Aditi Sahu

Serum Based Diagnosis of Asthma Using Raman Spectroscopy: An Early Phase Pilot Study

The currently prescribed tests for asthma diagnosis require compulsory patient compliance, and are usually not sensitive to mild asthma. Development of an objective test using minimally invasive samples for diagnosing and monitoring of the response of asthma may help better management of the disease. Raman spectroscopy (RS) has previously shown potential in several biomedical applications, including pharmacology and forensics. In this study, we have explored the feasibility of detecting asthma and determining treatment response in asthma patients, through RS of serum. Serum samples from 44 asthma subjects of different grades (mild, moderate, treated severe and untreated severe) and from 15 reference subjects were subjected to Raman spectroscopic analysis and YKL-40 measurements. The force expiratory volume in 1 second (FEV1) values were used as gold standard and the serum YKL-40 levels were used as an additional parameter for diagnosing the different grades of asthma. For spectral acquisition, serum was placed on a calcium fluoride (CaF2) window and spectra were recorded using Raman microprobe. Mean and difference spectra comparisons indicated significant differences between asthma and reference spectra. Differences like changes in protein structure, increase in DNA specific bands and increased glycosaminoglycans-like features were more prominent with increase in asthma severity. Multivariate tools using Principal-component-analysis (PCA) and Principal-component based-linear-discriminant analysis (PC-LDA) followed by Leave-one-out-cross-validation (LOOCV), were employed for data analyses. PCA and PC-LDA results indicate separation of all asthma groups from the reference group, with minor overlap (19.4%) between reference and mild groups. No overlap was observed between the treated severe and untreated severe groups, indicating that patient response to treatment could be determined. Overall promising results were obtained, and a large scale validation study on random subjects is warranted before the routine clinical usage of this technique.

Handheld optical coherence tomography–reflectance confocal microscopy probe for detection of basal cell carcinoma and delineation of margins

Abstract. We present a hand-held implementation and preliminary evaluation of a combined optical coherence tomography (OCT) and reflectance confocal microscopy (RCM) probe for detecting and delineating the margins of basal cell carcinomas (BCCs) in human skin in vivo. A standard OCT approach (spectrometer-based) with a central wavelength of 1310 nm and 0.11 numerical aperture (NA) was combined with a standard RCM approach (830-nm wavelength and 0.9 NA) into a common path hand-held probe. Cross-sectional OCT images and enface RCM images are simultaneously displayed, allowing for three-dimensional microscopic assessment of tumor morphology in real time. Depending on the subtype and depth of the BCC tumor and surrounding skin conditions, OCT and RCM imaging are able to complement each other, the strengths of each helping overcome the limitations of the other. Four representative cases are summarized, out of the 15 investigated in a preliminary pilot study, demonstrating how OCT and RCM imaging may be synergistically combined to more accurately detect BCCs and more completely delineate margins. Our preliminary results highlight the potential benefits of combining the two technologies within a single probe to potentially guide diagnosis as well as treatment of BCCs.

Oral cancer screening: serum Raman spectroscopic approach

Abstract. Serum Raman spectroscopy (RS) has previously shown potential in oral cancer diagnosis and recurrence prediction. To evaluate the potential of serum RS in oral cancer screening, premalignant and cancer-specific detection was explored in the present study using 328 subjects belonging to healthy controls, premalignant, disease controls, and oral cancer groups. Spectra were acquired using a Raman microprobe. Spectral findings suggest changes in amino acids, lipids, protein, DNA, and β-carotene across the groups. A patient-wise approach was employed for data analysis using principal component linear discriminant analysis. In the first step, the classification among premalignant, disease control (nonoral cancer), oral cancer, and normal samples was evaluated in binary classification models. Thereafter, two screening-friendly classification approaches were explored to further evaluate the clinical utility of serum RS: a single four-group model and normal versus abnormal followed by determining the type of abnormality model. Results demonstrate the feasibility of premalignant and specific cancer detection. The normal versus abnormal model yields better sensitivity and specificity rates of 64 and 80%; these rates are comparable to standard screening approaches. Prospectively, as the current screening procedure of visual inspection is useful mainly for high-risk populations, serum RS may serve as a useful adjunct for early and specific detection of oral precancers and cancer.

