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Mahesh

07/01/24 06:43 AM IST

How AI can help detect cancer

In News
  • As India sees an ever-rising tide of cancer cases, Mumbai’s Tata Memorial Hospital is turning to artificial intelligence for help.
Bio Imaging Bank
  • The project’s overarching goal is to create a robust repository encompassing radiology and pathology images, intricately linked with clinical information, outcome data, treatment specifics, and additional metadata.
  • This comprehensive resource is strategically designed for the training, validation, and rigorous testing of AI algorithms.
  • Initially focusing on head neck cancers and lung cancers, with a minimum of 1000 patients for each cancer type, the project aims to surpass the committed patient data for both cancer types by its completion date.
  • Alongside database creation, the project involves training and testing multiple AI algorithms using the gathered data, addressing medically relevant tasks such as screening for lymph node metastases, nucleus segmentation and classification, biomarker prediction (for instance, HPV in oropharyngeal and EGFR in lung cancer), and therapy response prediction.
  • The multi-institutional project is funded by the Department of Biotechnology, in collaboration with IIT-Bombay, RGCIRC-New Delhi, AIIMS-New Delhi, and PGIMER-Chandigarh.
Significance of technology
  • AI contributes significantly to cancer detection by emulating the human brain’s information processing.
  • In cancer diagnosis, AI analyses radiological and pathological images, learning from extensive datasets to recognise unique features associated with various cancers.
  • This technology facilitates early detection by identifying tissue changes and potential malignancies.
  • Comprehensive imaging generates longitudinal patient data, aiding in understanding behaviour, treatment response, disease recurrence, and overall survival.
  • AI and machine learning protocols utilise this data to develop predictive models for tumour survival and guide treatment aggressiveness
  • The creation of a tumour image bank involves segmenting and annotating images, outlining tumours, identifying different features, and annotating them as malignant, inflammatory, or edematous.
  • Biopsy results, histopathology, immunohistochemistry reports, and genomic sequences are correlated with images and clinical data to develop diverse algorithms.
  • This approach allows TMH to develop algorithms for different tumours, assess treatment responses directly from images, and avoid unnecessary chemotherapy for predicted non-responders, offering clinical utility.
  • Leveraging the biobank, predictive and diagnostic models are developed using thousands of breast cancer images, undergoing AI and ML analysis with technical support from partners like IIT-Bombay.
Way forward
  • In the future, AI is poised to play a transformative role in cancer treatment, particularly in mitigating fatalities in rural India.
  • AI’s potential lies in tailoring treatment approaches based on diverse patient profiles, and thus optimising therapy outcomes.
  • This technology is poised to significantly enhance precision in cancer solutions. 
  • Through continuous learning, AI enhances accuracy, ensuring timely cancer diagnoses, improving patient outcomes, and aiding healthcare professionals in decision-making processes.
  • The use of AI tools raises debates about potential replacement of human radiologists, facing regulatory scrutiny and resistance from some doctors and health institutions.
Source- Indian Express

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