The role of cardiac ultrasound virtual simulation technology in the construction of clinical diagnostic reasoning of structural heart diseases

Abstract

Background

Clinical reasoning education is a very systematic and highly logical medical learning process, but the existing teaching models and methods often divide this process into several stages for separate training using a virtual reality (VR)simulator can simulate and reconstruct the cardiac anatomical structure, ultrasonic section operation, and color doppler ultrasound parameter measurement, then integrate it into a single disease or case. In this case, the students' operation skills,decision-making and communication skills were trained by cardiac physical examination, inquiry and interpretation of laboratory examination results. This study aims to investigate whether the application of virtual simulation technology in cardiac ultrasound learning can improve students' thinking ability in the diagnosis and treatment of structural heart diseases.

Method

This study involved fifty-nine undergraduate students studying clinical medicine in the fifth semester at Jinan University. We employed a simple randomization method for random grouping. Random numbers were generated in Excel based on the students' student IDs. Then the students were sorted and divided into the experimental group, which used virtual simulation teaching based on ultrasound, and the control group, which used traditional teaching method. Following the completion of theory teaching, operation demonstration, clinical skills practice and VR practice, students underwent an offline image assessment and online systematic test, which included cardiac ultrasound operation assessment and virtual simulation case assessment to evaluate their proficiency in clinical skills and analytical ability in clinical reasoning. Furthermore, the VR group was given a separate questionnaire to provide their feedback on the cardiac ultrasound virtual simulation education.

Results

There were no statistically significant differences between the two groups in the scores for offline image interpretation and patient inquiry in the virtual simulation case analysis (P > 0.05). The scores for physical examination in virtual simulation case analysis (P < 0.05), virtual simulation ultrasound manipulation(P < 0.05) and diagnosis in virtual simulation case analysis(P < 0.05) were higher in the VR group than in the control group, and the difference was statistically significant. The total score for all evaluation of teaching quality in the VR group was higher than in the control group (P < 0.05). Furthermore, the majorityof students in the VR group displayed satisfaction with course experience, learning effect, teaching evaluation, and overall evaluation.

Conclusion

This research demonstrates that cardiac ultrasound virtual simulation technology could improve students' thinking ability in diagnosing and treating of structural heart diseases. The virtual simulation technology not only could be used for technology imitation but also could leverage its characteristics to demonstrate the process of a certain disease from anatomy to pathophysiology and clinical signs from shallow to deep.

Introduction

Clinical decision-making is a progressive reasoning process that begins with a comprehensive understanding of human anatomy and tissue function, proceeds to the analysis of patient complaints and clinical signs, and is followed by verification through imaging and laboratory tests, ultimately leading to diagnostic conclusions and treatment planning. In medical education, we refer to this process as the training of clinical thinking ability [1]. This is a systematic and highly logical medical learning process, but the existing teaching models and methodsoften divide this process into several stages for separate training, which maks.

it impossible to integrate it into a single disease or case [2]. Individual pictures, videos, and case materials can not allow students to experience the real clinical decision-making process or achieve the goal of training their clinical thinkingability. For example, cardiac ultrasound learning is well-known for its complexity and differences but it is the most useful method in the diagnosis of structural heart diseases. Previously, the cardiac ultrasound teaching at the undergraduate level only focused on interpreting the results of cardiac ultrasound imaging, but did not provide a systematic understanding of the relationship between cardiac ultrasound imaging, anatomical structure and cardiac hemodynamics. Real clinical practice is certainly the best method of training this reasoning ability [3, 4],but for undergraduate level students, there are only fewer opportunities for such practice, and the homogeneity of teaching is poor [2].

Modern medical education has introduced educational strategies such as active learning, experiential learning, and participatory learning to deal with these issues. Active learning enhances clinical diagnostic reasoning by fostering critical engagement with clinical data through self-directed inquiry, problem-based learning (PBL), and iterative case analysis [5]. Experiential learning integrates clinical immersion with structured reflection to build adaptive expertise. Direct patient encounters foster probabilistic reasoning under uncertainty [6]. Participatory learning emphasizes that learners actively engage in the process of knowledge construction. Through means such as simulating clinical scenarios and conducting group discussions, students are enabled to exercise their clinical skills in practical situations [7]. When participating, students are confronted with actual or nearly authentic cases, and they need to apply medical knowledge and reasoning abilities to make diagnostic and treatment decisions [8]. Through continuous practice and feedback, they can gradually improve their clinical skill levels and learn to make reasonable decisions in complex clinical situations. The application of these educational strategies is of paramount importance for the cultivation of sophisticated clinical reasoning skills. Nevertheless, in actual medical teaching practice, there is ashortage of a medium that can integrate these teaching strategies comprehensively.

