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Research Article
Originally Published 15 March 1996
Free Access

Optical Coherence Tomography for Optical Biopsy : Properties and Demonstration of Vascular Pathology

Abstract

Background Optical coherence tomography (OCT) is a recently developed medical diagnostic technology that uses back-reflected infrared light to perform in situ micron scale tomographic imaging. In this work, we investigate the ability of OCT to perform micron scale tomographic imaging of the internal microstructure of in vitro atherosclerotic plaques.
Methods and Results Aorta and relevant nonvascular tissue were obtained at autopsy. Two-dimensional cross-sectional imaging of the exposed surface of the arterial segments was performed in vitro with OCT. A 1300-nm wavelength, superluminescent diode light source was used that allows an axial spatial resolution of 20 μm. The signal-to-noise ratio was 109 dB. Images were displayed in gray scale or false color. Imaging was performed over 1.5 mm into heavily calcified tissue, and a high contrast was noted between lipid- and water-based constituents, making OCT attractive for intracoronary imaging. The 20-μm axial resolution of OCT allowed small structural details such as the width of intimal caps and the presence of fissures to be determined. The extent of lipid collections, which had a low backscattering intensity, also were well documented.
Conclusions OCT represents a promising new technology for imaging vascular microstructure with a level of resolution not previously achieved with the use of other imaging modalities. It does not require direct contact with the vessel wall and can be performed with a catheter integrated with a relatively inexpensive optical fiber. The high contrast among tissue constituents, high resolution, and ability to penetrate heavily calcified tissue make OCT an attractive new imaging technology for intracoronary diagnostics.
Contributions from several groups have now shown that most myocardial infarctions result from the rupture of a mild to moderately sized cholesterol-laden plaque in a coronary artery followed by a cascading sequence of biochemical reactions resulting in thrombosis and vessel occlusion.1 2 3 4 The plaques at highest risk for rupture are those with a large core of lipid roofed by a structurally weak fibrous cap.2 5
These lesions are difficult to detect by conventional radiological techniques, and even when they are seen, their infrastructure cannot be analyzed, so that lipid content and wall structure are not determined.6 7 8 9 10 11 To date, no modality other than postmortem histology has provided the level of resolution and contrast necessary to diagnose lesions likely to undergo rupture.12 Predicting future coronary events is particularly important in view of the high percentage of occlusions resulting in sudden death.13 In this study, we investigated the application of a new imaging modality, optical coherence tomography (OCT) for diagnostic imaging of vascular pathology with the long-term objective of improved risk stratification and the micron scale guidance of interventional procedures such as percutaneous transluminal coronary angioplasty and directional coronary atherectomy.
OCT performs in situ, microscopic, cross-sectional tomographic imaging in tissues.14 OCT is analogous to ultrasound B-mode imaging except that is uses light rather than sound. OCT performs imaging in biological tissues by directing an optical beam of infrared light onto the tissue and measuring the reflected or backscattered intensity of light from microstructures within tissue as a function of depth. Thus, an OCT image represents a cross-sectional, micron scale picture of the optical reflectance properties of the tissue.
OCT technology is based on fiber optics, which are used in optical communications technology. Thus, OCT technology is robust, portable, low cost, and can be readily interfaced with optical fiber techniques to catheters and endoscopes. OCT has been investigated and reduced to clinical practice in ophthalmology. Preliminary clinical studies demonstrate that OCT can noninvasively image structures of the anterior eye and retina with unprecedented resolution.14 15 16 17 OCT has been especially promising for the diagnosis and monitoring of macular diseases.18 Since quantitative information also can be obtained from OCT images, it also may provide the first objective clinical assessment of diseases such as glaucoma.19
This article presents investigations that suggest the feasibility of using OCT for intravascular imaging and diagnosis of lesions likely to undergo plaque rupture. In contrast to applications in ophthalmology, where the tissue structures are transparent, the application of OCT for intravascular imaging involves imaging of tissues that are nontransparent. Although vascular and other tissues strongly absorb visible wavelengths of light, most tissues are relatively nonabsorbing at infrared wavelengths. Thus, imaging depth is limited by light scattering rather than absorption. By performing OCT imaging at longer infrared wavelengths (1300 versus 800 nm conventionally used in ophthalmic OCT), the imaging depth in vascular tissues can be increased to permit full thickness imaging of the vessel. The axial resolution of images achieved using OCT here is less than 20 μm, up to 10 times higher than conventional ultrasound, magnetic resonance imaging (MRI), or computed tomography. We present systematic studies in vitro that establish the ability of OCT to produce image contrast between adipose and muscle tissue, penetrate highly calcified tissues, as well as image several types of vascular pathologies that correlate with histopathology. These results provide baseline information for interpreting OCT images and suggest that OCT can be a powerful diagnostic tool for imaging of intravascular pathology.

