Peripheral Arterial Disease (PAD) is caused by a reduction of the internal diameters of the arteries in the upper or lower extremities mainly due to atherosclerosis. If not treated, its worsening may led to a complete occlusion, causing the death of the cells lacking proper blood supply, followed by gangrene that may require chirurgical amputation. We have recently performed a clinical study in which good sensitivities and specificities were achieved with dynamic diffuse optical tomography. To gain a better understanding of the physiological foundations of many of the observed effects, we started to develop a mathematical model for PAD. The model presented in this work is based on a multi-compartment Windkessel model, where the vasculature in the leg and foot is represented by resistors and capacitors, the blood pressure with a voltage drop, and the blood flow with a current. Unlike existing models, the dynamics induced by a thigh-pressure-cuff inflation and deflation during the measurements are taken into consideration. This is achieved by dynamically varying the resistances of the large veins and arteries. By including the effects of the thigh-pressure cuff, we were able to explain many of the effects observed during our dynamic DOT measurements, including the hemodynamics of oxy- and deoxy-hemoglobin concentration changes. The model was implemented in MATLAB and the simulations were normalized and compared with the blood perfusion obtained from healthy, PAD and diabetic patients. Our preliminary results show that in unhealthy patients the total system resistance is sensibly higher than in healthy patients.
Dynamic optical tomographic imaging has shown promise in diagnosing and monitoring peripheral arterial disease
(PAD), which affects 8 to 12 million in the United States. PAD is the narrowing of the arteries that supply blood to the
lower extremities. Prolonged reduced blood flow to the foot leads to ulcers and gangrene, which makes placement of
optical fibers for contact-based optical tomography systems difficult and cumbersome. Since many diabetic PAD
patients have foot wounds, a non-contact interface is highly desirable. We present a novel non-contact dynamic
continuous-wave optical tomographic imaging system that images the vasculature in the foot for evaluating PAD. The
system images at up to 1Hz by delivering 2 wavelengths of light to the top of the foot at up to 20 source positions
through collimated source fibers. Transmitted light is collected with an electron multiplying charge couple device
(EMCCD) camera. We demonstrate that the system can resolve absorbers at various locations in a phantom study and
show the system’s first clinical 3D images of total hemoglobin changes in the foot during venous occlusion at the thigh.
Our initial results indicate that this system is effective in capturing the vascular dynamics within the foot and can be used
to diagnose and monitor treatment of PAD in diabetic patients.
We present a dynamic contact-free continuous-wave diffuse optical tomography system for the detection and monitoring of peripheral arterial disease (PAD) in the foot. Peripheral Arterial Disease (PAD) is the narrowing of the functional area of the artery generally due to atherosclerosis. It affects between 8-12 million people in the United States and if untreated this can lead to ulceration, gangrene and ultimately amputation. Contact-Free imaging is highly desirable, due to the presence of ulcerations and gangrene in many patients affected by PAD. The system uses an electron multiplying charge coupled device (EMCCD) camera for detection to achieve a dynamic range of 86 dB with a frame rate of 1 Hz using 20 collimated source fibers and 2 wavelengths. We present first clinical results showing 3D images of total hemoglobin changes in response to a dynamic thigh cuff.
Peripheral Arterial Disease (PAD) is the narrowing of the functional area of the artery generally due to atherosclerosis. It affects between 8-12 million people in the United States and if untreated this can lead to ulceration, gangrene and ultimately amputation. The current diagnostic method for PAD is the ankle-brachial index (ABI). The ABI is a ratio of the patient’s systolic blood pressure in the foot to that of the brachial artery in the arm, a ratio below 0.9 is indicative of affected vasculature. However, this method is ineffective in patients with calcified arteries (diabetic and end-stage renal failure patients), which falsely elevates the ABI recording resulting in a false negative reading. In this paper we present our results in a pilot study to deduce optical tomography’s ability to detect poor blood perfusion in the foot. We performed an IRB approved 30 patient study, where we imaged the feet of the enrolled patients during a five stage dynamic imaging sequence. The patients were split up into three groups: 10 healthy subjects, 10 PAD patients and 10 PAD patients with diabetes and they were imaged while applying a pressure cuff to their thigh. Differences in the magnitude of blood pooling in the foot and rate at which the blood pools in the foot are all indicative of arterial disease.
