Dedicated cone-beam CT system for extremity imaging.

PURPOSE: To provide initial assessment of image quality and dose for a cone-beam computed tomographic (CT) scanner dedicated to extremity imaging. MATERIALS AND METHODS: A prototype cone-beam CT scanner has been developed for imaging the extremities, including the weight-bearing lower extremities. Initial technical assessment included evaluation of radiation dose measured as a function of kilovolt peak and tube output (in milliampere seconds), contrast resolution assessed in terms of the signal difference-to-noise ratio (SDNR), spatial resolution semiquantitatively assessed by using a line-pair module from a phantom, and qualitative evaluation of cadaver images for potential diagnostic value and image artifacts by an expert CT observer (musculoskeletal radiologist). RESULTS: The dose for a nominal scan protocol (80 kVp, 108 mAs) was 9 mGy (absolute dose measured at the center of a CT dose index phantom). SDNR was maximized with the 80-kVp scan technique, and contrast resolution was sufficient for visualization of muscle, fat, ligaments and/or tendons, cartilage joint space, and bone. Spatial resolution in the axial plane exceeded 15 line pairs per centimeter. Streaks associated with x-ray scatter (in thicker regions of the patient--eg, the knee), beam hardening (about cortical bone--eg, the femoral shaft), and cone-beam artifacts (at joint space surfaces oriented along the scanning plane--eg, the interphalangeal joints) presented a slight impediment to visualization. Cadaver images (elbow, hand, knee, and foot) demonstrated excellent visibility of bone detail and good soft-tissue visibility suitable to a broad spectrum of musculoskeletal indications. CONCLUSION: A dedicated extremity cone-beam CT scanner capable of imaging upper and lower extremities (including weight-bearing examinations) provides sufficient image quality and favorable dose characteristics to warrant further evaluation for clinical use.

Investigation of the variability in the assessment of digital chest X-ray image quality.

A large database of digital chest radiographs was developed over a 14-month period. Ten radiographic technologists and five radiologists independently evaluated a stratified subset of images from the database for quality deficiencies and decided whether each image should be rejected. The evaluation results showed that the radiographic technologists and radiologists agreed only moderately in their assessments. When compared against each other, radiologist and technologist reader groups were found to have even less agreement than the inter-reader agreement within each group. Radiologists were found to be more accepting of limited-quality studies than technologists. Evidence from the study suggests that the technologists weighted their reject decisions more heavily on objective technical attributes, while the radiologists weighted their decisions more heavily on diagnostic interpretability relative to the image indication. A suite of reject-detection algorithms was independently run on the images in the database. The algorithms detected 4 % of postero-anterior chest exams that were accepted by the technologist who originally captured the image but which would have been rejected by the technologist peer group. When algorithm results were made available to the technologists during the study, there was no improvement in inter-reader agreement in deciding whether to reject an image. The algorithm results do, however, provide new quality information that could be captured within a site-wide, reject-tracking database and leveraged as part of a site-wide QA program.

An image-based technique to assess the perceptual quality of clinical chest radiographs.

PURPOSE: Current clinical image quality assessment techniques mainly analyze image quality for the imaging system in terms of factors such as the capture system modulation transfer function, noise power spectrum, detective quantum efficiency, and the exposure technique. While these elements form the basic underlying components of image quality, when assessing a clinical image, radiologists seldom refer to these factors, but rather examine several specific regions of the displayed patient images, further impacted by a particular image processing method applied, to see whether the image is suitable for diagnosis. In this paper, the authors developed a novel strategy to simulate radiologists' perceptual evaluation process on actual clinical chest images. METHODS: Ten regional based perceptual attributes of chest radiographs were determined through an observer study. Those included lung grey level, lung detail, lung noise, rib-lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. Each attribute was characterized in terms of a physical quantity measured from the image algorithmically using an automated process. A pilot observer study was performed on 333 digital chest radiographs, which included 179 PA images with 10:1 ratio grids (set 1) and 154 AP images without grids (set 2), to ascertain the correlation between image perceptual attributes and physical quantitative measurements. To determine the acceptable range of each perceptual attribute, a preliminary quality consistency range was defined based on the preferred 80% of images in set 1. Mean value difference (µ(1) - µ(2)) and variance ratio (σ(1) (2)/σ(2) (2)) were investigated to further quantify the differences between the selected two image sets. RESULTS: The pilot observer study demonstrated that our regional based physical quantity metrics of chest radiographs correlated very well with their corresponding perceptual attributes. The distribution comparisons, mean value difference estimations, and variance ratio estimations of each physical quantity between sets of images from two different techniques matched our expectation that the image quality of set 1 should be better than that of set 2. CONCLUSIONS: The measured physical quantities provide a robust reflection of perceptual image quality in clinical images. The methodology can be readily applied for automated evaluation of perceptual image quality in clinical chest radiographs.

