Patent Application
20070167836
Techniques capable of evaluating human disease in a safe, minimally invasive and reproducible way are of importance for clinical disease diagnosis, risk assessment, therapeutic decision-making, and evaluating the effects of therapy, and for investigations of disease pathogenesis and pathophysiology. Among the clinical methods available to diagnose tissue lesions, pathologic examination of cytology preparations, biopsies and surgical specimens is the present day standard.
Pathologists have traditionally based their diagnoses primarily on tissue morphology. However, as the field of diagnostic pathology has evolved, assessment of tissue morphology has become more sophisticated, including such techniques as morphometry (or quantitative image analysis) and ploidy analysis. Pathologic diagnosis has also begun to move from complete dependence on morphology to inclusion of a host of adjunct techniques that provide biochemical and molecular information as well. This is particularly true for the diagnosis of cancer, where routine diagnosis begins with morphology but usually also includes such molecular diagnostic techniques such as immunohistochemistry and in situ hybridization that identify specific molecular signatures.
This molecular information is not only of use for diagnosis, but is also of use for risk assessment and therapeutic decision-making, for example, in qualifying patients for molecular therapies, such as gene therapy or therapy with monoclonal antibodies directed against specific molecular targets. This molecular information has also greatly advanced the understanding of the pathogenesis and pathophysiology of many diseases, particularly cancer. But this evolution toward a focus on molecular events is not unique to the diagnosis of cancer. Recent molecular studies are also beginning to shed light on the pathogenesis and pathophysiology of cardiovascular disease, not only atherosclerosis but other disease (such as the cardiomyopathies) as well.
Diseases are more reliably identified by biochemical signatures than purely morphological markers. The present invention relates to the use of Raman spectroscopy in combination with other spectroscopic methods to provide biochemical and morphologic information and to further provide molecular information reflective of the metabolic state of tissue. This combination of biochemical, morphologic and metabolic information is used as the basis of more robust diagnostic methods. These types of molecular signature can be used for disease diagnosis, the disease progression and response to therapy.
Thus, in a preferred embodiment Raman and fluorescence can be used in combination to measure tissue in vivo using a probe or can be used to measure excised tissue samples. In a further embodiment Raman and reflected light can be used in combination for measurements on a human or animal body with a probe or on biological samples. Additionally, Raman, fluorescence and reflectance measurements can be made using a probe for in vivo or ex vivo measurements. A common light delivery and light collection probe can be used in preferred embodiments of the invention.
The combination of modalities in the modal spectroscopy (TMS) has several advantages over the single modalities alone. First, fluorescence spectroscopy provides information about tissue metabolites, such and NADH, that are not provided by Raman spectroscopy. Second, TMS uses diffuse reflectavi spectroscopy (DRS) to overcome distortion of fluorescence signatures by the effects of tissue absorption and scattering, and extract the intrinsic fluorescence signature (IFS). Third, in addition to its value in extracting IFS, DRS provides critical information about the tissue absorbers and scatterers themselves. Finally, while DRS provides information about tissue components responsible for diffusive scattering, light scattering spectroscopy (LSS) provides information about tissue components responsible for single backscattering. The combination of techniques into TMS, therefore, provides a wealth of information about tissue fluorophores, absorbers and scatterers, which creates a much more complete biochemical, morphologic and metabolic tissue profile.
TMS and Raman methods have been applied to specific diseases based on the strengths of each spectroscopic modality for detecting the primary biochemical or morphologic hallmarks of that disease. For example, cancer is a characterized by rapid cellular proliferation that is reflected in increased cellular metabolism. TMS, which provides IFS and DRS information about key cellular metabolites such as NADH and oxy- and deoxy-hemoglobin is, thus, a natural choice of modality for the diagnosis of cancer. TMS also provides information about key morphologic cellular changes, such as the nuclear enlargement and pleomorphism (variation in size and shape), that are characteristic of cancer. On the other hand, vulnerable atherosclerotic plaque is the end result of an inflammatory process that leads to thinning and rupture of the fibrous cap, leading to the release of thrombogenic necrotic lipid core material into the blood stream. Atherosclerotic plaques are also subject to calcific mineralization of the fibrous cap and necrotic core. Most lipids and calcium salts are strong Raman scatterers and, thus, Raman spectroscopy is a natural choice of modality for the diagnosis of vulnerable atherosclerotic plaque.
The combination of spectroscopic modalities in multimodal spectroscopy (MMS) can provide information not provided by each modality. The whole (MMS) is also greater than the sum of the various individual modalities, because the biochemical and morphologic information provided is complementary—that is—the information provided by one technique often answers a question raised by the results of another. For example, for vulnerable atherosclerotic plaque, Raman spectroscopy provides information about the aggregate spectral contribution of foam cells and necrotic core, but raises questions about their individual contributions. Both DRS and light scattering answer those questions by providing specific information about the contribution of foam cells. So by combining the modalities in MMS one can decipher the separate contributions of both foam cells and necrotic core.
