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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Technol Cancer Res Treat. Author manuscript; available in PMC Aug 7, 2006.
Published in final edited form as:
PMCID: PMC1533770
Optical Tomography with Ultrasound Localization: Initial Clinical Results and Technical Challenges
Quing Zhu, Ph.D.
Bioengineering Program Electrical and Computer Engineering Department University of Connecticut 371 Fairfield Rd, U2157 Storrs, CT 06269, USA
Corresponding Author: Quing Zhu, Ph.D. Email: zhu/at/
Optical tomography with ultrasound localization utilizes co-registered ultrasound lesion structure information to guide optical imaging reconstruction. A hand-held probe consisting of a commercial ultrasound transducer and near infrared optical imaging sensors was used to simultaneously acquire ultrasound images and optical measurements. A dual-mesh scheme was used to map the ultrasound-visible lesions to finer-grid lesion regions and coarser-grid background regions for optical imaging reconstruction. As a result, optical imaging reconstruction was well-conditioned for inverse mapping of lesion hemoglobin concentration and blood oxygen saturation. Initial clinical results have shown that early stage invasive cancers may be distinguished by a two-fold greater total hemoglobin concentration compared with fibroadenomas and other benign lesions. Initial results of advanced cancers have shown that the hemoglobin distribution is highly distorted and heterogeneous and the distorted distributions correlate with histological microvessel density counts and could be used to assess chemotherapy response.
Optical imaging of large organs is feasible in a spectrum window that exists within tissues in the 700–900 nm near infrared (NIR) region, in which photon transport is dominated by scattering rather than absorption. In fact, light transillumination (also called diaphanography) was introduced 70 years ago as a diagnostic tool to locate and identify breast cancers (1). Unfortunately, transillumination did not achieve sufficient sensitivity and specificity to be used clinically, primarily due to intensive light scattering (2, 3). During the last decade, developments in light propagation theory and modeling as well as advancement of instrumentation in optical sources and detectors, have enabled researchers to apply tomographic principles to localize and quantify light absorption and scattering in the breast (420). If a single optical wavelength is used, optical absorption related to tumor hemoglobin concentration and other normal blood vessels can be measured. If two or more optical wavelengths are used, both oxygenated hemoglobin and deoxygenated hemoglobin concentrations can be measured simultaneously. Tumor hemoglobin concentration is directly related to tumor angiogenesis (4, 12), a key factor required for tumor growth and metastasis (21). In addition, tumor metabolism and tumor hypoxia, important indicators of tumor response to various forms of therapy (22), can be probed by NIR diffused light as well (11, 19, 20).
However, optical tomography alone suffers from low spatial resolution and location uncertainty because the problem of intense light scattering in tissue remains. The tomographic inversion approaches are, in general, underdetermined and ill-posed (23). The image reconstruction results depend on many parameters, such as the system signal-to-noise ratio, measurement geometry, regularization schemes used in inversion, et cetera. More recently, many research groups have investigated the use of a priori lesion structure information provided by other imaging modalities, such as ultrasound (US) (2432), MRI (8, 11, 3334), and X-ray mammography (35) to improve the localization of optical tomography. A flexible light guide using optical fibers makes optical imaging compatible with many other imaging modalities and allows for simultaneous imaging under identical geometric conditions. Furthermore, the lesion structure information provided by other modalities can be used to assist optical imaging reconstruction and therefore to reduce the location uncertainty and to improve the quantification accuracy of light.
US is frequently used as an adjunct tool to mammography in differentiating simple cysts from solid lesions and also plays an important role in guiding interventional procedures such as needle aspiration, core-needle biopsy, and prebiopsy needle localization (3637). However, ultrasound features that occur in solid breast masses are not reliable enough to determine whether invasive evaluation is needed or non-invasive follow-up is indicated (36). The lack of specificity of ultrasound has prompted radiologists to recommend biopsies on most solid nodules (38).
