R. Van Metter

Optimization of image acquisition techniques for dual-energy imaging of the chest

Experimental and theoretical studies were conducted to determine optimal acquisition techniques for a prototype dual-energy (DE) chest imaging system. Technique factors investigated included the selection of added x-ray filtration, kVp pair, and the allocation of dose between low- and high-energy projections, with total dose equal to or less than that of a conventional chest radiograph. Optima were computed to maximize lung nodule detectability as characterized by the signal-difference-to-noise ratio (SDNR) in DE chest images. Optimal beam filtration was determined by cascaded systems analysis of DE image SDNR for filter selections across the periodic table (Z(filter) = 1-92), demonstrating the importance of differential filtration between low- and high-kVp projections and suggesting optimal high-kVp filters in the range Z(filter) = 25-50. For example, added filtration of approximately 2.1 mm Cu, approximately 1.2 mm Zr, approximately 0.7 mm Mo, and approximately 0.6 mm Ag to the high-kVp beam provided optimal (and nearly equivalent) soft-tissue SDNR. Optimal kVp pair and dose allocation were investigated using a chest phantom presenting simulated lung nodules and ribs for thin, average, and thick body habitus. Low- and high-energy techniques ranged from 60-90 kVp and 120-150 kVp, respectively, with peak soft-tissue SDNR achieved at [60/120] kVp for all patient thicknesses and all levels of imaging dose. A strong dependence on the kVp of the low-energy projection was observed. Optimal allocation of dose between low- and high-energy projections was such that approximately 30% of the total dose was delivered by the low-kVp projection, exhibiting a fairly weak dependence on kVp pair and dose. The results have guided the implementation of a prototype DE imaging system for imaging trials in early-stage lung nodule detection and diagnosis.

Optimal kVp selection for dual-energy imaging of the chest: Evaluation by task-specific observer preference tests

Human observer performance tests were conducted to identify optimal imaging techniques in dual-energy (DE) imaging of the chest with respect to a variety of visualization tasks for soft and bony tissue. Specifically, the effect of kVp selection in low- and high-energy projection pairs was investigated. DE images of an anthropomorphic chest phantom formed the basis for observer studies, decomposed from low-energy and high-energy projections in the range 60-90 kVp and 120-150 kVp, respectively, with total dose for the DE image equivalent to that of a single chest radiograph. Five expert radiologists participated in observer preference tests to evaluate differences in image quality among the DE images. For visualization of soft-tissue structures in the lung, the [60/130] kVp pair provided optimal image quality, whereas [60/140] kVp proved optimal for delineation of the descending aorta in the retrocardiac region. Such soft-tissue detectability tasks exhibited a strong dependence on the low-kVp selection (with 60 kVp providing maximum soft-tissue conspicuity) and a weaker dependence on the high-kVp selection (typically highest at 130-140 kVp). Qualitative examination of DE bone-only images suggests optimal bony visualization at a similar technique, viz., [60/140] kVp. Observer preference was largely consistent with quantitative analysis of contrast, noise, and contrast-to-noise ratio, with subtle differences likely related to the imaging task and spatial-frequency characteristics of the noise. Observer preference tests offered practical, semiquantitative identification of optimal, task-specific imaging techniques and will provide useful guidance toward clinical implementation of high-performance DE imaging systems.

Dual-energy imaging of the chest: optimization of image acquisition techniques for the 'bone-only' image.

Experiments were conducted to determine optimal acquisition techniques for bone image decompositions for a prototype dual-energy (DE) imaging system. Technique parameters included kVp pair (denoted [kVp(L)/kVp(H)]) and dose allocation (the proportion of dose in low- and high-energy projections), each optimized to provide maximum signal difference-to-noise ratio in DE images. Experiments involved a chest phantom representing an average patient size and containing simulated ribs and lung nodules. Low- and high-energy kVp were varied from 60-90 and 120-150 kVp, respectively. The optimal kVp pair was determined to be [60/130] kVp, with image quality showing a strong dependence on low-kVp selection. Optimal dose allocation was approximately 0.5-i.e., an equal dose imparted by the low- and high-energy projections. The results complement earlier studies of optimal DE soft-tissue image acquisition, with differences attributed to the specific imaging task. Together, the results help to guide the development and implementation of high-performance DE imaging systems, with applications including lung nodule detection and diagnosis, pneumothorax identification, and musculoskeletal imaging (e.g., discrimination of rib fractures from metastasis).

