2-D Ultrasonic Array-Based Optical Coherence Elastography

Near-infrared spectroscopy-enabled electromechanical systems for fast mapping of biomechanics and subcutaneous diagnosis

Fast and accurate assessment of skin mechanics holds great promise in diagnosing various epidermal diseases, yet substantial challenges remain in developing simple and wearable strategies for continuous monitoring. Here, we present a design concept, named active near-infrared spectroscopy patch (ANIRP) for continuously mapping skin mechanics. ANIRP addresses these challenges by integrating near-infrared (NIR) sensing with mechanical actuators, enabling rapid measurement (<1 s) of Young's modulus, high spatial sensing density (~1 cm2), and high spatial sensitivity (<1 mm). Unlike conventional electromechanical sensors, NIR sensors precisely capture vibrational frequencies propagated from the actuators without needing ultraclose contact, enhancing wearing comfort. Demonstrated examples include ANIRPs for comprehensively moduli mapping of artificial tissues with varied mechanical properties emulating tumorous fibrosis. On-body validation of the ANIRP across skin locations confirms its practical utility for clinical monitoring of epidermal mechanics, promising considerable advancements in real-time, noninvasive skin diagnostics and continuous health monitoring.

Optical coherence elastography and its applications for the biomechanical characterization of tissues

The biomechanical characterization of the tissues provides significant evidence for determining the pathological status and assessing the disease treatment. Incorporating elastography with optical coherence tomography (OCT), optical coherence elastography (OCE) can map the spatial elasticity distribution of biological tissue with high resolution. After the excitation with the external or inherent force, the tissue response of the deformation or vibration is detected by OCT imaging. The elastogram is assessed by stress-strain analysis, vibration amplitude measurements, and quantification of elastic wave velocities. OCE has been used for elasticity measurements in ophthalmology, endoscopy, and oncology, improving the precision of diagnosis and treatment of disease. In this article, we review the OCE methods for biomechanical characterization and summarize current OCE applications in biomedicine. The limitations and future development of OCE are also discussed during its translation to the clinic.

An improved Fourier Ptychography algorithm for ultrasonic array imaging

Inspired by the optical imaging algorithm, the Fourier Ptychography (FP) algorithm is adopted to improve the resolution of ultrasonic array imaging. In the FP algorithm, the steady-state spectrum is utilized to recover the high-resolution ultrasonic images. Meanwhile, the parameters of FP algorithm are empirical, which can affect the imaging quality of ultrasonic array. Then the particle swarm optimization (PSO) algorithm is used to optimize the parameters of FP algorithm to further improve the imaging quality of ultrasonic array. The tungsten imaging experiments and pig eye imaging experiments are conducted to demonstrate the feasibility and effectiveness of the developed algorithm. In addition, the proposed algorithm and the coherent wave superposition (CWS) algorithm are both based on single plane wave (SPW) algorithms and they are then compared. The results show that the CWS algorithm and FP algorithm have good longitudinal and lateral resolutions, respectively. The particle swarm optimization-based FP (PSOFP) imaging algorithm has both excellent lateral and longitudinal resolutions. The average lateral resolution of PSOFP imaging algorithm is improved by 34.47% compared with CWS imaging algorithm in the tungsten wires experiments, and the lateral boundary structure width of the lens is improved by 49.48% in the pig eye experiments. The proposed algorithm can effectively improve the ultrasonic imaging quality for medical application.

In vivo corneal elastography: A topical review of challenges and opportunities

Clinical measurement of corneal biomechanics can aid in the early diagnosis, progression tracking, and treatment evaluation of ocular diseases. Over the past two decades, interdisciplinary collaborations between investigators in optical engineering, analytical biomechanical modeling, and clinical research has expanded our knowledge of corneal biomechanics. These advances have led to innovations in testing methods (ex vivo, and recently, in vivo) across multiple spatial and strain scales. However, in vivo measurement of corneal biomechanics remains a long-standing challenge and is currently an active area of research. Here, we review the existing and emerging approaches for in vivo corneal biomechanics evaluation, which include corneal applanation methods, such as ocular response analyzer (ORA) and corneal visualization Scheimpflug technology (Corvis ST), Brillouin microscopy, and elastography methods, and the emerging field of optical coherence elastography (OCE). We describe the fundamental concepts, analytical methods, and current clinical status for each of these methods. Finally, we discuss open questions for the current state of in vivo biomechanics assessment techniques and requirements for wider use that will further broaden our understanding of corneal biomechanics for the detection and management of ocular diseases, and improve the safety and efficacy of future clinical practice.

