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Ultrasound-modulated optical tomography

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.[1] It is used in imaging of biological soft tissues and has potential applications for early cancer detection.[2] 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.[3]

Ultrasound-modulated optical tomography
Purposeimaging of soft tissue

Basic Description of Acousto-Optic Tomography edit

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.[4]

Sufficiently coherent light traveling through a medium creates a speckle pattern (Fig 1 of next citation).[5] 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.[5]

Use of Light and Sound in Conjunction edit

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).[6] 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).[7] DOT has fantastic penetration, on the scale of centimeters, but suffers from inferior resolution (~1cm).[8]

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).[9]

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. [10] 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. [4] 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. [3]

Advantages edit

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.[5][11] 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 edit

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.[12] 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. [3]
    • Thus, UOT systems typically require high temporal resolution in order to be able to derive data from stable speckle patterns.

Basic Concepts edit

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 edit

There are three important mechanisms behind UOT technology.

1 Incoherent Modulation of Light Due to Ultrasound-Induced Variations in Optical Properties of Medium. [5][13] 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.[5][13] 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.[5][13] 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.[5] These three mechanisms are the fundamental building blocks required to design a UOT system.

UOT analytic model edit

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). [13]

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:

 [13]

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.[13] 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:

 [13]

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;[14]   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.

 [14]

For simplicity, the Fourier transformed term exp(-iω0t) is dropped, and the ω here represents relative angular frequency of unmodulated light. For example, if ω=0 this equation is calculating the spectral density with absolute angular frequency ω0. Since G1 is an even autocorrelation function, the spectral intensity at ωa can be written as:

 [14]

Here, the n and Ta represent the acoustic period. Since the frequency spectrum is symmetric about ω0, the one side modulation depth is defined as:

 [15]

Then we can consider the condition under the second approximation (weak-modulation approximation). In this situation, the term   is much smaller than 1. By applying the feature of sinh function, which is the main component of G1 function, the original autocorrelation G1 can be further simplified as:

 [15]

Therefore, the one side modulation depth can be simplified as  . From previous equation, we can see  . Therefore, in conclusion, A and M1 has quadratic relationship. Such quadratic modulation can be captured by a Fabry-Perot interferometer. Or, we can calculate the ratio between observed AC signal and he observed DC signal (also named as apparent modulation depth) which can carry enough information to represent such modulation as well.

In conclusion, in UOT analytic model, with the help of weak-scattering approximation, weak-modulation approximation, diffusion theory, and Wiener-Khinchin theorem, the relationship between acoustic amplitude and modulated light can be successfully observed.

Time-Resolved Frequency-Swept UOT (Forward model) edit

For single-frequency UOT, the axial resolution along ultrasonic axis is always limited by the elongated ultrasonic focal zone. To improve the axial resolution, Ultrasonic frequency-swept UOT model is designed. In this system, the object is placed in a tank full of UOT scattering medium. There will also be an ultrasound absorber at the bottom of the tank to avoid rebound of ultrasound. Basically, a function generator will produce a frequency signal relating to time. After passing through a power amplifier and a transformer, such frequency command will be sent to the ultrasonic transducer to generate ultrasonic beam with different frequencies. After a brief calculation, a focused ultrasonic beam will be sent to the medium and the target. Meanwhile, a laser beam which is perpendicular to the ultrasonic beam will also illuminate the scattering medium. Then, on the other side of the light source, the PMT, modulated by frequency signal sent through the first function generator will detect transmitted light signal within the tank and transfer the optical signal to electrical signal. The electrical signal will then pass through an amplifier, an Oscilloscope and be stored in the data base.

With such data base, spectral intensity vs frequency plots at multiple points can be generated (The first spectrum is generated as a reference, produced by optical signal far from the object.). Each of the spectrum can then be further converted to a 1D image showing the interior of the medium in the direction perpendicular to the tank (z direction). In the end, all the 1D image will be pieced together to generate a full view inside the medium.

