An analysis of radiographer preliminary image evaluation - A focus on common false negatives

Radiographers' insights on the impact of their potential role in image interpretation within a low resource setting

INTRODUCTION

The global shortage of radiologists has led to a growing concern in medical imaging, prompting the exploration of strategies, such as including radiographers in image interpretation, to mitigate this challenge. However, in low-resource settings, progress in adopting similar approaches has been limited. This study aimed to explore radiographers' perceptions regarding the impact of their potential role in image interpretation within a low-resource setting.

METHODS

The study used a qualitative descriptive design and was conducted at two public referral hospitals. Radiographers with at least one year of experience were purposively sampled and interviewed using a semi-structured interview guide after consenting. Data saturation determined the sample size, and content analysis was applied for data analysis.

RESULTS

Two themes emerged from fourteen interviews conducted with two male and twelve female radiographers. Theme one revealed the potential for enhanced healthcare delivery through improved diagnostic support, bridging radiologist shortages, career development and fulfilment as positive outcomes of role extension. Theme two revealed possible implementation hurdles including radiographer resistance and reluctance, limited training, lack of professional trust, and legal and ethical challenges.

CONCLUSION

Radiographers perceived their potential participation positively, envisioning enhanced healthcare delivery, however, possible challenges like resistance and reluctance of radiographers, limited training, and legal/ethical issues pose hurdles. Addressing these challenges through tailored interventions, including formal education could facilitate successful implementation. Further studies are recommended to explore radiographers' competencies, providing empirical evidence for sustaining and expanding this role extension.

IMPLICATION FOR PRACTICE

The study further supports the integration of radiographers into image interpretation with the potential to enhance healthcare delivery, however, implementation challenges in low-resource settings require careful consideration.

Analysing false-positive errors when Australian radiographers use preliminary image evaluation

INTRODUCTION

Diagnostic errors in the emergency departments can have major implications on patient outcomes. Preliminary Image Evaluation (PIE) is a brief comment written by a radiographer describing an acute or traumatic pathology on a radiograph and can be used to complement referrer's image interpretation in the absence of the radiologist report. Currently, no studies exist that focus their analysis on false-positive (FP) errors in PIE. The purpose of this study was to investigate the regions of the body that cause the most FP errors and recognise other areas in image interpretation that may need additional attention.

METHODS

A longitudinal retrospective clinical audit was conducted to determine the accuracy of radiographer PIE's over 5 years from January 2016 to December 2020. PIE's were compared to the radiologist report to assess for diagnostic accuracy. FP and unsure errors were further categorised by anatomical region and age.

RESULTS

Over this period, a sample size of 11,090 PIE audits were included in the study demonstrating an overall PIE accuracy of 87.7%. Foot, ankle and chest regions caused the most FP errors, while ankle, shoulder and elbow caused the most unsure cases. 76% of the unsure cases were negative for any pathology when compared to the radiologist report. The paediatric population accounted for 21.3% of FP cases and 33.6% of unsure cases.

CONCLUSION

Findings in this study should be used to tailor education specific to radiographer image interpretation. Improving radiography image interpretation skills can assist in improving referrer diagnostic accuracy, thus improving patient outcomes.

Real-time x-ray abnormality alerts for emergency departments using a radiographer comment model - a multisite pilot study

INTRODUCTION

The timely communication of clinically significant image appearances to Emergency Department (ED) referrers is necessary for optimum patient care. Australian reliance on verbal communication only is time-limited, open to misinterpretation and lacks transparency. A combined radiographer alert and comment model was designed to reliably communicate image abnormalities to ED referrers in real-time.

METHODS

A multidisciplinary steering group designed the model for all ED general imaging. Protocols were developed to document radiographer comments (critical, urgent and clinically significant) in patients' medical records. Critical findings were communicated directly to ED. Five NSW hospitals varying in size, complexity and population demographics piloted the model between three to twelve months during 2021-2022. Site auditors compared comments with the radiology report and designated each as True Positive (TP), False Positive (FP), indeterminate and clinically significant. Indeterminate cases were analysed by an external radiologist. Inter-observer consensus was obtained for all classifications via two independent auditors. The Positive Predictive Value (PPV), or precision of the comment, was calculated for each site.

RESULTS

Radiographers (n = 69) provided comments for 1102 cases. The pooled average PPV for TP was 0.96; (0.947-0.971; 95% CI). The weighted mean error (FP comments) was 3.9%; (2.9% - 5.3%.; 95% CI).

CONCLUSION

The Radiographer Comment model provided consistent levels of commenting precision and reproducibility across a range of sites with a pooled average PPV (0.96). The False Positive rate or weighted mean error (FP) of 3.9% (2.9% - 5.3%.; 95% CI) was low.

IMPLICATIONS FOR FUTURE PRACTICE

A strategic, interprofessional approach in the implementation of an image alert combined with a Radiographer Comment can be adapted across a variety of hospital settings for ED and other departments.

Australian radiographer roles in the emergency department; evidence of regulatory compliance to improve patient safety - A narrative review

OBJECTIVES

Using a narrative approach, this paper aims to determine the extent of Australian radiographers' regulatory compliance to improve patient safety when performing appendicular X-ray and non-contrast brain computed tomography (CT) in the Emergency Department (ED).

KEY FINDINGS

A narrative review explored relevant literature and key regulatory policy. Ten documents were identified, three main themes were developed related to the radiographer roles in X-ray request justification, dose optimisation and preliminary image evaluation (PIE). Radiographers were equally aware of justification and optimisation pre and post the introduction of a Medical Code of Practice. The collective PIE accuracy of radiographers remained unaffected by changes in mode of PIE delivery and regulatory factors but varied based on the anatomical region.

