DeepMed is an ISO-13485 certified start-up MedTech company based in Manchester, UK. Through the support of SBRI we developed an AI-powered product, DeepPath™ – LYDIA, to assist histopathologists in performing lymph node metastasis detection quickly and accurately.

DeepPath™ – LYDIA is expected to improve and accelerate the oncology diagnosis and treatment pipeline, which is currently under pressure. The system was CE-Marked in May 2022 as a Class I decision support product as per IVDD.

AI oncology diagnostics can support overstretched pathologists

The oncology-histopathology combination was selected as our initial focus for two reasons. Cancer incidence is growing globally as the population ages, and histopathology is at the centre of all diagnostics.

In addition, histopathology itself drives patient management and affects the outcome of patient treatment. Secondly, the field of histopathology needs more experts.

The USA reports state a 20% decrease in active pathologists in the past decade. That shortage of pathologists causes pathology departments to be under intense pressure, resulting in a 15% drop in diagnostic accuracy, long waiting times to receive results, and up to two months of treatment delays.

All these issues directly affect patient outcomes, overall survival, and quality of life.

How does the AI oncology diagnostics system, DeepPath™ – LYDIA, work?

Histopathological diagnosis in cancer consists of two main pillars: grading and staging.

In grading a tumour, a tumorous tissue section is examined under a microscope, and based on the morphological characteristics of the whole tumour and the tumour cells, the cancer type and subtype are deduced. This indicates the tumour’s aggressiveness and guides the oncologists towards specific therapeutic strategies.

On the other hand, in staging, tissue sections from lymph nodes surrounding the tumour site are examined under a microscope to determine whether the tumour has spread beyond the primary site, an event known as metastasis.

The oncologists completely alter the consequent diagnostic procedures and therapeutic protocols if a tumour has metastasised. DeepPath™ – LYDIA focuses on the former diagnostic aspect, namely staging, to offer decision support to histopathologists.

DeepPath™ – LYDIA is a groundbreaking AI oncology diagnostics system that detects metastatic tumours on digitised microscope slides of Hematoxylin & Eosin (H&E) stained lymph nodes.

It is the first CE-Marked metastasis detection system to identify tumours from four different cancer types: breast, lung, colon and melanoma, accounting for ~43% of total cancer incidence.

The AI oncology diagnostics system outlines the detected tumour regions (also measuring maximum diameter for each region) and presents them to the histopathologist for making the diagnosis; it also re-ranks multiple lymph node slides that belong to a single case from high to low or no tumour content for a further efficiency boost.

Beyond Diagnostic Decision Support

DeepMed participated in the public VisioMel-Challenge along with 540 other participants and, through just three submissions, made it to the top 10 with a performance that is marginally close to the leader.

This competition concentrated on predicting relapse in melanoma patients from digitised slides of H&E-stained biopsies using AI. The competition was based on the extensive RIC-Mel dataset, which included data from over 40,000 patients across 49 sites in France.

VisioMel was a collaborative effort initiated in 2021 by the French Society of Pathology, the French Society of Dermatology, the French Cutaneous Cancers Group, and the National Professional Council of Pathologists.

The primary sponsor was the French Ministerial Delegation for Digital Health as part of the French government’s ‘Digital Health Acceleration Strategy’.

Source: https://www.openaccessgovernment.org/ai-oncology-diagnostics-help-the-nhs/160404/