Search

The rich collection of annotated datasets piloted the robustness of deep learning techniques to effectuate the implementation of diverse medical imaging tasks. Over 15% of deaths include children under age five are caused by pneumonia globally. In this study, we describe our deep learning based approach for the identification and localization of pneumonia in Chest X-rays (CXRs) images. Researchers usually employ CXRs for the diagnostic imaging study. Several factors such as positioning of the patient and depth of inspiration can change the appearance of the chest X-ray, complicating interpretation further. Our identification model ( https://github.com/amitkumarj441/identify_pneumonia ) is based on Mask-RCNN, a deep neural network which incorporates global and local features for pixel-wise segmentation. Our approach achieves robustness through critical modifications of the training process and a novel post-processing step which merges bounding boxes from multiple models. The proposed identification model achieves better performances evaluated on chest radiograph dataset which depict potential pneumonia causes.

INTRODUCTION AND OBJECTIVES:A previous randomized trial found that obtaining ultrasound (US) as the first diagnostic imaging study for adults with suspected ureteral stones reduces radiation without increasing return ED visits or missed diagnoses. These results are consistent with EAU guidelines that US should be the first imaging modality for nephrolithiasis. We sought to determine the potential reduction in radiation exposure for an US-first approach using population-based diagnostic imaging patterns in the ED.METHODS:We performed a cross-sectional study of adults who presented to 70 emergency departments in South Carolina between 1996 and 2017 using all payer hospital claims data. All ED encounters within a 6 month “episode” following the initial ED visit were identified, along with ultrasound and CT ordered at the visits. Patterns of US and CT during the first two consecutive ER visits were determined at the patient- and hospital-level. Imaging patterns in which only a CT was performed were classified...

Diagnostic imaging has mirrored the steady growth of healthcare utilization in the USA. This has created greater opportunity for diagnostic errors, which can be costly in terms of morbidity and mortality as well as dollars and cents. The purposes of this study were to describe all return visits to a tertiary care urban pediatric emergency department (PED) resulting from diagnostic imaging discrepancies and to calculate the costs of these return visits. From July 2014 to February 2015, all children who underwent a diagnostic imaging study during an ED visit were assembled. Analysis was performed on all children who were called back and returned to the ED following a discrepant read. Direct and indirect costs to the patient, family, hospital, and society for these return visits were calculated. During the study period, 8310 diagnostic imaging studies were performed, with 207 (2.5%) discrepant reads. Among the discrepant reads, 37 (0.4% of total, 17.9% of discrepant) patients had a return visit to the ED for further management. Including ED charges, time and travel costs to the family, and costs of radiation exposure, return visits for radiologic discrepancies over this 8-month period cost a total of $84,686.47, averaging $2288.82 per patient. Though the overall diagnostic imaging discrepancy rate among our study population was low, the clinically significant discrepancies requiring return ED visits were potentially high risk, and costly for the patient, family, and healthcare system.

Because of the increasing concern about its excessive and inappropriate use, guidelines have been developed for the appropriate use of diagnostic imaging [1-3]. Guidelines for diagnostic imaging are also incorporated into more comprehensive clinical practice guidelines [4,5]. Guidelines should be evidence based [6], and in assessing the evidence, accuracy is usually the primary criterion used to evaluate the role of diagnostic imaging [7,8]. Unfortunately, the quality of the evidence is usually given a lower grade [4,5], and the methodology for assessing the evidence in imaging guidelines has been criticized [9]. In fact, the type of evidence needed for imaging guidelines needs to be reassessed. Accuracy is obviously a very important attribute of effective diagnostic imaging. A study designed to test the accuracy of diagnostic imaging must be methodologically rigorous to avoid bias, and the methodology must be clearly described in any report [10]. The ost difficult issue in the design of study of the accuracy of a diagnosic imaging procedure is the selecion of the reference or “gold” stanard against which the accuracy of he diagnostic test is measured. The est reference standard is usually athology. In the ideal world, all he patients in a study should be ssessed by the same reference stanard. However, in practice, this is irtually never possible. In assessing he accuracy of diagnostic imaging, atients in a study who are thought o have the condition being assessed ay undergo biopsy or some other ype of surgical exploration, and the ccuracy of the test for those patients can be assessed against the reference standard of pathology. However, patients who do not have any evidence of the disease on their imaging studies cannot ethically undergo biopsy and are therefore assessed using a different reference standard, usually follow-up. This results in what is called verification bias, and verification bias can result in overestimation of both sensitivity and specificity [10]. If 2 diagnostic imaging examinations are being compared, and the same reference standards are being used for both, verification bias may be less of a problem. There are also statistical methods available that can help correct for verification bias [11]. However, if the true accuracy of a diagnostic imaging study is being investigated, verification bias is a significant and usually unavoidable problem. Defining a reference standard for assessing the accuracy of imaging in the diagnosis of conditions that are not usually or cannot be confirmed pathologically becomes even more difficult. For instance, radiography has been used to diagnose fractures for more than a century [12]. We do know certain situations in which the diagnostic accuracy of an x-ray is limited, for instance, in the diagnosis of fractures of the femoral neck in the elderly [13], but there have been no large-scale studies to determine the overall accuracy of x-rays in the diagnosis of fractures. There are other conditions in which the establishment of a reference standard is extremely difficult or controversial. A very common indication for an x-ray of the chest is the diagnosis of pneumonia. However, we do not know the ac

Objective. To develop a pathway to provide safe, effective, and efficient sedation for pediatric diagnostic imaging studies using non-radiology personnel. Materials and methods. A multidisciplinary team considered manpower and training requirements and national sedation standards before designing a sedation pathway, which included scheduling, pre-sedation history and physical, medication protocols, and monitoring. Oral and IV medication protocols were developed based on patient age and weight. Sedation delays were defined as >15 min (IV) or >30 min (PO) from start of sedation to start of imaging. A sedation failure resulted in an incomplete diagnostic imaging study. Failure rates of 124 sedations before and 388 sedations after the pathway were compared. Results. The sedation failure rate for 7 months prior to pathway initiation was 15% (19/124). In the first 25 months after pathway initiation, failures were significantly reduced to 1.5% (6/388) (P 55 min). Deviation from the recommended medication protocol accounted for most of the 115 delays. Only minor adverse events were seen (12/388, 3.1%). Conclusion. Implementing a pediatric sedation pathway significantly decreases the sedation failure rate. Pediatric residents and nurses can safely, effectively and efficiently sedate pediatric patients for routine diagnostic imaging procedures without the need for a radiology department sedation team in a department with a small-to-moderate volume of pediatric patients.