In recent years, with the rapid development of artificial intelligence and computer technology, creating three-dimensional (3D) images based on digital technology can simulate and interact in a seemingly real way. This teaching method is called virtual simulation teaching [9], which is widely used in some high-risk and non-repeatable teaching projects due to its low cost and wide application scenarios [10]. The teaching scenarios of virtual simulation are currently mainly divided into two categories: the first one is used to develop technical skills, such as programming skills which require a large amount of 3D visualization. Its application examples include anatomy learning, surgical procedures, and cardiopulmonary resuscitation (CPR) [11]. The second one is used to teach"soft skills", such as empathy and communication skills with patients [12, 13]. Virtual simulation is defined as an immersive, screen based experience [8], which can be applied to cardiac ultrasound learning to enhance students'experience and reproduce the structure of the heart through 3D simulation technology.

Recent virtual reality (VR) advancements are increasingly recognized for their transformative potential in medical education, mainly through integrating pedagogical approaches such as serious games and collaborative learning. For example,the Immersive Virtual Anatomy Laboratory (IVAL), a VR-based serious game for skeletal anatomy education, has demonstrated high levels of user engagement and satisfaction, pointing to the motivational aspects of VR learning [14]. Furthermore, empirical evidence suggests that VR-based training can offer advantages over traditional learning methods, potentially leading to reduced learning-termand improved performance on knowledge assessments [15]. Longitudinal studies also indicate collaborative VR environments can enhance can enhance long-term knowledge retention and foster essential teamwork skills among medical students [16]. These findings underscore the potential of VR as a cutting-edge educational tool that combines immersive experiences, collaborative opportunities, and practical knowledge transfer, warranting further exploration within specific clinicaldomains like cardiac ultrasound training.

In order to verify the role of virtual simulation teaching of cardiac ultrasound in training medical students'thinking ability of clinical diagnosis and treatmen of cardiac structural diseases, we collected real clinical ultrasound images and clinical cases from the First Affiliated Hospital of Jinan University, and independently designed the"Integrated Virtual Simulation Experiment Software for Diagnosis of Heart Valve Diseases Based on Auscultation and Echocardiography".This system has been widely applied in the undergraduate practical teaching of.

internal medicine and diagnostics in our medical college, and it is also used inthe clinical skills training courses for the training of internal medicine residents.In this study, the corresponding scenario modules were set up in advance around the teaching objectives, and the cardiac anatomical structure, ultrasonic section operation, and color Doppler ultrasound parameter measurement were simulated and reconstructed. The real cardiac ultrasound operation was simulated through multi-sensory forms such as vision, hearing, and touch. In addition, the students'operation skills, decision-making skills and communication skills were trained with cardiac physical examination, inquiry, and interpretation of laboratoryexamination results. This study aims to investigate whether the application of virtual simulation technology in cardiac ultrasound learning can improve students'thinking ability in diagnosing and treating structural heart diseases.

Methods

Subjects

This study has been granted an exemption from requiring ethics approval from The Ethics Review Committee for Scientific Research Involving Personnel of the First Affiliated Hospital of Jinan University. The fifth-grade undergraduates of clinical medicine from the First Affiliated Hospital of Jinan University were randomly divided into experimental group (using virtual simulation teaching based on ultrasound) and control group (using traditional teaching method). We employed a simple randomization method for random grouping. Random numbers were generated in Excel based on the students'student IDs. The inclusion criteria included: (1) proficient communication and comprehension skills; (2) consistent attendance without absenteeism. Exclusion criteria included: (1) refusal to participate, (2) failure to complete all courses, (3) failure to complete the final test, and (4) incomplete questionnaire responses. The study emphasized voluntary participation, allowing participants to withdraw at any time without providing a reason.Using a random number table method, the 59 students were divided into two groups. There were experimental VR group (n = 29) and control group B (n = 30) participating in this study(Fig. 1). There was no statistically significant difference in gender and age between the two groups, which were comparable.

Fig. 1

Flow chart showing the study process

VR equipment information

Virtual Simulation Experiment Software for Diagnosis of Heart Valve Diseases Based on Auscultation and Echocardiography V1.0 (No.2022SR1451629) is freely available for download at https://xnfz.jnu.edu.cn/home. It can be used by anyone for non-commercial research purposes.

Study design

According to the clinical medicine training program of Jinan University, both groups of students followed the same teaching syllabus. This course was based on the chapter"Internal Medicine—Heart Valve Disease"and was taught and evaluated by the same teaching team. An overview of the course design was showed in Fig. 2.

