Design and Evaluation of Mobile X-ray for Rapid and Accurate Diagnosis of Thoracic Disease

Thoracic Diseases

Computed tomography (CT) is the most accurate test for evaluating patients with thoracic disease. However, access to CT is limited due to long wait times and for the sickest patients in Hospital who cannot be transported from the ward to the CT scanner. The investigators propose to modify a standard X-ray unit to provide more detailed information of the chest such that a CT scan is not required for all patients.

Dual-energy (DE) imaging consists of acquiring paired low and high-energy x-ray images. The use of DE to improve radiological contrast was first described by Jacobson et al in 1958; followed by Mistretta et al and Alvarez and Macovski in the mid-1970s. With the advent of new digital X-ray detectors that provide high dose efficiency and rapid readout of digital X-ray projections, there has been renewed interest in using DE x-ray imaging for lung nodule detection. More recently, portable x-ray detectors have made bedside DE imaging possible. Jabri et. al. presented a portable DE system with novel respiratory and cardiac gating, and Hoggarth et. al. investigated the potential for DE subtraction in improving the visualization of lung tumors while performing image-guided radiotherapy. The investigators group is experienced in investigating DE for lung nodule detection, this theoretical framework was instrumental in optimizing a clinical prototype for high-performance DE chest X-ray. It identified optimal DE image acquisition and decomposition techniques, and validated the approach in comparison to human observer performance. The analysis further demonstrated that - given a high-performance flat plate detector, optimal acquisition and decomposition - DE chest X-ray is possible at the same dose as conventional computer radiography (CR) and digital radiography (DR) chest X-ray, while significantly improving conspicuity of subtle lung nodules by the reduction of overlying background noise. The DE work undertaken by our group is unique in terms of providing a clear theoretical framework for optimizing a clinical prototype for best performance in terms of image quality and patient exposure to ionizing radiation.

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