Development of Functional Requirements for Ex Vivo Pathology Applications of In Vivo Microscopy Systems: A Proposal From the In Vivo Microscopy Committee of the College of American Pathologists.

CONTEXT.­: In vivo microscopy (IVM) allows direct, real-time visualization of tissue histology in living patients without the need for tissue removal, processing, or staining. The IVM technologies in clinical use include confocal microscopy and optical coherence tomography. These technologies also show promise for use with pathology specimens (ex vivo microscopy [EVM]). However, few systems designed for EVM are commercially available, at least in part because of the lack of defined minimal functional requirements (FRs). OBJECTIVE.­: To develop minimal FRs for likely high-volume pathology applications of EVM. DESIGN.­: The IVM Committee of the College of American Pathologists identified potential EVM pathology applications based on the published literature. A subcommittee of IVM and EVM early adopters and experts then defined FRs for the most likely EVM applications. RESULTS.­: Potential EVM applications include assessment of margins, adequacy of needle biopsies and aspirates for diagnosis, and transplant tissues; selection of tissue for molecular studies or biorepository; and guidance in block selection from gross specimens. The first 3 applications were selected for development of FRs. The FRs were identified based on existing laboratory practices and guidelines and input from experts in the field and included device footprint and portability, specimen preparation, imaging time, field of view or resolution, morphologic diagnostic capability, yield, accuracy, ease of use, safety, and cost. CONCLUSIONS.­: Consensus was achieved on FRs that would accommodate the selected EVM applications. Publication and dissemination of those FRs will provide guidance to engineers, researchers, and vendors on how to optimally adapt IVM technologies for EVM for widespread adoption by pathologists.

Optical Coherence Tomography: A Novel Imaging Method for Post-lumpectomy Breast Margin Assessment-A Multi-reader Study.

RATIONALE AND OBJECTIVES: This study aimed to assess whether different breast cancer subspecialty physicians can be trained to distinguish non-suspicious from suspicious areas of post-lumpectomy specimen margin in patients with breast cancer using optical coherence tomography (OCT) images (a near-infrared based imaging technique) with final histology as the reference standard. MATERIALS AND METHODS: This institutional review board-exempt, Health Insurance Portability and Accountability Act-compliant study was performed on 63 surgically excised breast specimens from 35 female patients, creating a 90-case atlas containing both non-suspicious and suspicious areas for cancer. OCT images of the specimens were performed, providing 6.5-15 µm resolution with tissue visualization 1-2 mm subsurface. From the 90-case atlas, 40 cases were chosen for training and 40 were randomly selected for reader assessment. Three breast imaging radiologists, two pathologists, two breast surgeons, and one non-clinical reader were trained and assessed for ability to distinguish non-suspicious from suspicious findings blinded to clinical data and corresponding histology slides. Duration of training and assessment, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the curve for each reader were calculated as well as averages by subspecialty. RESULTS: The average training time was 3.4 hours (standard deviation, 1.2). The average assessment time was 1.9 hours (standard deviation, 0.7). The overall average reader sensitivity, specificity, and accuracy for detecting suspicious findings with histologic confirmation of cancer at the surgical margin for all eight readers were 80%, 87%, and 87%, respectively. Radiologists demonstrated the highest average among the disciplines, 85%, 93%, and 94%, followed by pathologists, 79%, 90%, and 84%, and surgeons, 76%, 84%, and 82% respectively. CONCLUSIONS: With relatively short training (3.4 hours), readers from different medical specialties were able to distinguish suspicious from non-suspicious OCT imaging findings in ex vivo breast tissue as confirmed by histology. These results support the potential of OCT as a real-time intraoperative tool for post-lumpectomy specimen margin assessment.

Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy.