Raman spectroscopy and cytopathology of oral exfoliated cells for oral cancer diagnosis

For oral cancers, screening and monitoring of high-risk populations can aid in early diagnosis and improve overall outcomes. Of the new methods, approaches based on exfoliative cytology are more practical for mass screening and monitoring of high-risk populations. Raman spectroscopy and exfoliative cytology for cervical cancers have shown promise in differentiating normal and abnormal samples. In this study, the feasibility of Raman oral exfoliative cytology along with cytopathology for oral cancer diagnosis was evaluated in 70 specimens. Exfoliated cells were obtained from 15 healthy volunteers (HV), 15 healthy tobacco users (HT), and 20 contralateral or disease control (DC) and 20 tumor (T) sites of same oral-cancer patients. Pap staining was carried out post Raman spectral acquisition. Spectral findings demonstrate that with increase in severity of pathology from HV to T, higher DNA and changes in secondary structure of proteins were encountered. Owing to heterogeneity in cellular samples, two different approaches – point-spectra and patient-wise – were evaluated for data analysis. PCA and PC-LDA using both approaches indicate that HV and HT are distinct from cancer groups DC and T. Misclassifications were also observed between HT and DC. These findings also correlate with cytopathological findings. Fewer misclassifications and higher classification efficiency were observed for the patient-wise approach. A large-scale validation study needs to be undertaken for evaluating the utility of Raman oral exfoliative cytology for screening of oral cancers using the patient-wise approach.

In vivo Raman spectroscopy–assisted early identification of potential second primary/recurrences in oral cancers: An exploratory study

Higher rates of local recurrences and second primaries, ascribable to field cancerization, are known problem in oral cancers. The present study explored utility of identification of potential recurrences by Raman spectroscopy, which has been shown to identify oral precancers, cancers, and field cancerization in humans and micro‐sized mechanical irritation‐induced tumors in animals.

In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy

Oral cancers suffer from poor disease-free survival rates due to delayed diagnosis. Noninvasive, rapid, objective approaches as adjuncts to visual inspection can help in better management of oral cancers. Raman spectroscopy (RS) has shown potential in identification of oral premalignant and malignant conditions and also in the detection of early cancer changes like cancer-field-effects (CFE) at buccal mucosa subsite. Anatomic differences between different oral subsites have also been reported using RS. In this study, anatomical differences between subsites and their possible influence on healthy vs pathological classification were evaluated on 85 oral cancer and 72 healthy subjects. Spectra were acquired from buccal mucosa, lip and tongue in healthy, contralateral (internal healthy control), premalignant and cancer conditions using fiber-optic Raman spectrometer. Mean spectra indicate predominance of lipids in healthy buccal mucosa, contribution of both lipids and proteins in lip while major dominance of protein in tongue spectra. From healthy to tumor, changes in protein secondary-structure, DNA and heme-related features were observed. Principal component linear discriminant analysis (PC-LDA) followed by leave-one-out-cross-validation (LOOCV) was used for data analysis. Findings indicate buccal mucosa and tongue are distinct entities, while lip misclassifies with both these subsites. Additionally, the diagnostic algorithm for individual subsites gave improved classification efficiencies with respect to the pooled subsites model. However, as the pooled subsites model yielded 98% specificity and 100% sensitivity, this model may be more useful for preliminary screening applications. Large-scale validation studies are a pre-requisite before envisaging future clinical applications.

Raman spectroscopy for detection of imatinib in plasma: A proof of concept

Imatinib is the standard first line treatment for chronic myeloid leukemia (CML). Owing to dose-related toxicities of Imatinib such as neutropenia, there is scope for treatment optimization through therapeutic drug monitoring (TDM). Trough concentration of 1 μg/mL is considered the therapeutic threshhold. Existing methods for the detection of Imatinib in plasma are limited by long read out time and expensive instrumentation. Hence, Raman spectroscopy was explored as a rapid and objective tool for monitoring Imatinib concentration. Three approaches: conventional Raman spectroscopy (CRS), Drop coating deposition Raman (DCDR) spectroscopy and surface-enhanced Raman spectroscopy (SERS) were employed to detect the required trough concentration of 1 μg/mL and above. Detection of therapeutically relevant concentrations (1 μg/mL) using SERS and suitable nanoparticle substrates has been demonstrated. Prospectively, rigorous validation using clinical samples is necessary to confirm the utility of this approach in routine clinical usage.

