Integration of interactive three-dimensional image post-processing software into undergraduate radiology education effectively improves diagnostic skills and visual-spatial ability

The Role of Three-Dimensional Modeling to Improve Comprehension of Liver Anatomy and Tumor Characteristics for Medical Students and Surgical Residents

OBJECTIVE

Studying liver anatomy can be challenging for medical students and surgical residents due to its complexity. Three-dimensional visualization technology (3DVT) allows for a clearer and more precise view of liver anatomy. We sought to assess how 3DVT can assist students and surgical residents comprehend liver anatomy.

DESIGN

Data from 5 patients who underwent liver resection for malignancy at our institution between September 2020 and April 2022 were retrospectively reviewed and selected following consensus among the investigators. Participants were required to complete an online survey to investigate their understanding of tumor characteristics and vascular variations based on patients' computed tomography (CT) and 3DVT.

SETTING

The study was carried out at the General and Hepato-Biliary Surgery Department of the University of Verona.

PARTICIPANTS

Among 32 participants, 13 (40.6%) were medical students, and 19 (59.4%) were surgical residents.

RESULTS

Among 5 patients with intrahepatic lesions, 4 patients (80.0%) had at least 1 vascular variation. Participants identified number and location of lesions more correctly when evaluating the 3DVT (84.6% and 80.9%, respectively) compared with CT scans (61.1% and 64.8%, respectively) (both p ≤ 0.001). The identification of any vascular variations was more challenging using the CT scans, with only 50.6% of correct answers compared with 3DVT (72.2%) (p < 0.001). Compared with CT scans, 3DVT led to a 23.5%, 16.1%, and 21.6% increase in the correct definition of number and location of lesions, and vascular variations, respectively. 3DVT allowed for a decrease of 50.8 seconds (95% CI 23.6-78.0) in the time needed to answer the questions. All participants agreed on the usefulness of 3DVT in hepatobiliary surgery.

CONCLUSIONS

The 3DVT facilitated a more precise preoperative understanding of liver anatomy, tumor location and characteristics.

Extended reality veterinary medicine case studies for diagnostic veterinary imaging instruction: Assessing student perceptions and examination performance

Educational technologies in veterinary medicine aim to train veterinarians faster and improve clinical outcomes. COVID-19 pandemic, shifted face-to-face teaching to online, thus, the need to provide effective education remotely was exacerbated. Among recent technology advances for veterinary medical education, extended reality (XR) is a promising teaching tool. This study aimed to develop a case resolution approach for radiographic anatomy studies using XR technology and assess students' achievement of differential diagnostic skills. Learning objectives based on Bloom's taxonomy keywords were used to develop four clinical cases (3 dogs/1 cat) of spinal injuries utilizing CT scans and XR models and presented to 22 third-year veterinary medicine students. Quantitative assessment (ASMT) of 7 questions probing 'memorization', 'understanding and application', 'analysis' and 'evaluation' was given before and after contact with XR technology as well as qualitative feedback via a survey. Mean ASMT scores increased during case resolution (pre 51.6% (±37%)/post 60.1% (± 34%); p < 0.01), but without significant difference between cases (Kruskal-Wallis H = 2.18, NS). Learning objectives were examined for six questions (Q1-Q6) across cases (C1-4): Memorization improved sequentially (Q1, 2 8/8), while Understanding and Application (Q3,4) showed the greatest improvement (26.7%-76.9%). Evaluation and Analysis (Q5,6) was somewhat mixed, improving (5/8), no change (3/8) and declining (1/8).Positive student perceptions suggest that case studies' online delivery was well received stimulating learning in diagnostic imaging and anatomy while developing visual-spatial skills that aid understanding cross-sectional images. Therefore, XR technology could be a useful approach to complement radiological instruction in veterinary medicine.

Practice-Based Learning Using Smart Class: A Competency-Based Model in Undergraduate Radiology Education

RATIONALE AND OBJECTIVES

A need for adequate and early exposure to radiology practice is rising in undergraduate students, taking competency development as the orientation. We aimed to develop a competency-based model of practice-based learning for undergraduate radiology education.

