Kim, Myeong-Seong;Jeong, Jong-Seong;Kim, Myeong-Goo
Journal of Radiation Protection and Research
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v.36
no.2
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pp.79-85
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2011
OThe purpose of this article was to measure and compare the value of the metal artifact reduction (MAR) algorithm by Dual energy(kVp switching) CT (Computed Tomography) for non using MAR and we introduced new variable Dual energy CT applications through a clinical scan. The used equipment was GE Discovery 750HD with Dual-Energy system(kVp switching). CT scan was performed on the neck and abdomen area subject for patients. Studies were from Dec 20 2010 to Feb 10 2011 and included 25 subject patients with prosthesis. We were measured the HU (Hounsfield Unit) and noise value at metal artifact appear(focal loss of signal and white streak artifact area) according to the using MAR algorithm. Statistical analyses were performed using the paired sample t-test. In patient subject case, the statistical difference of showing HU was p=0.01 and p=0.04 respectively. At maximum black hole artifact area and white streak artifact area according to the using MAR algorithm. However noise was p=0.05 and p=0.04 respectively; and not the affected black hole and white streak artifact area. Dual Energy CT with the MAR algorithm technique is useful reduce metal artifacts and could improve the diagnostic value in the diagnostic image evaluation of metallic implants area.
The aim of this study is to evaluate the diagnostic ability of dual-energy computed tomography (DECT) for Composition determination of urinary stones in phantom model. Seventeen cases with urinary stones who underwent DECT were enrolled in the study. The composition of the urinary stones was extracted from the seventeen patients were analyzed with DECT in phantom model with fresh pork. The volume scan method using Dual-energy software was used and the scanned image sets were assessed. All 17 urinary stones of the phantom model were analyzed according to the stone composition using DE stone Analysis were divided into uric acid stones (n=6, 35.29%) and non-uric acid stones (n=11, 64.71%). These urinary stones were pathologically confirmed. The mean attenuation values of uric acid stones at 135 kV, 100 kV and 80 kV was 348.87 ± 166.37 HU, 345.33 ± 151.18 HU and 337.94 ± 172.77 HU, respectively. The mean attenuation values of non-uric acid stones at 135 kV, 100 kV and 80 kV was 551.93 ± 297.09 HU, 747.04 ± 351.31 HU and 958.19 ± 424.72 HU, respectively. At 80 kV, uric acid stones and non-uric acid stones showed significant difference in the attenuation values(P<0.05). The attenuation values of DECT could differentiate the compositions of urinary stones between uric acid and non-uric acid stones at 80 kV in phantom model.
Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.
The study examines changes in calcium volume on born by comparing two figures; one is measured by dual energy computed tomography(DECT) followed by applying variation in monochromatic energy selection(keV), material decomposition(MD), and material suppressed iodine(MSI) analysis, and the other is measured by conventional single source computed tomography(CSCT). For this study, based on CSCT images taken by using human mimicked phantom, 70, 100, 140 keV and MSI, MD material calcium weighting(MCW) and MD material iodine weighting(MIW) of DECT were applied respectively. Then calculated calcium volume was converted to Agatston score for comparison. Volume of human mimicked phantom was in inverse proportion to keV. The volume decreased while keV increased(p<0.05). The most similar DECT volumes were reconstructed at 70 keV, the difference was showed $35.8{\pm}12.2$ for rib, femur ($16.1{\pm}24.1$), pelvis($13.7{\pm}18.8$), and spine($179.0{\pm}61.8$). However, the volume of MSI was down for each organ; the volume of rib was 5.55%, femur(76.34%), pelvis(55.16%) and spine(87.58%). The volume of MSI decreased 55.9% for rib, femur(80.7%), pelvis(69.6%) and spine(54.2%) while MD MIW reduced for rib(83.51%), femur(87.68%), pelvis(86.64%), and spine(82.62%). With the results, the study found that outcomes were affected by the method which examiners employed. When using DECT, calcium volume of born dropped with keV increased. It also found that the most similar DECT images were reconstructed at 70 keV. The results of experiments implied that the users of MSI and MD should be cautious of errors as there are big differences in scores between those two methods.