Fig. 2

Flow chart of the teaching process of the two groups; PPT: PowerPoint VR: virtual reality

Control group

Preparation before class

Based on the teaching content of each class, the teacher taught 5 cases of typical structural heart disease echocardiography operation and the key points of disease diagnosis and treatment by PPT before class. The echocardiography images and operation methods were distributed to the students in the form of video(Basic Course of Cardiac Ultrasound) for after-class learning, mainly including cardiac anatomy, basic principles, indications, limitations, standard views, ultrasonic probe operation instructions, and the main points of echocardiography used to diagnose the structure and function of heart valves. The total learning time of students is required to be no less than 20 h. The teaching team designated teachers to answer questions and guide the whole course.

Internship class

Divide 30 students into 5 groups of 6 each. Select typical patients with structural heart disease for consultation, physical examination, and case data reading under the guidance of teachers. Then, conduct practical training on cardiac ultrasound operation in the cardiac ultrasound room (including left ventricular long axis section, large artery short axis section, mitral valve short axis section, four chamber cardiac section, and measurement methods of basic cardiac ultrasound data). A cardiac specialist will explain the usage standards of cardiac ultrasound, the key points of cardiac section operation, and the identification and measurement of cardiac anatomical structures under each section.Each student was required to complete the operations and measurements of four ultrasonic sections.

Experimental group

Preparation before class: Based on the teaching content of each class, the teacher taught 5 cases of typical structural heart disease echocardiography operation and the key points of disease diagnosis and treatment by PPT before class (the specific content was the same as the control group). Before class, 2 h of spare time were selected to learn the key points of system operation in the virtual simulation system under the guidance of teachers in the training center. After class, students independently logged in the virtual simulation experiment platform of Jinan University for virtual simulation experiment operation, and the total time on the computer was not less than 20 h. If students encounter any difficulties, they can communicate with teachers through the discussion area of the online course platform to ensure timely communication.

Internship Class: Divide 29 students into 6 groups, with 5 students in each group except for one group of 4. Randomly select one case from the virtual simulation assessment mode in each group, and work together in the virtual simulation system to consultations, physical examinations, and cardiac ultrasound operations (including left ventricular long axis view, large artery short axis view, mitral valve short axis view, four chamber view, and measurement methods for basic cardiac ultrasound data) (Figs. 3 and 4). A cardiac specialist explains the usage standards of cardiac ultrasound, the key points of cardiac section operation, and the identification and measurement of cardiac anatomical structures under each section.

Fig. 3

Internship class in the VR group which contained consultations, physical examinations, cardiac ultrasound operations and ultrasound imaging data measurements (from A to D)

Fig. 4

Learning steps of cardiac ultrasound virtual simulation in the VR group

Assessment and evaluation methods

Evaluation of teaching quality

The offline image assessment consists of 10 ultrasound image diagnosis reading questions, each worth 2 points, for a total of 20 points. The ultrasound images used are selected according to the ultrasound diagnosis teaching syllabus and double-blind grading is conducted by the same teacher. The online assessment includes cardiac ultrasound operation assessment and virtual simulation case assessment. Each student randomly selects a case of structural heart disease and conducts an independent case analysis based on the provided information. By completing consultation, physical examination, cardiac ultrasound operation, and data measurement, the characteristics of the patient's case are analyzed and summarized, and preliminary diagnosis and differential diagnosis ideas are proposed. The system scores each step based on the operation situation, with a total score of 80 points. The assessment of cardiac ultrasound operation includes three aspects: obtaining sectional views of four sections, measuring ultrasound imaging data, and evaluating image stability.

Evaluation of teaching Satisfaction

After completing all courses, a satisfaction survey was conducted using a questionnaire which we designed for studentes in the VR group (online supplement 1). This questionnaire included 8 items in four dimensions learning effect, course evaluation, teaching evaluation and overall evaluation eight items: ① helps to understand the pathogenesis of structural heart diseases; ② helps to complete the skills independently; ③ How satisfied are you with the design of the virtual simulation course? ④ The virtual simulation teaching of cardiac ultrasoundis helpful for self-directed learning (not limited by time and space); ⑤ How satisfied are you with the theory taught and the operational demonstrations in theonline course? ⑥ How satisfied are you with the assessment and evaluation mechanism in the course? ⑦Would you like to adopt the virtual simulation teaching model for other medical skills training projects? ⑧Has the teaching modeof virtual simulation improved the sense of security and confidence in clinical diagnosis and treatment?The Cronbach's α coefficient of the survey form is 0.806. The survey forms are all multiple-choice questions, each with five options:5 represents strongly agree(satisfied), 4 represents agree(satisfied), 3 represents unsure, 2 represents disagree(dissatisfied),1 represents strongly disagree(dissatisfied), we considered a score ≥ 4 as an agreement. Fill out the questionnaire anonymously, distribute it on the spot after the last ultrasound internship class, and collect it after filling out. A total of 29 questionnaires were distributed.