Measurements show that for vulnerable plaque, in some cases, two or more modalities are needed to fully characterize the contribution of a single tissue component. For example, as discussed above, oxy- and deoxy-hemoglobin are metabolites that may be key to the spectroscopic diagnosis of cancer. Hemoglobin is a strong tissue absorber and, therefore, it is a potential cause of distortion of tissue fluorescence signatures. This problem has been addressed in part by the use of TMS to derive undistorted IFS signatures. However, measurements in surgical breast biopsies have shown that in extremely bloody operative fields it is not be possible to account for all the absorbance effects of hemoglobin and achieve accurate diagnosis using TMS. On the other hand, hemoglobin is a weak Raman scatterer at NIR excitation wavelengths, and excellent model fits can be achieved for spectra acquired in bloody fields/tissues.
The combination of TMS and Raman spectroscopy in MMS provides a more complete and complementary biochemical, morphologic and metabolic tissue profiles than either TMS or Raman spectroscopy alone resulting in better diagnostic accuracy. Another key advantage in combining both techniques is the potential for depth sensing. TMS and Raman spectroscopy can use different excitation wavelengths, and therefore sample different tissue volumes because of wavelength-dependent differences in absorption and scattering. A Raman source preferably emits in a range of 750 nm to 1000 nm while the fluorescence source can employ one or more laser sources or a filtered white light source. Reflectance measurements preferably use a broadband source such as xenon flash lamp.
This difference in sampling volume can be exploited to provide information about the depth (or thickness) or certain tissue structures of layers. For example, the thickness of the fibrous cap is used to the diagnosis of vulnerable atherosclerotic plaque. The fibrous cap is composed largely of collagen. IFS and Raman spectroscopy both provide information about the contribution of collagen to tissue spectra. Comparison of the results from these two techniques, which use different excitation wavelengths and sample different tissue volumes, may provide information about the thickness of the fibrous cap. DRS and Raman spectroscopy both provide information about the contribution of deoxy-hemoglobin to the tissue spectra. Comparison of the results of these two techniques, which again use different excitation wavelengths and sample different tissue volumes, can provide depth-sensitive information useful in mapping cancers and pre-cancers of breast tissue.
Multimodal spectroscopy (MMS) is a system for spectral diagnosis and efficacy of combining spectroscopic results from TMS and Raman spectroscopy to provide better diagnostic detail and a more comprehensive picture of the biochemical, morphological and metabolic changes that occur in diseased tissues. The probe used in such measurements can be an endoscope or a small diameter probe for insertion through an endoscope channel or a small diameter catheter for insertion in the arterial system, for example.
The Raman methods for the diagnosis of breast cancer are based on a linear combination model similar to that used for peripheral arteries, that yields fit coefficients for epithelial cell nuclei and cell cytoplasm, fat cells, stromal collagen fibers, β-carotene, calcium oxalate and hydroxyapatite and cholesterol-like deposits (corresponding to tissue necrosis). The diagnostic procedure makes use of fit coefficients collagen and fat, two components of the tumor stroma.
Breast cancer, like most cancers, is characterized by abnormal cell proliferation and differentiation as well as increased cell metabolism. Fluorescence, reflectance and LSS provide information about cell metabolism and tissue scatterers such as cell nuclei that is not provided by Raman spectroscopy. Therefore, by combining Raman spectroscopy with fluorescence, reflectance and/or LSS, a method for the diagnosis of breast cancer incorporates contributions from both the malignant epithelial cells and the stroma.
a-2b are basis spectra;
a-3c are scatter plots of an MMS system;
a-4c are plots of an MMS system;
a-6c show spectra and fits for MMS modes;
FIGS. 11B-D are Raman, reflectance and fluorescence data of an artery;
An MMS system is generally illustrated in
The sampled tissue volume for Raman spectroscopy is 1 mm3. Using the combined biochemical and morphologic spectral model, the data are fit to a linear combination of Raman basis spectra for eight breast tissue components: cell cytoplasm, cell nucleus, stromal collagen fibers, fat cells, β-carotene, collagen, calcium hydroxyapatite, calcium oxalate dehydrate, and cholesterol-like lipid deposits (foci of necrosis). The data were then analyzed prospectively using the fit coefficients for stromal collagen (collagen) and fat cells (Fat) in our Raman algorithm for breast cancer diagnosis. A scatter plot and decision lines for the Raman diagnostic algorithm are shown in
IFS were extracted from the combined fluorescence and DRS. The IFS spectra were analyzed using multivariate curve resolution (MCR) with non-negativity constraints, a standard chemometric method, to extract two spectral components at each excitation wavelength. The resulting MCR-generated spectral components at 340 nm are shown in
For diffusive scattering (μs′), wavelength dependence of the form Aλ−B is used. Two absorbers, oxyhemoglobin and β-carotene, were used to model the extracted absorption coefficient μa. Therefore, DRS provided, among other parameters, the amplitude of the scattering coefficient, A, and the concentration of oxyhemoglobin.