We have developed a novel hybrid optical tomography and US technique to improve optical reconstruction (2728) and ultrasound specificity (3032). Our unique approach employs a commercial ultrasound transducer and NIR optical imaging sensors mounted on a hand-held probe as shown in Figure 1. The co-registered ultrasound is used for lesion localization and optical sensors are used for imaging tumor angiogenesis and tumor hypoxia. With the US localization, the entire imaging volume is thus segmented into lesion regions of a finer imaging grid and non-lesion regions of a coarse grid. As a result, the total number of imaging voxels with unknown optical properties is significantly reduced, and the inversion is well determined. In addition, since the lesion absorption coefficient is higher than that of background tissue, in general, the total absorption of the lesion over a smaller voxel is on the same scale as the total absorption of the background over a bigger voxel. Thus, our dual-mesh scheme further conditions the inversion by reconstructing total absorption distribution instead of absorption per se. The absorption distribution is obtained by dividing the total distribution with different voxel sizes in lesion and background regions, respectively. The dual-mesh algorithm has been tested in phantoms (39) and in a group of patients (3032, 39). Initial clinical results have shown that early stage invasive cancers may be distinguished by a two-fold greater total hemoglobin concentration compared to fibroadenomas and other benign lesions (30, 32). Preliminary results of advanced cancers have shown that the hemoglobin distribution is highly distorted and heterogeneous. The distorted distributions correlate with histological microvessel density counts and may be used to assess chemotherapy response (31).
Figure 1
Figure 1
(a) Prototype of our hand-held combined probe and a frequency domain NIR optical imager. (b) Sensor distribution of the combined probe. The diameter of the combined probe is 10 cm. Smaller circles are optical source fibers and big circles are detector (more ...)
Our unique approach uses ultrasound localization to overcome the poor localization achievable with diffused light and thus significantly improves the sensitivity and specificity of optical tomography. Our unique approach may have significant clinical applications for improving breast cancer diagnosis and assessing treatment response of advanced breast cancers and estimating treatment efficacy.
Co-registration of Optical Tomography and Ultrasound
Photon density waves launched from a source and detected by a detector travel a “banana” path, which can be visualized by Monte Carlo simulation shown in Figure 2. In all figures, the horizontal axis is the propagation depth in centimeters and the vertical axis is the lateral dimension in centimeters. Source and detector positions are marked as S and D. The source-detector separations shown in (a), (b) and (c) are 2.8 cm, 4.1 cm, and 5.5 cm, respectively. At each source location 10,000,000 photons were generated. Each photon propagated in the medium, being absorbed or scattered. The color scale is the normalized absorption intensity. The optical properties of the medium used in simulation were absorption coefficient 0.03 cm−1 and reduced scattering coefficient 6.0 cm−1, which were representative values of breast tissue. As one can see, the photon density waves probe the medium over a large region. The high sensitivity region in both spatial and depth dimensions depends on the source-detector separation. For a detector located further from the source shown in Part (c), the photon waves propagated wider and deeper can be detected. With many source and detector pairs of different separations shown in Fig. 1(b), the photon density waves can probe the medium underneath and be detected with high sensitivity. Ultrasound is a coherent imaging modality and the sound waves propagate into the medium along a straight path and reflected waves from tissue underneath are used for forming images. Therefore, sensors of two modalities probe the medium underneath although the sensor locations are offset on the probe. Thus, the two modalities have unique synergy not only in providing complementary structure and function information of the lesion but also in optimization of sensor locations.
Figure 2
Figure 2
Monte Carlo simulation demonstrating photon propagation path launched from a source and detected by a detector. (a) source-detector separation is 2.8 cm. (b) source-detector separation is 4.1 cm. (c) source-detector separation is 5.5 cm.
Prototype Frequency Domain Optical System
The technical aspects of our NIR imager have been described in detail previously (28). Briefly, the imager consisted of 12 pairs of dual wavelength (780nm and 830nm) laser diodes, which were used as light sources, and their outputs were coupled to the probe through optical fibers. The source output was switched between the two wavelengths. On the receiving side, 8 photomultiplier (PMT) tubes were used to detect diffusely scattered light from the tissue and 8 optical fibers were used to couple detected light to the PMTs. Recently, an additional wavelength (660nm) was added to the system, which allows estimation of tumor oxygenation saturation. The outputs of laser diodes were amplitude modulated at 140 MHz and the detector outputs were demodulated to 20KHz. Eight detection signals and one reference were amplified, sampled and acquired into a PC simultaneously. The entire data acquisition took about 3 to 4 seconds, which was fast enough for acquiring data from patients.
