Literature DB >> 31775082

A predictive factor for patients with acute respiratory distress syndrome: CT lung volumetry of the well-aerated region as an automated method.

Akira Nishiyama1, Naoko Kawata2, Hajime Yokota3, Toshihiko Sugiura2, Yosuke Matsumura4, Takashi Higashide5, Takuro Horikoshi3, Shigeto Oda4, Koichiro Tatsumi2, Takashi Uno3.   

Abstract

PURPOSE: Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury that frequently shows fatal outcomes. As radiographic predictive factors, some reports have focused on the region of ill-aerated lung, but none have focused on well-aerated lung. Our objective was to evaluate the relationship between computed tomography (CT) volume of the well-aerated lung region and prognosis in patients with ARDS.
METHOD: This retrospective observational study of a single intensive care unit (ICU) included patients with ARDS treated between April 2011 and May 2013. We identified 42 patients with ARDS for whom adequate helical CT scans were available. CT images were analyzed for 3-dimensional reconstruction, and lung region volumes were measured using automated volumetry methods. Lung regions were identified by CT attenuation in Hounsfield units (HU).
RESULTS: Of the 42 patients, 35 (83.3 %) survived 28 days and 32 (76.2 %) survived to ICU discharge. CT lung volumetry was performed within 144.5 ± 76.6 s, and inter-rater reliability of CT lung volumetry for lung regions below -500 HU (well-aerated lung region) were near-perfect. Well-aerated lung region showed a positive correlation with 28-day survival (P = 0.020), and lung volumes below -900 HU correlated positively with 28-day survival and ICU survival, respectively (P = 0.028, 0.017). Survival outcome was better for percentage of well-aerated lung region/predicted total lung capacity ≥40 % than for <40 % (P = 0.039).
CONCLUSIONS: CT lung volumetry of the well-aerated lung region using an automated method allows fast, reliable quantitative CT analysis and potentially prediction of the clinical course in patients with ARDS.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute respiratory distress syndrome; CT; Chest; Intensive care unit; Lung volumetry

Mesh:

Year:  2019        PMID: 31775082     DOI: 10.1016/j.ejrad.2019.108748

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  14 in total

1.  ARDS Clinical Practice Guideline 2021.

Authors:  Sadatomo Tasaka; Shinichiro Ohshimo; Muneyuki Takeuchi; Hideto Yasuda; Kazuya Ichikado; Kenji Tsushima; Moritoki Egi; Satoru Hashimoto; Nobuaki Shime; Osamu Saito; Shotaro Matsumoto; Eishu Nango; Yohei Okada; Kenichiro Hayashi; Masaaki Sakuraya; Mikio Nakajima; Satoshi Okamori; Shinya Miura; Tatsuma Fukuda; Tadashi Ishihara; Tetsuro Kamo; Tomoaki Yatabe; Yasuhiro Norisue; Yoshitaka Aoki; Yusuke Iizuka; Yutaka Kondo; Chihiro Narita; Daisuke Kawakami; Hiromu Okano; Jun Takeshita; Keisuke Anan; Satoru Robert Okazaki; Shunsuke Taito; Takuya Hayashi; Takuya Mayumi; Takero Terayama; Yoshifumi Kubota; Yoshinobu Abe; Yudai Iwasaki; Yuki Kishihara; Jun Kataoka; Tetsuro Nishimura; Hiroshi Yonekura; Koichi Ando; Takuo Yoshida; Tomoyuki Masuyama; Masamitsu Sanui
Journal:  J Intensive Care       Date:  2022-07-08

2.  Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation.

Authors:  Ezio Lanza; Riccardo Muglia; Isabella Bolengo; Orazio Giuseppe Santonocito; Costanza Lisi; Giovanni Angelotti; Pierandrea Morandini; Victor Savevski; Letterio Salvatore Politi; Luca Balzarini
Journal:  Eur Radiol       Date:  2020-06-26       Impact factor: 5.315

3.  Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia.

Authors:  Davide Colombi; Flavio C Bodini; Marcello Petrini; Gabriele Maffi; Nicola Morelli; Gianluca Milanese; Mario Silva; Nicola Sverzellati; Emanuele Michieletti
Journal:  Radiology       Date:  2020-04-17       Impact factor: 11.105

Review 4.  COVID-19 pneumonia: current evidence of chest imaging features, evolution and prognosis.

Authors:  Anna Rita Larici; Giuseppe Cicchetti; Riccardo Marano; Lorenzo Bonomo; Maria Luigia Storto
Journal:  Chin J Acad Radiol       Date:  2021-05-04

5.  The incremental value of computed tomography of COVID-19 pneumonia in predicting ICU admission.

Authors:  Maurizio Bartolucci; Matteo Benelli; Margherita Betti; Sara Bicchi; Luca Fedeli; Federico Giannelli; Donatella Aquilini; Alessio Baldini; Guglielmo Consales; Massimo Edoardo Di Natale; Pamela Lotti; Letizia Vannucchi; Michele Trezzi; Lorenzo Nicola Mazzoni; Sandro Santini; Roberto Carpi; Daniela Matarrese; Luca Bernardi; Mario Mascalchi
Journal:  Sci Rep       Date:  2021-08-02       Impact factor: 4.379

6.  Prognostic Implication of Volumetric Quantitative CT Analysis in Patients with COVID-19: A Multicenter Study in Daegu, Korea.

Authors:  Byunggeon Park; Jongmin Park; Jae Kwang Lim; Kyung Min Shin; Jaehee Lee; Hyewon Seo; Yong Hoon Lee; Jun Heo; Won Kee Lee; Jin Young Kim; Ki Beom Kim; Sungjun Moon; Sooyoung Choi
Journal:  Korean J Radiol       Date:  2020-08-04       Impact factor: 3.500

7.  CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients.

Authors:  Fengjun Liu; Qi Zhang; Chao Huang; Chunzi Shi; Lin Wang; Nannan Shi; Cong Fang; Fei Shan; Xue Mei; Jing Shi; Fengxiang Song; Zhongcheng Yang; Zezhen Ding; Xiaoming Su; Hongzhou Lu; Tongyu Zhu; Zhiyong Zhang; Lei Shi; Yuxin Shi
Journal:  Theranostics       Date:  2020-04-27       Impact factor: 11.556

8.  Association of "initial CT" findings with mortality in older patients with coronavirus disease 2019 (COVID-19).

Authors:  Yan Li; Zhenlu Yang; Tao Ai; Shandong Wu; Liming Xia
Journal:  Eur Radiol       Date:  2020-06-10       Impact factor: 5.315

9.  Clinical and laboratory data, radiological structured report findings and quantitative evaluation of lung involvement on baseline chest CT in COVID-19 patients to predict prognosis.

Authors:  Cappabianca Salvatore; Fusco Roberta; de Lisio Angela; Paura Cesare; Clemente Alfredo; Gagliardi Giuliano; Lombardi Giulio; Giacobbe Giuliana; Russo Gaetano Maria; Belfiore Maria Paola; Urraro Fabrizio; Grassi Roberta; Feragalli Beatrice; Miele Vittorio
Journal:  Radiol Med       Date:  2020-10-12       Impact factor: 3.469

Review 10.  Advances in medical imaging to evaluate acute respiratory distress syndrome.

Authors:  Shan Huang; Yuan-Cheng Wang; Shenghong Ju
Journal:  Chin J Acad Radiol       Date:  2021-07-17
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