Blinding

In our study, the students in the two groups were all unaware of the experimental designs of their groups. To eliminate the subjective bias caused by knowing the students'group categorizations during the scoring process, in the offline image assessment, double-blind grading was conducted by the same teacher. In the online assessment, the system scores each step based on the operation situation.

Statistical method

Mac 2019 version of Microsoft Excel was used to collect all the score data and the questionnaire data, GraphPad Prism 8 was used to test the normality andhomogeneity of variance between the control group and the VR group, Continuous variables with normal distribution were presented as mean ± standard deviation (SD). Suppose the data matched the normal distribution the independent samples t-test was used, if not the Mann–Whitney U-test was used. Frequency analysis was conducted to analyze the rate of students’ agreement with each question in the questionnaire as reflected in the count data and expressed asa percentage (%). P < 0.050 determined that it was statistically significant. Some graphswere plotted using GraphPad Prism 8.

Results

Participants’ demographic data

The demographic data of the control group and the VR group are presented in Table 1. This study comprised a total of 59 students, the control group are 30 students and the VR group are 29 students. The average age of the students inthe control group was 22.40 ± 0.85, while in the VR group it was 22.03 ± 0.78, there The male/female ratio in the control group was 12/18 and in the VR group was 14/15. Experience for using virtual reality simulations was conducted using a questionnaire method. We compared the age, gender and experience in VR of the two groups and found no signifcant diferences (P > 0.05).

Table 1 Demographic Characteristics and Prior VR Experience of Participants

Results of teaching quality

The score for offline image reading in the VR group was better than that in the control group but the differences were not statistically significant (14.34 ± 3.03 VS 14.27 ± 3.05, P > 0.05). Compared to the control group, the VR group performed somewhat better on patient inquiry in the virtual simulation case assessment but the difference was also not statistically significant (16.17 ± 2.44 VS 14.97 ± 2.70, P > 0.05). The scores for physical examination(16.17 ± 1.74 VS 14.73 ± 2.55, P < 0.05), ultrasound manipulation (16.00 ± 2.82 VS 13.87 ± 3.56, P < 0.05) and diagnosis (16.07 ± 2.80 VS 14.07 ± 3.30, P < 0.05) were higher in the VR group than in the control group, and the difference was statistically significant. The total score for teaching quality the VR group were higher than the control group, the difference was statistically significant (78.76 ± 6.94 VS 71.90 ± 5.28, P < 0.05)(Fig. 5).

Fig. 5

Results of teaching quality; A: The score for offline image reading and online virtual simulation case assessment; B: The total score for online and offline assessment

Perspectives survey about cardiac ultrasound virtual simulation technology

Table 2 presents the opinions of students in VR Group regarding cardiac ultrasound virtual simulation technology in the construction of clinical diagnostic reasoning. Four dimensions were designed which include course experience, learning effect, teaching evaluation, and overall evaluation. Questions 1–2 aimed to assess students’ course experience, questions 3–4 were for learning effect and questions 5–6, 7–8 were respectively reflected teaching evaluation, overall evaluation. The result showed that a higher number of students reported an improved.

Table 2 Questionnaire results

course experience. Specifically, the virtual simulation teaching of cardiac ultrasound helps to understand the pathogenesis of structural heart diseases (72.4%, 4.03 ± 0.94) and helps to complete the skills independently (79.3%, 4.07 ± 0.84). The majority of students expressed the VR training was helpful for self-directed learning which not limited by time and space (75.9%, 4.03 ± 0.94), improved the sense of security and confidence in clinical diagnosis and treatment (75.8%, 4.10 ± 1.11) and satisfied with the assessment and evaluation mechanism in the course (75.9%, 4.03 ± 0.68). More than half of the students were satisfied with the design of the virtual simulation course (62.1%, 3.69 ± 1.04), the theory taught and the operational demonstrations in the VR course (62.1%,3.79 ± 0.94) and would like to adopt the virtual simulation teaching model for other medical skills training projects (68.9%, 3.69 ± 0.89).

