The preoperative assessment of thoracic wall adhesions using four-dimensional computed tomography.
Diagnostic accuracy
Four-dimensional computed tomography
Lung cancer surgery
Preoperative assessment
Thoracic wall adhesion
Journal
General thoracic and cardiovascular surgery
ISSN: 1863-6713
Titre abrégé: Gen Thorac Cardiovasc Surg
Pays: Japan
ID NLM: 101303952
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
received:
17
12
2022
accepted:
21
01
2023
medline:
17
7
2023
pubmed:
6
2
2023
entrez:
5
2
2023
Statut:
ppublish
Résumé
Pleural adhesions are challenging during lung cancer surgery and may be associated with a long surgery time and excessive blood loss due to pleural adhesiolysis. We used preoperative four-dimensional computed tomography to quantitatively assess parietal pleural adhesions and determine its diagnostic accuracy. A total of 216 patients with lung cancer underwent four-dimensional computed tomography during the study period. Pleural adhesions were subsequently confirmed by surgery in 85 of these patients, whereas 126 patients had no adhesions. The movements of the tumor or target vessels (α) was tracked. Receiver-operating characteristic curve analysis was used to identify the relationship between adhesions and (α). The movement of (α) was smaller in patients with adhesions than in those without adhesions. The greater the adhesion, the shorter the movement distance (p < 0.001). Receiver-operating characteristic curve analysis demonstrated an area under the curve for the moving (α) point at 0.71 (95% confidence interval: 0.62-0.80) in the upper lung field and at 0.75 (95% confidence interval: 0.64-0.85) in the lower field. To identify adhesions, a cut off of 11.3 mm (sensitivity = 43.6%, specificity = 93.2%) in the upper lung field and a cut off of 41.2 mm (sensitivity = 71.4%, specificity = 66.0%) in the lower lung field were established. Four-dimensional computed tomography is a novel and helpful modality for predicting the presence of parietal pleural adhesions. To obtain robust evidence, further accumulation of cases and re-examination of the analysis methods are needed.
Identifiants
pubmed: 36739555
doi: 10.1007/s11748-023-01912-z
pii: 10.1007/s11748-023-01912-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
464-471Informations de copyright
© 2023. The Author(s), under exclusive licence to The Japanese Association for Thoracic Surgery.
Références
Hyuna S, Jacques F, Rebecca LS, Mathieu L, Isabelle S, Ahmedin J, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.
doi: 10.3322/caac.21660
Committee for Scientific Affairs, The Japanese Association for Thoracic Surgery, Shimizu H, Okada M, Toh Y, Doki Y, et al. Thoracic and cardiovascular surgeries in Japan during 2018: Annual report by the Japanese Association for Thoracic Surgery. Gen Thorac Cardiovasc Surg. 2021;69:179–212.
doi: 10.1007/s11748-020-01460-w
Pitz CC, Brutel de la Rivière A, Elbers HR, Westermann CJ, van den Bosch JM. Surgical treatment of 125 patients with non-small cell lung cancer and chest wall involvement. Thorax. 1996;51:846–50.
Watanabe S, Asamura H, Miyaoka E, Okumura M, Yoshino I, Fujii Y, et al. Results of T4 surgical cases in the Japanese lung cancer registry study: should mediastinal fat tissue invasion really be included in the T4 category? J Thorac Oncol. 2013;8:759–65.
doi: 10.1097/JTO.0b013e318290912d
pubmed: 23608818
Kobayashi N, Kawamura T, Yanagihara T, Goto Y, Ichimura H, Sato Y. Impacts of pleural adhesions on lobectomies for malignant lung tumors. Gen Thorac Cardiovasc Surg. 2022;70:1042–7.
doi: 10.1007/s11748-022-01843-1
pubmed: 35739454
Goldstraw P, Chansky K, Crowley J, Rami-Porta R, Asamura H, Eberhardt WE, et al. The IASLC lung cancer staging project: proposals for revision of the TNM stage groupings in the forthcoming (eighth) edition of the TNM classification for lung cancer. J Thorac Oncol. 2016;11:39–51.
