An evidence-based approach to artificial intelligence education for medical students: A systematic review

The exponential growth of artificial intelligence (AI) in the last two decades has been recognized by many as an opportunity to improve the quality of patient care. However, medical education systems have been slow to adapt to the age of AI, resulting in a paucity of AI-specific education in medical schools. The purpose of this systematic review is to evaluate the current evidence-based recommendations for the inclusion of an AI education curriculum in undergraduate medicine. Six databases were searched from inception to April 23, 2022 for cross sectional and cohort studies of fair quality or higher on the Newcastle-Ottawa scale, systematic, scoping, and integrative reviews, randomized controlled trials, and Delphi studies about AI education in undergraduate medical programs. The search yielded 991 results, of which 27 met all the criteria and seven more were included using reference mining. Despite the limitations of a high degree of heterogeneity among the study types and a lack of follow-up studies evaluating the impacts of current AI strategies, a thematic analysis of the key AI principles identified six themes needed for a successful implementation of AI in medical school curricula. These themes include ethics, theory and application, communication, collaboration, quality improvement, and perception and attitude. The themes of ethics, theory and application, and communication were further divided into subthemes, including patient-centric and data-centric ethics; knowledge for practice and knowledge for communication; and communication for clinical decision-making, communication for implementation, and communication for knowledge dissemination. Based on the survey studies, medical professionals and students, who generally have a low baseline knowledge of AI, have been strong supporters of adding formal AI education into medical curricula, suggesting more research needs to be done to push this agenda forward.

Recommendations for Improving Canadian Radiology Equity, Diversity and Inclusion

Improving equity, diversity, and inclusion (EDI) within Canadian radiology is critical for optimal patient care and to reduce health disparities. Although there are increasing national EDI initiatives, there is a paucity of resources available to assist radiology departments as the culture of EDI evolves and faculty and institutions are expected to incorporate EDI in their practice. We present practical recommendations for radiology departments, radiology training programs, and individual radiologists wishing or mandated to improve EDI in the workplace. Actionable strategies for creating an environment that promotes EDI, attracting and supporting diverse trainees, and for how individual radiologists can be allies are presented. These EDI strategies are imperative to provide the best patient care and to strengthen the future of Canadian radiology.

Canadian Radiology Gender Pay Gap-Reality or Myth?

Introduction: Prior studies on Canadian physicians' income have demonstrated a gender pay gap (GPG); however, there is a paucity of data in the Radiology specialty. A cross-sectional study was conducted to determine if practicing Canadian radiologists' self-reported income is related to gender, controlling for demographic and work variables. Methods: English and French online surveys were distributed by email and social media to radiologists and trainees (May-July 2021). The association between Gender (controlling for Ethnicity variables, Region, having Children, Full-/Part-Time work, and Academic position) and Self-Reported Income was examined using chi-square tests. Pearson correlations examined relationships between opinion variables. Analyses were conducted using SPSS V28.0. A priori significance was P < .05. Study had ethics approval. Results: Four hundred and fifty-four practicing Canadian radiologists responded. Majority were women (51.2%, n = 227), a non-visible Minority (71.7%, n = 317), and from Western Provinces (67.8%, n = 308). Significant relationship was established between Self-Reported Income and Gender (χ2 = 10.44, df = 2, P < .05). More men (70.6%, n = 120) than women (56.4%, n = 110), reported income "greater than $500 000"; fewer men (20.6%, n = 35) than women (35.9%, n = 70) reported "$300 000-$500 000"; a similar percent of men (8.8%, n = 15) and women (7.7%, n = 15) reported "less than $300 000." No relationship was found between self-reported income and gender for ethnicity variables, those without children, part-time, or non-academic radiologists. The opinion "Addressing the GPG is important" correlated to "Canadian Association of Radiologists should collect demographic data" (r = 0.63). Responses were low for ethnic minorities and non-western provinces. Conclusion: Our results suggest a GPG exists in Canadian radiology and is an important first step for future studies.

