Analysis of microcirculation measurements by novice users trained by a standardized interactive tutorial: An inter-observer variability study

2016 ◽  
Vol 62 (2) ◽  
pp. 123-128 ◽  
Author(s):  
Vladimir Cerny ◽  
Islam Abdo ◽  
Ronald B. George ◽  
Liivi Maddison ◽  
Nivin Sharawi ◽  
...  
Keyword(s):  
Observer Variability ◽  
Inter Observer Variability ◽  
Novice Users ◽  
Interactive Tutorial ◽  
Variability Study

scholarly journals EP-1657: Inter-observer variability study for daily CBCT registration of VMAT prostate treatment

2015 ◽  
Vol 115 ◽  
pp. S908 ◽  
Author(s):  
N. Zahra ◽  
C. Monnet ◽  
E. Bartha ◽  
M. Courbis ◽  
M. Le Grévellec ◽  
...  
Keyword(s):  
Observer Variability ◽  
Inter Observer Variability ◽  
Variability Study

scholarly journals Inter-Observer and Intra-Observer Variations in the Assessment of Epithelial Dysplasia in Oral Lichenoid Diseases

2021 ◽  
Vol 8 (2) ◽  
pp. 84-88
Author(s):  
Marwa Zohdy ◽  
Simone Cazzaniga ◽  
Helga Nievergelt ◽  
Roland Blum ◽  
Valérie G. A. Suter ◽  
...  
Keyword(s):  
Lichen Planus ◽  
Oral Lichen Planus ◽  
Epithelial Dysplasia ◽  
Observer Variability ◽  
Oral Lichenoid Lesions ◽  
Inter Observer Variability ◽  
Oral Lichen

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.

scholarly journals Automated left atrial time-resolved segmentation in MRI long-axis cine images using active contours

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ricardo A. Gonzales ◽  
Felicia Seemann ◽  
Jérôme Lamy ◽  
Per M. Arvidsson ◽  
Einar Heiberg ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Active Contours ◽  
Imaging Biomarkers ◽  
Observer Variability ◽  
Time Resolved ◽  
Variability Analysis ◽  
Automated Method ◽  
Inter Observer Variability ◽  
Atrial Size ◽  
And Function

Abstract Background Segmentation of the left atrium (LA) is required to evaluate atrial size and function, which are important imaging biomarkers for a wide range of cardiovascular conditions, such as atrial fibrillation, stroke, and diastolic dysfunction. LA segmentations are currently being performed manually, which is time-consuming and observer-dependent. Methods This study presents an automated image processing algorithm for time-resolved LA segmentation in cardiac magnetic resonance imaging (MRI) long-axis cine images of the 2-chamber (2ch) and 4-chamber (4ch) views using active contours. The proposed algorithm combines mitral valve tracking, automated threshold calculation, edge detection on a radially resampled image, edge tracking based on Dijkstra’s algorithm, and post-processing involving smoothing and interpolation. The algorithm was evaluated in 37 patients diagnosed mainly with paroxysmal atrial fibrillation. Segmentation accuracy was assessed using the Dice similarity coefficient (DSC) and Hausdorff distance (HD), with manual segmentations in all time frames as the reference standard. For inter-observer variability analysis, a second observer performed manual segmentations at end-diastole and end-systole on all subjects. Results The proposed automated method achieved high performance in segmenting the LA in long-axis cine sequences, with a DSC of 0.96 for 2ch and 0.95 for 4ch, and an HD of 5.5 mm for 2ch and 6.4 mm for 4ch. The manual inter-observer variability analysis had an average DSC of 0.95 and an average HD of 4.9 mm. Conclusion The proposed automated method achieved performance on par with human experts analyzing MRI images for evaluation of atrial size and function.

scholarly journals Assessment of intramyocardial hemorrhage with dark-blood T2*-weighted cardiovascular magnetic resonance

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Xingmin Guan ◽  
Yinyin Chen ◽  
Hsin-Jung Yang ◽  
Xinheng Zhang ◽  
Daoyuan Ren ◽  
...  
Keyword(s):  
Cardiovascular Magnetic Resonance ◽  
Magnetic Resonance ◽  
Major Adverse Cardiovascular Events ◽  
Observer Variability ◽  
Dark Blood ◽  
Imaging Characteristics ◽  
Inter Observer Variability ◽  
Sensitivity Specificity ◽  
Bright Blood ◽  
T2 Weighted Images

Abstract Background Intramyocardial hemorrhage (IMH) within myocardial infarction (MI) is associated with major adverse cardiovascular events. Bright-blood T2*-based cardiovascular magnetic resonance (CMR) has emerged as the reference standard for non-invasive IMH detection. Despite this, the dark-blood T2*-based CMR is becoming interchangeably used with bright-blood T2*-weighted CMR in both clinical and preclinical settings for IMH detection. To date however, the relative merits of dark-blood T2*-weighted with respect to bright-blood T2*-weighted CMR for IMH characterization has not been studied. We investigated the diagnostic capacity of dark-blood T2*-weighted CMR against bright-blood T2*-weighted CMR for IMH characterization in clinical and preclinical settings. Materials and methods Hemorrhagic MI patients (n = 20) and canines (n = 11) were imaged in the acute and chronic phases at 1.5 and 3 T with dark- and bright-blood T2*-weighted CMR. Imaging characteristics (Relative signal-to-noise (SNR), Relative contrast-to-noise (CNR), IMH Extent) and diagnostic performance (sensitivity, specificity, accuracy, area-under-the-curve, and inter-observer variability) of dark-blood T2*-weighted CMR for IMH characterization were assessed relative to bright-blood T2*-weighted CMR. Results At both clinical and preclinical settings, compared to bright-blood T2*-weighted CMR, dark-blood T2*-weighted images had significantly lower SNR, CNR and reduced IMH extent (all p < 0.05). Dark-blood T2*-weighted CMR also demonstrated weaker sensitivity, specificity, accuracy, and inter-observer variability compared to bright-blood T2*-weighted CMR (all p < 0.05). These observations were consistent across infarct age and imaging field strengths. Conclusion While IMH can be visible on dark-blood T2*-weighted CMR, the overall conspicuity of IMH is significantly reduced compared to that observed in bright-blood T2*-weighted images, across infarct age in clinical and preclinical settings at 1.5 and 3 T. Hence, bright-blood T2*-weighted CMR would be preferable for clinical use since dark-blood T2*-weighted CMR carries the potential to misclassify hemorrhagic MIs as non-hemorrhagic MIs.

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