Modeling and design of a cone-beam CT head scanner using task-based imaging performance optimization.

Detection of acute intracranial hemorrhage (ICH) is important for diagnosis and treatment of traumatic brain injury, stroke, postoperative bleeding, and other head and neck injuries. This paper details the design and development of a cone-beam CT (CBCT) system developed specifically for the detection of low-contrast ICH in a form suitable for application at the point of care. Recognizing such a low-contrast imaging task to be a major challenge in CBCT, the system design began with a rigorous analysis of task-based detectability including critical aspects of system geometry, hardware configuration, and artifact correction. The imaging performance model described the three-dimensional (3D) noise-equivalent quanta using a cascaded systems model that included the effects of scatter, scatter correction, hardware considerations of complementary metal-oxide semiconductor (CMOS) and flat-panel detectors (FPDs), and digitization bit depth. The performance was analyzed with respect to a low-contrast (40-80 HU), medium-frequency task representing acute ICH detection. The task-based detectability index was computed using a non-prewhitening observer model. The optimization was performed with respect to four major design considerations: (1) system geometry (including source-to-detector distance (SDD) and source-to-axis distance (SAD)); (2) factors related to the x-ray source (including focal spot size, kVp, dose, and tube power); (3) scatter correction and selection of an antiscatter grid; and (4) x-ray detector configuration (including pixel size, additive electronics noise, field of view (FOV), and frame rate, including both CMOS and a-Si:H FPDs). Optimal design choices were also considered with respect to practical constraints and available hardware components. The model was verified in comparison to measurements on a CBCT imaging bench as a function of the numerous design parameters mentioned above. An extended geometry (SAD = 750 mm, SDD = 1100 mm) was found to be advantageous in terms of patient dose (20 mGy) and scatter reduction, while a more isocentric configuration (SAD = 550 mm, SDD = 1000 mm) was found to give a more compact and mechanically favorable configuration with minor tradeoff in detectability. An x-ray source with a 0.6 mm focal spot size provided the best compromise between spatial resolution requirements and x-ray tube power. Use of a modest anti-scatter grid (8:1 GR) at a 20 mGy dose provided slight improvement (~5-10%) in the detectability index, but the benefit was lost at reduced dose. The potential advantages of CMOS detectors over FPDs were quantified, showing that both detectors provided sufficient spatial resolution for ICH detection, while the former provided a potentially superior low-dose performance, and the latter provided the requisite FOV for volumetric imaging in a centered-detector geometry. Task-based imaging performance modeling provides an important starting point for CBCT system design, especially for the challenging task of ICH detection, which is somewhat beyond the capabilities of existing CBCT platforms. The model identifies important tradeoffs in system geometry and hardware configuration, and it supports the development of a dedicated CBCT system for point-of-care application. A prototype suitable for clinical studies is in development based on this analysis.

Task-Based Regularization Design for Detection of Intracranial Hemorrhage in Cone-Beam CT.

Prompt and reliable detection of acute intracranial hemorrhage (ICH) is critical to treatment of a number of neurological disorders. Cone-beam CT (CBCT) systems are potentially suitable for detecting ICH (contrast 40-80 HU, size down to 1 mm) at the point of care but face major challenges in image quality requirements. Statistical reconstruction demonstrates improved noise-resolution tradeoffs in CBCT head imaging, but its capability in improving image quality with respect to the task of ICH detection remains to be fully investigated. Moreover, statistical reconstruction typically exhibits nonuniform spatial resolution and noise characteristics, leading to spatially varying detectability of ICH for a conventional penalty. In this work, we propose a spatially varying penalty design that maximizes detectability of ICH at each location throughout the image. We leverage theoretical analysis of spatial resolution and noise for a penalized weighted least-squares (PWLS) estimator, and employ a task-based imaging performance descriptor in terms of detectability index using a nonprewhitening observer model. Performance prediction was validated using a 3D anthropomorphic head phantom. The proposed penalty achieved superior detectability throughout the head and improved detectability in regions adjacent to the skull base by ~10% compared to a conventional uniform penalty. PWLS reconstruction with the proposed penalty demonstrated excellent visualization of simulated ICH in different regions of the head and provides further support for development of dedicated CBCT head scanning at the point-of-care in the neuro ICU and OR.

Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging.

Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ~40-80 HU, size > 1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of intracranial hemorrhage.

Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation.

PURPOSE: To determine the degree of irreversible image compression detectable in conservative viewing conditions. MATERIALS AND METHODS: An image-comparison workstation, which alternately displayed two registered and magnified versions of an image, was used to study observer detection of image degradation introduced by irreversible compression. Five observers evaluated 20 16-bit posteroanterior digital chest radiographs compressed with Joint Photographic Experts Group (JPEG) or wavelet-based trellis-coded quantization (WTCQ) algorithms at compression ratios of 8:1-128:1 and x2 magnification by using (a) traditional two-alternative forced choice; (b) original-revealed two-alternative forced choice, in which the noncompressed image is identified to the observer; and (c) a resolution-metric method of matching test images to degraded reference images. RESULTS: The visually lossless threshold was between 8:1 and 16:1 for four observers. JPEG compression resulted in performance as good as that with WTCQ compression at these ratios. The original-revealed forced-choice method was faster and as sensitive as the two-alternative forced-choice method. The resolution-metric results were robust and provided information on performance above visually lossless levels. CONCLUSION: The image-comparison workstation is a versatile tool for comparative assessment of image quality. At x2 magnification, images compressed with either JPEG or WTCQ algorithms were indistinguishable from unaltered original images for most observers at compression ratios between 8:1 and 16:1, indicating that 10:1 compression is acceptable for primary image interpretation.