Abstract
In this study, we aim to provide a deep convolutional network based femoral neck fracture detection system on radiographs for emergency patients. We retrospectively collected 1,491 frontal pelvic radiographs from three institutions and assigned them to the following data sets: primary dataset (710 radiographs, to fine-tune and validate the initial model called the Digital Radiography Fracture Detection System [DR-FDS]), internal test set 1 (189 radiographs) and 2 (235 radiographs), and external test set 1 (189 radiographs) and 2 (168 radiographs). Per-bounding box recall and precision and per-image sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were computed. We randomly extracted 300 radiographs from the above test sets and compared their effect on the diagnostic accuracy and efficiency of fine-tuned model-assisted and unassisted clinicians. The fine-tuned DR-FDS showed a better overall performance in detecting femoral neck fractures than did the initial DR-FDS. The fine-tuned DR-FDS achieved AUC values of 0.9526 (95%CI, 0.9048–0.9767) and 0.9633(95%CI, 0.9346-0.9797) in internal test sets 1 and 2. In external test sets 1 and 2, this model also achieved promising results with AUC values of 0.9231 (95%CI, 0.8779–0.9520), and 0.9937 (95%CI 0.9739–0.9985), respectively. The clinicians showed a statistically significant increase in specificity, sensitivity, and accuracy for the identification of minimal/undisplaced fracture and a decrease in the average reading time. The object detection model that is fine-tuned has high sensitivity and specificity and the universal ability to detect and locate femoral neck fractures on pelvic radiographs.
Highlights
The femur is the longest and strongest bone in the body
We randomly split the primary dataset into the training set (n = 610) which was used to fine-tune the DR-FDS, and tuning set (n = 100) which was used to select the final model
In order to validate our model performance in real-world clinical environment, we split 253 consecutive PXRs from emergency patients (EPs) in Emergency Radiology department of JLU-1 and considered them as internal test set 2, which were consisted of all kinds of pelvic fractures over a three-month period in 2020 (July to September), this data set was included to investigate the feasibility of extending this method to other types of proximal hip fractures
Summary
The femur is the longest and strongest bone in the body. The femoral neck, the upper part of the femur, often suffers severe fractures [1]. The associate editor coordinating the review of this manuscript and approving it for publication was Gang Wang. Considered as one of the most serious osteoporotic fractures, which are considered as the main cause of disability in elderly individuals worldwide [2], [3]. Fractures of the neck of the femur can seriously affect the quality of life of patients. Survivors may require considerable social and nursing care, which increases social and economic burdens [4].
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