The TMS diagnostic method used logistic regression and leave-one-out cross validation, and the analysis was performed in sequential fashion. Scatter plots and decision lines for each step of the diagnostic method are shown in
The measurements were obtained using TMS and Raman spectroscopic techniques independently can also be obtained using a combined diagnostic procedure. In developing the MMS algorithm, only parameters that were diagnostic in one of the three individual spectroscopic modalities were used. The diagnostic parameters from TMS are scattering parameter A, and the fit coefficient for oxyhemoglobin, β-carotene, and NADH and collagen by IFS at 340 nm excitation wavelength. The diagnostic Raman parameters are the fit coefficients for fat and collagen. Like the TMS diagnostic procedure, this algorithm incorporates contributions from both the epithelial cells (NADH) and stroma (collagen).
The MMS diagnostic method was developed using logistic regression and leave-one-out cross validation. As with TMS, the analysis is performed in sequential fashion.
Table 4 shows a detailed comparison of the diagnostic performance of all three methods, Raman, TMS and MMS, with MMS providing the best sensitivity and specificity, as well as overall accuracy. By introducing a parameter from the Raman model to the first step a greater number of correctly diagnosed normal tissues.
The results indicate that MMS, a combination of DRS, IFS, and Raman spectroscopy provides better results than those obtained from each technique alone. This can result from the combined MMS diagnostic algorithm combines spectral parameters derived from both epithelial cells and stroma and (taken together) have a larger sample volume.
As in breast cancer, the development of atherosclerosis is governed by subtle chemical and morphological changes in the arterial wall, manifesting themselves in the development of a plaque that causes luminal obstruction. Many of these changes are the result of metabolically active inflammatory and smooth muscle cells, such as foam cells, that degrade LDL and release it into the necrotic core in the form of ceroid and other LDL degradation byproducts.
The preferred method for the diagnosis of atherosclerosis are based on a linear combination model that yields fit coefficients for 10 morphological components of artery wall, including collagen fibers (CF), elastic lamina (EL), smooth muscle cells (SMC), adventitial adipocytes (AA), cholesterol crystals (CC), β-carotene crystals (β-CC), foam cells/necrotic core (FC/NC) and calcium mineralizations (CM). A preferred algorithm was developed for classification of lesions as non-atherosclerotic, non-calcified plaque and calcified plaque. This diagnostic algorithm was based on combined fit coefficients for cholesterol crystals+foam cells/necrotic core (the latter two having indistinguishable Raman basis spectra) and the fit coefficient for calcium mineralizations.
A preferred embodiment relates to a procedure for measuring vulnerable plaque. These are most often plaques with a thin fibrous cap overlying a large necrotic lipid core, and may have other features of vulnerability including foam cells and other inflammatory cells, intraplaque hemorrhage or thrombosis. A second Raman algorithm capable of diagnosing vulnerable plaque with about the same sensitivity and specificity as a previous algorithm for plaque classification (˜85-95%). This second algorithm for the diagnosis of vulnerable plaque makes use of the fit coefficients of 5 artery morphological components: the combined fit coefficients for foam cells+necrotic core and the fit coefficient for calcifications, as in the previous algorithm, plus the fit coefficients for collagen and hemoglobin. A preferred algorithm for the diagnosis of vulnerable plaque involves using spectral parameters that distinguish between metabolically active foam cells and the non-metabolically active necrotic core.
Fluorescence, reflectance and LSS provide information about cell metabolism and tissue scatterers such as foam cells, the cytoplasm of which is filled with a foam-like aggregate of lipid-filled lysosomal vesicles where the metabolism and degradation of LDL takes place. Therefore, by combining Raman spectroscopy with fluorescence, reflectance and optionally LSS, an algorithm for the diagnosis of vulnerable plaque incorporates contributions from metabolically active, potential scatterers like foam cells as well as non-metabolically active plaque constituents like the necrotic core. But, MMS has a further advantage for the diagnosis of vulnerable plaque, and that is the ability to provide depth information about key biochemical and morphologic structures like the fibrous cap, that too undergoes degradation, this time, by matrix metalloproteinase that renders it more prone to rupture.
In vitro measurements of MMS for the diagnosis of vulnerable plaque using 17 frozen archival tissues from carotid endarterectomies have been performed.
