<title>Clinical applications of dynamic optical tomography in vascular disease</title>

Abstract

Vascular disease is a significant source of mortality and morbidity for many patient populations. While substantial strides in surgical therapeutics have been made in the past decade, our limited understanding of the microvascular processes, which are invisible to conventional imaging modalities and beyond the scope of our current physiologic paradigms, has slowed the advancement of medical therapeutic interventions. In this report we present data in support of an emerging body of work demonstrating that the method of dynamic optical tomography can yield critical insights into the underpinnings of microvascular pathophysiology in large tissue structures. In a series of experiments designed to characterize specific properties of the peripheral vasculature, we provide first-time descriptions of spatially mapped time-varying vascular responses. Specifically, properties delineated are (1) that inherent vascular rhythms can act as natural "contrast agents" that allow spatial discrimination of tissue components in cross-section, (2) that complex vascular responses can be decomposed into multiple spatially coincident time-evolving processes, and (3) that occult long-term "evolutionary-type" microvascular processes (e.g. , chronic tobacco use) can be revealed. Taken together, these capabilities contribute to a global understanding of the peripheral vascular response, affording new opportunities for improved diagnostic and therapeutic strategies.

<title>Imaging of spatio-temporal coincident states by dynamic optical tomography</title>

“…The current capabilities add to those enumerated in a series of accompanying reports wherein we describe instrumentation 1 and numerical methods 16 that we have adopted for the collection and analysis of time-series image data. These methods represent various components of a more inclusive methodology we seek to apply for the characterization of the spatiotemporal properties of vascular reactivity in large tissues using near infrared optical imaging methods.…”

Optomechanical imaging system for breast cancer detection

“…In recent years, our group has emphasized the added value of recording dynamic elements of tissue optical contrast that may naturally occur (e.g., natural beat frequencies associated with the vascular tree) or can be introduced through controlled manipulations [18][19][20]. By enabling highdensity dynamic optical measures of the breast combined with concurrent viscoelastic measures explored through precise articulation, our goal here has been to capture the key elements of both strategies as a means for improved detection of breast cancer.…”

“…The other approach is to define dynamic responses of the tissue based on measures of relative changes in the optical signal [16,17]. While not easily supporting absolute constituent measures, this approach has the added benefit of exploring any of a host of dynamic features associated with Hb signals that may occur spontaneously (e.g., vascular rhythms) [18] or can be induced by controlled provocations [19,20]. In a previous report, we described a system that can dynamically image both breasts simultaneously and provided evidence of enhanced tumor detection from a simple respiratory maneuver [21].…”

Time-frequency analysis of functional optical mammographic images

“…An important point, stressed in our first dynamic-imaging report [1] and has elaborated upon in subsequent papers and presentations [5][6][7], is that the most effective means of extracting clinically valuable information available from NIR optical tomography is through application of mathematical time-series analysis methods to sequences of detector data and/or reconstructed images rather than by direct inspection of individual optical coefficient or hemoglobin concentration images. This point is born out by the case results to follow, wherein a different analytic strategy we are studying was used to analyze the data collected from each subject.…”