Dual-mesh Optical Reconstruction Algorithm
The details of our dual-mesh optical imaging reconstruction algorithm have been described previously (27, 39). Briefly, the optical tomographic reconstruction takes advantages of US localization of lesions and segments the imaging volume into a finer grid in US identified lesion region and a coarser grid in non-lesion regions (see Fig. 3). To account for possible larger angiogenesis extension of ultrasound-identified lesions, we have used a much larger region of interest (ROI) for finer grid lesion mapping. Therefore, the exact lesion shape is not important and an elliptical ROI is used in imaging reconstruction. In all images, 0.5 cm × 0.5 cm × 0.5 cm imaging grid was used for lesion region and 1.5cm × 1.5cm × 1 cm was used for background region. A modified Born approximation is used to relate the scattered field Usd(rsi,rdi,ω) measured at the optical source (s) and detector (d) pair i to light absorption variations Δμaλ(r′) of wavelength λ in each volume element of two regions within the sample. The matrix form of image reconstruction is given by
Figure 3
Figure 3
Illustration of the dual-mesh optical imaging reconstruction with the assistance of ultrasound lesion mapping. The entire imaging volume is segmented into lesion (L) and background regions (B). The finer imaging grid is used for the lesion region and (more ...)
equation M1
where WL and WB are weight matrices for lesion and background regions, respectively;
equation M2
equation M3
are total absorption distributions of lesion and background regions, respectively. The weight matrices are calculated based on the background absorption equation M4 and reduced scattering equation M5 measurements obtained from the normal contralateral breast. Instead of reconstructing Δμaλ distribution directly, as is done in the standard Born approximation, the total absorption distribution M is reconstructed and the total is divided by different voxel sizes of lesion and background tissue to obtain Δμaλ distribution. By choosing a finer grid for lesion and a coarse grid for background tissue, we can maintain the total number of voxels with unknown optical absorption on the same scale of the total measurements. As a result, the inverse problem is less underdetermined. In addition, since the lesion absorption coefficient is higher than that of background tissue, in general, the total absorption of the lesion over a smaller voxel is of the same scale as the total absorption of the background over a bigger voxel. Therefore, the matrix [ML, MB] is appropriately scaled for inversion. In addition, we have incorporated a scaling factor to correct depth dependence of the weight matrix W and large phantom absorbers can be imaged uniformly in propagation direction or depth (39). The reconstruction is formulated as a least square problem and the unknown distribution M is iteratively calculated using the standard conjugate gradient method. In general, only three iterations are needed for the algorithm to converge to a stable solution.
Since the major chromophores are deoxygenated (deoxyHb) and oxygenated (oxyHb) hemoglobin in the wavelength range studied, we can estimate deoxyHb and oxyHb concentrations at each imaging voxel by inverting the following equations voxel by voxel as:
equation M6
equation M7
where μaλ1 (r′) and μaλ2 (r′) are absorption coefficients obtained at imaging voxel r, where wavelengths λ1 and λ2 correspond to 780 nm and 830 nm in our system, respectively. epsilon s are extinction coefficients given in Ref. (40). The total hemoglobin concentration totalHb(r′) = deoxyHb(r′) + oxyHb(r′) and oxygenation saturation
equation M8
can be calculated as:
equation M9
equation M10
where Δ = epsilonHbλ1 epsilonHb02λ2epsilonHb02λ1 epsilonHbλ2. Among the available wave-lengths in our system, the wavelength pair of 780nm and 830nm is better for calculating total hemoglobin concentration, and the wavelength pair of 660nm and 830 nm is better for estimating hemoglobin oxygenation saturation. These wavelength pairs were used in computing total hemoglobin concentration and oxygen saturation distributions. To quantify the spatial extension of the angiogenesis distribution, we have measured the full width at half maximum (FWHM) in x and y spatial dimensions and computed the geometric mean, referred to as FWHM. The maximum lesion total hemoglobin concentration was measured and the background total hemoglobin concentration was computed outside the finer-grid imaging region. The average lesion total hemoglobin concentration was measured within FWHM.
Initial Clinical Results
Pilot clinical trials using the combined approach have been conducted at University of Connecticut Health Center and Hartford Hospital. To date, more than 100 patients have been enrolled and published results can be found in Refs. (30, 32). An example obtained from an early stage invasive ductal carcinoma is shown in Figure 4. The ultrasound showed a nodular mass with internal echoes and the lesion was considered suspicious (see Fig. 4a). The estimated lesion diameter measured from ultrasound image was 8 mm.
