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OBJECTIVES: In the United Kingdom, radiographers with a qualification in image interpretation have interpreted mammograms since 1995. These radiographers work under the title of radiography advanced practitioners (RAP) or Consultant Radiographer. This study extends upon what has been very recently published by exploring further clinical, non-clinical and experiential factors that may impact the reporting performance of RAPs. METHODS: Fifteen RAPs interpreted an image test set of 60 2D mammograms of known truth using the Detected-X software platform. Unknown to the reader, twenty cases contained a malignancy. Sensitivity, specificity, lesion sensitivity, receiver operating characteristic (ROC) and jack-knife free response operating characteristic (AFROC) values were established for each RAP. Specific features that had significant impact on accuracy were identified using Student's-T and Mann Whitney tests. RESULTS: RAPs with more than 10 years' experience in image interpretation, compared to those with less than 10 years' experience, demonstrated lower specificity (51.3% vs 84.8%, p = 0.0264), ROC (0.83 vs 0.91, p = 0.0264) and AFROC (0.75 vs 0.87, p = 0.0037) values. Further, higher sensitivity values of 90.7% were seen in those RAPs who had an eye test in the last year compared to those who had not, 82% (p = 0.021). Other changes are presented in the paper. CONCLUSION: These data reveal previously unidentified factors that impact the diagnostic efficacy of RAPs when interpreting mammographic images. Highlighting such findings will empower screening authorities to better examine ways of standardising performance and offer a baseline for performance benchmarks. IMPLICATIONS FOR PRACTICE: This study for the first time performs an initial exploration of the factors that may be associated with RAP performance when interpreting screening mammograms.

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OBJECTIVES: Physician's evaluation of interstitial lung disease (ILD) extension with high-resolution computed tomography (HRCT) has limitations such as lack of objectivity and reproducibility. This study aimed to investigate the utility of computer-based deep-learning analysis using QZIP-ILD® software (DL-QZIP) compared with conventional approaches in connective tissue disease (CTD) -related ILD. METHODS: Patients with CTD-ILD visiting our Rheumatology Centre between December 2020 and April 2024 were recruited. Quantitative scores, including the percentage of lung involvement in ground-glass opacity (QGG), total fibrotic lesion (QFIB), and overall ILD extension encompassing both QGG and QFIB (QILD), calculated by DL-QZIP, were compared with semiquantitative visual method, employing intraclass correlation coefficients (ICC). We compared the capability of QILD scores to distinguish patients with forced vital capacity (FVC) % <70 in both methods determined by the area under the curve (AUC) by the receiver-operating characteristic curve analysis and DeLong's test. RESULTS: Eighty patients (median age, 66 years; 14 men) were included. Median QGG, QFIB, and QILD scores were 3.45%, 2.19%, and 5.35% using DL-QZIP, and 3.25%, 4.06%, and 8.48% using visual method, respectively. Correlations between DL-QZIP and visual method were 0.75 for QGG, 0.61 for QFIB, and 0.75 for QILD. The AUC of QILD scores for FVC% <70 was significantly higher with DL-QZIP (0.833) compared with visual method (0.660) (p < 0.01). CONCLUSION: QZIP-ILD® demonstrates superior capability in distinguishing patients with a radiological scenario correlated to severe physiological impairment, while showing relatively good correlations in quantifying the extent on HRCT compared with conventional method in CTD-ILD.

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BACKGROUND: Diagnosing and treating tonsillitis pose no significant challenge for otolaryngologists; however, it can increase the infection risk for healthcare professionals amidst the coronavirus pandemic. In recent years, with the advancement of artificial intelligence (AI), its application in medical imaging has also thrived. This research is to identify the optimal convolutional neural network (CNN) algorithm for accurate diagnosis of tonsillitis and early precision treatment. METHODS: Semi-supervised learning with pseudo-labels used for self-training was adopted to train our CNN, with the algorithm including UNet, PSPNet, and FPN. A total of 485 pharyngoscopic images from 485 participants were included, comprising healthy individuals (133 cases), patients with the common cold (295 cases), and patients with tonsillitis (57 cases). Both color and texture features from 485 images are extracted for analysis. RESULTS: UNet outperformed PSPNet and FPN in accurately segmenting oropharyngeal anatomy automatically, with average Dice coefficient of 97.74% and a pixel accuracy of 98.12%, making it suitable for enhancing the diagnosis of tonsillitis. The normal tonsils generally have more uniform and smooth textures and have pinkish color, similar to the surrounding mucosal tissues, while tonsillitis, particularly the antibiotic-required type, shows white or yellowish pus-filled spots or patches, and shows more granular or lumpy texture in contrast, indicating inflammation and changes in tissue structure. After training with 485 cases, our algorithm with UNet achieved accuracy rates of 93.75%, 97.1%, and 91.67% in differentiating the three tonsil groups, demonstrating excellent results. CONCLUSION: Our research highlights the potential of using UNet for fully automated semantic segmentation of oropharyngeal structures, which aids in subsequent feature extraction, machine learning, and enables accurate AI diagnosis of tonsillitis. This innovation shows promise for enhancing both the accuracy and speed of tonsillitis assessments.

