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18F-FDG PET/CT显像“uWS-MI”医学影像处理软件临床应用的可行性分析

Feasibility study on clinical application of 18F-FDG PET/CT imaging “uWS - MI” medical image processing software

  • 摘要: 目的:通过与美国GE公司研发的“GE AWS46工作站”对比,评估上海联影医疗科技有限公司研发的PET/CT后处理工作站“uWS-MI”的应用有效性,并评价其稳定性、可靠性及数据管理等是否满足临床要求。方法:选择30例恶性肿瘤患者,治疗前后均采用美国GE公司生产的Discovery VCT 64型PET/CT仪进行18F-FDG PET/CT显像。在“uWS-MI”和“GE AWS46”工作站上分别采用半自动一键式分割1个典型病灶,由两名同时具有核医学和CT上岗证的核医学科医师采用“满意”“一般”“不满意”3分法独立评价其分割效果(肿瘤的完整性、轮廓的准确性)。该两名医师基于肿瘤分割计算每例患者初次PET/CT显像时1个典型病灶的体积、标准摄取值(standard uptake value, SUV)最大值、SUV平均值、SUV阈值、SUV峰值、总葡萄糖酵解量(total lesion glycolysis,TLG)。同时由该两名医师分别评价“uWS-MI”医学影像处理软件的交互性和工作流,以及系统的稳定性、可靠性和数据管理是否满足临床要求。结果:两名医师独立采用“uWS-MI”和“GE AWS46”对病灶分割效果的评价差异均无统计学意义。“uWS-MI”和“GE AWS46”基于肿瘤分割计算的每例患者初次PET/CT显像时1个典型病灶的体积、SUV最大值、SUV平均值、SUV阈值、TLG差异均无统计学意义;“uWS-MI”组SUV峰值显著大于“GE AWS46”组(t=3.36,P=0.002)。两名医师对“uWS-MI”医学影像处理软件的交互性和工作流,系统的稳定性、可靠性、数据管理的满意率均为100%。结论:“uWS-MI”医学影像处理软件对病灶的分割效果较理想,获取的病灶体积及SUV数据均能用于临床诊断,且系统及界面应用满意度较好,可在临床推广应用。

     

    Abstract: Objective:By comparing with “GE AWS46 workstation” developed by GE Company in the United States, the effectiveness of “uWS-MI” medical imaging software developed by Shanghai United Imaging Healthcare Co., Ltd. was evaluated, and whether its stability, reliability, and data management met the clinical requirements was assessed. Methods:A total of 30 patients with malignant tumor were analyzed by the 18F-FDG PET/CT imaging (Discovery VCT 64, GE, U.S.) before and after the treatment. On “uWS-MI” and “GE AWS46” workstations, a typical lesion was segmented by semi-automatic one-click method. Two nuclear medicine physicians, who both had the qualifications of nuclear medicine and CT certification, conducted a blind evaluation using the 3-point method (satisfaction, general, and unsatisfactory) for the evaluation of the tumor completeness and contouring accuracy. The volume, standard uptake value (SUV) maximum, SUV average, SUV threshold, SUV peak, total lesion glycolysis (TLG) value of a typical tumor lesion in primary PET/CT imaging were calculated based on tumor segmentation. At the same time, the two physicians evaluated the interaction and workflow of “uWS-MI” medical image processing software, as well as whether the stability, reliability, and data management of the system met the clinical requirements. Results:There was no significant difference in the evaluation of lesion segmentation between the two physicians using “uWS-MI” and “GE AWS46” independently. The primary PET/CT images from “uWS-MI” medical imaging software and “GE AWS46” workstation based on tumor segmentation calculation showed that a typical tumor’s volume, SUV maximum, SUV average, SUV threshold, and TLG were not significantly different, but SUV peak from “uWS-MI” medical imaging software was greater than that from “GE AWS46” workstation (t=3.36, P=0.002). The two physicians respectively evaluated the interaction and workflow of “uWS-MI” medical image processing software, and the stability, reliability and data management of the system. The satisfaction rates of the evaluation were all 100%. Conclusions:The segmentation effect of “uWS-MI” medical image processing software on lesions, as well as the acquired lesion volume and SUV data could be used for clinical diagnosis, and the interaction and workflow of the software are satisfactory, which can be popularized and applied in clinical practice.

     

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