Digital radiography reject analysis: data collection methodology, results, and recommendations from an in-depth investigation at two hospitals.

Reject analysis was performed on 288,000 computed radiography (CR) image records collected from a university hospital (UH) and a large community hospital (CH). Each record contains image information, such as body part and view position, exposure level, technologist identifier, and--if the image was rejected--the reason for rejection. Extensive database filtering was required to ensure the integrity of the reject-rate calculations. The reject rate for CR across all departments and across all exam types was 4.4% at UH and 4.9% at CH. The most frequently occurring exam types with reject rates of 8% or greater were found to be common to both institutions (skull/facial bones, shoulder, hip, spines, in-department chest, pelvis). Positioning errors and anatomy cutoff were the most frequently occurring reasons for rejection, accounting for 45% of rejects at CH and 56% at UH. Improper exposure was the next most frequently occurring reject reason (14% of rejects at CH and 13% at UH), followed by patient motion (11% of rejects at CH and 7% at UH). Chest exams were the most frequently performed exam at both institutions (26% at UH and 45% at CH) with half captured in-department and half captured using portable x-ray equipment. A ninefold greater reject rate was found for in-department (9%) versus portable chest exams (1%). Problems identified with the integrity of the data used for reject analysis can be mitigated in the future by objectifying quality assurance (QA) procedures and by standardizing the nomenclature and definitions for QA deficiencies.

Neonatal chest computed radiography: image processing and optimal image display.

OBJECTIVE: The purpose of this study was to determine soft-copy image display preferences of brightness, latitude, and detail contrast for neonatal chest computed radiography to establish a baseline for future work on low-dose imaging. CONCLUSION: Observers preferred brighter images with higher detail contrast and narrow to middle latitude for soft-copy display compared with the typical screen-film hard-copy appearance. Future research on low-dose neonatal chest imaging will be facilitated by an understanding of optimal soft-copy image display.

Multi-resolution statistical image reconstruction for mitigation of truncation effects: application to cone-beam CT of the head.

A prototype cone-beam CT (CBCT) head scanner featuring model-based iterative reconstruction (MBIR) has been recently developed and demonstrated the potential for reliable detection of acute intracranial hemorrhage (ICH), which is vital to diagnosis of traumatic brain injury and hemorrhagic stroke. However, data truncation (e.g. due to the head holder) can result in artifacts that reduce image uniformity and challenge ICH detection. We propose a multi-resolution MBIR method with an extended reconstruction field of view (RFOV) to mitigate truncation effects in CBCT of the head. The image volume includes a fine voxel size in the (inner) nontruncated region and a coarse voxel size in the (outer) truncated region. This multi-resolution scheme allows extension of the RFOV to mitigate truncation effects while introducing minimal increase in computational complexity. The multi-resolution method was incorporated in a penalized weighted least-squares (PWLS) reconstruction framework previously developed for CBCT of the head. Experiments involving an anthropomorphic head phantom with truncation due to a carbon-fiber holder were shown to result in severe artifacts in conventional single-resolution PWLS, whereas extending the RFOV within the multi-resolution framework strongly reduced truncation artifacts. For the same extended RFOV, the multi-resolution approach reduced computation time compared to the single-resolution approach (viz. time reduced by 40.7%, 83.0%, and over 95% for an image volume of 6003, 8003, 10003 voxels). Algorithm parameters (e.g. regularization strength, the ratio of the fine and coarse voxel size, and RFOV size) were investigated to guide reliable parameter selection. The findings provide a promising method for truncation artifact reduction in CBCT and may be useful for other MBIR methods and applications for which truncation is a challenge.

Task-based statistical image reconstruction for high-quality cone-beam CT.

