Su Nam Lee;Andrew Lin;Damini Dey;Daniel S. Berman;Donghee Han
Korean Journal of Radiology
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제25권6호
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pp.518-539
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2024
Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.
Objective: To evaluate circularity as a quantitative shape factor of small renal tumor on computed tomography (CT) in differentiating fat-poor angiomyolipoma (AML) from renal cell carcinoma (RCC). Materials and Methods: In 257 consecutive patients, 257 pathologically confirmed renal tumors (either AML or RCC less than 4 cm), which did not include visible fat on unenhanced CT, were retrospectively evaluated. A radiologist drew the tumor margin to measure the perimeter and area in all the contrast-enhanced axial CT images. In each image, a quantitative shape factor, circularity, was calculated using the following equation: 4 x π x (area ÷ perimeter2). The median circularity (circularity index) was adopted as a representative value in each tumor. The circularity index was compared between fat-poor AML and RCC, and the receiver operating characteristic (ROC) curve analysis was performed. Univariable and multivariable binary logistic regression analysis was performed to determine the independent predictor of fat-poor AML. Results: Of the 257 tumors, 26 were AMLs and 231 were RCCs (184 clear cell RCCs, 25 papillary RCCs, and 22 chromophobe RCCs). The mean circularity index of AML was significantly lower than that of RCC (0.86 ± 0.04 vs. 0.93 ± 0.02, p < 0.001). The mean circularity index was not different between the subtypes of RCCs (0.93 ± 0.02, 0.92 ± 0.02, and 0.92 ± 0.02 for clear cell, papillary, and chromophobe RCCs, respectively, p = 0.210). The area under the ROC curve of circularity index was 0.924 for differentiating fat-poor AML from RCC. The sensitivity and specificity were 88.5% and 90.9%, respectively (cut-off, 0.90). Lower circularity index (≤ 0.9) was an independent predictor (odds ratio, 41.0; p < 0.001) for predicting fat-poor AML on multivariable logistic regression analysis. Conclusion: Circularity is a useful quantitative shape factor of small renal tumor for differentiating fat-poor AML from RCC.
Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.
Kim, Dong-Wook;Kim, Hee-Joung;Haijo Jung;Soonil Hong;Yoo, Young-Il;Kim, Dong-Hyeon;Kim, Kee-Deog
Proceedings of the Korean Society of Medical Physics Conference
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한국의학물리학회 2002년도 Proceedings
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pp.506-508
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2002
As an advancement of medical imaging modalities and analyzing software with multi-function, active researches to acquire high contrast and high resolution image being done. In recently, development of medical imaging modalities like as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) is aiming to display anatomical structure more accuracy and faster. Thus, one of the important areas in CT today is the use of CT scanner for the quantitative evaluation of 3-D reconstruction images from 2-D tomographic images. In CT system, the effective slice thickness and the quality of 3-D reconstructed image will be influenced by imaging acquisition parameters (e.g. pitch and scan mode). In diagnosis and surgical planning, the accurate distance measurements of 3-D anatomical structures play an important role and the accuracy of distance measurements will depend on the acquisition parameters such as slice thickness, pitch, and scan mode. The skull phantom was scanned with SDCT for various acquisition parameters and acquisition slice thicknesses were 3 and 5 mm, and reconstruction intervals were 1, 2, and 3 mm to each pitch. 3-D visualizations and distance measurements were performed with PC based 3-D rendering and analyzing software. Results showed that the image quality and the measurement accuracy of 3-D SDCT images are independent to the reconstruction intervals and pitches.