Multiscale deformable registration for dual-energy x-ray imaging

Dual-energy (DE) imaging of the chest improves the conspicuity of subtle lung nodules through the removal of overlying anatomical noise. Recent work has shown double-shot DE imaging (i.e., successive acquisition of low- and high-energy projections) to provide detective quantum efficiency, spectral separation (and therefore contrast), and radiation dose superior to single-shot DE imaging configurations (e.g., with a CR cassette). However, the temporal separation between high-energy (HE) and low-energy (LE) image acquisition can result in motion artifacts in the DE images, reducing image quality and diminishing diagnostic performance. This has motivated the development of a deformable registration technique that aligns the HE image onto the LE image before DE decomposition. The algorithm reported here operates in multiple passes at progressively smaller scales and increasing resolution. The first pass addresses large-scale motion by means of mutual information optimization, while successive passes (2-4) correct misregistration at finer scales by means of normalized cross correlation. Evaluation of registration performance in 129 patients imaged using an experimental DE imaging prototype demonstrated a statistically significant improvement in image alignment. Specific to the cardiac region, the registration algorithm was found to outperform a simple cardiac-gating system designed to trigger both HE and LE exposures during diastole. Modulation transfer function (MTF) analysis reveals additional advantages in DE image quality in terms of noise reduction and edge enhancement. This algorithm could offer an important tool in enhancing DE image quality and potentially improving diagnostic performance.

Development and implementation of a high-performance, cardiac-gated dual-energy imaging system

Mounting evidence suggests that the superposition of anatomical clutter in a projection radiograph poses a major impediment to the detectability of subtle lung nodules. Through decomposition of projections acquired at multiple kVp, dual-energy (DE) imaging offers to dramatically improve lung nodule detectability and, in part through quantitation of nodule calcification, increase specificity in nodule characterization. The development of a high-performance DE chest imaging system is reported, with design and implementation guided by fundamental imaging performance metrics. A diagnostic chest stand (Kodak RVG 5100 digital radiography system) provided the basic platform, modified to include: (i) a filter wheel, (ii) a flat-panel detector (Trixell Pixium 4600), (iii) a computer control and monitoring system for cardiac-gated acquisition, and (iv) DE image decomposition and display. Computational and experimental studies of imaging performance guided optimization of key acquisition technique parameters, including: x-ray filtration, allocation of dose between low- and high-energy projections, and kVp selection. A system for cardiac-gated acquisition was developed, directing x-ray exposures to within the quiescent period of the heart cycle, thereby minimizing anatomical misregistration. A research protocol including 200 patients imaged following lung nodule biopsy is underway, allowing preclinical evaluation of DE imaging performance relative to conventional radiography and low-dose CT.

MO‐D‐L100J‐09: A Multi‐Resolution, Multi‐Scale, Mutual Information Technique for Registration of High‐ and Low‐KVp Projections in Dual‐Energy Imaging

