A.C. Sharma

Bio: A.C. Sharma is an academic researcher from Duke University. The author has contributed to research in topics: Neutron stimulated emission computed tomography & Semiconductor detector. The author has an hindex of 12, co-authored 26 publications receiving 729 citations. Previous affiliations of A.C. Sharma include Durham University.

A finite-element method model of soft tissue response to impulsive acoustic radiation force

Abstract: Several groups are studying acoustic radiation force and its ability to image the mechanical properties of tissue. Acoustic radiation force impulse (ARFI) imaging is one modality using standard diagnostic ultrasound scanners to generate localized, impulsive, acoustic radiation forces in tissue. The dynamic response of tissue is measured via conventional ultrasonic speckle-tracking methods and provides information about the mechanical properties of tissue. A finite-element method (FEM) model has been developed that simulates the dynamic response of tissues, with and without spherical inclusions, to an impulsive acoustic radiation force excitation from a linear array transducer. These FEM models were validated with calibrated phantoms. Shear wave speed, and therefore elasticity, dictates tissue relaxation following ARFI excitation, but Poisson's ratio and density do not significantly alter tissue relaxation rates. Increased acoustic attenuation in tissue increases the relative amount of tissue displacement in the near field compared with the focal depth, but relaxation rates are not altered. Applications of this model include improving image quality, and distilling material and structural information from tissue's dynamic response to ARFI excitation. Future work on these models includes incorporation of viscous material properties and modeling the ultrasonic tracking of displaced scatterers.

Acoustic radiation force impulse imaging of in vivo breast masses

Abstract: Acoustic radiation force impulse (ARFI) imaging utilizes brief, high energy, focused acoustic pulses to generate radiation force in tissue, and conventional ultrasonic correlation-based methods to track the resulting tissue displacements in order to image the relative mechanical properties of tissue. In an ongoing clinical study, ARFI datasets from in vivo breast masses are acquired prior to core biopsy. Matched B-mode and ARFI images are generated for each mass. Data sets are divided based upon biopsy results, and images are evaluated for differentiating features. The purpose of this study is to acquire in vivo ARFI datasets in real-time, and to identify differentiable features between benign and malignant breast masses in the ARFI images. A modified Siemens SONOLINE Antares/spl trade/ scanner and a VF10-5 probe were programmed to implement ARFI imaging in a multi-focal zone configuration. Under an IRB approved protocol. patients scheduled for breast core biopsy were recruited for participation. Data was acquired in real-time and processed offline. Matched B-mode and ARFI images were evaluated concurrently. To date, 27 masses have been imaged under this experimental protocol. In addition, single focal zone ARFI data acquired from 52 masses with a Siemens SONOLINE Elegra/spl trade/ scanner and a 75L40 transducer were evaluated for consistency of the differentiating features. Of the 27 masses interrogated via multi-focal-zone ARFI, 9 were malignant, 9 were benign fibroadenomas, 4 were cysts, and the rest were other benign masses (i.e. lymph nodes, fat necrosis, etc.) Structures in matched B-mode images are in good agreement with those in ARFI displacement images, with both modalities demonstrating comparable resolution. In general ARFI displacement images of malignant breast masses exhibit increased contrast and improved margin definition over matched B-mode images. Cancers displace less (i.e. they are stiffer) than the surrounding tissue, and generally appear larger than in matched B-mode images. In addition, some malignant masses exhibit a slower recovery time, which has not been observed with benign masses. The cysts and fibroadenomas, in general, exhibit less contrast in ARFI images than in matched B-mode images. In many cases, fibroadenomas are not clearly distinguished from the surrounding tissues in ARFI displacement images, and can appear either stiffer or softer than the surrounding tissue. Acoustic streaming is observed in cyst fluid in response to ARFI excitation. ARFI displacement images portray different, complementary information than matched B-mode images. Some possible differentiating features between malignant and benign breast masses have been identified by this pilot study. Promising features include: differences in B-mode and ARFI lesion size. displacement magnitude, recovery time, and image contrast. These results encourage further study of breast mass characterization using ARFI imaging.

Introduction to neutron stimulated emission computed tomography.

Abstract: Neutron stimulated emission computed tomography (NSECT) is presented as a new technique for in vivo tomographic spectroscopic imaging. A full implementation of NSECT is intended to provide an elemental spectrum of the body or part of the body being interrogated at each voxel of a three-dimensional computed tomographic image. An external neutron beam illuminates the sample and some of these neutrons scatter inelastically, producing characteristic gamma emission from the scattering nuclei. These characteristic gamma rays are acquired by a gamma spectrometer and the emitting nucleus is identified by the emitted gamma energy. The neutron beam is scanned over the body in a geometry that allows for tomographic reconstruction. Tomographic images of each element in the spectrum can be reconstructed to represent the spatial distribution of elements within the sample. Here we offer proof of concept for the NSECT method, present the first single projection spectra acquired from multi-element phantoms, and discuss potential biomedical applications.