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INTRODUCTION: Medical imaging's critical role in diagnosis requires prompt and precise image interpretation. Numerous radiology departments, especially in low-resourced settings, encounter challenges such as a shortage of radiologists in their operational setup. This study explored the perceptions of radiographers and radiologists from low-resourced departments in a single country regarding operational challenges and potential solutions in image interpretation. METHODS: A qualitative approach was utilised, involving heads of departments, senior radiographers, and radiologists with a minimum of 5 years of experience, from three major state referral hospitals. Face-to-face, semi-structured interviews were conducted in November 2022, using an interview guide that included questions on the challenges encountered during image interpretation and the proposed solutions. Data analysis was conducted using Atlas.ti version 9.0, following the four-step content analysis method. All participants willingly provided consent to participate in the study. RESULTS: Ten participants, comprising two radiologists and eight radiographers participated in the study. The research identified three main themes: image interpretation pathways, image interpretation operational challenges and proposed solutions for image interpretation. In addition, a total of 10 subthemes were generated from the three main themes. CONCLUSION: The study revealed critical challenges and the need to explore the formal inclusion of radiographers in image interpretation, as a way to improve efficiency. However, a comprehensive assessment of the image interpretation system, encompassing radiographers' knowledge and competence, is recommended for context-specific, empirical-based modifications to enhance service provision.

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AIM: To investigate the associations between the hour of the day and Prostate Imaging-Reporting and Data System (PI-RADS) scores assigned by radiologists in prostate MRI reports. MATERIALS AND METHODS: Retrospective single-center collection of prostate MRI reports over an 8-year period. Mean PI-RADS scores assigned between 0800 and 1800 h were examined with a regression model. RESULTS: A total of 35'004 prostate MRI interpretations by 26 radiologists were included. A significant association between the hour of day and mean PI-RADS score was identified (ß2 = 0.005, p < 0.001), with malignant scores more frequently assigned later in the day. CONCLUSION: These findings suggest chronobiological factors may contribute to variability in radiological assessments. Though the magnitude of the effect is small, this may potentially add variability and impact diagnostic accuracy.

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BACKGROUND: The College of Radiographers' vision was that diagnostic radiographers in the UK would be writing preliminary clinical evaluations (PCE) on images. Their 2013 policy supporting the use of PCE has not been updated in a decade and it might be suggested PCE practices in the UK have not really moved on, though elsewhere it appears to have gained traction. The aim of this scoping review was to establish the current global status of the use of PCE. METHOD: The Arksey and O'Malley scoping review framework and PRISMA-ScR guidelines were used to develop a protocol to identify studies between January 2013 to January 2024 using six databases. Collated literature was analysed using content analysis to identify themes. RESULTS: 52 relevant studies were identified for inclusion. Studies focused predominantly on evaluating accuracy, education, perceptions, and new initiatives. Themes identified a developing role in the use of PCE internationally, perhaps more than in the UK, and in a range of modalities and clinical settings though projectional radiography remains the mainstay. Barriers and drivers to the use of PCE were identified in addition to some quality mechanisms used to support PCE implementation, though impact of implementation was not well explored. CONCLUSION: Considering PCE has been an aspiration for more than a decade, it remains relatively infrequently researched. There is growing scope internationally, particularly in Australia, yet there is no real evaluation of the impact and role that PCE may have. IMPLICATIONS FOR PRACTICE: Until further research into the potential impact of PCE and barriers to its implementation, it is likely practices may not evolve with the risk AI technologies may supersede necessity for the practice.

