Breast cancer is now the most common cancer worldwide and in India, its burden is rising at an alarming pace. Despite increased awareness, women continue to face delayed diagnosis, fragmented care, and unequal access to treatment. In this authored article, Dr. Tejal Gorasia, Consultant Breast Expert at Oncolife Cancer Centre, Satara, highlights how artificial intelligence (AI) and innovative care models are beginning to close these gaps and build a more integrated pathway for patients.
Despite rising awareness, India’s breast cancer burden continues to grow due to delayed diagnosis, uneven access to care, and lack of coordination across the healthcare system. Technology and innovation are promising when it comes to building a more connected and effective pathway for patients. This article helps to understand how AI-powered tools are making breast cancer detection, diagnosis, and treatment more accessible
According to GLOBOCAN, the Global Cancer Observatory under the World Health Organization, which monitors the cancer burden worldwide, breast cancer is the most common cancer in the world. In India alone over 1.9 lakhs new cases of breast cancer were reported in 2022 contributing to 13.6 per cent of all cancer cases combined. This roughly translates to 1 woman being detected with breast cancer every 4 minutes. Reportedly, by the end of 2022, over 5.25 lakh women were alive in India having been diagnosed with breast cancer in the previous five years. Globally breast cancer incidence is increasing at an annual rate of 3.1 per cent. It is also estimated that by the year 2040, the incidence of new cases worldwide will reach over 30 lakhs. Most of these cases would be reported in economically developing countries in Asia and Africa.
Another study by the World Health Organization (WHO) revealed that in 2022, there were an estimated 2.3 million women diagnosed with breast cancer and 670 000 deaths globally. Breast cancer occurs in every country of the world in women at any age after puberty, but with increasing rates in later life.
According to the WHO, breast cancer is a disease in which abnormal breast cells grow out of control and form tumours. If left unchecked, the tumours can spread throughout the body and become fatal. Breast cancer cells begin inside the milk ducts and/or the milk-producing lobules of the breast. The earliest form (in situ) is not life-threatening and can be detected in early stages. Cancer cells can spread into nearby breast tissue (invasion). This creates tumours that cause lumps or thickening. Invasive cancers can spread to nearby lymph nodes or other organs (metastasize). Metastasis can be life-threatening and fatal.
Breast cancer can be caused by genetics, family history, hormonal changes, and lifestyle habits like poor diet, obesity, smoking, or alcohol use. Age, late pregnancy, and lack of regular screening also increase the risk. It is the most common cancer among women in India, with a rising incidence in both urban and rural areas. Even though the awareness campaigns and screening programs have been widely conducted across the country, many women struggle in silence, which impacts their quality of life.
The problem can be fragmented care and delayed diagnosis: The reason is not just late presentation, but also the fragmented nature of breast cancer care, from screening to diagnosis, treatment, and long-term follow-up. Patients often face delays, miscommunication, and unequal access to specialists. To improve survival rates and quality of life, India must move beyond creating an integrated care pathway. Rural women may be required to travel long distances for a mammogram or biopsy. Whereas urban women tend to face long waiting times at crowded tertiary hospitals. However, women shouldn’t be worried anymore, as AI and innovation will help to bring about a positive change.
The promise of AI and innovation: Currently, AI-driven tools are making breast cancer detection, diagnosis, and treatment accessible, accurate, and timely for patients. Know the many advantages of it for the patients.
AI-integrated mammography: Machine learning algorithms can analyze mammogram images with utmost precision and detect early signs of cancer in the patient. AI can assist in detecting malignant cells faster and with fewer errors, and can be widely used in the centres.
Innovative care models: So, know that tele-oncology, mobile diagnostic units, and digital health records can allow rural patients to connect with urban specialists, ensuring prompt care.Building a Connected Breast Cancer Care Pathway: It is necessary to standardize screening protocols that are supported by AI, encourage affordable telehealth solutions for follow-ups and survivorship care for patients to build a smooth pathway that ensures earlier detection, faster treatment, and better survival outcomes.
