OBJECTIVE: To devise a new method to measure the amount of soft tissue in pulmonary ground-glass opacity nodules, and to compare the use of this method with a previous volumetric measurement method by use of a phantom study. MATERIALS AND METHODS: Phantom nodules were prepared with material from fixed normal swine lung. Forty nodules, each with a diameter of 10 mm, were made with a variable mean attenuation. The reference-standard amount of soft tissue in the nodules was obtained by dividing the weight by the specific gravity. The imaging data on the phantom nodules were acquired with the use of a 16-channel multidetector CT scanner. The CT-measured amount of soft tissue of the nodules was calculated as follows: soft tissue amount = volume x (1 + mean attenuation value / 1,000). The relative percentage error (RPE) between the CT-measured amount of the soft tissue and the reference-standard amount of the soft tissue was also measured. The RPEs determined with use of the new method were compared with the RPEs determined with the current volumetric measurement method by the use of the paired t test. RESULTS: The CT-measured amount of soft tissue showed a strong correlation with the reference-standard amount of soft tissue (R(2) = 0.996, p < 0.01). The mean RPE of the CT-measured amount of soft tissue in the nodules was -7.79 +/- 1.88%. The mean RPE of the CT-measured volume was 114.78 +/- 51.02%, which was significantly greater than the RPE of the CT-measured amount of soft tissue (p < 0.01). CONCLUSION: The amount of soft tissue measured by the use of CT reflects the reference-standard amount of soft tissue in the ground-glass opacity nodules much more accurately than does the use of the CT-measured volume.
Animals ; Lung Neoplasms/*radiography ; Phantoms, Imaging ; Reference Standards ; Swine ; *Tomography, X-Ray Computed

OBJECTIVE: The CT accreditation program was established in 2004 by the Korean Institute for Accreditation of Medical Image (KIAMI) to confirm that there was proper quality assurance of computed tomography (CT) images. We reviewed all the failed CT phantom image evaluations performed in 2005 and 2006. MATERIALS AND METHODS: We analyzed 604 failed CT phantom image evaluations according to the type of evaluation, the size of the medical institution, the parameters of the phantom image testing and the manufacturing date of the CT scanners. RESULTS: The failure rates were 10.5% and 21.6% in 2005 and 2006, respectively. Spatial resolution was the most frequently failed parameter for the CT phantom image evaluations in both years (50.5% and 49%, respectively). The proportion of cases with artifacts increased in 2006 (from 4.5% to 37.8%). The failed cases in terms of image uniformity and the CT number of water decreased in 2006. The failure rate in general hospitals was lower than at other sites. In 2006, the proportion of CT scanners manufactured before 1995 decreased (from 12.9% to 9.3%). CONCLUSION: The continued progress in the CT accreditation program may achieve improved image quality and thereby improve the national health of Korea.
*Accreditation ; Korea ; Phantoms, Imaging ; Societies, Medical ; Tomography, X-Ray Computed/*standards

Our purpose is to introduce and analyze the data quality assurance (DQA) protocol of functional magnetic resonance imaging (fMRI). A water phantom was scanned to get DQA indexes. An fMRI sequence was used to get signal noise ratio (SNR) and Drift, which was calculated from maximum difference ratio of the average signal intensity in the region of interest (ROI) of image serials. The long period application of this method demonstrated that this DQA protocol can reflect imaging performance and the state of stability of the MRI scanner. Some application experience and discussion involved in DQA were also presented here.
Algorithms ; Artifacts ; Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted ; methods ; Magnetic Resonance Imaging ; methods ; Phantoms, Imaging ; standards ; Quality Control

Concerns have been raised over x-ray radiation dose associated with repeated computed tomography (CT) scans for tumor surveillance and radiotherapy planning. In this paper, we present a low-dose CT image reconstruction method for improving low-dose CT image quality. The method proposed exploited rich redundancy information from previous normal-dose scan image for optimizing the non-local weights construction in the original non-local means (NLM)-based low-dose image reconstruction. The objective 3D low-dose volume and the previous 3D normal-dose volume were first registered to reduce the anatomic structural dissimilarity between the two datasets, and the optimized non-local weights were constructed based on the registered normal-dose volume. To increase the efficiency of this method, GPU was utilized to accelerate the implementation. The experimental results showed that this method obviously improved the image quality, as compared with the original NLM method, by suppressing the noise-induced artifacts and preserving the edge information.
Algorithms ; Artifacts ; Humans ; Imaging, Three-Dimensional ; methods ; Phantoms, Imaging ; Radiation Dosage ; Radiation Protection ; standards ; Radiographic Image Interpretation, Computer-Assisted ; methods ; standards ; Tomography, X-Ray Computed ; methods

OBJECTIVETo study regular patterns of cone artifact resulted from interpolation algorithm of spiral CT.

METHODSBased on the principle of interpolation algorithm and back-projection reconstruction, a mathematical model of the reconstructed image was established to clarify the relation of the scanning parameters and the characteristics of the scanned object with the cone artifact. Experiments were carried out by a set of acrylic phantoms on siemens plus 4 CT scanners.

RESULTSThe artifact in the image was directly proportional to the table increment per gantry rotation of the scanner, and was positively correlated to the tangent of half cone-angle and inversely to the radii in the reconstruction plane of the phantom. The theoretical analysis was validated by experimental results.

CONCLUSIONThe cone artifact is related to the scanning parameters and the characteristics of the scanned object.

Algorithms ; Artifacts ; Computer Simulation ; Image Processing, Computer-Assisted ; methods ; standards ; Models, Theoretical ; Phantoms, Imaging ; Tomography, Spiral Computed ; instrumentation ; methods

OBJECTIVE: To evaluate the impact of the adaptive iterative dose reduction (AIDR) three-dimensional (3D) algorithm in CT on noise reduction and the image quality compared to the filtered back projection (FBP) algorithm and to compare the effectiveness of AIDR 3D on noise reduction according to the body habitus using phantoms with different sizes. MATERIALS AND METHODS: Three different-sized phantoms with diameters of 24 cm, 30 cm, and 40 cm were built up using the American College of Radiology CT accreditation phantom and layers of pork belly fat. Each phantom was scanned eight times using different mAs. Images were reconstructed using the FBP and three different strengths of the AIDR 3D. The image noise, the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of the phantom were assessed. Two radiologists assessed the image quality of the 4 image sets in consensus. The effectiveness of AIDR 3D on noise reduction compared with FBP were also compared according to the phantom sizes. RESULTS: Adaptive iterative dose reduction 3D significantly reduced the image noise compared with FBP and enhanced the SNR and CNR (p < 0.05) with improved image quality (p < 0.05). When a stronger reconstruction algorithm was used, greater increase of SNR and CNR as well as noise reduction was achieved (p < 0.05). The noise reduction effect of AIDR 3D was significantly greater in the 40-cm phantom than in the 24-cm or 30-cm phantoms (p < 0.05). CONCLUSION: The AIDR 3D algorithm is effective to reduce the image noise as well as to improve the image-quality parameters compared by FBP algorithm, and its effectiveness may increase as the phantom size increases.
*Algorithms ; Animals ; Body Size ; Image Processing, Computer-Assisted/*methods ; *Phantoms, Imaging/standards ; Radiation Dosage ; Signal-To-Noise Ratio ; Subcutaneous Fat, Abdominal/*radiography ; Swine ; Tomography, X-Ray Computed/*methods