Ultrasound-modulated optical tomography (UOT), also known as Acousto-Optic Tomography (AOT), is a hybrid imaging modality that combines light and sound; it is a form of tomography involving ultrasound. It is used in imaging of biological soft tissues and has potential applications for early cancer detection.Sakadžić, Sava. "Ultrasound-modulated optical tomography in soft biological tissues." Ph. D. dissertation, Texas A&M University, 2006. As a hybrid modality which uses both light and sound, UOT provides some of the best features of both: the use of light provides strong contrast and sensitivity (both molecular and functional); these two features are derived from the optical component of UOT. The use of ultrasound allows for high resolution, as well as a high imaging depth. However, the difficulty of tackling the two fundamental problems with UOT (low SNR in deep tissue and short speckle decorrelation time) have caused UOT to evolve relatively slowly; most work in the field is limited to theoretical simulations or phantom / sample studies.
Basic Description of Acousto-Optic Tomography In UOT, ultrasound transducers are used to apply ultrasounds wave into a medium, usually some biological tissue. Applying these ultrasound waves, or an ultrasound field, to a region of tissue will change the optical properties of the tissue in time and space. This region of ultrasound-modulated tissue is the region of interest (ROI) which will be analyzed. Photons are then sent into the tissue from some source, such as a laser. Eventually, despite the strength of optical scattering in tissue, some of these photons will pass through the ROI. The photons that pass through the ROI will change according to the modulation of the tissue; this causes the photons to be "tagged". Typically, this tagging will cause the frequency of the light to shift by the frequency of the US field.
Sufficiently coherent light traveling through a medium creates a speckle pattern (Fig 1 of next citation). Modulating the ultrasound field applied to the ROI will cause the speckle patterns to change, due to the 3 modulation mechanisms which are explained below. The changes of these speckle patterns are used to derive various properties of the tissue during reconstruction and analysis. Optical properties that can be derived include the optical absorption coefficient, the optical scattering coefficient, and the fluence in the region of interest; UOT can also be used to derive mechanical properties as well.
Use of Light and Sound in Conjunction Optical imaging modalities typically rely on ballistic photons to collect and convey information. However, as a result of strong optical scattering in tissue, conventional imaging modalities struggle to image deeper into tissue, past the optical diffusion limit (typically about 1 mm into tissue). Various imaging modalities have been developed to peer deeper into tissue, such as diffuse optical tomography (DOT) and optical coherence tomography (OCT). While OCT has fantastic spatial resolution (3.5 and 7 micrometer resolutions, axially and lateral respectively), its imaging depth is limited to the millimeter range (e.g. 2.5 mm). DOT has fantastic penetration, on the scale of centimeters, but suffers from inferior resolution (~1cm).
To address the difficulty of deep optical imaging, hybrid ultrasound and optical imaging modalities have been developed, namely UOT and photoacoustic imaging (PAI). Both imaging modalities use diffuse photons, which typically cannot be used to transmit information from deep within the tissue. This is because strong optical scattering means that it is incredibly difficult to determine where the photons have traveled and how many scattering events they might have gone through. UOT and PAI have different ways to effectively transfer information from the diffuse photons within the tissue back to the system, which allows for centimeter imaging depths (deeper than DOT) while retaining high spatial resolutions (millimeters to 100s of micrometers).
Photoacoustic imaging sends a pulse of light into tissue; as photons are absorbed by the tissue, the resulting heating rise results in thermoelastic expansion. This leads to a pressure wave propagation, which is collected by ultrasound transducers. Thus, PAI uses photons to acquire information deep inside tissue and uses ultrasound to transmit that information to the system. In contrast, UOT relies on photons for information transmission and uses ultrasound to acquire information. Ultrasound is used in UOT to "tag" or identify photons which have passed through the region of interest; these photons can be trusted to carry information back to the system regarding the region of interest. The modulation of the ultrasound will accordingly change the optical properties of the tissue, which can be used to derive both optical and mechanical properties.
The difference in the use of ultrasound between PAI and UOT means that different types of information can be derived from the two different modalities. PAI is proficient in delivering information regarding optical absorption; UOT can provide information regarding both optical absorption and optical scattering. Thus, UOT has a strong advantage over PAI in that UOT can provide information about tissue/organ structure as well as tissue metabolism.
Advantages UOT utilizes all photons within deep tissue; as long as they have not been absorbed and they pass through the ROI, those photons can still be used to convey information in UOT. Thus, UOT can achieve imaging depths (exploiting diffuse photons) deeper than 9 cm into the body while retaining high spatial resolutions (from the dimensions of the ultrasound focus), ~mm scale, as of 2017. UOT can be used to derive mechanical and optical properties of the tissue; compared to PAI, which can only derive optical absorption, UOT can derive absorption and scattering properties of the tissue.