Methods

OCT measures cross-sectional tomographic images in tissue and is similar to ultrasound B-mode imaging except that it uses light rather than sound. OCT also differs from ultrasound in that the detection in OCT is based on interferometry.19 20 21 22 23 In ultrasound, the time the ultrasound pulse takes to travel to a surface and be reflected back can be measured by an electronic clock. However, this is not possible with optical techniques because of the high speeds associated with the propagation of light. This limitation is overcome with the use of a reference light path and interferometry.
A detailed presentation of the principles of operation of OCT and factors that govern its performance have been published elsewhere.14 15 In addition to modifications in optics and electronics, the source has been changed to image in nontransparent tissue, which is described below. The OCT system uses fiber optics and a compact diode light source similar to those used in compact disc players. A schematic of the system is shown in Fig 1. Precision distance measurements are performed by Michelson-type interferometry. Light from the source is split evenly by an optical fiber splitter, which functions as an interferometer. One of the fibers directs light to the tissue and the other to a moving reference mirror. The distal end of the optical fiber can be interfaced to a catheter. The position of the reference mirror is precisely controlled by the system electronics. The light signal reflected from the tissue is recombined with the signal reflected from the mirror. Interference between the light reflected from the tissue and the light reflected from the reference mirror occurs only when the two path lengths are matched to within the coherence length of the light source. This allows precise (micron scale) determination of the distance within the sample from which the light was reflected.
OCT therefore measures the intensity of backscattering (reflection) light from within the tissue plotted as a function of depth. A cross-sectional image is produced in a manner similar to radar by recording axial reflectance profiles while the transverse position of the optical beam on the tissue specimen is scanned. The image is displayed either in gray scale or false color in order to differentiate tissue microstructure.
A 1300-nm wavelength, superluminescent diode source with a 50-nm bandwidth (wavelength distribution) was used for all studies presented here except where indicated. System parameters including the optical beam confocal parameter (focusing properties), signal-to-noise ratio, incident power at the sample, and reference arm power were carefully controlled to maintain consistency. Intralipid (Kabi Pharmacia Inc) and barium sulfate, which have well-established optical properties, were used as controls to confirm that system performance was reproducible throughout the imaging runs.24 The relationship between optical bandwidth (Δλ) and ranging resolution (ΔL) is well established by previous results and from electrodynamic theory and is given mathematically by the formula17
\[{\Delta}L{=}\frac{2\ ln\ 2}{{\pi}}\ \frac{{\lambda}^{2}}{{\Delta}{\lambda}}\]
The 50-nm bandwidth (wavelength spectrum of incident light) for the low-coherence light source used in these measurements yielded an axial spatial resolution of less than 20 μm as experimentally confirmed by measuring the point spread function with a mirror.20 25 26 27 The confocal parameter (depth of focus) for the optical beam was 520 μm. The lateral resolution was 30 μm and determined by the optical spot size.
The measured signal-to-noise ratio was 109 dB, using a power of 160 μW at the sample. The signal-to-noise ratio was measured by measuring the maximum signal when the optical beam was reflected from a high reflecting mirror divided by the background noise level of the instrument.27 This signal-to-noise ratio determines the dynamic range with which it is possible to image.
In general, the signal-to-noise ratio for this type of optical measurement can be predicted by using results from optical communications theory.25 27 The signal-to-noise ratio (SNR) determines the minimum detectable reflectivity in the tissue and can be mathematically described by
\[SNR{=}\frac{1}{2}\ \frac{{\eta}}{\mathit{{\hslash}}{\omega}}\ \frac{\mathit{P}_{s}}{NEB}\]
where η is the detector quantum efficiency, ℏω is the photon energy, NEB is the noise-equivalent bandwidth of the demodulation filter, and Ps is the power received by the detector from the sample arm. The sensitivity to weakly reflected light depends only on the detection filter bandwidth and the available optical power.
Cross-sectional images of backscattering intensity versus longitudinal depth and transverse position were displayed as gray scale or false color images. The image size was 250 (transverse) by 500 pixels (longitudinal) unless stated. The image acquisition times ranged from 3 to 45 seconds.
Aorta was obtained within 5 hours of the initiation of the autopsy. The specimens were placed in normal saline with 0.05% sodium azide and stored at 0°C. The tissue was cut into segments smaller than 5×5 cm with the luminal surface exposed. Over 50 plaques of different morphologies from 9 consecutive patients were sampled.
Imaging was performed at room temperature through air. Similar procedures were used with nonvascular tissue (myocardium, peritoneal adipose, epiglottis, and clavicle). The position of the beam on the sample was monitored with a monocular infrared scope or visible light-guiding beam. The peripheral areas of imaged arterial sections were marked with microinjections of dye. After imaging, the sample underwent routine histological processing, being fixed in 10% buffered formalin for 24 hours and subsequently decalcified in a standard Cal Ex solution (Fisher Inc) for 5 hours. The arteries were processed for routine paraffin embedding. Five-micron-thick sections of the arteries were cut at marked imaging sites. Staining was performed with hematoxylin and eosin to identify different components of the vascular wall. Stained histological sections were compared with the OCT images, allowing a better qualitative understanding of tissue properties that alter backscattering (reflection) intensity and produce contrast. The maintenance of spatial relationships among tissue microstructures was confirmed by comparison with histology. Histology from nonvascular tissue is included only to confirm tissue identification. During imaging, the tissue samples were wet with 5 mL of normal saline to prevent drying.