Purpose: In dual‐energy (DE) imaging, double‐shot acquisition provides superior DQE and detectability index compared to sandwiched detectors, but introduces the potential for misregistration artifacts (e.g., respiratory, cardiac, and bulk motion). This paper reports a projection registration scheme operating at various levels of scale and resolution to resolve misregistration errors prior to DE decomposition. Method and Materials: The method is based on joint histograms of the high‐ and low‐kVp images (or ROIs therein), with optimal image transformations computed to maximize the mutual information between the images. The image is subdivided into a series of ROIs, with an optimal transformation computed for each ROI. Large ROIs are downsampled to reduce the computational complexity of the optimization. The ROI transformations are smoothed and interpolated to determine a pixel‐wise transformation for the entire image. This is repeated with progressively smaller ROIs. Results: The results demonstrate that large scale ROIs (400×400 pixel) are effective in correcting bulk patient motion such as drift or relaxation. A second pass with a smaller ROI (200×200 pixel) corrects breathing and cardiac motion. A final pass with yet smaller ROIs (100×100 pixels) is effective at correcting the motion of fine bronchio‐vascular structure. The combination of these in an iterative multi‐resolution, multi‐scale method effectively registers the high‐ and low‐kVp projections such that DE images exhibit significantly reduced motion artifacts — particularly in the scapulae, aorta, heart,liver, and bronchioles. Expert radiologist readings suggest a significant improvement in image quality and diagnostic performance. Conclusion: The iterative, multi‐resolution, multi‐scale registration corrects misregistration progressively at scales ranging from bulk anatomical drift down to smaller scale motion such as that of fine pulmonary vasculature. The approach is a vital part of the DE image processing chain that has been implemented for a clinical DE imaging trial with 200 patients. Research partly supported by Eastman Kodak Co.

SU‐FF‐I‐115: Cardiac‐Gated Dual‐Energy Imaging of the Chest: Design and Performance Evaluation of a Cardiac Trigger Based On a Fingertip Pulse Oximeter

Purpose: A research prototype for high‐performance dual‐energy (DE) imaging of the chest is under development. This paper discusses the development and characterization of a cardiac gating system designed to precisely trigger the imagingsystem according to cardiac phase and minimize anatomical misregistration due to heart motion. Method and Materials: A fingertip pulse oximeter was employed to measure the peripheral pulse waveform and trigger x‐ray exposures during the quiescent phase of the heart (diastole). Temporal delays accounted in the timing scheme include physiological pulse propagation, waveform processing, and imagingsystem delays (filter‐wheel, bucky‐grid, and flat‐panel detector). An empirical model of the diastolic period allows calculation of the implemented delay, timp, required to trigger correctly at any patient heart‐rate. Performance was evaluated in terms of accuracy and precision of diastole‐trigger coincidence and expert assessment of cardiac motion artifact in gated and ungated DE images.Results: The model suggests a triggering scheme characterized by two heart‐rate (HR) regimes: below a HR‐threshold, sufficient time exists to expose on the same heartbeat ( t imp = 0) ; above the HR‐threshold, a characteristic timp(HR) delays exposure to the subsequent heartbeat, accounting for all fixed and variable system delays. Initial implementation indicated 83% accuracy in diastole‐trigger coincidence. By modifying the HR estimation method (reduced temporal smoothing of the pulse waveform), trigger accuracy of 100% was achieved. Cardiac‐gated DE patient images demonstrate significantly reduced cardiac motion as assessed by expert radiologists. Conclusion: A pulse oximeter combined with a cardiac model provides accurate x‐ray triggering and significantly reduces heart motion artifacts. A simple fingertip clip presents logistic, cost, and workflow advantages compared to ECG. The system has been implemented in a clinical research trial, with gated and ungated arms allowing characterization of the impact of cardiac motion artifact on diagnostic performance. Conflict of Interest: Research sponsored in part by Eastman Kodak.

Measurement of MTF by noise power analysis of one-dimensional white noise patterns

AbstractA method (or measuring the modulation transfer function (MTF) of digital printers is described that applies well-known techniques from the analysis of random data. More specifically, it is well-known that the input and output noise power spectra of linear systems can be used to estimate their transfer characteristics. In this application, small-amplitude one-dimensional white noise is used as the input to a digital laser printer. The noise power spectrum of the resulting film image is then estimated. From this the small-signal system MTF is obtained. This method will be demonstrated and discussed in the context of other methods described in the literature.