Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

Abstract

The “Dynamic Chest Image Analysis” project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT) and nuclear medicine (NM) studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media

Development of pulmonary blood flow evaluation method with a dynamic flat-panel detector: quantitative correlation analysis with findings on perfusion scan

“…For determination of cardiac phase, the average pixel value was measured in the region of interest (ROI) located around the left ventricular wall throughout all frames, as shown in Fig. 2a [9,15]. Increases and decreases in pixel values were determined as the diastole phase and the systole phase, respectively (Fig.…”

“…However, it is extremely difficult to evaluate slight changes in X-ray translucency by visual observation. Many reports have indicated the feasibility of pulmonary densitometry for quantifying these changes [6][7][8][9]. These methods have not been adopted for clinical use because of technical limitations, such as poor image quality and a small field of view (FOV) [10].…”

Spectral analysis of non‐contrast fluoroscopy for evaluation of pulmonary perfusion: Feasibility and sensitivity testing with a phantom

“…Advancements in digital radiography and fluoroscopy with larger flat panel detectors have enabled a new field exploring this dynamic signal within the chest. 8,9 Recent work employing a "Dynamic Radiography" system with specialized equipment has shown promising results in identifying perfusion pathology correlating to V/Q and pulmonary angiography. [10][11][12][13][14][15][16] These methods exploit the signal in the lungs by one of two methods.…”

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

“…Furthermore, accurate interpretation requires a great deal of knowledge regarding respiratory physiology. There have been many reports demonstrating the feasibility of pulmonary densitometry [11][12][13][14][15]. These methods have not been adopted in clinical use because of technical limitations, such as poor image quality and small field of view (FOV) [16].…”