胸膜超声在呼吸系统疾病中的应用现状及展望

doi:10.3969/j.issn.1006-7795.2023.06.010

摘要/Abstract

摘要： 胸膜超声作为肺部超声的一部分，简便、高效，是评估和监测呼吸系统疾病的重要有效手段。常规技术包括胸膜的静态和动态评估，如胸膜形态、厚度、运动情况、胸膜下改变及胸腔积液，这与呼吸系统各疾病的病理生理存在密切联系。因此，不同呼吸系统疾病表现为不同的胸膜改变，可以帮助医生快速区分肺水肿、慢性阻塞性肺疾病、肺炎、肺栓塞、肺间质纤维化等疾病。胸膜超声在胸腔积液和周围型肺占位的定性及定量评估中，展现出独特优势。超声新技术如斑点追踪技术、超声造影、弹性成像、深度学习算法等的应用，使得胸膜超声进入新阶段。随着技术的进步，胸膜超声展示出巨大应用潜力，特别是动态征象的人工智能识别、三维模型计算胸腔积液量、周围型肺结节的人工智能识别及定性诊断等，可能会更加高效地提供临床信息和改变诊疗模式。本文就胸膜超声在呼吸系统疾病中的应用现状及未来发展趋势作一综述。

关键词: 超声, 胸膜, 呼吸系统疾病

Abstract: As a part of lung ultrasound, pleural ultrasound is a simple, efficient, important, and effective tool in the assessment and monitoring of respiratory diseases. Routine techniques include static and dynamic assessment of the pleura, such as pleural morphology, thickness, motion, subpleural changes, and pleural effusion, which are closely related to the pathophysiology of various respiratory diseases. Therefore, different respiratory diseases show different pleural changes, which can help us to quickly differentiate between diseases such as pulmonary edema, chronic obstructive pulmonary disease, pneumonia, pulmonary embolism, and interstitial fibrosis. Pleural ultrasound demonstrates unique advantages in the qualitative and quantitative assessment of pleural effusion and peripheral lung occupations. New ultrasound technologies such as speckle tracking technology, ultrasonography, elastography, and the application of deep learning algorithms have brought pleural ultrasound into a new phase. With the advancement of technology, pleural ultrasound demonstrates great potential for application, especially artificial intelligence (AI) recognition of dynamic signs, 3D models calculation of pleural effusion volume, AI recognition of peripheral lung nodules, and qualitative diagnosis, which may provide clinical information and change the diagnostic and treatment modes more efficiently. In this review, the status and future development of pleural ultrasound application in respiratory diseases are discussed.

Key words: ultrasound, pleura, respiratory diseases

中图分类号:

R445
R56

孙哲, 马姣姣, 张波. 胸膜超声在呼吸系统疾病中的应用现状及展望[J]. 首都医科大学学报, 2023, 44(6): 966-972.

Sun Zhe, Ma Jiaojiao, Zhang Bo. Application status and prospects of pleural ultrasound in respiratory diseases[J]. Journal of Capital Medical University, 2023, 44(6): 966-972.

