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Objective:To investigate the accuracy and reproducibility of a new method, Automatic Measurement of Arterial Stiffness(AMAS) system, for arterial stiffness automatic measurement based on regional pulse wave velocity (PWV).Methods:A total of 30 hypertensive patients who were hospitalized in the Department of Cardiology in Tangdu Hospital, Air Force Military Medical University from September 1 to 30, 2019 were enrolled as hypertensive group, while 30 healthy participants at the same time were collected as healthy group. Carotid-femoral PWV (cfPWV) was measured in all subjects by two independent observers using the conventional manual method and the AMAS system. The measurements were compared and the agreement was analyzed.Results:There was no significant difference of cfPWV between AMAS system and the manual method, and the intraclass correlation coefficient was 0.953 (95% CI=0.922-0.971). Bland-Altman plots showed good agreement [mean difference: -(0.08±0.40)m/s; limit of agreement: -0.87-0.71 m/s]. Time consumption for cfPWV measurement using the AMAS system was significantly less than that of conventional manual method, saving about 70% of the time. The cfPWV measured by AMAS showed good intra- and inter-observer reproducibility. Conclusions:AMAS system is accurate and reproducible in measuring arterial stiffness. It may provide a noninvasive, rapid, reliable approach for arterial stiffness evaluation in clinical settings.
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Objective To determine the consistency of urogenital hiatus ( U H ) data between the semi‐automatic measurement and manual measurement using transperineal pelvic floor ultrasonography . Methods Total of 286 three‐dimensional images of minimal U H dimension were obtained . And they were divided into study group ( 100 images) and test group ( 186 images) randomly . T hree experts traced and created the w hole profile of the U H of those images in the study group by M AT LAB . T hen the semi‐automatic software was obtained through machine learning algorithms . In the test group , 6 parameters of U H ( including anterioposterior diameter , transverse diameter ,circumference , area ,left and right levator urethral gap distance) were measured by two experts ( D 1 and D2 ) both manually and semi‐automatically . T he time experts spent on measuring was also recorded and compared . Results T he time used for semi‐automatic measurement was significantly shorter than that for manual measurement [ ( 7 .49 ± 1 .51 ) s vs ( 42 .42 ± 11 .08) s ,( 7 .52 ± 1 .37) s vs ( 43 .45 ± 9 .09) s for D1 and D2 , t ＝ －12 .09 ,－13 .64 ,all P＝0 .00] . T he Pearson correlation coefficients between semi‐automatic and manual measurements of 6 parameters were 0 .857 －0 .985 ( P ＜ 0 .01) ,0 .853 －0 .979 ( P ＜ 0 .01 ) in D1 and D2 ,respectively . T he interclass correlation coefficients ( ICC) of six parameters were ranged from 0 .846 －0 .985 for D1 and 0 .843～0 .979 for D2 ( all P ＜ 0 .01 ) . T he Bland Altman plot also showed good agreement between two methods . Conclusions Intellectual recognition and semi‐automatic measurement has simplified the process for U H measurement ,and it is proved to be a reliable and timesaving method that is practical for clinical use .
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Objective To investigate the feasibility of the automatic cystocele severity grading software for quantitative evaluation of prolapse of bladder posterior wall by transperineal ultrasound . Methods One hundred and seventy transperineal ultrasound video clips were recorded when the female patients performing the Valsalva maneuver and those clips were divided into training group ( 85 cases) and test group ( 85 cases) randomly ,then the ralated structures of the images from the training group offline were marked . Through machine learning algorithm ,the computer had learned and was able to analyzed the marking information ,then the automatic cystocele severity grading software was obtained . And later the software was ran to mark the structures and get the cystocele severity grading in the images from the test group . Meanwhile , the same structures of the same images manually were marked and after an interval of more than two weeks the process were repeated by 3 doctors . Finally the grading results obtained from the software and the measurers of the 3 doctors were compared . Results The intelligent identification and automatic measurement software obtained from the machine learning algorithm was able to identify the related structures . The grading results of each measurer were of good consistency ( κ :0 .72 －0 .78 ;ICC :0 .980－0 .990) . The grading results between different measurers were of good consistency ( κ :0 .65－0 .75 ;ICC :0 .985－0 .992) . The grading results between automatic software and three different measurers were of good consistency ( κ :0 .63－0 .67 ;ICC :0 .967－0 .969 ; r ＝0 .936 ,0 .943 ,0 .936 ,all P ＜0 .01) . Conclusions The automatic cystocele severity grading software is able to identify the related structures in the images and reliable to apply the software in pelvic floor ultrasound .
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Objective To explore whether Cdc42 is an independent influence factor in regulating the migration of A549 cells by using quantitative measurement method,and to verify the effectiveness of an automatic measurement and calculation method for in vitro cell migration assay.Methods Cdc42 was overexpressed in human lung adenocarcinoma A549 cell line,and then in vitro scratch assay was applied to evaluate the migration of the cells.Different methods were used to measure the images acquired at different time points for quantitative analysis.Accuracy and repeatability of different measurement methods were analyzed.Results The results showed that overexpression of Cdc42 alone significantly advanced the migration of A549 cells (P＜0.05).The new method is efficient,accurate and reproducible as compared to manual measurement,and has significant advantages in target recognition and noise removal as compared to the existing measurement method in Image Pro Plus 6.0.Conclusions Over expression of Cdc42 significantly increased A549 cell migration ability in vitro.The new method can realize the automatic quantitative analysis of cell migration in vitro.
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Objective In order to improve the accuracy and efficiency of the measurement of range of motion (ROM) of human lower limbs and simplify process of ROM measurement,an automatic measurement of ROM of human lower limbs based on Kinect technique was proposed and tested in this study.Methods Fifty examinee were randomly divided into 5 groups,namely groups a,b,c,d and e,respectively,each group had 10 members.Using the human skeleton tracking technology from Kinect,the positions of the examinee's lower limbs were captured and tracked by processing the depth data of lower limbs' key joints.Then the information of ROM of hip and knee was output on human-computer interaction interface in real-time.By comparison with traditional manual measurement results,the accuracy of automatic measuring method could be verified.Meanwhile,with the aid of speech recognition and output technology,the mode of warning information transfer and the way of subject switch were optimized.Results According to the method of Grubbs-test and t-test,the ROM values | t | from the subjects' hip abduction (t =0.57,P =0.597),hip adduction (t =0.52,P =0.621),hip anteflexion (t =1.01,P =0.371),hip postextension (t =0.12,P =0.902),hip external rotation (t =0.00,P =1.000),hip internal rotation (t =0.34,P =0.753),knee flexion and extension (t =1.12,P =0.280) all were under the threshold value t0.025 (4) =2.776 on the premise of a level of significance α =0.05,which indicated that there was no significant difference between measured results and expected values(P ＞ 0.05).Conclusion The automatic measurement of ROM of lower limbs can be realized which can improve the measurement accuracy,simplify the measurement process and enhance the practicability of ROM of lower limbs measurement.