Literature DB >> 19234283

MDCT for automated detection and measurement of pneumothoraces in trauma patients.

Wenli Cai1, Malek Tabbara, Noboru Takata, Hiroyuki Yoshida, Gordon J Harris, Robert A Novelline, Marc de Moya.   

Abstract

OBJECTIVE: The size of a pneumothorax is an important index to guide the emergency treatment of trauma patients--chest tube drainage. The purpose of this study was to develop and validate an automated computer-aided volumetry scheme for detection and measurement of pneumothoraces for trauma patients imaged with MDCT.
MATERIALS AND METHODS: Three pigs and 68 trauma patients with at least one diagnosed occult pneumothorax (23 women and 45 men; age range, 14-89 years; mean age, 41 +/- 19 years) were selected for the development and validation of our computer-aided volumetry scheme for pneumothorax. Computer-aided volumetry of pneumothorax consisted of five automated steps: extraction of pleural region, detection of pneumothorax candidates, delineation of the detected pneumothorax candidates, reduction of false-positive findings, and report of the volumetric measurement of pneumothoraces.
RESULTS: In the animal study, our computer-aided volumetry scheme yielded a mean value of 24.27 +/- 0.64 mL (SD) compared with 25 mL of air volume manually injected in each scan. The correlation coefficients were 0.999 and 0.997 for the in vivo and ex vivo comparison, respectively. In the patient study, the sensitivity of our computer-aided volumetry scheme was 100% with a false-positive rate of 0.15 per case for 32 occult pneumothoraces > or = 25 mL. The correlation coefficient was 0.999 for manual volumetry comparison. This automated computer-aided volumetry scheme took approximately 3 minutes to finish the detection and measurement per case.
CONCLUSION: The results show that our computer-aided volumetry scheme provides an automated method for accurate and efficient detection and measurement of pneumothoraces in MDCT images of trauma patients.

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Year:  2009        PMID: 19234283     DOI: 10.2214/AJR.08.1339

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  13 in total

1.  Optimizing working space in laparoscopy: CT-measurement of the effect of neuromuscular blockade and its reversal in a porcine model.

Authors:  John Vlot; Patricia A Specht; René M H Wijnen; Joost van Rosmalen; Egbert G Mik; Klaas M A Bax
Journal:  Surg Endosc       Date:  2014-11-01       Impact factor: 4.584

2.  Optimizing working-space in laparoscopy: measuring the effect of mechanical bowel preparation in a porcine model.

Authors:  John Vlot; Juliette C Slieker; René Wijnen; Johan F Lange; Klaas N M A Bax
Journal:  Surg Endosc       Date:  2013-01-15       Impact factor: 4.584

3.  Optimizing working space in porcine laparoscopy: CT measurement of the effects of intra-abdominal pressure.

Authors:  John Vlot; Rene Wijnen; Robert Jan Stolker; Klaas Bax
Journal:  Surg Endosc       Date:  2012-12-13       Impact factor: 4.584

4.  MDCT for computerized volumetry of pneumothoraces in pediatric patients.

Authors:  Wenli Cai; Edward Y Lee; Abhinav Vij; Soran A Mahmood; Hiroyuki Yoshida
Journal:  Acad Radiol       Date:  2011-01-07       Impact factor: 3.173

5.  Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography.

Authors:  Sebastian Röhrich; Thomas Schlegl; Constanze Bardach; Helmut Prosch; Georg Langs
Journal:  Eur Radiol Exp       Date:  2020-04-17

6.  Automatic segmentation and measurement of pleural effusions on CT.

Authors:  Jianhua Yao; John Bliton; Ronald M Summers
Journal:  IEEE Trans Biomed Eng       Date:  2013-01-29       Impact factor: 4.538

7.  MDCT quantification is the dominant parameter in decision-making regarding chest tube drainage for stable patients with traumatic pneumothorax.

Authors:  Wenli Cai; June-Goo Lee; Karim Fikry; Hiroyuki Yoshida; Robert Novelline; Marc de Moya
Journal:  Comput Med Imaging Graph       Date:  2012-05-04       Impact factor: 4.790

8.  Using thoracic ultrasonography to accurately assess pneumothorax progression during positive pressure ventilation: a comparison with CT scanning.

Authors:  Nils Petter Oveland; Hans Morten Lossius; Kristian Wemmelund; Paal Johan Stokkeland; Lars Knudsen; Erik Sloth
Journal:  Chest       Date:  2013-02-01       Impact factor: 9.410

9.  Micropower impulse radar: a novel technology for rapid, real-time detection of pneumothorax.

Authors:  Phillip D Levy; Tracey Wielinski; Alan Greszler
Journal:  Emerg Med Int       Date:  2011-05-30       Impact factor: 1.112

10.  Automated quantification of pneumothorax in CT.

Authors:  Synho Do; Kristen Salvaggio; Supriya Gupta; Mannudeep Kalra; Nabeel U Ali; Homer Pien
Journal:  Comput Math Methods Med       Date:  2012-10-03       Impact factor: 2.238

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