Figure 4
Figure 4
(a) shows a gray scale ultrasound image of a non-palpable lesion of a 55-year-old woman. The lesion measuring 8 mm in diameter pointed by the arrow was located at the 4 o’clock position of the right breast. Ultrasound showed a nodular mass with (more ...)
An ultrasound guided core needle biopsy revealed intraductal and infiltrating ductal carcinoma (nuclear grade II, histological grade III). The optical absorption maps at both wavelengths are shown in Figure 4b and c, respectively. In both (b) and (c), the first slice is 0.7 cm deep into the breast tissue from the skin surface and the last slice is closer to the chest wall. The spacing of the slices is 0.5 cm. The horizontal and vertical axes of each slice are spatial x and y dimensions of 9 cm in size. The lesion is well resolved in slice #5 and shows much larger spatial extension at 830 nm than that at 780 nm. The measured maximum total hemoglobin concentration for lesion is 122 μ moles, the average measured within FWHM is 91 μ moles and the measured average background hemoglobin concentration is 14 μ moles.
The initial patient population obtained from both University of Connecticut Health Center and Hartford Hospital consisted of malignant cases (n=10), fibroadenomas (n=32), fibrocystic changes (n=17), fibrosis (n=9), other benign solid lesions (n=8), complex cysts (n=21), and combined fibroadenoma and fibrocystic changes with neoplasia/carcinoma in situ and hyperplasia (n=3) (30, 32). The mean maximum total hemoglobin concentration and the mean average hemoglobin values were calculated. No significant difference was found among benign groups but a more than twofold higher total hemoglobin concentration was found in malignant (mean maximum 121 μ mol/liter (±23.8), mean average 88 μ mol/liter (±21.7) measured within FWHM) versus benign groups (mean maximum 57 μ mol/liter (±23.7), mean average 40 μ mol/liter (±16.6) measured within FWHM). Both maximum and average of total hemoglobin level were statistically significantly higher in the malignant group than in the benign group (P<0.001).
The limited cases of combined fibroadenoma and fibrocystic changes with neoplasia/carcinoma in situ and hyperplasia (n=3) suggest that optical tomography may not be sensitive to high-risk hyperplasia or early stage mixed benign changes and non-invasive neoplasia/carcinoma in situ because tumor neovascularization has not been developed. This result is consistent with magnetic resonance imaging (MRI) findings on the low detection sensitivity of carcinoma in situ. However, our cases are limited and optical tomography may be useful in identifying more aggressive type of carcinoma in situ that may have early neovasculature changes.
In addition to distinguishing benign from early stage malignant tumors, optical tomography with US localization has additional benefits to map tumor vascularity and tumor hypoxia when studying larger tumors already diagnosed by US. These indices can be followed before and during theraputic interventions. It has been shown that tumor hypoxia is related to the growth rate and chemotheraputic responsiveness of tumors (41). The ability to demonstrate and follow these parameters before and during therapy non-invasively could prove invaluable in choosing tailored treatments especially in the era of new drugs targeting angiogenesis.
An example was obtained from a patient with a diffusely swollen breast (31). No discrete mass was palpable. An incisional biopsy from the lower inner quadrant showed a poorly differentiated infiltrating ductal carcinoma. Positive emission tomography (PET) imaging obtained before her chemotherapy treatment revealed a diffusely involved breast with nodal and epidural metastasis (31). She was given Adriamycin Cytoxan followed by Texotere during her neoadjuvant chemotherapy. We identified an upper quadrant mass from ultrasound and monitored total hemoglobin concentration and oxygen saturation during her treatment. Figure 5a, b, and c are ultrasound images acquired at the beginning, after four cycles and eight cycles of chemotherapy; d, e, and f are corresponding total hemoglobin changes, and g, h, and i are corresponding oxygen saturation maps. The maximum hemoglobin concentration had significantly decreased from 255.3 to 147.5 to 76.9 in units of μ mol/liter as did the spatial extension from the beginning to the end of the treatment. High oxygen saturation was noted in the tumor initially near the chest-wall region (slice 6 and 7 of Fig. 5g) and fell to deoxygenated levels at the time of the second scan (Fig. 5h and i). The initial incisional biopsy was in a region where there was no demonstrable mass on ultrasound so the initial microvessel count of total 190 microvessels per 10 consecutive fields under 200 magnifications is not from the same region imaged by optical tomography shown in Figure 5d. Microvessel counts of surgical samples obtained from anterior and posterior region of the imaged area were 111 and 68 which correlate with higher and lower hemoglobin images seen in slice 4 and 6 of Figure 5f. PET imaging showed a complete response to chemotherapy (31). Upon completion of neoadjuvant chemotherapy, the patient underwent left modified radical mastectomy. Residual tumor was noted diffusely infiltrating all the quadrants of the breast as well as beneath the nipple. However, there was marked reduction in tumor cellularity to 5% throughout the fibrotic bed of the residual tumor. Currently, more chemotherapy patients have been enrolled to this study and results will be reported in the near future.