Disadvantages There are two fundamental problems with UOT:
UOT has very low signal to noise in deep tissue; with an imaging depth of several centimeters, the ratio between untagged and tagged photons can be greater than 100:1 and even 1000:1. As the tagged photons are the photons which carry the information, this leads to difficulties in recovering data as a result of strong background noise (untagged photons). This is due to deep tissue having a large diffuse volume, which leads to a very low ultrasound focus. Because of this incredibly weak signal to noise ratio, compensatory methods are required for any practical UOT system. One way to tackle this problem is by effective filtering techniques, which allow for a large decrease in the background noise of untagged protons. The other problem is to improve the sensitivity of the UOT system to tagged photons. UOT data comes from speckles resulting from scattering of photons through tissue. As biological tissue is constantly in motion on a microscopic scale, UOT imaging in-vivo results in a very short speckle decorrelation time of less than 1 millisecond in biological tissue. Thus, UOT systems typically require high temporal resolution in order to be able to derive data from stable speckle patterns.
Basic Concepts UOT is built upon the modulation of light due to the effects of ultrasonic waves on the optical properties of the testing medium. The target within the testing medium will be irradiated by a laser beam and a focused ultrasonic wave. The reemitted light propagating through the ultrasonic field or ultrasonic focal zone will then carry information of local optical and acoustic properties of this zone. These properties will be used to reconstruct images showing the inside view of the medium.
Mechanisms There are three important mechanisms behind UOT technology.
1 Incoherent Modulation of Light Due to Ultrasound-Induced Variations in Optical Properties of Medium. As the ultrasonic wave propagates through the medium, the mass density of the medium will be changed due to the vibration. This variation in mass density will then influence the local optical properties. For example, the local absorption coefficient, scattering coefficient, and the index of refraction will all be modulated. With different optical properties, the reemitted light features (like intensity) will be modified.
2 Variations in Optical Phase in Response to Ultrasound-Induced Displacements of Scatterers. This mechanism mainly describes the effect in a microcosmic view. With the vibration from focused ultrasound, the local scatterers within the medium will be moved. When coherent light passes through such region, the displacement of scatterers will then cause optical phases change and then further modulate the light's free-path lengths. In the end, the reemitted light will form speckle pattern.
3 Variations in Optical Phase in Response to Ultrasonic Modulation of Index of Refraction of Background Medium. Similar to the second mechanism, the mass density modulation caused by ultrasonic wave vibration will also modulate the medium's index of refraction. This effect can further influence the free-path phases when light passes through the ultrasonic region and form a speckle pattern.
In conclusion, these three mechanisms describe how the modulation of the ultrasonic wave can modulate and fluctuate the light intensity (in mechanism 1), the light phase and form speckle pattern (mechanism 2 and 3). Mechanisms 2 and 3 require a coherent light source; mechanism 1 does not. When coherent light sources are applied, mechanism 1 can be disregarded, as its effect compared to mechanisms 2 and 3 are effectively negligible. These three mechanisms are the fundamental building blocks required to design a UOT system.
UOT analytic model In analytic model, two approximations are made. (1) the optical wavelength is much shorter than the mean free path (weak-scattering approximation) and (2) the ultrasound-induced change in the optical path length is much less than the optical wavelength (weak-modulation approximation).
With the first approximation, we can assume the ensemble-averaged correlations between electric fields are the same. Since the differences between correlation results from different paths are negligible. With this assumption, the correlations for electric fields G1(ꚍ) can be written as the following:
In this equation the parenthesis represents the ensemble and time averaging. Es demsontrates the unit-amplitude electric field of the scattered light of a path of length s, and p(s) denotes the probability density function of s. In analytic UOT model, we treat the light source as an optical plane wave. We assume the plane wave light normally hit a slab of thickness d. The transmitted light will be captured by a point detector. After applying diffusion theory, the original G1 equation can be further modified as:
Where
In these equations, ωa represents the acoustic angular frequency, and the n0 is the background index of refraction; k0 is the magnitude of the optical wave vector in vacuo; A is the acoustic amplitude, which is proportional to the acoustic pressure; ka is the magnitude of the acoustic wavevector; lt' is the optical transport mean free path; η is the elasto-optical coefficient; ρ is the mass density; represents how ultrasound averagely change the light per free path via index of refraction and displacementare respectively.
After deriving the autocorrelation equation, Wiener-Khinchin theorem is applied. With this theorem, we can further connect G1 with the spectral density of the modulated speckle. Their relationship in frequency space is shown as the following Fourier transformation equation.