The Institut Català de la Salut (ICS) has developed four proprietary artificial intelligence algorithms that have improved the diagnosis of breast cancer. It is a first step in a digital transformation project of pathological anatomy services that will be expanded to other tumors. Specialists are already working on an algorithm for lung cancer.
The idea is that AI helps with detection. In the case of breast cancer, based on the quantification of four biomarkers, or molecules whose presence signals a disease process: HER2, Ki67, estrogen receptors and progesterone receptors. The technology has already been used in nearly 600 possible breast cancers in the entire ICS hospital network.
The advances are part of the Digipàtics project, which the ICS began to deploy in 2021. Since then, more than 2 million slides with histological preparations (microscopic samples of biological tissues) have been digitized, which form the database that feeds the learning artificial intelligence algorithms to refine tumor diagnoses.
Pathologists and AI specialists from the Polytechnic University of Catalonia collaborate in the development. “Algorithms help quantify prognostic markers – an analysis that until now was done manually – with larger numbers, faster and more reproducibly, not so dependent on the expertise of whoever is looking at the images,” explains Jordi Temprana. , assistant physician in the Vall d'Hebron pathological anatomy service.
This Barcelona center is one of the seven hospitals that contribute samples to the database, along with Arnau de Vilanova, Doctor Trueta, Germans Trias i Pujol, Doctor Trueta, Joan XXIII and Verge de la Cinta. It is the largest pathological anatomy network in Europe, where 168 pathologists can share cases, diagnoses and knowledge in real time.
Hospitals produce a million slides a year and 24 scanners work to digitize all the samples. Networking and the greater precision that digitalization provides means improving speed, security, efficiency and equity in the territory, according to Temprana. In addition, there is better availability of cases for the training of resident doctors.
“Algorithms behave as if you had a super expert always available to make a determination. You can share cases, consult a difficult case more easily and make a faster and more accurate diagnosis,” says Temprana.
So why do we need doctors? “It is not the algorithm that makes the diagnosis, but the doctor, but it helps. The pathologist makes the diagnosis by looking at the image, interpreting the image, and the machine provides extra information that can make it faster and safer.”
The application of AI to cancer diagnosis is incipient, but it is the future. And they will also extend to treatment. “We don't know where the limit is, we don't know when, but we will see changes in the way we work,” says Temprano: “We have started with breast cancer because it is very prevalent, has a lot of social impact and has well-known biomarkers.” .
The ICS hospital network is already working to also develop algorithms for the diagnosis of lung cancer starting this year.