Neutron Stimulated Emission Computed Tomography for Diagnosis of Breast Cancer

Abstract: Neutron stimulated emission computed tomography (NSECT) is being developed as a non-invasive spectroscopic imaging technique to determine element concentrations in the human body. NSECT uses a beam of fast neutrons that scatter inelastically from atomic nuclei in tissue, causing them to emit characteristic gamma photons that are detected and identified using an energy-sensitive gamma detector. By measuring the energy and number of emitted gamma photons, the system can determine the elemental composition of the target tissue. Such determination is useful in detecting several disorders in the human body that are characterized by changes in element concentration, such as breast cancer. In this paper we describe our experimental implementation of a prototype NSECT system for the diagnosis of breast cancer and present experimental results from sensitivity studies using this prototype. Results are shown from three sets of samples: (a) excised breast tissue samples with unknown element concentrations, (b) a multi-element calibration sample used for sensitivity studies, and (c) a small-animal specimen, to demonstrate detection ability from in-vivo tissue. Preliminary results show that NSECT has the potential to detect elements in breast tissue. Several elements were identified common to both benign and malignant samples, which were confirmed through neutron activation analysis (NAA). Statistically significant differences were seen for peaks at energies corresponding to 37Cl, 56Fe, 58Ni, 59Co, 79Br and 87Rb. The spectrum from the small animal specimen showed the presence of 12C from tissue, from bone, and elements 39K, 27Al, 37Cl, 56Fe, 68Zn and 25Mg. Threshold sensitivity for the four elements analyzed was found to range from 0.3 grams to 1 gram, which is higher than the microgram sensitivity required for cancer detection. Patient dose levels from NSECT were found to be comparable to those of screening mammography.

Breast cancer detection using neutron stimulated emission computed tomography: prominent elements and dose requirements.

Abstract: Neutron stimulated emission computed tomography (NSECT) is being developed to noninvasively determine concentrations of trace elements in biological tissue. Studies have shown prominent differences in the trace element concentration of normal and malignant breast tissue. NSECT has the potential to detect these differences and diagnose malignancy with high accuracy with dose comparable to that of a single mammogram. In this study, NSECT imaging was simulated for normal and malignant human breast tissue samples to determine the significance of individual elements in determining malignancy. The normal and malignant models were designed with different elemental compositions, and each was scanned spectroscopically using a simulated 2.5 MeV neutron beam. The number of incident neutrons was varied from 0.5 million to 10 million neutrons. The resulting gamma spectra were evaluated through receiver operating characteristic (ROC) analysis to determine which trace elements were prominent enough to be considered markers for breast cancer detection. Four elemental isotopes ({sup 133}Cs, {sup 81}Br, {sup 79}Br, and {sup 87}Rb) at five energy levels were shown to be promising features for breast cancer detection with an area under the ROC curve (A{sub Z}) above 0.85. One of these elements - {sup 87}Rb at 1338 keV - achieved perfect classification atmore » 10 million incident neutrons and could be detected with as low as 3 million incident neutrons. Patient dose was calculated for each gamma spectrum obtained and was found to range from between 0.05 and 0.112 mSv depending on the number of neutrons. This simulation demonstrates that NSECT has the potential to noninvasively detect breast cancer through five prominent trace element energy levels, at dose levels comparable to other breast cancer screening techniques.« less

Quantifying hepatic shear modulus in vivo using acoustic radiation force.