Task-based analysis of medical imaging performance underlies many ongoing efforts in the development of new imaging systems. In statistical image reconstruction, regularization is often formulated in terms to encourage smoothness and/or sharpness (e.g. a linear, quadratic, or Huber penalty) but without explicit formulation of the task. We propose an alternative regularization approach in which a spatially varying penalty is determined that maximizes task-based imaging performance at every location in a 3D image. We apply the method to model-based image reconstruction (MBIR-viz., penalized weighted least-squares, PWLS) in cone-beam CT (CBCT) of the head, focusing on the task of detecting a small, low-contrast intracranial hemorrhage (ICH), and we test the performance of the algorithm in the context of a recently developed CBCT prototype for point-of-care imaging of brain injury. Theoretical predictions of local spatial resolution and noise are computed via an optimization by which regularization (specifically, the quadratic penalty strength) is allowed to vary throughout the image to maximize local task-based detectability index ([Formula: see text]). Simulation studies and test-bench experiments were performed using an anthropomorphic head phantom. Three PWLS implementations were tested: conventional (constant) penalty; a certainty-based penalty derived to enforce constant point-spread function, PSF; and the task-based penalty derived to maximize local detectability at each location. Conventional (constant) regularization exhibited a fairly strong degree of spatial variation in [Formula: see text], and the certainty-based method achieved uniform PSF, but each exhibited a reduction in detectability compared to the task-based method, which improved detectability up to ~15%. The improvement was strongest in areas of high attenuation (skull base), where the conventional and certainty-based methods tended to over-smooth the data. The task-driven reconstruction method presents a promising regularization method in MBIR by explicitly incorporating task-based imaging performance as the objective. The results demonstrate improved ICH conspicuity and support the development of high-quality CBCT systems.

Automatic image hanging protocol for chest radiographs in PACS.

Chest radiography is one of the most widely used techniques in diagnostic imaging. It comprises at least one-third of all diagnostic radiographic procedures in hospitals. However, in the picture archive and communication system, images are often stored with the projection and orientation unknown or mislabeled, which causes inefficiency for radiologists' interpretation. To address this problem, an automatic hanging protocol for chest radiographs is presented. The method targets the most effective region in a chest radiograph, and extracts a set of size-, rotation-, and translation-invariant features from it. Then, a well-trained classifier is used to recognize the projection. The orientation of the radiograph is later identified by locating the neck, heart, and abdomen positions in the radiographs. Initial experiments are performed on the radiographs collected from daily routine chest exams in hospitals and show promising results. Using the presented protocol, 98.2% of all cases could be hung correctly on projection view (without protocol, 62%), and 96.1% had correct orientation (without protocol, 75%). A workflow study on the protocol also demonstrates a significant improvement in efficiency for image display.

Technical assessment of a prototype cone-beam CT system for imaging of acute intracranial hemorrhage.

PURPOSE: A cone-beam CT scanner has been developed for detection and monitoring of traumatic brain injury and acute intracranial hemorrhage (ICH) at the point of care. This work presents a technical assessment of imaging performance and dose for the scanner in phantom and cadaver studies as a prerequisite to clinical translation. METHODS: The scanner incorporates a compact, rotating-anode x-ray source and a flat-panel detector (43 × 43 cm2) on a mobile U-arm gantry with source-axis distance = 550 mm and source-detector distance = 1000 mm. Central and peripheral doses were measured in 16 cm diameter CTDI phantoms using a 0.6 cm3 Farmer ionization chamber for various scan techniques and as a function of longitudinal position, including out of field. Spatial resolution, contrast, noise, and image uniformity were assessed in quantitative and anthropomorphic head phantoms. Two reconstruction protocols were evaluated, including filtered backprojection (FBP) for high-resolution bone imaging and penalized weighted least squares (PWLS) reconstruction for low-contrast soft tissue (ICH) visualization. A fresh cadaver was imaged with and without simulated ICH using the scanner as well as a diagnostic multidetector CT (MDCT) scanner using a standard head protocol. Images were interpreted by a fellowship-trained neuroradiologist for imaging tasks of ICH detection, gray-white-CSF differentiation, detection of midline shift, and fracture detection. RESULTS: The nominal scan protocol involved 720 projections acquired over a 360° orbit at 100 kV and 216 mAs, giving a dose (weighted CTDI) of 22.8 mGy (∼1.2 mSv effective dose). Out-of-field dose decreased to <10% within 6 cm of the field edge (approximate to the thyroid position). Image uniformity demonstrated <1% variation between the edge of the field (near the cranium) and center of the image. The high-resolution FBP reconstruction protocol showed ∼0.9 mm point spread function (PSF) full-width at half-maximum (FWHM). The smooth PWLS reconstruction protocol yielded ∼1.2 mm PSF FWHM and contrast-to-noise ratio exceeding 5.7 in ∼50 HU spherical ICH, resulting in conspicuous depiction of ICH down to ∼2 mm (the smallest diameter investigated). Cadaver images demonstrated good differentiation of brain and CSF (sufficient, but inferior to MDCT, recognizing that the CBCT dose was one-third that of MDCT), excellent visualization of cranial sutures and fracture (potentially superior to MDCT), clear detection of midline shift, and conspicuous detection of ICH. CONCLUSIONS: Technical assessment of the prototype demonstrates dose characteristics and imaging performance consistent with point-of-care detection and monitoring of head injury-most notably, conspicuous detection of ICH-and supports translation of the system to clinical studies.