Results

OCT achieves high image contrast and differentiation between lipid- and water-based tissue, a limitation of conventional imaging technologies. Fig 2A shows an in vitro OCT image of cardiac muscle abutting adipose tissue. Because the optical backscattered reflectance of fat cells is significantly lower than muscle, the image dramatically differentiates these two tissues. Fig 2B demonstrates the corresponding adipose histology. Fig 2C shows a quantitative plot of the backscattered reflectance as a function of depth for both tissue morphologies. The high reflection peaks observed in the measurement of adipose tissue may be attributed to supportive tissue structures, while lipid structures have very low reflectivity compared with muscle. Thus, in contrast to ultrasound imaging, lipid- and water-based tissues have distinct optical reflectance properties that enable OCT imaging to sharply delineate the microstructure within lipid-laden atherosclerotic arteries.28 29
Fig 3 demonstrates the dependence of imaging penetration depth on the wavelength of light used. A human epiglottis was imaged in vitro with the use of low-coherence light sources at wavelengths of 850 and 1300 nm with equal incident intensities (100 μW). The image obtained at 850 nm only shows structures predominately near the tissue surface. In contrast, the image at 1300 nm permits identification of underlying cartilage because light at this wavelength suffers less scattering and absorption, thus penetrating deeper into the tissue. In general, both imaging depth as well as tissue contrast are determined by tissue absorption and scattering properties, which vary with wavelength.30 Thus, use of different wavelengths provides an approach for optimizing imaging depth as well as contrast and differentiation between different tissue morphologies. The change to 1300-nm diodes is an important modification from the ophthalmolgic studies, which allows imaging in nontransparent tissue.
A major limitation of ultrasound for intravascular imaging is that it cannot penetrate heavily calcified tissue.31 Fig 4 shows an OCT image with the corresponding histology of an in vitro human clavicle, demonstrating imaging at depths of over 1.5 mm into the cortical bone. Unlike sound waves, infrared light is less strongly reflected from calcified tissues and thus OCT imaging is possible even within these structures. A different false color map was used that gives better detail of deeper structures. Similar results were achieved in calcified aortic lesions.

