Intra- and inter-observer variability of uterine measurements with three-dimensional ultrasound and implications for clinical practice

2015 ◽  
Vol 31 (4) ◽  
pp. 557-564 ◽  
Author(s):  
Sotirios H. Saravelos ◽  
Tin-Chiu Li
2017 ◽  
Vol 33 (7) ◽  
pp. 515-518 ◽  
Author(s):  
Jessica Subirá ◽  
Jose Alberola-Rubio ◽  
María Jose Núñez ◽  
Alicia Marzal Escrivá ◽  
Antonio Pellicer ◽  
...  

2002 ◽  
Vol 23 (7) ◽  
pp. 655-660 ◽  
Author(s):  
Justin Greisberg ◽  
John Drake ◽  
Joseph Crisco ◽  
Christopher DiGiovanni

Gastrocnemius contracture may be a significant cause of many foot disorders. Gastrocnemius tension can be estimated clinically by measuring maximum ankle dorsiflexion during full knee extension. Such measurements, when made with currently available goniometric devices, are subject to high levels of intra- and inter-observer variability. We have designed a device to more consistently measure ankle dorsiflexion, using three dimensional tracking sensors on the leg and foot. The applied dorsiflexion torque is kept constant by a computer, and the computer also monitors hindfoot position to maintain a neutrally aligned foot during testing. Repeated measurements on 26 feet were taken to determine the consistency of the device. The correlation coefficient for the measurements was 0.96, indicating very low intra- observer variability. The standard deviation of the repeated measures was 2°. Based on the 95% confidence interval, the device can be considered accurate to within 4°. Given this accuracy, this instrument could be used to assess gastrocnemius tension, its role in foot pathology, and the effectiveness of surgical lengthening. Compared to other currently available measuring devices, this instrument is the most reliable in estimating ankle dorsiflexion, since it is capable of controlling hindfoot position and applied dorsiflexion torque, and it can be easily constructed by other laboratories.


2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
M Previtero ◽  
N Ruozi ◽  
G Sammarco ◽  
D Azzolina ◽  
R M Tenaglia ◽  
...  

Abstract BACKGROUND New automated approaches for left heart chamber quantification based on adaptive analytics algorithms have been introduced for both two- (2DE) and three-dimensional (3DE) echocardiography. These algorithms measure a left ventricular ejection fraction (LVEF) and reduce the intra- and inter-observer variability associated with the conventional manual tracing of LV endocardial borders. However, the clinical utility of these algorithms in the sudden cardiac death (SCD) risk stratification of patients with organic heart disease remains to be clarified. PURPOSE We sought to test the feasibility and the accuracy of two automated algorithms that measure 2DE and 3DE LVEF in patients with impaired LV systolic function and to define the cut-off values for fully automated 2DE and 3DE LVEF that could predict major arrhythmic events (MAE). We wanted also to assess the feasibility of replacing manual 2DE and semi-automated (SA) 3DE LVEF with fully-automated (FA) 2DE and 3DE LVEF respectively, in the stratification of high arrhythmic risk patients. METHODS We prospectively enrolled 240 patients (63 ± 13 years, 81% men) with both ischemic and non-ischemic cardiomyopathy with 2DE LVEF < 50%, no previous MAE or coronary artery revascularization < 90 days, after at least 3 months of optimal medical therapy for heart failure. MAE were defined as SCD, resuscitated cardiac arrest (CA), ventricular fibrillation, sustained ventricular tachycardia and appropriate ICD shocks. The risk detection cut-off values for 2DE and 3DE FA LVEF were computed using the maximally selected rank statistics method. In order to predict the risk of MAE we created four different risk models, including both clinical characteristics (age, NYHA class, aetiology of the LV dysfunction) and imaging-derived data (2DE manual LVEF, 2DE FA LVEF, 3DE SA LVEF and 3DE FA LVEF), analyzed by a ROC curve. RESULTS During a 27 ± 25months follow-up period, 31 patients (13%) presented MAE including SCD (n= 22; 9%), resuscitated CA (n = 3; 1%) and appropriate ICD shocks (n = 6; 2%). Both 2DE and 3DE FA LVEF showed high feasibility (92% and 95%, respectively), and good agreement with conventional LVEF (2DE mean difference 4 ± 7%, and 3DE mean difference 4 ± 7%). We identified two FA LVEF cut-offs for the MAE detection: 2DE <39% (p = 0.006) and 3DE <37% (p = 0.005). The model including the 2DE FA LVEF showed an area under the curve (AUC) larger than the one including conventional 2DE LVEF (0.83 vs 0.80). Conversely, the AUC obtained with FA 3DE LVEF model was slightly lower than the one obtained using SA 3DE LVEF model (0.80 vs 0.84). CONCLUSIONS Both 2DE and 3DE FA LVEF are feasible and accurate alternative to the conventional (manual) or SA endocardial border tracing. The use of specific FA 2DE LVEF cut-off values showed a comparable predictive power in the MAE risk stratification compared to the conventional one with the advantage of very low intra- and inter-observer variability.


2021 ◽  
Vol 11 (2) ◽  
pp. 844
Author(s):  
Oscar J. Pellicer-Valero ◽  
Victor Gonzalez-Perez ◽  
Juan Luis Casanova Ramón-Borja ◽  
Isabel Martín García ◽  
María Barrios Benito ◽  
...  

Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was trained with five challenging and heterogeneous MR prostate datasets (and two US datasets), with segmentations from many different experts with varying segmentation criteria. The model achieves a consistently strong performance in all datasets independently (mean Dice Similarity Coefficient -DSC- above 0.91 for all datasets except for one), outperforming the inter-expert variability significantly in MR (mean DSC of 0.9099 vs. 0.8794). When evaluated on the publicly available Promise12 challenge dataset, it attains a similar performance to the best entries. In summary, the model has the potential of having a significant impact on current prostate procedures, undercutting, and even eliminating, the need of manual segmentations through improvements in terms of robustness, generalizability and output resolution.


2021 ◽  
Vol 8 (2) ◽  
pp. 84-88
Author(s):  
Marwa Zohdy ◽  
Simone Cazzaniga ◽  
Helga Nievergelt ◽  
Roland Blum ◽  
Valérie G. A. Suter ◽  
...  

Oral lichen planus (OLP) and oral lichenoid lesions (OLL) can both present with histological dysplasia. Despite the presence of WHO-defined criteria for the evaluation of epithelial dysplasia, its assessment is frequently subjective (inter-observer variability). The lack of reproducibility in the evaluation of dysplasia is even more complex in the presence of a lichenoid inflammation. We evaluated dysplasia in 112 oral biopsies with lichenoid inflammation in order to study the inter-observer and the intra-observer variability.


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