Evaluation of detector readout gain mode and bowtie filters for cone-beam CT imaging of the head.

The effects of detector readout gain mode and bowtie filters on cone-beam CT (CBCT) image quality and dose were characterized for a new CBCT system developed for point-of-care imaging of the head, with potential application to diagnosis of traumatic brain injury, intracranial hemorrhage (ICH), and stroke. A detector performance model was extended to include the effects of detector readout gain on electronic digitization noise. The noise performance for high-gain (HG), low-gain (LG), and dual-gain (DG) detector readout was evaluated, and the benefit associated with HG mode in regions free from detector saturation was quantified. Such benefit could be realized (without detector saturation) either via DG mode or by incorporation of a bowtie filter. Therefore, three bowtie filters were investigated that varied in thickness and curvature. A polyenergetic gain correction method was developed to equalize the detector response between the flood-field and projection data in the presence of a bowtie. The effect of bowtie filters on dose, scatter-to-primary ratio, contrast, and noise was quantified in phantom studies, and results were compared to a high-speed Monte Carlo (MC) simulation to characterize x-ray scatter and dose distributions in the head. Imaging in DG mode improved the contrast-to-noise ratio (CNR) by ~15% compared to LG mode at a dose (D 0, measured at the center of a 16 cm CTDI phantom) of 19 mGy. MC dose calculations agreed with CTDI measurements and showed that bowtie filters reduce peripheral dose by as much as 50% at the same central dose. Bowtie filters were found to increase the CNR per unit square-root dose near the center of the image by ~5-20% depending on bowtie thickness, but reduced CNR in the periphery by ~10-40%. Images acquired at equal CTDIw with and without a bowtie demonstrated a 24% increase in CNR at the center of an anthropomorphic head phantom. Combining a thick bowtie filter with a short arc (180° + fan angle) scan centered on the posterior of the head reduced dose to the eye lens by up to 90%. Acquisition in DG mode (without a bowtie filter) was beneficial to the detection of small, low contrast lesions (e.g. subtle ICH) in CBCT. While bowtie filters were found to reduce dose, mitigate sensor saturation at the periphery in HG mode, and improve CNR at the center of the image, the image quality at the periphery was slightly reduced compared to DG mode, and the use of a bowtie required careful implementation of the polyenergetic flood-field correction to avoid artifacts.

Stationary chest tomosynthesis using a carbon nanotube x-ray source array: a feasibility study.

Chest tomosynthesis is a low-dose, quasi-3D imaging modality that has been demonstrated to improve the detection sensitivity for small lung nodules, compared to 2D chest radiography. The purpose of this study is to investigate the feasibility and system requirements of stationary chest tomosynthesis (s-DCT) using a spatially distributed carbon nanotube (CNT) x-ray source array, where the projection images are collected by electronically activating individual x-ray focal spots in the source array without mechanical motion of the x-ray source, detector, or the patient. A bench-top system was constructed using an existing CNT field emission source array and a flat panel detector. The tube output, beam quality, focal spot size, system in-plane and in-depth resolution were characterized. Tomosynthesis slices of an anthropomorphic chest phantom were reconstructed for image quality assessment. All 75 CNT sources in the source array were shown to operate reliably at 80 kVp and 5 mA tube current. Source-to-source consistency in the tube current and focal spot size was observed. The incident air kerma reading per mAs was measured as 74.47 uGy mAs(-1) at 100 cm. The first half value layer of the beam was 3 mm aluminum. An average focal spot size of 2.5  ×  0.5 mm was measured. The system MTF was measured to be 1.7 cycles mm(-1) along the scanning direction, and 3.4 cycles mm(-1) perpendicular to the scanning direction. As the angular coverage of 11.6°-34°, the full width at half maximum of the artifact spread function improved greatly from 9.5 to 5.2 mm. The reconstructed tomosynthesis slices clearly show airways and pulmonary vascular structures in the anthropomorphic lung phantom. The results show the CNT source array is capable of generating sufficient dose for chest tomosynthesis imaging. The results obtained so far suggest an s-DCT using a distributed CNT x-ray source array is feasible.

Improved visualization of tubes and lines in portable intensive care unit radiographs: a study comparing a new approach to the standard approach.

Tube and line interpretation in portable chest radiographs was assessed using a new visualization method. When using the new method, radiologists' interpretation time was reduced by 30% vs. standard modality processing and window and level (23 vs. 33 s). For pulmonary ICU physicians, reading time was essentially unchanged. There was more than a 50% reduction in the use of inferential language in the dictation for both reader groups when using the new method, suggesting greater interpretation confidence.