In summary, a frequency-swept (chirped) ultrasonic wave can encode laser light traversing the acoustic axis with various frequencies. Decoding the transmitted light provides resolution along the acoustic axis. This scheme is analogous to MRI.[16]

Development edit

Was first proposed as a method for virus detection in 2013.[17]

Recent advances in UOT (2020 onwards) include 1) the development of Coded Ultrasound Transmissions for SNR gain in AOI,[18] 2) the development of Homodyne Time of Flight AOI,[9] 3) the use of super-resolution techniques to improve UOT beyond the acoustic diffraction limit,[11] and 4) the use of coaxial interferometry to better enable modern high-performance cameras for parallel detection of UOT signals. [19]

  1. Levi et al. [20] discovered that the use of coded sequences of acoustic pulses can turn the speckle modulation at every time instant into the sum of acoustically modulated regions. CT-AOI can keep the spatial resolution from single cycle ultrasound pulses while increasing SNR by the half of the square root of the number of cycles. In this paper, Levi et al. use 79 cycles to gain an experimental 4 times increase to the SNR.
  2. As a follow-up to their previous work, Levi et al. developed[9] a homodyne AOI scheme enabling the detection of tagged detection with a single low-gain photodetector. This method leads to a 4 times SNR increase over more traditional high-gain photodetectors, such as photomultiplier tubes. In this homodyne time-of-flight AOI system, the reemitted light is not detected directly but is rather interfered with a reference beam in a homodyne configuration. The interference leads to an optical amplification of the US-modulated light, enabling its detection with low-gain photodetectors with a bandwidth that is higher than the AO modulation frequency. This setup does not temporally integrate the signal, allowing for much more flexibility regarding speckle decorrelation. This is because the measurement signal can be divided in post-processing, allowing the analysis of time windows wherein the speckles are stable.
  3. Doktofksy et al.[11] utilized super-resolution optical fluctuations imaging (SOFI) techniques to gain massive improvements to spatial resolution in UOT. Naturally fluctuating speckle grains present in UOT images are analogous to blinking fluorophores in SOFI, which enables super-resolution.
  4. Normally, single-pixel detectors (e.g. photodiode) are used in UOT. These detectors suffer from limited dynamic range, which causes difficulties with low modulation depth. Modulation depth can be enhanced by using multiple pixels in parallel; the enhancement is equal to N ^ (1/2), where N represents the number of pixels. Modern high-performance cameras have millions of pixels but have low temporal resolution (slow framerate and long exposure time). Lin et al. [19] tackled this issue by designing a system with paired illumination from two co-propagated beams with slightly different optical frequencies.

