Diffuse optical mammography

Last updated
Diffuse optical mammography
Example of tissue composition maps. - Fig.2.jpg
Example of breast constituents' concentrations maps through optical mammography (right cranio-caudal view). The blue arrow points to the lesion. Hb stands for deoxy-hemoglobin, HbO2 for oxy-hemoglobin, tHb for total hemoglobin. [1]
Purposeinvestigation of the breast composition through spectral analysis

Diffuse optical mammography, or simply optical mammography, is an emerging imaging technique that enables the investigation of the breast composition through spectral analysis. It combines in a single non-invasive tool the capability to implement breast cancer risk assessment, [2] lesion characterization, [3] therapy monitoring [4] and prediction of therapy outcome. [5] It is an application of diffuse optics, which studies light propagation in strongly diffusive media, such as biological tissues, working in the red and near-infrared spectral range, between 600 and 1100 nm. [6]

Contents

Comparison with conventional imaging techniques

Currently, the most common breast imaging techniques are X-ray mammography, ultrasounds, MRI and PET.[ citation needed ]

X-ray mammography is widely spread for breast screening, thanks to its high spatial resolution [7] and the short measurement time. However, it is not sensitive to the breast physiology, [8] it is characterized by a limited efficiency in investigating dense breasts [9] and it is harmful due to the use of ionizing radiation. [10] Ultrasounds are non-invasive and they are used especially on young women, [11] who are usually characterized by dense breasts, but the images interpretation depends on the operator's experience. MRI shows a good correlation with the tumour dimensions and is claimed to be the best method for the identification and characterization of lesions. [12] Even though there is no verified long-term health risk from the magnetic fields employed during an MRI, it is not used as first investigative tool because of the high costs and the elevated duration of the exam. [13] Finally, PET allows the early evaluation of the metabolic changes of the tumour, [14] but it is very expensive and requires the administration of a radioactive tracer. For this reason, its application is not frequently recommended.

On the contrary, optical mammography is cheap, efficient also on dense breasts, and devoid of any side effect, so that it can be used to track the evolution of the patient's condition on a daily basis. It is also able to characterize breast from a physiologic point of view. [15] However, being still under development, there is a lack of standardization in data analysis among the research groups dealing with it, and it suffers from low spatial resolution. For this reason, a "multimodal approach" is suggested, where optical mammography is complementary to another conventional technique, so that also the diagnostic efficacy is improved. [10] [15]

Physical mechanism

Photon migration in diffusive media

Biological tissues are diffusive media, which means that light attenuation during propagation is due not only to absorption, but also to scattering. The former is related to the chemical composition of the medium and induces photon annihilation, whereas the latter depends on the microscopic inhomogeneities of its refractive index and determines deviations in photon's trajectory. [6] The absorption coefficient represents the probability per unit length that an absorption event takes place, while the scattering coefficient denotes the probability per unit length that a scattering event occurs. [16] However, many studies refer to the reduced scattering coefficient rather than the simple scattering coefficient, in order to take into account the medium's anisotropy. The medium's anisotropy is represented by the factor , which is the average cosine of the angular deflection. [6]

Light propagation through highly diffusive media is typically described through the heuristic approach of the radiative transport theory, sided by the so-called “diffusion approximation”: scattering is assumed to be isotropic and strongly dominant over absorption. This is fairly accurate for example for the breast tissue, in the red and near infrared spectral range (between 600 and 1100 nm), known also as "therapeutic window". In the therapeutic window, light can penetrate a few centimetres, so that it can explore the volume at exam. This is the reason why photon migration in biological tissues is known also as "diffuse optics". [6]

The relation between reduced scattering coefficient and wavelength () derives from the Mie theory: [17]

Experimental breast constituent's normalized absorption spectra. Hb stands for deoxy-hemoglobin, HbO2 for oxy-hemoglobin. Breast constituent's absorption spectra.png
Experimental breast constituent's normalized absorption spectra. Hb stands for deoxy-hemoglobin, HbO2 for oxy-hemoglobin.

where is the reference wavelength and and refer to the size of the scattering centres and their density, respectively.

Regarding the absorption coefficient, the relation with is mediated by the so-called “extinction coefficient” , [18] that in combination with the Lambert-Beer law gives

where is the concentration of the ith breast constituent. Measuring at different wavelengths, the breast constituents’ concentrations can be extrapolated.

