Pulmonary Function Diagnosis Based on Respiratory Changes in Lung Density With Dynamic Flat-Panel Detector Imaging: An Animal-Based Study

Clinical utility of dynamic chest radiography as an auxiliary tool for atrial fibrillation detection in heart failure: a pilot study

BACKGROUND

Dynamic chest radiography (DCR) can estimate haemodynamic parameters in patients with heart failure (HF). Atrial fibrillation (AF) often coexists with HF; however, owing to its sometimes paroxysmal nature and minimal or absent symptoms, many patients with AF remain undiagnosed. Additional tools for AF diagnosis may be beneficial; therefore, we evaluated the ability of DCR to distinguish patients with HF in sinus rhythm (SR) from those with AF.

METHODS

In this small-sample pilot study, 20 patients with HF (median age, 67 years; males, 85%) underwent 12-lead electrocardiography and DCR on the same day. Aortic arch (Ao), right atrial (RA), right and left pulmonary artery (PA), and left ventricular (LV) apex pixel values (PVs) were measured. Seventeen patients were in SR and three demonstrated AF on 12-lead electrocardiography before DCR.

RESULTS

The PV and PV change rate waveforms of the Ao, RA, PAs, and LV apex were regular in SR and irregular with AF. The difference between patients in SR and those with AF was particularly clear in the LV apex PV change rate waveforms. In addition, the heart rates (HRs) of patients in SR and with AF could be calculated from the PV change rate waveforms and were similar to those calculated by 12-lead electrocardiography.

CONCLUSIONS

DCR can detect AF in patients with HF and may be able to infer HR.

Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases

ABSTRACT

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally advanced the field of thoracic imaging. This review summarizes key developments in imaging modalities, computational tools, and clinical applications, highlighting major breakthroughs in thoracic diseases-lung cancer, pulmonary nodules, interstitial lung disease (ILD), chronic obstructive pulmonary disease (COPD), COVID-19 pneumonia, and pulmonary embolism-and outlining future directions.Artificial intelligence (AI)-driven computer-aided detection systems and radiomic analyses have notably improved the detection and classification of pulmonary nodules, while photon-counting detector CT (PCD-CT) and low-field MRI offer enhanced resolution or radiation-free strategies. For lung cancer, CT texture analysis and perfusion imaging refine prognostication and therapy planning. ILD assessment benefits from automated diagnostic tools and innovative imaging techniques, such as PCD-CT and functional MRI, which reduce the need for invasive diagnostic procedures while improving accuracy. In COPD, dual-energy CT-based ventilation/perfusion assessment and dark-field radiography enable earlier detection and staging of emphysema, complemented by deep learning approaches for improved quantification. COVID-19 research has underscored the clinical utility of chest CT, radiographs, and AI-based algorithms for rapid triage, disease severity evaluation, and follow-up. Furthermore, tuberculosis remains a significant global health concern, highlighting the importance of AI-assisted chest radiography for early detection and management. Meanwhile, advances in CT pulmonary angiography, including dual-energy reconstructions, allow more sensitive detection of pulmonary emboli.Collectively, these innovations demonstrate the power of merging novel imaging technologies, quantitative functional analysis, and AI-driven tools to transform thoracic disease management. Ongoing progress promises more precise and personalized diagnostic and therapeutic strategies for diverse thoracic diseases.

Ability of dynamic chest radiography to identify left ventricular systolic dysfunction in heart failure