CONCLUSION

While current Australian regulations mandate radiographer request justification, dose optimisation and PIE, the degree of compliance by Australian radiographers remains uncertain. Current literature provides evidence that radiographers can improve patient care and safety through justification, optimisation, and PIE delivery. Change in workplace practice, supported by key stakeholders including radiologists, is essential to integrate radiographers' functions into routine ED clinical practice. Further research is required to audit radiographers' regulatory compliance to improve patient safety.

IMPLICATIONS FOR PRACTICE

Patient safety in ED can be improved with timely and accurate diagnosis provided by radiographers. Radiographers have a professional obligation to adhere to the capabilities and standards for safe medical radiation practice defined by Australian regulations. Therefore, radiographers must justify the X-ray request, optimise the radiation dose where appropriate and communicate urgent or unexpected findings to the referrer.

A revolutionary acute subdural hematoma detection based on two-tiered artificial intelligence model

BACKGROUND

The article was planned to make the first evaluation in terms of acute subdural hemorrhages, thinking that it can help in appropriate pathologies by tomography interpretation with the artificial intelligence (AI) method, at least in a way to quickly warn the responsible doctor.

METHODS

A two-level AI-based hybrid method was developed. The proposed model uses the mask-region convolutional neural network (Mask R-CNN) technique, which is a deep learning model, in the hemorrhagic region's mask generation stage, and a problem-specific, optimized support vector machines (SVM) technique which is a machine learning model in the binary classification stage. Furthermore, the bee colony algorithm was used for the optimization of SVM algorithms' parameters.

RESULTS

In the first stage, the mean average precision (mAP) value was obtained as 0.754 when the intercept over union (IOU) value was taken as 0.5 with the Mask R-CNN architecture used. At the same time, when a 5-fold cross-validation was applied, the mAP value was obtained 0.736. With the hyperparameter optimization for both Mask R-CNN and the SVM algorithm, the accuracy of the two-level classification process was obtained as 96.36%. Furthermore, final false-negative rate and false-positive rate values were obtained as 6.20%, and 2.57%, respectively.

CONCLUSION

With the proposed model, both the detection of hemorrhage and the presentation of the suspicious area to the physician were performed more successfully on two dimensional (2D) images with low cost and high accuracy compared to similar studies and today's interpretations with telemedicine techniques.

Reducing diagnostic errors in the emergency department at the time of patient treatment

OBJECTIVE

The purpose of the present study was to compare and combine the radiographic interpretation accuracy of emergency clinicians and radiographers in clinical practice.

METHODS

A total of 838 radiographic examinations were included for analysis from 1 August to 24 August 2020. The range of examinations reviewed included the appendicular and axial skeleton, chest and abdomen. Both paediatric and adult examinations were reviewed. The emergency clinician's and radiographer's interpretations for each examination were compared to the radiologist's report. This allowed mean sensitivity, specificity and diagnostic accuracy to be calculated.

RESULTS

The radiographer's interpretation demonstrated a mean sensitivity, specificity and accuracy of 80%, 98% and 92%, respectively. The emergency clinician's interpretation demonstrated a mean sensitivity, specificity and accuracy of 82%, 95% and 89%, respectively. When the radiographer's and emergency clinician's interpretations were combined, it yielded a mean sensitivity, specificity and accuracy of 90%, 93% and 92%, respectively.

CONCLUSIONS

This is the first study to directly compare and combine the accuracy of an emergency clinician's radiographic interpretation with a radiographer's interpretation within clinical practice. The present study demonstrated that with the addition of a radiographer's interpretation, an emergency clinician's interpretation can be more accurate than the emergency clinician's interpretation in isolation. This highlights the value of a radiographer's interpretation that can complement an emergency clinician's interpretation when a radiologist's report is unavailable.

The efficacy of preliminary clinical evaluation for emergency department chest radiographs with trauma presentations in pre- and post-training situations

INTRODUCTION

The chest X-ray (CXR) is the most frequently performed radiographic examination. This study evaluates radiographers' ability to localise traumatic CXR pathology and provide a preliminary clinical evaluation (PCE) for these cases.

METHODS

This observer study was performed in a district general hospital in the United Kingdom (UK). A 58-case image bank was used with 20 positive cases. Participants were awarded a maximum of three points, based on abnormality recognition and descriptive accuracy. Localisation data were recorded with ROCView. Training was delivered via short online recorded tutorials covering an introduction of a systematic search strategy for CXR, how to recognise the common abnormalities covered in the tests, how to structure a PCE and multiple practice cases to review at participants' own pace. Pre- and post-training data was recorded.

RESULTS

Nine participants completed the study. Overall, pooled sensitivity remained consistent (78.9%-78.8%) following training, specificity and accuracy showed improvement of 79.0%-89.9% and 78.9%-86.0% respectively. An increase in the number of correct localisations and PCE scores were also evident. Participants performed better at correctly identifying a pneumothorax compared to skeletal abnormalities.

CONCLUSION

Improvements in performance were evident for most participants' abnormality localisations and PCE scores, following the training intervention. The study highlighted areas of CXR PCE that may require further training, such as detecting superimposed or subtle abnormalities.

IMPLICATIONS FOR PRACTICE

This study provides additional support for the development of PCE systems in additional areas of imaging practice.

The role of quality improvement in radiography

This editorial discusses the importance of quality improvement and quality assurance in the provision of medical imaging services, by exploring two studies which aim to improve the quality of practice in emergency departments (ED). The quality of work by ED radiographers are continually planned, measured, assessed, and improved to enhance patient care outcomes - from the accurate diagnosis of patients, maintaining the consistency of diagnostic images, and to minimising radiation exposure to patients.