Breast constituents' absorption spectra

The main breast constituents are oxy and deoxy-hemoglobin, water, lipids and collagen. [1] In particular, collagen has been recognized as an independent risk factor for developing breast cancer. [19]

Blood strongly absorbs in the red spectral range, whereas collagen, water and lipids have their absorption peaks at wavelengths longer than 900 nm. The distinction between oxy and deoxy-haemoglobin is due to the presence of a second large peak in the case of oxy-haemoglobin. Lipids are characterized by absorption maxima at 930 nm and 1040 nm, while the wavelength 975 nm is sensitive to water. Finally, an absorption peak for collagen takes place at 1030 nm. [16] [1]

Possible implementations

Diffuse optical mammography can be implemented exploiting three different approaches: time domain, [20] frequency domain [21] and continuous wave. [22] Moreover, there exist two main geometries to perform an optical measurement:

Whatever the chosen approach is, any optical mammograph must comprehend some essential elements: laser sources, a detector, a signal processor.

The use of multiple laser sources allows to investigate the breast constituents' concentrations of interest, by selecting some specific wavelengths. Detectors are usually photomultiplier tubes [23] or avalanche photodiodes. [27] Finally, the signal processor could be a device for Time-correlated single photon counting [28] in the case of a time-resolved optical mammograph, [25] or a filter for frequency modulation in the case of frequency-domain ones. [29]

Based on the number and position of sources and detectors, an optical mammograph can produce bidimensional or three-dimensional breast constituents' maps.[ citation needed ]

Time domain

In time-domain measurements, short light pulses of the order of hundreds of picoseconds are delivered to the breast and its optical properties are retrieved from the features of the re-emitted pulses, which have undergone delay, broadening and attenuation. [25] [30] Time-correlated single photon counting is fundamental to cope with the low-level output signal. [28]

Frequency domain

In frequency-domain measurements, an intensity-modulated signal is injected into the breast and its optical properties are deduced from the dephasement and the demodulation of the output signal with respect to the input one. The measurement is repeated for different values of the frequency modulation. [29] [31]

Continuous wave

In continuous wave (CW) measurements, the light source is a continuous wave laser, which hinders the separation of the absorption and scattering contributions with a single measurement. A possible solution is to perform space or angle-resolved measurements. In general, the CW approach is combined with the frequency domain one, in order to reinforce the strengths of both. [27]

Potential applications

Breast cancer risk assessment

A denser breast is more likely to develop breast cancer. [19] A dense breast is characterized by a meaningful amount of fibrous tissue, relatively to the adipose one. The main constituents of a fibrous tissue are water, collagen and hemoglobin and optical mammography is able to discriminate and quantify tissues' components. [2] Therefore, by measuring breast constituents' concentrations, optical mammography could assess breast cancer risk. [2] [32] [33]

Lesion characterization

Tumours are generally made of fibrous tissue and could be recognized in the constituents' maps as local spots with higher concentrations of water, collagen and hemoglobin with respect to the surrounding, mostly adipose, healthy tissues. Studies demonstrate that the variation in concentration with respect to the healthy tissue is statistically more marked in the case of malignant tumours than benign ones. [34] [35] In addition, the scattering coefficient is generally higher for benign lesions. Such distinctions suggest that optical mammography could characterize breast lesions. [34] [35] [36] [37]

Therapy monitoring and prediction of therapy outcome

Breast cancer management depends on the characteristics of the tumour and the patient's condition. One of the possible strategies is the administration of neoadjuvant therapy, whose goal is to shrink the tumour size before surgery. [38] Studies show that if the therapy is efficient, then the water, collagen and hemoglobin contents of the lesion show a decreasing behaviour over time, which suggests that the initially fibrous tissue acquires features similar to the adipose one. [4] [39] Optical measurements in correspondence with therapy sessions could track its evolution, so to assess the patient's response to it. Moreover, it is believed that therapy effectiveness could be predicted even on the first day of treatment on the base of initial breast constituents' concentrations. [40] [5]

See also


Related Research Articles

Medical optical imaging is the use of light as an investigational imaging technique for medical applications, pioneered by American Physical Chemist Britton Chance. Examples include optical microscopy, spectroscopy, endoscopy, scanning laser ophthalmoscopy, laser Doppler imaging, and optical coherence tomography. Because light is an electromagnetic wave, similar phenomena occur in X-rays, microwaves, and radio waves.

Computed tomography laser mammography (CTLM) is the trademark of Imaging Diagnostic Systems, Inc. for its optical tomographic technique for female breast imaging.

<span class="mw-page-title-main">Functional near-infrared spectroscopy</span> Optical technique for monitoring brain activity

Functional near-infrared spectroscopy (fNIRS) is an optical brain monitoring technique which uses near-infrared spectroscopy for the purpose of functional neuroimaging. Using fNIRS, brain activity is measured by using near-infrared light to estimate cortical hemodynamic activity which occur in response to neural activity. Alongside EEG, fNIRS is one of the most common non-invasive neuroimaging techniques which can be used in portable contexts. The signal is often compared with the BOLD signal measured by fMRI and is capable of measuring changes both in oxy- and deoxyhemoglobin concentration, but can only measure from regions near the cortical surface. fNIRS may also be referred to as Optical Topography (OT) and is sometimes referred to simply as NIRS.