Abstract: The speed at which shear waves propagate in tissue can be used to quantify the shear modulus of the tissue. As many groups have shown, shear waves can be generated within tissues using focused, impulsive, acoustic radiation force excitations, and the resulting displacement response can be ultrasonically tracked through time. The goals of the work herein are twofold: (i) to develop and validate an algorithm to quantify shear wave speed from radiation force-induced, ultrasonically-detected displacement data that is robust in the presence of poor displacement signal-to-noise ratio and (ii) to apply this algorithm to in vivo datasets acquired in human volunteers to demonstrate the clinical feasibility of using this method to quantify the shear modulus of liver tissue in longitudinal studies. The ultimate clinical application of this work is noninvasive quantification of liver stiffness in the setting of fibrosis and steatosis. In the proposed algorithm, time-to-peak displacement data in response to impulsive acoustic radiation force outside the region of excitation are used to characterize the shear wave speed of a material, which is used to reconstruct the material's shear modulus. The algorithm is developed and validated using finite element method simulations. By using this algorithm on simulated displacement fields, reconstructions for materials with shear moduli (mu) ranging from 1.3-5 kPa are accurate to within 0.3 kPa, whereas stiffer shear moduli ranging from 10-16 kPa are accurate to within 1.0 kPa. Ultrasonically tracking the displacement data, which introduces jitter in the displacement estimates, does not impede the use of this algorithm to reconstruct accurate shear moduli. By using in vivo data acquired intercostally in 20 volunteers with body mass indices ranging from normal to obese, liver shear moduli have been reconstructed between 0.9 and 3.0 kPa, with an average precision of +/-0.4 kPa. These reconstructed liver moduli are consistent with those reported in the literature (mu = 0.75-2.5 kPa) with a similar precision (+/-0.3 kPa). Repeated intercostal liver shear modulus reconstructions were performed on nine different days in two volunteers over a 105-day period, yielding an average shear modulus of 1.9 +/- 0.50 kPa (1.3-2.5 kPa) in the first volunteer and 1.8 +/- 0.4 kPa (1.1-3.0 kPa) in the second volunteer. The simulation and in vivo data to date demonstrate that this method is capable of generating accurate and repeatable liver stiffness measurements and appears promising as a clinical tool for quantifying liver stiffness.

Imaging the elastic properties of tissue: the 20 year perspective.

Abstract: After 20 years of innovation in techniques that specifically image the biomechanical properties of tissue, the evolution of elastographic imaging can be viewed from its infancy, through a proliferation of approaches to the problem to incorporation on research and then clinical imaging platforms. Ultimately this activity has culminated in clinical trials and improved care for patients. This remarkable progression represents a leading example of translational research that begins with fundamentals of science and engineering and progresses to needed improvements in diagnostic and monitoring capabilities applied to major categories of disease, surgery and interventional procedures. This review summarizes the fundamental principles, the timeline of developments in major categories of elastographic imaging, and concludes with recent results from clinical trials and forward-looking issues.

Medical ultrasound: imaging of soft tissue strain and elasticity

Abstract: After X-radiography, ultrasound is now the most common of all the medical imaging technologies. For millennia, manual palpation has been used to assist in diagnosis, but it is subjective and restricted to larger and more superficial structures. Following an introduction to the subject of elasticity, the elasticity of biological soft tissues is discussed and published data are presented. The basic physical principles of pulse-echo and Doppler ultrasonic techniques are explained. The history of ultrasonic imaging of soft tissue strain and elasticity is summarized, together with a brief critique of previously published reviews. The relevant techniques—low-frequency vibration, step, freehand and physiological displacement, and radiation force (displacement, impulse, shear wave and acoustic emission)—are described. Tissue-mimicking materials are indispensible for the assessment of these techniques and their characteristics are reported. Emerging clinical applications in breast disease, cardiology, dermatology, gastroenterology, gynaecology, minimally invasive surgery, musculoskeletal studies, radiotherapy, tissue engineering, urology and vascular disease are critically discussed. It is concluded that ultrasonic imaging of soft tissue strain and elasticity is now sufficiently well developed to have clinical utility. The potential for further research is examined and it is anticipated that the technology will become a powerful mainstream investigative tool.

An overview of elastography - an emerging branch of medical imaging.

Abstract: From times immemorial manual palpation served as a source of information on the state of soft tissues and allowed detection of various diseases accompanied by changes in tissue elasticity. During the last two decades, the ancient art of palpation gained new life due to numerous emerging elasticity imaging (EI) methods. Areas of applications of EI in medical diagnostics and treatment monitoring are steadily expanding. Elasticity imaging methods are emerging as commercial applications, a true testament to the progress and importance of the field.In this paper we present a brief history and theoretical basis of EI, describe various techniques of EI and, analyze their advantages and limitations, and overview main clinical applications. We present a classification of elasticity measurement and imaging techniques based on the methods used for generating a stress in the tissue (external mechanical force, internal ultrasound radiation force, or an internal endogenous force), and measurement of the tissue response. The measurement method can be performed using differing physical principles including magnetic resonance imaging (MRI), ultrasound imaging, X-ray imaging, optical and acoustic signals.Until recently, EI was largely a research method used by a few select institutions having the special equipment needed to perform the studies. Since 2005 however, increasing numbers of mainstream manufacturers have added EI to their ultrasound systems so that today the majority of manufacturers offer some sort of Elastography or tissue stiffness imaging on their clinical systems. Now it is safe to say that some sort of elasticity imaging may be performed on virtually all types of focal and diffuse disease. Most of the new applications are still in the early stages of research, but a few are becoming common applications in clinical practice.