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Background
Morphology and glenoid involvement determine the necessity of surgical management in scapula fractures. While being present in only a small share of patients with shoulder trauma, numerous classification systems have been in use over the years for categorization of scapula fractures. The purpose of this study was to evaluate the established AO/OTA classification in comparison to the classification system of Euler and Rüedi (ER) with regard to interobserver reliability and confidence in clinical practice.
Methods
Based on CT imaging, 149 patients with scapula fractures were retrospectively categorized by two trauma surgeons and two radiologists using the classification systems of ER and AO/OTA. To measure the interrater reliability, Fleiss kappa (κ) was calculated independently for both fracture classifications. Rater confidence was stated subjectively on a five-point scale and compared with Wilcoxon signed rank tests. Additionally, we computed the intraclass correlation coefficient (ICC) based on absolute agreement in a two-way random effects model to assess the diagnostic confidence agreement between observers.
Results
In scapula fractures involving the glenoid fossa, interrater reliability was substantial (κ = 0.722; 95% confidence interval [CI] 0.676–0.769) for the AO/OTA classification in contrast to moderate agreement (κ = 0.579; 95% CI 0.525–0.634) for the ER classification system. Diagnostic confidence for intra-articular fracture patterns was superior using the AO/OTA classification compared to ER (p < 0.001) with higher confidence agreement (ICC: 0.882 versus 0.831). For extra-articular fractures, ER (κ = 0.817; 95% CI 0.771–0.863) provided better interrater reliability compared to AO/OTA (κ = 0.734; 95% CI 0.692–0.776) with higher diagnostic confidence (p < 0.001) and superior agreement between confidence ratings (ICC: 0.881 versus 0.912).
Conclusions
The AO/OTA classification is most suitable to categorize intra-articular scapula fractures with glenoid involvement, whereas the classification system of Euler and Rüedi appears to be superior in extra-articular injury patterns with fractures involving only the scapula body, spine, acromion and coracoid process.
Objective
Multipartite epicondyles may mimic fractures in the setting of pediatric elbow trauma. This study examines the prevalence of multipartite epicondyles during skeletal development and their association with pediatric elbow fractures.
Materials and methods
In this retrospective analysis, 4282 elbow radiographs of 1265 elbows of 1210 patients aged 0–17 years were reviewed. The radiographs were analyzed by two radiologists in consensus reading, and the number of visible portions of the medial and lateral epicondyles was noted. For elbows in which epicondylar ossification was not yet visible, the epicondyles were already fused with the humerus or could not be sufficiently evaluated due to projection issues or because osteosynthesis material was excluded. In total, 187 elbows were included for the lateral and 715 for the medial epicondyle analyses.
Results
No multipartite medial epicondyles were found in patients without history of elbow fracture, whereas 9% of these patients had multipartite lateral epicondyles (p < 0.01). Current or previous elbow fractures increased the prevalence of multipartite epicondyles, with significant lateral predominance (medial epicondyle + 9% vs. lateral + 24%, p < 0.0001). Including all patients regardless of a history of elbow fracture, multipartite medial epicondyles were observed in 3% and multipartite lateral epicondyles in 18% (p < 0.0001). There was no gender difference in the prevalence of multipartition of either epicondyle, regardless of a trauma history.
Conclusion
Multipartite medial epicondyles occur in patients with current or previous elbow fractures only, whereas multipartite lateral epicondyles may be constitutional. Elbow fractures increase the prevalence of multipartite epicondyles on both sides, with significant lateral predominance.
Key Points
• Multipartite medial epicondyles should be considered of traumatic origin.
• Multipartite lateral epicondyles may be constitutional.
• Elbow fractures increase the prevalence of multipartite epicondyles on both sides with lateral predominance.
Background
To increase the image quality of end-expiratory and end-inspiratory phases of retrospective respiratory self-gated 4D MRI data sets using non-rigid image registration for improved target delineation of moving tumors.
Methods
End-expiratory and end-inspiratory phases of volunteer and patient 4D MRI data sets are used as targets for non-rigid image registration of all other phases using two different registration schemes: In the first, all phases are registered directly (dir-Reg) while next neighbors are successively registered until the target is reached in the second (nn-Reg). Resulting data sets are quantitatively compared using diaphragm and tumor sharpness and the coefficient of variation of regions of interest in the lung, liver, and heart. Qualitative assessment of the patient data regarding noise level, tumor delineation, and overall image quality was performed by blinded reading based on a 4 point Likert scale.
