Interpretation Of Radiographs Research Articles

NIMG-31. CASE REPORT: DIAGNOSIS OF AN INFILTRATIVE GLIOMA IN A LI-FRAUMENI SYNDROME PATIENT OBSCURED BY LESION RESPONSIVENESS TO NSCLC TREATMENT

Abstract Li-Fraumeni syndrome is a rare, autosomal dominant disorder linked to germline mutations of the TP53 suppressor gene. Patients with this syndrome are predisposed to various malignancies and a variety of brain tumors to include choroid plexus carcinoma, medulloblastoma, and glioma. We present a 46-year-old woman with a history of Li-Fraumeni syndrome which manifested with multiple systemic malignancies including breast cancer, ovarian teratoma, and leiomyosarcoma. The patient had been undergoing MRI brain surveillance since 2018, which was initially notable for a right cerebellar midline focus of enhancement associated with slowly evolving right middle cerebellar peduncle FLAIR signal, with no detectable neurologic symptoms. She underwent systemic therapy for non-small cell lung cancer (NSCLC) with pemetrexed/cisplatin. Her next MRI brain in August 2023 showed resolution of the cerebellar enhancement with small residual FLAIR signal. In April 2024, the patient presented with new neurologic symptoms to include ataxia, dizziness, difficulty swallowing, and memory loss. Repeat MRI brain revealed new infiltrative FLAIR signal throughout the right temporal lobe extending from the posterior fossa, contiguous with the previously seen cerebellar findings and consistent with infiltrative glioma. Due to fragmented records and care in multiple systems, her updated MRI initially created a diagnostic challenge with a radiographic interpretation of likely encephalitis. This is a unique case documenting a middle-aged female with Li-Fraumeni syndrome, followed for multiple cancers, presenting with new neurologic symptoms and progressive infiltrative FLAIR changes spanning from the cerebellum into the right temporal lobe. These findings highlight the natural history of a TP53 deficient tumor that ostensibly responded to a cisplatin-based regimen given for a different indication, thereby delaying time to symptom onset and need for biopsy. Surveillance of low grade lesions in patients with underlying tumor predisposition syndromes must be interpreted in context of systemic disease burden and concurrent treatments for other neoplasms.

Deep learning improves physician accuracy in the comprehensive detection of abnormalities on chest X-rays.

Chest X-rays are the most commonly performed medical imaging exam, yet they are often misinterpreted by physicians. Here, we present an FDA-cleared, artificial intelligence (AI) system which uses a deep learning algorithm to assist physicians in the comprehensive detection and localization of abnormalities on chest X-rays. We trained and tested the AI system on a large dataset, assessed generalizability on publicly available data, and evaluated radiologist and non-radiologist physician accuracy when unaided and aided by the AI system. The AI system accurately detected chest X-ray abnormalities (AUC: 0.976, 95% bootstrap CI: 0.975, 0.976) and generalized to a publicly available dataset (AUC: 0.975, 95% bootstrap CI: 0.971, 0.978). Physicians showed significant improvements in detecting abnormalities on chest X-rays when aided by the AI system compared to when unaided (difference in AUC: 0.101, p < 0.001). Non-radiologist physicians detected abnormalities on chest X-ray exams as accurately as radiologists when aided by the AI system and were faster at evaluating chest X-rays when aided compared to unaided. Together, these results show that the AI system is accurate and reduces physician errors in chest X-ray evaluation, which highlights the potential of AI systems to improve access to fast, high-quality radiograph interpretation.

Implementation and analysis of clinically-relevant anatomy imaging for first-year dental students.

Radiographic imaging interpretation is a central competency of the dental profession. Previous research has determined that radiographic interpretations vary across dentists. In addition, the efficacy of empirical learning within the realm of medical imaging analysis remains understudied. This project aimed to improve an existing anatomy curriculum as well as students' radiographic interpretation skills via implementation of medical radiographic case studies with scaffolded exercises. Three medical imaging activities were developed by the authors and presented in the anatomy laboratory for 60 first-year dental students. Each module included identical pre-activity and post-activity questionnaires, radiographic images with corresponding lesson plans, and open-response questions on the activity's valuable and challenging components. Pre-activity and post-activity questionnaire scores were compared via a Wilcoxon signed rank test. Kruskal-Wallis tests were conducted to determine the impact of previous anatomy experience and previous medical imaging experience on student performance. Thematic analysis was applied to open response comments. A statistically significant improvement in questionnaire scores was observed in the first medical imaging activity. No significant change in scores was observed for the other two activities. Students valued the activities' interactive structure, review of course material, and application to the dental profession. Students reported challenges in radiographic image interpretation and lack of previous knowledge on course concepts. While medical imaging activities failed to consistently improve student-learning outcomes, they introduced skill development in radiographic analysis and increased student confidence. These findings suggest a need for additional research on experiential methodologies within medical imaging education.