References edit

  1. ^ Zemp, Roger J.; Kim, Chulhong; Wang, Lihong V. (April 2007). "Ultrasound-modulated optical tomography with intense acoustic bursts" (PDF). Appl Opt. 46 (10): 1615–23. Bibcode:2007ApOpt..46.1615Z. doi:10.1364/ao.46.001615. PMID 17356603.
  2. ^ Sakadžić, Sava. "Ultrasound-modulated optical tomography in soft biological tissues." Ph. D. dissertation, Texas A&M University, 2006.
  3. ^ a b c Omidali, Mohammadreza; Mardanshahi, Ali; Särestöniemi, Mariella; Zhao, Zuomin; Myllylä, Teemu (2023-01-25). "Acousto−Optics: Recent Studies and Medical Applications". Biosensors. 13 (2): 186. doi:10.3390/bios13020186. ISSN 2079-6374. PMC 9953934. PMID 36831952.
  4. ^ a b Wang, Lihong V. (2004). "Ultrasound-Mediated Biophotonic Imaging: A Review of Acousto-Optical Tomography and Photo-Acoustic Tomography". Disease Markers. 19 (2–3): 123–138. doi:10.1155/2004/478079. ISSN 0278-0240. PMC 3851612. PMID 15096709.
  5. ^ a b c d e f g Gunther, Jacqueline; Andersson-Engels, Stefan (September 2017). "Review of current methods of acousto-optical tomography for biomedical applications". Frontiers of Optoelectronics. 10 (3): 211–238. doi:10.1007/s12200-017-0718-4. ISSN 2095-2759. S2CID 255537005.
  6. ^ Giacomelli, Michael G.; Wax, Adam (2011-02-17). "Imaging beyond the ballistic limit in coherence imaging using multiply scattered light". Optics Express. 19 (5): 4268–4279. Bibcode:2011OExpr..19.4268G. doi:10.1364/oe.19.004268. ISSN 1094-4087. PMC 3368313. PMID 21369257. S2CID 12633277.
  7. ^ Lee, Jang-Hoon; Stefan, Sabina; Walek, Konrad; Nie, Jiarui; Min, Kyounghee; Yang, Taeseok Daniel; Lee, Jonghwan (2023-03-10). "Investigating the correlation between early vascular alterations and cognitive impairment in Alzheimer's disease in mice with SD-OCT". Biomedical Optics Express. 14 (4): 1494–1508. doi:10.1364/boe.481826. ISSN 2156-7085. PMC 10110305. PMID 37078054.
  8. ^ Nguyen, Hoang-Dung; Hong, Keum-Shik (2016-08-16). "Bundled-optode implementation for 3D imaging in functional near-infrared spectroscopy". Biomedical Optics Express. 7 (9): 3491–3507. doi:10.1364/boe.7.003491. ISSN 2156-7085. PMC 5030027. PMID 27699115.
  9. ^ a b c Levi, Ahiad R.; Hazan, Yoav; Lev, Aner; Sfez, Bruno G.; Rosenthal, Amir (2023-02-01). "Homodyne time-of-flight acousto-optic imaging for low-gain photodetector". Biomedical Engineering Letters. 13 (1): 49–56. doi:10.1007/s13534-022-00252-w. ISSN 2093-985X. PMC 9873866. PMID 36711164.
  10. ^ Tang, Yuqi; Wu, Huaiyu; Klippel, Paul; Zhang, Bohua; Huang, Hsiao-Ying Shadow; Jing, Yun; Jiang, Xiaoning; Yao, Junjie (2022-01-31). "Deep thrombosis characterization using photoacoustic imaging with intravascular light delivery". Biomedical Engineering Letters. 12 (2): 135–145. doi:10.21203/rs.3.rs-1312641/v1. PMC 9046522. PMID 35529341. Retrieved 2023-04-26.
