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.
A. F. Ortega, Eileen Julliette Orantes Zacaríaz, M. B. Apráez et al.· International science journa...· 0 citations
Immune senescence has emerged as one of the principal biological mechanisms linking aging with the development and progression of autoimmune rheumatic diseases. Rather than representing a simple decline in immune function, aging induces profound remodeling of both innate and adaptive immunity, characterized by chronic low-grade inflammation, loss of immune tolerance, impaired cellular regeneration, mitochondrial dysfunction, telomere shortening, epigenetic alterations, and expansion of senescent immune-cell populations. The objective of this review was to analyze current evidence regarding the mechanisms through which immune senescence reshapes autoimmune rheumatic diseases and to examine its clinical implications, biomarkers, and emerging therapeutic strategies. A narrative literature review was conducted using the scientific method and included publications retrieved from PubMed/MEDLINE, Scopus, Web of Science, ScienceDirect, SpringerLink, Nature, Frontiers, and Wiley. The evidence consistently demonstrated that inflammaging, adaptive immune remodeling, and cellular senescence contribute to disease progression, increased susceptibility to infections, reduced vaccine responsiveness, cardiovascular complications, frailty, osteoporosis, sarcopenia, and diminished functional capacity. Conventional inflammatory biomarkers remain widely used; however, increasing attention has been directed toward multi-omics technologies, epigenetic clocks, mitochondrial biomarkers, proteomics, metabolomics, and immune-cell phenotyping for more accurate assessment of biological immune aging. Current therapeutic approaches continue to rely on disease-modifying antirheumatic drugs and biologic agents, while emerging interventions—including JAK inhibitors, mTOR modulation, senolytic therapies, microbiome-targeted strategies, and precision medicine—offer promising opportunities for future individualized management. Overall, immune senescence should be recognized as a fundamental component of autoimmune rheumatic diseases, providing important opportunities for improving diagnosis, risk stratification, therapeutic decision-making, and long-term clinical outcomes in aging populations.