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INTRODUCTION: There is growing interest in the development and application of standardized imaging criteria (SIC), to minimize variability and improve the reproducibility of image interpretation in head and neck squamous cell carcinoma (HNSCC). METHODS: "Squamous cell carcinoma" AND "standardized interpretation criteria" OR "radiographic response assessment" were searched using PubMed and Google Scholar for articles published between 2009 and 2024, returning 56 publications. After abstract review, 18 were selected for further evaluation, and 6 different SICs (i.e., PERCIST, Porceddu, Hopkins, NI-RADS, modified Deauville, and Cuneo) were included in this review. Each SIC is evaluated in the context of 8 desired traits of a standardized reporting system. RESULTS: Two SICs have societal endorsements (i.e., PERCIST, NI-RADS); four can be used in the evaluation of locoregional and systemic disease (i.e., PERCIST, Hopkins, NI-RADS, Cuneo), and four have specific categories for equivocal imaging results (i.e., Porceddu, NI-RADS, modified Deauville, and Cuneo). All demonstrated areas for future improvement in the context of the 8 desired traits. CONCLUSION: Multiple SICs have been developed for and demonstrated value in HNSCC post-treatment imaging; however, these systems remain underutilized. Selecting an SIC with features that best match the needs of one's practice is expected to maximize the likelihood of successful implementation.

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INTRODUCTION: With the use of expert consensus a digital training tool was developed which proved useful when teaching radiographers how to interpret chest images. The training tool included A) a search strategy and B) an educational video programme to communicate the search strategies using eye tracking technology. METHODS: A multi-reader multi-case study was undertaken to assess the effectiveness of a training tool and study day. The interventions were designed to cover a range of potential pathological presentations. Participants, physiotherapists and nurse practitioners working at a cardiothoracic Intensive Care Unit (ICU), were asked to interpret 20 chest images at the beginning of the study and following access to each intervention. Participants received access to the training tool at different times for a period of 4-6 weeks. A study day was then be provided to all participants and interpretations of a different dataset were completed by all. Each participant was asked to complete a questionnaire to gain perceptions of the training provided. RESULTS: Twenty-eight participants interpreted a total of 1680 chest radiographs. Improvements in specificity were noted across the participants. Sensitivity fell in both groups following both training interventions. CONCLUSION: Face to face learning and digital components are potentially useful in professional development and revision in chest x-ray interpretation for non-medical healthcare professionals working in an ICU setting. IMPLICATIONS FOR PRACTICE: The training tool and study day may be useful as image interpretation revision aids or to accompany formal methods of education.

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OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomical structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal. METHODS: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions. RESULTS: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3 % and a normalised surface distance (NSD) of 98.2 ± 2.2 %. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4 % and a NSD of 98.4 ± 3.6 %. CONCLUSIONS: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software. CLINICAL SIGNIFICANCE: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.

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BACKGROUND: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening condition, especially in cases of delayed treatment. Computed tomography angiography (CTA) plays a pivotal role in the early identification of upper and lower GIB and in the prompt treatment of the haemorrhage. AIM: To determine whether a volumetric estimation of the extravasated contrast at CTA in GIB may be a predictor of subsequent positive angiographic findings. METHODS: In this retrospective single-centre study, 35 patients (22 men; median age 69 years; range 16-92 years) admitted to our institution for active GIB detected at CTA and further submitted to catheter angiography between January 2018 and February 2022 were enrolled. Twenty-three (65.7%) patients underwent endoscopy before CTA. Bleeding volumetry was evaluated in both arterial and venous phases via a semi-automated dedicated software. Bleeding rate was obtained from volume change between the two phases and standardised for unit time. Patients were divided into two groups, according to the angiographic signs and their concordance with CTA. RESULTS: Upper bleeding accounted for 42.9% and lower GIB for 57.1%. Mean haemoglobin value at the admission was 7.7 g/dL. A concordance between positive CTA and direct angiographic bleeding signs was found in 19 (54.3%) cases. Despite no significant differences in terms of bleeding volume in the arterial phase (0.55 mL vs 0.33 mL, P = 0.35), a statistically significant volume increase in the venous phase was identified in the group of patients with positive angiography (2.06 mL vs 0.9 mL, P = 0.02). In the latter patient group, a significant increase in bleeding rate was also detected (2.18 mL/min vs 0.19 mL/min, P = 0.02). CONCLUSION: In GIB of any origin, extravasated contrast volumetric analysis at CTA could be a predictor of positive angiography and may help in avoiding further unnecessary procedures.

