Dr. Lal PathLabs becomes first in India to adopt AI-based module for cancer lymph node metastasis detection
The accurate detection of cancer spread to lymph nodes is a critical factor in determining the stage and treatment strategy for patients. Missing these signs of cancer progression can allow the disease to advance, increasing the chances of it spreading to distant organs and reducing survival rates. The ability to identify even occult metastases in patients with early-stage cancer has the potential to significantly influence treatment plans and improve outcomes.
Traditionally, detecting micrometastases—small clusters of cancer cells hidden in lymph nodes—has been a time-consuming and complex process, often requiring advanced testing. The new AI system, called QiAI Lymph Node Dx, addresses this challenge by using deep learning to analyze digital slides and identify cancer cells with exceptional precision. This integration of AI into diagnostic practice ensures that cancer detection becomes faster, more reliable, and highly accurate.
What makes this development especially impactful is its ability to pick up even single cancer cells, which were later validated through immunohistochemistry testing. The AI model has been tested across various cancer types, including breast, colon, stomach, and esophageal cancers, consistently delivering highly accurate results. Breast cancer, which accounts for nearly 28% of cancer cases among women in India, particularly stands to benefit from this breakthrough, highlighting the clinical relevance of the technology.
By achieving complete sensitivity and negative predictive value—meaning no metastatic cases went undetected—the AI system has proven to be a robust screening tool. Its tumor-agnostic design allows it to function effectively across different cancer types, making it a versatile solution for oncologists and pathologists alike.
As cancer incidence continues to rise in India, the integration of advanced AI-powered diagnostic tools such as QiAI Lymph Node Dx is set to transform the landscape of cancer care. By enabling earlier and more accurate diagnoses, this technology not only improves the efficiency of medical practice but also ensures better treatment decisions, offering renewed hope to patients battling cancer.
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