Analysis of subcutaneous swine fat via deep Raman spectroscopy using a fiber-optic probe.

Since the fat content of pork is a deciding factor in meat quality grading, the use of a noninvasive subcutaneous probe for real-time in situ monitoring of the fat components is of importance to vendors and other interested parties. In this work, we developed a spectroscopic method using a fiber-optic probe for subcutaneous fat analysis that utilizes spatially offset Raman spectroscopy (SORS). Here, normalized Raman spectra were acquired as a function of spatial offset, and the relative composition of fat-to-skin was determined. We found that the Raman intensity ratio varied disproportionately depending on the fat content and that the variations of the slope were correlated to the thickness of the fat layer. Furthermore, ordinary least square (OLS) regression using two components indicated that the depth-resolved SORS spectra reflected the relative thickness of the fat layer. We concluded that the local distribution of subcutaneous fat could be measured noninvasively using a pair of fiber-optic probes.

Correction to: Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing.

The authors would like to bring to the reader's attention that the Clarke error grid plot presented in Fig. 3 was generated using codes adapted from following reference.

Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing.

Optical monitoring of blood glucose levels for non-invasive diagnosis is a growing area of research. Recent efforts in this direction have been inclined towards reducing the requirement of calibration framework. Here, we are presenting a systematic investigation on the influence of variation in the ratio of calibration and validation points on the prospective predictive accuracy of spectral models. A fiber-optic probe coupled Raman system has been employed for transcutaneous measurements. Limit of agreement analysis between serum and partial least square regression predicted spectroscopic glucose values has been performed for accurate comparison. Findings are suggestive of strong predictive accuracy of spectroscopic models without requiring substantive calibration measurements. Graphical abstract.

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.

Direct observation of glucose fingerprint using in vivo Raman spectroscopy.

Noninvasive blood glucose monitoring has been a long-standing dream in diabetes management. The use of Raman spectroscopy, with its molecular specificity, has been investigated in this regard over the past decade. Previous studies reported on glucose sensing based on indirect evidence such as statistical correlation to the reference glucose concentration. However, these claims fail to demonstrate glucose Raman peaks, which has raised questions regarding the effectiveness of Raman spectroscopy for glucose sensing. Here, we demonstrate the first direct observation of glucose Raman peaks from in vivo skin. The signal intensities varied proportional to the reference glucose concentrations in three live swine glucose clamping experiments. Tracking spectral intensity based on linearity enabled accurate prospective prediction in within-subject and intersubject models. Our direct demonstration of glucose signal may quiet the long debate about whether glucose Raman spectra can be measured in vivo in transcutaneous glucose sensing.

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.

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.

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.

A multimodal spectroscopy system for real-time disease diagnosis.

The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides complementary and depth-sensitive information about tissue composition. As such, MMS is a promising tool for disease diagnosis, particularly in atherosclerosis and breast cancer. We have developed an integrated MMS instrument and optical fiber spectral probe for simultaneous collection of all three modalities in a clinical setting. The MMS instrument multiplexes three excitation sources, a xenon flash lamp (370-740 nm), a nitrogen laser (337 nm), and a diode laser (830 nm), through the MMS probe to excite tissue and collect the spectra. The spectra are recorded on two spectrograph/charge-coupled device modules, one optimized for visible wavelengths (reflectance and fluorescence) and the other for the near-infrared (Raman), and processed to provide diagnostic parameters. We also describe the design and calibration of a unitary MMS optical fiber probe 2 mm in outer diameter, containing a single appropriately filtered excitation fiber and a ring of 15 collection fibers, with separate groups of appropriately filtered fibers for efficiently collecting reflectance, fluorescence, and Raman spectra from the same tissue location. A probe with this excitation/collection geometry has not been used previously to collect reflectance and fluorescence spectra, and thus physical tissue models ("phantoms") are used to characterize the probe's spectroscopic response. This calibration provides probe-specific modeling parameters that enable accurate extraction of spectral parameters. This clinical MMS system has been used recently to analyze artery and breast tissue in vivo and ex vivo.

Optical fiber probe for biomedical Raman spectroscopy.

In vitro experiments have demonstrated the ability of Raman spectroscopy to diagnose a wide variety of diseases. Recent in vivo investigations performed with optical fiber probes were promising but generally limited to easily accessible organs, often requiring relatively long collection times. We have implemented an optical design strategy to utilize system throughput fully by characterizing the Raman distribution from tissue. This scheme optimizes collection efficiency, minimizes noise, and has resulted in small-diameter, highly efficient Raman probes that are capable of collecting high-quality data in 1 s. Performance has been tested through simulations and experiments with tissue models and several in vitro tissue types, demonstrating that this new design can advance Raman spectroscopy as a clinically practical technique.