Application of echocardiography in diagnosing right heart occupying lesions

苏志虹 黄枢 杨晓岑 李琪虹 黄顺发

doi:10.16098/j.issn.0529-1356.2026.01.010

PDF(3273 KB)

Acta Anatomica Sinica ›› 2026, Vol. 57 ›› Issue (1) : 64-70. DOI: 10.16098/j.issn.0529-1356.2026.01.010

Robotics and Surgical Navigation Column

Application of echocardiography in diagnosing right heart occupying lesions

SU Zhi-hong¹, HUANG Shu¹, YANG Xiao-cen¹, LI Qi-hong¹, HUANG Shun-fa^2*

Author information +

History +

Abstract

Objective To evaluate the diagnostic value of echocardiography for right heart occupying lesions (RHOL). MethodsA retrospective analysis was conducted on echocardiographic data from 76 patients with pathologically confirmed RHOL. The echocardiographic diagnoses were compared with pathological findings to calculate the diagnostic accuracy. ResultsAmong the 76 RHOL cases, malignant tumors were the most common (40/76, 52.6%), with an echocardiographic diagnostic accuracy of 92.5% (37/40). Other identified lesions included myxomas (14/76) and thrombi (12/76). Echocardiography demonstrated high diagnostic accuracy for myxomas, thrombi, and residual calcification of the eustachian valve (83.3%-100%). In contrast, the diagnostic accuracy was lower for lipomas and intravenous leiomyomatosis (33.3% and 50%, respectively). Furthermore, pericardial effusion was present in 62.5% (25/40) of the malignant cases. ConclusionEchocardiography is an effective tool for diagnosing RHOL, showing high diagnostic value for malignant tumors, thrombi, and myxomas. The presence of concurrent pericardial effusion serves as a significant indicator of malignant lesions.

Key words

Ultrasonic cardiography / Right heart / Cardiac occupying lesion / Retrospective analysis / Human

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

SU Zhi-hong, HUANG Shu, YANG Xiao-cen, LI Qi-hong, HUANG Shun-fa. Application of echocardiography in diagnosing right heart occupying lesions[J]. Acta Anatomica Sinica. 2026, 57(1): 64-70 https://doi.org/10.16098/j.issn.0529-1356.2026.01.010

References

［1］Hudzik BM-JK，Glowacki J. Maglinant tumors of the heart［J］. Cancer Epidemiol，2015，39（5）：665-672.

［2］Chen Y, Li Y, Zhang N, et al. Clinical and imaging features of primary cardiac angiosarcoma［J］. Diagnostics (Basel), 2020,10(10):776.

［3］Kusunose K, Haga A, Abe T, et al. Utilization of artificial intelligence in echocardiography［J］. Circ J, 2019, 83(8):1623-1629.

［4］Lin Y, Wu W, Gao L, et al. Multimodality imaging of benign primary cardiac tumor［J］. Diagnostics (Basel), 2022,12(10):2543.

［5］Qayyum SN. A comprehensive review of applications of artificial intelligence in echocardiography［J］. Curr Probl Cardiol, 2024, 49(2):102250.

［6］Madani A, Arnaout R, Mofrad M, et al. Fast and accurate view classification of echocardiograms using deep learning［J］. NPJ Digit Med, 2018, 1:6.

［7］Liu GW, Sun Y, Ma N, et al. Pathological classification and ultrasonic characteristics of occupying lesions in the right heart system in children ［J］. Journal of Cardiovascular and Pulmonary Diseases, 2022, 41(1): 84-88. (in Chinese)

刘国文,孙妍,马宁,等.儿童右心系统占位性病变的病理分型及超声特征分析［J］.心肺血管病杂志,2022,41(1):84-88.

［8］Li MM. Diagnostic value of echocardiography for primary cardiac tumors［J］. Gansu Medical Journal, 2020, 39(10): 927-929. (in Chinese)

李萌萌.超声心动图对原发性心脏肿瘤的诊断价值［J］.甘肃医药,2020,39(10):927-929.

［9］Shi W, Mo LL, Bi LL, et al. Analysis of the application value of echocardiography in the diagnosis of right heart occupying lesions［J］. Chinese Journal of Cardiovascular Rehabilitation Medicine, 2019, 28(1): 69-72. (in Chinese)

施唯,莫凌莉,毕磊磊,等.超声心动图在右心占位性病变诊断中的应用价值分析［J］.心血管康复医学杂志,2019, 28(1):69-72.

［10］Zhang L, Chen Y. Application value of color doppler ultrasound in diagnosis of intracardiac thrombus［J］. Chinese Journal of Thrombosis and Hemostasis, 2020, 26(5): 770-771,773. (in Chinese)

张蕾,陈艳.彩色多普勒超声在心腔血栓诊断中的应用价值［J］.血栓与止血学, 2020,26(5):770-771，773.

［11］Sun ShF. Application of echocardiography in differentiating cardiac tumors from intracardiac thrombi and vegetations［J］. Journal of Imaging Research and Medical Applications, 2019, 3(16): 112-113. (in Chinese)

孙石芬.超声心动图在鉴别心脏肿瘤与心内血栓及赘生物中的应用［J］.影像研究与医学应用,2019,3(16):112-113.

［12］Zhou TZh, Yi F, Lu X. Analysis of ultrasonic imaging characteristics in patients with cardiac myxoma［J］. Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases, 2024, 24(7): 48-50. (in Chinese)

周天志,易芳,鲁旭.心脏粘液瘤患者超声影像特征分析［J］.心脑血管病防治,2024,24(7):48-50.

［13］Wu XQ, Yang XY, Li Y, et al. Progress in clinical diagnosis and treatment of cardiac lipoma［J］. Shandong Medical Journal, 2018,58(44): 109-112. (in Chinese)

吴晓琴,杨新宇,李旸,等.心脏脂肪瘤的临床诊治进展［J］.山东医药,2018,58(44):109-112.

［14］Li LL, Guo HW, Wei K, et al. Clinical characteristics and surgical treatment outcomes of cardiac lipoma［J］. Practical Geriatrics, 2019, 1: 33-35. (in Chinese)

李林林,郭宏伟,魏柯,等.心脏脂肪瘤的临床特征及外科治疗结果［J］.实用老年医学,2019, 1:33-35.

［15］Lim WH, Lamaro VP, Sivagnanam V. Manifestation and management of intravenous leiomyomatosis: a systematic review of the literature［J］. Surg Oncol, 2022，45:101879.

［16］Zhang J, Deo RC. Response by Zhang and Deo to letter regarding article, “fully automated echocardiogram interpretation in clinical practice: feasibility and diagnostic accuracy”［J］. Circulation, 2019,139(13):1648-1649.

［17］Pirruccello JP, Di Achille P, Choi SH, et al. Deep learning of left atrial structure and function provides link to atrial fibrillation risk［J］. Nat Commun, 2024，15(1):4304.

［18］Ouyang D, He B, Ghorbani A, et al. Video-based AI for beat-to-beat assessment of cardiac function［J］. Nature, 2020, 580(7802):252-256.

［19］Zhang J, Xiao S, Zhu Y, et al. Advances in the application of artificial intelligence in fetal echocardiography［J］. J Am Soc Echocardiogr, 2024,37(5):550-561.