Influence of Prior Imaging Review on Recommendations for Additional Diagnostic Testing: Retrospective Analysis of Imaging Reports in a Chiropractic Radiology Practice

ObjectiveThe purpose of this study was to assess the influence of prior imaging review on recommendations for additional diagnostic testing in an academic chiropractic radiology practice. A secondary aim was to explore the influence of prior imaging review on radiographic interpretation. MethodsWe retrospectively reviewed radiology reports generated from July 18, 2022, to July 18, 2023, from the Palmer College of Chiropractic main campus (Davenport, Iowa) clinic system. Imaging interpretation included an automated search for prior images in an internal picture archival and communication system (PACS). Images from regional health system databases were available and sought by radiologists when (1) unclear radiologic findings had potential clinical implications or (2) prior imaging could clarify potential problems detected in a clinical history. Data were abstracted to a secure adaptive electronic questionnaire and analyzed descriptively. ResultsWe reviewed 1712 radiographic and 165 musculoskeletal diagnostic ultrasound reports for 1552 unique individuals (811 [52.3%] females and 741 [47.7%] males) with a mean age of 42.1 years (range, 2-93 years). Prior imaging was described in 417 (22.2%) reports; 246 (58.9%) indicated images from internal PACS, 192 (46.0%) indicated images from external PACS, and 21 noted both internal and external PACS. Prior imaging findings were credited with answering a clinical question in 98 (23.5%), and a radiographic question in 228 (54.7%) of 417 reports. The process negated the need for follow-up diagnostic testing recommendations in 119 (28.5%) instances, leading to additional imaging recommendations in 19 (4.6%). ConclusionData obtained in this study suggest that comparing current and previous imaging may help reduce unnecessary additional imaging or follow-up diagnostic testing recommendations. Prior imaging review may also facilitate diagnostic confidence and interpretation clarity.

The Accuracy of Radiographers Preliminary Image Evaluations of Axial Radiographs: a Prospective Longitudinal Study at Al-Hussein Hospital, Iraq

Introduction: Modern emergency departments are under increasing pressure that can only be alleviated by new approaches to meeting demand. One strategy could be the adoption of radiographer preliminary image evaluations (PIEs), which would significantly reduce the time it takes emergency teams to receive critical imagery results. The aim of this study was to examine the accuracy of radiographers’ interpretations of axial radiographs and the impact a short training program had on their image interpretation skills. Methods: Forty-one radiographers volunteered to participate in the study. From 15 January to 15 April 2023 radiographers produced PIEs for 24 axial radiographs which were compared to the radiology reports for the same images. The accuracy each of the radiographers’ PIEs were categorized as true positive, true negative, false positive and false negative, with numerical scores to enable mean accuracies to be calculated. The radiographers’ accuracy was then reassessed on the same images after they had completed a two-week training program on axial skeletal radiograph interpretation. Results: The study reported that demonstrated that most (TP) radiographer PIEs (M = 5.66, SD = 1.24) were about facial bone fracture. Moreover, this study demonstrated that most (FN/TP) radiographer PIEs (M = 3.83, SD = 1.69) were that cases about inflammatory disease of the axial spine, such as ankylosing spondylitis. In contrast, the most common cases misinterpreted were about cervical spine disorders such as diffuse idiopathic skeletal hyperostosis (DISH) (M = 2.49, SD = 1.36). Years of experience in radiography showed a positive but not statistically significant influence on accuracy. Additionally, post training mean accuracy significantly improved. Conclusion: This study found radiographers provided quite accurate PIEs for facial bone fractures when compared to the full radiology reports of the same images. The findings also highlighted specific pathologies that were frequently misinterpreted. A two-week training program was found to be effective at improving radiographers’ ability to correctly identify and describe abnormalities present in axial radiographs.