OCT Imaging of Aortic Atherosclerotic Plaques

Figs 5 through 10 demonstrate imaging of atherosclerotic lesions in human abdominal aorta specimens. An intramural collection of lipid can be seen in Fig 5, where the arrows identify corresponding areas in the histology and OCT image. In Fig 6, a smaller collection of lipid and matrix is present deep within the intimal wall. Fig 7 demonstrates a small intimal layer covering a large atherosclerotic plaque that is heavily calcified and has a relatively low lipid content. The ability to identify fine structural detail such as the width of intimal caps in vivo probably will lead to significant improvements in patient risk stratification. Backscattering within the plaque is higher than the heavily lipid-laden plaques in Figs 5 and 10. Fig 8 illustrates a fissure within the vessel wall extending into a heavily calcified plaque. Plaques in Fig 9 were obtained from a patient who died as a result of a ruptured aortic aneurysm. The plaque in Fig 9A has a thin intimal layer overlaying a large lipid collection. The thin wall relative to lipid content increases the likelihood of rupture. In Fig 9B, the thin plaque has a well-delineated central penetration of lipid into deeper portions of the artery that turns and tracks near the media-intima interface. Figs 8 and 9B demonstrate the ability of OCT to image structural details within plaques such as fissuring. Fissures that extend from the surface into the media often result in intramural thrombus formation and a rapid increase in plaque size, occasionally resulting in complete occlusion.4 These lesions can only be accurately diagnosed by postmortem histology; therefore, selective therapy cannot be deployed effectively against them. A deep lipid-laden plaque is present in Fig 10, with its histological correlate. The back wall of the plaque is not seen because the elastic layer also has a low backscattering intensity and results in little contrast when abutting lipid-laden areas.

Discussion

Rupture of lipid-filled atherosclerotic plaques in coronary arteries is now believed to be the most common mechanism initiating acute myocardial infarction.2 3 4 However, current imaging techniques only have a limited ability to identify these lesions. Furthermore, these technologies do not have sufficient resolution to precisely guide the microsurgical removal of plaque by interventional catheter-based procedures. For these reasons, other methods of imaging have been aggressively pursued recently to overcome these limitations, including MRI, angioscopy, and intravascular ultrasound (IVUS). MRI (and closely related magnetic resonance angiography) is a promising technology to screen for the presence of coronary artery disease.32 Its advantages are that it is noninvasive, it can give information on flow in addition to anatomic obstruction, and it has a limited ability to provide spectroscopic information on tissue composition. Its limitations are the low resolution (greater than 100 μm even in animal studies), the very poor visualization of the circumflex and only proximal images of the other major arteries, the expensive instrumentation, and the fact that mechanical interventions cannot be deployed simultaneously.33 Furthermore, though it may eventually be able to screen for areas suspicious for unstable plaques, it is unlikely that its low resolution will be able to identify these small areas definitively. Angioscopy is the direct visualization of the surface of the blood vessel with a fiber optic bundle. It has the advantage over other imaging methods in diagnosing surface fissuring and the presence of thrombus.11 34 35 Its disadvantages are that it depends on a clear field of vision, it cannot accurately measure luminal dimensions for guiding interventions, and it cannot image through the vessel wall.36 High-frequency ultrasound (20 to 30 MHz) is superior to angiography in its ability to diagnose dissections, assess the adequacy of coronary interventions, guide stent deployment, and determine the extent of arterial stenosis, most notably at ostial sites.37 38 However, the maximum attainable resolution of 100 μm, which decreases linearly with distance, limits its ability to delineate structure.39 Furthermore, it is limited in its ability to assess lipid content (lower limit, 250 μm) and has a poor interobserver agreement as to whether lipid is present in vivo (in some instances not significantly different from chance).28 29 Also, clot is very poorly differentiated from plaque.40
The intravascular use of OCT has the potential of overcoming these limitations. This study demonstrates the ability of OCT to delineate in vitro plaque morphology. The structural details such as the thickness of intimal caps, extent of lipid collections, and presence of fissures were assessed at a level of resolution (20 μm) not achievable by other imaging modalities. Further refinements in instrumentation, including the use of different light sources based on broader bandwidth diodes or femtosecond pulse lasers could increase this resolution to 4 μm or less.41 42 In addition to high resolution, the high dynamic range of OCT (109 dB) provides high contrast between tissue constituents, and the ability to penetrate heavily calcified tissue makes OCT well suited for intravascular diagnostics. The use of light rather than acoustic waves has the additional advantage that since absorption of light, unlike sound, is strongly dependent on molecular composition, OCT has the potential for performing in vivo biochemical analysis based on spectroscopic properties.
Imaging in this study was performed in air but can be performed in saline, which is transparent to both visible and infrared light without appreciable loss of image quality. Preliminary results suggest that it will also be possible to image through varying depths of blood. Although blood strongly absorbs visible light, it has very low absorption in infrared wavelengths (1300 nm). However, optical scattering effects can reduce the amount of optical signal that is reflected. This in turn will limit the penetration depth of the imaging. In addition, it should be noted that there are other ways to improve performance in this scenario. The effect that blood has on imaging is a clinically important question that requires further investigation. If the presence of blood produces excessive degradation of imaging, simultaneous injection of saline may be required for intravascular use.
Future investigations will focus on adaptating OCT for in vivo imaging, including the development of an intravascular imaging catheter, optimization of incident light source wavelength, and reduction of image aquisition times. Since OCT is based on fiber optic technology, it can readily be engineered and adapted to perform imaging through a disposable, fiber optic–based delivery catheter. The diameter of a standard optical fiber is 125 μm (smaller fibers also can be used); thus it is small enough to be integratable with a catheter. The catheter can be implemented in a manner similar to transluminal ultrasound. In this case there must be a reflecting and focusing element on the distal end of the catheter. These can be miniaturized with the use of micro-optical fabrication techniques. The ultimate catheter technology should resemble transluminal ultrasound catheters in size. The remainder of the system is compact and portable.
Since imaging depth and contrast are functions of optical wavelength, the choice of optimal imaging wavelengths should further improve imaging performance. Finally, although the current acquisition times of 3 to 45 seconds used in this study are inadequate for in vivo imaging, imaging speed may be reduced significantly. Instrument developments including increasing source power, scanning speed, and redesign of electronics are straightforward and should result in a one to two orders of magnitude reduction in image acquisition time.