Dynamic chest radiography (DCR) can estimate haemodynamic parameters in heart failure (HF). However, no studies have evaluated its ability to determine cardiac systolic function in HF. This experimental study investigates the correlation between left ventricular (LV) ejection fraction (LVEF) and DCR image parameters in HF. Ninety-one patients with acute HF (median age, 58 years; males, 75%) (cardiologist diagnosis using the Framingham criteria) underwent DCR and transthoracic echocardiography after treatment for the uncompensated phase of HF. The LV apex pixel value (PV) change was measured by DCR. Correlations between the PV change and LVEF, as well as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of DCR, were evaluated. LVEF and LV apex PV change were correlated in all patients (R = 0.428, P < 0.001) and in patients with LVEF < 50% (n = 38; R = 0.355, P = 0.029), < 40% (n = 31; R = 0.343, P = 0.059), and < 30% (n = 23; R = 0.321, P = 0.135). There was no significant correlation for patients with LVEF ≥ 50% (n = 53; R = - 0.004, P = 0.980). The LV apex PV change rate cutoff values for identifying LVEF < 50%, < 40%, and < 30% were 9.3% (AUC: 0.761, sensitivity: 0.698, specificity: 0.789, P < 0.001), 5.5% (AUC: 0.765, sensitivity: 0.883, specificity: 0.645, P < 0.001), and 5.5% (AUC: 0.767, sensitivity: 0.838, specificity: 0.696, P < 0.001), respectively. DCR may be useful to identify LV systolic dysfunction based on LVEF in acute HF.

Assessment of pulmonary function in COPD patients using dynamic digital radiography: A novel approach utilizing lung signal intensity changes during forced breathing

Objectives

To investigate the association of lung signal intensity changes during forced breathing using dynamic digital radiography (DDR) with pulmonary function and disease severity in patients with chronic obstructive pulmonary disease (COPD).

Methods

This retrospective study included 46 healthy subjects and 33 COPD patients who underwent posteroanterior chest DDR examination. We collected raw signal intensity and gray-scale image data. The lung contour was extracted on the gray-scale images using our previously developed automated lung field tracking system and calculated the average of signal intensity values within the extracted lung contour on gray-scale images. Lung signal intensity changes were quantified as SImax/SImin, representing the maximum ratio of the average signal intensity in the inspiratory phase to that in the expiratory phase. We investigated the correlation between SImax/SImin and pulmonary function parameters, and differences in SImax/SImin by disease severity.

Results

SImax/SImin showed the highest correlation with VC (rs = 0.54, P < 0.0001), followed by FEV1 (rs = 0.44, P < 0.0001), both of which are key indicators of COPD pathophysiology. In a multivariate linear regression analysis adjusted for confounding factors, SImax/SImin was significantly lower in the severe COPD group compared to the normal group (P = 0.0004) and mild COPD group (P=0.0022), suggesting its potential usefulness in assessing COPD severity.

Conclusion

This study suggests that the signal intensity changes of lung fields during forced breathing using DDR reflect the pathophysiology of COPD and can be a useful index in assessing pulmonary function in COPD patients, potentially improving COPD diagnosis and management.

Current advances in pulmonary functional imaging

Recent advances in imaging analysis have enabled evaluation of ventilation and perfusion in specific regions by chest computed tomography (CT) and magnetic resonance imaging (MRI), in addition to modalities including dynamic chest radiography, scintigraphy, positron emission tomography (PET), ultrasound, and electrical impedance tomography (EIT). In this review, an overview of current functional imaging techniques is provided for each modality. Advances in chest CT have allowed for the analysis of local volume changes and small airway disease in addition to emphysema, using the Jacobian determinant and parametric response mapping with inspiratory and expiratory images. Airway analysis can reveal characteristics of airway lesions in chronic obstructive pulmonary disease (COPD) and bronchial asthma, and the contribution of dysanapsis to obstructive diseases. Chest CT is also employed to measure pulmonary blood vessels, interstitial lung abnormalities, and mediastinal and chest wall components including skeletal muscle and bone. Dynamic CT can visualize lung deformation in respective portions. Pulmonary MRI has been developed for the estimation of lung ventilation and perfusion, mainly using hyperpolarized 129Xe. Oxygen-enhanced and proton-based MRI, without a polarizer, has potential clinical applications. Dynamic chest radiography is gaining traction in Japan for ventilation and perfusion analysis. Single photon emission CT can be used to assess ventilation-perfusion (V˙/Q˙) mismatch in pulmonary vascular diseases and COPD. PET/CT V˙/Q˙ imaging has also been demonstrated using "Galligas". Both ultrasound and EIT can detect pulmonary edema caused by acute respiratory distress syndrome. Familiarity with these functional imaging techniques will enable clinicians to utilize these systems in clinical practice.

