Licurse Mindy Y, Lalevic Darco, Zafar Hanna M, Schnall Mitchell D, Cook Tessa S
Department of Radiology, Hospital of the University of Pennsylvania, 3400 Spruce Street, 1 Silverstein Building, Philadelphia, PA, 19146, USA.
Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
J Digit Imaging. 2017 Apr;30(2):156-162. doi: 10.1007/s10278-016-9912-y.
An automated radiology recommendation-tracking engine for incidental focal masses in the liver, pancreas, kidneys, and adrenal glands was launched within our institution in July 2013. For 2 years, the majority of CT, MR, and US examination reports generated within our health system were mined by the engine. However, the need to expand the system beyond the initial four organs was soon identified. In July 2015, the second phase of the system was implemented and expanded to include additional anatomic structures in the abdomen and pelvis, as well as to provide non-radiology and non-imaging options for follow-up. The most frequent organs with incidental findings, outside of the original four, included the ovaries and the endometrium, which also correlated to the most frequently ordered imaging follow-up study of pelvic ultrasound and non-imaging follow-up study of endometrial biopsies, respectively. The second phase expansion has demonstrated new venues for augmenting and improving radiologist roles in optimal communication and management of incidental findings.
2013年7月,我们机构推出了一个用于跟踪肝脏、胰腺、肾脏和肾上腺偶发局灶性肿块的自动化放射学推荐跟踪引擎。两年来,该引擎挖掘了我们医疗系统内生成的大部分CT、MR和超声检查报告。然而,很快就发现有必要将该系统扩展到最初的四个器官之外。2015年7月,该系统的第二阶段得以实施,并扩展到包括腹部和骨盆的其他解剖结构,同时还提供非放射学和非成像的随访选项。在最初的四个器官之外,发现偶然病变最频繁的器官包括卵巢和子宫内膜,这也分别与盆腔超声最常进行的成像随访研究和子宫内膜活检最常进行的非成像随访研究相关。第二阶段的扩展展示了在优化偶然发现的沟通和管理方面增强和改善放射科医生作用的新途径。