TMS spectra were collected using the FastEEM instrument and Raman using the clinical Raman system, with the associated probes. Care was taken in placing the Raman probe at the same site on the tissue as the FastEEM probe. Once the spectra were acquired, the exact spot of probe placement was marked with colloidal ink for registration with histopathology. The artery specimens were then fixed and submitted for routine pathology examination, which was performed by a cardiovascular pathologist blinded to the spectroscopy results. The histopathology examination of the lesions included an assessment of a number of histologic features of vulnerable plaque, including thickness of the fibrous cap, size of the necrotic core, superficial foam cells, intraplaque hemorrhage and ulceration. The histopathology results are summarized in Table 5. A vulnerable plaque index (VPI) was assigned to each specimen. Of the 17 lesions, 4 exhibited VPI scores ≧10 and were classified as vulnerable plaques.
MMS spectral analysis for artery was similar to that for the breast. Again, OLS is used to fit the Raman data using the morphological model. The DRS spectra were fit using the diffusion theory model. Modeling of the DRS spectra yielded, among other parameters, scattering coefficient A and hemoglobin concentration. IFS were analyzed using MCR with non-negativity constraints to find two spectral components at 308 nm and 340 nm. The IFS data was fit using ordinary least squares (OLS) using the two MCR components as the model. The Raman basis spectra, DRS extinctions and IFS MCR components are shown in
IF = infimal fibroplasias, ATS = atherosclerotic, ATM = atheromatous, FS = fibrotic-sclerotic, C = calcified.
a-6c shows the spectroscopic data and model fits for three different artery lesions, an intimal fibroplasia (a), a non-vulnerable plaque (b) and a vulnerable plaque (c). All of the MMS spectra could be fit very well using the previously described models.
Four spectral parameters were correlated with the histopathologic features of vulnerable plaque: DRS scattering parameter A and hemoglobin concentration; an IFS parameter ρ=C308/C340, where C308 and C340 are the contributions of the more blue-shifted MCR basis spectra; and the Raman parameter Σ=CC+FC/NC, where CC and FC/NC are the relative contributions in the Raman spectra of cholesterol crystals and foam cells+necrotic core, respectively. The diagnostic potential as it relates to assessing plaque vulnerability for each of the spectral parameters will be discussed separately in the next paragraphs.
As described earlier, intraplaque hemorrhage is a marker of plaque vulnerability. Histopathology indicates that the lesion in specimen #14 is the site of acute intraplaque hemorrhage (Table 5); whereas the other lesions not hemorrhagic.
Superficial foam cells are important in assessing plaque vulnerability as they are often present in the fibrous cap near plaque erosions and ruptures, and are a likely source of MMPs that degrade the fibrous cap and lead to plaque rupture.
As discussed above, an important feature of vulnerable plaque is the presence of a thin fibrous cap. A cap thickness of less than 65 μm is an established criterion of vulnerability. IFS spectra at 308 and 340 nm excitation wavelengths were obtained to parameterize fibrous cap thickness. Two MCR spectral components to be associated with collagen and/or elastin, structural proteins that characterize the upper layers of both normal artery (normal intima) and atherosclerotic lesions (fibrous cap). Comparing the MCR spectra to the known spectral of those fluorophores, the red-shifted spectrum resembled elastin while the blue-shifted spectrum is similar to collagen (
The key spectroscopic parameters obtained from IFS, DRS and Raman spectroscopies are displayed together in Table 6 for all 17 specimens. This method uses yes/no results based on the threshold values rather than numerical values. Each column represents a spectroscopic marker of a histologic feature of vulnerable plaque: Hb, indicative of intraplaque hemorrhage; scattering parameter A, indicative of foam cells close to the surface; ρ, indicative of fibrous cap thickness; and Σ, indicative of the build up of necrotic core material. Note that 3 of the 4 vulnerable plaques can be identified by detecting a thin cap (ρ>2) together with another parameter such as A or Σ.