  11. ^ a b c Doktofsky, Daniel; Rosenfeld, Moriya; Katz, Ori (2020-01-03). "Acousto optic imaging beyond the acoustic diffraction limit using speckle decorrelation". Communications Physics. 3 (1): 5. Bibcode:2020CmPhy...3....5D. doi:10.1038/s42005-019-0267-9. ISSN 2399-3650. S2CID 257110849.
  12. ^ Huang, Yujia; Cua, Michelle; Brake, Joshua; Liu, Yan; Yang, Changhuei (February 2020). "Investigating ultrasound–light interaction in scattering media". Journal of Biomedical Optics. 25 (2): 025002. Bibcode:2020JBO....25b5002H. doi:10.1117/1.JBO.25.2.025002. ISSN 1083-3668. PMC 7043283. PMID 32103649.
  13. ^ a b c d e f g Wang, Lihong V.; Wu, Hsin-l (July 2009). Biomedical Optics: Principles and Imaging. John Wiley & Sons. pp. 323–324. ISBN 9780470177013.
  14. ^ a b c Wang, Lihong V.; Wu, Hsin-I (July 2009). Biomedical Optics: Principles and Imaging. John Wiley & Sons. p. 325. ISBN 9780470177013.
  15. ^ a b Wang, Lihong V; Wu, Hsin-I (July 2009). Biomedical Optics: Principles and Imaging. John Wiley & Sons. p. 326. ISBN 9780470177013.
  16. ^ Wang, Lihong V; Wu, Hsin-I (July 2009). Biomedical Optics: Principles and Imaging. John Wiley & Sons. p. 329. ISBN 9780470177013.
  17. ^ F. A. 77.3, H. W. 187, and G. W. 189, A comprehensive approach to heart virus detection using light: Photosenthesis sun localization by ultrasound cola and tissue characterization by spectrum disincrimination," Protocall. SPY 1888, 500-510 (2013)
  18. ^ Levi, Ahiad; Monin, Sagi; Hahamovich, Evgeny; Lev, Aner; Sfez, Bruno G.; Rosenthal, Amir (2020-05-14). "Increased SNR in acousto-optic imaging via coded ultrasound transmission". Optics Letters. 45 (10): 2858–2861. arXiv:2003.04692. Bibcode:2020OptL...45.2858L. doi:10.1364/ol.392617. ISSN 0146-9592. PMID 32412486. S2CID 212645883.
  19. ^ a b Lin, Guangzhong; Wu, Daixuan; Luo, Jiawei; Liang, Hanpeng; Wei, Ziyang; Xu, Yiyun; Liu, Sinuo; Shao, Lijie; Shen, Yuecheng (2022-12-06). "Coaxial interferometry for camera-based ultrasound-modulated optical tomography with paired illumination". Optics Express. 30 (26): 46227–46235. Bibcode:2022OExpr..3046227L. doi:10.1364/oe.470956. ISSN 1094-4087. PMID 36558581. S2CID 253795277.
  20. ^ Levi, Ahiad; Monin, Sagi; Hahamovich, Evgeny; Lev, Aner; Sfez, Bruno G.; Rosenthal, Amir (2020-05-14). "Increased SNR in acousto-optic imaging via coded ultrasound transmission". Optics Letters. 45 (10): 2858–2861. arXiv:2003.04692. Bibcode:2020OptL...45.2858L. doi:10.1364/ol.392617. ISSN 0146-9592. PMID 32412486. S2CID 212645883.