Automatic Segmentation of Wrist Bones in CT Using a Statistical Wrist Shape + Pose Model

Segmentation of the wrist bones in CT images has been frequently used in different clinical applications including arthritis evaluation, bone age assessment and image-guided interventions. The major challenges include non-uniformity and spongy textures of the bone tissue as well as narrow inter-bone spaces. In this work, we propose an automatic wrist bone segmentation technique for CT images based on a statistical model that captures the shape and pose variations of the wrist joint across 60 example wrists at nine different wrist positions. To establish the correspondences across the training shapes at neutral positions, the wrist bone surfaces are jointly aligned using a group-wise registration framework based on a Gaussian Mixture Model. Principal component analysis is then used to determine the major modes of shape variations. The variations in poses not only across the population but also across different wrist positions are incorporated in two pose models. An intra-subject pose model is developed by utilizing the similarity transforms at all wrist positions across the population. Further, an inter-subject pose model is used to model the pose variations across different wrist positions. For segmentation of the wrist bones in CT images, the developed model is registered to the edge point cloud extracted from the CT volume through an expectation maximization based probabilistic approach. Residual registration errors are corrected by application of a non-rigid registration technique. We validate the proposed segmentation method by registering the wrist model to a total of 66 unseen CT volumes of average voxel size of 0.38 mm. We report a mean surface distance error of 0.33 mm and a mean Jaccard index of 0.86.

Registration of a statistical model to intraoperative ultrasound for scaphoid screw fixation

PURPOSE

Volar percutaneous scaphoid fracture fixation is conventionally performed under fluoroscopy-based guidance, where surgeons need to mentally determine a trajectory for the insertion of the screw and its depth based on a series of 2D projection images. In addition to challenges associated with mapping 2D information to a 3D space, the process involves exposure to ionizing radiation. Three-dimensional ultrasound has been suggested as an alternative imaging tool for this procedure; however, it has not yet been integrated into clinical routine since ultrasound only provides a limited view of the scaphoid and its surrounding anatomy.

METHODS

We propose a registration of a statistical wrist shape + scale + pose model to a preoperative CT and intraoperative ultrasound to derive a patient-specific 3D model for guiding scaphoid fracture fixation. The registered model is then used to determine clinically important intervention parameters, including the screw length and the trajectory of screw insertion in the scaphoid bone.

RESULTS

Feasibility experiments are performed using 13 cadaver wrists. In 10 out of 13 cases, the trajectory of screw suggested by the registered model meets all clinically important intervention parameters. Overall, an average 94 % of maximum allowable screw length is obtained based on the measurements from gold standard CT. Also, we obtained an average 92 % successful volar accessibility, which indicates that the trajectory is not obstructed by the surrounding trapezium bone.

CONCLUSIONS

These promising results indicate that determining clinically important screw insertion parameters for scaphoid fracture fixation is feasible using 3D ultrasound imaging. This suggests the potential of this technology in replacing fluoroscopic guidance for this procedure in future applications.

Pearls for Interpreting Computed Tomography of the Cervical Spine in Trauma

The high morbidity and mortality associated with cervical spine injuries makes identification and classification essential. It is important to have a systematic approach to evaluation, especially in the trauma setting with other distracting injuries. Understanding the anatomy and biomechanics enables rapid and accurate interpretation of images. In severe trauma and in patients with rigid spinal disease, the classic patterns of injury may be difficult or impossible to recognize. This article provides an approach to acquiring and interpreting cervical spine images in the setting of acute trauma and reviews the classic patterns of injury.

Bone enhancement in ultrasound using local spectrum variations for guiding percutaneous scaphoid fracture fixation procedures

PURPOSE

The scaphoid bone is the most frequently fractured bone in the wrist. When fracture fixation is indicated, a screw is inserted into the bone either in an open surgical procedure or percutaneously under fluoroscopic guidance. Due to the complex geometry of the wrist, fracture fixation is a challenging task. Fluoroscopic guidance exposes both the patient and the physician to ionizing radiation. Ultrasound-based guidance has been suggested as a real-time, radiation-free alternative. The main challenge of using ultrasound is the difficulty in interpreting the images due to the low contrast and noisy nature of the data.

METHODS

We propose a bone enhancement method that exploits local spectrum features of the ultrasound image. These features are utilized to design a set of quadrature band-pass filters and subsequently estimate the local phase symmetry, where high symmetry is expected at the bone locations. We incorporate the shadow information below the bone surfaces to further enhance the bone responses. The extracted bone surfaces are then used to register a statistical wrist model to ultrasound volumes, allowing the localization and interpretation of the scaphoid bone in the volumes.

RESULTS

Feasibility experiments were performed using phantom and in vivo data. For phantoms, we obtain a surface distance error 1.08 mm and an angular deviation from the main axis of the scaphoid bone smaller than 5°, which are better compared to previously presented approaches.

CONCLUSION

The results are promising for further development of a surgical guidance system to enable accurate anatomy localization for guiding percutaneous scaphoid fracture fixations.