Publications by authors named "Parag Chitnis"

Rehabilitation from musculoskeletal injuries focuses on reestablishing and monitoring muscle activation patterns to accurately produce force. The aim of this study is to explore the use of a novel low-powered wearable distributed Simultaneous Musculoskeletal Assessment with Real-Time Ultrasound (SMART-US) device to predict force during an isometric squat task. Participants (N = 5) performed maximum isometric squats under two medical imaging techniques; clinical musculoskeletal motion mode (m-mode) ultrasound on the dominant vastus lateralis and SMART-US sensors placed on the rectus femoris, vastus lateralis, medial hamstring, and vastus medialis.

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Objective: Wearable ultrasound is emerging as a new paradigm of real-time imaging in freely moving humans and has wide applications from cardiovascular health monitoring to human gesture recognition. However, current wearable ultrasound devices have typically employed pulse-echo imaging which requires high excitation voltages and sampling rates, posing safety risks, and requiring specialized hardware. Our objective was to develop and evaluate a wearable ultrasound system based on time delay spectrometry (TDS) that utilizes low-voltage excitation and significantly simplified instrumentation.

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Wearable ultrasound has the potential to become a disruptive technology enabling new applications not only in traditional clinical settings, but also in settings where ultrasound is not currently used. Understanding the basic engineering principles and limitations of wearable ultrasound is critical for clinicians, scientists, and engineers to advance potential applications and translate the technology from bench to bedside. Wearable ultrasound devices, especially monitoring devices, have the potential to apply acoustic energy to the body for far longer durations than conventional diagnostic ultrasound systems.

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Indocyanine green (ICG) is an FDA approved dye widely used for fluorescence imaging in research, surgical navigation, and medical diagnostics. However, ICG has a few drawbacks, such as concentration-dependent aggregation and absorbance, nonspecific cellular targeting, and rapid photobleaching. Here, we report a novel DNA-based nanosensor platform that utilizes monomers of ICG and cholesterol.

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Fluorescence and photoacoustic imaging techniques offer valuable insights into cell- and tissue-level processes. However, these optical imaging modalities are limited by scattering and absorption in tissue, resulting in the low-depth penetration of imaging. Contrast-enhanced imaging in the near-infrared window improves imaging penetration by taking advantage of reduced autofluorescence and scattering effects.

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Levator ani muscle (LAM) avulsion is a common complication of vaginal childbirth and is linked to several pelvic floor disorders. Diagnosing and treating these conditions require imaging of the pelvic floor and examination of the obtained images, which is a time-consuming process subjected to operator variability. In our study, we proposed using deep learning (DL) to automate the segmentation of the LAM from 3D endovaginal ultrasound images (EVUS) to improve diagnostic accuracy and efficiency.

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In this study, we investigated the performance of four deep learning frameworks of U-Net, U-NeXt, DeepLabV3+, and ConResNet in multi-class pixel-based segmentation of the extraocular muscles (EOMs) from coronal MRI. Performances of the four models were evaluated and compared with the standard F-measure-based metrics of intersection over union (IoU) and Dice, where the U-Net achieved the highest overall IoU and Dice scores of 0.77 and 0.

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Introduction: Patellar tendon adaptations occur in response to mechanical load. Appropriate loading is necessary to elicit positive adaptations with increased risk of injury and decreased performance likely if loading exceeds the capacity of the tendon. The aim of the current study was to examine intra-individual associations between workloads and patellar tendon properties and neuromuscular performance in collegiate volleyball athletes.

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Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-crafted parameters to achieve good performance. Many iterations are usually required to reconstruct a high-quality image, which is computationally expensive due to repeated evaluations of the physical model.

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Near-infrared photoacoustic imaging (NIR-PAI) combines the advantages of optical and ultrasound imaging to provide anatomical and functional information of tissues with high resolution. Although NIR-PAI is promising, its widespread use is hindered by the limited availability of NIR contrast agents. J-aggregates (JA) made of indocyanine green dye (ICG) represents an attractive class of biocompatible contrast agents for PAI.

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Electrical muscle stimulation (EMS) is widely used in rehabilitation and athletic training to generate involuntary muscle contractions. However, EMS leads to rapid muscle fatigue, limiting the force a muscle can produce during prolonged use. Currently available methods to monitor localized muscle fatigue and recovery are generally not compatible with EMS.

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Traditional implanted drug delivery systems cannot easily change their release profile in real time to respond to physiological changes. Here we present a microfluidic aqueous two-phase system to generate microcapsules that can release drugs on demand as triggered by focused ultrasound (FUS). The biphasic microcapsules are made of hydrogels with an outer phase of mixed molecular weight (MW) poly(ethylene glycol) diacrylate that mitigates premature payload release and an inner phase of high MW dextran with payload that breaks down in response to FUS.

