Quantitative analysis of dynamic contrast enhancement MRI between orbital lymphoma and inflammatory mass based on different regions of interest selection
机构:[1]Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing 100730, Peoples R China医技科室放射科首都医科大学附属北京同仁医院首都医科大学附属同仁医院[2]Capital Med Univ, Clin Ctr Eye Tumors, Beijing 100730, Peoples R China
PurposeTo assess the value of dynamic contrast enhanced MRI (DCE-MRI) quantitative parameters in differentiating orbital lymphoma from inflammatory mass based on different regions of interest selection.Materials and methodsThe study population consists of 83 patients with histologically proven orbital masses (39 lymphomas and 44 inflammatory masses). Two methods of selecting regions of interest (ROI) were compared to obtain quantitative parameters: (a) a round or ovoid region of 8 mm(2) covering the most enhanced area, and (b) covering the lesion but excluding areas of hemorrhage or necrosis on the slice with the largest tumor area. Parametric maps were obtained for quantitative parameters including K-trans, V-e and K-ep. Quantitative parameters that distinguish orbital lymphoma from orbital inflammatory mass were analyzed by receiver operating characteristic curves (ROC).ResultsK(ep) values (ROI selection method a) were significantly higher in orbital lymphoma compared with orbital inflammatory mass (p = 0.003) and V-e values (ROI selection method a and b) of orbital lymphoma were significantly lower than orbital inflammatory mass (p = 0.01, p = 0.006, respectively). K-ep (ROI selection method a) could distinguish lymphoma from inflammatory mass with sensitivity (97.4%, 38/39), specificity (52.3%, 23/44), positive predictive value (64.4%, 38/59), negative predictive value (95.8%, 23/24) and accuracy (73.5%, 61/83). V-e (ROI selection method a) could distinguish lymphoma from inflammatory mass with sensitivity (54.5%, 24/44), specificity (79.5%, 31/39), positive predictive value (75%, 24/32), negative predictive value (60.8%, 31/51) and accuracy (66.3%, 55/83). V-e (ROI selection method b) distinguished lymphoma from inflammatory mass with sensitivity (48.7%, 21/44), specificity (86.4%, 34/39), positive predictive value (80.8%, 21/26), negative predictive value (59.6%, 34/57), and accuracy (66.3%, 55/83). The pairwise comparison of the AUCs among these significant quantitative parameters showed no difference in distinguishing orbital lymphoma from orbital inflammatory mass (Z = 1.066, p = 0.286, Z = 0.998, p = 0.318 and Z = 0.370, p = 0.711, respectively).ConclusionQuantitative parameters can differentiate orbital lymphoma from inflammatory mass. ROI selection methods had no definite effect on the diagnostic performance.
基金:
Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support [ZYLX201704]; High Level Health Technical Personnel of Bureau of Health in Beijing [2014-2-005]; Priming Scientific Research Foundation for the Senior Researcher in Beijing Tongren Hospital, Capital Medical University [2016-YJJ-GGL-011]
第一作者机构:[1]Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing 100730, Peoples R China[2]Capital Med Univ, Clin Ctr Eye Tumors, Beijing 100730, Peoples R China
通讯作者:
通讯机构:[1]Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing 100730, Peoples R China[2]Capital Med Univ, Clin Ctr Eye Tumors, Beijing 100730, Peoples R China
推荐引用方式(GB/T 7714):
Song Liyuan,Wang Xinyan,Guo Jian,et al.Quantitative analysis of dynamic contrast enhancement MRI between orbital lymphoma and inflammatory mass based on different regions of interest selection[J].CHINESE JOURNAL OF ACADEMIC RADIOLOGY.2020,3(1):41-49.doi:10.1007/s42058-020-00025-3.
APA:
Song, Liyuan,Wang, Xinyan,Guo, Jian&Xian, Junfang.(2020).Quantitative analysis of dynamic contrast enhancement MRI between orbital lymphoma and inflammatory mass based on different regions of interest selection.CHINESE JOURNAL OF ACADEMIC RADIOLOGY,3,(1)
MLA:
Song, Liyuan,et al."Quantitative analysis of dynamic contrast enhancement MRI between orbital lymphoma and inflammatory mass based on different regions of interest selection".CHINESE JOURNAL OF ACADEMIC RADIOLOGY 3..1(2020):41-49