The purpose of this simulation study was to evaluate the possibility of pancreas detection through effective atomic number information using dual-energy computed tomography(CT). The effective atomic number of 10 tissue-equivalent materials were estimated through stoichiometric calibration. For stoichiometric calibration, HU values at low-energy (80 kV) and high-energy (140 kV) for 10 tissue-equivalent materials were used. Based on this method, the effective atomic number image of the tissue-equivalent material was extracted through an iterative algorithm. According to the results, the attenuation ratio in accordance with the effective atomic number was estimated to have an R2 value of 0.9999, and the effective atomic number of Pancreas, Water, Liver, Blood, Spongiosa, and Cortical bone was overall within 1% accuracy compared to the theoretical value. Conventional pancreatic cancer examination uses a contrast medium, so there is a possibility of potential side effects of the contrast medium. In order to solve this problem, it is thought that it will be possible to contribute to an accurate and safe examination by extracting the effective atomic number using dual-energy CT without contrast enhancement. Based on this study, future research will be conducted on the detection of pancreatic cancer using the HU value of pancreatic cancer based on clinical images.
Lee, Jun Seok;Son, Dong Wuk;Lee, Su Hun;Ki, Sung Soon;Lee, Sang Weon;Song, Geun Sung;Woo, Joon Bum;Kim, Young Ha
Journal of Korean Neurosurgical Society
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v.65
no.1
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pp.96-106
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2022
Objective : The most common complication of anterior cervical discectomy and fusion (ACDF) is cage subsidence and maintenance of disc height affects postoperative clinical outcomes. We considered cage subsidence as an inappropriate indicator for evaluating preservation of disc height. Thus, this study aimed to consider patients with complications such as reduced total disc height compared to that before surgery and evaluate the relevance of several factors before ACDF. Methods : We retrospectively reviewed the medical records of 40 patients who underwent stand-alone single-level ACDF using a polyetheretherketone (PEEK) cage at our institution between January 2012 and December 2018. Our study population comprised 19 male and 21 female patients aged 24-70 years. The minimum follow-up period was 1 year. Twenty-seven patients had preoperative bone mineral density (BMD) data on dual-energy X-ray absorptiometry. Clinical parameters included sex, age, body mass index, smoking history, and prior medical history. Radiologic parameters included the C2-7 cobb angle, segmental angle, sagittal vertical axis, disc height, and total intervertebral height (TIH) at the preoperative and postoperative periods. Cage decrement was defined as the reduction in TIH at the 6-month follow-up compared to preoperative TIH. To evaluate the bone quality, Hounsfield unit (HU) value was calculated in the axial and sagittal images of conventional computed tomography. Results : Lumbar BMD values and cervical HU values were significantly correlated (r=0.733, p<0.001). We divided the patients into two groups based on cage decrement, and 47.5% of the total patients were regarded as cage decrement. There were statistically significant differences in the parameters of measuring the HU value of the vertebra and intraoperative distraction between the two groups. Using these identified factors, we performed a receiver operating characteristic (ROC) curve analysis. Based on the ROC curve, the cut-off point was 530 at the HU value of the upper cortical and cancellous vertebrae (p=0.014; area under the curve [AUC], 0.727; sensitivity, 94.7%; specificity, 42.9%) and 22.41 at intraoperative distraction (p=0.017; AUC, 0.722; sensitivity, 85.7%; specificity, 57.9%). Using this value, we converted these parameters into a bifurcated variable and assessed the multinomial regression analysis to evaluate the risk factors for cage decrement in ACDF. Intraoperative distraction and HU value of the upper vertebral body were independent factors of postoperative subsidence. Conclusion : Insufficient intraoperative distraction and low HU value showed a strong relationship with postoperative intervertebral height reduction following single stand-alone PEEK cage ACDF.
Hye Jung Choo;Sun Joo Lee;Dong Wook Kim;Yoo Jin Lee;Jin Wook Baek;Ji-yeon Han;Young Jin Heo
Korean Journal of Radiology
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v.22
no.8
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pp.1341-1351
/
2021
Objective: To compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty. Materials and Methods: We included 58 patients (28 male and 30 female; mean age [range], 71.4 [61-83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and -0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts. Results: iMAR-applied, polychromatic images using weighting factors of -0.3 and 0.0 (P-0.3i and P0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P-0.3i, P0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P-0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application. Conclusion: Polychromatic images combined with iMAR application, P-0.3i and P0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.