We introduce here a temporally constrained image reconstruction algorithm for fast dynamic imaging of the
spatial distribution of tissue parameters such as oxy-hemoglobin, HbO2, or deoxy-hemoglobin, Hb, and their
derived parameters, e.g., HbT or StO2. An unknown spatial-temporal distribution of the tissue parameter is
represented by a combination of basis functions where bases are predefined and their coefficients are
unknown. The performance of the new algorithm is evaluated using experimental studies with dynamic
imaging of vascular disease in foot. The results show that the temporally constrained algorithm leads to 26-
fold acceleration in the image reconstruction as compared to more traditional methods that have to
reconstruct all time frames data sequentially.
KEYWORDS: Digital signal processing, Breast, Imaging systems, Sensors, Tumors, Breast imaging, Signal detection, Optical tomography, Dynamical systems, Tissues
Diffuse optical tomography has shown promising results as a tool for breast cancer screening and monitoring response to chemotherapy. Dynamic imaging of the transient response of the breast to an external stimulus, such as pressure or a respiratory maneuver, can provide additional information that can be used to detect tumors. We present a new digital continuous-wave optical tomography system designed to simultaneously image both breasts at fast frame rates and with a large number of sources and detectors. The system uses a master-slave digital signal processor-based detection architecture to achieve a dynamic range of 160 dB and a frame rate of 1.7 Hz with 32 sources, 64 detectors, and 4 wavelengths per breast. Included is a preliminary study of one healthy patient and two breast cancer patients showing the ability to identify an invasive carcinoma based on the hemodynamic response to a breath hold.
KEYWORDS: Breast, Digital signal processing, Imaging systems, Tumors, Breast cancer, Optical imaging, Mammography, Breast imaging, Signal processing, Sensors
Continuous wave optical tomography is non-ionizing, uses endogenous contrast, and can be performed quickly and at
low cost which makes it a suitable imaging modality for breast cancer screening. Using multiple wavelengths of light to
illuminate the breast at various angles, three-dimensional images of the distribution of chromophores such as oxy- and
deoxy-hemoglobin can help identify cancerous tissue. Dynamic optical imaging can provide additional insight into
cancer characteristics such as angiogenesis and metabolism. Here we present the first clinical data acquired with our
novel digital breast imaging system. This system is based upon a Digital Signal Processor (DSP) architecture that
leverages the immediate digitization of acquired analog data to reduce noise and quickly process large amounts of data.
Employing this new instrument we have investigated the dynamic changes due to a breath hold and its potential for use
in breast cancer screening. Over the course of a breath hold, images have been collected simultaneously from both
breasts at a rate of 1.7 frames per second with 32 sources and 64 detectors per breast and four wavelengths of light at
765, 805, 827, and 905nm. Initial results involving one healthy volunteer and one breast cancer patient support the
potential use of dynamic imaging for breast cancer detection.
Peripheral Artery Disease (PAD) affects over 10 million Americans and is associated with significant morbidity and
mortality. While in many cases the ankle-brachial index (ABI) can be used for diagnosing the disease, this parameter is
not dependable in the diabetic and elderly population. These populations tend to have calcified arteries, which leads to
elevated ABI values. Dynamic optical tomography (DDOT) promises to overcome the limitations of the current
diagnostic techniques and has the potential to initiate a paradigm shift in the diagnosis of vascular disease. We have
performed initial pilot studies involving 5 PAD patients and 3 healthy volunteers. The time traces and tomographic
reconstruction obtained from measurements on the feet show significant differences between healthy and affected
vasculatures. In addition, we found that DOT is capable of identifying PAD in diabetic patients, who are misdiagnosed
by the traditional ABI screening.
KEYWORDS: Digital signal processing, Imaging systems, Breast, Signal processing, Optical fibers, Signal detection, Breast cancer, Breast imaging, Sensors, Tissue optics
Breast cancer characteristics such as angiogenesis and hypoxia can be quantified by using optical
tomography imaging to observe the hemodynamic response to an external stimulus. A digital near-infrared
tomography system has been developed specifically for the purpose of dynamic breast imaging. It
simultaneously acquires four frequency encoded wavelengths of light at 765, 808, 827, and 905nm in order
to facilitate the functional imaging of oxy- and deoxy-hemoglobin, lipid concentration and water content.
The system uses 32 source fibers to simultaneously illuminate both breasts. There are 128 detector fibers,
64 fibers for each breast, which deliver the detected light to silicon photo-detectors. The signal is
conditioned by variable gain amplifiers and filters and is quantized by an analog to digital converter
(ADC). The sampled signal is then passed on for processing using a Digital Signal Processor (DSP) prior
to display on a host computer. The system can acquire 2.23 frames per second with a dynamic range of
236 dB.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.