The ability of MMS to provide depth-sensitive information is more relevant to measurements of atherosclerosis than those of breast cancer because of the layered structure of the arterial wall. Define the optical penetration depth as the depth at which the power of light incident on a tissue sample falls to 1/e of its incident value. Generally the optical properties of aorta indicates penetration depths of about 90, 150 and 1200 microns for light of wavelengths 308, 340 and 830 nm, respectively. The penetration depths at different IFS wavelengths were measured by incrementally stacking 20 μm thick sections of aortic media. The FastEEM probe tip was placed in contact with the tissue and the transmitted power was measured as a function of tissue thickness. The penetration depths at 308 and 340 nm were measured as 85 and 105 μm, respectively. These values correspond with prior results especially noting the variability of human tissue. They also agree with estimates obtained from the formula δ=1/μeff=1/√{square root over (3μa(μa+μ′s))}, using the known scattering and absorption properties of arterial tissue at different wavelengths;
Note that in the single-ended geometry of our artery measurements (i.e. the probe both delivers and collects light at the same position) the sampling depth, which can be defined as 1/δs=1/δex+1/δem, where δex and δem are the penetration depths of the excitation and emission light, respectively. The sampling depth characterizes the attenuation of both the excitation and the emitted light, which can be at a longer wavelength, as in the case of fluorescence or Raman scattering. Thus the sampling depths of IFS308 and IFS340 are much smaller: 50 and 60 μm, respectively, taking into account the longer wavelengths of the emitted light. A previous measurement established a sampling depth of 470 μm for Raman spectroscopy of artery using 830 nm excitation. In the following, use 50, 60 and 470 um as the sampling depths at 308, 340 and 830 nm, respectively. Note that the definition of penetration as the length where light is attenuated to 1/e of its original value is somewhat arbitrary and that, optionally the device can sample deeper than those values. Similarly, different wavelength regions of the diffuse reflectance spectra sample tissue at different depths. In general, short wavelength IFS (308 nm, in particular) provides information about the top layer (intima/fibrous cap), longer wavelength IFS samples somewhat deeper, and Raman spectroscopy has the greatest sampling depth.
Multimodal spectroscopy (MMS) is a spectral diagnosis technology that combines spectroscopic results from TMS and Raman spectroscopy to provide more accurate disease diagnosis and a more comprehensive picture of biochemical, morphological and metabolic state of the tissue as it relates to disease pathogenesis and pathophysiology. FIGS. 11B-D illustrate in vivo Raman (
The results have demonstrated that combining information from Raman, fluorescence and reflectance spectroscopies provides better diagnostic accuracy than that provided by any one of the spectroscopic techniques independently, and that differences in sampling volumes can be used to advantage for depth sensing.
The present invention relates spectroscopic diagnosis of a wide range of diseases including oral, esophageal, colon and cervical cancer, as well as the diagnosis of vulnerable atherosclerotic plaque and breast cancer. A preferred embodiment spectroscopically extracts biochemical, morphologic and metabolic information related to features of plaque vulnerability or predictive of breast cancer. More than rendering precise disease diagnoses, the system extracts accurate biochemical, morphologic and metabolic information about tissue composition. The system stores IFS morphological basis spectra using microspectroscopy, and performs ex vivo and in vivo tissue measurements using DRS, IFS, and Raman spectroscopic techniques.
Combined MMS spectral data provides insight into depth dependent morphological features of breast cancer (collagen) and vulnerable plaque (fibrous cap thickness and superficiality of foam cells). These measurements simultaneously collect and analyze Raman, DRS and IFS spectra from the same spot without registration errors using an MMS probe.
Quantitative information about biochemical and morphological tissue components are provided from DRS and Raman spectra using basis spectra in our linear combination model. IFS can also provide quantitative information. Meaningful data modeling can be obtained using fluorescence basis spectra measured from biochemical and morphologic tissues structures measured in situ uses the IFS technique to remove the artifacts of tissue absorption and scattering. This can be useful as basis spectra obtained by microspectroscopy of thin (<6 μm) tissue sections or cell cultures can have little or no scattering or absorption effects, and thus may not model uncorrected raw fluorescence spectra as well as IFS spectra.
To build representative libraries of basis spectra, 50-100 spectra were acquired each from a variety of tissue and cellular sources. Tissue handling and preparation methods can lead to spectral distortions. For example, increased absorption has been observed in frozen-thawed tissue, possibly the result of red blood cell lysis, with a concomitant decrease in tissue fluorescence. These changes are less significant in artery wall than in epithelial tissues. Several steps are taken to minimize these artifacts in the collection of IFS basis spectra. First, all IFS basis spectra are collected from freshly excised tissues within 30-60 minutes of excision.
In the case of artery, basis spectra are obtained initially from cryostat sections of fresh tissue that has been immediately snap frozen in liquid nitrogen. Basis spectra are obtained on these sections within minutes of preparation. The passively thawed frozen sections maintained in a humid chamber to prevent drying.
Optionally, basis spectra obtained either from fresh tissue sections (or short term organ cultures) maintained in a balanced electrolyte solution such as Hanks Balanced Salt solution at neutral pH. Under these conditions it is known that tissue remains viable for at least 90 minutes, with minimal changes in fluorescence. Basis spectra can also be obtained from live human cell cultures, where appropriate, to provide a relatively pure population of cells. Cell cultures from which basis spectra may be obtained for artery studies include primary cultures of normal human endothelial and smooth muscle cells and various cell culture models of foam cells, such as LDL fed human alveolar macrophages. Cell cultures from which basis spectra may be obtained for the breast studies include primary cell cultures of normal breast epithelial cells, myoepithelial cells and fibroblasts and human breast cancer cell lines.