Dynamic chest radiography as a novel minimally invasive hemodynamic imaging method in patients with heart failure

PURPOSE

Dynamic chest radiography allows for non-invasive cardiopulmonary blood flow assessment. However, data on its use for heart failure hemodynamic assessment are scarce. We utilized dynamic chest radiography to estimate heart failure hemodynamics.

METHOD

Twenty heart failure patients (median age, 67 years; 17 men) underwent dynamic chest radiography and right heart catheterization. The analyzed images were 16-bit images (grayscale range: 0-65,535). Right atrial, right pulmonary artery, and left ventricular apex pixel values (average of the grayscale values of all pixels within a region of interest) were measured. The correlations of the minimum, maximum, mean, amount of change, and rate of change in pixel values with right atrial pressure, pulmonary artery pressure, pulmonary artery wedge pressure, and cardiac index were analyzed.

RESULTS

The mean right atrial pixel value and mean right atrial pressure (R = -0.576, P = 0.008), mean right pulmonary artery pixel value and mean pulmonary artery pressure (R = -0.546, P = 0.013), and left ventricular apex pixel value change rate and mean pulmonary artery wedge pressure (R = -0.664, P = 0.001) or cardiac index (R = 0.606, P = 0.005) were correlated. The left ventricular apex pixel value change rate identified low cardiac index (area under the curve, 0.792; 95% confidence interval, 0.590-0.993; P = 0.031) and low cardiac index with high pulmonary artery wedge pressure (area under the curve, 0.902; 95% confidence interval, 0.000-1.000; P = 0.030).

CONCLUSIONS

Dynamic chest radiography is a minimally invasive tool for heart failure hemodynamic assessment.

Quantitative analysis of changes in lung density by dynamic chest radiography in association with CT values: a virtual imaging study and initial clinical corroboration

Dynamic chest radiography (DCR) identifies pulmonary impairments as decreased changes in radiographic lung density during respiration (Δpixel values), but not as scaled/standardized computed tomography (CT) values. Quantitative analysis correlated with CT values is beneficial for a better understanding of Δpixel values in DCR-based assessment of pulmonary function. The present study aimed to correlate Δpixel values from DCR with changes in CT values during respiration (ΔCT values) through a computer-based phantom study. A total of 20 four-dimensional computational phantoms during forced breathing were created to simulate both CT and projection images of the same virtual patients. The Δpixel and ΔCT values of the lung fields were correlated on a regression line, and the inclination was statistically evaluated to determine whether there were significant differences among physical types, sex, and breathing methods. The resulting conversion expression was also assessed in the DCR images of 37 patients. The resulting Δpixel values for 30/37 (81%) real patients, 6/7 (86%) normal controls, and 24/30 (80%) chronic obstructive pulmonary disorder patients were within the range of ΔCT values ± standard deviation (SD) reported in a previous study. In addition, no significant differences were detected for each condition of thoracic breathing, suggesting that the same regression line inclination values measured across the entire lung can be used for the conversion of Δpixel values, providing a quantitative analysis that can be correlated with ΔCT values. The developed conversion expression may be helpful for improving the understanding of respiratory changes using radiographic lung densities from DCR-based assessments of pulmonary function.

[Paradigm Shift in Respiratory Diagnosis: Current Status and Future Prospects of Dynamic Chest Radiography]

