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Automatic quantification of left ventricular function by medical students using ultrasound.

ABSTRACT: BACKGROUND:Automatic analyses of echocardiograms may support inexperienced users in quantifying left ventricular (LV) function. We have developed an algorithm for fully automatic measurements of mitral annular plane systolic excursion (MAPSE) and mitral annular systolic (S') and early diastolic (e') peak velocities. We aimed to study the influence of user experience of automatic measurements of these indices in echocardiographic recordings acquired by medical students and clinicians. METHODS:We included 75 consecutive patients referred for echocardiography at a university hospital. The patients underwent echocardiography by clinicians (cardiologists, cardiology residents and sonographers), who obtained manual reference measurements of MAPSE by M-mode and of S' and e' by colour tissue Doppler imaging (cTDI). Immediately after, each patient was examined by 1 of 39 medical students who were instructed in image acquisition on the day of participation. Each student acquired cTDI recordings from 1 to 4 patients. All cTDI recordings by students and clinicians were analysed for MAPSE, S' and e' using a fully automatic algorithm. The automatic measurements were compared to the manual reference measurements. RESULTS:Correct tracking of the mitral annulus was feasible in 50 (67%) and 63 (84%) of the students' and clinicians' recordings, respectively (p?=?0.007). Image quality was highest in the clinicians' recordings. Mean difference?±?standard deviation of the automatic measurements of the students' recordings compared to the manual reference was -?0.0?±?2.0?mm for MAPSE, 0.3?±?1.1?cm/s for S' and 0.6?±?1.4?cm/s for e'. The corresponding intraclass correlation coefficients for MAPSE, S' and e' were 0.85 (good), 0.89 (good) and 0.92 (excellent), respectively. Automatic measurements from the students' and clinicians' recordings were in similar agreement with the reference when mitral annular tracking was correct. CONCLUSIONS:In case of correct tracking of the mitral annulus, the agreement with reference for the automatic measurements was overall good. Low image quality reduced feasibility. Adequate image acquisition is essential for automatic analyses of LV function indices, and thus, appropriate education of the operators is mandatory. Automatic measurements may help inexperienced users of ultrasound, but do not remove the need for dedicated education and training.

SUBMITTER: Grue JF

PROVIDER: S-EPMC7077164 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Automatic quantification of left ventricular function by medical students using ultrasound.

Grue Jahn Frederik JF Storve Sigurd S Dalen Håvard H Mjølstad Ole Christian OC Samstad Stein O SO Eriksen-Volnes Torfinn T Torp Hans H Haugen Bjørn Olav BO

BMC medical imaging 20200316 1

<h4>Background</h4>Automatic analyses of echocardiograms may support inexperienced users in quantifying left ventricular (LV) function. We have developed an algorithm for fully automatic measurements of mitral annular plane systolic excursion (MAPSE) and mitral annular systolic (S') and early diastolic (e') peak velocities. We aimed to study the influence of user experience of automatic measurements of these indices in echocardiographic recordings acquired by medical students and clinicians.<h4> ...[more]

PMID: 32178639

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Project description:BackgroundThe beating heart is the generator of blood flow through the cardiovascular system. Within the heart's own chambers, normal complex blood flow patterns can be disturbed by diseases. Methods for the quantification of intra-cardiac blood flow, with its 4D (3D+time) nature, are lacking. We sought to develop and validate a novel semi-automatic analysis approach that integrates flow and morphological data.MethodIn six healthy subjects and three patients with dilated cardiomyopathy, three-directional, three-dimensional cine phase-contrast cardiovascular magnetic resonance (CMR) velocity data and balanced steady-state free-precession long- and short-axis images were acquired. The LV endocardium was segmented from the short-axis images at the times of isovolumetric contraction (IVC) and isovolumetric relaxation (IVR). At the time of IVC, pathlines were emitted from the IVC LV blood volume and traced forwards and backwards in time until IVR, thus including the entire cardiac cycle. The IVR volume was used to determine if and where the pathlines left the LV. This information was used to automatically separate the pathlines into four different components of flow: Direct Flow, Retained Inflow, Delayed Ejection Flow and Residual Volume. Blood volumes were calculated for every component by multiplying the number of pathlines with the blood volume represented by each pathline. The accuracy and inter- and intra-observer reproducibility of the approach were evaluated by analyzing volumes of LV inflow and outflow, the four flow components, and the end-diastolic volume.ResultsThe volume and distribution of the LV flow components were determined in all subjects. The calculated LV outflow volumes [ml] (67 +/- 13) appeared to fall in between those obtained by through-plane phase-contrast CMR (77 +/- 16) and Doppler ultrasound (58 +/- 10), respectively. Calculated volumes of LV inflow (68 +/- 11) and outflow (67 +/- 13) were well matched (NS). Low inter- and intra-observer variability for the assessment of the volumes of the flow components was obtained.ConclusionsThis semi-automatic analysis approach for the quantification of 4D blood flow resulted in accurate LV inflow and outflow volumes and a high reproducibility for the assessment of LV flow components.