ultrasound, modulated, optical, tomography, also, known, acousto, optic, tomography, hybrid, imaging, modality, that, combines, light, sound, form, tomography, involving, ultrasound, used, imaging, biological, soft, tissues, potential, applications, early, can. 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 1 It is used in imaging of biological soft tissues and has potential applications for early cancer detection 2 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 3 Ultrasound modulated optical tomographyPurposeimaging of soft tissueContents 1 Basic Description of Acousto Optic Tomography 2 Use of Light and Sound in Conjunction 3 Advantages 4 Disadvantages 5 Basic Concepts 5 1 Mechanisms 6 UOT analytic model 7 Time Resolved Frequency Swept UOT Forward model 8 Development 9 ReferencesBasic Description of Acousto Optic Tomography editIn 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 4 Sufficiently coherent light traveling through a medium creates a speckle pattern Fig 1 of next citation 5 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 5 Use of Light and Sound in Conjunction editOptical 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 6 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 7 DOT has fantastic penetration on the scale of centimeters but suffers from inferior resolution 1cm 8 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 9 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 10 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 4 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 3 Advantages editUOT 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 5 11 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 editThere 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 12 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 3 Thus UOT systems typically require high temporal resolution in order to be able to derive data from stable speckle patterns Basic Concepts editUOT 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 edit There are three important mechanisms behind UOT technology 1 Incoherent Modulation of Light Due to Ultrasound Induced Variations in Optical Properties of Medium 5 13 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 5 13 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 5 13 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 5 These three mechanisms are the fundamental building blocks required to design a UOT system UOT analytic model editIn 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 13 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 G 1 t p s E s t E s t t d s displaystyle G1 tau int p s langle E s t E s t tau rangle ds nbsp 13 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 13 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 G 1 t d l t sinh e 1 c o s w a t 1 2 sinh d l t e 1 c o s w a t 1 2 displaystyle G1 tau left frac left frac d l t right sinh varepsilon 1 cos omega a tau 1 2 sinh d l t varepsilon 1 cos omega a tau 1 2 right nbsp 13 Where e 6 d n d d n 0 k 0 A 1 2 displaystyle varepsilon 6 delta n delta d n 0 k 0 A 1 2 nbsp d n a n 1 a n 2 h 2 displaystyle delta n alpha n1 alpha n2 eta 2 nbsp a n 1 1 2 k a l t arctan k a l t displaystyle alpha n1 1 2k a l t arctan k a l t nbsp a n 2 a n 1 k a l t arctan k a l t 1 displaystyle alpha n2 frac alpha n1 k a l t arctan k a l t 1 nbsp d d 1 6 displaystyle delta d frac 1 6 nbsp In these equations wa 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 h is the elasto optical coefficient r is the mass density 14 d n d d displaystyle delta n delta d nbsp 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 S w G 1 t exp i w t d t displaystyle S omega int infty infty G1 tau exp i omega tau d tau nbsp 14 For simplicity the Fourier transformed term exp iw0t is dropped and the w here represents relative angular frequency of unmodulated light For example if w 0 this equation is calculating the spectral density with absolute angular frequency w0 Since G1 is an even autocorrelation function the spectral intensity at wa can be written as I n 1 T a 0 T a cos n w a t G 1 t d t displaystyle I n frac 1 T a int limits 0 T a cos n omega a tau G1 tau d tau nbsp 14 Here the n and Ta represent the acoustic period Since the frequency spectrum is symmetric about w0 the one side modulation depth is defined as M 1 I 1 I 0 displaystyle M 1 frac I 1 I 0 nbsp 15 Then we can consider the condition under the second approximation weak modulation approximation In this situation the term d l t e 1 2 displaystyle d l t varepsilon 1 2 nbsp is much smaller than 1 By applying the feature of sinh function which is the main component of G1 function the original autocorrelation G1 can be further simplified as G 1 t 1 1 6 d l t 2 e 1 c o s w a t displaystyle G1 tau 1 frac 1 6 frac d l t 2 varepsilon 1 cos omega a tau nbsp 15 Therefore the one side modulation depth can be simplified as M 1 1 12 d l t 2 e displaystyle M 1 frac 1 12 frac d l t 2 varepsilon nbsp From previous equation we can see e 6 d n d d n 0 k 0 A 1 2 displaystyle