Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study

PurposeDecreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values.MethodsSequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6).ResultsIn normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes.ConclusionsVentilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis.

[1]  Andrea Aliverti,et al.  Quantification of trapped gas with CT and 3 He MR imaging in a porcine model of isolated airway obstruction. , 2009, Radiology.

[2]  Seymour Sprayregen,et al.  The current and continuing important role of ventilation-perfusion scintigraphy in evaluating patients with suspected pulmonary embolism. , 2008, Seminars in nuclear medicine.

[3]  Sumiaki Matsumoto,et al.  Dynamic oxygen-enhanced MRI versus quantitative CT: pulmonary functional loss assessment and clinical stage classification of smoking-related COPD. , 2008, AJR. American journal of roentgenology.

[4]  Klaus Zöphel,et al.  Ventilation/perfusion lung scintigraphy: what is still needed? A review considering technetium-99m-labeled macro-aggregates of albumin , 2009, Annals of nuclear medicine.

[5]  K. Doi,et al.  Image feature analysis for computer-aided diagnosis: accurate determination of ribcage boundary in chest radiographs. , 1995, Medical physics.

[6]  田中 利恵 Breathing chest radiography using a dynamic flat-panel detector combined with computer analysis , 2006 .

[7]  Nobuhiko Hata,et al.  Lung motion and volume measurement by dynamic 3D MRI using a 128-channel receiver coil. , 2009, Academic radiology.

[8]  Robert A. Novelline,et al.  Fundamentals of Radiology: Fourth edition , 1988 .

[9]  M Intaglietta,et al.  Pulmonary ventilation and perfusion during graded pulmonary arterial occlusion. , 1973, Journal of applied physiology.

[10]  Rie Tanaka,et al.  Evaluation of Pulmonary Function Using Breathing Chest Radiography With a Dynamic Flat Panel Detector: Primary Results in Pulmonary Diseases , 2006, Investigative radiology.

[11]  Hiroto Hatabu,et al.  Quantitative analysis of the velocity and synchronicity of diaphragmatic motion: dynamic MRI in different postures. , 2006, Magnetic resonance imaging.

[12]  Bürsch Jh,et al.  Densitometric studies in digital subtraction angiography: assessment of pulmonary and myocardial perfusion. , 1985 .

[13]  Jonathan G Goldin,et al.  Imaging the lungs in patients with pulmonary emphysema. , 2009, Journal of thoracic imaging.

[14]  Rie Tanaka,et al.  Sequential dual-energy subtraction technique with a dynamic flat-panel detector (FPD): primary study for image-guided radiation therapy (IGRT) , 2008, Radiological physics and technology.

[15]  N R Silverman Clinical video-densitometry. Pulmonary ventilation analysis. , 1972, Radiology.

[16]  J. Bürsch,et al.  Densitometric studies in digital subtraction angiography: assessment of pulmonary and myocardial perfusion. , 1985, Herz.

[17]  M. Kallergi,et al.  Improved method for automatic identification of lung regions on chest radiographs. , 2001 .

[18]  Rie Tanaka,et al.  [Pulmonary functional diagnostic imaging using a dynamic flat-panel detector: comparison with findings in pulmonary scintigraphy]. , 2009, Nihon Hoshasen Gijutsu Gakkai zasshi.

[19]  Masayuki Suzuki,et al.  Computerized Methods for Determining Respiratory Phase on Dynamic Chest Radiographs Obtained by a Dynamic Flat-Panel Detector (FPD) System , 2004, Journal of Digital Imaging.

[20]  Jiang Du,et al.  Imaging of lung ventilation and respiratory dynamics in a single ventilation cycle using hyperpolarized He‐3 MRI , 2007, Journal of magnetic resonance imaging : JMRI.

[21]  M Intaglietta,et al.  Determination of pulmonary pulsatile perfusion by fluoroscopic videodensitometry. , 1972, Journal of applied physiology.

[22]  Robert A. Novelline,et al.  Fundamentals of Radiology , 1997 .

[23]  Jianming Liang,et al.  Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging , 2003, EURASIP J. Adv. Signal Process..

[24]  K Doi,et al.  Basic imaging properties of a large image intensifier-TV digital chest radiographic system. , 1987, Investigative radiology.

[25]  Masayuki Suzuki,et al.  Detectability of Regional Lung Ventilation with Flat-panel Detector-based Dynamic Radiography , 2008, Journal of Digital Imaging.