<span class="mw-page-title-main">Optical tomography</span>

Optical tomography is a form of computed tomography that creates a digital volumetric model of an object by reconstructing images made from light transmitted and scattered through an object. Optical tomography is used mostly in medical imaging research. Optical tomography in industry is used as a sensor of thickness and internal structure of semiconductors.

<span class="mw-page-title-main">Bruce J. Tromberg</span> American chemist

Bruce J. Tromberg is an American photochemist and a leading researcher in the field of biophotonics. He is the director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) within the National Institutes of Health (NIH). Before joining NIH, he was Professor of Biomedical Engineering at The Henry Samueli School of Engineering and of Surgery at the School of Medicine, University of California, Irvine. He was the principal investigator of the Laser Microbeam and Medical Program (LAMMP), and the Director of the Beckman Laser Institute and Medical Clinic at Irvine. He was a co-leader of the Onco-imaging and Biotechnology Program of the NCI Chao Family Comprehensive Cancer Center at Irvine.

<span class="mw-page-title-main">Second-harmonic imaging microscopy</span>

Second-harmonic imaging microscopy (SHIM) is based on a nonlinear optical effect known as second-harmonic generation (SHG). SHIM has been established as a viable microscope imaging contrast mechanism for visualization of cell and tissue structure and function. A second-harmonic microscope obtains contrasts from variations in a specimen's ability to generate second-harmonic light from the incident light while a conventional optical microscope obtains its contrast by detecting variations in optical density, path length, or refractive index of the specimen. SHG requires intense laser light passing through a material with a noncentrosymmetric molecular structure, either inherent or induced externally, for example by an electric field.

<span class="mw-page-title-main">Monte Carlo method for photon transport</span>

Modeling photon propagation with Monte Carlo methods is a flexible yet rigorous approach to simulate photon transport. In the method, local rules of photon transport are expressed as probability distributions which describe the step size of photon movement between sites of photon-matter interaction and the angles of deflection in a photon's trajectory when a scattering event occurs. This is equivalent to modeling photon transport analytically by the radiative transfer equation (RTE), which describes the motion of photons using a differential equation. However, closed-form solutions of the RTE are often not possible; for some geometries, the diffusion approximation can be used to simplify the RTE, although this, in turn, introduces many inaccuracies, especially near sources and boundaries. In contrast, Monte Carlo simulations can be made arbitrarily accurate by increasing the number of photons traced. For example, see the movie, where a Monte Carlo simulation of a pencil beam incident on a semi-infinite medium models both the initial ballistic photon flow and the later diffuse propagation.

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. 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 ; 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 have caused UOT to evolve relatively slowly; most work in the field is limited to theoretical simulations or phantom / sample studies.

The near-infrared (NIR) window defines the range of wavelengths from 650 to 1350 nanometre (nm) where light has its maximum depth of penetration in tissue. Within the NIR window, scattering is the most dominant light-tissue interaction, and therefore the propagating light becomes diffused rapidly. Since scattering increases the distance travelled by photons within tissue, the probability of photon absorption also increases. Because scattering has weak dependence on wavelength, the NIR window is primarily limited by the light absorption of blood at short wavelengths and water at long wavelengths. The technique using this window is called NIRS. Medical imaging techniques such as fluorescence image-guided surgery often make use of the NIR window to detect deep structures.

Robert Alfano is an Italian-American experimental physicist. He is a Distinguished Professor of Science and Engineering at the City College and Graduate School of New York of the City University of New York, where he is also the founding director of the Institute for Ultrafast Spectroscopy and Lasers (1982). He is a pioneer in the fields of Biomedical Imaging and Spectroscopy, Ultrafast lasers and optics, tunable lasers, semiconductor materials and devices, optical materials, biophysics, nonlinear optics and photonics; he has also worked extensively in nanotechnology and coherent backscattering. His discovery of the white-light supercontinuum laser is at the root of optical coherence tomography, which is breaking barriers in ophthalmology, cardiology, and oral cancer detection among other applications. He initiated the field known now as Optical Biopsy

<span class="mw-page-title-main">Diffuse optical imaging</span>

Diffuse optical imaging (DOI) is a method of imaging using near-infrared spectroscopy (NIRS) or fluorescence-based methods. When used to create 3D volumetric models of the imaged material DOI is referred to as diffuse optical tomography, whereas 2D imaging methods are classified as diffuse optical imaging.

