Background: Teleradiology has the potential to link medical experts and specialties despite geographical separation. In a project report about hospital-based teleradiology, the significance of technical and human factors during the implementation and growth of a teleradiology network are explored. Evaluation: The article identifies major obstacles during the implementation and growth of the teleradiology network of the Berlin Trauma Hospital (BG Unfallkrankenhaus Berlin) between 2004 and 2020 in semi-structured interviews with senior staff members. Quantitative analysis of examination numbers, patient numbers, and profits relates the efforts of the staff members to the monetary benefits and success of the network. Identification of qualitative and quantitative factors for success: Soft and hard facilitators and solutions driving the development of the national teleradiology network are identified. Obstacles were often solved by technical innovations, but the time span between required personal efforts, endurance, and flexibility of local and external team members. The article describes innovations driven by teleradiology and hints at the impact of teleradiology on modern medical care by relating the expansion of the teleradiology network to patient transfers and profits. Conclusion: In addition to technical improvements, interpersonal collaborations were key to the success of the teleradiology network of the Berlin Trauma Hospital and remained a unique feature and selling point of this teleradiology network.

We here introduce a digital scanning method for determining leg length and angles. The leg length and angle measurements, image quality and radiation dose were evaluated. A composite overview image was reconstructed from a series of individual images. In 45 overview images, the total leg length and the femoro-tibial angle were determined by two radiologists, and the inter- and intra-observer variability was examined in the light of the measured values as well as the subjective assessment of the image quality. A dose comparison was carried out with a series of conventional whole leg images. The mean standard deviation of the multiple measurements of leg length was 0.4 mm for researcher I and 0.5 mm for researcher II. The difference in the mean values of the measured leg lengths between the researchers was 0.3 mm. The mean standard deviation of the multiple measurements of the femoro-tibial angle was 0.1 degrees for both researchers. The difference in the mean values of the measured femoro-tibial angle between the researchers was 0.03 degrees. On average, the marks for the image quality awarded by researcher II with an average score of 2 were very significantly worse than those awarded by researcher I with an average score of 1.5. The mean entrance dose value determined was 0.16 mGy lower in the digital system (0.49 mGy) than that of the comparative conventional series (0.65 mGy). Where there is a large number of possible length and angle measurements, the proposed procedure offers the advantages of good image quality, digital image processing, measurements that are easy to perform, reproducible and accurate, and lower radiation dose, and it is superior to conventional whole leg images.

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Objective:
In the context of primary in-hospital trauma management timely reading of computed tomography (CT) images is critical. However, assessment of the spine is time consuming, fractures can be very subtle, and the potential for under-diagnosis or delayed diagnosis is relevant. 
Artificial intelligence is increasingly employed to assist radiologists with the detection of spinal fractures and prioritization of cases.
Currently, algorithms focusing on the cervical spine are commercially available.
A common approach is the vertebra-wise classification.
Instead of a classification task, we formulate fracture detection as a segmentation task aiming to find and display all individual fracture locations presented in the image.\\ 
Approach:
Based on 195 CT examinations, 454 cervical spine fractures were identified and annotated by radiologists at a tertiary trauma centre. 
We trained for the detection a U-Net via 4-fold-cross validation to segment spine fractures and the spine via a multi-task loss. 
We further compared advantages of two image reformation approaches - straightened curved planar reformatted (CPR) around the spine and spinal canal aligned volumes of interest (VOI) - to achieve a unified vertebral alignment in comparison to processing the Cartesian data directly.
Main results:
Of the three data versions (Cartesian, reformatted, VOI) the VOI approach showed the best detection rate and a reduced computation time. The proposed algorithm was able to detect 87.2\% of cervical spine fractures at an average number of false positives of 3.5 per case. Evaluation of the method on a public spine dataset resulted in 0.9 false positive detections per cervical spine case. 
Significance:
The display of individual fracture locations as provided with high sensitivity by the proposed voxel classification based fracture detection has the potential to support the trauma CT reading workflow by reducing missed findings. 

No abstract