Microcalcifications are an early mammographic sign of breast cancer and frequent target for stereotactic biopsy. Despite their indisputable value, microcalcifications, particularly of the type II variety that are comprised of calcium hydroxyapatite deposits, remain one of the least understood disease markers. Here we employed Raman spectroscopy to elucidate the relationship between pathogenicity of breast lesions in fresh biopsy cores and composition of type II microcalcifications. Using a chemometric model of chemical-morphological constituents, acquired Raman spectra were translated to characterize chemical makeup of the lesions. We find that increase in carbonate intercalation in the hydroxyapatite lattice can be reliably employed to differentiate benign from malignant lesions, with algorithms based only on carbonate and cytoplasmic protein content exhibiting excellent negative predictive value (93-98%). Our findings highlight the importance of calcium carbonate, an underrated constituent of microcalcifications, as a spectroscopic marker in breast pathology evaluation and pave the way for improved biopsy guidance.

Advances in optics for biotechnology, medicine and surgery.

The guest editors introduce a Biomedical Optics Express feature issue that includes contributions from participants at the 2013 conference on Advances in Optics for Biotechnology, Medicine and Surgery XIII.

Application of Raman spectroscopy to identify microcalcifications and underlying breast lesions at stereotactic core needle biopsy.

Microcalcifications are a feature of diagnostic significance on a mammogram and a target for stereotactic breast needle biopsy. Here, we report development of a Raman spectroscopy technique to simultaneously identify microcalcification status and diagnose the underlying breast lesion, in real-time, during stereotactic core needle biopsy procedures. Raman spectra were obtained ex vivo from 146 tissue sites from fresh stereotactic breast needle biopsy tissue cores from 33 patients, including 50 normal tissue sites, 77 lesions with microcalcifications, and 19 lesions without microcalcifications, using a compact clinical system. The Raman spectra were modeled on the basis of the breast tissue components, and a support vector machine framework was used to develop a single-step diagnostic algorithm to distinguish normal tissue, fibrocystic change (FCC), fibroadenoma, and breast cancer, in the absence and presence of microcalcifications. This algorithm was subjected to leave-one-site-out cross-validation, yielding a positive predictive value, negative predictive value, sensitivity, and specificity of 100%, 95.6%, 62.5%, and 100% for diagnosis of breast cancer (with or without microcalcifications) and an overall accuracy of 82.2% for classification into specific categories of normal tissue, FCC, fibroadenoma, or breast cancer (with and without microcalcifications). Notably, the majority of breast cancers diagnosed are ductal carcinoma in situ (DCIS), the most common lesion associated with microcalcifications, which could not be diagnosed using previous Raman algorithm(s). Our study shows the potential of Raman spectroscopy to concomitantly detect microcalcifications and diagnose associated lesions, including DCIS, and thus provide real-time feedback to radiologists during such biopsy procedures, reducing nondiagnostic and false-negative biopsies.

Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications.

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologic assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt.

Development and comparative assessment of Raman spectroscopic classification algorithms for lesion discrimination in stereotactic breast biopsies with microcalcifications.

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. Here, we develop and compare different approaches for developing Raman classification algorithms to diagnose invasive and in situ breast cancer, fibrocystic change and fibroadenoma that can be associated with microcalcifications. In this study, Raman spectra were acquired from tissue cores obtained from fresh breast biopsies and analyzed using a constituent-based breast model. Diagnostic algorithms based on the breast model fit coefficients were devised using logistic regression, C4.5 decision tree classification, k-nearest neighbor (k -NN) and support vector machine (SVM) analysis, and subjected to leave-one-out cross validation. The best performing algorithm was based on SVM analysis (with radial basis function), which yielded a positive predictive value of 100% and negative predictive value of 96% for cancer diagnosis. Importantly, these results demonstrate that Raman spectroscopy provides adequate diagnostic information for lesion discrimination even in the presence of microcalcifications, which to the best of our knowledge has not been previously reported.

Intrinsic versus laser-induced fluorescence spectroscopy for coronary atherosclerosis: a generational comparison model for testing diagnostic accuracy.