Sternalis featuring tendomuscular fusion to the contralateral sternocleidomastoid: a cadaveric case report.

To report the morphologic and spatial relationships of a bilateral sternalis muscle variant. Routine cadaveric dissection in an undergraduate anatomy laboratory revealed two sternalis muscles parasternal to the sternal body. Subsequent fine prosection of the anterior thoracic wall and neck was carried out to uncover the soft tissue attachments of both sternalis muscles. Positional relationship to neighboring anterior thoracic and neck structures, and geometric dimensions of the muscle bellies and tendons, were documented. Both sternalis muscles were imbedded in the pectoral fascia, with their muscle fibers running obliquely to the midsternal line. The right sternalis muscle was notably larger in length, width, and thickness compared to the sternalis muscle on the left. The right sternalis muscle featured a distinct superior cord-like intermediate tendon that traversed superolateral and fused directly with the contralateral sternomastoid and sterno-occipital portions of the left sternocleidomastoid muscle. The superior tendon of the left sternalis muscle was aponeurotic and affixed to the cord-tendon of the right sternalis muscle. A distinct tendinous entheses for the sternal head for both sternocleidomastoid muscles were noted at the manubrial body. This case report describes a unique bilateral sternalis muscle variant with conjoined sternocleidomastoid muscle integration. This anatomical description of a sternalis-sternocleidomastoid muscle morphology may supplement radiographic interpretations and support diagnostic accuracy.

The Accuracy of Radiographers Preliminary Image Evaluations of Axial Radiographs: a Prospective Longitudinal Study at Al-Hussein Hospital, Iraq

Introduction: Modern emergency departments are under increasing pressure that can only be alleviated by new approaches to meeting demand. One strategy could be the adoption of radiographer preliminary image evaluations (PIEs), which would significantly reduce the time it takes emergency teams to receive critical imagery results. The aim of this study was to examine the accuracy of radiographers’ interpretations of axial radiographs and the impact a short training program had on their image interpretation skills. Methods: Forty-one radiographers volunteered to participate in the study. From 15 January to 15 April 2023 radiographers produced PIEs for 24 axial radiographs which were compared to the radiology reports for the same images. The accuracy each of the radiographers’ PIEs were categorized as true positive, true negative, false positive and false negative, with numerical scores to enable mean accuracies to be calculated. The radiographers’ accuracy was then reassessed on the same images after they had completed a two-week training program on axial skeletal radiograph interpretation. Results: The study reported that demonstrated that most (TP) radiographer PIEs (M 66, SD = 1.24) were about facial bone fracture. Moreover, this study demonstrated that most (FN/TP) radiographer PIEs (M = 3.83, SD = 1.69) were that cases about inflammatory disease of the axial spine, such as ankylosing spondylitis. In contrast, the most common cases misinterpreted were about cervical spine disorders such as diffuse idiopathic skeletal hyperostosis (DISH) (M = 2.49, SD = 1.36). Years of experience in radiography showed a positive but not statistically significant influence on accuracy. Additionally, post training mean accuracy significantly improved. Conclusion: This study found radiographers provided quite accurate PIEs for facial bone fractures when compared to the full radiology reports of the same images. The findings also highlighted specific pathologies that were frequently misinterpreted. A two-week training program was found to be effective at improving radiographers’ ability to correctly identify and describe abnormalities present in axial radiographs.

Identifying marginal adaptation discrepancies of lithium disilicate crowns using seven different vertical X‐ray angulations

AbstractPurposeTo study the effect of different vertical angulations on the ability to radiographically assess vertical marginal discrepancies of lithium disilicate crowns.Materials and MethodsTwenty‐one lithium disilicate crowns were fabricated for three different prepared natural teeth: incisor, canine, and premolar. Vertical marginal discrepancies ranging from 0 to 300 µm were intentionally created. The seated crowns were radiographed using seven different vertical angulations, totaling 147 images. Thirty experienced evaluators scored each image for marginal discrepancy, and values were statistically analyzed.ResultsSignificant differences in the ability to accurately assess marginal discrepancies from radiographs were observed for the study factors of angulation, tooth type, and degree of marginal discrepancy (p &lt; 0.001).ConclusionsThe radiographic interpretation of the marginal discrepancies of lithium disilicate crowns is significantly affected by the dimension of the marginal discrepancy. Specifically on premolar crowns, it is significantly affected by different vertical angulations of the X‐ray beam. When evaluating marginal discrepancy on lithium disilicate crowns radiographically, vertical beam angulation within ±10° to the cemento‐enamel junctionCEJ plane is recommended.

Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference

PurposeThe purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radiographs, using standard dose CT examination as the standard of reference. Materials and methodsThis retrospective study included 94 adult patients with suspected bone fractures who underwent a standard dose CT examination and radiographs of the pelvis and/or hip and extremities at our institution between January 2022 and August 2023. For all patients, an AI solution was used retrospectively on the radiographs to detect and localize bone fractures of the pelvis and/or hip and extremities. Results of the AI solution were compared to the reading of each radiograph by a radiologist using McNemar test. The results of standard dose CT examination as interpreted by a senior radiologist were used as the standard of reference. ResultA total of 94 patients (63 women; mean age, 56.4 ± 22.5 [standard deviation] years) were included. Forty-seven patients had at least one fracture, and a total of 71 fractures were deemed present using the standard of reference (25 hand/wrist, 16 pelvis, 30 foot/ankle). Using the standard of reference, the analysis of radiographs by the AI solution resulted in 58 true positive, 13 false negative, 33 true negative and 15 false positive findings, yielding 82 % sensitivity (58/71; 95 % confidence interval [CI]: 71–89 %), 69 % specificity (33/48; 95 % CI: 55–80 %), and 76 % accuracy (91/119; 95 % CI: 69–84 %). Using the standard of reference, the reading of the radiologist resulted in 65 true positive, 6 false negative, 42 true negative and 6 false positive findings, yielding 92 % sensitivity (65/71; 95 % CI: 82–96 %), 88 % specificity (42/48; 95 % CI: 75–94 %), and 90 % accuracy (107/119; 95 % CI: 85–95 %). The radiologist outperformed the AI solution in terms of sensitivity (P = 0.045), specificity (P = 0.016), and accuracy (P < 0.001). ConclusionIn this study, the radiologist outperformed the AI solution for the diagnosis of pelvic, hip and extremity fractures of the using radiographs. This raises the question of whether a strong standard of reference for evaluating AI solutions should be used in future studies comparing AI and human reading in fracture detection using radiographs.

Novel 3-dimensional classification of cervical abrasion using CBCT: A comprehensive analysis

IntroductionTooth cervical abrasion (CA) is a prevalent non-carious cervical lesion that poses challenges for accurate diagnosis from periapical radiographs due to difficulties in assessing the lesion's extent, associated bone loss, and pulpal involvement. The presence of overlying bone structures on the palatal side when lesions are located on the buccal side, or vice versa, further complicates radiographic interpretation. So it is important to define the lesions in all three dimensions. ObjectiveTo provide a three-dimensional descriptive classification for cervical abrasion lesions using Cone Beam Computed Tomography (CBCT). MethodA total of 50 patients with cervical abrasion were selected for the study. From these patients, teeth (n = 10) from each of the four different quadrants were chosen. A CBCT scan with a 6 × 6 cm field of view (FOV) was performed, and the DICOM files of the cervical lesions were transferred to 3-D imaging software. The CBCT images of the cervical abrasion lesions were assessed at the level of the deepest point of the lesion along the long axis of the tooth in both axial and sagittal planes. The height (A), buccolingual dimension (B), circumferential spread (C), and remaining dentine thickness (D) were evaluated and classified using new scoring criteria for each dimension. The reliability and reproducibility of the classification were assessed to ensure its clinical applicability. ConclusionCBCT can be utilized to classify tooth cervical abrasion in endodontics, enhancing diagnosis, analysis, and treatment outcomes. This three-dimensional view facilitates easier communication among clinicians, allows for tailored treatment approaches, and opens new avenues for research.

Black and white: how good are clinicians at diagnosing elbow injuries from paediatric elbow radiographs alone?

ObjectivesPaediatric trauma elbow radiographs are difficult to interpret and there is a potential for harm if misdiagnosed. The primary goal of this study was to assess the ability of healthcare...