<span class="mw-page-title-main">Breast imaging</span>

In medicine, breast imaging is a sub-speciality of diagnostic radiology that involves imaging of the breasts for screening or diagnostic purposes. There are various methods of breast imaging using a variety of technologies as described in detail below. Traditional screening and diagnostic mammography uses x-ray technology and has been the mainstay of breast imaging for many decades. Breast tomosynthesis is a relatively new digital x-ray mammography technique that produces multiple image slices of the breast similar to, but distinct from, computed tomography (CT). Xeromammography and galactography are somewhat outdated technologies that also use x-ray technology and are now used infrequently in the detection of breast cancer. Breast ultrasound is another technology employed in diagnosis and screening that can help differentiate between fluid filled and solid lesions, an important factor to determine if a lesion may be cancerous. Breast MRI is a technology typically reserved for high-risk patients and patients recently diagnosed with breast cancer. Lastly, scintimammography is used in a subgroup of patients who have abnormal mammograms or whose screening is not reliable on the basis of using traditional mammography or ultrasound.

The Beckman Laser Institute is an interdisciplinary research center for the development of optical technologies and their use in biology and medicine. Located on the campus of the University of California, Irvine in Irvine, California, an independent nonprofit corporation was created in 1982, under the leadership of Michael W. Berns, and the actual facility opened on June 4, 1986. It is one of a number of institutions focused on translational research, connecting research and medical applications. Researchers at the institute have developed laser techniques for the manipulation of structures within a living cell, and applied them medically in treatment of skin conditions, stroke, and cancer, among others.

<span class="mw-page-title-main">Photoacoustic microscopy</span>

Photoacoustic microscopy is an imaging method based on the photoacoustic effect and is a subset of photoacoustic tomography. Photoacoustic microscopy takes advantage of the local temperature rise that occurs as a result of light absorption in tissue. Using a nanosecond pulsed laser beam, tissues undergo thermoelastic expansion, resulting in the release of a wide-band acoustic wave that can be detected using a high-frequency ultrasound transducer. Since ultrasonic scattering in tissue is weaker than optical scattering, photoacoustic microscopy is capable of achieving high-resolution images at greater depths than conventional microscopy methods. Furthermore, photoacoustic microscopy is especially useful in the field of biomedical imaging due to its scalability. By adjusting the optical and acoustic foci, lateral resolution may be optimized for the desired imaging depth.

Multiple scattering low coherence interferometry (ms/LCI) is an imaging technique that relies on analyzing multiply scattered light in order to capture depth-resolved images from optical scattering media. With current applications primarily in medical imaging, has the advantage of a higher range since forward scattered light attenuates less with depth when compared to the specularly reflected light that is assessed in more conventional imaging methods such as optical coherence tomography. This allows ms/LCI to image through up to 90 mean free scattering paths, compared to roughly 27 scattering MFPs in OCT and 1–2 scattering MFPs in confocal microscopy.

Time-domain diffuse optics or time-resolved functional near-infrared spectroscopy is a branch of functional near-Infrared spectroscopy which deals with light propagation in diffusive media. There are three main approaches to diffuse optics namely continuous wave (CW), frequency domain (FD) and time-domain (TD). Biological tissue in the range of red to near-infrared wavelengths are transparent to light and can be used to probe deep layers of the tissue thus enabling various in vivo applications and clinical trials.

<span class="mw-page-title-main">Christine P. Hendon</span> American electrical engineer and computer scientist

Christine P. Hendon is an electrical engineer and computer scientist and an associate professor in the Department of Electrical Engineering at Columbia University in New York City. Hendon is a pioneer in medical imaging. She develops biomedical optics technologies, using optical coherence tomography and near infrared spectroscopy systems, that enable physicians to perform guided interventional procedures and allow for structure-function dissection of human tissues and organs. Her advances in imaging technologies have led to improved diagnostic abilities and treatments for cardiac arrhythmias as well as breast cancer and preterm birth. She has been recognized for her development of optical imaging catheters for cardiac wall imaging by Forbes 30 under 30, the MIT Technology Review’s 35 Innovators Under 35, and by President Obama with the Presidential Early Career Awards in 2017.

Diffuse correlation spectroscopy (DCS) is a type of medical imaging and optical technique that utilizes near-infrared light to directly and non-invasively measure tissue blood flow. The imaging modality was created by David Boas and Arjun Yodh in 1995.

Spatial Frequency Domain Imaging (SFDI) is a non-invasive optical imaging method that uses spatially modulated light to extract quantitative information about tissue properties. Its large field of view coupled with its quantitative approach to imaging has made it a novel imaging modality, with many use cases in murine pre-clinical trials. Its clinical relevance in human medical practice so far has been limited, but there are currently outstanding clinical trials in their recruitment phase for the use of the technology.