The basis spectra can be collected using a confocal microscope adapted for TMS microspectroscopy. A confocal fluorescence system uses excitation light generated by the FastEEM instrument. The excitation light from the FastEEM is delivered from a 200 um fiber, focused to 100 um aperture and collimated. The collimated light is delivered down to the objective using a neutral density beam splitter (90/10) and collected light from the thin tissue is be focused to a confocal pinhole. This light is delivered to the FastEEM spectrograph and CCD via optical fibers. The microscope stage is programmed to FastEEM scan in the features of interest. A bright field image of the specimen is obtained and used for registration between pathology and spectroscopy. The FastEEM software is synchronized for operation between the microscope and FastEEM excitation source and CCD camera.
With the library of biochemical and morphological basis spectra morphological basis spectra (of such structures as foam cells in atherosclerosis and epithelial cell nuclei and cytoplasm in breast cancer) are fit with the same linear combination method used previously for Raman spectroscopy, using biochemical basis spectra to determine their precise chemical composition and identify the fluorophores characteristic of each structure. The basis spectra are also fit to ex vivo IFS tissue spectra, and quantitative information about the presence of fluorophores (tryptophan, collagen, elastin, NADH, FAD, β-carotene) and the morphologic structures they comprise, is extracted. Using this quantitative spectral information obtained from all three spectral modalities, an automated method to characterize morphological components associated with disease state, including their depth profiles, is provided. Quantization of the biochemical and morphologic composition of the tissues is incorporated into algorithms for the diagnosis of vulnerable plaque and breast cancer. Similar basis spectra libraries, spectral models and diagnostic algorithms are used for cancers of the oral cavity, colon, bladder and cervix.
Using at least 200 spectra each from ex vivo fresh arterial (carotid and femoral) and breast tissues from at least 40 different patients spectra are acquired using the MMS instrument using the integrated MMS probe. The location of the spectroscopic site is established by attaching a metal sleeve to the probe that can make a shallow incision around the site. After removing the probe, the location can be marked with an ink dot. The sample can be fixed in formalin and submitted for histopathological examination, by a pathologist. Both spectral analysis and quantitative image analysis (QIA) of the samples is performed in parallel, using the same tissue site for both measurements.
To evaluate the depth sensing capabilities of different fluorescence excitation wavelengths, Monte Carlo models are employed to simulate light propagation within tissue. Monte Carlo models can have simple layered structures with physiological dimensions and optical properties to simulate light propagation in the normal arterial or breast tissue. Optical properties can be measured with an integrating sphere. The spatial distribution of morphological features associated with vulnerable plaque or breast cancer are estimated using QIA software. This information, along with the IFS basis spectra, are used as input into fluorescence Monte Carlo models to evaluate the ability of different excitation wavelengths to probe morphological structures such as foam cells and necrotic core.
DRS provides information about the presence of Hb, indicative of thrombus or intraplaque hemorrhage, and the amplitude of the scattering coefficient A is related to the presence of foam cells and their depth within the artery wall (superficiality). IFS provides information about fibrous cap thickness through the ratio of MCR components at 340 to 308 nm excitation. Raman spectroscopy also provides information related to the presence of foam cells or necrotic core. Thus MMS modalities provide important diagnostic parameters related to collagen (Raman and IFS)., diffusive scattering (DRS) and NADH (IFS) that are of use for breast cancer diagnosis.
There are additional correlations between IFS and DRS-measured parameters and key morphological features of breast cancer and vulnerable plaque. For example, detection of β-carotene by DRS can be a strong marker of tissue necrosis and extracellular lipid pools. Tryptophan is another fluorophore that plays an important diagnostic role in both atherosclerosis and breast cancer.
Fit coefficients from MMS morphological models can be used to predict disease/tissue parameters using logistic regression. These fit coefficients can be used as parameters for an algorithm for distinguishing vulnerable and non-vulnerable plaque and the full spectrum of breast lesions, both benign and malignant.
Spectroscopic instrumentation for MMS can comprise a combined instrument in which a clinical Raman system and a FastEEM are linked together for use with a single combined spectral probe. Alternatively a smaller integrated clinical instrument for a variety of clinical studies involving atherosclerosis, breast cancer Barrett's esophagus and oral cancer. A number of specialized MMS spectral probes can be used for front-view, sing-viewing and circumferential imaging modes. See for example U.S. application Ser. No. 10/407,923 filed on Apr. 4, 2003, the entire contents of which is incorporated herein by reference. The measurement for breast cancer and atherosclerosis can be obtained using two independent instruments and separate spectral probes. Due to the differences in these probes, which determines the light collection efficiency, it is preferable to use a single probe. This will eliminate registration uncertainties between Raman and DRS/IFS data and ensure that illumination areas will be the same. This instrument provides the full, range of fluorescence excitation wavelengths and can include a front-looking MMS spectral probe.
