Stanley Mathew

Biochemical correlation of Raman spectra of normal, benign and malignant breast tissues: a spectral deconvolution study.

The aim of this study was to understand and correlate spectral features and biochemical changes in normal, fibroadenoma and infiltrating ductal carcinoma of breast tissues using Raman spectra that were part of the spectroscopic models developed and evaluated by us earlier. Spectra were subjected to curve fitting and intensities plots of resultant curve resolved bands were computed. This study has revealed that fat (1301 and 1440 cm−1), collagen (1246, 1271, and 1671 cm−1) and DNA (1340 and 1480 cm−1) bands have strong presence in normal, benign and malignant breast tissues, respectively. Intensity plots of various combinations of curved resolved bands were also explored to classify tissue types. Combinations of fat (1301 cm−1) and collagen (1246, 1271, and 1671 cm−1)/amide I; DNA (1340 cm−1) and fat (1301 cm−1); collagen (1271 cm−1) and DNA (1480 cm−1) are found to be good discriminating parameters. These results are in tune with findings of earlier studies carried out on western population as well as our molecular biological understanding of normal tissues and neoplastic processes. Thus the finding of this study further demonstrates the efficacy Raman spectroscopic approaches in diagnostic applications as well as in understanding molecular phenomenon in breast cancers.

Raman Spectroscopy of Breast Tissues

Breast cancer is one of the leading female cancers. The major drawback of the gold standard of screening, mammography, is the high rate of false reports, aside from the risk from repeated exposure to harmful ionizing radiations. Histopathology, the gold standard of diagnosis, is time consuming and often prone to subjective interpretations. Molecular level diagnosis ‘omics’ is becoming increasingly popular; among these is metabolomics, diagnosis based on ‘metabolic fingerprinting’. In the present article we review a Raman spectroscopic approach to metabolic fingerprinting in breast cancer detection. This review opens with a brief background on anatomical and etiological aspects of breast cancers. We present an overview of conventional detection approaches in breast cancer screening and diagnosis methods, followed by a concise note on the basics of optical spectroscopy and its applications in the screening/diagnosis of breast malignancy. We present the recent developments in Raman spectroscopic diagnosis of breast cancers and also share our experience in Raman spectroscopic classification of normal, benign and malignant breast tissues. Perspectives and current status of Raman spectroscopic screening/diagnosis of breast cancers are also discussed.

Autofluorescence of Breast Tissues: Evaluation of Discriminating Algorithms for Diagnosis of Normal, Benign, and Malignant Conditions

OBJECTIVE We evaluated different discriminating algorithms for classifying laser-induced fluorescence spectra of normal, benign, and malignant breast tissues that were obtained with 325-nm excitation. BACKGROUND DATA Mammography and histopathology are the conventional gold standard methods of screening and diagnosis of breast cancers, respectively. The former is prone to a high rate of false-positive results and poses the risk of repeated exposure to ionizing radiation, whereas the latter suffers from subjective interpretations of morphological features. Thus the development of a more reliable detection and screening methodology is of great interest to those practicing breast cancer management. Several studies have demonstrated the efficacy of optical spectroscopy in diagnosing cancer and other biomedical applications. MATERIALS AND METHODS Autofluorescence spectra of normal, benign, and malignant breast tissues, with 325-nm excitation, were recorded. The data were subjected to diverse discriminating algorithms ranging from intensities and ratios of curve-resolved bands to principal components analysis (PCA)-derived parameters. RESULTS Intensity plots of collagen and NADPH, two known fluorescent biomarkers, yielded accurate classification of the different tissue types. PCA was carried out on both unsupervised and supervised methods, and both approaches yielded accurate classification. In the case of the supervised classification, the developed standard sets were verified and evaluated. The limit test approach provided unambiguous and objective classification, and this method also has the advantage of being user-friendly, so untrained personnel can directly compare unknown spectra against standard sets to make diagnoses instantly, objectively, and unambiguously. CONCLUSION The results obtained in this study further support the efficacy of 325-nm-induced autofluorescence, and demonstrate the suitability of limit test analysis as a means of objectively and unambiguously classifying breast tissues.

