About this Research Topic
Efforts to improve cancer imaging technologies are crucial for diagnosing and treating the disease effectively. This transition from experimental to clinical use requires bridging the gap between research findings and practical application in patient care. By advancing these technologies, such as MRI, PET scans, and advanced optical imaging techniques, healthcare professionals can enhance early detection, precision in treatment planning, and monitoring of cancer progression. However, this progression involves overcoming various challenges, including ensuring the reliability, accessibility, and cost-effectiveness of these imaging modalities. Collaborative efforts between researchers, clinicians, and industry partners are essential to streamline this translation process and facilitate the integration of cutting-edge imaging technologies into routine clinical practice, ultimately improving outcomes for cancer patients.
This Research Topic invites manuscripts exploring the validation and introduction of bench to bedside imaging-based technologies in precision oncology (diagnosis, prognosis and prediction of clinical outcomes), including:
- Validation and testing of imaging-based technologies for cancer screening and detection
- The integration of validated imaging-based technologies into clinical practice
- Validation of computational AI models in for advances in the diagnosis in oncology
- Imaging Biobanks/ database
We welcome submissions of several article types including but not limited to: Original Research, Reviews, Hypothesis and Theory, and Data Reports.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
This Research Topic invites manuscripts exploring the validation and introduction of bench to bedside imaging-based technologies in precision oncology (diagnosis, prognosis and prediction of clinical outcomes), including:
- Validation and testing of imaging-based technologies for cancer screening and detection
- The integration of validated imaging-based technologies into clinical practice
- Validation of computational AI models in for advances in the diagnosis in oncology
- Imaging Biobanks/ database
We welcome submissions of several article types including but not limited to: Original Research, Reviews, Hypothesis and Theory, and Data Reports.
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Keywords: Oncology, Imaging, AI, Functional Imaging, Molecular probes, PET Imaging, CT, MR, Advanced Imaging
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