A combined instrument can use a FastEEM (See U.S. Pat. No. 6,912,412 incorporated herein by reference) and Raman system combined under a single LabView software program that synchronizes the operation of both units. This instrument collects a set of IFS spectra and a DRS spectrum in 0.2 seconds, followed by collection of a Raman spectrum in 1 second, for example. Excitation light from FastEEM and Raman sources is coupled into a single tapered fiber with 0.22 NA. The tapered fiber has a 600 μm core diameter at one end allowing up to four excitation inputs and can be drawn down to a single 200 μm core for use at the distal end of the probe. For ease of fabrication, MMS probes can be assembled with 15 collection fibers surrounding the central excitation fiber. Alternatively a reduced diameter device has 9 fibers around a single fiber in the probe. The 15 fibers are split at the proximal end so that 10 of the 15 fibers are coupled into the Raman spectrograph while the remaining 5 fibers are coupled to the FastEEM spectrograph. The collection fibers have a core diameter of 200 μm with 0.26 NA. High NA Anhydroguide G fibers can be used in the Raman instrument. They are well suited for near IR wavelengths but have a 40-50% transmission loss in the 300-400 nm region. The Superguide G fibers used in FastEEM have negligible transmission losses in the same UV wavelength range, but low NA. In spite of transmission losses in Anhydroguide G fibers, the spectral quality is not significantly reduced, due to the strength of the fluorescence and reflectance signals at these wavelengths. In one embodiment of an MMS probe, both Superguide and Anhydroguide fibers are used in a single probe to provide a baseline performance level with the optimum transmission properties.
Of the three spectral signals (Raman, DRS and fluorescence), Raman is typically the weakest. Thus, a spectral probe capable of collecting high-quality Raman spectra should easily collect fluorescence and reflectance spectra as well. The spectral probe design for the combined instrument is single-ring front-viewing Raman probe.
Placement of filters and ball lens, can be the same as the Raman probe, but the filter characteristics has tighter specifications when used with all three spectral modalities.
In
The wavelength-dependent sampling volume and depth of penetration of the probe can be determined with tissue phantoms and/or thin sections of tissue. The diameter of the excitation spot illuminating the tissue can be approximately equal for all wavelengths; however, the tissue penetration depth is different for different excitation wavelengths. Because the spot diameter and penetration depth are important for diagnostic algorithms and they are measured and checked with Zemax optical design models and Monte Carlo models.
A compact portable MMS instrument that incorporates all three spectroscopic modalities (DRS, IFS and Raman) is shown in
To accommodate the requirements for using all three spectroscopic modalities, spectra are collected over the wavelength range 300-1000 nm. Excitation light for each modality is delivered sequentially to the sample, and fluorescence, DRS and Raman spectra are acquired. This is followed by real-time analysis of the data, during which IFS spectra are derived from the fluorescence and DRS spectra. The information from the different modalities provides depth-sensitive, complementary chemical and morphological information on tissue sites.
The measurements include IFS spectra excited at 308 and 340 nm, DRS and Raman spectra. The combined TMS/Raman instrument is used for FastEEM fluorescence excitation wavelengths to determine the diagnostic value of the various excitation wavelengths. The most appropriate two or three fluorescence wavelengths can be used in the integrated system.
Data acquisition, analysis and tissue characterization preferably occurs in 5 sec or less. Triggering of the light sources is accomplished by means of a National Instruments Timer/Counter card and a Princeton Instruments CCD controller, respectively. The sequence of operation can be controlled by computer 205 as follows: (1) Initialize CCD for spectral acquisition; (2) open shutter for the CCD and activate insertion of appropriate collection filter; (3) trigger light source (LED, diode laser or flashlamp); (4) acquire spectrum; (5) close shutter; (6) read/transfer data and store in computer 206 and display at 208. The time for acquiring all spectra depends upon the excitation power, thus the exposure time can be adjusted to accommodate signal levels.
Separate excitation and reflectance sources can be used for each spectroscopic modality. Laser emitting diodes 214 (˜1 mW) provide fluorescence excitation light at 308 and 340 nm, a 60W xenon flashlamp generates a continuous spectrum from 300-1000 nm for DRS, and a laser diode 212 at 830 nm (500 mW) will generate the Raman excitation light. A flashlamp 218 can be used in the FastEEM, and the 830 nm laser diode in the Raman system. Each of these four light sources can be focused onto separate 200 μm core diameter optical fibers, and then coupled together into a 600-to-200 μm tapered optical fiber The output can be connected to the combined spectral probe via an SMA connector. The system enables fluorescence excitation wavelengths to be added and/or changed.