Occlusal splint therapy- myth or fact? -A case report

The term Temporomandibular Joint Disorders (TMD) refers to a group of intricate disorders with a variety of etiologies that frequently call for multimodal therapy strategies. Treatment of TMDs requires careful diagnosis and treatment planning to resolve occlusal and functional problems. In contemporary dental practice, splint therapy can be used as an effective and conservative means of treatment of TMDs. In this case report occlusal splint therapy was used to treat a male patient of 27yrs age who had symptoms of TMD, including pain in the head, neck, and shoulder. After 8 months of splint therapy, a clinical examination and radiographic interpretation showed considerable changes, including decreased pain frequency, better jaw function, and radiographic evidence of altered joint spaces. This case report shows the effectiveness of occlusal splint therapy in treating temporomandibular joint disorders.

Clinical decision making in the assessment and treatment of closed hand fractures: A scoping review.

Closed hand fractures represent a significant proportion of emergency department attendances, result in substantial health service utilisation and have a detrimental effect on quality of life. Increasingly, hand therapists in the United Kingdom provide first line fracture treatment. However, the knowledge and skills required to work in such an extended scope capacity have not been elucidated or standardised. This literature review synthesises and reports evidence for the knowledge requisite of clinicians to make evidence-based treatment decisions for patients with hand fractures. A systematic search was undertaken, using Embase, MEDLINE, PsychInfo and CINAHL electronic databases. Inclusion criteria were English language, full research reports of studies assessing of the reliability or validity of the decision-making process in hand fracture treatment published between 2013 and 2023. Data were summarised narratively. 15 studies met inclusion criteria; most assessed decision making for metacarpal fractures. Studies on imaging (n = 4) suggested the reliability of plain radiograph interpretation of hand fracture characteristics such as angulation is good and similar across various levels of experience. Agreement between surgeons and therapists in choosing surgical or nonsurgical treatment was generally good, but factors influencing decision making remained unclear. No evidence was identified that explored clinical assessment knowledge (subjective or objective patient factors) or the specific competencies required to treat hand fractures. There is limited evidence for the knowledge and skills required of clinicians for the competent assessment and treatment of hand fractures. Stakeholder consensus work is required to develop robust competencies and standardise practice.

Reporting radiographers' interaction with Artificial Intelligence-How do different forms of AI feedback impact trust and decision switching?

Artificial Intelligence (AI) has been increasingly integrated into healthcare settings, including the radiology department to aid radiographic image interpretation, including reporting by radiographers. Trust has been cited as a barrier to effective clinical implementation of AI. Appropriating trust will be important in the future with AI to ensure the ethical use of these systems for the benefit of the patient, clinician and health services. Means of explainable AI, such as heatmaps have been proposed to increase AI transparency and trust by elucidating which parts of image the AI 'focussed on' when making its decision. The aim of this novel study was to quantify the impact of different forms of AI feedback on the expert clinicians' trust. Whilst this study was conducted in the UK, it has potential international application and impact for AI interface design, either globally or in countries with similar cultural and/or economic status to the UK. A convolutional neural network was built for this study; trained, validated and tested on a publicly available dataset of MUsculoskeletal RAdiographs (MURA), with binary diagnoses and Gradient Class Activation Maps (GradCAM) as outputs. Reporting radiographers (n = 12) were recruited to this study from all four regions of the UK. Qualtrics was used to present each participant with a total of 18 complete examinations from the MURA test dataset (each examination contained more than one radiographic image). Participants were presented with the images first, images with heatmaps next and finally an AI binary diagnosis in a sequential order. Perception of trust in the AI systems was obtained following the presentation of each heatmap and binary feedback. The participants were asked to indicate whether they would change their mind (or decision switch) in response to the AI feedback. Participants disagreed with the AI heatmaps for the abnormal examinations 45.8% of the time and agreed with binary feedback on 86.7% of examinations (26/30 presentations).'Only two participants indicated that they would decision switch in response to all AI feedback (GradCAM and binary) (0.7%, n = 2) across all datasets. 22.2% (n = 32) of participants agreed with the localisation of pathology on the heatmap. The level of agreement with the GradCAM and binary diagnosis was found to be correlated with trust (GradCAM:-.515;-.584, significant large negative correlation at 0.01 level (p = < .01 and-.309;-.369, significant medium negative correlation at .01 level (p = < .01) for GradCAM and binary diagnosis respectively). This study shows that the extent of agreement with both AI binary diagnosis and heatmap is correlated with trust in AI for the participants in this study, where greater agreement with the form of AI feedback is associated with greater trust in AI, in particular in the heatmap form of AI feedback. Forms of explainable AI should be developed with cognisance of the need for precision and accuracy in localisation to promote appropriate trust in clinical end users.

