Photon-Counting Computed Tomography in the Era of Precision Medicine: Technological Advances, Artificial Intelligence Integration, and Multidisciplinary Clinical Applications
Photon-Counting Computed Tomography (PCCT) has emerged as one of the most significant innovations in diagnostic imaging by introducing photon-counting detector technology capable of overcoming several intrinsic limitations of conventional energy-integrating detector computed tomography. This review analyzes the technological principles underlying PCCT, its integration with artificial intelligence, current clinical applications, implementation challenges, and future perspectives in precision medicine. A structured review of the contemporary scientific literature was conducted using internationally recognized biomedical databases and peer-reviewed publications focusing on detector technology, spectral imaging, quantitative imaging biomarkers, radiation dose optimization, and multidisciplinary clinical applications. The reviewed evidence consistently demonstrated that PCCT provides superior spatial resolution, improved contrast-to-noise ratio, enhanced spectral imaging, quantitative tissue characterization, and substantial reduction of electronic noise and beam-hardening artifacts while maintaining lower radiation exposure than conventional CT systems. The greatest clinical benefits were observed in cardiovascular imaging, oncology, neurology, pediatric radiology, pulmonary imaging, abdominal imaging, and musculoskeletal applications. The integration of artificial intelligence further enhances image reconstruction, automated segmentation, lesion detection, radiomics, workflow optimization, and quantitative image analysis, facilitating increasingly individualized diagnostic assessment. Despite important challenges related to acquisition costs, infrastructure requirements, protocol standardization, and broader clinical implementation, the available evidence supports Photon-Counting Computed Tomography as a transformative technology with the potential to redefine diagnostic imaging and strengthen the development of precision medicine across diverse healthcare systems.