Hwang, Eunjin;Antony, Chermaine Deepa;Choi, Jung-Ah;Kim, Minsu;Khil, Eun Kyoung;Choi, Il
Investigative Magnetic Resonance Imaging
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제25권2호
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pp.109-117
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2021
Purpose: To investigate the reliability of CT and MRI for quantitative and qualitative analyses of lumbar paraspinal muscle fatty infiltration (PSFI) and correlation of PSFI with intervertebral disc pathology. Materials and Methods: Lumbar spine CT and MRI of 36 subjects were reviewed retrospectively. Two observers independently outlined lumbar paraspinal muscles at each mid-intervertebral disc level. Paraspinal muscles on CT and MRI were graded according to the Goutallier grading system (GGS). The area, mean value, and standard deviation (SD) of the Hounsfield unit (HU) were obtained. Intervertebral discs were assessed on axial image of T2WI at each level. Correlations between qualitative and quantitative data and intervertebral disc pathology, age, and sex were evaluated. Results: Inter- and intra-observer agreements for results of GGS on MRI were substantial (κ = 0.79) and moderate (κ = 0.59), respectively. Inter- and intra-observer agreements for results of GGS on CT were almost perfect (κ = 0.88) and substantial (κ = 0.66), respectively. Quantitative measurements of HU showed almost perfect inter- and intra-observer reliabilities (κ = 0.82 and κ = 0.99, respectively). There were statistically significant correlations between intervertebral disc pathology and PSFI at L1-2, L2-3, and L4-5 levels on MRI and at L1-2 and L3-4 levels on CT. Age showed significant correlation with results of GGS at all levels on CT and MRI. Conclusion: This study showed that GGS results and HU measurements could be useful for evaluating PSFI because they showed correlations with intervertebral disc pathology results at certain levels.
The uterus, one of women's reproductive organs, is also closely related to women's health. Among them, hemorrhagic luteal cysts, one of the causes of pelvic pain that women often experience, were observed through CT and ultrasound, and the quality of images was evaluated through quantitative and qualitative evaluations. This study sought to find out whether the test method is more helpful to patients during CT and ultrasound. This study was conducted on 15 adolescent women and 15 adult women(21.31±3.45 average age). The equipment used for filming used EC3-10X (3~10 MHZ) and Philips Mx8000 iCT 256 among Endocavity Probes among Ecube Platinum. After setting a constant ROI on the cyst and the interface as a quantitative analysis method, SNR and CNR values were measured on a 5-point scale based on image quality, lesion clarity, image distortion, clarity of the interface, and motion artifacts (p<0.05). Independent t-test and Mann Whiteny U were performed, and the statistical program used was noted when SPSS (Version 22.0 for windows software package, Chicago, IL, USA) was statistically less than 0.05. Comparing the SNR and CNR values for this experiment, it can be seen that the SNR value was higher in the case of CT images(p<0.05). As a result of the qualitative evaluation, the quality of the image, the clarity of the lesion, the distortion of the image, the clarity of the interface, and the clarity of the boundary were measured on a 5-point scale based on the movement artifact. Comparing each score, CT images scored higher with a finer difference than ultrasound images(p<0.05). In conclusion, both test methods showed excellent results in finding the patient's lesions. However, in quantitative and qualitative evaluations, CT produced higher results in detecting lesions than ultrasound. However, for cyst tests that require continuous observation, ultrasonography, a non-invasive method that is advantageous for patients, will be clinically useful. Therefore, observing the patient's lesions by appropriately distributing these two test methods will provide optimal diagnostic information. These results will be useful for providing clinical basic data and educational materials to CT and US users in the future.
Purpose: To evaluate the effect of the slice thickness and the size of region of interest (ROI) on CT number using quantitative CT phantom Materials and Methods: The phantom containing 150 mg/cc, 75 mg/cc and 0 mg/cc calcium hydroxyapatite was scanned with 1, 3, 5 and 10 mm slice thicknesses by single energy quantitative computed tomography (QCT). CT numbers were measured on center position of the phantom. Shape of ROI was circular and sizes were 1, 3, 5, 11, 16, 21, 26 and 33 mm². ANOVA and Tukey's multiple comparison method were performed for statistical comparison of CT numbers according to different slice thicknesses. Coefficient of variation of CT number measured in each size of ROI was evaluated in same slice thickness. Results : CT numbers had statistically significant difference according to slice thicknesses (p<0.05). As the slice thickness increased, CT number also increased. As the density of phantom became lower and the size of ROI became smaller, the coefficient of variation of CT number increased. When the size of ROI was more than 11 mm² in 1 mm slice thickness, 5 mm² in 3 mm slice thickness and 3 mm² in 5 mm slice thickness, the coefficient of variation became consistent. In 10 mm slice thickness, the size of ROI had little effect on the coefficient of variation. Conclusion: CT number had variation according to the slice thickness and the size of ROI although the object was homogeneous. The slice thickness and the size of ROI are critical factors in precision of the CT number measurements.
