Hepatic and pancreatic extracellular volume fraction analysis using contrast-enhanced CT in patients with diabetes mellitus and pre-diabetes.

PURPOSE: Liver and pancreatic fibrosis is associated with diabetes mellitus (DM), and liver fibrosis is associated with pancreatic fibrosis. This study aimed to investigate the relationship between the hepatic and pancreatic extracellular volume fractions (fECVs), which correlate with tissue fibrosis, and their relationships with DM and pre-DM (pDM). MATERIAL AND METHODS: We included 100 consecutive patients with known or suspected liver and/or pancreatic diseases who underwent contrast-enhanced CT. Patients were classified as nondiabetes, pDM, and DM with hemoglobin A1c (HbA1c) levels of < 5.7%, 5.7%-6.5%, and ≥ 6.5% or fasting plasma glucose (FPG) levels of < 100, 100-125 mg/dL, and ≥ 126 mg/dL, respectively. Subtraction images between unenhanced and equilibrium-phase images were prepared. The liver and the pancreas were automatically extracted using a high-speed, three-dimensional image analysis system, and their respective mean CT values were calculated. The enhancement degree of the aorta (Δaorta) was measured. fECV was calculated using the following equation: fECV = (100 - hematocrit) * Δliver or pancreas/Δaorta. Differences were investigated in hepatic and pancreatic fECVs among the three groups, and the correlation between each two in hepatic fECV, pancreatic fECV, and HbA1c was determined. RESULTS: The pancreatic fECV, which was positively correlated with the hepatic fECV and HbA1c (r = 0.51, P < 0.001, and r = 0.51, P < 0.001, respectively), significantly differed among the three groups (P < 0.001) and was significantly greater in DM than in pDM or nondiabetes and in pDM with nondiabetes (P < 0.001). Hepatic fECV was significantly greater in DM than in nondiabetes (P < 0.05). CONCLUSION: The pancreatic fECV and pDM/DM are closely related.

Pancreatic fibrosis by extracellular volume fraction using Contrast-enhanced computed tomography and relationship with pancreatic cancer.

PURPOSE: This study aimed to assess the relationship between pancreatic fibrosis measured by the extracellular volume fraction (ECV) using contrast-enhanced computed tomography (CT) and the histologic pancreatic fibrosis fraction and investigate the relationship between pancreatic fibrosis and pancreatic cancer. METHOD: The study included 88 consecutive patients (48 males, 40 females; median age, 69 years; range, 17-89 years); 47 had pancreatic cancer, and 41 had other diseases. Fifty-two cases were evaluated pathologically for pancreatic fibrosis. The histologic pancreatic fibrosis fraction was quantified using image analysis software in nontumorous pancreatic tissue at the resection stump using 2-µm-thick Azan-stained slides. Two board-certified radiologists measured ECV in the pancreatic parenchyma at an estimated transection line. The correlation between histologic pancreatic fibrosis fraction and ECV was investigated, and whether the ECV value could be used as a biomarker for pancreatic cancer was investigated. RESULTS: The histologic pancreatic fibrosis fraction was significantly correlated with the ECV (r = 0.64, P < 0.01). Pancreatic fibrosis evaluated by ECV was higher in pancreatic cancer patients than in other patients (P < 0.01). On receiver-operating characteristic curve analysis, the ECV had good diagnostic accuracy for the development of pancreatic cancer (cut-off value 32.8%; sensitivity 61.0%, specificity 85.1%). ECV was identified on multivariate analysis as an independent risk factor for pancreatic cancer (odds ratio 1.16; P < 0.01). CONCLUSIONS: Extracellular volume fraction was strongly related to the histologic pancreatic fibrosis fraction, which was independently associated with pancreatic cancer. Thus, extracellular volume fraction is an imaging biomarker that reflects the progression of pancreatic fibrosis and may potentially help predict the development of pancreatic cancer, although further investigation will be needed.

Visualization of small visceral arteries on abdominal CT angiography using ultra-high-resolution CT scanner.