Laser-induced fluorescence (LIF) and intrinsic fluorescence spectroscopy (IFS) have been used experimentally for diagnosing coronary atherosclerosis. In this study, we demonstrated the diagnostic superiority of IFS at 342-nm excitation (IFS(342)) versus LIF (LIF(342)) and described a protocol for head-to-head comparison of old (LIF) versus new (IFS) generations of similar diagnostic methods, labeled as "generational comparison model". IFS(342) and LIF(342) were modeled with basis spectra of media, fibrous caps, and superficial foam cells and of their correspondent chemicals (elastin, collagen, and lipoproteins). The average accuracy and receiver operating characteristic area under the curve of IFS(342) in single-, double-, and triple-parameter diagnostic algorithm iterations, geared toward identifying 84 atherosclerotic specimens from a group of 117 coronary segments, was 90% ± 1% and 0.87 ± 0.025, superior to LIF(342) (84% ± 3% and 0.84 ± 0.016; P = 0.0002 and 0.02, respectively) in a generational comparison model.

Precision of Raman spectroscopy measurements in detection of microcalcifications in breast needle biopsies.

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. We developed Raman spectroscopy decision algorithms to detect breast microcalcifications, based on fit coefficients (FC) derived by modeling tissue Raman spectra as a linear combination of the Raman spectra of 9 chemical and morphologic components of breast tissue. However, little or no information is available on the precision of such measurements and its effect on the ability of Raman spectroscopy to make predictions for breast microcalcification detection. Here we report the precision, that is, the closeness of agreement between replicate Raman spectral measurements--and the model FC derived from them--obtained ex vivo from fresh breast biopsies from patients undergoing stereotactic breast needle biopsy, using a compact clinical Raman system. The coefficients of variation of the model FC averaged 0.03 for normal breast tissue sites, 0.12 for breast lesions without, and 0.22 for breast lesions with microcalcifications. Imprecision in the FC resulted in diagnostic discordance among replicates only for line-sitters, that is, tissue sites with FC values near the decision line or plane. The source of this imprecision and their implications for the use of Raman spectroscopy for guidance of stereotactic breast biopsies for microcalcifications are also discussed. In summary, we conclude that the precision of Raman spectroscopy measurements in breast tissue obtained using our compact clinical system is more than adequate to make accurate and repeatable predictions of microcalcifications in breast tissue using decision algorithms based on model FC. This provides strong evidence of the potential of Raman spectroscopy guidance of stereotactic breast needle biopsies for microcalcifications.

Portable optical fiber probe-based spectroscopic scanner for rapid cancer diagnosis: a new tool for intraoperative margin assessment.

There continues to be a significant clinical need for rapid and reliable intraoperative margin assessment during cancer surgery. Here we describe a portable, quantitative, optical fiber probe-based, spectroscopic tissue scanner designed for intraoperative diagnostic imaging of surgical margins, which we tested in a proof of concept study in human tissue for breast cancer diagnosis. The tissue scanner combines both diffuse reflectance spectroscopy (DRS) and intrinsic fluorescence spectroscopy (IFS), and has hyperspectral imaging capability, acquiring full DRS and IFS spectra for each scanned image pixel. Modeling of the DRS and IFS spectra yields quantitative parameters that reflect the metabolic, biochemical and morphological state of tissue, which are translated into disease diagnosis. The tissue scanner has high spatial resolution (0.25 mm) over a wide field of view (10 cm × 10 cm), and both high spectral resolution (2 nm) and high spectral contrast, readily distinguishing tissues with widely varying optical properties (bone, skeletal muscle, fat and connective tissue). Tissue-simulating phantom experiments confirm that the tissue scanner can quantitatively measure spectral parameters, such as hemoglobin concentration, in a physiologically relevant range with a high degree of accuracy (<5% error). Finally, studies using human breast tissues showed that the tissue scanner can detect small foci of breast cancer in a background of normal breast tissue. This tissue scanner is simpler in design, images a larger field of view at higher resolution and provides a more physically meaningful tissue diagnosis than other spectroscopic imaging systems currently reported in literatures. We believe this spectroscopic tissue scanner can provide real-time, comprehensive diagnostic imaging of surgical margins in excised tissues, overcoming the sampling limitation in current histopathology margin assessment. As such it is a significant step in the development of a platform technology for intraoperative management of cancer, a clinical problem that has been inadequately addressed to date.