Objective: To objectively and subjectively assess and compare the characteristics of monoenergetic images [MEI (+)] and polyenergetic images (PEI) acquired by dual-energy CT (DECT) of patients with breast cancer. Materials and Methods: This retrospective study evaluated the images and data of 42 patients with breast cancer who had undergone dual-phase contrast-enhanced DECT from June to September 2019. One standard PEI, five MEI (+) in 10-kiloelectron volt (keV) intervals (range, 40-80 keV), iodine density (ID) maps, iodine overlay images, and Z effective (Zeff) maps were reconstructed. The contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) were calculated. Multiple quantitative parameters of the malignant breast lesions were compared between the arterial and the venous phase images. Two readers independently assessed lesion conspicuity and performed a morphology analysis. Results: Low keV MEI (+) at 40-50 keV showed increased CNR and SNRbreastlesion compared with PEI, especially in the venous phase ([CNR: 40 keV, 20.10; 50 keV, 14.45; vs. PEI, 7.27; p < 0.001], [SNRbreastlesion: 40 keV, 21.01; 50 keV, 16.28; vs. PEI, 10.77; p < 0.001]). Multiple quantitative DECT parameters of malignant breast lesions were higher in the venous phase images than in the arterial phase images (p < 0.001). MEI (+) at 40 keV, ID, and Zeff reconstructions yielded the highest Likert scores for lesion conspicuity. The conspicuity of the mass margin and the visual enhancement were significantly better in 40-keV MEI (+) than in the PEI (p = 0.022, p = 0.033, respectively). Conclusion: Compared with PEI, MEI (+) reconstructions at low keV in the venous phase acquired by DECT improved the objective and subjective assessment of lesion conspicuity in patients with malignant breast lesions. MEI (+) reconstruction acquired by DECT may be helpful for the preoperative evaluation of breast cancer.
Suyon Chang;Jung Im Jung;Kyongmin Sarah Beck;Kiyuk Chang;Yaeni Kim;Kyunghwa Han
Korean Journal of Radiology
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v.25
no.7
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pp.634-643
/
2024
Objective: This study aimed to evaluate the diagnostic efficacy and safety of low-contrast-dose, dual-source dual-energy CT before transcatheter aortic valve replacement (TAVR) in patients with compromised renal function. Materials and Methods: A total of 54 consecutive patients (female:male, 26:38; 81.9 ± 7.3 years) with reduced renal function underwent pre-TAVR dual-energy CT with a 30-mL contrast agent between June 2022 and March 2023. Monochromatic (40- and 50-keV) and conventional (120-kVp) images were reconstructed and analyzed. The subjective quality score, vascular attenuation, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were compared among the imaging techniques using the Friedman test and post-hoc analysis. Interobserver reliability for aortic annular measurement was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. The procedural outcomes and incidence of post-contrast acute kidney injury (AKI) were assessed. Results: Monochromatic images achieved diagnostic quality in all patients. The 50-keV images achieved superior vascular attenuation and CNR (P < 0.001 in all) while maintaining a similar SNR compared to conventional CT. For aortic annular measurement, the 50-keV images showed higher interobserver reliability compared to conventional CT: ICC, 0.98 vs. 0.90 for area and 0.97 vs. 0.95 for perimeter; 95% limits of agreement width, 0.63 cm2 vs. 0.92 cm2 for area and 5.78 mm vs. 8.50 mm for perimeter. The size of the implanted device matched CT-measured values in all patients, achieving a procedural success rate of 92.6%. No patient experienced a serum creatinine increase of ≥ 1.5 times baseline in the 48-72 hours following CT. However, one patient had a procedural delay due to gradual renal function deterioration. Conclusion: Low-contrast-dose imaging with 50-keV reconstruction enables precise pre-TAVR evaluation with improved image quality and minimal risk of post-contrast AKI. This approach may be an effective and safe option for pre-TAVR evaluation in patients with compromised renal function.
Tae Jun Ha;Hee Sang Kim;Seong Uk Kang;DooHee Lee;Woo Jin Kim;Ki Won Moon;Hyun-Soo Choi;Jeong Hyun Kim;Yoon Kim;So Hyeon Bak;Sang Won Park
Journal of the Korean Society of Radiology
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v.18
no.3
/
pp.187-201
/
2024
Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.
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