Preoperative assessment of parietal pleural invasion/adhesion of subpleural lung cancer: advantage of software-assisted analysis of 4-dimensional dynamic-ventilation computed tomography

Objective To evaluate the accuracy of four-dimensional (4D) dynamic-ventilation computed tomography (CT) scanning coupled with our novel image analysis software to diagnose parietal pleural invasion/adhesion of peripheral (subpleural) lung cancer. Methods Eighteen patients with subpleural lung cance...

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Bibliographic Details
Published in:European radiology 2019-10, Vol.29 (10), p.5247-5252
Main Authors: Yamashiro, Tsuneo, Moriya, Hiroshi, Tsubakimoto, Maho, Nagatani, Yukihiro, Kimoto, Tatsuya, Murayama, Sadayuki
Format: Article
Language:English
Subjects:
Accuracy
Adhesion
Adhesion tests
Aged
Aged, 80 and over
Chest
Color
Computed Tomography
Computer programs
Diagnostic Radiology
Diagnostic software
Diagnostic systems
Dimensional analysis
Female
Four-Dimensional Computed Tomography - methods
Humans
Image analysis
Image processing
Image reconstruction
Image resolution
Imaging
Internal Medicine
Interventional Radiology
Lung - pathology
Lung cancer
Lung Neoplasms - diagnostic imaging
Lung Neoplasms - pathology
Lung Neoplasms - surgery
Male
Medical imaging
Medicine
Medicine & Public Health
Middle Aged
Neoplasm Invasiveness
Neuroradiology
Pleural Neoplasms - diagnostic imaging
Pleural Neoplasms - pathology
Preoperative Care - methods
Radiology
Respiration
Retrospective Studies
ROC Curve
Sensitivity
Sensitivity and Specificity
Software
Surgery
Tissue Adhesions - diagnostic imaging
Tissue Adhesions - pathology
Ultrasound
Ventilation
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Summary:Objective To evaluate the accuracy of four-dimensional (4D) dynamic-ventilation computed tomography (CT) scanning coupled with our novel image analysis software to diagnose parietal pleural invasion/adhesion of peripheral (subpleural) lung cancer. Methods Eighteen patients with subpleural lung cancer underwent both 4D dynamic-ventilation CT during free breathing and conventional (static) chest CT during preoperative assessment. The absence of parietal pleural invasion/adhesion was surgically confirmed in 13 patients, while the presence of parietal pleural invasion/adhesion was confirmed in 5 patients. Two chest radiologists, who were blinded to patient status, cooperatively evaluated the presence of pleural invasion/adhesion using two different imaging modalities: (i) conventional high-resolution CT images, reconstructed in the axial, coronal, and sagittal directions, and (ii) 4D dynamic-ventilation CT images combined with a color map created by image analysis software to visualize movement differences between the lung surface and chest wall. Parameters of diagnostic accuracy were assessed, including a receiver operating characteristic analysis. Results Software-assisted 4D dynamic-ventilation CT images achieved perfect diagnostic accuracy for pleural invasion/adhesion (sensitivity, 100%; specificity, 100%; area under the curve [AUC], 1.000) compared to conventional chest CT (sensitivity, 60%; specificity, 77%; AUC, 0.846). Conclusion Software-assisted 4D dynamic-ventilation CT can be considered as a novel imaging approach for accurate preoperative analysis of pleural invasion/adhesion of peripheral lung cancer. Key Points • 4D dynamic-ventilation CT can correctly assess parietal pleural invasion/adhesion of peripheral lung cancer. • A unique color map clearly demonstrates parietal pleural invasion/adhesion. • Our technique can be expanded to diagnose “benign” pleural adhesions for safer thoracoscopic surgery.
ISSN:0938-7994
1432-1084
DOI:10.1007/s00330-019-06131-w