1.Summary and analysis on external quality assessment results of clinical immunology during 2009 - 2013
International Journal of Laboratory Medicine 2015;(6):801-802,805
Objective To perform the summary and analysis on the external quality assessment(EQA) results of the clinical im‐munology during 2009 - 2013 to find out the possible problems existing in the laboratory work of the clinical immunology for con‐tinuously improve the quality of clinical immunological detections and ensuring the accuracy of clinical immunological test results . Methods The results of the external quality assessment in the clinical Immunology participating in the National Center for Clinical and Laboratory and the Guangxi Center for Clinical Laboratory during 2009 - 2013 were performed the statistical analysis and sum‐mary .Results 600 samples were detected during these 5 years .The performance was worst in 2012 ,the annual coincidence rate of the results was 98% ;and which in other 4 years was 100% ;each 1 sample of result in the two items of anti‐HCV and anti‐TP was unconformity during these 5 years ,the total coincidence rate was 98 .6% ;the total coincidence rates of HBsAg ,HBsAb ,HBeAg , HBeAb ,HBcAb and anti‐HIV were 100% .Conclusion By participating in the external quality assessment of the clinical immunolo‐gy and retrospectively analyzing the results ,the possible problems would be found and some effective improvement measures could be formulated in time for improving the quality of examinations and ensuring to provide reliable laboratory data for clinic .
2.Virtual touch tissue imaging quantification in differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules
Songnian WU ; Jiandi HE ; Tianan JIANG ; Liyun ZHONG ; Xinfa ZHANG
Chinese Journal of Ultrasonography 2016;25(7):573-578
Objective To observe the value of virtual tough tissue imaging quantification (VTIQ) in differential diagnosis of thyroid imaging reporting and data system(TI-RADS) 4 thyroid nodules.Methods A total of 185 patients with 192 TI-RADS 4 nodules were included in this study.The nodules were divided into three groups according to the maximum size as follows:Group Ⅰ,the maximum size≤0.6 cm;Group Ⅱ,0.6 cm< the maximum size≤ 1.0 cm;Group Ⅲ,the maximum size > 1.0 cm.Shear wave velocities (SWV) of nodules were measured by means of VTIQ technique.With pathological diagnosis as the gold standard,SWV value of benign and malignant nodules were analyzed and ROC curve was drawn to assess the diagnostic efficiency.Results By the ROC curve test,at SWV cut-off values of 2.44 m/s for group Ⅰ and group Ⅱ,2.49 m/s for group Ⅲ,the sensitivity were 79.0 %,76.0 %,88.6%,specificity were 88.6%,89.5 %,93.7 %,accuracy were 83.5 %,81.8 %,90.1%,Youden index were 0.68,0.66,0.82,respectively.Conclusions VTIQ can reflect the hardness of TI-RADS 4 nodules,the value of the differential diagnosis of such nodules is high,convenient,noninvasive and not limited by the size of nodules.
3.Computer-aided diagnosis for the detection of the pulmonary nodules on digital chest radiography in lung cancer screening
Yan XU ; Daqing MA ; Wen HE ; Xinfa MA
Chinese Journal of Radiology 2010;44(11):1157-1160
Objective To evaluate the value of computer-aided detection (CAD) system for pulmonary nodule detection using digital chest radiography in lung cancer screening. Methods One hundred consecutive digital chest radiographs from 6280 outpatients for lung cancer screening were independently reviewed by a thoracic radiologist and a computer-aided pulmonary nodule detection system.The radiographs were also reviewed by two experienced thoracic radiologists and the true nodules confirmed by two radiologists with reference to the CT images were marked and stored as a gold standard in the CAD system. The sensitivity and false positive of the radiologist and the CAD system for the detection of nodules on digital chest radiographs were compared. Results Ninety-five and 304 nodules were identified by radiologist and the CAD system, respectively. Of 134 nodules marked as true nodules by experienced radiologists, 82 (61.2%) and 105 (78. 4% ) nodules were identified by the radiologist and the CAD,respectively. The radiologist missed 35 true nodules which were only detected by CAD. The CAD system missed 10 true nodules which were only detected by radiologist. One hundred and twelve (83.6%) nodules were identified by radiologist with the CAD system. One hundred and ninety-nine nodules identified by CAD were false-positive with a rate of 2. 0 ( 199/100 ) per case. Conclusion Combining review of digital radiographs by radiologist with CAD system can improve the detection of pulmonary nodules in lung cancer screening.