Novel molecular imaging methods can improve the specificity and accuracy of prostate cancer identification, which is more conducive to disease staging and intervention, and improve patient prognosis. At the same time, it allows earlier detection and understanding of the pathological characteristics of tumors. Although the advantages of new molecular imaging techniques for prostate cancer detection have gradually emerged, the appropriate scan time and the relationship between imaging and tumor characteristics are still unclear. More reliable, quantifiable, and repeatable examination methods are needed to evaluate. The occurrence and development of tumor heterogeneity have brought certain difficulties to prognosis and treatment. How to effectively identify at the early stage and avoid unnecessary invasive examinations are always urgent problems to be solved. In addition, in the consistency verification of pathological features and imaging features, how to select the most characteristic regions of the tumor itself may be the main obstacle, and it is more dependent on the role of novel molecular imaging. We would like to invite researchers from both universities and hospitals to discuss cutting-edge technological advances in all areas of cancer molecular imaging, such as novel imaging techniques, artificial intelligence, and radiomics.
We hope to discuss innovative and valuable imaging methods and new perspectives by studying prostate cancer diagnosis, exploring the pathological and physiological mechanisms of prostate cancer, and providing more information for treatment and prognosis. These may include but are not limited to the followings:
• Novel imaging technologies for prostate cancer
• Consistency verification of molecular imaging and pathology
• Biomarkers for early imaging of prostate cancer
• Molecular imaging methods for risk identification and prognostic assessment
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.
Novel molecular imaging methods can improve the specificity and accuracy of prostate cancer identification, which is more conducive to disease staging and intervention, and improve patient prognosis. At the same time, it allows earlier detection and understanding of the pathological characteristics of tumors. Although the advantages of new molecular imaging techniques for prostate cancer detection have gradually emerged, the appropriate scan time and the relationship between imaging and tumor characteristics are still unclear. More reliable, quantifiable, and repeatable examination methods are needed to evaluate. The occurrence and development of tumor heterogeneity have brought certain difficulties to prognosis and treatment. How to effectively identify at the early stage and avoid unnecessary invasive examinations are always urgent problems to be solved. In addition, in the consistency verification of pathological features and imaging features, how to select the most characteristic regions of the tumor itself may be the main obstacle, and it is more dependent on the role of novel molecular imaging. We would like to invite researchers from both universities and hospitals to discuss cutting-edge technological advances in all areas of cancer molecular imaging, such as novel imaging techniques, artificial intelligence, and radiomics.
We hope to discuss innovative and valuable imaging methods and new perspectives by studying prostate cancer diagnosis, exploring the pathological and physiological mechanisms of prostate cancer, and providing more information for treatment and prognosis. These may include but are not limited to the followings:
• Novel imaging technologies for prostate cancer
• Consistency verification of molecular imaging and pathology
• Biomarkers for early imaging of prostate cancer
• Molecular imaging methods for risk identification and prognostic assessment
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.
