Tuesday, December 06, 2022

HM Hospital applies AI to ovarian cancer diagnosis

HM Hospitales aplica la IA al diagnóstico del cáncer de ovario

Jesus García-Donas, head of the Gynecological and Genitourinary Tumor Unit of HM CIOCC Madrid

And Artificial Intelligence (AI) Studies applied to ovarian cancer This allows advances in the knowledge of molecular biomarkers predictive and prognostic of this type of tumor, which will contribute to a better understanding of disease development and, therefore, Define personalized diagnosis, more accurate and efficient, The Clara Campal Comprehensive Oncology Center (HM CIOOC) in collaboration with the Juan Carlos I University designed and developed this important collaborative work.

Until now, some genetic alterations were determined as predictive and prognostic biomarkers in ovarian cancer, such as inactivating mutations in the BRCA1 and BRCA2 genes, but they are insufficient to understand the global evolution of the disease. thus,
HM CIOCC and Juan Carlos I University have collaborated to carry out this multicentre observational research Identification of biomarkers with potential effect in clinical practice.

Jesus García-Donas, head of the Gynecological and Genitourinary Tumor Unit at HM CIOCC Madrid and co-author of the study, explains that “at present, they know that cancer is a complex disease, in the development of which not only genetic changes are important, but microenvironmental conditions affect, regulation of gene expression and, of course, the conditions of the person suffering from it. This is forcing them to change the previous, somewhat simplistic approach, in which a tumor was considered only as the sum of mutations and it is necessary to integrate multiple data to understand the neoplasm and predict its development. Is”.

more than 300 patients

To perform this study, clinical and genomic data from 300 patients with advanced ovarian cancer were recorded with the aim of establishing the relationship between them and the variables that determine disease progression, which Represents “a novel line of work”. what they are installing Artificial intelligence algorithms capable of integrating genomic dataTo address it in a complex and comprehensive manner along with the clinical and pathological features of the disease. We think that this approach can give us a vision closer to reality than classic approaches focused on specific punctual changes”, indicates García-Donas.

In this sense, the AI ​​algorithm identified patterns common to cases that were resistant versus responding well to treatment. If confirmed in independent groups, we will be able to create a new and . will face promising line of work In which our accuracy in predicting the development of a case can increase exponentially.

what to do withl the predictive and predictive role of certain variables, the results confirm that maximal effort surgery favors reduction of said burden after patients with a high tumor burden at the time of diagnosis have been subjected to neoadjuvant treatment. The relationship between these variables leads to longer survival in accordance with previous data in the literature.

Several previous studies have shown an association between certain genetic alterations (BRCA1/2 and RAD51C) and the development of the disease. The application of artificial intelligence has allowed Define other gene correlations to be confirmed by increasing the number of data, that is, of the cases to be indexed. García-Donas believes that “this work is pioneering in ovarian cancer and that achieving a real impact on patient management will require a coordinated effort between medical oncologists, basic researchers and computer engineers.”

agreement with microsoft

HM Hospitals’ participation in this study is an example of the clear commitment that, since the beginning of the year, the group has been striving for the application of artificial intelligence to cancer research. As a result of the agreement signed with Microsoft, automation of clinical history analysis and data collection from clinical history is being undertaken with a dual purpose: to guide clinical activity and support research, Accelerating the development of new procedures and drugs.

For García-Donas, “Working in the field of artificial intelligence applied to health is always a formidable challenge”. “Currently, once we have established the best study methodology, we want to move on” predicting response to specific treatments so that we can personalize the treatment of patients using artificial intelligence.” In this way, he is confident that “when we are able to understand disease at an advanced stage, we will be able to apply the same method to early disease.” in which the chances of cure are very high. Perhaps it is in this context that the impact of this technology could decisively change the course of the disease.”

While it may include statements, data or notes from health institutions or professionals, the information contained in medical writing is edited and prepared by journalists. We advise the reader to consult a health professional on any health-related questions.

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