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OBJECTIVES: Our study comprised a single-center retrospective in vitro correlation between spectral properties, namely ρ/Z values, derived from scanning blood samples using dual-energy computed tomography (DECT) with the corresponding laboratory hemoglobin/hematocrit (Hb/Hct) levels and assessed the potential in anemia-detection. METHODS: DECT of 813 patient blood samples from 465 women and 348 men was conducted using a standardized scan protocol. Electron density relative to water (ρ or rho), effective atomic number (Zeff), and CT attenuation (Hounsfield unit) were measured. RESULTS: Positive correlation with the Hb/Hct was shown for ρ (r-values 0.37-0.49) and attenuation (r-values 0.59-0.83) while no correlation was observed for Zeff (r-values -0.04 to 0.08). Significant differences in attenuation and ρ values were detected for blood samples with and without anemia in both genders (p value < 0.001) with area under the curve ranging from 0.7 to 0.95. Depending on the respective CT parameters, various cutoff values for CT-based anemia detection could be determined. CONCLUSION: In summary, our study investigated the correlation between DECT measurements and Hb/Hct levels, emphasizing novel aspects of ρ and Zeff values. Assuming that quantitative changes in the number of hemoglobin proteins might alter the mean Zeff values, the results of our study show that there is no measurable correlation on the atomic level using DECT. We established a positive in vitro correlation between Hb/Hct values and ρ. Nevertheless, attenuation emerged as the most strongly correlated parameter with identifiable cutoff values, highlighting its preference for CT-based anemia detection. CLINICAL RELEVANCE STATEMENT: By scanning multiple blood samples with dual-energy CT scans and comparing the measurements with standard laboratory blood tests, we were able to underscore the potential of CT-based anemia detection and its advantages in clinical practice. KEY POINTS: Prior in vivo studies have found a correlation between aortic blood pool and measured hemoglobin and hematocrit. Hemoglobin and hematocrit correlated with electron density relative to water and attenuation but not Zeff. Dual-energy CT has the potential for additional clinical benefits, such as CT-based anemia detection.

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INTRODUCTION: Radiographer commenting is a written account of suspected abnormalities identified on medical imaging examinations by the radiographer at the time of image acquisition. Radiographer comments were originally implemented to support emergency clinicians; however, they may also have the potential to support radiologists in reducing missed findings. Therefore, the aim of this study was to investigate if a newly implemented radiographer comment system could reduce the number of errors made in radiology reports for general X-rays. Incidental findings from multisite collaborative research led to the hypothesis that in some cases radiographer comments could accurately detect abnormal X-ray appearances that were not otherwise documented in the radiologist report, thereby enabling results to be revised and errors collaboratively reduced [1]. METHODS: This study was conducted at an 800-bed hospital, where 92% of general radiographers self-selected to participate. Radiographer comments were provided to referring physicians through the electronic medical record and could be made for any emergency or inpatient general X-ray examinations. All comments made over a 12-month period were audited against the corresponding radiologist report. Radiologists were blinded to radiographer comments at the time of reporting. Where discrepancies between the radiographer comment and radiologist report arose, additional radiologist review or subsequent imaging reports were used to determine the accurate interpretation. The number of discrepant radiographer comments that were deemed true positive (TP) and provided new and correct diagnostic information compared to the radiologist report were identified. These were converted to a percentage of total radiographer comments that were therefore able to positively influence radiologist report accuracy. The number of discrepant cases where radiographer comments were deemed false positive (FP) was also measured and converted to a percentage of the total comments. Confidence intervals for both TP and FP binomial proportions were calculated using the Wilson Score Interval. RESULTS: Over 12 months, 282 radiographer comments were made to alert clinically significant radiographic appearances on general X-ray. Of these, 32 radiographer comments were discrepant with the report. Of these 32 comments, 24 were deemed TP meaning they correctly identified a pathological imaging appearance that was not otherwise documented in the radiology report. Therefore, 8.5% of all radiographer comments added value by correctly identifying a pathology that was not otherwise documented, 95% CI (5.8% - 12.4%). This enabled results to be promptly amended and reporting errors collaboratively reduced. Conversely, eight (2.8%) radiographer comments were discrepant with the report but deemed FP and did not add value to the investigation, 95% CI (1.4% - 5.5%). The remaining 250 non-discrepant comments did not contribute to error reduction but provided real-time abnormality detection that benefitted managing teams. CONCLUSION: These findings are consistent with previous literature proposing radiographer comments may provide a safety net for radiologists due to factors such as direct patient contact, ability to expand on clinical history, and difference in accumulated expertise. This study demonstrates that radiographer comments may be effectively used as a multidisciplinary error-reduction tool to assist radiologists in their important role and improve clinical outcomes.