Discussion

The construction of medical students'diagnostic and treatment thinking ability is of paramount importance in clinical medicine teaching [17]. Existing undergraduate medical courses provide guidance on the basic elements of the diagnostic process, such as collecting medical history, physical examination, and differential diagnosis. However, to a large extent, students still learn the limited knowledge, skills, and behaviors required for effective clinical reasoning through experience and apprenticeship [18]. In a survey of American medical schools, 84% of internal medicine intern directors stated that students have poor understanding of key clinical reasoning concepts when entering clinical internships [19]. We are trying to explore a new teaching method that uses virtual simulation technology to reconstruct typical clinical cases, gradually presenting heart valve disease from anatomical changes, valve dysfunction, patient complaints, physical signs, and cardiac ultrasound images. This allows students to learn the virtual simulation operation of cardiac ultrasound while building their clinical thinking ability for the diagnosis and treatment of valve disease. We did not set the purpose of this study solely as improving the operational skills of cardiac ultrasound, because for undergraduate medical students, through more intuitive methods and diverse interactions, they can integrate the knowledge they have learned in a disease and gain the experience of independently solving problems, thus independently summarizing relevant experiences, which we believe is a way for them to build clinical thinking ability.

Previous studies have shown that simulator training for echocardiography can improve the teaching effectiveness of clinical ultrasound apprenticeship courses and is an effective method for training clinical doctors to master trans-thoracic ultrasound operations [20]. The above research mainly explores the improvement of ultrasound operation skills through the training of ultrasound simulators. However, in clinical teaching, the application of virtual simulation technology should not only stay in the stage of technology imitation [21], but should also leverage its characteristics such as human–machine dialogue, 3D imaging, and big data capacity to demonstrate the process of a certain disease from anatomy to pathophysiology and clinical signs from shallow to deep [22, 23]. Enable students to understand the anatomical structures in ultrasound images and what pathological signs may arise from these anatomical changes. Centered around the technique of echocardiography, this logical line is sorted and reproduced, and through repeated simulation training, it helps students build a coherent medical thinking model. In our study, we found that there was no statistically significant difference in the scores of the two groups for offline image interpretation and patient inquiry in virtual simulation case analysis indicating that through pre-internship training and teacher guidance, there was no significant difference in the mastery of basic knowledge and recognition of basic images between the two groups. This negative result was mainly due to the fact that both groups adopted the same method for acquiring basic knowledge before class. The result also demonstrated the necessity of pre-class basic education in this study. The VR group scored significantly higher than the control group in the online assessment of physical examination, cardiac ultrasound operation practice. Especially in terms of diagnosis in virtual simulation case analysis, the VR group showed a clear advantage compared with the control group. It is considered that the generation of this result is mainly attributed to three aspects. Firstly, the 3D reconstructed cardiac anatomical structure has apparent advantages in enabling students to understand the lesion characteristics of structural heart diseases fully. Secondly, the human–computer interaction in virtual simulation operations promotes students'thinking about the relationship between the pathophysiological mechanisms of diseases and their clinical manifestations. Thirdly, better understanding of the relationship between cardiac ultrasound imaging, anatomical structure and cardiac hemodynamics requires more clinical reasoning skills which indicates that the application of the virtual simulation experimental system has a certain role in improving the construction of medical students'diagnosis and treatment thinking.

In our research, simulation is a means of immediately putting newly acquired knowledge into practice, as training combines both theory and practice. This experiential learning promotes the acquisition of skills and does not immediately affect students who encounter difficulties at the bedside. In fact, from the evaluation of teaching satisfaction, we found that the application of virtual simulation training significantly improved students'sense of security and confidence in clinical diagnosis and treatment, which is consistent with the conclusion of Skinner etal.’s research that ultrasound simulators are effective in teaching the mental support and cognitive skills required for cardiac ultrasound practice [24].

Limitation

The observation time of this study is relatively short, and the training time is limited, mainly as a supplement to undergraduate clinical medicine courses. Therefore, there is limited evaluation of the development of disease diagnosis and treatment thinking among these students after entering clinical practice in the future. Virtual simulation experiments, as a training mode that breaks through time and space limitations, can enable students to undergo repeated online training and make more long-term evaluations in the future. On the other hand, the sample size of this study is relatively small and lacks comparison of learning outcomes among students from different majors and stages. This study is only a single-center study. our virtual simulation software users are mainly students majoring in clinical medicine at Jinan University. The experimental results have not been compared with those of students from a broader range of similar medical colleges, which limits the experimental results to a certain extent. Therefore, further evaluation is needed for the audience of virtual simulation experiments.

Conclusion

This research demonstrates for the first time that cardiac ultrasound virtual simulation technology can improve students'thinking ability in the diagnosis and treatment of structural heart diseases. The virtual simulation technology not only can be used for technology imitation, but also can leverage its characteristics to demonstrate the process of a certain disease from anatomy to pathophysiology and clinical signs from shallow to deep.