High sensitivity methods for automated rib fracture detection in pediatric radiographs.

Rib fractures are highly predictive of non-accidental trauma in children under 3 years old. Rib fracture detection in pediatric radiographs is challenging because fractures can be obliquely oriented to the imaging detector, obfuscated by other structures, incomplete, and non-displaced. Prior studies have shown up to two-thirds of rib fractures may be missed during initial interpretation. In this paper, we implemented methods for improving the sensitivity (i.e. recall) performance for detecting and localizing rib fractures in pediatric chest radiographs to help augment performance of radiology interpretation. These methods adapted two convolutional neural network (CNN) architectures, RetinaNet and YOLOv5, and our previously proposed decision scheme, "avalanche decision", that dynamically reduces the acceptance threshold for proposed regions in each image. Additionally, we present contributions of using multiple image pre-processing and model ensembling techniques. Using a custom dataset of 1109 pediatric chest radiographs manually labeled by seven pediatric radiologists, we performed 10-fold cross-validation and reported detection performance using several metrics, including F2 score which summarizes precision and recall for high-sensitivity tasks. Our best performing model used three ensembled YOLOv5 models with varied input processing and an avalanche decision scheme, achieving an F2 score of 0.725 ± 0.012. Expert inter-reader performance yielded an F2 score of 0.732. Results demonstrate that our combination of sensitivity-driving methods provides object detector performance approaching the capabilities of expert human readers, suggesting that these methods may provide a viable approach to identify all rib fractures.

The Reliability of Assessing Radiographic Healing of Osteochondritis Dissecans of the Knee.

BACKGROUND: The reliability of assessing healing on plain radiographs has not been well-established for knee osteochondritis dissecans (OCD). PURPOSE: To determine the inter- and intrarater reliability of specific radiographic criteria in judging healing of femoral condyle OCD. STUDY DESIGN: Cohort study (Diagnosis); Level of evidence, 3. METHODS: Ten orthopedic sports surgeons rated the radiographic healing of 30 knee OCD lesions at 2 time points, a minimum of 1 month apart. First, raters compared pretreatment and 2-year follow-up radiographs on "overall healing" and on 5 subfeatures of healing, including OCD boundary, sclerosis, size, shape, and ossification using a continuous slider scale. "Overall healing" was also rated using a 7-tier ordinal scale. Raters then compared the same 30 pretreatment knee radiographs in a stepwise progression to the 2-, 4-, 7-, 12-, and 24-month follow-up radiographs on "overall healing" using a continuous slider scale. Interrater and intrarater reliability were assessed using intraclass correlations (ICC) derived from a 2-way mixed effects analysis of variance for absolute agreement. RESULTS: Overall healing of the OCD lesions from pretreatment to 2-year follow-up radiographs was rated with excellent interrater reliability (ICC = 0.94) and intrarater reliability (ICC = 0.84) when using a continuous scale. The reliability of the 5 subfeatures of healing was also excellent (interrater ICCs of 0.87-0.89; intrarater ICCs of 0.74-0.84). The 7-tier ordinal scale rating of overall healing had lower interrater (ICC = 0.61) and intrarater (ICC = 0.68) reliability. The overall healing of OCD lesions at the 5 time points up to 24 months had interrater ICCs of 0.81-0.88 and intrarater ICCs of 0.65-0.70. CONCLUSION: Interrater reliability was excellent when judging the overall healing of OCD femoral condyle lesions on radiographs as well as on 5 specific features of healing on 2-year follow-up radiographs. Continuous scale rating of OCD radiographic healing yielded higher reliability than the ordinal scale rating. Raters showed substantial to excellent agreement of OCD overall radiographic healing measured on a continuous scale at 2, 4, 7, 12, and 24 months after starting treatment.