Potential of Simulators in Ultrasound Diagnostics

Potential of Simulators in Ultrasound Diagnostics

Artificial intelligence (AI) and ultrasound simulators are being used increasingly in medical imaging. With the rapid advent of AI and phantoms in the field of medicine, the question arises as to what influence they have on ultrasound diagnostics. If you ask ChatGPT 3.5 about the efficacy of ultrasound simulators, it will tell you, among other things, that ultrasound simulators are invaluable in medical education and in the training of physicians and medical staff, and that aspiring physicians can learn the basics of ultrasound imaging without jeopardizing the health and well-being of real patients and without the need for expensive equipment. Even though this seems somewhat exaggerated at the moment, the advantages of ultrasound phantoms and automated image analysis are evident. One focus of the so-called “SonoTrainer” is its use in the training and continuing education of physicians. The simulators available today already cover various interdisciplinary fields of application. This includes both diagnostic imaging and interventional procedures for training purposes as well as for diagnosis, setting measurement points, device calibration, and quality control. So-called “tissue-mimicking phantoms” mimic the acoustic properties of human tissue to simulate ultrasound images. “Needle insertion phantoms” support learning of ultrasound-guided procedures, such as amniocentesis or tumor biopsy. “Breast phantoms” simulate breast tissue imaging and are used for training and continuing education in breast sonography. “Obstetric gynecological ultrasound phantoms” are also increasingly being discussed as an education and training tool in prenatal diagnostics and vaginal sonography. In view of the fact that continuing education is facing major challenges in many areas of medicine due to scarce institutional, personnel and financial resources, the integration of ultrasound simulators into the medical curriculum can be used as a complementary part of a structured learning program during medical studies, or for the continuing medical education of physicians. Examples include ultrasound training as part of medical studies. In this context, a study from Lausanne comprising three hours of theoretical and practical content, incl. FAST/eFAST examinations and looking for free fluid on an ultrasound simulator, showed that 89 % of students were in favor of using an ultrasound simulator. It was also shown, however, that 53 % of the students already felt they were competent to perform an ultrasound examination of the abdomen after just three hours of training. This prompted me to reflect on my role as a teacher, and highlighted the importance of balanced planning of course content and the critical use of newer methods [1]. These experiences have shown how important it is, notwithstanding the excitement about this technology, to also convey the complexity of sonography and the limitations of using a phantom.

In prenatal diagnostics as well, ultrasound simulators and AI support learning and recognition of normal sonoanatomy and standardized biometry, as well as visualization of fetal malformations. A meta-analysis conducted by the German Institute for Quality and Efficiency in Health Care (IQWiG) showed a positive association between the qualifications and experience of the examiner and the detection rate of fetal anomalies [2].

Recent studies show that structured learning using a phantom can raise the standard of ultrasound examination in prenatal diagnostics and improve measurement accuracy. Training on the simulator also enables faster learning and visualization of standard fetal structures, including fetal echocardiography and fetal anomalies [3] [4] [5]. In a multicenter study published in this edition, Zhao et al. show that the simulator-based obstetric ultrasound competency assessment tool (OUCAT) has good reliability and validity in assessing ultrasound skills in obstetrics, and can be used to assess the competence of ultrasound examiners. They were also able to demonstrate that the competence of experts was significantly better than that of experienced trainees, and experienced trainees were significantly better than beginners. In this study, the OUCAT comprised 123 elements, 117 of which were able to clearly distinguish between beginners and experts (p < 0.05).

The INVUS phantom, also presented in this edition by Seitzinger et al., enables standardized and realistic training in ultrasound-guided procedures. The study participants included inexperienced (n = 40) and experienced ultrasound examiners (n = 41). Of a total of 81 ultrasound examiners, 73 participants rated the visualization of the lesions as a realistic representation and 86 % (70/81) considered the phantom to be of high clinical significance for learning ultrasound-guided puncture procedures [7].

With regard to the future of the ultrasound machines themselves, it is expected that the resolution will increase and the image quality will improve. AI algorithms will increasingly lead to the automation of image analysis, and perhaps also to providing real-time support in imaging. It should be noted that the data collected so far, while promising, is retrospective and cannot be applied directly to clinical work. In addition to larger training datasets, there is a need for validation studies, which may be particularly helpful for inexperienced ultrasound examiners [8].

This is of relevance since, for example, the number of diagnostic puncture procedures, such as chorionic villus sampling or amniocentesis in prenatal diagnostics, has rapidly decreased due to the optimization of non-invasive screening for trisomies [9]. As a consequence of the declining puncture rates in prenatal diagnostics, not enough physicians are handling the number of cases required to become qualified in this technique [9]. The phantoms for biopsy training could potentially facilitate learning as an additional module; however, this should first be scientifically evaluated.

Combined with rapid developments in AI, the newest generation simulators will not replace core medical skills – but they will help to better structure training and continuing education, and better prepare physicians for clinical applications in their work. For example, a first step would be to determine what proportion of ultrasound simulator training should be included in different courses. Some of the required number of ultrasound examinations could be performed on the phantom. It would also be useful to set up workstations with ultrasound simulators in the clinics that can be used by trainees and for ongoing education. The simulators already enable users to practice various scenarios and obtain feedback. The SonoTrainer thus paves the way for new perspectives in mentoring and for certification programs. The importance of ultrasound simulators in the future will depend on how realistic the simulator is. Realistic tissue models and imaging modules will support the achievement of learning objectives. At the same time, it is necessary to perform a scientific evaluation of the efficacy of this equipment, which can be expensive to purchase, in terms of meeting the clinical requirements. And considering that medical tasks are not limited to diagnostic imaging and clinical evaluation of the images, communication skills will also continue to be a crucial part of the physician’s role – accordingly, simulators and AI will not replace medical tasks, but will challenge and promote them.

Prof. Sevgi Tercanli

Prof. Luigi Raio

Interessenkonflikt

Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht.

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Publication History

Article published online:
04 April 2024