Dynamic chest radiography (DCR) is a flat-panel detector (FPD) -based functional X-ray imaging, which is performed as an additional examination in chest radiography. The large field of view of FPDs permits real-time observation of motion/kinetic findings on the entire lungs, right and left diaphragm, ribs, and chest wall; heart wall motions; respiratory changes in lung density; and diameter of the intrathoracic trachea. Since the dynamic FPDs had been developed in the early 2000s, we focused on the potential of dynamic FPDs for functional X-ray imaging and have launched a research project for the development of an imaging protocol and digital image-processing techniques for the DCR. The quantitative analysis of motion/kinetic findings is helpful for a better understanding of pulmonary function, because the interpretation of dynamic chest radiographs is challenging and time-consuming for radiologists, pulmonologists, and surgeons. Recent clinical studies have demonstrated the usefulness of DCR combined with the digital image processing techniques for the evaluation of pulmonary function and circulation. Especially, there is a major concern in color-mapping images based on dynamic changes in radiographic lung density, where pulmonary impairments can be detected as color defects, even without the use of contrast media or radioactive medicine. Dynamic chest radiography is now commercially available for the use in general X-ray room and therefore can be deployed as a simple and rapid means of functional imaging in both routine and emergency medicine. This review article describes the current status and future prospects of DCR, which might bring a paradigm shift in respiratory diagnosis.

Dynamic chest radiography: clinical validation of ventilation and perfusion metrics derived from changes in radiographic lung density compared to nuclear medicine imaging

Background

Dynamic chest radiography (DCR) is a type of non-contrast-enhanced functional lung imaging with a dynamic flat-panel detector (FPD). This study aimed to assess the clinical significance of ventilation and perfusion metrics derived from changes in radiographic lung density on DCR in comparison to nuclear medicine imaging-derived metrics.

Methods

DCR images of 42 lung cancer patients were sequentially obtained during respiration using a dynamic FPD imaging system. For each subdivided lung region, the maximum change in the averaged pixel value (Δ_max), i.e., lung density, due to respiration and cardiac function was calculated, and the percentage of Δ_max relative to the total of all lung regions (Δ_max%) was computed for ventilation and perfusion, respectively. The Δ_max% was compared to the accumulation of radioactive agents such as Tc-99m gas and Tc-99m macro-aggregated albumin (radioactive agents%) on ventilation and perfusion scans in the subdivided lung regions, by Spearman's correlation coefficient (r) and the Dice similarity coefficients (DSC). To facilitate visual evaluation, Δ_max% was visualized as a color scaling, where larger Δ_max values were indicated by higher color intensities.

Results

We found a moderate correlation between Δ_max% and radioactive agents% on ventilation and perfusion scans, with perfusion metrics (r=0.57, P<0.001) showing a higher correlation than ventilation metrics (r=0.53, P<0.001). We also found a good or strong correlation (r≥0.5) in 80.9% (34/42) of patients for perfusion metrics (r=0.60±0.16) and in 52.4% (22/42) of patients for ventilation metrics (r=0.53±0.16). DSC indicated a moderate correlation for both metrics. Decreased pulmonary function was observed in the form of reduced color intensities on color-mapping images.

Conclusions

DCR-derived ventilation and perfusion metrics correlated reasonably well with nuclear medicine imaging findings in lung subdivisions, suggesting that DCR could provide useful information on pulmonary function without the use of radioactive contrast agents.

Vector-Field dynamic X-ray (VF-DXR) using Optical Flow Method

OBJECTIVES

To explore the feasibility of Vector-Field DXR (VF-DXR) using optical flow method (OFM).

METHODS

Five healthy volunteers and five COPD patients were studied. DXR was performed in the standing position using a prototype X-ray system (Konica Minolta Inc., Tokyo, Japan). During the examination, participants took several tidal breaths and one forced breath. DXR image file was converted to the videos with different frames per second (fps): 15 fps, 7.5 fps, five fps, three fps, and 1.5 fps. Pixel-value gradient was calculated by the serial change of pixel value, which was subsequently converted mathematically to motion vector using OFM. Color-coding map and vector projection into horizontal and vertical components were also tested.

RESULTS

Dynamic motion of lung and thorax was clearly visualized using VF-DXR with an optimal frame rate of 5 fps. Color-coding map and vector projection into horizontal and vertical components were also presented. VF-DXR technique was also applied in COPD patients.

CONCLUSION

The feasibility of VF-DXR was demonstrated with small number of healthy subjects and COPD patients.

