Scientists have developed an innovative AI-enhanced imaging platform, OC-PAM, for non-invasive, label-free longitudinal monitoring of cancer organoids and spheroids. This advancement addresses the limitations of conventional imaging methods, which often struggle with high-content analysis over time, particularly for patient-derived models. Led by researchers from the Medical University of Vienna and Politecnico di Torino, OC-PAM combines optical coherence microscopy and photoacoustic microscopy to track treatment responses in real-time. The platform effectively evaluates organoid viability, monitors responses to chemotherapy, and identifies drug-tolerant persister cells. Additionally, it employs machine learning techniques for radiomics-based analysis, offering high classification performance in assessing organoid viability. By enabling detailed studies of drug resistance and rare cell populations, OC-PAM not only advances cancer biology but also supports personalized approaches to oncology and accelerates drug development efforts. This innovative technology significantly enhances the capability for cancer research and pharmacological exploration.
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