Real-time guidance by deep learning of experienced operators to improve the standardization of echocardiographic acquisitions.

European heart journal. Imaging methods and practice Pub Date : 2023-11-27 eCollection Date: 2023-09-01 DOI:10.1093/ehjimp/qyad040
Sigbjorn Sabo, David Pasdeloup, Hakon Neergaard Pettersen, Erik Smistad, Andreas Østvik, Sindre Hellum Olaisen, Stian Bergseng Stølen, Bjørnar Leangen Grenne, Espen Holte, Lasse Lovstakken, Havard Dalen
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Abstract

Aims: Impaired standardization of echocardiograms may increase inter-operator variability. This study aimed to determine whether the real-time guidance of experienced sonographers by deep learning (DL) could improve the standardization of apical recordings.

Methods and results: Patients (n = 88) in sinus rhythm referred for echocardiography were included. All participants underwent three examinations, whereof two were performed by sonographers and the third by cardiologists. In the first study period (Period 1), the sonographers were instructed to provide echocardiograms for the analyses of the left ventricular function. Subsequently, after brief training, the DL guidance was used in Period 2 by the sonographer performing the second examination. View standardization was quantified retrospectively by a human expert as the primary endpoint and the DL algorithm as the secondary endpoint. All recordings were scored in rotation and tilt both separately and combined and were categorized as standardized or non-standardized. Sonographers using DL guidance had more standardized acquisitions for the combination of rotation and tilt than sonographers without guidance in both periods (all P ≤ 0.05) when evaluated by the human expert and DL [except for the apical two-chamber (A2C) view by DL evaluation]. When rotation and tilt were analysed individually, A2C and apical long-axis rotation and A2C tilt were significantly improved, and the others were numerically improved when evaluated by the echocardiography expert. Furthermore, all, except for A2C rotation, were significantly improved when evaluated by DL (P < 0.01).

Conclusion: Real-time guidance by DL improved the standardization of echocardiographic acquisitions by experienced sonographers. Future studies should evaluate the impact with respect to variability of measurements and when used by less-experienced operators.

Clinicaltrialsgov identifier: NCT04580095.

通过对经验丰富的操作员进行深度学习来提供实时指导,从而提高超声心动图采集的标准化程度。
目的:超声心动图的标准化程度不高可能会增加操作者之间的差异性。本研究旨在确定通过深度学习(DL)对经验丰富的超声技师进行实时指导是否能提高心尖记录的标准化程度:研究纳入了窦性心律患者(n = 88)进行超声心动图检查。所有参与者均接受了三次检查,其中两次由超声技师进行,第三次由心脏病专家进行。在第一个研究阶段(第一阶段),超声技师接受指导,为分析左心室功能提供超声心动图。随后,经过简单培训后,超声技师在第二阶段进行第二次检查时使用 DL 指导。视图标准化由人类专家进行回顾性量化,作为主要终点,DL 算法作为次要终点。所有记录均按旋转和倾斜度分别或合并评分,并分为标准化和非标准化两类。在由人类专家和 DL 进行评估时(除心尖两腔(A2C)视图由 DL 评估外),使用 DL 引导的超声技师在两个时期内获得的旋转和倾斜组合标准化程度均高于未使用引导的超声技师(所有 P 均小于 0.05)。在对旋转和倾斜进行单独分析时,A2C 和心尖长轴旋转以及 A2C 倾斜均有显著改善,而在由超声心动图专家进行评估时,其他均有数值上的改善。此外,除 A2C 旋转外,其他均在 DL 评估时有明显改善(P < 0.01):结论:DL 的实时指导提高了经验丰富的超声技师超声心动图采集的标准化程度。未来的研究应评估测量的可变性和经验不足的操作者使用时的影响:NCT04580095。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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