参考文献

［1］GBD Chronic Respiratory Disease Collaborators. Prevalence and attributable health burden of chronic respiratory diseases, 1990－2017: a systematic analysis for the Global Burden of Disease Study 2017［J］. Lancet Respir Med, 2020, 8(6): 585－596.
［2］Antony V B. Immunological mechanisms in pleural disease［J］. Eur Respir J, 2003, 21(3): 539－544.
［3］Joyner C R Jr, Herman R J, Reid J M. Reflected ultrasound in the detection and localization of pleural effusion［J］. JAMA, 1967, 200(5): 399－402.
［4］Demi L, Wolfram F, Klersy C, et al. New international guidelines and consensus on the use of lung ultrasound［J］. J Ultrasound Med, 2023, 42(2): 309－344.
［5］Gargani L, Romei C, Bruni C, et al. Lung ultrasound B-lines in systemic sclerosis: cut-off values and methodological indications for interstitial lung disease screening［J］. Rheumatology (Oxford), 2022, 61(SI): SI56-SI64.
［6］Haaksma M E, Smit J M, Heldeweg M L A, et al. Extended lung ultrasound to differentiate between pneumonia and atelectasis in critically ill patients: a diagnostic accuracy study［J］. Crit Care Med, 2022, 50(5): 750－759.
［7］Hew M, Heinze S. Chest ultrasound in practice: a review of utility in the clinical setting［J］. Intern Med J, 2012, 42(8): 856－865.
［8］Laursen C B, Clive A, Hallifax R, et al. European respiratory society statement on thoracic ultrasound［J］. Eur Respir J, 2021, 57(3): 2001519.
［9］Tan G L, Lian X H, Zhu Z X, et al. Use of lung ultrasound to differentiate coronavirus disease 2019 (COVID-19) pneumonia from community-acquired pneumonia［J］. Ultrasound Med Biol, 2020, 46(10): 2651－2658.
［10］Chira R, Chira A, Mânzat S􀅣pl􀅣can R, et al. Pleural ultrasonography. Pictorial essay［J］. Med Ultrason, 2014, 16(4): 364－371.
［11］李虹, 李一丹, 朱维维, 等. 高频胸膜肺超声对呼吸困难患者肺部疾病的诊断价值: 与CT对照研究［J］. 中华超声影像学杂志, 2016, 25(4): 305－308.
［12］赵浩天, 刘元琳, 刘奕, 等. 胸膜超声表现的临床意义［J］. 中国超声医学杂志, 2023, 39(1): 12－16.
［13］Dobbe L, Rahman R, Elmassry M, et al. Cardiogenic pulmonary edema［J］. Am J Med Sci, 2019, 358(6): 389－397.
［14］Rabe K F, Watz H. Chronic obstructive pulmonary disease［J］. Lancet, 2017, 389(10082): 1931－1940.
［15］Allinovi M, Parise A, Giacalone M, et al. Lung ultrasound may support diagnosis and monitoring of COVID-19 pneumonia［J］. Ultrasound Med Biol, 2020, 46(11): 2908－2917.
［16］Reissig A, Kroegel C. Transthoracic ultrasound of lung and pleura in the diagnosis of pulmonary embolism: a novel non-invasive bedside approach［J］. Respiration, 2003, 70(5): 441－452.
［17］Podolanczuk A J, Wong A W, Saito S, et al. Update in interstitial lung disease 2020［J］. Am J Respir Crit Care Med, 2021, 203(11): 1343－1352.
［18］王睿, 张慧, 丁毅, 等. 间质性肺疾病高分辨率CT常见征象的超声特点［J］. 中华结核和呼吸杂志, 2020, 43(7): 564－570.
［19］Buda N, Piskunowicz M, Porzezińska M, et al. Lung ultrasonography in the evaluation of interstitial lung disease in systemic connective tissue diseases: criteria and severity of pulmonary fibrosis-analysis of 52 patients［J］. Ultraschall Med, 2016, 37(4): 379－385.
［20］Mullan C P, Madan R, Trotman-Dickenson B, et al. Radiology of chest wall masses［J］. AJR Am J Roentgenol, 2011, 197(3): W460-W470.
［21］Adams F V, Galati V. M-mode ultrasonic localization of pleural effusion. Use in patients with nondiagnostic physical and roentgenographic examinations［J］. JAMA, 1978, 239(17): 1761－1764.
［22］Yang P C, Luh K T, Chang D B, et al. Value of sonography in determining the nature of pleural effusion: analysis of 320 cases［J］. AJR Am J Roentgenol, 1992, 159(1): 29－33.
［23］Shao R J, Du M J, Xie J T. Use of lung ultrasound for the diagnosis and treatment of pleural effusion［J］. Eur Rev Med Pharmacol Sci, 2022, 26(23): 8771－8776.
［24］Bugalho A, Ferreira D, Dias S S, et al. The diagnostic value of transthoracic ultrasonographic features in predicting malignancy in undiagnosed pleural effusions: a prospective observational study［J］. Respiration, 2014, 87(4): 270－278.