Paola Taroni is an Italian engineer and physicist at the Polytechnic University of Milan. Her research considers the development of optical approaches for cancer diagnoses. She has held various leadership positions

References

  1. 1 2 3 4 Taroni, Paola; Paganoni, Anna Maria; Ieva, Francesca; Pifferi, Antonio; Quarto, Giovanna; Abbate, Francesca; Cassano, Enrico; Cubeddu, Rinaldo (16 January 2017). "Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study". Scientific Reports. 7 (1): 40683. Bibcode:2017NatSR...740683T. doi: 10.1038/srep40683 . PMC   5238417 . PMID   28091596. S2CID   33523292.
  2. 1 2 3 Taroni, Paola; Pifferi, Antonio; Quarto, Giovanna; Spinelli, Lorenzo; Torricelli, Alessandro; Abbate, Francesca; Villa, Anna; Balestreri, Nicola; Menna, Simona; Cassano, Enrico; Cubeddu, Rinaldo (2010). "Noninvasive assessment of breast cancer risk using time-resolved diffuse optical spectroscopy". Journal of Biomedical Optics. 15 (6): 060501–060501–3. Bibcode:2010JBO....15f0501T. doi: 10.1117/1.3506043 . PMID   21198142.
  3. ↑ Quarto, Giovanna; Spinelli, Lorenzo; Pifferi, Antonio; Torricelli, Alessandro; Cubeddu, Rinaldo; Abbate, Francesca; Balestreri, Nicola; Menna, Simona; Cassano, Enrico; Taroni, Paola (18 September 2014). "Estimate of tissue composition in malignant and benign breast lesions by time-domain optical mammography". Biomedical Optics Express. 5 (10): 3684–3698. doi:10.1364/BOE.5.003684. PMC   4206334 . PMID   25360382.
  4. 1 2 Jiang, Shudong; Pogue, Brian W.; Carpenter, Colin M.; Poplack, Steven P.; Wells, Wendy A.; Kogel, Christine A.; Forero, Jorge A.; Muffly, Lori S.; Schwartz, Gary N.; Paulsen, Keith D.; Kaufman, Peter A. (August 2009). "Evaluation of Breast Tumor Response to Neoadjuvant Chemotherapy with Tomographic Diffuse Optical Spectroscopy: Case Studies of Tumor Region-of-Interest Changes". Radiology. 252 (2): 551–560. doi: 10.1148/radiol.2522081202 . PMC   2753781 . PMID   19508985.
  5. 1 2 Cerussi, A.; Hsiang, D.; Shah, N.; Mehta, R.; Durkin, A.; Butler, J.; Tromberg, B. J. (28 February 2007). "Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy". Proceedings of the National Academy of Sciences. 104 (10): 4014–4019. Bibcode:2007PNAS..104.4014C. doi: 10.1073/pnas.0611058104 . PMC   1805697 . PMID   17360469.
  6. 1 2 3 4 Martelli, Fabrizio; Del Bianco, Samuele; Ismaelli, Andrea; Zaccanti, Giovanni (2010). Light propagation through biological tissue and other diffusive media : theory, solutions, and software. SPIE. ISBN   9780819476586.
  7. ↑ Yang, Kai; Kwan, Alexander L. C.; Boone, John M. (15 May 2007). "Computer modeling of the spatial resolution properties of a dedicated breast CT system". Medical Physics. 34 (6Part1): 2059–2069. Bibcode:2007MedPh..34.2059Y. doi:10.1118/1.2737263. PMC   2838398 . PMID   17654909.
  8. ↑ Dobruch-Sobczak, Katarzyna; Piotrzkowska-Wróblewska, Hanna; Klimoda, Ziemowit; Secomski, Wojciech; Karwat, Piotr; Markiewicz-Grodzicka, Ewa; Kolasińska-Ćwikła, Agnieszka; Roszkowska-Purska, Katarzyna; Litniewski, Jerzy (28 June 2019). "Monitoring the response to neoadjuvant chemotherapy in patients with breast cancer using ultrasound scattering coefficient: A preliminary report". Journal of Ultrasonography. 19 (77): 89–97. doi: 10.15557/JoU.2019.0013 . PMC   6750328 . PMID   31355579. S2CID   198295706.
  9. ↑ Marshall, Eliot (18 February 2010). "Brawling Over Mammography". Science. 327 (5968): 936–938. doi:10.1126/science.327.5968.936. PMID   20167758.