MATERIALS AND METHODS

The model of practice-based learning was constructed upon an e-learning smart class environment, with case-based learning and simulators for competency development. To assess the model effectiveness, a randomized controlled experiment was performed, where 57 third-year medical students received the model (Smart-Class group) and another 57 received traditional teaching (Traditional group). Seven quizzes, a final exam, and a survey were performed in both groups.

RESULTS

Smart-Class group achieved higher mean score in the quizzes (r = -0.4, p < 0.001) and application subscore in the final exam (r = -0.3, p = 0.005) compared to Traditional group. Smart-Class group also gave higher ratings in students' perceptions concerning promotion of learning interests, radiology skills, and diagnostic reasoning (r = -0.2 to -0.3, p = 0.001-0.034).

CONCLUSION

Practice-based learning using smart class improved students' application ability and satisfactions in undergraduate radiology education, suggesting it a practical model for early exposure to radiology practice and competency development for undergraduate medical students.

Review of Learning Tools for Effective Radiology Education During the COVID-19 Era

Coronavirus disease 2019 (COVID-19) has significantly disrupted medical education around the world and created the risk of students missing vital education and experience previously held within actively engaging in-person activities by switching to online leaning and teaching activities. To retain educational yield, active learning strategies, such as microlearning and visual learning tools are increasingly utilized in the new digital format. This article will introduce the challenges of a digital learning environment, review the efficacy of applying microlearning and visual learning strategies, and demonstrate tools that can reinforce radiology education in this constantly evolving digital era such as innovative tablet apps and tools. This will be key in preserving and augmenting essential medical teaching in the currently trying socially and physically distant times of COVID-19 as well as in similar future scenarios.

Case-based radiological anatomy instruction using cadaveric MRI imaging and delivered with extended reality web technology

PURPOSE

Extended reality (XR) technology enhances learning in medical education. The purpose of this study was to develop and apply a case-based approach for teaching radiological anatomy utilizing XR technology for improved student exploration and engagement.

METHODS

The workflow consisted of MRI scanning cadavers followed by radiological, pathological, and anatomical assessment, and finally case presentation based on XR visualizations and student interaction. Case information (Subject, History, and Physical Exam) was presented to student groups who generated and recorded hypotheses using Google Forms.

RESULTS

Use of all components of the system was voluntary and a total of 74 students responded to the survey request (response rate = 95%). Assessment of the experience was conducted through a qualitative survey comprising four Likert scale questions (1-5, 1 lowest), three binary questions, and open-ended comments. Mean, standard deviation, and overall agreement (mean ± SD, OA) showed that students found MRI scans of cadavers to be helpful for dissections (4.14 ± 1.1, 74.3%) and provided an understanding of relevant anatomy (4.32 ± 0.9, 79.7%), while 78.4% of students used the DICOM viewer to visualize scans of cadavers. The difficulty of use was found to be average (2.90 ± 1.0, 23%). zSpace visualizations were used by 40.5% of students, generally agreeing that an understanding of spatial relationships improved as a result (3.60 ± 1.0, 43.2%). More case-based sessions were favored by 97.3% of students.

CONCLUSIONS

Results suggest that cadaveric MRI radiological visualization and XR technology enhance understanding of case-based anatomical dissections and encourage student exploration and engagement.

Spatial abilities training in the field of technical skills in health care: A systematic review

Objective

To conduct a systematic review of the effect of interventions on spatial abilities in the field of technical skills in health care.

Methods

A literature search was conducted up to November 14, 2017 in Scopus and in several databases on EBSCOhost platform. Citations were obtained, articles related to retained citations were reviewed and a final list of included studies was identified. Methods in the field of technical skills relating an intervention to spatial abilities test scores between intervention groups or obtained before and after the intervention were identified as eligible. The quality of included studies was assessed and data were extracted in a systematic way.

Results

A series of 5513 citations was obtained. Ninety-nine articles were retained and fully reviewed, yielding four included studies. No difference in the Hidden Figure Test score after one year was observed after residency training in General Surgery of at least nine months. A first-year dental curriculum was not found to elevate the Novel Object Cross-Sections Test score (P = 0.07). A two-semester learning period of abdominal sonography was found to increase the Revised Minnesota Paper Form Board Test score (P < 0.05). A hands-on radiology course using interactive three-dimensional image post-processing software consisting of seven two-hour long seminars on a weekly basis was found to amplify the Cube Perspective Test score (P < 0.001).