ADVANCES IN KNOWLEDGE

A new Vector-Field Dynamic X-ray (VF-DXR) technique is feasible for dynamic visualization of lung, diaphragms, thoracic cage, and cardiac contour.

Dynamic Chest X-Ray Using a Flat-Panel Detector System: Technique and Applications

Dynamic X-ray (DXR) is a functional imaging technique that uses sequential images obtained by a flat-panel detector (FPD). This article aims to describe the mechanism of DXR and the analysis methods used as well as review the clinical evidence for its use. DXR analyzes dynamic changes on the basis of X-ray translucency and can be used for analysis of diaphragmatic kinetics, ventilation, and lung perfusion. It offers many advantages such as a high temporal resolution and flexibility in body positioning. Many clinical studies have reported the feasibility of DXR and its characteristic findings in pulmonary diseases. DXR may serve as an alternative to pulmonary function tests in patients requiring contact inhibition, including patients with suspected or confirmed coronavirus disease 2019 or other infectious diseases. Thus, DXR has a great potential to play an important role in the clinical setting. Further investigations are needed to utilize DXR more effectively and to establish it as a valuable diagnostic tool.

Comparison of dynamic flat-panel detector-based chest radiography with nuclear medicine ventilation-perfusion imaging for the evaluation of pulmonary function: A clinical validation study

PURPOSE

Dynamic chest radiography (DCR) is a flat-panel detector (FPD)-based functional lung imaging technique capable of measuring temporal changes in radiographic lung density due to ventilation and perfusion. The aim of this study was to determine the diagnostic performance of DCR in the evaluation of pulmonary function based on changes in radiographic lung density compared to nuclear medicine lung scans.

METHODS

This study included 53 patients with pulmonary disease who underwent DCR and nuclear medicine imaging at our institution. Dynamic chest radiography was conducted using a dynamic FPD system to obtain sequential chest radiographs during one breathing cycle. The maximum change in the average pixel value (Δ_max ) was measured, and the percentage ofΔ_max in each lung region, calculated relative to the sum of all lung regions (Δ_max %), was calculated for each factor (ventilation and perfusion). The Δ_max % was compared with the accumulation of radioactive agents (radioactive agents%) on ventilation and perfusion scans in each lung and lung region using correlation coefficients and scatter plots. The ratio of ventilation to perfusion Δ_max % was calculated and compared with nuclear medicine ventilation-perfusion (V/Q) findings in terms of sensitivity and specificity for V/Q mismatch in each lung region.

RESULTS

There was a high correlation between Δ_max % and radioactive agents% for each lung (Ventilation: r = 0.81, perfusion: r = 0.87). However, correlation coefficients were lower (0.37 to 0.80) when comparing individual lung regions, with the upper lung regions showing the lowest correlation coefficients. The sensitivity and specificity of DCR for V/Q mismatch were 63.3% (19/30) and 60.1% (173/288), respectively. Motion artifacts occasionally increased Δ_max %, resulting in false negatives.

CONCLUSIONS

Ventilation and perfusion Δ_max % correlated reasonably with radioactive agents% on ventilation and perfusion scans. Although the regional correlations were lower and the detection performance for V/Q mismatch was not enough for clinical use at the moment, these results suggest the potential for DCR to be used as a functional imaging modality that can be performed without the use of radioactive contrast agents. Further technical improvement is required for the implementation of DCR-based V/Q studies.

The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics

Objectives

To assess the clinical severity of COVID-19 pneumonia using qualitative and/or quantitative chest CT indicators and identify the CT characteristics of critical cases.

Materials and Methods

Fifty-one patients with COVID-19 pneumonia including ordinary cases (group A, n=12), severe cases(group B, n=15) and critical cases (group C, n=24) were retrospectively enrolled. The qualitative and quantitative indicators from chest CT were recorded and compared using Fisher's exact test, one-way ANOVA, Kruskal-Wallis H test and receiver operating characteristic analysis.