  10. 1 2 Grosenick, Dirk; Rinneberg, Herbert; Cubeddu, Rinaldo; Taroni, Paola (11 July 2016). "Review of optical breast imaging and spectroscopy". Journal of Biomedical Optics. 21 (9): 091311. Bibcode:2016JBO....21i1311G. doi: 10.1117/1.JBO.21.9.091311 . hdl: 11311/1013563 . PMID   27403837. S2CID   42000848.
  11. ↑ Kaplan, Stuart S. (December 2001). "Clinical Utility of Bilateral Whole-Breast US in the Evaluation of Women with Dense Breast Tissue". Radiology. 221 (3): 641–649. doi:10.1148/radiol.2213010364. PMID   11719658.
  12. ↑ Hylton, Nola (10 March 2005). "Magnetic Resonance Imaging of the Breast: Opportunities to Improve Breast Cancer Management". Journal of Clinical Oncology. 23 (8): 1678–1684. doi:10.1200/JCO.2005.12.002. PMID   15755976.
  13. ↑ Lord, S.J.; Lei, W.; Craft, P.; Cawson, J.N.; Morris, I.; Walleser, S.; Griffiths, A.; Parker, S.; Houssami, N. (September 2007). "A systematic review of the effectiveness of magnetic resonance imaging (MRI) as an addition to mammography and ultrasound in screening young women at high risk of breast cancer". European Journal of Cancer. 43 (13): 1905–1917. doi:10.1016/j.ejca.2007.06.007. PMID   17681781.
  14. ↑ Bénard, François; Turcotte, Éric (12 May 2005). "Imaging in breast cancer: Single-photon computed tomography and positron-emission tomography". Breast Cancer Research. 7 (4): 153–62. doi: 10.1186/bcr1201 . PMC   1175073 . PMID   15987467.
  15. 1 2 Taroni, Paola (2012). "Diffuse optical imaging and spectroscopy of the breast: A brief outline of history and perspectives". Photochem. Photobiol. Sci. 11 (2): 241–250. doi:10.1039/c1pp05230f. PMID   22094324.
  16. 1 2 Jacques, Steven L (7 June 2013). "Optical properties of biological tissues: a review". Physics in Medicine and Biology. 58 (11): R37–R61. Bibcode:2013PMB....58R..37J. doi:10.1088/0031-9155/58/11/R37. PMID   23666068.
  17. ↑ Wang, Xin; Pogue, Brian W.; Jiang, Shudong; Song, Xiaomei; Paulsen, Keith D.; Kogel, Christine; Poplack, Steven P.; Wells, Wendy A. (2005). "Approximation of Mie scattering parameters in near-infrared tomography of normal breast tissue in vivo". Journal of Biomedical Optics. 10 (5): 051704. Bibcode:2005JBO....10e1704W. doi: 10.1117/1.2098607 . PMID   16292956. S2CID   45813277.
  18. ↑ Taroni, Paola; Quarto, Giovanna; Pifferi, Antonio; Abbate, Francesca; Balestreri, Nicola; Menna, Simona; Cassano, Enrico; Cubeddu, Rinaldo; Batra, Surinder K. (1 June 2015). "Breast Tissue Composition and Its Dependence on Demographic Risk Factors for Breast Cancer: Non-Invasive Assessment by Time Domain Diffuse Optical Spectroscopy". PLOS ONE. 10 (6): e0128941. Bibcode:2015PLoSO..1028941T. doi: 10.1371/journal.pone.0128941 . PMC   4452361 . PMID   26029912.
  19. 1 2 Provenzano, Paolo P; Inman, David R; Eliceiri, Kevin W; Knittel, Justin G; Yan, Long; Rueden, Curtis T; White, John G; Keely, Patricia J (28 April 2008). "Collagen density promotes mammary tumor initiation and progression". BMC Medicine. 6 (1): 11. doi: 10.1186/1741-7015-6-11 . PMC   2386807 . PMID   18442412.
  20. ↑ Taroni, Paola; Pifferi, Antonio; Torricelli, Alessandro; Comelli, Daniela; Cubeddu, Rinaldo (2003). "In vivo absorption and scattering spectroscopy of biological tissues". Photochemical & Photobiological Sciences. 2 (2): 124–129. doi: 10.1039/B209651J . PMID   12664972.
  21. ↑ Durduran, T.; Choe, R.; Culver, J. P.; Zubkov, L.; Holboke, M. J.; Giammarco, J.; Chance, B.; Yodh, A. G. (21 August 2002). "Bulk optical properties of healthy female breast tissue". Physics in Medicine and Biology. 47 (16): 2847–2861. Bibcode:2002PMB....47.2847D. doi:10.1088/0031-9155/47/16/302. PMID   12222850.