Conclusions

OCT achieves high resolution, can image through highly calcified tissue, has high dynamic range, and can be adapted for catheter-based imaging. OCT is a promising new technology for intravascular imaging and the diagnosis of high-risk coronary lesions.
Figure 1. Schematic of the optical coherence tomography (OCT) system. OCT is based on low-coherence interferometry. Light is generated from either an infrared low-coherence diode (similar to compact disc players) or a femtosecond laser source. The beam is split evenly, half to the sample and half to a reference mirror. The reflected light intensity from structures within the tissue is measured by recombining its signal with that returning from the moving reference mirror (whose distance is accurately known). Interference occurs only when the two paths are matched within the coherence length of the source, allowing micron scale ranging.
Figure 2. Contrast between lipid- and water-based tissue. A, Optical coherence tomography (OCT) can be clinically useful for identifying high-risk atherosclerotic plaques because it achieves high-image contrast and differentiation between lipid- and water-based tissue, a limitation of conventional imaging technologies. An in vitro OCT image of cardiac muscle (m) abutting adipose tissue (a) is shown. Because the optical backscattered reflectance of fat cells is significantly lower than muscle, the image dramatically differentiates these two tissues. Thus, lipid- and water-based tissues have distinct optical relfectance properties that enable OCT imaging to sharply delineate the microstructure within lipid-laden atherosclerotic arteries. Bar represents 500 μm. B, Histology for the adipose has been included to confirm tissue identification. C, Quantitative plot of the backscattered reflectance as a function of depth for both tissue morphologies. The high reflection peaks observed in the measurement of adipose tissue may be attributed to supportive tissue structures, while lipid structures have very low reflectivity compared with muscle. Thus, in contrast to ultrasound imaging, lipid- and water-based tissues have distinct optical reflectance properties that enable OCT imaging to sharply delineate the microstructure within lipid-laden atherosclerotic arteries.
Figure 3. Dependence of imaging depth on wavelength of the incident light. A human epiglottis was imaged at both 850 and 1300 nm. The underlying cartilage (c) could be visualized only using longer wavelengths, while a larger reflection at the surface occurred with the 850 nm light. Superficial secretory glands (g) were visualized at both wavelengths. Bars represent 500 μm. In this image, data are displayed as the logarithm of backscattering intensity versus depth (in gray scale) to emphasize deeper structures. Corresponding histology is included.
Figure 4. A major limitation of ultrasound for intravascular imaging is that it cannot penetrate heavily calcified tissue. This shows an optical coherence tomography (OCT) image of an in vitro human clavicle, demonstrating imaging at depths of over 1.5 mm into the cortical bone. Unlike sound waves, light is less strongly reflected from calcified tissues, and thus OCT imaging is possible even within these structures. Similar results were achieved in calcified aortic lesions. The periosteum is well demarcated at the surface. Bar represents 500 μm. Corresponding histology is included.
Figure 5. Optical coherence tomography (OCT) image and histological section from a heavily calcified human aorta. Upper surface of the tissue represents the lumen of the aorta. An intramural collection of lipid is present to the right of the image, with a relatively low backscattering intensity. Arrows within the lipid collection represent corresponding areas in the histology and OCT image. Bar represents 500 μm.
Figure 6. Optical coherence tomography (OCT) image with corresponding histology of an atherosclerotic human aorta. A small, intramural collection of lipid and matrix is present deep within the thickened intimal wall. Bar represents 500 μm. Image is 250×250 pixels.
Figure 7. Optical coherence tomography (OCT) image demonstrating a small intimal layer (arrow) covering a large atherosclerotic plaque (left). The plaque is heavily calcified with a relatively low lipid content. OCT allows high-resolution delineation of microstructural details, such as wall thickness, which are important features of unstable plaques. Bar represents 500 μm.
Figure 8. Optical coherence tomography (OCT) image demonstrating a fissure (arrow) extending from the luminal surface into an underlying plaque. The image demonstrates the ability of OCT to access structural damage within the vessel wall. Plaque (P) is present right and below the fissure. Bar represents 500 μm.
Figure 9. Images of various plaques with fine internal microstructural features. A, Optical coherence tomography (OCT) image of an in vitro thin-walled atherosclerotic plaque with an increased likelihood of rupture. The small plaque has a lipid-filled core (dark area within walls) separated from the lumen by a small intimal cap (arrow). The ability to determine internal plaque structure on a micron scale makes OCT well suited for intravascular imaging. B, Small plaque with a complicated internal structure. The low backscattering areas (dark) within the wall correspond to lipid that extends both in longitudinal and axial directions. Arrows identify a small penetration into deeper intima followed by tracking at the intima-media border. Structural changes within plaques are believed to play an important role in atherosclerosis and the progression of myocardial infarction. The color table has been changed in this image to delineate deeper structures more effectively. Bars represent 500 μm.
Figure 10. A relatively deep lipid-laden aortic atherosclerotic plaque that penetrates to the media. Arrow identifies corresponding areas between the optical coherence tomography image and histology. The elastic layer has a low backscattering intensity, so the interface between it and the plaque is not well defined. Bar represents 500 μm.