Multimodal spectroscopy detects features of vulnerable atherosclerotic plaque.

Early detection and treatment of rupture-prone vulnerable atherosclerotic plaques is critical to reducing patient mortality associated with cardiovascular disease. The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides detailed biochemical information about tissue and can detect vulnerable plaque features: thin fibrous cap (TFC), necrotic core (NC), superficial foam cells (SFC), and thrombus. Ex vivo MMS spectra are collected from 12 patients that underwent carotid endarterectomy or femoral bypass surgery. Data are collected by means of a unitary MMS optical fiber probe and a portable clinical instrument. Blinded histopathological analysis is used to assess the vulnerability of each spectrally evaluated artery lesion. Modeling of the ex vivo MMS spectra produce objective parameters that correlate with the presence of vulnerable plaque features: TFC with fluorescence parameters indicative of collagen presence; NC∕SFC with a combination of diffuse reflectance ß-carotene∕ceroid absorption and the Raman spectral signature of lipids; and thrombus with its Raman signature. Using these parameters, suspected vulnerable plaques can be detected with a sensitivity of 96% and specificity of 72%. These encouraging results warrant the continued development of MMS as a catheter-based clinical diagnostic technique for early detection of vulnerable plaques.

Mechanism of ceroid formation in atherosclerotic plaque: in situ studies using a combination of Raman and fluorescence spectroscopy.

Accumulation of the lipid-protein complex ceroid is a characteristic of atherosclerotic plaque. The mechanism of ceroid formation has been extensively studied, because the complex is postulated to contribute to plaque irreversibility. Despite intensive research, ceroid deposits are defined through their fluorescence and histochemical staining properties, while their composition remains unknown. Using Raman and fluorescence spectral microscopy, we examine the composition of ceroid in situ in aorta and coronary artery plaque. The synergy of these two types of spectroscopy allows for identification of ceroid via its fluorescence signature and elucidation of its chemical composition through the acquisition of a Raman spectrum. In accordance with in vitro predictions, low density lipoprotein (LDL) appears within the deposits primarily in its peroxidized form. The main forms of modified LDL detected in both coronary artery and aortic plaques are peroxidation products from the Fenton reaction and myeloperoxidase-hypochlorite pathway. These two peroxidation products occur in similar concentrations within the deposits and represent ∼40 and 30% of the total LDL (native and peroxidized) in the aorta and coronary artery deposits, respectively. To our knowledge, this study is the first to successfully employ Raman spectroscopy to unravel a metabolic pathway involved in disease pathogenesis: the formation of ceroid in atherosclerotic plaque.

Detection of coronary atherosclerotic plaques with superficial proteoglycans and foam cells using real-time intrinsic fluorescence spectroscopy.