ASTM International Subcommittee E07.02 on Reference Radiological Images: A brief history and update of recent work

Radiographic interpretation is a combination of art and science. The radiograph interpreter must be well versed in x-ray physics, conditions of the exposure, characteristics of the source and image detector, the design of the part, its specifications, and potential flaws. But there is also an art to interpretation that is gained over years of looking at many radiographs taken in many different conditions. As an aid to interpretation, reference radiographs have been developed and well accepted as means of identifying different types of indications and grading those indications for accept/reject decisions. Industrial radiography began in 1922 under the direction of HH Lester at the US Army Watertown Arsenal. The first radiography standards and reference radiographs appeared in the 1930s. ASTM International Committee E07 on Nondestructive Testing was formed out of Committee E04 on Metallography X-ray Methods subcommittee in 1938 when ASTM was the American Society for Testing Materials. An ASTM Subcommittee on Reference Radiographs was formed in 1950 and immediately adopted some of these first reference films as consensus standards. Since those first reference radiograph standards ASTM has developed both film and digital radiograph standards for 11 types of castings and 3 types of welds, several radiographic parameter demonstration films, a standard film for measuring film digitization performance, and films for evaluating visual acuity of radiograph interpreters. This paper discusses the history of reference films and the recent development of digital reference images, film digitizer performance film, and the visual acuity standard. The just-approved ASTM E3168 Standard Practice for Determining Low-Contrast Visual Acuity of Radiographic Interpreters is the first standard containing actual radiographic images of varying sharpness, contrast, and noise that can be used to evaluate interpreters and/or interpretation environments. This paper documents the initial statistical study performed on the visual acuity standard films.

YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition

ObjectivesIn the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagnosis. This study evaluates the effectiveness of YOLO-v5 in the automatic detection, segmentation, and numbering of deciduous and permanent teeth in mixed dentition pediatric patients based on PRs.MethodsA total of 3854 mixed pediatric patients PRs were labelled for deciduous and permanent teeth using the CranioCatch labeling program. The dataset was divided into three subsets: training (n = 3093, 80% of the total), validation (n = 387, 10% of the total) and test (n = 385, 10% of the total). An artificial intelligence (AI) algorithm using YOLO-v5 models were developed.ResultsThe sensitivity, precision, F-1 score, and mean average precision-0.5 (mAP-0.5) values were 0.99, 0.99, 0.99, and 0.98 respectively, to teeth detection. The sensitivity, precision, F-1 score, and mAP-0.5 values were 0.98, 0.98, 0.98, and 0.98, respectively, to teeth segmentation.ConclusionsYOLO-v5 based models can have the potential to detect and enable the accurate segmentation of deciduous and permanent teeth using PRs of pediatric patients with mixed dentition.

Radiographic characterization of the maxillary septum and septal bullae in horses: An ex vivo study.

The anatomical variations of the maxillary septum and the septal bullae can generate challenges during the interpretation of radiographs of the horses' heads and make it difficult to accurately identify the sites affected in sinus disorders. The description of the radiographic appearance of these structures is currently scarce in the scientific literature. This work aims to describe the anatomical and radiographic characteristics of the maxillary septum and maxillary septal bullae in horses. Six chemically preserved equine cadaver heads were used which, after being submitted to the maxillary osseous flap, the maxillary septum and its respective bullae were identified. Radiographic examinations before and after contrast impregnation on these structures were performed. The positioning of the maxillary septum varied between the anatomical specimens and between the sides of the same specimen. The 30° oblique dorsoventral lateral and lateral projections allowed the identification of the maxillary septum and septal bullae. However, the bullae remained superimposed on the dental arches in the dorsoventral projections with the mandible in a neutral position or with the mandible displaced. The oblique offset radiographic positioning was suggested and proved effective for the examination of the maxillary septal bullae, where the mandible was displaced to the side of the bullae to be examined, and the radiographic beam inclined in the same direction. The maxillary septum and its bullae could be properly identified in a macroscopic way after the osseous flap and the contrasted radiographic examination allowed its adequate interpretation. Variations in size and position are considered normal for the equine species.

Does 3D simulation impact clinical reasoning for orthodontic treatment planning of impacted maxillary canines?

