AIRTIFICIAL INTELLIGENCE BASED BREAST CANCER ANALYSIS TECHNIQUE

Abstract

Breast cancer can be simply understood as an abnormal growth of cells that possess invasive capabilities. Some of these cells can leave the tumor location and embark upon the lymph nodes or the nearest underlying muscle tissues and that’s when breast cancer becomes life-threatening. Breast cancer can appear in different parts of the breast. Breast cancer is quite complicated and presents itself in very unique ways in different people. It is estimated that one out of 22 women in India will get breast cancer in their lifetime. Each year more than 2 million people are diagnosed with breast cancer globally. A woman is at a significantly higher risk than a man for getting breast cancer. In women, there is about a lifetime risk of 10 percent of getting breast cancer [1].

 An early diagnosis makes all the difference. Treating breast cancer early provides the best chance of preventing the disease from returning and potentially reaching an incurable stage. There are countless benefits of an early diagnosis. At an early stage, breast cancer is a very much curable and survivable disease. It provides the patient with many options to consider down the road instead of jumping to the last viable solution of mastectomy. Usually, when a patient experiences unusual symptoms such as nipple discharge or a lump, they should make sure to book an appointment with their doctor. Any reason for a woman to think that something has changed in their breasts is an indication. The first step of diagnosis is targeted imaging with the help of mammograms or tomosynthesis imaging or ultrasound in some cases. But usually, the first sets of scans do not impart complete information and hence additional scans every consecutive month are advised by the doctors. In some cases, a biopsy can be carried out to determine whether the tumor is benign or malignant. An accurate prognosis can be quite difficult because of the biological heterogeneity of breast cancer. Mammography has been shown to provide accurate results for early breast cancer screening but in some specific situations, such as in a patient with dense breasts [2], uncommon architectural distortions, or significant extensive scarring from prior biopsies the results were quite unreliable [3]. The conventional imaging techniques cannot precisely detect the involvement of axillary lymph nodes or even the presence of any distant metastases which adversely affect the further prognosis of the patient [4].

Hence, we are proposing the idea of using computed tomography imaging techniques over conventional imaging techniques. Computed tomography is the x-ray technique to diagnose diseases and injuries. Tomos = slice; graphine=imaging of an object by analyzing its slices.  If one has large breast cancer, then the patient may be ordered to get a CT scan to know the level of spreading of cancer into the chest wall (Figure 1). This helps to jump to the conclusion if cancer can be removed with mastectomy. CT scans are also used to examine other parts of the body where breast cancer can spread, such as the lymph nodes, lungs, liver, brain, or spine.  If your symptoms or other findings suggest that cancer has severely spread then one needs to have CT scans of the head, chest, and abdomen too [5].

We are going to carry out this task through “ARTIFICIAL INTELLIGENCE”. Since breast imaging is facing exponential growth of pressure in imaging requests, so a solution can be found to take the edge off these pressures by adopting AI to improve workflow efficiency and patient outcomes as well.