Jadvar Hossein
Department of Radiology, Keck School of Medicine of USC, University of Southern California, 2250 Alcazar Street, CSC 102, Los Angeles, CA 90033, USA.
PET Clin. 2015 Apr;10(2):255-63. doi: 10.1016/j.cpet.2014.12.007. Epub 2015 Jan 22.
Many standard nonimaging-based prediction tools exist for prostate cancer. However, these tools may be limited in individual cases and need updating based on the improved understanding of the underlying complex biology of the disease and the emergence of the novel targeted molecular imaging methods. A new platform of automated predictive tools that combines the independent molecular, imaging, and clinical information can contribute significantly to patient care. Such a platform will also be of interest to regulatory agencies and payers as more emphasis is placed on supporting those interventions that have quantifiable and significant beneficial impact on patient outcome.
目前有许多基于非成像技术的前列腺癌标准预测工具。然而，这些工具在个别病例中可能存在局限性，并且需要根据对该疾病潜在复杂生物学的深入理解以及新型靶向分子成像方法的出现进行更新。一个结合独立分子、成像和临床信息的自动化预测工具新平台可以为患者护理做出重大贡献。随着越来越强调支持那些对患者预后有可量化且显著有益影响的干预措施，这样的平台也将受到监管机构和支付方的关注。
