Faster and more accurate skin cancer diagnoses with AI and advanced imaging techniques

What are your scientific background?

My research career began at the University of Helsinki, where I did my PhD with a focus on new non-invasive hyperspectral imaging for skin cancer diagnostics. Our research group was built around my PhD project and involved an interdisciplinary team. Our publications were among the first in this field. Early in my career, I also conducted several clinical studies focusing on new treatment methods for skin cancers.
During these clinical projects, I became increasingly interested in skin pathology. After completing my specialist training in dermatology in 2015, I decided to specialise further and started specialist training in pathology. In September 2016, I moved to Sweden and started working at Clinical Pathology at Sahlgrenska University Hospital while continuing with postdoctoral research. My postdoctoral work shifted focus, including studies of mass spectrometry and studies involving other new imaging techniques. More recently, my research has expanded into artificial intelligence (AI), where I am involved in creating AI tools to improve diagnostic precision in pathology. Since 2021, I hold docentships at both the University of Helsinki and the Sahlgrenska Academy, University of Gothenburg. Since April 2023, I work as a senior lecturer at the Department of Biomedicine, University of Gothenburg.
 

What are the big scientific questions you are working with? Is there a vision for your research group?

My research group aims to develop advanced AI-powered solutions and innovative imaging techniques to improve the accuracy and efficiency of skin cancer diagnostics. By integrating AI into digital pathology, I aim to improve diagnostic accuracy and reveal novel histopathological characteristics, including prognostic markers and genetic changes. Our goal is to create "digital biomarkers" that can help doctors make a diagnosis earlier and better predict how a patient will respond to different treatments. This can lead to more personalised treatment and better outcomes for patients. In addition, we leverage cutting-edge technologies such as fluorescence confocal microscopy (FCM) and ToF-SIMS mass spectrometry in combination with AI. . FCM offers rapid point-of-care diagnostics, enabling faster pre- and intraoperative evaluations to reduce healthcare costs and improve patient outcomes. In addition, ToF-SIMS mass spectrometry focuses on lipidomics to identify early biomarkers of cancer progression and develop novel therapeutic targets. Together, these innovations aim to transform cancer care through faster, more accurate and personalised diagnostics.

Why did you start with research?

I come from an academic background, with my father being a professor of mathematics so academia has always been an integral part of my life, making it a natural step for me to start a research career. It was the excitement of discovering new innovations that sparked my passion for research. Life as a researcher is not boring!

What co-operations do you have today: with other scientific group, with industry, or clinical?

My research group is interdisciplinary and consists of several PhD students and postdoctoral researchers from different medical and natural sciences. The collaborations span multiple disciplines and internationally, integrating the expertise of clinicians in dermatology, surgery and pathology, as well as experts in computational science and chemistry. Our recent advances in artificial intelligence in pathology have led to the development of commercially viable AI tools designed to improve diagnostic precision in pathology.
 

Short description of your research for non-academics:

I work to improve skin cancer diagnosis and treatment using advanced technology. My research focuses on artificial intelligence (AI) to analyze digital images of skin tumors, for faster and more accurate diagnostics. We aim to identify aggressive cancers at an early stage, predict which patients are likely to develop metastases, and determine which treatments are most effective for each individual. I also study fluorescence confocal microscopy (FCM), which allows for immediate imaging intraoperatively, reducing delays and unnecessary procedures. In addition, I investigate how changes in cancer cell lipids can act as early warning signals and targets for new treatments. My goal is to make skin cancer care faster, more accurate, individualized and accessible for the benefit of patients and the healthcare system.