varepsilon 6 delta n delta d n 0 k 0 A 1 2 nbsp Therefore in conclusion A and M1 has quadratic relationship Such quadratic modulation can be captured by a Fabry Perot interferometer Or we can calculate the ratio between observed AC signal and he observed DC signal also named as apparent modulation depth which can carry enough information to represent such modulation as well In conclusion in UOT analytic model with the help of weak scattering approximation weak modulation approximation diffusion theory and Wiener Khinchin theorem the relationship between acoustic amplitude and modulated light can be successfully observed Time Resolved Frequency Swept UOT Forward model editFor single frequency UOT the axial resolution along ultrasonic axis is always limited by the elongated ultrasonic focal zone To improve the axial resolution Ultrasonic frequency swept UOT model is designed In this system the object is placed in a tank full of UOT scattering medium There will also be an ultrasound absorber at the bottom of the tank to avoid rebound of ultrasound Basically a function generator will produce a frequency signal relating to time After passing through a power amplifier and a transformer such frequency command will be sent to the ultrasonic transducer to generate ultrasonic beam with different frequencies After a brief calculation a focused ultrasonic beam will be sent to the medium and the target Meanwhile a laser beam which is perpendicular to the ultrasonic beam will also illuminate the scattering medium Then on the other side of the light source the PMT modulated by frequency signal sent through the first function generator will detect transmitted light signal within the tank and transfer the optical signal to electrical signal The electrical signal will then pass through an amplifier an Oscilloscope and be stored in the data base With such data base spectral intensity vs frequency plots at multiple points can be generated The first spectrum is generated as a reference produced by optical signal far from the object Each of the spectrum can then be further converted to a 1D image showing the interior of the medium in the direction perpendicular to the tank z direction In the end all the 1D image will be pieced together to generate a full view inside the medium In summary a frequency swept chirped ultrasonic wave can encode laser light traversing the acoustic axis with various frequencies Decoding the transmitted light provides resolution along the acoustic axis This scheme is analogous to MRI 16 Development editWas first proposed as a method for virus detection in 2013 17 Recent advances in UOT 2020 onwards include 1 the development of Coded Ultrasound Transmissions for SNR gain in AOI 18 2 the development of Homodyne Time of Flight AOI 9 3 the use of super resolution techniques to improve UOT beyond the acoustic diffraction limit 11 and 4 the use of coaxial interferometry to better enable modern high performance cameras for parallel detection of UOT signals 19 Levi et al 20 discovered that the use of coded sequences of acoustic pulses can turn the speckle modulation at every time instant into the sum of acoustically modulated regions CT AOI can keep the spatial resolution from single cycle ultrasound pulses while increasing SNR by the half of the square root of the number of cycles In this paper Levi et al use 79 cycles to gain an experimental 4 times increase to the SNR As a follow up to their previous work Levi et al developed 9 a homodyne AOI scheme enabling the detection of tagged detection with a single low gain photodetector This method leads to a 4 times SNR increase over more traditional high gain photodetectors such as photomultiplier tubes In this homodyne time of flight AOI system the reemitted light is not detected directly but is rather interfered with a reference beam in a homodyne configuration The interference leads to an optical amplification of the US modulated light enabling its detection with low gain photodetectors with a bandwidth that is higher than the AO modulation frequency This setup does not temporally integrate the signal allowing for much more flexibility regarding speckle decorrelation This is because the measurement signal can be divided in post processing allowing the analysis of time windows wherein the speckles are stable Doktofksy et al 11 utilized super resolution optical fluctuations imaging SOFI techniques to gain massive improvements to spatial resolution in UOT Naturally fluctuating speckle grains present in UOT images are analogous to blinking fluorophores in SOFI which enables super resolution Normally single pixel detectors e g photodiode are used in UOT These detectors suffer from limited dynamic range which causes difficulties with low modulation depth Modulation depth can be enhanced by using multiple pixels in parallel the enhancement is equal to N 1 2 where N represents the number of pixels Modern high performance cameras have millions of pixels but have low temporal resolution slow framerate and long exposure time Lin et al 19 