Clinical reasoning is an essential competence to develop in the diagnosis and treatment planning of impacted maxillary canines to ensure good treatment outcomes. It involves skills of radiographic interpretation and mental visualization. To master these, postgraduate students learn to interpret 2D and 3D X-rays to locate these canines accurately. This process demands the creation of mental models of the impaction and resolving it either by envisioning the canine's movement to its correct position or considering its removal. To facilitate this cognitive exercise, a 3D-printed simulator, derived from Cone Beam Computed Tomography scans, serves as a tool to allow students to experiment with various movement simulations, helping them select the most viable treatment approach.This project aimed to assess the differences in expert and novice orthodontists’ clinical reasoning for impacted maxillary canines, and whether the addition of a 3D simulator would affect their reasoning. Thirteen (13) novices randomly assigned to a control and intervention group and three (3) experts took part in a Think-Aloud exercise to diagnose and treatment plan a case of bilaterally impacted maxillary canines. Experts and intervention group novices had the 3D simulator in addition to standardized patient records. Their responses were recorded and analyzed according to a coding scheme reflecting the clinical reasoning process. While experts demonstrated quick clinical judgment and found the 3D simulator redundant, novices were more uncertain and required additional cues. Novices using the 3D simulator described more elaborate treatment plans and had increased awareness of potential complications as compared to the control group.

Radiographic Errors in Intraoral Periapical Radiographs

Background: Radiographs are considered as pivotal aid in the diagnosis and treatment planning of various Oro-dental pathologies. Changes in the quality of radiographs may lead to misinterpretation, which results in incorrect diagnosis and treatment planning. The technical and processing errors can largely influence the radiographic interpretation. Both paralleling and bisecting angle techniques can have both technical and manual errors. Aims: To estimate the frequency of radiographical errors in conventional radiographs taken by undergraduate dental students. Materials And Method: Thousand (1000) dental radiographs taken by undergraduate students were examined. Patient's age ranged between 5 -75 years. X- ray films were examined on X-ray film viewer and were classified according to type of errors and anatomical distribution. Results: The study aimed to identify common faults encountered during routine radiography. The most frequently observed error was Improper Vertical Angulation. Interns performed better in obtaining radiographs compared to Final year students. Keywords: Radiographic errors, Dental students, Bisecting angle technique.

IMG-32. USER EVALUATION OF AN AI-POWERED WEB APPLICATION TO SUPPORT RADIOGRAPHIC INTERPRETATION OF PATIENTS WITH ADAMANTINOMATOUS CRANIOPHARYNGIOMA

Abstract BACKGROUND In neuro-oncology, accurately interpreting radiographic images, especially for diagnosing central nervous system (CNS) tumors like Adamantinomatous Craniopharyngioma (ACP), presents formidable challenges. Even with advanced imaging technologies such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT), pinpointing features related to ACP invasiveness remains daunting. METHODS We introduced an interactive web application that utilizes a custom AI model to analyze preoperative MRI and CT images of 50 patients with ACP. This application can predict a 12-point radiographic feature profile and rank patients based on similarity, aiming to support clinicians in making more precise diagnoses. We deployed our application on a hospital-grade radiographic reading terminal. Our application’s utility and user-friendliness were evaluated through a user study involving four neurosurgeons and two neuroradiologists, who constructed 12-point radiographic feature profiles for ten patients within a 30-minute timeframe given patient MRI and CT images. RESULTS Our study subjects reported high self-assessed numeracy (SNS scores ranging from 4 to 5.25) despite varied preferences in engaging with numerical data. Subjects could efficiently learn to navigate our software interface, with an average task completion time of approximately 3 minutes and 25 seconds per patient. Introducing AI into the task workflow resulted in a slight, statistically non-significant increase in completion time, indicating that while AI modifies interaction dynamics, it does not significantly hinder efficiency in task performance. We observed distinct agreement patterns between clinicians and AI prediction, utilizing Fleiss’ Kappa for categorization. AI assistance subtly boosted clinicians’ confidence and slightly lessened the perceived difficulty of interpreting radiographic images. However, these benefits were not statistically significant. CONCLUSIONS Our study highlights the promise of AI in improving neuro-oncology diagnostics, showing that clinicians quickly adapted to an AI-enhanced application, which subtly influenced their radiographic interpretation. This finding underscores the potential for AI to enhance decision-making accuracy in challenging cases like ACP.