Figure 5
Figure 5
Corresponding US images acquired at the beginning (a), after 4 cycles (b) and 8 cycles (c) of chemotherapy. (d), (e), and (f) are corresponding NIR hemoglobin concentrations, while (g), (h), and (i) are oxygen saturation maps. Slice 1 is the x-y image (more ...)
Photon Density Wave Distortion Introduced by Chest Wall and/or Heterogeneous Small Dense Breasts
Since conventional ultrasound is used in pulse echo reflection geometry, it is desirable to acquire optical measurements with the same geometry. Compared with transmission geometry or ring geometry where the light sources and detectors are deployed on a pair of parallel plates or a ring, the reflection geometry has the advantage of probing reduced breast tissue thickness because patients are scanned in the supine position. Consequently, lesions closer to the chest-wall can be imaged. However, when the chest-wall is within 1.0 cm to 2.0 cm depth, the optical measurements obtained from distant source-detector pairs are distorted. The distortion is caused by the underlying heterogeneous chest wall consisting of muscles and bones. The distorted distant measurements are quite complex. In some patients, the measured distant amplitude profiles consist of many random points, while in others, the amplitude profiles bend considerabllly from expected linear curves. In general, when the amplitude values are low, the phase profiles behave like random variables. As a result, measurements beyond a certain distance have to be removed before imaging. Since the depth of chest-wall and average breast tissue absorption and scattering coefficients vary from patient to patient, it is difficult to predict the cutoff source-detector distance. As a consequence, the data processing and image reconstruction have to be done off-line for each individual patient by examining the data and removing distant measurements. This simple filtering approach can largely eliminate the image distortion caused by the noisy distant source-detector pairs (42).
Currently, we are working on curve fitting procedures and finite-element-based imaging reconstruction to estimate the second layer optical properties and therefore to set up a suitable boundary condition at breast tissue and chest-wall layer for forward model. We are also working on layered Green function based imaging reconstruction to incorporate the curved amplitude and phase profiles, which have the influence of the chest-wall layer.
Optical imaging of small dense breast is a challenge since measured diffusive waves are highly distorted due to heterogeneity of the tissue. The poor probe-tissue contact also produces large perturbations at certain source-detector pair positions, which will introduce image artifacts. These artifacts, in general, can be identified because they often appear at edges of the imaging probe.
Since real-time ultrasound can provide lesion and chest-wall depths, a suitable probe size can be selected on-site to provide more useful optical measurements with appropriate source-detector distribution. In addition, a smaller probe can improve probe-tissue contact for small dense breasts. Future systems should include multiple probes of different sizes for best imaging results.
Imaging Shallow Lesions
In our study, a black probe was used to house optical source and detector fibers, therefore, an absorption boundary condition is a good approximation for optical measurements. However, for lesions located less than 0.5 cm to 0.7 cm deep from the skin surface, the light detection sensitivity is low and reconstructed absorption maps are very noisy even with ultrasound localization. This is related to the “banana” path of photons traveling from a source to a detector with the absorbing boundary condition. Closely located source-detector pairs can improve the light illumination of shallow targets and therefore detection sensitivity. However, a typical dynamic range of optical detectors in general will cause saturation for the near source-detector pairs, which have to be eliminated before imaging. Unlike in the case of an absorbing boundary in a semi-infinite geometry, the path of photons propagating from a source to a detector under a reflection boundary condition is similar to one half of the electrical field distribution induced by an electrical dipole (43). This implies that a high perturbation region exists in the area near the boundary, which is ideal for probing a shallow target with higher sensitivity. We have demonstrated with phantoms that the combined probe with a reflection boundary is suitable for detecting shallow targets with high sensitivity (44). Future prototype systems should also include probes of certain reflection coefficients to improve sensitivity of shallow lesion imaging.