Unique spectral markers discern recurrent Glioblastoma cells from heterogeneous parent population.

An inability to discern resistant cells from bulk tumour cell population contributes to poor prognosis in Glioblastoma. Here, we compared parent and recurrent cells generated from patient derived primary cultures and cell lines to identify their unique molecular hallmarks. Although morphologically similar, parent and recurrent cells from different samples showed variable biological properties like proliferation and radiation resistance. However, total RNA-sequencing revealed transcriptional landscape unique to parent and recurrent populations. These data suggest that global molecular differences but not individual biological phenotype could differentiate parent and recurrent cells. We demonstrate that Raman Spectroscopy a label-free, non-invasive technique, yields global information about biochemical milieu of recurrent and parent cells thus, classifying them into distinct clusters based on Principal-Component-Analysis and Principal-Component-Linear-Discriminant-Analysis. Additionally, higher lipid related spectral peaks were observed in recurrent population. Importantly, Raman spectroscopic analysis could further classify an independent set of naïve primary glioblastoma tumour tissues into non-responder and responder groups. Interestingly, spectral features from the non-responder patient samples show a considerable overlap with the in-vitro generated recurrent cells suggesting their similar biological behaviour. This feasibility study necessitates analysis of a larger cohort of naïve primary glioblastoma samples to fully envisage clinical utility of Raman spectroscopy in predicting therapeutic response.

Optical diagnostics in oral cancer: An update on Raman spectroscopic applications

Raman spectroscopy (RS) is a sensitive vibrational spectroscopic method that can detect even subtle biochemical changes during the onset of disease. Consequently, RS has been extensively investigated for disease diagnosis, including cancers. Oral cancers are known to suffer from dismal survival rates, which have not improved for several decades. As delayed diagnosis contributes to the low disease-free survival rate observed in oral cancers, RS has also been explored for the early diagnosis of oral cancers. This review summarizes the major developments in the field, including diagnosis, surgical margin assessment and prediction of treatment response, and in the overall management of oral cancers. The article comprises an overview of epidemiology, diagnosis, treatment, and recently introduced diagnostic adjuncts for oral cancers, the basic principle, instrumentation of RS, multivariate analysis that impart objectivity to the approach, and finally a discussion on the recent applications in oral cancers. PubMed and Google Scholar database have been used to compile information available online till December 2015.

Raman spectroscopy of serum: A study on oral cancers

BACKGROUND: Early detection of oral cancers can lead to improved survival rates. Due to limitations of existing methods, alternative approaches like Raman spectroscopy are therefore being explored. Ex vivo approaches are more suitable as they obviate need of on-site instrumentation and stringent experimental conditions. Serum Raman spectroscopy has shown potential in detecting cancers like cervical, breast, colorectal and head and neck cancers. Feasibility of classification of normal and oral cancer using serum Raman spectroscopy with 532 nm excitation has also been explored. OBJECTIVE: In the present study, feasibility of differentiating normal and cancer serum samples using 785 nm excitation laser – the most widely used laser for biomedical applications was explored. METHODS: 36 buccal mucosa, 33 tongue cancer patients and 17 healthy subjects were recruited and Raman spectra of sera were recorded using assembled Raman microprobe coupled with 40× objective. To eliminate heterogeneity, average of 3 spectra recorded from each sample was subjected to PCA and PC-LDA followed by leave-one-out cross-validation. RESULTS: Findings indicate average classification efficiency of ∼78% for normal and cancer. Buccal mucosa and tongue cancer serum could also be classified with an efficiency of ∼68%. CONCLUSIONS: Findings of the study corroborate with the previous study and indicate potential of this approach in management of oral cancer in future, after prospective validation.