Gradually, artificial intelligence tools are applied to clinical practice for greater knowledge and approach to lung cancer. Knowing patients’ response to treatments, such as immunotherapy, avoiding gender bias in research that harms women, or helping improve survival are some of its potential.
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Radiologist Raquel Pérez-López, researcher at the Vall de Hebron Institute of Oncology (VHIO) and the Cris Cancer Foundation. Photo provided
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Radiologist Raquel Pérez-López, researcher at the Vall de Hebron Oncology Institute (VHIO) and the Cris Cancer Foundation. Photo provided
“There are already artificial intelligence tools that we use on a daily basis, especially for the early diagnosis of cancer,” explains radiologist Raquel Pérez-López to EFEsalud, specifying that clinical studies are still needed to validate the possibilities that technology based on analysis and on the massive combination of data.
As part of World Lung Cancer Day, November 17, the researcher from the Vall d’Hebron Institute of Oncology (VHIO), in Barcelona, and the Cris Cancer Foundation analyzes one of the study paths that can have artificial intelligence (AI) in this cancer, one of the most frequent with more than 32,000 diagnoses per year.
Artificial intelligence to know the response to immunotherapy
This is a line of research carried out by VHIwith financing from Cris Foundation against cancerand which consists of using artificial intelligence to predict whether patients will respond to immunotherapy treatments, new generation drugs that have helped improve survival in this type of cancer.
“We want to select the best candidates who can benefit from immunotherapy,” says the doctor about the clinical trial already underway.
And it relies on patient information provided by three sources: the CT image, the MRI and the biopsy of the tumor to know
“AI allows us to do this type of analysis on a medical image. The information contained in CT images has not yet been exploited. Artificial intelligence allows us to integrate this type of data in relation to the volume of the disease, where it is distributed and what pattern the tumor has to better understand which patients are most likely to benefit from immunotherapy,” indicates Dr. Raquel Pérez López.
“We try to capture the characteristics of tumor cells and their microenvironment, such as lymphocyte cells, vasculature… factors that are involved in the probability of response and that can be captured with images and interpreted using artificial intelligence models,” he emphasizes.
Artificial intelligence against false positives and negatives
Among the handicaps of lung cancer, the late diagnosis (its symptoms can be confused with other pathologies) e false positives or negatives that imaging tests may show and the subsequent need to confirm with a biopsy
It is precisely in diagnosis that artificial intelligence has made the greatest progress, allowing the characteristics of pulmonary nodules to be identified and analyzed, excluding false positives and false negatives.
But AI also allows us to make progress in finding biomarkers or combinations of genetic alterations associated with a greater likelihood of response and prognosis.
The doctor recalls the important research work that focuses on the use of AI for risk prediction and, therefore, prevention of lung cancer, taking into account not only variables already managed, such as being a smoker , but also the analysis of the patient’s clinical situation, information, lifestyle habits or family history.
Put an end to gender prejudice
The annual report “Cancer figures in Spain in 2024” of Spanish Society of Medical Oncology (SEOM)in collaboration with the Spanish Cancer Registry Network (REDECAN)reflects that lung cancer in women is the third most common in incidence (after breast and colorectal cancer) with an estimated 10,285 cases this year.
Growing numbers among women, by 2024 an increase in cases of 12.3% is expected compared to the previous year and one of the causes is the consequences of the tobacco habit.
This makes it necessary to work from a gender perspective, with women’s own data, in the prevention, approach and research on lung cancer,
“There are gender differences in cancer in general and also in lung cancer, differences in predisposition or risk of suffering from it, in prognosis, in tolerance to treatment, which are secondary to different biology as well as sociocultural aspects that must be the subject of a ‘thorough investigation,’ observes this organization.
In this sense, artificial intelligence can also play its role by managing to identify specific aspects of women compared to men, but on condition that, says the University researcher VHI Raquel Pérez-López, artificial intelligence models must be trained to take into account this diversity, which is also necessary between different ethnicities.
Present and future of artificial intelligence tools in lung cancer which over time will be able to contribute to reducing mortality from this tumor, which currently causes deaths from cancer, and which in over 80% of cases is due to tobacco habits.
How is artificial intelligence changing the way clinical trials for lung cancer are conducted?
Interview: The Future of Lung Cancer Treatment with AI
Time.news Editor: Welcome to our interview today! We have the pleasure of speaking with Dr. Raquel Pérez-López, a radiologist and researcher at the Vall d’Hebron Institute of Oncology and the Cris Cancer Foundation. As we recently recognized World Lung Cancer Day, it’s an opportune time to discuss how artificial intelligence is reshaping the landscape of lung cancer treatment. Thank you for joining us, Dr. Pérez-López.
Dr. Raquel Pérez-López: Thank you for having me! It’s a crucial time to discuss the advancements in AI, especially in the area of lung cancer.
Editor: To start, could you explain how AI is being applied in the clinical practice of lung cancer?
Dr. Pérez-López: Certainly! AI tools are gradually making their way into our daily practice, particularly in the early diagnosis of lung cancer. We’re using AI to analyze large datasets, including medical images and patient profiles, which enables us to understand how patients respond to treatments, especially immunotherapy, and to refine our approach to personalized medicine.
Editor: That sounds promising. Can you elaborate on how AI predicts responses to immunotherapy?
Dr. Pérez-López: We’re currently conducting clinical trials that harness AI to improve our ability to select candidates for immunotherapy. By analyzing data from CT scans, MRIs, and tumor biopsies, we can identify specific characteristics of the tumors—like their cellular makeup and associated immune factors—that indicate which patients are likely to respond well to these novel treatments.
Editor: It’s impressive how AI can synthesize information from multiple sources. What challenges does the clinical community currently face that AI can help address?
Dr. Pérez-López: One major challenge is the late diagnosis of lung cancer. Symptoms often mimic other conditions, which can lead to misdiagnosis. AI enhances our diagnostic capacity by improving our ability to identify lung nodules and reducing false positives and negatives in imaging tests. This means we can confirm diagnoses much earlier, which is critical for effective treatment.
Editor: Speaking of diagnoses, I understand that gender bias in cancer research is a significant issue. How does AI contribute to alleviating this problem?
Dr. Pérez-López: Yes, gender bias has historically skewed cancer research, often focusing more on male responses to treatment. AI has the potential to change this by analyzing a broader range of data points, including those specific to women. This helps ensure that research outcomes are more representative and that women receive appropriate treatment options based on their unique responses to therapies.
Editor: That’s a necessary shift. As we wrap up, what’s your vision for the future of AI in lung cancer treatment?
Dr. Pérez-López: My hope is that, as AI technology continues to evolve, we will refine our ability to predict patient responses to not only immunotherapy but also other treatments. This will ultimately help tailor therapies more effectively, improve survival rates, and personalize prevention strategies by considering not just smoking habits but a broad array of lifestyle and genetic factors.
Editor: Thank you, Dr. Pérez-López, for sharing your insights with us today. It’s clear that AI holds tremendous promise in transforming lung cancer diagnosis and treatment.
Dr. Pérez-López: Thank you for the opportunity to discuss this vital topic! Together, we can look forward to a future with improved outcomes for lung cancer patients.
Editor: And thank you to our audience for joining us. Stay tuned for more discussions on the groundbreaking advancements in healthcare!