It is an indisputable dogma in extremity radiography to acquire x-ray studies in at least two complementary projections, which is also true for distal radius fractures in children. However, there is cautious hope that computer vision could enable breaking with this tradition in minor injuries, clinically lacking malalignment. We trained three different state-of-the-art convolutional neural networks (CNNs) on a dataset of 2,474 images: 1,237 images were posteroanterior (PA) pediatric wrist radiographs containing isolated distal radius torus fractures, and 1,237 images were normal controls without fractures. The task was to classify images into fractured and non-fractured. In total, 200 previously unseen images (100 per class) served as test set. CNN predictions reached area under the curves (AUCs) up to 98% [95% confidence interval (CI) 96.6%–99.5%], consistently exceeding human expert ratings (mean AUC 93.5%, 95% CI 89.9%–97.2%). Following training on larger data sets CNNs might be able to effectively rule out the presence of a distal radius fracture, enabling to consider foregoing the yet inevitable lateral projection in children. Built into the radiography workflow, such an algorithm could contribute to radiation hygiene and patient comfort.

Purpose: Computed tomography pulmonary angiography (CT-PA) is frequently used in the diagnostic workup of pulmonary embolism (PE), even in highly radiosensitive patient populations. This study aims to assess CT-PA with reduced z-axis coverage (compared with a standard scan range covering the entire lung) for its sensitivity for detecting PE and its potential to reduce the radiation dose. Materials and Methods: We retrospectively analyzed 602 consecutive CT-PA scans with definite or possible PE reported. A reduced scan range was defined based on the topogram, where the cranial slice was set at the top of the aortic arch and the caudal slice at the top of the lower hemidiaphragm. Locations of emboli in relation to the reduced scan range were recorded. Results: We included 513 CT-PA scans with definite acute PE in statistical analysis. Patients’ median age was 66 (52 to 77) years, 46% were female. Median dose length product was 270.8 (111.3 to 503.9) mGy*cm. Comparing the original and reduced scan ranges, the mean scan length was significantly reduced by 48.0±8.6% (26.8±3.0 vs. 13.9±2.6 cm, P<0.001). Single emboli outside the reduced range in addition to emboli within were found in 15 scans (2.9%), while only 1 scan (0.2%) had an embolus outside the reduced range and none within it. The resulting sensitivity of CT-PA with reduced scan range was 99.81% (95% confidence interval: 98.74%-99.99%) for detecting any PE. Conclusion: A reduced scan length in CT-PA, as defined above, would substantially decrease radiation dose while maintaining diagnostic accuracy for detecting PE.

In clinical practice, fracture age estimation is commonly required, particularly in children with suspected non-accidental injuries. It is usually done by radiologically examining the injured body part and analyzing several indicators of fracture healing such as osteopenia, periosteal reaction, and fracture gap width. However, age-related changes in healing timeframes, inter-individual variabilities in bone density, and significant intra- and inter-operator subjectivity all limit the validity of these radiological clues. To address these issues, for the first time, we suggest an automated neural network-based system for determining the age of a pediatric wrist fracture. In this study, we propose and evaluate a deep learning approach for automatically estimating fracture age. Our dataset included 3570 medical cases with a skewed distribution toward initial consultations. Each medical case includes a lateral and anteroposterior projection of a wrist fracture, as well as patients’ age, and gender. We propose a neural network-based system with Monte-Carlo dropout-based uncertainty estimation to address dataset skewness. Furthermore, this research examines how each component of the system contributes to the final forecast and provides an interpretation of different scenarios in system predictions in terms of their uncertainty. The examination of the proposed systems’ components showed that the feature-fusion of all available data is necessary to obtain good results. Also, proposing uncertainty estimation in the system increased accuracy and F1-score to a final $0.906\pm 0.011$ on a given task.

Purpose: To evaluate the safety and efficacy of retrievable scaffold therapy combined with sirolimus-coated balloon angioplasty for treating infrapopliteal artery lesions. Methods: The DEEPER LIMUS study enrolled Rutherford class 3 to 5 patients with infrapopliteal artery disease. Patients underwent vessel preparation with retrievable scaffold therapy followed by sirolimus-coated balloon angioplasty. The primary safety outcome measure was a composite of all-cause mortality, major amputation, or clinically driven target lesion revascularization at 6 months. Secondary outcome measures included acute vessel recoil, perioperative death, angiographic late lumen loss between post-procedure and 6 months, as well as primary patency, major amputation, change in Rutherford class, and wound healing through 12 months. Results: The study included 26 patients (mean age 71 years, 62% male, 88% Rutherford 5) with 28 treated infrapopliteal lesions (36% occluded, 54% TASC B/C). Acute vessel recoil, measured in seven patients, was negligible (2.4 mm after treatment vs. 2.3 mm 15 minutes after deployment). A 6-month primary safety event occurred in 11.5% of patients (1 all-cause mortality, 1 major amputation, 1 clinically driven target lesion revascularization). Late lumen loss at 6 months was 0.7±0.7 mm. At 12 months, primary patency was 89.5%, improvement in Rutherford class was observed in 68.2% of patients, 90% of patients were deemed very low/low major limb amputation risk based on Wound, Ischemia, and foot Infection (WIfI) scores, and no additional major amputations or clinically driven target lesion revascularizations were reported. Conclusions: Retrievable scaffold therapy combined with sirolimus-coated balloon angioplasty demonstrated promising safety and efficacy through 12 months in patients with infrapopliteal artery disease. Level of Evidence IV: Case Series. Graphical

Artificial intelligence performance in pediatric fracture detection was influenced by test set composition and image complexity, where an internal test set of difficult radiographs was associated with decreased odds of correct predictions.