  22. ↑ Matcher, Stephen J. (25 October 2016). "Signal Quantification and Localization in Tissue Near-Infrared Spectroscopy". Handbook of Optical Biomedical Diagnostics, Second Edition, Volume 1: Light-Tissue Interaction. pp. 585–687. doi:10.1117/3.2219603.ch9. ISBN   9781628419092.
  23. 1 2 Jiang, Huabei; Iftimia, Nicusor V.; Xu, Yong; Eggert, Julia A.; Fajardo, Laurie L.; Klove, Karen L. (February 2002). "Near-Infrared Optical Imaging of the Breast with Model-Based Reconstruction". Academic Radiology. 9 (2): 186–194. doi:10.1016/s1076-6332(03)80169-1. PMID   11918371.
  24. ↑ Xu, Ronald X; Young, Donn C; Mao, Jimmy J; Povoski, Stephen P (18 December 2007). "A prospective pilot clinical trial evaluating the utility of a dynamic near-infrared imaging device for characterizing suspicious breast lesions". Breast Cancer Research. 9 (6): R88. doi: 10.1186/bcr1837 . PMC   2246191 . PMID   18088411. S2CID   3323560.
  25. 1 2 3 Ferocino, Edoardo; Martinenghi, Edoardo; Dalla Mora, Alberto; Pifferi, Antonio; Cubeddu, Rinaldo; Taroni, Paola (23 January 2018). "High throughput detection chain for time domain optical mammography". Biomedical Optics Express. 9 (2): 755–770. doi:10.1364/BOE.9.000755. PMC   5854076 . PMID   29552410.
  26. ↑ Enfield, Louise C.; Gibson, Adam P.; Everdell, Nicholas L.; Delpy, David T.; Schweiger, Martin; Arridge, Simon R.; Richardson, Caroline; Keshtgar, Mohammad; Douek, Michael; Hebden, Jeremy C. (18 May 2007). "Three-dimensional time-resolved optical mammography of the uncompressed breast". Applied Optics. 46 (17): 3628–38. Bibcode:2007ApOpt..46.3628E. doi:10.1364/AO.46.003628. PMID   17514325.
  27. 1 2 Bevilacqua, Frédéric; Berger, Andrew J.; Cerussi, Albert E.; Jakubowski, Dorota; Tromberg, Bruce J. (1 December 2000). "Broadband absorption spectroscopy in turbid media by combined frequency-domain and steady-state methods". Applied Optics. 39 (34): 6498–6907. Bibcode:2000ApOpt..39.6498B. doi:10.1364/AO.39.006498. PMID   18354663.
  28. 1 2 Becker, Wolfgang; Bergmann, Axel; Biscotti, Giovanni Luca; Rueck, Angelika (2004). "Advanced time-correlated single photon counting techniques for spectroscopy and imaging in biomedical systems". In Neev, Joseph; Schaffer, Christopher B; Ostendorf, Andreas (eds.). Commercial and Biomedical Applications of Ultrafast Lasers IV. Vol. 5340. International Society for Optics and Photonics. pp. 104–112. doi:10.1117/12.529143. S2CID   17283884.
  29. 1 2 Chance, B.; Cooper, C. E.; Delpy, D. T.; Reynolds, E. O. R.; Tromberg, Bruce J.; Coquoz, Olivier; Fishkin, Joshua B.; Pham, Tuan; Anderson, Eric R.; Butler, John; Cahn, Mitchell; Gross, Jeffrey D.; Venugopalan, Vasan; Pham, David (29 June 1997). "Non–invasive measurements of breast tissue optical properties using frequency–domain photon migration". Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences. 352 (1354): 661–668. Bibcode:1997RSPTB.352..661T. doi:10.1098/rstb.1997.0047. PMC   1691955 . PMID   9232853.
  30. ↑ Grosenick, Dirk; Wabnitz, Heidrun; Rinneberg, Herbert H.; Moesta, K. Thomas; Schlag, Peter M. (1 May 1999). "Development of a time-domain optical mammograph and first in vivo applications". Applied Optics. 38 (13): 2927–43. Bibcode:1999ApOpt..38.2927G. doi:10.1364/AO.38.002927. PMID   18319875.
  31. ↑ Moesta, KT; Fantini, S; Jess, H; Totkas, S; Franceschini, MA; Kaschke, M; Schlag, PM (April 1998). "Contrast features of breast cancer in frequency-domain laser scanning mammography". Journal of Biomedical Optics. 3 (2): 129–36. Bibcode:1998JBO.....3..129M. doi: 10.1117/1.429869 . PMID   23015049.