Conclusion

Spatial abilities tests scores were enhanced by courses in abdominal sonography and hands-on radiology, but were not improved by residency training in General Surgery and first-year dental curriculum.

Hands-on or no hands-on training in ultrasound imaging: A randomized trial to evaluate learning outcomes and speed of recall of topographic anatomy

Medical students have difficulties in interpreting two-dimensional (2D) topographic anatomy on sectional images. Hands-on and no hands-on training in ultrasound imaging facilitate learning topographic anatomy. Hands-on training is linked with active search for patterns of anatomical structures and might train pattern recognition for image interpretation better although the added value on learning outcomes is unclear. This study explores first year medical students' knowledge in topographic anatomy of the upper abdomen after attending hands-on or no hands-on training in ultrasound in a randomized trial. While students in the hands-on ultrasound group (N = 21) generated and interpreted standardized planes of ultrasound imaging, students in the no hands-on seminar group (N = 22) interpreted provided ultrasound images by correlation to three-dimensional (3D) anatomical prosections. Afterwards knowledge in topographic anatomy was measured repetitively by text and ultrasound image-based multiple choice (MC) examinations. As surrogate for pattern recognition, students rated whether answers were known after reflection or instantly. While intrinsic motivation was higher in the ultrasound group, no differences in the MC-examination score were found between ultrasound and seminar group instantly (66.5 ±10.9% vs. 64.5% ±11.0%, P = 0.551) or six weeks (62.9% ±12.3% vs. 61.5% ±11.0%, P = 0.718) after training. In both groups scores in text-based questions declined (P < 0.001) while scores in image-based questions remained stable (P = 0.895) with time. After six weeks more image-based questions were instantly known in the hands-on ultrasound compared to seminar-group (28% ±17.3% vs. 16% ±13.5%, P = 0.047). Hands-on ultrasound-training is linked with faster interpreting of ultrasound images without loss in accuracy. The added value of hands-on training might be facilitation of pattern recognition.

Oppositional Gravitational Search Algorithm and Artificial Neural Network-based Classification of Kidney Images

Ultrasound (US) imaging has been broadly utilized as part of kidney diagnosis because of its ability to show structural abnormalities like cysts, stones, and infections as well as information about kidney function. The main aim of this research is to effectively classify normal and abnormal kidney images through US based on the selection of relevant features. In this study, abnormal kidney images were classified through gray-scale conversion, region-of-interest generation, multi-scale wavelet-based Gabor feature extraction, probabilistic principal component analysis-based feature selection and adaptive artificial neural network technique. The anticipated method is executed in the working platform of MATLAB, and the results were analyzed and contrasted. Results show that the proposed approach had 94% accuracy and 100% specificity. In addition, its false-acceptance rate is 0%, whereas that of existing methods is not <27%. This shows the precise prediction level of the proposed approach, compared with that of existing methods.

What We Do and Do Not Know about Teaching Medical Image Interpretation

Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete offline courses and curricula, studies that evaluated e-learning modules, and studies that evaluated specific educational interventions. Twenty-three percent of all studies evaluated the implementation of complete courses or curricula, and 44% of the studies evaluated the implementation of e-learning modules. We argue that these studies have encouraging results but provide little information for educators: too many differences exist between conditions to unambiguously attribute the learning effects to specific instructional techniques. Moreover, concepts are not uniformly defined and methodological weaknesses further limit the usefulness of evidence provided by these studies. Thirty-two percent of the studies evaluated a specific interventional technique. We discuss three theoretical frameworks that informed these studies: diagnostic reasoning, cognitive schemas and study strategies. Research on diagnostic reasoning suggests teaching students to start with non-analytic reasoning and subsequently applying analytic reasoning, but little is known on how to train non-analytic reasoning. Research on cognitive schemas investigated activities that help the development of appropriate cognitive schemas. Finally, research on study strategies supports the effectiveness of practice testing, but more study strategies could be applicable to learning medical image interpretation. Our commentary highlights the value of evaluating specific instructional techniques, but further evidence is required to optimally inform educators in medical image interpretation.