Results

Depending on the severity of the disease, the number of involved lung segments and lobes, the frequencies of consolidation, crazy-paving pattern and air bronchogram increased in more severe cases. Qualitative indicators including total severity score for the whole lung and total score for crazy-paving and consolidation could distinguish groups B and C from A(69% sensitivity, 83% specificity and 73% accuracy) but were similar between group B and group C. Combined qualitative and quantitative indicators could distinguish these three groups with high sensitivity(B+C vs. A, 90%; C vs. B, 92%), specificity(100%, 87%) and accuracy(92%, 90%). Critical cases had higher total severity score(>10) and higher total score for crazy-paving and consolidation(>4) than ordinary cases, and had higher mean lung density(>-779HU) and full width at half maximum(>128HU) but lower relative volume of normal lung density(≦50%) than ordinary/severe cases. In our critical cases, eight patients with relative volume of normal lung density smaller than 40% received mechanical ventilation for supportive treatment, and two of them had died.

Conclusion

A rapid, accurate severity assessment of COVID-19 pneumonia based on chest CT would be feasible and could provide help for making management decisions, especially for the critical cases.

Evaluation of intrathoracic tracheal narrowing in patients with obstructive ventilatory impairment using dynamic chest radiography: A preliminary study

PURPOSE

Dynamic chest radiography (DCR) can observe the dynamic structure of the chest using continuous pulse fluoroscopy irradiation. However, its usefulness remains largely undetermined. The purpose of this study was to examine the relationship between changes in tracheal diameter during deep breathing and obstructive ventilation disorders using DCR.

METHOD

Twelve participants with obstructive ventilatory impairment and 28 with normal pulmonary function underwent DCR during one cycle of deep inspiration and expiration. Three evaluators blinded to pulmonary function test results independently measured lateral diameters of the trachea in DCR images to determine whether there was a difference in the amount of change in tracheal diameter depending on the presence or absence of pulmonary dysfunction. Tracheal narrowing was defined as a decrease in the lateral tracheal diameter of more than 30 %. Participants were divided into a narrowing group and a non-narrowing group, and it was examined whether each group correlated with values of pulmonary function tests.

RESULTS

Tracheal diameter was significantly narrowed in subjects with obstructive ventilatory impairment compared to normal subjects (P <  0.01). When subjects were divided into narrowing (tracheal narrowing rate [TNr] = 41.5 ± 7.7 %, n = 9) and non-narrowing groups (TNr = 9.1 ± 7.0 %, n = 31, p < 0.01), FEV1%-G, and %V25 were significantly smaller in the narrowing group than in the non-narrowing group (p < 0.01).

CONCLUSIONS

Changes in tracheal diameter during deep breathing were easily evaluated using DCR. DCR may, therefore, be useful for evaluating obstructive ventilation disorders.

Dynamic-Ventilatory Digital Radiography in Air Flow Limitation: A Change in Lung Area Reflects Air Trapping

OBJECTIVE

The aim of this study was to determine the utility of dynamic-ventilatory digital radiography (DR) for pulmonary function assessment in patients with airflow limitation.

METHODS

One hundred and eighteen patients with airflow limitation (72 patients with lung cancer before surgery, 35 patients with chronic obstructive pulmonary disease [COPD], 6 patients with asthma, and 5 patients with asthma-COPD overlap syndrome) were assessed with dynamic-ventilatory DR. The patients were instructed to inhale and exhale slowly and maximally. Sequential chest X-ray images were captured in 15 frames per second using a dynamic flat-panel imaging system. The relationship between the lung area and the rate of change in the lung area due to respiratory motion with respect to pulmonary function was analyzed.

RESULTS

The rate of change in the lung area from maximum inspiration to maximum expiration (Rs ratio) was associated with the RV/TLC ratio (r = 0.48, p < 0.01) and the percentage of the predicted FEV1 (r = -0.33, p < 0.01) in patients with airflow limitations. The Rs ratio also decreased in an FEV1-dependent manner.

CONCLUSION

The rate of change in the lung area due to respiratory motion evaluated with dynamic DR reflects air trapping. Dynamic DR is a potential tool for the comprehensive assessment of pulmonary function in patients with COPD.