Dr. Lal PathLabs (DLPL) has adopted a deep learning-based AI module to detect lymph node metastasis, including micrometastasis, in cancer cases. This technology, validated in collaboration with Qritive, was showcased at USCAP 2025.
Accurate identification of cancer spread to lymph nodes is vital in determining the stage and treatment path for patients. If the spread of cancer to the lymph nodes is left undetected, it can allow the disease to progress to later stages, increasing the risk of metastasis to distant organs and significantly reducing survival rates. Therefore, the identification of occult metastases in patients with early-stage cancer could have a substantial clinical impact on treatment planning and optimal therapy for patients with cancer.
Detecting micrometastases—tiny clusters of cancer cells in lymph nodes—usually takes a lot of time and special tests. The AI tool QiAI Lymph Node Dx changes that by using deep learning to quickly and accurately spot cancer cells on digital slides. Adding this technology to regular medical practice makes diagnosing cancer faster and more reliable.
Highlights:
- 100 per cent sensitivity and negative predictive value: The AI model detected all metastatic cases with no false negatives, making it a powerful screening tool.
- Enhanced accuracy: Even a single cancer cell metastasis was detected and later confirmed using immunohistochemistry.
- Tumour agnostic: The AI module has been validated across multiple cancer types, including breast cancer (which accounts for approximately 28.2 per cent of cancer cases among women in India)—demonstrating its versatility and broad clinical applicability.
- This leads to earlier, more accurate diagnoses—improving treatment decisions for patients.
Shankha Banerjee, CEO, Dr. Lal PathLabs, says, “This advanced technology allows us to identify cancer spread with exceptional precision and speed — particularly micrometastasis that may be missed by the human eye. By integrating AI into our pathology workflow, we are not only enhancing diagnostic accuracy but also enabling quicker clinical decisions, which can significantly improve treatment outcomes and quality of life for patients.”
The AI system was tested on digital slides from breast, colon, stomach, and oesophageal cancer cases. It accurately detected single-cell and micrometastases that had been missed during manual reviews. These results were later validated through immunohistochemistry (IHC), confirming the system’s reliability.
“The role of a pathologist is evolving rapidly, and we must evolve with it. Introducing AI into our diagnostic workflow is not just about adopting technology — it’s about reimagining how we detect and respond to disease,” said Dr Vandana Lal, Executive Director, Dr. Lal PathLabs.
Commenting on the development, Bruno Occhipinti, CEO, Qritive, said, “We previously got the opportunity to collaborate with the team at Dr. Lal PathLabs on a study, which resulted in the abstract presented at USCAP’25 in Boston. Following extensive testing and workflow validation, we are now excited to go live and enable the transformative impact of our AI-powered solution on critical diagnoses.”