The Importance of Human-Computer Interaction in Radiology E-learning

With the development of cross-sectional imaging techniques and transformation to digital reading of radiological imaging, e-learning might be a promising tool in undergraduate radiology education. In this systematic review of the literature, we evaluate the emergence of image interaction possibilities in radiology e-learning programs and evidence for effects of radiology e-learning on learning outcomes and perspectives of medical students and teachers. A systematic search in PubMed, EMBASE, Cochrane, ERIC, and PsycInfo was performed. Articles were screened by two authors and included when they concerned the evaluation of radiological e-learning tools for undergraduate medical students. Nineteen articles were included. Seven studies evaluated e-learning programs with image interaction possibilities. Students perceived e-learning with image interaction possibilities to be a useful addition to learning with hard copy images and to be effective for learning 3D anatomy. Both e-learning programs with and without image interaction possibilities were found to improve radiological knowledge and skills. In general, students found e-learning programs easy to use, rated image quality high, and found the difficulty level of the courses appropriate. Furthermore, they felt that their knowledge and understanding of radiology improved by using e-learning. In conclusion, the addition of radiology e-learning in undergraduate medical education can improve radiological knowledge and image interpretation skills. Differences between the effect of e-learning with and without image interpretation possibilities on learning outcomes are unknown and should be subject to future research.

Radiology resident MR and CT image analysis skill assessment using an interactive volumetric simulation tool - the RadioLOG project

OBJECTIVE

Assess the use of a volumetric simulation tool for the evaluation of radiology resident MR and CT interpretation skills.

MATERIAL AND METHODS

Forty-three participants were evaluated with a software allowing the visualisation of multiple volumetric image series. There were 7 medical students, 28 residents and 8 senior radiologists among the participants. Residents were divided into two sub-groups (novice and advanced). The test was composed of 15 exercises on general radiology and lasted 45 min. Participants answered a questionnaire on their experience with the test using a 5-point Likert scale. This study was approved by the dean of the medical school and did not require ethics committee approval.

RESULTS

The reliability of the test was good with a Cronbach alpha value of 0.9. Test scores were significantly different in all sub-groups studies (p < 0.0225). The relation between test scores and the year of residency was logarithmic (R² = 0.974). Participants agreed that the test reflected their radiological practice (3.9 ± 0.9 on a 5-point scale) and was better than the conventional evaluation methods (4.6 ± 0.5 on a 5-point scale).

CONCLUSION

This software provides a high quality evaluation tool for the assessment of the interpretation skills in radiology residents.

KEY POINTS

• This tool allows volumetric image analysis of MR and CT studies. • A high reliability test could be created with this tool. • Test scores were strongly associated with the examinee expertise level. • Examinees positively evaluated the authenticity and usability of this tool.

Volumetric CT-images improve testing of radiological image interpretation skills

RATIONALE AND OBJECTIVES

Current radiology practice increasingly involves interpretation of volumetric data sets. In contrast, most radiology tests still contain only 2D images. We introduced a new testing tool that allows for stack viewing of volumetric images in our undergraduate radiology program. We hypothesized that tests with volumetric CT-images enhance test quality, in comparison with traditional completely 2D image-based tests, because they might better reflect required skills for clinical practice.

MATERIALS AND METHODS

Two groups of medical students (n=139; n=143), trained with 2D and volumetric CT-images, took a digital radiology test in two versions (A and B), each containing both 2D and volumetric CT-image questions. In a questionnaire, they were asked to comment on the representativeness for clinical practice, difficulty and user-friendliness of the test questions and testing program. Students' test scores and reliabilities, measured with Cronbach's alpha, of 2D and volumetric CT-image tests were compared.

RESULTS

Estimated reliabilities (Cronbach's alphas) were higher for volumetric CT-image scores (version A: .51 and version B: .54), than for 2D CT-image scores (version A: .24 and version B: .37). Participants found volumetric CT-image tests more representative of clinical practice, and considered them to be less difficult than volumetric CT-image questions. However, in one version (A), volumetric CT-image scores (M 80.9, SD 14.8) were significantly lower than 2D CT-image scores (M 88.4, SD 10.4) (p<.001). The volumetric CT-image testing program was considered user-friendly.

CONCLUSION

This study shows that volumetric image questions can be successfully integrated in students' radiology testing. Results suggests that the inclusion of volumetric CT-images might improve the quality of radiology tests by positively impacting perceived representativeness for clinical practice and increasing reliability of the test.