Results
The median coefficient of variation was lower for both registration schemes compared to the target. Median dir-Reg coefficient of variation of all ROIs was 5.6% lower for expiration and 7.0% lower for inspiration compared with nn-Reg. Statistical significant differences between the two schemes were found in all comparisons. Median sharpness in inspiration is lower compared to expiration sharpness in all cases. Registered data sets were rated better compared to the targets in all categories. Over all categories, mean expiration scores were 2.92 +/- 0.18 for the target, 3.19 +/- 0.22 for nn-Reg and 3.56 +/- 0.14 for dir-Reg and mean inspiration scores 2.25 +/- 0.12 for the target, 2.72 +/- 215 0.04 for nn-Reg and 3.78 +/- 0.04 for dir-Reg.
Conclusions
In this work, end-expiratory and inspiratory phases of a 4D MRI data sets are used as targets for non-rigid image registration of all other phases. It is qualitatively and quantitatively shown that image quality of the targets can be significantly enhanced leading to improved target delineation of moving tumors.
Background
Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentation of lung images which were scanned by a fast UTE sequence exploiting the stack-of-spirals trajectory can provide sufficiently good accuracy for the calculation of functional parameters.
Methods
In this study, lung images were acquired in 20 patients suffering from cystic fibrosis (CF) and 33 healthy volunteers, by a fast UTE sequence with a stack-of-spirals trajectory and a minimum echo-time of 0.05 ms. A convolutional neural network was then trained for semantic lung segmentation using 17,713 2D coronal slices, each paired with a label obtained from manual segmentation. Subsequently, the network was applied to 4920 independent 2D test images and results were compared to a manual segmentation using the Sørensen–Dice similarity coefficient (DSC) and the Hausdorff distance (HD). Obtained lung volumes and fractional ventilation values calculated from both segmentations were compared using Pearson’s correlation coefficient and Bland Altman analysis.
To investigate generalizability to patients outside the CF collective, in particular to those exhibiting larger consolidations inside the lung, the network was additionally applied to UTE images from four patients with pneumonia and one with lung cancer.
Results
The overall DSC for lung tissue was 0.967 ± 0.076 (mean ± standard deviation) and HD was 4.1 ± 4.4 mm. Lung volumes derived from manual and deep learning based segmentations as well as values for fractional ventilation exhibited a high overall correlation (Pearson’s correlation coefficent = 0.99 and 1.00). For the additional cohort with unseen pathologies / consolidations, mean DSC was 0.930 ± 0.083, HD = 12.9 ± 16.2 mm and the mean difference in lung volume was 0.032 ± 0.048 L.
Conclusions
Deep learning-based image segmentation in stack-of-spirals based lung MRI allows for accurate estimation of lung volumes and fractional ventilation values and promises to replace the time-consuming step of manual image segmentation in the future.
Background: Computed tomography (CT) pulmonary angiography is the diagnostic reference standard in suspected pulmonary embolism (PE). Favorable results for dual-energy CT (DECT) images have been reported for this condition. Nowadays, dual-energy data acquisition is feasible with different technical options, including a single-source split-filter approach. Therefore, the aim of this retrospective study was to investigate image quality and radiation dose of thoracic split-filter DECT in comparison to conventional single-energy CT in patients with suspected PE.
Methods: A total of 110 CT pulmonary angiographies were accomplished either as standard single-energy CT with automatic tube voltage selection (ATVS) (n=58), or as split-filter DECT (n=52). Objective [pulmonary artery CT attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] and subjective image quality [four-point Likert scale; three readers (R)] were compared among the two study groups. Size-specific dose estimates (SSDE), dose-length-product (DLP) and volume CT dose index (CTDIvol) were assessed for radiation dose analysis.
Results: Split-filter DECT images yielded 67.7% higher SNR (27.0 vs. 16.1; P<0.001) and 61.9% higher CNR (22.5 vs. 13.9; P<0.001) over conventional single-energy images, whereas CT attenuation was significantly lower (344.5 vs. 428.2 HU; P=0.013). Subjective image quality was rated good or excellent in 93.0%/98.3%/77.6% (R1/R2/R3) of the single-energy CT scans, and 84.6%/82.7%/80.8% (R1/R2/R3) of the split-filter DECT scans. SSDE, DLP and CTDIvol were significantly lower for conventional single-energy CT compared to split-filter DECT (all P<0.05), which was associated with 26.7% higher SSDE.
