Textural pattern classification for oral squamous cell carcinoma.

Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer-aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey-level co-occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy.

A matched case control study of risk indicators of breast cancer in assam, India.

Breast cancer is the leading cause of cancer death among women worldwide especially in a developing country like India. It also occupies the highest place with relative proportion 17.5% in the Hospital Based Cancer Registry in progress in the Dr. B. Borooah Cancer Research Institute. Dr. B. Borooah Cancer Research Institute is the Regional Cancer Care Center for entire North East region of India. With this background a matched case control study of 100 cases of breast cancer and 100 controls was carried out to investigate the role of different Socio economic, Female Reproductive and Life style related factors and to understand the etiology of breast cancer in Assam. Controls are matched to the cases by age at diagnosis (±5 years), family income and place of residence with matching ratio 1:1. Data were collected using questionnaire and then conditional logistic regression analysis is used to estimate the odd ratios for several factors. Study revealed that breast cancer occurrence has statistical association with the factors chewing habits (p=0.003), number of children (p=0.080), age at marriage (p=0.014), age at first child birth (p=0.007), age at menarche (p=0.010).

Estimating Risk of Breast Cancer Occurrences at Different Ages: Application of Survival Techniques

Background: Awareness is the primary means to control breast cancer occurrence. The purpose of the present work is to study the risk of breast cancer occurrence in different age group, for the study area, Assam, India, by means of survival analysis techniques. Methods: Survival and hazard functions are key concepts in survival analysis for describing the distribution of event times. In the present research a new individialized model has been proposed for cumulative hazard function, taking gamma probability distribution as probability distribution of breast cancer occurrences. Kaplan Meier Survival method has been applied to find out the probability of diseases occurrence in the early menarche and late menarche group. The data used for implementation were collected from the Record Department of a prime local cancer institute, for the period 2010-2012. The information for the risk factor age at menarche were collected from the patients registered during August 2011 to February 2012. Results: The study reveals that in the study area, cumulative hazard of the women belonging to 35 to 50 years is higher than the early and late aged women. The cumulative hazard plot with shape parameter 0.5, 1 and 10 shows that cumulative risk for early aged women are greater than the late age women but when this values is increased from 10, the opposite trend is observed. Further, the median age of disease occurrence among early menarche group is 52 years and for late menarche it is 54 years. Conclusion: The model developed could successfully point out the age group for women lying at higher risk of breast cancer occurrence. Additionally the important risk factor, age at menarche, was effectively applied to supplement to this calculation. It is hoped that practical use of this method would enhance not only awareness but also early detection of the said disease.