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Conventional reconstruction methods for photoacoustic images are not suitable for the scenario of sparse sensing and geometrical limitation. To overcome these challenges and enhance the quality of reconstruction, several learning-based methods have recently been introduced for photoacoustic tomography reconstruction. The goal of this study is to compare and systematically evaluate the recently proposed learning-based methods and modified networks for photoacoustic image reconstruction.

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Photoacoustic tomography (PAT) is a non-ionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their "view" of the imaging target, which result in image reconstruction artifacts degrading image quality. Iterative reconstruction methods can be used to reduce artifacts but are computationally expensive.

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Heterogeneity of echo-texture and lack of sharply delineated tissue boundaries in diagnostic ultrasound images make three-dimensional (3D) registration challenging, especially when the volumes to be registered are considerably different due to local changes. We implemented a novel computational method that optimally registers volumetric ultrasound image data containing significant and local anatomical differences. It is A Multi-stage, Multi-resolution, and Multi-volumes-of-interest Volume Registration Method.

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Photoacoustic imaging is an emerging imaging modality that is based upon the photoacoustic effect. In photoacoustic tomography (PAT), the induced acoustic pressure waves are measured by an array of detectors and used to reconstruct an image of the initial pressure distribution. A common challenge faced in PAT is that the measured acoustic waves can only be sparsely sampled.

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Objective: To assess age-related changes in the pelvic floor muscular hiatus and their association with symptoms of pelvic organ prolapse, urinary and fecal incontinence, and sexual function.

Methods: In this pilot study we performed 3D endovaginal ultrasonography in two age groups of nulliparous women: 18 to 40 years and 52 to 85 years. Anterior-posterior (AP) diameter, left-right (LR) diameter, and the Minimal Levator Hiatus area were measured.

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Detection of inertial and stable cavitation is important for guiding high-intensity focused ultrasound (HIFU). Acoustic transducers can passively detect broadband noise from inertial cavitation and the scattering of HIFU harmonics from stable cavitation bubbles. Conventional approaches to cavitation noise diagnostics typically involve computing the Fourier transform of the time-domain noise signal, applying a custom comb filter to isolate the frequency components of interest, followed by an inverse Fourier transform.

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Objective Ventricular shunts are a mainstay of hydrocephalus treatment, but the detection of its clinical failure often relies on circumstantial evidence. A direct, non-interventional method for reliably evaluating cerebrospinal fluid (CSF) function does not exist due to the difficulty of measuring in vivo flow characteristics. The objective of this study is to apply a novel method of ultrasound monitoring to characterize the oscillation observed during pulsatile CSF flow and failure states in an in vitro and cadaveric model.

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A frequency-domain, non-contact approach to photoacoustic microscopy (PAM) that employs amplitude-modulated (0.1-1 MHz) laser for excitation (638-nm pump) in conjunction with a 2-wave mixing interferometer (532-nm probe) for non-contact detection of photoacoustic waves at the specimen surface is presented. A lock-in amplifier is employed to detect the photoacoustic signal.

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Hydrocephalus, where cerebrospinal fluid (CSF) production rate is greater than reabsorption rate, leads to impaired neurological function if left untreated. Ventriculoperitoneal shunts (VPS) are implanted in the brain ventricles to route CSF. VPS systems have a high failure rate, and failure symptoms resemble symptoms of common maladies.

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The subharmonic threshold for ultrasound contrast agents has been defined as a 20-25 dB difference between the fundamental and subharmonic (2/1) spectral components of the backscatter signal. However, this Fourier-based criterion assumes a linear time-invariant signal. A more appropriate criterion for short cycle and frequency-modulated waveforms is proposed with an adaptive signal-processing approach based on the empirical mode decomposition (EMD) method.

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Implantable devices have a large potential to improve human health, but they are often made of biofouling materials that necessitate special coatings, rely on electrical connections for external communication, and require a continuous power source. This paper demonstrates an alternative platform, which we call iTAG (implantable thermally actuated gel), where an implanted capsule can be wirelessly controlled by ultrasound to trigger the release of compounds. We constructed a millimeter-sized capsule containing a co-polymer gel (NiPAAm-co-AAm) that contracts above body temperature (i.

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Polymer-shelled ultrasound contrast agents (UCAs) may expel their encapsulated gas subject to ultrasound-induced shell buckling or rupture. Nonlinear oscillations of this gas bubble can produce a subharmonic component in the ultrasound backscatter. This study investigated the relationship between this gas-release mechanism and shell-thickness-to-radius ratios (STRRs) of polymer-shelled UCAs.

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This paper presents an adaptive synthetic-focusing scheme that, when applied to photoacoustic (PA) data acquired using an annular array, improves focusing across a greater imaging depth and enhances spatial resolution. The imaging system was based on a 40-MHz, 5-element, annular-array transducer with a focal length of 12 mm and an 800-µm diameter hole through its central element to facilitate coaxial delivery of 532-nm laser. The transducer was raster-scanned to facilitate 3D acquisition of co-registered ultrasound and PA image data.

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