Conclusions: In the diagnostic workup of acute PE, the split-filter allows for dual-energy data acquisition from single-source single-layer CT scanners. The existing opportunity to assess pulmonary “perfusion” based on analysis of iodine distribution maps is associated with higher radiation dose in terms of increased SSDE than conventional single-energy CT with ATVS. Moreover, a proportion of up to 3.8% non-diagnostic examinations in the current reference standard test for PE is not negligible.
Background:
Contrast-enhanced cardiovascular magnetic resonance angiography (CE-CMRA) is the established imaging modality for patients with Marfan syndrome requiring life-long annual aortic imaging before and after aortic root replacement. Contrast-free CMRA techniques avoiding side-effects of contrast media are highly desirable for serial imaging but have not been evaluated in the postoperative setup of Marfan patients. The purpose of this study was to assess the feasibility of non-contrast balanced steady-state free precession (bSSFP) magnetic resonance imaging for aortic monitoring of postoperative patients with Marfan syndrome.
Methods:
Sixty-four adult Marfan patients after aortic root replacement were prospectively included. Fourteen patients (22%) had a residual aortic dissection after surgical treatment of type A dissection. bSSFP imaging and CE-CMRA were performed at 1.5 Tesla. Two radiologists evaluated the images regarding image quality (1 = poor, 4 = excellent), artifacts (1 = severe, 4 = none) and aortic pathologies. Readers measured the aortic diameters at defined levels in both techniques. Statistics included observer agreement for image scoring and diameter measurements and ROC analyses for comparison of the diagnostic performance of bSSFP and CE-CMRA.
Results:
Both readers observed no significant differences in image quality between bSSFP and CE-CMRA and found a median image quality score of 4 for both techniques (all p > .05). No significant differences were found regarding the frequency of image artifacts in both sequences (all p > .05). Sensitivity and specificity for detection of aortic dissections was 100% for both readers and techniques. Compared to bSSFP imaging, CE-CMRA resulted in higher diameters (mean bias, 0.9 mm; p < .05). The inter-observer biases of diameter measurements were not significantly different (all p > .05), except for the distal graft anastomosis (p = .001). Using both techniques, the readers correctly identified a graft suture dehiscence with aneurysm formation requiring surgery.
Conclusion:
Unenhanced bSSFP CMR imaging allows for riskless aortic monitoring with high diagnostic accuracy in Marfan patients after aortic root surgery.
Abstract
To compare intravenous contrast material (CM) injection protocols for dual-energy CT pulmonary angiography (CTPA) in patients with suspected acute pulmonary embolism with regard to image quality and pulmonary perfused blood volume (PBV) values. A total of 198 studies performed with four CM injection protocols varying in CM volume and iodine delivery rates (IDR) were retrospectively included: (A) 60 ml at 5 ml/s (IDR = 1.75gI/s), (B) 50 ml at 5 ml/s (IDR = 1.75gI/s), (C) 50 ml at 4 ml/s (IDR = 1.40gI/s), (D) 40 ml at 3 ml/s (IDR = 1.05gI/s). Image quality and PBV values at different resolution settings were compared. Pulmonary arterial tract attenuation was highest for protocol A (397 ± 110 HU; p vs. B = 0.13; vs. C = 0.02; vs. D < 0.001). CTPA image quality of protocol A was rated superior compared to protocols B and D by reader 1 (p = 0.01; < 0.001), and superior to protocols B, C and D by reader 2 (p < 0.001; 0.02; < 0.001). Otherwise, there were no significant differences in CTPA quality ratings. Subjective iodine map ratings did not vary significantly between protocols A, B, and C. Both readers rated protocol D inferior to all other protocols (p < 0.05). PBV values did not vary significantly between protocols A and B at resolution settings of 1, 4 and 10 (p = 0.10; 0.10; 0.09), while otherwise PBV values displayed a decreasing trend from protocol A to D (p < 0.05). Higher CM volume and IDR are associated with superior CTPA and iodine map quality and higher absolute PBV values.