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PURPOSE: To determine the optimal window setting for virtual monoenergetic images (VMI) reconstructed from dual-layer spectral coronary computed tomography angiography (DE-CCTA) datasets. MATERIAL AND METHODS: 50 patients (30 males; mean age 61.1 ± 12.4 years who underwent DE-CCTA from May 2021 to June 2022 for suspected coronary artery disease, were retrospectively included. Image quality assessment was performed on conventional images and VMI reconstructions at 70 and 40 keV. Objective image quality was assessed using contrast-to-noise ratio (CNR). Two independent observers manually identified the best window settings (B-W/L) for VMI 70 and VMI 40 visualization. B-W/L were then normalized with aortic attenuation using linear regression analysis to obtain the optimized W/L (O-W/L) settings. Additionally, subjective image quality was evaluated using a 5-point Likert scale, and vessel diameters were measured to examine any potential impact of different W/L settings. RESULTS: VMI 40 demonstrated higher CNR values compared to conventional and VMI 70. B-W/L settings identified were 1180/280 HU for VMI 70 and 3290/900 HU for VMI 40. Subsequent linear regression analysis yielded O-W/L settings of 1155/270 HU for VMI 70 and 3230/880 HU for VMI 40. VMI 40 O-W/L received the highest scores for each parameter compared to conventional (all p < 0.0027). Using O-W/L settings for VMI 70 and VMI 40 did not result in significant differences in vessel measurements compared to conventional images. CONCLUSION: Optimization of VMI requires adjustments in W/L settings. Our results recommend W/L settings of 1155/270 HU for VMI 70 and 3230/880 HU for VMI 40.

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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.

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PURPOSE: Missed and misidentified neoplastic lesions in longitudinal studies of oncology patients are pervasive and may affect the evaluation of the disease status. Two newly identified patterns of lesion changes, lone lesions and non-consecutive lesion changes, may help radiologists to detect these lesions. This study evaluated a new interpretation revision workflow of lesion annotations in three or more consecutive scans based on these suspicious patterns. METHODS: The interpretation revision workflow was evaluated on manual and computed lesion annotations in longitudinal oncology patient studies. For the manual revision, a senior radiologist and a senior neurosurgeon (the readers) manually annotated the lesions in each scan and later revised their annotations to identify missed and misidentified lesions with the workflow using the automatically detected patterns. For the computerized revision, lesion annotations were first computed with a previously trained nnU-Net and were then automatically revised with an AI-based method that automates the workflow readers' decisions. The evaluation included 67 patient studies with 2295 metastatic lesions in lung (19 patients, 83 CT scans, 1178 lesions), liver (18 patients, 77 CECT scans, 800 lesions) and brain (30 patients, 102 T1W-Gad MRI scans, 317 lesions). RESULTS: Revision of the manual lesion annotations revealed 120 missed lesions and 20 misidentified lesions in 31 out of 67 (46%) studies. The automatic revision reduced the number of computed missed lesions by 55 and computed misidentified lesions by 164 in 51 out of 67 (76%) studies. CONCLUSION: Automatic analysis of three or more consecutive volumetric scans helps find missed and misidentified lesions and may improve the evaluation of temporal changes of oncological lesions.

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OBJECTIVES: Interpretation of dental radiographs is a difficult process, particularly for inexperienced students. This study introduced concept mapping for dental students to help in the radiographic interpretation of common jaw lesions. We aimed to analyze the efficacy of the concept map (CM) in radiographic interpretation, with a discussion of the diagnostic reasoning dilemma. METHODS: This study included 39 dental students. After a 1-h class for CM guidance and based on three group discussions and one-on-one feedback, the students completed and submitted CMs for three jaw diseases (ameloblastoma, odontogenic keratocyst, and simple bone cyst). All participants underwent a pretest and posttest of knowledge and diagnosis; all students but one completed an open-ended questionnaire regarding the use of CMs. RESULTS: Concept mapping effectively improved diagnostic accuracy. The participants' posttest scores were better than their pretest scores in both knowledge and diagnostic tests. Most of the students attempted radiographic interpretation through analytic reasoning. The time required for the students to draw a CM varied from student to student from 3-5 h to 1-3 days. CONCLUSION: This study shows that CMs can improve the radiographic diagnostic ability of dental students by providing a framework for analytic reasoning. Continuous research is warranted to improve the effectiveness of CM in oral radiographic interpretation in the dental student's class.