Symptoms experienced by cancer patients and barriers to symptom management

Background: People living with cancer experience wide variety of symptoms. If symptoms are not managed well, it may hamper an individuals ability to continue his or her activities of daily life. Treatment of symptoms relieves suffering and improves the rate of recovery as well as the quality of life. Objectives: To assess the symptoms of suffering among cancer patients and to identify the perceived barriers to their symptom management. Materials and Methods: A cross-sectional study was carried out among 768 cancer patients selected by stratified sampling with a proportionate selection from each stratum. Data were collected from cancer patients by interview technique using structured validated questionnaire. Results: Majority of the samples (30.2%) belonged to the age group of 51–60 years, most of them were diagnosed with head and neck cancer (40.1%) and 57.7% had stage III disease. The majority of the patients studied had pain (77%), tiredness (96.5%), disturbed sleep (96.4%), weight loss (63.3%), and irritability (85.7%). Most of the patients had lack of appetite (89.4%), feeling of sadness (96.6%), worry (94.5%), and feeling of nervousness (82.8%). Majority of the patients had some misconception regarding symptoms, that is, increasing pain signifies disease progression (92.7%), medicine to control pain may weaken the immune system (89.9%) and pain is inevitable for cancer patients (78.5%). Seventy-seven percent of samples reported that the anxiety or depression is expected after the diagnosis of cancer. Conclusion: This study provides an overview of symptoms among cancer patients and barriers experienced by them.

Protein profile study of breast-tissue homogenates by HPLC-LIF.

Proteomics is a promising approach for molecular understanding of neoplastic processes including response to treatment. Widely used 2D-gel electrophoresis/Liquid chromatography coupled with mass spectrometry (LC-MS) are time consuming and not cost effective. We have developed a high-sensitivity (femto/subfemtomoles of protein/20 mul) High Performance Liquid Chromatography-Laser Induced Fluorescence HPLC-LIF instrument for studying protein profiles of biological samples. In this study, we have explored the feasibility of classifying breast tissues by multivariate analysis of chromatographic data. We have analyzed 13 normal, 17 malignant, 5 benign and 4 post-treatment breast-tissue homogenates. Data was analyzed by Principal Component Analysis PCA in both unsupervised and supervised modes on derivative and baseline-corrected chromatograms. Our findings suggest that PCA of derivative chromatograms gives better classification. Thus, the HPLC-LIF instrument is not only suitable for generation of chromatographic data using femto/subfemto moles of proteins but the data can also be used for objective diagnosis via multivariate analysis. Prospectively, identified fractions can be collected and analyzed by biochemical and/or MS methods.

Jack in the box: inguinal endometriosis

A 39-year-old woman with a left-sided inguinal swelling was referred to us with a diagnosis of inguinal hernia. On asking leading questions, the patient gave a typical history of cyclical pain and increased swelling during menstruation. Fine-needle aspiration biopsy revealed endometrial glands. Preoperatively, the extent of the endometriotic lesion was delineated using MRI. The lesion was approached through the patients caesarean scar for cosmetic reasons and excised in toto. Final diagnosis was round ligament endometriosis. The patient was asymptomatic at 3, 6 and 12 months’ follow-up. This case re-emphasises the fact that endometriosis is an enigmatic disease and can be found anywhere in the body. Thus, a woman of reproductive age presenting with any cyclical symptom should be asked about its relation to her menstrual cycle.

Quality of life among cancer patients

Introduction: Cancer is a leading cause of death. People living with cancer experience a variety of symptoms. Quality of life (QOL) is a major concern of patients with terminal cancer. Symptoms affect their QOL. Management of symptoms improves distress and QOL. Objective: The objective of the study was to assess the QOL among cancer patients. Materials and Methods: A survey was conducted among 768 cancer patients selected by a convenient sampling technique. Data was collected from cancer patients by interview technique using structured and validated interviewed schedule. Results: Out of 768 cancer patients, 30.2% patients were in the age group of 51–60 years, majority with head–and-neck cancer (40.1%), and 57.7% had stage III disease. QOL of majority of patients was influenced by their symptoms. 82.3% of them had low QOL scores. Conclusion: Cancer patients experienced many symptoms that affected their QOL. There is a need to develop interventions for effective management of symptoms that will empower the patients to have a greater sense of control over their illness and treatment and to improve the QOL.