UV diode sources can be used compact light sources in the 300-340 nm range available. UV light emitting diodes at wavelengths as short as 275 nm or UV LEDs in the 305-360 nm wavelength range can be used. Present 308 nm LEDs produce 1-2 mW of CW power in a bandwidth of 10-15 nm, emitted from a 0.1 mm aperture over a 30° angular range. Because of this large bandwidth, a filter can be used to restrict the light to a 2 nm bandwidth. Thus, under present conditions, ˜1 μJ of 308 nm light can be delivered via 200 micron core, 0.26 NA, fused silica optical fiber in 10 ms, resulting in the acquisition of high SNR fluorescence spectra. Characteristics of 340 nm LEDs are even more favorable.
Each of the spectral probe collection fibers, typically nine, (fifteen in one design) are coupled to an SMA connector mounted on the front panel of the instrument. Long (wavelength) pass filters 220 mounted on a programmable wheel driven by a stepper motor are positioned in the return beam path to prevent Raman and fluorescence excitation light scattered from the tissue from entering the spectrograph. Since the reflectance measurements cover a broad range (300-1000nm), the acquired spectra contain second order contributions. Taking two reflectance measurements, one with no filter and another with a long pass 500 nm cutoff filter (mounted on the wheel), eliminates these contributions. The unfiltered reflectance provides spectral information below 600 nm, and the filtered reflectance provides information above 500 nm. The Princeton Instruments Spec10:400BR CCD camera of the Raman system can be coupled to an Acton Research Spectra Pro 150 spectrograph with a grating blazed at 500 nm and 200 grooves/mm. Alternatively two separate gratings or dispersive elements can deliver different light modalities onto separate regions of the detector.
This combination of fluorescence, reflectance and Raman capabilities in one instrument provides a compact clinical instrument. With a single spectrograph/CCD combination, a spectral range of 300-1000 nm is covered, compared to 155 nm in our existing Raman system. This causes an increase in spectral dispersion by a factor of 4.5, and a reduction in system resolution from 10 to 45 cm−1. However, if the spectral resolution degrades the accuracy of the Raman fit coefficients significantly such that diagnostic accuracy is also degraded. A two spectrograph/CCD system can also be used with one spectrograph/CCD combination is dedicated to Raman while the other to fluorescence/reflectance. A high-speed mirror will direct the collected light to appropriate spectrograph/CCD combination.
A further embodiment of a system 250 is shown in
The detection of vulnerable plaques, margin assessment in breast cancer and transdermal needle biopsies can be performed using front-viewing, side-viewing or circumferential imaging probes.
Using the integrated MMS system, spectra are collected from several of these margins prior to excision and thus only tissue that would normally be excised during the procedure will be removed. During each procedure, the distal end of the sterilized MMS front-viewing probe is placed in gentle contact with the marginal breast tissue in the surgical cavity under direct visualization while spectra are acquired. All room and surgical lights will be turned off during the measurements. The spectrally examined marginal tissue will then excised by the surgeon and submitted for conventional pathological examination.
Under local anesthesia following a manual incision of the skin, a cannula having a diameter 0.5 to 2 cm is advanced toward the suspect lesion guided under ultrasound or stereotactic mammography. The central channel of the needle contains a circular blade that is used to cut the biopsy and will provide access for the MMS probe. Once positioned in the lesion, a MMS side-viewing probe is inserted in the central channel and acquire a series of spectra as the probe is withdrawn along the opening. The probe is withdrawn and cutting blade replaced and a biopsy is acquired. Biopsies are performed over a 360 degree around the axis of the needle without it being withdrawn with typically twelve cores of tissue are removed using 11 to 14 gauge needles. The excised biopsy specimens are submitted for specimen. radiography to document the presence of calcification and then conventional pathology.
A digital photograph of the lesion and probe placement is recorded. Precise registration between the probe location and biopsy site is ensured by immediately scoring a circular region of tissue slightly larger than diameter of the probe with a 1.5 mm punch biopsy. A larger punch biopsy (˜-3.5 mm) is used to remove a larger tissue specimen for histopathology and slide preparation. The smaller mark is located later when viewing the slide under the microscope.
While the present invention has been described here in conjunction with a preferred embodiment, a person with ordinary skill in the art, after reading the foregoing specification, can effect changes, substitutions of equivalents and other types of alterations to the system and method that are set forth herein. Each embodiment described above can also have included or incorporated therewith such variations as disclosed in regard to any or all of the other embodiments. Thus, it is intended that protection granted by Letters Patent hereon be limited in breadth only by definitions contained in the appended claims and any equivalents thereof.
This application claims the priority of U.S. Provisional Application No. 60/702,248, filed Jul. 25, 2005 entitled, MULTI MODAL SPECTROSCOPY. The entire content of the above application is being incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| 60702248 | Jul 2005 | US |
