Editor's note: Artificial intelligence (AI) is changing the diagnosis and treatment model of urological tumors, especially in terms of intelligent imaging and intelligent pathology, and is expected to become a powerful assistant for clinicians. Dr. Vasileios Sakalis, Consultant at Hippokration General Hospital, Thessaloniki, reported a review of the application of AI in urological tumors at this conference, and in an interview with " Oncology Frontier " In the on-site interview, he shared more views on AI application scenarios and other topics.Vasileios Sakalis
MSc, PhD, FEBU, FRCS
Consultant at Hippokration General Hospital, Thessaloniki
Oncology Frontier：How accurate do you think current AI is in the field of urological cancers?
Dr. Vasileios Sakalis: Artificial intelligence has reached a remarkable level of accuracy, especially when utilizing imaging modalities like MRI to extract features. The precision and sensitivity of AI models are particularly high in identifying malignancies. However, the accuracy slightly decreases when dealing with more complex data extraction, such as prognostic models or predicting Gleason scores.
Oncology Frontier：AI can use quantitative imaging properties to understand and effectively identify tumors in images. Can it currently be used in clinical practice to assist doctors in diagnosis?
Dr. Vasileios Sakalis: AI’s capability to interpret quantitative imaging properties has already been integrated into clinical practice, marking a significant advancement. Through machine learning and deep learning techniques, AI can uncover image features invisible to the human eye, merging them with clinical data to produce highly accurate diagnostic information.
Oncology Frontier： In terms of therapeutic areas, where can artificial intelligence be used in urological oncology?
Dr. Vasileios Sakalis: AI models are being actively utilized and assessed across all urological cancers, with a particular focus on prostate, kidney, and bladder cancers due to their prevalence. While efforts are ongoing to develop AI models for rarer cancers, the evidence supporting AI’s effectiveness is most robust in prostate cancer research, underscored by the substantial number of systematic reviews available.
Oncology Frontier：Due to the heterogeneity of urological tumors, the prognosis of different patients varies greatly. How to use AI to better predict patients, thereby continuously adjusting treatment plans and improving long-term survival?
Dr. Vasileios Sakalis: The European Association of Urology is exploring AI’s potential to create predictive models that can personalize treatment. Leveraging big data, AI can generate specific outcomes and evidence tailored to individual patients or patient groups, aiming to refine treatment approaches based on precise predictive insights.
Oncology Frontier：A number of research developments were announced at this conference. Which ones are you most interested in?
Dr. Vasileios Sakalis: Beyond my keen interest in AI and big data analysis for urological conditions, my focus extends to the study of male lower urinary tract symptoms and neurogenic bladder. I am actively involved with the European Association of Urology, particularly in the male LUTS panel, where my primary interest lies in functional urology.
