scholarly journals Inter-observer variability and its correlation to experience in measurement of lower limb mechanical axis on long leg radiographs

2016 ◽  
Vol 7 (4) ◽  
pp. 260-264 ◽  
Author(s):  
Raju Vaishya ◽  
Vipul Vijay ◽  
Vikas P. Birla ◽  
Amit Kumar Agarwal
2018 ◽  
Vol 6 (4_suppl2) ◽  
pp. 2325967118S0001
Author(s):  
Hagen Hommel

Mechanical axis of the lower limb assessed in standing long-leg radiographs was demonstrated to change within the first three postoperative months after total knee arthroplasty (TKA). The underlying mechanism including the influence of limb loading for the change in mechanical axis alignment after TKA has not been evaluated so far. Mechanical axis of the lower limb and limb loading were evaluated in 115 patients 10 days and 12 weeks after TKA. Mechanical axis was measured in standing long-leg radiographs while limb loading was simultaneously assessed using a scale. Absolute and relative limb loading with their correlation to the mechanical axis were calculated. Mechanical axis in patients with postoperative complete extension (n = 100) changed from an initial -0.82° ± 1.9° valgus alignment to a varus axis of +0.6° ± 1.5 (p < 0.01). This change in alignment was accompanied by an increased limb loading from 89.9% 10.7% to 93.0% 7.0% (p < 0.01). The mechanical axis highly/significantly correlated with relative limb loading in both measurements (r = 0.804, p < 0.001 respectively r = 0.562, p < 0.001). These alterations and distinctions were much more pronounced in patients with postoperative incomplete extension. Mechanical axis of the leg significantly changes while limb loading increases within the first three postoperative months after TKA. The postoperative alignment highly correlates with the loading of the lower limb. Therefore, the actual mechanical axis can only be assessed at physiological limb loading in long-leg radiographs at complete extension with full weight bearing.


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.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ricardo A. Gonzales ◽  
Felicia Seemann ◽  
Jérôme Lamy ◽  
Per M. Arvidsson ◽  
Einar Heiberg ◽  
...  

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.


2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Xingmin Guan ◽  
Yinyin Chen ◽  
Hsin-Jung Yang ◽  
Xinheng Zhang ◽  
Daoyuan Ren ◽  
...  

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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