In Vivo Biomechanical Measurements of the Cornea

In early corneal examinations, the relationships between the morphological and biomechanical features of the cornea were unclear. Although consistent links have been demonstrated between the two in certain cases, these are not valid in many diseased states. An accurate assessment of the corneal biomechanical properties is essential for understanding the condition of the cornea. Studies on corneal biomechanics in vivo suggest that clinical problems such as refractive surgery and ectatic corneal disease are closely related to changes in biomechanical parameters. Current techniques are available to assess the mechanical characteristics of the cornea in vivo. Accordingly, various attempts have been expended to obtain the relevant mechanical parameters from different perspectives, using the air-puff method, ultrasound, optical techniques, and finite element analyses. However, a measurement technique that can comprehensively reflect the full mechanical characteristics of the cornea (gold standard) has not yet been developed. We review herein the in vivo measurement techniques used to assess corneal biomechanics, and discuss their advantages and limitations to provide a comprehensive introduction to the current state of technical development to support more accurate clinical decisions.

Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation

Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and medical imaging. However, only a few studies on how to generate acoustic holograms have been conducted, and even conventional acoustic hologram algorithms show limited performance in the fast and accurate generation of acoustic holograms, thus hindering the development of novel applications. We here propose a deep learning-based framework to achieve fast and accurate acoustic hologram generation. The framework has an autoencoder-like architecture; thus, the unsupervised training is realized without any ground truth. For the framework, we demonstrate a newly developed hologram generator network, the holographic ultrasound generation network (HU-Net), which is suitable for unsupervised learning of hologram generation, and a novel loss function that is devised for energy-efficient holograms. Furthermore, for considering various hologram devices (i.e., ultrasound transducers), we propose a physical constraint (PC) layer. Simulation and experimental studies were carried out for two different hologram devices, such as a 3-D printed lens, attached to a single element transducer, and a 2-D ultrasound array. The proposed framework was compared with the iterative angular spectrum approach (IASA) and the state-of-the-art (SOTA) iterative optimization method, Diff-PAT. In the simulation study, our framework showed a few hundred times faster generation speed, along with comparable or even better reconstruction quality, than those of IASA and Diff-PAT. In the experimental study, the framework was validated with 3-D printed lenses fabricated based on different methods, and the physical effect of the lenses on the reconstruction quality was discussed. The outcomes of the proposed framework in various cases (i.e., hologram generator networks, loss functions, and hologram devices) suggest that our framework may become a very useful alternative tool for other existing acoustic hologram applications, and it can expand novel medical applications.

2-D Array Design and Fabrication With Pitch-Shifting Interposer at Frequencies From 4 MHz up to 10 MHz

High element density and strict constraints of the element's size have significantly limited the design and fabrication of 2-D ultrasonic arrays, especially fully sampled 2-D arrays. Recently, 3-D printing technology has been one of the most rapidly developing fields. Along with the great progress of 3-D printing technology, complex and detailed 3-D structures have become readily available with a short iteration cycle, which allows us to reduce the complexity of routing and helps to ameliorate assembly problems in 2-D ultrasound array fabrication. In this work, we designed and fabricated 2-D ultrasound arrays for an array of applications with a pitch-shifting interposer, which allowed us to fit different array designs with the same circuit design and significantly reduce the requirements in routing and connection for 2-D array fabrication at frequencies from 4 to 10 MHz. Results demonstrated that this design would make 2-D arrays more available and affordable.

In vivo assessment of corneal biomechanics under a localized cross-linking treatment using confocal air-coupled optical coherence elastography

The localized application of the riboflavin/UV-A collagen cross-linking (UV-CXL) corneal treatment has been proposed to concentrate the stiffening process only in the compromised regions of the cornea by limiting the epithelium removal and irradiation area. However, current clinical screening devices dedicated to measuring corneal biomechanics cannot provide maps nor spatial-dependent changes of elasticity in corneas when treated locally with UV-CXL. In this study, we leverage our previously reported confocal air-coupled ultrasonic optical coherence elastography (ACUS-OCE) probe to study local changes of corneal elasticity in three cases: untreated, half-CXL-treated, and full-CXL-treated in vivo rabbit corneas (n = 8). We found a significant increase of the shear modulus in the half-treated (>450%) and full-treated (>650%) corneal regions when compared to the non-treated cases. Therefore, the ACUS-OCE technology possesses a great potential in detecting spatially-dependent mechanical properties of the cornea at multiple meridians and generating elastography maps that are clinically relevant for patient-specific treatment planning and monitoring of UV-CXL procedures.