OBJECTIVES: The protein components of low-density lipoprotein (LDL), oxidized LDL and proteoglycans such as versican contain tryptophan, an amino acid with characteristic fluorescence features at 308 nm excitation wavelength. We hypothesize that intrinsic fluorescence spectroscopy at 308 nm excitation wavelength IFS308, a method suitable for clinical use, can identify coronary artery lesions with superficial foam cells (SFCs) and/or proteoglycans. METHODS: We subjected 119 human coronary artery specimens to in vitro fluorescence and reflectance spectroscopy. We used 5 basis spectra to model IFS308, and extracted their contributions to each individual IFS308 spectrum. A diagnostic algorithm using the contributions of Total Tryptophan and fibrous cap to IFS308 was built to identify specimens with SFCs and/or proteoglycans in their top 50 µm. RESULTS: We detected SFCs and/or proteoglycans, such as versican or the glycosaminoglycan hyaluronan, in 24 fibrous cap atheromas or pathologic intimal thickening (PIT) lesions. An algorithm using the contributions of Total Tryptophan and fibrous cap to IFS308 was able to identify these segments with 92% sensitivity and 80% specificity. CONCLUSION: We were able to establish a set of characteristic LDL, oxidized LDL, versican and hyaluronan fluorescence spectra, ready to be used for real-time diagnosis. The IFS(308) technique detects SFCs and/or proteoglycans in fibrous cap atheromas and PIT lesions. SFCs and proteoglycans are histological markers of vulnerable plaques, and this study is a step further in developing an invasive clinical tool to detect the vulnerable atherosclerotic plaque.

Diagnosing breast cancer using Raman spectroscopy: prospective analysis.

We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided.

Diagnosing breast cancer using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy.

Using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy, we have developed an algorithm that successfully classifies normal breast tissue, fibrocystic change, fibroadenoma, and infiltrating ductal carcinoma in terms of physically meaningful parameters. We acquire 202 spectra from 104 sites in freshly excised breast biopsies from 17 patients within 30 min of surgical excision. The broadband diffuse reflectance and fluorescence spectra are collected via a portable clinical spectrometer and specially designed optical fiber probe. The diffuse reflectance spectra are fit using modified diffusion theory to extract absorption and scattering tissue parameters. Intrinsic fluorescence spectra are extracted from the combined fluorescence and diffuse reflectance spectra and analyzed using multivariate curve resolution. Spectroscopy results are compared to pathology diagnoses, and diagnostic algorithms are developed based on parameters obtained via logistic regression with cross-validation. The sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy (total efficiency) of the algorithm are 100, 96, 69, 100, and 91%, respectively. All invasive breast cancer specimens are correctly diagnosed. The combination of diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy yields promising results for discrimination of breast cancer from benign breast lesions and warrants a prospective clinical study.

In vivo Raman spectral pathology of human atherosclerosis and vulnerable plaque.

The rupture of vulnerable atherosclerotic plaque accounts for the majority of clinically significant acute cardiovascular events. Because stability of these culprit lesions is directly related to chemical and morphological composition, Raman spectroscopy may be a useful technique for their study. Recent developments in optical fiber probe technology have allowed for the real-time in vivo Raman spectroscopic characterization of human atherosclerotic plaque demonstrated in this work. We spectroscopically examine 74 sites during carotid endarterectomy and femoral artery bypass surgeries. Of these, 34 are surgically biopsied and examined histologically. Excellent signal-to-noise ratio spectra are obtained in only 1 s and fit with an established model, demonstrating accurate tissue characterization. We also report the first evidence that Raman spectroscopy has the potential to identify vulnerable plaque, achieving a sensitivity and specificity of 79 and 85%, respectively. These initial findings indicate that Raman spectroscopy has the potential to be a clinically relevant diagnostic tool for studying cardiovascular disease.

Detection of morphological markers of vulnerable atherosclerotic plaque using multimodal spectroscopy.

Vulnerable plaques, which are responsible for most acute ischemic events, are presently invisible to x-ray angiography. Their primary morphological features include a thin or ulcerated fibrous cap, a large necrotic core, superficial foam cells, and intraplaque hemorrhage. We present evidence that multimodal spectroscopy (MMS), a novel method that combines diffuse reflectance spectroscopy (DRS), intrinsic fluorescence spectroscopy (IFS), and Raman spectroscopy (RS), can detect these markers of plaque vulnerability. To test this concept, we perform an MMS feasibility study on 17 human carotid artery specimens. Following the acquisition of spectra, each specimen is histologically evaluated. Two parameters from DRS, hemoglobin concentration and a scattering parameter, are used to detect intraplaque hemorrhage and foam cells; an IFS parameter that relates to the amount of collagen in the topmost layers of the tissue is used to detect the presence of a thin fibrous cap; and an RS parameter related to the amount of cholesterol and necrotic material is used to detect necrotic core. Taken together, these spectral parameters can generally identify the vulnerable plaques. The results indicate that MMS provides depth-sensitive and complementary morphological information about plaque composition. A prospective in vivo study will be conducted to validate these findings.