Project description:PurposePoint-of-care ultrasound (POCUS) is a sensitive, safe, and efficient tool used in many clinical settings and is an essential part of medical education in the United States. Numerous studies present improved diagnostic performances and positive clinical outcomes among POCUS users. However, others stress the degree to which the modality is user-dependent, rendering high-quality POCUS training necessary in medical education. In this study, the authors aimed to investigate the potential of an artificial intelligence (AI) based quality indicator tool as a teaching device for cardiac POCUS performance.MethodsThe authors integrated the quality indicator tool into the pre-clinical cardiac ultrasound course for 4th-year medical students and analyzed their performances. The analysis included 60 students who were assigned to one of two groups as follows: the intervention group using the AI-based quality indicator tool and the control group. Quality indicator users utilized the tool during both the course and the final test. At the end of the course, the authors tested the standard echocardiographic views, and an experienced clinician blindly graded the recorded clips. Results were analyzed and compared between the groups.ResultsThe results showed an advantage in quality indictor users' median overall scores (P = 0.002) with a relative risk of 2.3 (95% CI: 1.10, 4.93, P = 0.03) for obtaining correct cardiac views. In addition, quality indicator users also had a statistically significant advantage in the overall image quality in various cardiac views.ConclusionsThe AI-based quality indicator improved cardiac ultrasound performances among medical students who were trained with it compared to the control group, even in cardiac views in which the indicator was inactive. Performance scores, as well as image quality, were better in the AI-based group. Such tools can potentially enhance ultrasound training, warranting the expansion of the application to more views and prompting further studies on long-term learning effects.

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Project description:BackgroundMedical students as future clinicians will apply their anatomy knowledge in medical imaging. There are various radiological resources available for the medical students to learn anatomy and contextualise it to the clinical setting. Ultrasound is a safe and non- invasive imaging procedure commonly used in clinical practice. This study aimed to use portable ultrasound and evaluate its impact as an adjunct to cadaveric anatomy teaching together with cross sectional anatomy images and line diagrams.MethodsUltrasound teaching was incorporated into upper limb and lower limb anatomy practical dissecting room sessions. The number of medical students who participated was 121 students from the year 2008 - 2009 and 94 students from the year 2009- 2010. The students were divided into groups of 15-20. Initially ultrasound demonstration was carried out on a volunteer and then the students were given the opportunity to use the ultrasound and identify normal anatomical structures visualized on images. For the students in the year 2009- 2010, ultrasound teaching was supplemented with cross sectional anatomy images and line diagrams. Questionnaires were distributed with seven questions rated using four point Likert scale and free text. Qualitative data was analysed using 2- proportion Z test and Fischer's exact test.ResultsThe number of students in the 2009-2010 year group who were confident in interpreting ultrasound images increased significantly when compared to the 2008-2009 year group of students. The majority of students were able to identify structures like bone, muscles and blood vessels on ultrasound images. There was a significant increase in the number of students who found the ultrasound teaching useful and also those who regarded ultrasound to have improved understanding of anatomy considerably.ConclusionsUltrasound acts as a useful adjunct to teach anatomy in a clinical context to medical students. The use of cross sectional anatomy images and line diagrams together can aid ultrasound image orientation of structures during these sessions. Early exposure to this imaging technology may prime students for later encounters with ultrasound during clinical practice.

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Automatic quantification of left ventricular function by medical students using ultrasound.

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Automatic quantification of left ventricular function by medical students using ultrasound.

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