  32. ↑ Simick, Michelle K.; Jong, Roberta; Wilson, Brian; Lilge, Lothar (2004). "Non-ionizing near-infrared radiation transillumination spectroscopy for breast tissue density and assessment of breast cancer risk". Journal of Biomedical Optics. 9 (4): 794–803. Bibcode:2004JBO.....9..794S. doi: 10.1117/1.1758269 . PMID   15250768.
  33. ↑ Blackmore, Kristina M.; Knight, Julia A.; Walter, Jane; Lilge, Lothar; Ho, Yuan-Soon (15 January 2015). "The Association between Breast Tissue Optical Content and Mammographic Density in Pre- and Post-Menopausal Women". PLOS ONE. 10 (1): e0115851. Bibcode:2015PLoSO..1015851B. doi: 10.1371/journal.pone.0115851 . PMC   4295879 . PMID   25590139. S2CID   15113061.
  34. 1 2 Leff, Daniel Richard; Warren, Oliver J.; Enfield, Louise C.; Gibson, Adam; Athanasiou, Thanos; Patten, Darren K.; Hebden, Jem; Yang, Guang Zhong; Darzi, Ara (28 April 2007). "Diffuse optical imaging of the healthy and diseased breast: A systematic review". Breast Cancer Research and Treatment. 108 (1): 9–22. doi:10.1007/s10549-007-9582-z. PMID   17468951. S2CID   10705543.
  35. 1 2 Grosenick, Dirk; Moesta, K Thomas; Möller, Michael; Mucke, Jörg; Wabnitz, Heidrun; Gebauer, Bernd; Stroszczynski, Christian; Wassermann, Bernhard; Schlag, Peter M; Rinneberg, Herbert (7 June 2005). "Time-domain scanning optical mammography: I. Recording and assessment of mammograms of 154 patients". Physics in Medicine and Biology. 50 (11): 2429–2449. Bibcode:2005PMB....50.2429G. doi:10.1088/0031-9155/50/11/001. PMID   15901947.
  36. ↑ Choe, Regine; Konecky, Soren D.; Corlu, Alper; Lee, Kijoon; Durduran, Turgut; Busch, David R.; Pathak, Saurav; Czerniecki, Brian J.; Tchou, Julia; Fraker, Douglas L.; DeMichele, Angela; Chance, Britton; Arridge, Simon R.; Schweiger, Martin; Culver, Joseph P.; Schnall, Mitchell D.; Putt, Mary E.; Rosen, Mark A.; Yodh, Arjun G. (2009). "Differentiation of benign and malignant breast tumors by in-vivo three-dimensional parallel-plate diffuse optical tomography". Journal of Biomedical Optics. 14 (2): 024020. Bibcode:2009JBO....14b4020C. doi:10.1117/1.3103325. PMC   2782703 . PMID   19405750.
  37. ↑ Zhu, Quing; Cronin, Edward B.; Currier, Allen A.; Vine, Hugh S.; Huang, Minming; Chen, NanGuang; Xu, Chen (October 2005). "Benign versus Malignant Breast Masses: Optical Differentiation with US-guided Optical Imaging Reconstruction". Radiology. 237 (1): 57–66. doi:10.1148/radiol.2371041236. PMC   1533766 . PMID   16183924.
  38. ↑ Wang, Shushu; Zhang, Yi; Yang, Xinhua; Fan, Linjun; Qi, Xiaowei; Chen, Qingqiu; Jiang, Jun (2013). "Shrink pattern of breast cancer after neoadjuvant chemotherapy and its correlation with clinical pathological factors". World Journal of Surgical Oncology. 11 (1): 166. doi: 10.1186/1477-7819-11-166 . PMC   3728037 . PMID   23883300. S2CID   6217814.
  39. ↑ Soliman, H.; Gunasekara, A.; Rycroft, M.; Zubovits, J.; Dent, R.; Spayne, J.; Yaffe, M. J.; Czarnota, G. J. (20 April 2010). "Functional Imaging Using Diffuse Optical Spectroscopy of Neoadjuvant Chemotherapy Response in Women with Locally Advanced Breast Cancer". Clinical Cancer Research. 16 (9): 2605–2614. doi: 10.1158/1078-0432.CCR-09-1510 . PMID   20406836. S2CID   1275542.
  40. ↑ Roblyer, D.; Ueda, S.; Cerussi, A.; Tanamai, W.; Durkin, A.; Mehta, R.; Hsiang, D.; Butler, J. A.; McLaren, C.; Chen, W.-P.; Tromberg, B. (18 August 2011). "Optical imaging of breast cancer oxyhemoglobin flare correlates with neoadjuvant chemotherapy response one day after starting treatment". Proceedings of the National Academy of Sciences. 108 (35): 14626–14631. Bibcode:2011PNAS..10814626R. doi: 10.1073/pnas.1013103108 . PMC   3167535 . PMID   21852577.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.