Intrinsic fluorescence and diffuse reflectance spectroscopy identify superficial foam cells in coronary plaques prone to erosion.

OBJECTIVE: Foam cells perform critical functions in atherosclerosis. We hypothesize that coronary segments with superficial foam cells (SFCs) situated in a region of interest with a depth of 200 mum can be identified using intrinsic fluorescence spectroscopy (IFS) and diffuse reflectance spectroscopy (DRS). This is a key step in our ongoing program to develop a spectroscopic technique for real-time in vivo diagnosis of vulnerable atherosclerotic plaque. METHODS AND RESULTS: We subjected 132 human coronary segments to in vitro IFS and DRS. We detected SFCs in 13 thick fibrous cap atheromas and 8 pathologic intimal thickening (PIT) lesions. SFCs colocalized with accumulations of smooth muscle cells and proteoglycans, including hyaluronan (P<0.001). Two spectroscopic parameters were generated from analysis of IFS at 480 nm excitation and DRS. A discriminatory algorithm using these parameters identified specimens with SFC area >40%, 20%, 10%, 5%, 2.5%, and 0% of the region of interest with 98%, 98%, 93%, 94%, 93%, and 90% accuracy, respectively. CONCLUSIONS: Our combined IFS and DRS technique accurately detects SFCs in thick fibrous cap atheromas and PIT lesions. Because SFCs are associated with histological markers of plaque erosion, our spectroscopic technique could prove useful in identifying vulnerable plaques.

In vivo margin assessment during partial mastectomy breast surgery using raman spectroscopy.

We present the first demonstration of in vivo collection of Raman spectra of breast tissue. Raman spectroscopy, which analyzes molecular vibrations, is a promising new technique for the diagnosis of breast cancer. We have collected 31 Raman spectra from nine patients undergoing partial mastectomy procedures to show the feasibility of in vivo Raman spectroscopy for intraoperative margin assessment. The data was fit with an established model, resulting in spectral-based tissue characterization in only 1 second. Application of our previously developed diagnostic algorithm resulted in perfect sensitivity and specificity for distinguishing cancerous from normal and benign tissues in our small data set. Significantly, we have detected a grossly invisible cancer that, upon pathologic review, required the patient to undergo a second surgical procedure. Had Raman spectroscopy been used in a real-time fashion to guide tissue excision during the procedure, the additional reexcision surgery might have been avoided. These preliminary findings suggest that Raman spectroscopy has the potential to lessen the need for reexcision surgeries resulting from positive margins and thereby reduce the recurrence rate of breast cancer following partial mastectomy surgeries.

Diagnosing breast cancer by using Raman spectroscopy.

We employ Raman spectroscopy to diagnose benign and malignant lesions in human breast tissue based on chemical composition. In this study, 130 Raman spectra are acquired from ex vivo samples of human breast tissue (normal, fibrocystic change, fibroadenoma, and infiltrating carcinoma) from 58 patients. Data are fit by using a linear combination model in which nine basis spectra represent the morphologic and chemical features of breast tissue. The resulting fit coefficients provide insight into the chemical/morphological makeup of the tissue and are used to develop diagnostic algorithms. The fit coefficients for fat and collagen are the key parameters in the resulting diagnostic algorithm, which classifies samples according to their specific pathological diagnoses, attaining 94% sensitivity and 96% specificity for distinguishing cancerous tissues from normal and benign tissues. The excellent results demonstrate that Raman spectroscopy has the potential to be applied in vivo to accurately classify breast lesions, thereby reducing the number of excisional breast biopsies that are performed.