Simultaneous Imaging of Light Absorption and Scattering Distributions
In the reported clinical studies (3032), we have used bulk absorption and reduced scattering coefficients obtained from the curve-fitting results of normal breasts to compute the weight matrices. The dual-mesh algorithm based on the analytical solution using the modified Born approximation was used to reconstruct the absorption variations of both the lesion and the background. Since scattering changes also contribute to the measured perturbations, we have attempted to reconstruct both absorption and reduced scattering changes simultaneously, but have not been successful with the dual-mesh algorithm based on the modified Born approximation. The main reasons are: I) the weight matrices of absorption and reduced scattering coefficients are not on the same order; and II) more unknowns of scattering variations are introduced in addition to unknown absorption variations.
Recently, we have improved simultaneously reconstruction of both absorption and reduced scattering changes using the dual-mesh algorithm implemented in a numerical finite element method (FEM) (45). FEM provides a more accurate weight matrix of the forward model but is rather computationally intensive. Preliminary results (45) have indicated that the reconstructed maximum absorption coefficients of benign lesions obtained from the dual-mesh FEM method were 6 to 40% lower than the corresponding results obtained from the dual-mesh modified Born approximation; while the maximum absorption coefficients of malignant cancers were either higher (8–36%) or lower (2–18%) than the corresponding results obtained from the dual-mesh Born approximation. As a result, the absorption and the total hemoglobin contrasts between malignant and benign lesions have been improved. The improvement was due to more accurate background tissue scattering calculation, which could be attributed to the absorption distribution if absorption alone was reconstructed. However, our sample size is too small to draw a conclusion and more cases are being computed. The current limitation is the intensive computation time needed for the forward matrix calculation of dual-mesh FEM and we are working on implementing the commercial FEM codes into specialized C codes to speed up the computation.
Frequency Domain Instrumentsand Wavelength Selection
We have constructed two frequency domain optical data acquisition systems. One consists of 12 dual-wavelength light sources and 8 parallel photomultiplier tube (PMT) detectors as shown in Figure 1 (28), and the other consists of 9 tri-wavelength light sources and 10 parallel avalanche photodiode (APD) detectors (46). The light modulation frequency is 140 MHz. The advantage of using PMT detector is its high detection sensitivity, and the disadvantage is its smaller dynamic range. As a result, two levels of light excitation have to be used to accommodate the need of light power for near source-detector pairs and distant source-detector pairs. APD detector has the advantage of a large dynamic range and is compact in size. However, the detector sensitivity fluctuates with the environmental temperature change. As a result, a cooling system is needed to maintain a constant temperature, which makes the system less desirable for clinical use. In addition, the sensitivity of APD detectors is much lower than PMT detectors at large source-detector separations, which makes an APD system undesirable for probing deep and large lesions.
The wavelength pairs of 780nm and 830nm and 660nmm and 830nm were used to calculate the total hemoglobin concentration and the hemoglobin oxygen saturation, respectively. In principle, absorption data from all three wavelengths can be used to compute the total hemoglobin concentration and the oxygen saturation. However, for the three wavelengths used in our system, the total hemoglobin concentration at voxel r′ can be estimated as Hbt (r′) = 0.0029 μa660(r′) + 0.1835 μa780(r′) + 0.2838 μa830(r′), and the contribution of the 660nm absorption data to the Hbt estimation is very small. Therefore, we have used the wavelength pair of 780nm and 830nm to compute Hbt as given in Equation [4]. The oxygen saturation Y(r′)% can be estimated as
equation M11
if all three wavelengths are used; while
equation M12
if the wavelength pair of 660nm and 830 nm is used. The resulting oxygen saturation distributions of using all three wavelengths and the wavelength pair of 660nm and 830nm are essentially the same. Therefore, we have used the wavelength pair of 660nm and 830nm to compute the Y(r′)% as given in Equation [5]. However, if the wavelength pair of 780nm and 830nm is used, the Y(r′)%, which depends on the ratio of
equation M13
(see Equation [5]), may exceed 100% or be less than zero in the background regions due to the close extinction coefficients of these two wavelengths and the larger percentage errors in background absorption estimation. When the wavelength pair of 660nm and 830nm is used, the larger difference of extinction coefficients of these two wavelengths can minimize this problem. However, our recent clinical data indicate that the 660nm wavelength is subject to high background tissue scattering and is not optimal for probing breast tissues. Currently, we are modifying our source system by incorporating two wavelengths in the neighborhood of 700nm and 750 nm.