tackled this issue by designing a system with paired illumination from two co propagated beams with slightly different optical frequencies References edit Zemp Roger J Kim Chulhong Wang Lihong V April 2007 Ultrasound modulated optical tomography with intense acoustic bursts PDF Appl Opt 46 10 1615 23 Bibcode 2007ApOpt 46 1615Z doi 10 1364 ao 46 001615 PMID 17356603 Sakadzic Sava Ultrasound modulated optical tomography in soft biological tissues Ph D dissertation Texas A amp M University 2006 a b c Omidali Mohammadreza Mardanshahi Ali Sarestoniemi Mariella Zhao Zuomin Myllyla Teemu 2023 01 25 Acousto Optics Recent Studies and Medical Applications Biosensors 13 2 186 doi 10 3390 bios13020186 ISSN 2079 6374 PMC 9953934 PMID 36831952 a b Wang Lihong V 2004 Ultrasound Mediated Biophotonic Imaging A Review of Acousto Optical Tomography and Photo Acoustic Tomography Disease Markers 19 2 3 123 138 doi 10 1155 2004 478079 ISSN 0278 0240 PMC 3851612 PMID 15096709 a b c d e f g Gunther Jacqueline Andersson Engels Stefan September 2017 Review of current methods of acousto optical tomography for biomedical applications Frontiers of Optoelectronics 10 3 211 238 doi 10 1007 s12200 017 0718 4 ISSN 2095 2759 S2CID 255537005 Giacomelli Michael G Wax Adam 2011 02 17 Imaging beyond the ballistic limit in coherence imaging using multiply scattered light Optics Express 19 5 4268 4279 Bibcode 2011OExpr 19 4268G doi 10 1364 oe 19 004268 ISSN 1094 4087 PMC 3368313 PMID 21369257 S2CID 12633277 Lee Jang Hoon Stefan Sabina Walek Konrad Nie Jiarui Min Kyounghee Yang Taeseok Daniel Lee Jonghwan 2023 03 10 Investigating the correlation between early vascular alterations and cognitive impairment in Alzheimer s disease in mice with SD OCT Biomedical Optics Express 14 4 1494 1508 doi 10 1364 boe 481826 ISSN 2156 7085 PMC 10110305 PMID 37078054 Nguyen Hoang Dung Hong Keum Shik 2016 08 16 Bundled optode implementation for 3D imaging in functional near infrared spectroscopy Biomedical Optics Express 7 9 3491 3507 doi 10 1364 boe 7 003491 ISSN 2156 7085 PMC 5030027 PMID 27699115 a b c Levi Ahiad R Hazan Yoav Lev Aner Sfez Bruno G Rosenthal Amir 2023 02 01 Homodyne time of flight acousto optic imaging for low gain photodetector Biomedical Engineering Letters 13 1 49 56 doi 10 1007 s13534 022 00252 w ISSN 2093 985X PMC 9873866 PMID 36711164 Tang Yuqi Wu Huaiyu Klippel Paul Zhang Bohua Huang Hsiao Ying Shadow Jing Yun Jiang Xiaoning Yao Junjie 2022 01 31 Deep thrombosis characterization using photoacoustic imaging with intravascular light delivery Biomedical Engineering Letters 12 2 135 145 doi 10 21203 rs 3 rs 1312641 v1 PMC 9046522 PMID 35529341 Retrieved 2023 04 26 a b c Doktofsky Daniel Rosenfeld Moriya Katz Ori 2020 01 03 Acousto optic imaging beyond the acoustic diffraction limit using speckle decorrelation Communications Physics 3 1 5 Bibcode 2020CmPhy 3 5D doi 10 1038 s42005 019 0267 9 ISSN 2399 3650 S2CID 257110849 Huang Yujia Cua Michelle Brake Joshua Liu Yan Yang Changhuei February 2020 Investigating ultrasound light interaction in scattering media Journal of Biomedical Optics 25 2 025002 Bibcode 2020JBO 25b5002H doi 10 1117 1 JBO 25 2 025002 ISSN 1083 3668 PMC 7043283 PMID 32103649 a b c d e f g Wang Lihong V Wu Hsin l July 2009 Biomedical Optics Principles and Imaging John Wiley amp Sons pp 323 324 ISBN 9780470177013 a b c Wang Lihong V Wu Hsin I July 2009 Biomedical Optics Principles and Imaging John Wiley amp Sons p 325 ISBN 9780470177013 a b Wang Lihong V Wu Hsin I July 2009 Biomedical Optics Principles and Imaging John Wiley amp Sons p 326 ISBN 9780470177013 Wang Lihong V Wu Hsin I July 2009 Biomedical Optics Principles and Imaging John Wiley amp Sons p 329 ISBN 9780470177013 F A 77 3 H W 187 and G W 189 A comprehensive approach to heart virus detection using light Photosenthesis sun localization by ultrasound cola and tissue characterization by spectrum disincrimination Protocall SPY 1888 500 510 2013 Levi Ahiad Monin Sagi Hahamovich Evgeny Lev Aner Sfez Bruno G Rosenthal Amir 2020 05 14 Increased SNR in acousto optic imaging via coded ultrasound transmission Optics Letters 45 10 2858 2861 arXiv 2003 04692 Bibcode 2020OptL 45 2858L doi 10 1364 ol 392617 ISSN 0146 9592 PMID 32412486 S2CID 212645883 a b Lin Guangzhong Wu Daixuan Luo Jiawei Liang Hanpeng Wei Ziyang Xu Yiyun Liu Sinuo Shao Lijie Shen Yuecheng 2022 12 06 Coaxial interferometry for camera based ultrasound modulated optical tomography with paired illumination Optics Express 30 26 46227 46235 Bibcode 2022OExpr 3046227L doi 10 1364 oe 470956 ISSN 1094 4087 PMID 36558581 S2CID 253795277 Levi Ahiad Monin Sagi Hahamovich Evgeny Lev Aner Sfez Bruno G Rosenthal Amir 2020 05 14 Increased SNR in acousto optic imaging via coded ultrasound transmission Optics Letters 45 10 2858 2861 arXiv 2003 04692 Bibcode 2020OptL 45 2858L doi 10 1364 ol 392617 ISSN 0146 9592 PMID 32412486 S2CID 212645883 Retrieved from https en wikipedia org w index php title Ultrasound modulated optical tomography amp 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