doi: 10.1016/j.jtho.2015.09.009
pubmed: 26762738
Glazer HS, Duncan-Meyer J, Aronberg DJ, Moran JF, Levitt RG, Sagel SS. Pleural and chest wall invasion in bronchogenic carcinoma: CT evaluation. Radiology. 1985;157:191–4.
doi: 10.1148/radiology.157.1.4034965
pubmed: 4034965
Ieko Y, Kadoya N, Kanai T, Nakajima Y, Arai K, Kato T, et al. The impact of 4DCT-ventilation imaging-guided proton therapy on stereotactic body radiotherapy for lung cancer. Radiol Phys Technol. 2020;13:230–7.
doi: 10.1007/s12194-020-00572-5
pubmed: 32537735
De Backer O, Dangas GD, Jilaihawi H, Leipsic JA, Terkelsen CJ, Makkar R, Kini AS, et al. Reduced leaflet motion after transcatheter aortic-valve replacement. N Engl J Med. 2020;382:130–9.
doi: 10.1056/NEJMoa1911426
pubmed: 31733182
Moon Y, Choi SY, Moon MH. The prognosis of stage I non-small cell lung cancer with visceral pleural invasion and whole pleural adhesion after video-assisted thoracoscopic lobectomy: A single center retrospective study. J Thorac Dis. 2020;12:5729–38.
doi: 10.21037/jtd-20-1840
pubmed: 33209405
pmcid: 7656347
Facciolo F, Cardillo G, Lopergolo M, Pallone G, Sera F, Martelli M. Chest wall invasion in non-small cell lung carcinoma: a rationale for en bloc resection. J Thorac Cardiovasc Surg. 2021;121:649–56.
doi: 10.1067/mtc.2001.112826
Tahiri M, Khereba M, Thiffault V, Ferraro P, Duranceau A, Martin J, et al. Preoperative assessment of chest wall invasion in non-small cell lung cancer using surgeon-performed ultrasound. Ann Thorac Surg. 2014;98:984–9.
doi: 10.1016/j.athoracsur.2014.04.111
pubmed: 25038014
Homma T, Ojima T, Yamamoto Y, Shimada Y, Akemoto Y, Kitamura N, et al. Utility of the sliding lung sign for the prediction of preoperative intrathoracic adhesions. J Thorac Dis. 2020;12:4224–32.
doi: 10.21037/jtd-20-886
pubmed: 32944334
pmcid: 7475547
Kajiwara N, Akata S, Uchida O, Usuda J, Ohira T, Kawate N, et al. Cine MRI enables better therapeutic planning than CT in cases of possible lung cancer chest wall invasion. Lung Cancer. 2010;69:203–8.
doi: 10.1016/j.lungcan.2009.10.016
pubmed: 19945190
Hong YJ, Hur J, Lee HJ, Kim YJ, Hong SR, Suh YJ, et al. Respiratory dynamic magnetic resonance imaging for determining aortic invasion of thoracic neoplasms. J Thorac Cardiovasc Surg. 2014;148:644–50.
doi: 10.1016/j.jtcvs.2013.12.060
pubmed: 24507989
Choong CK, Pasricha SS, Li X, Briggs P, Ramdave S, Crossett M, et al. Dynamic four dimensional computed tomography for preoperative assessment of lung cancer invasion into adjacent structures. Eur J Cardiothorac Surg. 2015;47:239–43.
doi: 10.1093/ejcts/ezu265
pubmed: 25082145
Suzuki J, Oizumi H, Watarai H, Hamada A, Nakahashi K, Takamori S, et al. The preoperative assessment of subpleural lung cancer movement to distinguish thoracic wall adhesion or invasion using four-dimensional computed-tomography. Gen Thorac Cardiovasc Surg. 2019;67:1097–9.
doi: 10.1007/s11748-019-01090-x
pubmed: 30843149
Sakuma K, Yamashiro T, Moriya H, Murayama S, Ito H. Parietal pleural invasion/adhesion of subpleural lung cancer: quantitative 4-dimensional CT analysis using dynamic-ventilatory scanning. Eur J Radiol. 2017;87:36–44.
doi: 10.1016/j.ejrad.2016.12.004
pubmed: 28065373