characterize tissue mechanical properties under finite deformations. Existing methods produce high contrast non-linear elastograms under conditions of pure uni-axial compression, but exhibit bias errors of 10-50% when the applied deformation deviates from the uni-axial condition. Since freehand transducer motion generally does not produce pure uniaxial compression, a motion-agnostic non-linearity estimator is desirable for clinical translation.