1.MRI features of triple-negative breast cancer and correlation with Ki-67 index in Uygur women
Renkan GAO ; Hui XU ; Yushuang LIANG
Chinese Journal of Medical Imaging Technology 2018;34(3):362-366
Objective To investigate MRI findings of triple-negative breast cancer (TNBC) and correlation with Ki-67 index in Uygur women.Methods Totally 97 patients with pathologically confirmed TNBC were enrolled.Among them,28 patients were Uygur nationality (Uygur group;28 lesions) and 69 were Han nationality (Han group;70 lesions).MRI features of the two groups were observed and compared,and the correlation between MRI findings and Ki-67 index in Uygur group was analyzed.Results The pathological type of TNBC in Uygur group and Han group was both mainly invasive ductal carcinoma (grade 3).There was no statistical difference of Ki-67 index nor ADC value between the two groups (both P>0.05).The Uygur patients were younger than Han patients (P<0.05) and maximum diameter of lesions and early enhancement rate in Uygur group were higher than those in Han group (all P<0.05).The margin and enhancement features of lesions were statistically different between the two groups (both P<0.05).The dominated type of time-signal intensity curve (TIC) in Uygur group was wash-out type,while in Han group was plateau type (P<0.001).The Ki-67 index was positively correlated with tumor shape and TIC type in Uygur group (r=0.464,0.606,both P<0.05).Conclusion MRI features of Uygur women with TNBC is somewhat different from Han women,and part features are correlated with Ki-67 index.
2. Consistency of ALK Ventana-D5F3 immunohistochemistry interpretation in lung adenocarcinoma among Chinese histopathologists
Lin LI ; Liping ZHANG ; Yuchen HAN ; Weiya WANG ; Yan JIN ; Qingxin XIA ; Yueping LIU ; Jin XIANG ; Chao LIU ; Shanshan LU ; Wei WU ; Zhen CHEN ; Juan PANG ; Yanfeng XI ; Yushuang ZHENG ; Dongmei GU ; Jun FAN ; Xiaona CHANG ; Weiwei WANG ; Liang WANG ; Zhihong ZHANG ; Xiaochu YAN ; Yi SUN ; Ji LI ; Feng HOU ; Jingyuan ZHANG ; Rongfang HUANG ; Jianping LU ; Zheng WANG ; Yongbin HU ; Hongtu YUAN ; Yujie DONG ; Lu WANG ; Zhenyu KE ; Jingshu GENG ; Lei GUO ; Jing ZHANG ; Jianming YING
Chinese Journal of Pathology 2019;48(12):921-927
Objective:
To understand the consistency of ALK Ventana-D5F3 immunohistochemistry (IHC) interpretation in Chinese lung adenocarcinoma among histopathologists from different hospitals, and to recommend solution for the problems found during the interpretation of ALK IHC in real world, with the aim of the precise selection of patients who can benefit from ALK targeted therapy.
Methods:
This was a multicenter and retrospective study. A total of 109 lung adenocarcinoma cases with ALK Ventana-D5F3 IHC staining were collected from 31 lung cancer centers in RATICAL research group from January to June in 2018. All cases were scanned into digital imaging with Ventana iSCANcoreo Digital Slide Scanning System and scored by 31 histopathologists from different centers according to ALK binary (positive or negative) interpretation based on its manufacturer′s protocol. The cases with high inconsistency rate were further analyzed using FISH/RT-PCR/NGS.
Results:
There were 49 ALK positive cases and 60 ALK negative cases, confirmed by re-evaluation by the specialist panel. Two cases (No. 2302 and No.2701) scored as positive by local hospitals were rescored as negative, and were confirmed to be negative by RT-PCR/FISH/NGS. The false interpretation rate of these two cases was 58.1% (18/31) and 48.4% (15/31), respectively. Six out of 31 (19.4%) pathologists got 100% accuracy. The minimum consistency between every two pathologists was 75.8%.At least one pathologist gave negative judgement (false negative) or positive judgement (false positive) in the 49 positive or 60 negative cases, accounted for 26.5% (13/49), 41.7% (25/60), respectively, with at least one uncertainty interpretation accounted for 31.2% (34/109).
Conclusion
There are certain heterogeneities and misclassifications in the real world interpretation of ALK-D5F3 IHC test, which need to be guided by the oncoming expert consensus based on the real world data.