Photoacoustic spectroscopy based investigatory approach to discriminate breast cancer from normal: a pilot study

In spite of many efforts for early detection of breast cancer, there is still lack of technology for immediate implementation. In the present study, the potential photoacoustic spectroscopy was evaluated in discriminating breast cancer from normal, involving blood serum samples seeking early detection. Three photoacoustic spectra in time domain were recorded from each of 20 normal and 20 malignant samples at 281nm pulsed laser excitations and a total of 120 spectra were generated. The time domain spectra were then Fast Fourier Transformed into frequency domain and 116.5625 - 206.875 kHz region was selected for further analysis using a combinational approach of wavelet, PCA and logistic regression. Initially, wavelet analysis was performed on the FFT data and seven features (mean, median, area under the curve, variance, standard deviation, skewness and kurtosis) from each were extracted. PCA was then performed on the feature matrix (7x120) for discriminating malignant samples from the normal by plotting a decision boundary using logistic regression analysis. The unsupervised mode of classification used in the present study yielded specificity and sensitivity values of 100% in each respectively with a ROC - AUC value of 1. The results obtained have clearly demonstrated the capability of photoacoustic spectroscopy in discriminating cancer from the normal, suggesting its possible clinical implications.

Photoacoustic spectroscopy based evaluation of breast cancer condition

Photoacoustic spectroscopy, a hybrid of optics and acoustics has been gaining popularity in the biomedical field very fast. The main aim in the present study was to apply this technique to detect and distinguish breast tumor tissues from normal and hence develop a tool for clinical applications. There were 224 photoacoustic spectra recorded from 28 normal and 28 breast tumor tissues using PZT detector at 281nm pulsed laser excitations from Nd-YAG laser pumped frequency doubled dye laser system. The recorded time domain photoacoustic spectra were fast Fourier transformed into frequency domain patterns in the frequency region 0-1250kHz and from each pattern, 7 features (mean, median, mode, variance, standard deviation, area under the curve & spectral residual after fitting with 10th degree polynomial) were extracted using MATLAB algorithms. These features were then tested for their significance between normal and malignant conditions using Student T-test and two of them (variance, std. deviation) showing significant variation were selected for further discrimination analysis using supervised quadratic discriminate analysis (QDA). In QDA, 60 spectra from each of the normal and malignant were used for making the respective calibration sets and the remaining 52 spectra from each were used for the validation. The performance of the analysis tested for the frequency region 406.25 - 625.31 kHz, showed specificity and sensitivity values of 100% and 88.46% respectively suggesting possible application of the technique in breast tumor detection.

Psychological impact of cancer diagnosis in newly diagnosed breast cancer patients

Aim: The aim of the study was to examine the impact of cancer diagnosis on the psychological status of women with breast cancer, focusing on anxiety and psychological distress experienced by breast cancer patients. Materials and Method: A descriptive, cross-sectional study was conducted among 80 breast cancer patients after an initial cancer diagnosis by using purposive sampling. The study was conducted in a tertiary care hospital in South India. Data was collected by using Demographic and Clinical proforma, State-Trait Anxiety Inventory and Impact of Event Scale. Sample characteristics were analyzed using descriptive statistics, the influence of anxiety on psychological distress was tested with correlation and a chi-square test was used to test the association between anxiety and distress with demographic and disease-related variables. Results: The sample consisted of 80 women with a mean age of 48.1 years. 96% were married, and 90% of them were housewives. Half of the subjects were educatedupto primary school. 80% were in stage II of cancer with a duration of diagnosis of 2-4 weeks.48% of the subjects were suffering from a moderate range of distress and 16% had severe psychological distress. Similarly, 80% of subjects had moderate to high level of anxiety. Anxiety did not have any influence on psychological distress. And only duration of diagnosis was associated with psychological distress. Conclusion: Results of the study suggest that cancer diagnosis can cause moderate to severe distress in breast cancer patients. Recognizing distress and intervening it on time is pivotal to improve treatment outcomes of women with breast cancer.