［25］Qureshi N R, Rahman N M, Gleeson F V. Thoracic ultrasound in the diagnosis of malignant pleural effusion［J］. Thorax, 2009, 64(2): 139－143.
［26］Lin F C, Chou C W, Chang S C. Usefulness of the suspended microbubble sign in differentiating empyemic and nonempyemic hydropneumothorax［J］. J Ultrasound Med, 2001, 20(12): 1341－1345.
［27］Vignon P, Chastagner C, Berkane V, et al. Quantitative assessment of pleural effusion in critically ill patients by means of ultrasonography［J］. Crit Care Med, 2005, 33(8): 1757－1763.
［28］Roch A, Bojan M, Michelet P, et al. Usefulness of ultrasonography in predicting pleural effusions>500 mL in patients receiving mechanical ventilation［J］. Chest, 2005, 127(1): 224－232.
［29］Balik M, Plasil P, Waldauf P, et al. Ultrasound estimation of volume of pleural fluid in mechanically ventilated patients［J］. Intensive Care Med, 2006, 32(2): 318.
［30］Remérand F, Dellamonica J, Mao Z, et al. Multiplane ultrasound approach to quantify pleural effusion at the bedside［J］. Intensive Care Med, 2010, 36(4): 656－664.
［31］Volpicelli G, Elbarbary M, Blaivas M, et al. International evidence-based recommendations for point-of-care lung ultrasound［J］. Intensive Care Med, 2012, 38(4): 577－591.
［32］Amir R, Knio Z O, Mahmood F, et al. Ultrasound as a screening tool for central venous catheter positioning and exclusion of pneumothorax［J］. Crit Care Med, 2017, 45(7): 1192－1198.
［33］Hew M, Tay T R. The efficacy of bedside chest ultrasound: from accuracy to outcomes［J］. Eur Respir Rev, 2016, 25(141): 230－246.
［34］Volpicelli G, Boero E, Sverzellati N, et al. Semi-quantification of pneumothorax volume by lung ultrasound［J］. Intensive Care Med, 2014, 40(10): 1460－1467.
［35］Prina E, Torres A, Carvalho C R R. Lung ultrasound in the evaluation of pleural effusion［J］. J Bras Pneumol, 2014, 40(1): 1－5.
［36］吴勇, 朱东山, 姚运明, 等. 超声检测胸膜滑动征判定胸膜腔粘连［J］. 中华胸心血管外科杂志, 2010, 26(3): 190－192.
［37］Mojoli F, Bouhemad B, Mongodi S, et al. Lung ultrasound for critically ill patients［J］. Am J Respir Crit Care Med, 2019, 199(6): 701－714.
［38］Tzadok B, Blumberg Y, Shubert M, et al. Speckled tracking of pleura-A novel tool for lung ultrasound; distinguishing COVID-19 from acute heart failure［J］. J Clin Med, 2022, 11(16): 4846.
［39］Duclos G, Bobbia X, Markarian T, et al. Speckle tracking quantification of lung sliding for the diagnosis of pneumothorax: a multicentric observational study［J］. Intensive Care Med, 2019, 45(9): 1212－1218.
［40］Sperandeo M, Trovato F M, Dimitri L, et al. Lung transthoracic ultrasound elastography imaging and guided biopsies of subpleural cancer: a preliminary report［J］. Acta radiol, 2015, 56(7): 798－805.
［41］Lim C K, Chung C L, Lin Y T, et al. Transthoracic ultrasound elastography in pulmonary lesions and diseases［J］. Ultrasound Med Biol, 2017, 43(1): 145－152.
［42］Ozgokce M, Yavuz A, Akbudak I, et al. Usability of transthoracic shear wave elastography in differentiation of subpleural solid masses［J］. Ultrasound Q, 2018, 34(4): 233－237.
［43］Wei H, Lu Y C, Ji Q, et al. The application of conventional us and transthoracic ultrasound elastography in evaluating peripheral pulmonary lesions［J］. Exp Ther Med, 2018, 16(2): 1203－1208.
［44］Kuo Y W, Chen Y L, Wu H D, et al. Application of transthoracic shear-wave ultrasound elastography in lung lesions［J］. Eur Respir J, 2021, 57(3): 2002347.
［45］Li W B, Shen M J, Zhang Y, et al. A model for predicting malignant sub-pleural solid masses using grayscale ultrasound and ultrasound elastography［J］. Ultrasound Med Biol, 2021, 47(5): 1212－1218.
［46］Jiang B, Li X L, Yin Y, et al. Ultrasound elastography: a novel tool for the differential diagnosis of pleural effusion［J］. Eur Respir J, 2019, 54(2): 1802018.