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INTRODUCTION: Policymakers wish to extend access to medical records, including medical imaging. Appreciating how patients might review radiographs could be key to establishing future training needs for healthcare professionals and how image sharing could be integrated into practice. METHOD: A pilot study in the UK using a survey was distributed to adult participants via the online research platform Prolific. All subjects were without prior professional healthcare experience. Participants reviewed ten radiographs (single projection only) and were asked a two-stage question. Firstly, if the radiograph was 'normal' or 'abnormal' and secondly, if they had answered 'abnormal', to identify the abnormality from a pre-determined list featuring generic terms for pathologies. RESULTS: Fifty participants completed the survey. A mean of 65.8 % of participants were able to correctly identify if radiographs were normal or abnormal. Results in relation to the identification of a pathology were not as positive, but still notable with a mean of 46.4 % correctly identifying abnormalities. Qualitative data demonstrated that members of the public are enthralled with reviewing radiographs and intrigued to understand their performance in identifying abnormalities. CONCLUSION: In the pilot, members of the public could identify if a radiograph is normal or abnormal to a reasonable standard. Further detailed interpretation of images requires supportive intervention. This pilot study suggests that patients can participate in image sharing as part of their care. Image sharing may be beneficial to the therapeutic relationship, aiding patient understanding and enhancing consultations between healthcare professional and patient. Further research is indicated.

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Background and Aims: Teleradiology is the practice of interpreting medical images acquired in an off-site location. Teleradiology has been utilized widely around the world to address the needs for subspecialty coverage, workload balancing, and as a solution for understaffing. This study aims to assess the perceptions of teleradiology among radiologists in Saudi Arabia, investigate any challenges they might face, and explore strategies that would help mitigate those challenges. Methods: A cross-sectional study using a self-administered electronic questionnaire was conducted to collect responses from radiologists practicing or having practiced teleradiology in Saudi Arabia. The questionnaire was conducted from January to June 2023, and 105 responses were included in the analysis. The responses were analyzed using chi-squared testing to investigate factors affecting the radiologists' perceptions. Results: The most common challenges for teleradiology were access to patients' health records, access to prior imaging exams, and concerns about image quality assurance. Around 74% of participants perceived teleradiology to be beneficial for geographic, after-hour, and subspecialties coverage. Teleradiology was also perceived to help reduce the turn-around time of radiology interpretations. Better communication with referring physicians and technologists was seen as a way to help improve teleradiology services. Conclusion: The findings suggest that the perception of teleradiology's challenges and benefits may not be influenced by experience, workplace, or subspecialty. Emphasis should be placed on the importance of quality assurance of images acquired remotely. Addressing the concerns and challenges related to access to patients' health records is also crucial to ensuring the successful implementation of teleradiology in the country.

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INTRODUCTION: In 2020, the Medical Radiation Practice Board of Australia made several revisions to its professional capabilities. To address this, medical radiation practitioners, including diagnostic radiographers, are required to escalate urgent findings in all radiographic settings. However, the confidence of radiographers in articulating descriptions of radiographic findings varies despite this requirement. This cross-sectional study explores how the implementation of eportfolio affects student self-perceived confidence in identifying and describing radiographic findings in both an academic and a clinical setting. METHODS: A Qualtrics survey was distributed to second-year radiography students who had used eportfolios. The survey comprised of four questions using a Likert-scale and one open-ended question. Quantitative data were analysed using the Wilcoxon signed-rank test and qualitative data was thematically assessed. RESULTS: Overall, 55 of 65 radiographic students (85%) completed the survey. Confidence (strongly agree and agree) decreased from 89% to 74% between academic and clinical environments when identifying abnormalities, and 89% to 73% when describing findings. This finding highlights the challenges students face when in the clinical environment. Wilcoxon signed rank test analysed a statistically significant relation between the two environments (P < 0.05). However, the relationship between identifying and describing skills was not statistically significant (P > 0.05). Following a review of the qualitative data, three recurring themes were identified among responses. CONCLUSION: ePortfolios assist in improving confidence in identification and description of radiographic abnormalities, particularly in an academic setting. The clinical environment presents unique challenges which may limit student clinical performance; however, this requires further investigation.