Elasticity measurements of ocular anterior and posterior segments using optical coherence elastography

The changes of biomechanical properties, especially the elasticity of the ocular tissues, are closely related to some ophthalmic diseases. Currently, the ophthalmic optical coherence elastography (OCE) systems are dedicated either to the anterior segment or to the retina. The elasticity measurements of the whole eye remain challenging. Here we demonstrated an acoustic radiation force optical coherence elastography (ARF-OCE) method to quantify the elasticity of the cornea and the retina. The experiment results show that the Young's moduli of the cornea and the retina were 16.66 ± 6.51 kPa and 207.96 ± 4.75 kPa, respectively. Our method can measure the elasticity of the anterior segment and the posterior segment, and provides a powerful tool to enhance ophthalmology research.

Wave-based optical coherence elastography: The 10-year perspective

After 10 years of progress and innovation, optical coherence elastography (OCE) based on the propagation of mechanical waves has become one of the major and the most studied OCE branches, producing a fundamental impact in the quantitative and nondestructive biomechanical characterization of tissues. Preceding previous progress made in ultrasound and magnetic resonance elastography; wave-based OCE has pushed to the limit the advance of three major pillars: (1) implementation of novel wave excitation methods in tissues, (2) understanding new types of mechanical waves in complex boundary conditions by proposing advance analytical and numerical models, and (3) the development of novel estimators capable of retrieving quantitative 2D/3D biomechanical information of tissues. This remarkable progress promoted a major advance in answering basic science questions and the improvement of medical disease diagnosis and treatment monitoring in several types of tissues leading, ultimately, to the first attempts of clinical trials and translational research aiming to have wave-based OCE working in clinical environments. This paper summarizes the fundamental up-to-date principles and categories of wave-based OCE, revises the timeline and the state-of-the-art techniques and applications lying in those categories, and concludes with a discussion on the current challenges and future directions, including clinical translation research.

Ultrasound Elastography under Deep Learning Algorithm to Analyze the Therapeutic Effect of Clustered Regularly Interspaced Short Palindromic Repeats Short Hairpin Ribonucleic Acid Nanoparticles on Cervical Cancer

This study aimed to analyze the effect of the deep learning algorithm on ultrasound elastography on the treatment of cervical cancer with clustered regularly interspaced short palindromic repeats (CRISPR) short hairpin ribonucleic acid (shRNA) nanoparticles, aiming to provide a reference for the clinical application of deep learning to analyze the therapeutic effect of the disease. In this study, CRISPR and shRNA plasmid nanoparticle drugs were used to treat 55 patients with cervical cancer in the experimental group, and normal saline was injected to another 53 patients in the control group, so compare the effect of nanoparticles in the treatment of cervical cancer. Professional doctors and the recurrent neural network (RNN) intelligent algorithm were used to score cervical cancer based on the ultrasound elastograph images by taking blue, green, and red (BGR) as diagnosis criteria. As a result, the experimental group had a total of 217 points before drug administration and a total of 224 points after drug administration. Each patient had an average increase of 0.13 points. The control group had a total of 200 points before drug administration and a total of 223 points after drug administration, and each patient had an average increase of 0.43 points. The experimental group was obviously different from the control group (P < 0.05). Each tissue image output by the RNN was clearer than the original image, and the score given by intelligent calculation was faster than that of professional doctors. The monitoring effect of the deep learning RNN intelligent algorithm on the therapeutic effect of nanomedicine was analyzed. It was found that the average accuracy of the experimental group and the control group was 98.95% and 90.34%, respectively; and the experimental group was greatly different from the control group (P < 0.05). In short, nano-CRISPR and shRNA drugs had remarkable effects on the treatment of cervical cancer, and the scores given by the deep learning intelligent algorithm were faster and more accurate, which provided theoretical guidance for the clinical application of deep learning algorithms to analyze the treatment effects of diseases.