The purpose of this study is to evaluate the relationship between osteoporotic postmenopausal women and its bone mineral density value by using the single energy quantitative CT. 1. Decreasing BMD with age is evident. There is a significant low BMD value in the osteoporotic women compared with the healthy subgroup. 2. BMD decrease from T12 to L4, except in healthy premenopausal women. 3. Relationship of spinal BMD expressed as average BMD of T12 through L4 Show strong correlation with mean BMD in all vertebral levels. 4. There are significantly different BMD value from T12 through L4 in subgroup 1, 2, 3 but there is no statistically significant difference between subgroup 2 and 3. Conclusion, There is a significant decreasing BMD with age but it is difficult to differentiate postmenopausal relatively healthy women from osteoporotic women by BMD.
Sparse-view computed tomography (CT) imaging technique is able to reduce radiation dose, ensure the uniformity of image characteristics among projections and suppress noise. However, the reconstructed images obtained by the sparse-view CT imaging technique suffer from severe artifacts, resulting in the distortion of image quality and internal structures. In this study, we proposed a convolutional neural network (CNN) with wavelet transformation and residual learning for reducing artifacts in sparse-view CT image, and the performance of the trained model was quantitatively analyzed. The CNN consisted of wavelet transformation, convolutional and inverse wavelet transformation layers, and input and output images were configured as sparse-view CT images and residual images, respectively. For training the CNN, the loss function was calculated by using mean squared error (MSE), and the Adam function was used as an optimizer. Result images were obtained by subtracting the residual images, which were predicted by the trained model, from sparse-view CT images. The quantitative accuracy of the result images were measured in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The results showed that the trained model is able to improve the spatial resolution of the result images as well as reduce artifacts in sparse-view CT images effectively. Also, the trained model increased the PSNR and SSIM by 8.18% and 19.71% in comparison to the imaging model trained without wavelet transformation and residual learning, respectively. Therefore, the imaging model proposed in this study can restore the image quality of sparse-view CT image by reducing artifacts, improving spatial resolution and quantitative accuracy.
Objective: Computed tomography (CT) is an established method for the diagnosis, staging, and treatment of multiple myeloma. Here, we investigated the potential of photon-counting detector computed tomography (PCD-CT) in terms of image quality, diagnostic confidence, and radiation dose compared with energy-integrating detector CT (EID-CT). Materials and Methods: In this prospective study, patients with known multiple myeloma underwent clinically indicated whole-body PCD-CT. The image quality of PCD-CT was assessed qualitatively by three independent radiologists for overall image quality, edge sharpness, image noise, lesion conspicuity, and diagnostic confidence using a 5-point Likert scale (5 = excellent), and quantitatively for signal homogeneity using the coefficient of variation (CV) of Hounsfield Units (HU) values and modulation transfer function (MTF) via the full width at half maximum (FWHM) in the frequency space. The results were compared with those of the current clinical standard EID-CT protocols as controls. Additionally, the radiation dose (CTDIvol) was determined. Results: We enrolled 35 patients with multiple myeloma (mean age 69.8 ± 9.1 years; 18 [51%] males). Qualitative image analysis revealed superior scores (median [interquartile range]) for PCD-CT regarding overall image quality (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), edge sharpness (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), image noise (4.0 [4.0-4.0] vs. 3.0 [3.0-4.0]), lesion conspicuity (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), and diagnostic confidence (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]) compared with EID-CT (P ≤ 0.004). In quantitative image analyses, PCD-CT compared with EID-CT revealed a substantially lower FWHM (2.89 vs. 25.68 cy/pixel) and a significantly more homogeneous signal (mean CV ± standard deviation [SD], 0.99 ± 0.65 vs. 1.66 ± 0.5; P < 0.001) at a significantly lower radiation dose (mean CTDIvol ± SD, 3.33 ± 0.82 vs. 7.19 ± 3.57 mGy; P < 0.001). Conclusion: Whole-body PCD-CT provides significantly higher subjective and objective image quality at significantly reduced radiation doses than the current clinical standard EID-CT protocols, along with readily available multi-spectral data, facilitating the potential for further advanced post-processing.
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