［47］Deng M M, Ye X W, Ma J W, et al. Ultrasonic elastography-guided pleural biopsy for the diagnosis of pleural effusion: a multicenter prospective study of diagnostic test performance［J］. Ann Am Thorac Soc, 2023, 20(9): 1242－1249.
［48］Fu Y, Lei Y T, Cui L G, et al. Can ultrasound and contrast-enhanced ultrasound help differentiate between subpleural focal organizing pneumonia and primary lung malignancy?［J］. Diagnostics (Basel), 2022, 12(9): 2074.
［49］Bai Z N, Liu T, Liu W, et al. Application value of contrast-enhanced ultrasound in the diagnosis of peripheral pulmonary focal lesions［J］. Medicine (Baltimore), 2022, 101(29): e29605.
［50］Safai Zadeh E, Weide J, Dietrich C F, et al. Diagnostic accuracy of B-mode- and contrast-enhanced ultrasound in differentiating malignant from benign pleural effusions［J］. Diagnostics (Basel), 2021, 11(7): 1293.
［51］Sperandeo M, Rea G, Grimaldi M A, et al. Contrast-enhanced ultrasound does not discriminate between community acquired pneumonia and lung cancer［J］. Thorax, 2017, 72(2): 178－180.
［52］Quarato C M I, Feragalli B, Lacedonia D, et al. Contrast-enhanced ultrasound in distinguishing between malignant and benign peripheral pulmonary consolidations: the debated utility of the contrast enhancement arrival time［J］. Diagnostics (Basel), 2023, 13(4): 666.
［53］Quarato C M I, Cipriani C, Dimitri L, et al. Assessing value of contrast-enhanced ultrasound vs. conventional transthoracic ultrasound in improving diagnostic yield of percutaneous needle biopsy of peripheral lung lesions［J］. Eur Rev Med Pharmacol Sci, 2021, 25(18): 5781－5789.
［54］Zhou D Z, Zhang Y X, Chen W X, et al. Enhanced ultrasound-guided versus non-enhanced ultrasound-guided percutaneous needle biopsy in tissue cellularity of lung malignancies: a propensity score matched study［J］. Quant Imaging Med Surg, 2022, 12(11): 5056－5067.
［55］Wang Y, Xu Z, Huang H, et al. Application of quantitative contrast-enhanced ultrasound for evaluation and guiding biopsy of peripheral pulmonary lesions: a preliminary study［J］. Clin Radiol, 2020, 75(1): 79.e19－79.e24.
［56］Wang J P, Zhou X L, Yan J P, et al. Nanobubbles as ultrasound contrast agent for facilitating small cell lung cancer imaging［J］. Oncotarget, 2017, 8(44): 78153－78162.
［57］Li N, Han L, Jing H. Contrast-enhanced ultrasound with a novel nanoparticle contrast agent for clinical diagnosis in patients with non-small cell lung cancer［J］. Exp Ther Med, 2017, 14(4): 3768－3773.
［58］Xing J, He W, Ding Y W, et al. Correlation between contrast-enhanced ultrasound and microvessel density via CD31 and CD34 in a rabbit VX2 lung peripheral tumor model［J］. Med Ultrason, 2018, 1(1): 37－42.
［59］Zhuo J, Fu W, Liu S. Correlation of contrast-enhanced ultrasound with two distinct types of blood vessels for the assessment of angiogenesis in Lewis lung carcinoma［J］. Ultraschall Med, 2014, 35(5): 468－472.
［60］Chen W X, Zhang Y X, Tang J X, et al. Correlations between contrast-enhanced ultrasound and microvessel density in non-small cell lung cancer: a prospective study［J］. Front Oncol, 2023, 13: 1086251.
［61］Tripathi A, Panicker M R, Rakkunedeth Hareendranathan A, et al. Unsupervised landmark detection and classification of lung infection using transporter neural networks［J］. Comput Biol Med, 2023, 152: 106345.
［62］Carrer L, Donini E, Marinelli D, et al. Automatic pleural line extraction and COVID-19 scoring from lung ultrasound data［J］. IEEE Trans Ultrason Ferroelectr Freq Control, 2020, 67(11): 2207－2217.
［63］Bassiouny R, Mohamed A, Umapathy K, et al. An interpretable object detection-based model for the diagnosis of neonatal lung diseases using ultrasound images［J］. Annu Int Conf IEEE Eng Med Biol Soc, 2021, 2021: 3029－3034.
［64］Porcel J M. Pleural ultrasound for clinicians［J］. Rev Clin Esp (Barc), 2016, 216(8): 427－435.