Acknowledgments

This work was supported in part by the National Institutes of Health (grants NIH-9-RO1-EY11289-10 and NIH-9-RO1-GM35459-09) and the Office of Naval Research, Medical Free Electron Laser Program (grant N00014-94-1-0717). The authors wish to thank Arthur E. Weyman, MD, Geoffrey Rose, MD, Stephen A. Boppart, and Neal Weissman, MD, for their comments. The technical support of Cathryn Blackwell and Joseph Gamba is also appreciated. Thanks to Cindy Kopf for her aid in the preparation of the manuscript.

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Circulation
Pages: 1206 - 1213
PubMed: 8653843

History

Received: 28 June 1995
Revision received: 19 October 1995
Accepted: 23 October 1995
Published online: 15 March 1996
Published in print: 15 March 1996

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Keywords

  1. atherosclerosis
  2. lasers
  3. imaging

Authors

Affiliations

Mark E. Brezinski
MD, PhD
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
Guillermo J. Tearney
BA, SM
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
Brett E. Bouma
PhD
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
Joseph A. Izatt
PhD
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
Michael R. Hee
BA, SM
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
Eric A. Swanson
SM
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
James F. Southern
MD, PhD
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.
James G. Fujimoto
PhD
From the Cardiac Unit (M.E.B.) and the Pathology Department (J.F.S.), Massachusetts General Hospital and Harvard Medical School, Boston; the Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics (G.J.T., B.E.B., J.A.I., M.R.H., J.G.F.), Massachusetts Institute of Technology, Cambridge; and Lincoln Laboratory (E.A.S.), Massachusetts Institute of Technology, Lexington.

Notes

Correspondence to James G. Fujimoto, PhD, Office 36-361, Massachusetts Institute of Technology, Cambridge, MA 02139.

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