Determination of total lung capacity in disease from routine chest roentgenograms

“…When diagno�is was attempted, using only a posterior-anterior film on full inspiration, the accuracy of diagnosis was much less. The roentgenographic estimation of total lung capacity was discussed by Cobb (66). He found a high degree of correlation between roent genographic estimation of total lung capacity and a method using nitrogen clearance.…”

Section: Radiologic Studiesmentioning

confidence: 99%

Pulmonary Emphysema

Ebert¹

1956

Annu. Rev. Med.

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A review of the recent literature on pulmonary emphysema seems appro priate at the present time, at which there has been an increasing interest in this disease. In part this is a reflection of the general emphasis on diseases affecting the older age groups and in part it is a result of the recent surge of interest in pulmonary physiology on the part of clinicians. The pathology of pulmonary emphysema is uninspiring and the roentgenologic appearance of the lungs is not dramatic. The disease does produce many alterations in the physiology of the lungs and for this reason investigation of this aspect of the disease has been most fruitful.The description of pulmonary emphysema by Laennec (1), which still stands as a model of writing on clinical subjects, should be read by anyone interested in the disease. Excellent reviews have been written by Kountz & Alexander (2) and by Christie (3). PATHOLOGYThere have been relatively few recent contributions to the pathology of pulmonary emphysema. Hartcroft (4) has made a major contribution to the understanding of the microscopic anatomy of the disease. He points out the need for the fixation of the lungs in an inflated state and for the consideration of the alveoli as three-dimensional structures. The alveoli are arranged about the alveolar duct as open stalls are related to the central passage of a barn. In emphysema the alveoli are increased in diameter and decreased in depth. The alveolar duct is increased in size. The appearance of rupture of the alveolar walls is an artifact resulting from the plane of the section passing through the mouths of the alveoli.There have also been studies of the bronchioles and vascular tree in pulmonary emphysema. One of the characteristic features of emphysema is increased resistance to air flow in the bronchial tree. Spain & Kaufman (5) made a careful study of the bronchioles in pulmonary emphysema. They found the walls of the terminal bronchioles to be thickened. The walls showed fibrosis and often inflammatory cell infiltration. The authors believe that these changes in the bronchioles are primary and that the changes in the alveoli are secondary to bronchiolar obstruction. Cudkowicz & Armstrong (6) described narrowing and obliteration of the intrapulmonary bronchial arteries in pulmonary emphysema. This resulted from medial hyperplasia and intimal thickening. Anastomoses between the bronchial and pulmonary 1 The survey of the literature pertaining to this review was completed in March, 1955. 123 Annu. Rev. Med. 1956.7:123-140. Downloaded from www.annualreviews.org Access provided by Lancaster University -UK on 02/05/15. For personal use only. Quick links to online content Further ANNUAL REVIEWS

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“…In fact, this has been a research interest for a century, with the first paper appearing in 1918 ( 14) demonstrating the correlation of external measurements from CXR to the pulmonary function test (gas dilution technique). All such previous literature, investigating predictive equations, was either based on the use of planimetric techniques [15][16][17][18] , or made assumption of a given a geometry [19][20][21] , or required several manual linear measurements to estimate TLV from CXR. However, all these studies required manual measurements to estimate TLV and used small sample sizes, making it unclear whether the techniques could be generalized to other populations.…”

Section: Introductionmentioning

confidence: 99%

Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning

Sogancioglu¹,

Scholten²,

Boulogne³

et al. 2021

Preprint

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Total lung volume is an important quantitative biomarker and is used for the assessment of restrictive lung diseases. In this study, we investigate the performance of several deep-learning approaches for automated measurement of total lung volume from chest radiographs. 7621 posteroanterior and lateral view chest radiographs (CXR) were collected from patients with chest CT available. Similarly, 928 CXR studies were chosen from patients with pulmonary function test (PFT) results. The reference total lung volume was calculated from lung segmentation on CT or PFT data, respectively. This dataset was used to train deep-learning architectures to predict total lung volume from chest radiographs. The experiments were constructed in a step-wise fashion with increasing complexity to demonstrate the effect of training with CT-derived labels only and the sources of error. The optimal models were tested on 291 CXR studies with reference lung volume obtained from PFT. The optimal deep-learning regression model showed an MAE of 408 ml and an MAPE of 8.1% and Pearson's r = 0.92 using both frontal and lateral chest radiographs as input. CT-derived labels were useful for pre-training but optimal performance was obtained by fine-tuning the network with PFT-derived labels. We demonstrate, for the first time, that state-of-the-art deep learning solutions can accurately measure total lung volume from plain chest radiographs. The proposed model can be used to obtain total lung volume from routinely acquired chest radiographs at no additional cost and could be a useful tool to identify trends over time in patients referred regularly for chest x-rays.

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Determination of total lung capacity in disease from routine chest roentgenograms

Cited by 22 publications

References 16 publications

Measurement of Total Lung Capacity by a Roentgenography-Planimetry Method in Children 4–16 Years of Age

Measurement of Total Lung Capacity by a Roentgenography-Planimetry Method in Children 4–16 Years of Age

Pulmonary Emphysema

Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning

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