Our initial results on breast lesion diagnosis and cancer treatment monitoring are encouraging. We anticipate a larger, prospective clinical trial to validate these results. In addition, the trends of hemoglobin concentration and oxygenation changes observed by this technology will be validated with histological microvessel density counts and hypoxia markers, respectively.
Our initial clinical results obtained from a small number of chemotherapy patients have indicated that the oxygenation saturation patterns changed considerably from heterogeneous and/or slightly oxygenated status (before treatment) to heterogeneous and/or deoxygenated status (during treatment) to either deoxygenated or normal oxygenation status (at the end of the treatment). There is only a limited amount of information in the literature with regard to what happens to hypoxia during a course of chemotherapy. Using an invasive needle electrode technique, Taghian et al. (47) reported that paclitaxel when administered first before doxorubicin decreased the mean interstitial fluid pressure by 36% and improved the tumor partial pressure of oxygen (pO2) by almost 100% in a group of breast cancer patients. In contrast, doxorubicin when administered before paclitaxel did not have a significant effect on either parameter. This difference was independent of the tumor size or response measured by ultrasound. There is also a limited amount of information in the literature with regard to hypoxia measured by either invasive electrode techniques or other non-invasive imaging techniques during radiation therapy (48). In patients with head and neck cancer, a decrease in median pO2 and an increase in hypoxic proportion (HP5) were observed at the end of radiation therapy (49). In patients with cervical cancer, mean pO2 increased and HP5 decreased in most but not all of the patients (50). However, even those with improvement still had substantial HP5 readings after treatment. A trial with positron emission tomography imaging demonstrated a decrease in hypoxia (51), and another trial in cervical cancer using radiation plus biologic radiation modifiers indicated that an increase in oxygenation during treatment correlated with an improved outcome (52). More information is needed as to the changes in hypoxia during chemotherapy of breast cancers.
US is frequently used as an adjunct tool to mammography in differentiating simple cysts from solid lesions and also plays an important role in guiding interventional procedures such as needle biopsy. Our technique has a potential role in characterizing functional changes of US-visible lesions and therefore in reducing benign biopsies. Since US-visible lesions are needed to map out target and background regions for optical imaging reconstruction, our technique is limited to this patient population and is not suitable for screening purposes.
Our technique may be used to monitor cancer recurrence and distinguish it from post-operative scar tissues. Currently, diagnostic mammography and careful physical examination are used in the follow-up surveillance of patients who have undergone breast-conservation therapy (5355). However, mammography is less sensitive in the treated breast than in the untreated breast due to surgery and radiation-induced changes in the parenchymal pattern (56). The sensitivity of mammography in this population ranges from 55% to 68% in various studies (5355). Therefore, techniques that can monitor cancer recurrence and distinguish it from post-operative scar tissues are needed, and our technique is a good candidate for this important task.
Many people have collaborated in this research project. Drs. Scott H. Kurtzman, Susan Tannenbaum, Bipin Jagjivan, Poornima Hegde, Mark Kane, Kristin Zarfos of University of Connecticut Health Center and Drs. Edward B. Cronin, Allen A Currier, Hugh A Vine of Hartford Hospital are greatly acknowledged for their contributions in clinical studies. Many people at the Optical and Ultrasound Imaging Laboratory of the ECE Department of the University of Connecticut have contributed to theory and modeling, instrumentation and clinical data acquisition. Drs. NanGuang Chen, Minming Huang, Baohong Yuan, and Daqing Piao are acknowledged for their help on instrumentation, modeling, and software developments. Graduate students Chen Xu, Skikui Yan, and Puyun Guo are acknowledged for their help on instrumentation and data acquisition. My sincere thanks to Professors Britton Chance, Arjun Yodh of University of Pennsylvania who helped me get started in this project. My special thank to Professor Rajeev Bansal of the ECE Department of the University of Connecticut for his encouragement and support in the past years. Ellen Oliver at the Cancer Center of University of Connecticut Health Center, and Roxanne Rotondaro of Hartford Hospital are thanked for their efforts on patient scheduling and recruiting.
The following funding agents are thanked for their funding support: the National Institute of Health (R01EB002136), the Donaghue Foundation, the ARMYMedical Research and Materiel Command (DAMD17-00-1-0217) and the State of Connecticut.
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