PURPOSE: To evaluate the image quality and ability to delineate the small visceral arteries of high-resolution (HR) abdominal CT angiography (CTA) using an ultra-high-resolution computed tomography (UHR CT) scanner. MATERIALS AND METHODS: Thirty-seven patients were enrolled who underwent abdominal CTA using a UHR CT scanner. The images were reconstructed with a matrix of 1024 × 1024 and 0.25 mm thickness for HR CTA and with a matrix of 512 × 512 and 0.5 mm thickness for normal resolution (NR) CTA. Maximum CT value, image quality, and delineation of the small arteries were compared between HR CTA and NR CTA. RESULTS: HR CTA showed significantly higher maximum CT value, higher image quality, and better delineation of the small arteries than did NR CTA (P < .005). CONCLUSION: HR CTA using a UHR CT scanner showed higher image quality than NR CTA and enhanced the delineation of visceral arteries.

The effect of the reconstruction algorithm for the pulmonary nodule detection under the metal artifact caused by a pacemaker.

The aim was to compare the effects of metal artifacts from a pacemaker on pulmonary nodule detection among computed tomography (CT) images reconstructed using filtered back projection (FBP), single-energy metal artifact reduction (SEMAR), and forward-projected model-based iterative reconstruction solution (FIRST).Nine simulated nodules were placed inside a chest phantom with a pacemaker. CT images reconstructed using FBP, SEMAR, and FIRST were acquired at low and standard dose, and were evaluated by 2 independent radiologists.FIRST demonstrated the most significantly improved metal artifact and nodule detection on low dose CT (P < .0032), except at 10 mA and 5-mm thickness. At standard-dose CT, SEMAR showed the most significant metal artifact reduction (P < .00001). In terms of nodule detection, no significant differences were observed between FIRST and SEMAR (P = .161).With a pacemaker present, FIRST showed the best nodule detection ability at low-dose CT and SEMAR is comparable to FIRST at standard dose CT.

Volumetric analysis of the thymic epithelial tumors: correlation of tumor volume with the WHO classification and Masaoka staging.

BACKGROUND: The purpose of our study was to investigate the correlation between tumor volume (TV) and each subtype of thymic epithelial tumors (TETs) based on the World Health Organization (WHO) classification and Masaoka staging. METHODS: Sixty-one consecutive patients (45 thymomas and 16 thymic carcinomas) were studied. All were classified according to Masaoka staging: 31 non-invasive TETs (stage I) and 30 invasive TETs (8 stage II, 11 stage III, 3 stage IVa, and 8 stage IVb). TV on computed tomography (CT) were semi-automatically calculated using our software. The correlation of TV with each WHO subtype and Masaoka staging was analyzed using Mann-Whitney U and Scheffe's F test. RESULTS: Thymic carcinoma (mean ± SD, 117.5±143.6 cm3) was significantly larger than thymoma (53.4±78.4 cm3) (P=0.0016). Stage IVb tumor (190.8±156.8 cm3) was significantly larger than stage I (33.1±42.6 cm3) (P<0.05). Invasive TETs were significantly larger than non-invasive TETs (P=0.0016). TV >54.3 cm3 indicated invasive TETs. CONCLUSIONS: TV of invasive TETs may be larger at the time of initial presentation. TV >54.3 cm3 indicates invasive TETs.

Effects of reconstruction technique on the quality of abdominal CT angiography: A comparison between forward projected model-based iterative reconstruction solution (FIRST) and conventional reconstruction methods.

PURPOSE: This study aimed to compare the quality of abdominal CT angiography (CTA) images obtained using conventional reconstruction algorithms with those obtained using a novel iterative algorithm (forward projected model-based iterative reconstruction solution, FIRST) for evaluating arteries in the abdomen. MATERIALS AND METHODS: Abdominal CTA images from 60 patients (M:F = 27:33; mean age, 62.4 ± 16.7 years) were reconstructed using three algorithms - filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR 3D), and FIRST. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the abdominal aorta, celiac trunk, superior mesenteric, renal, and right hepatic arteries were objectively evaluated via region-of-interest analysis and compared using the one-way analysis of variance test. Two radiologists independently scored and selected the best (score 3), second best (score 2), and the worst (score 1) images based on the visual image quality of peripheral arteries. Wilcoxon signed rank test was used for comparing image quality scores. RESULTS: FIRST and AIDR 3D significantly reduced image noise compared with FBP (P < 0.001). SNR and CNR were significantly higher with AIDR 3D and FIRST than with FBP reconstruction (P < 0.001), with FIRST displaying the highest CNR (14.31 ± 4.17) for the right hepatic artery than the other two methods (P < 0.05). Both radiologists scored FIRST images as having the best image quality among the three methods for peripheral abdominal artery evaluation (3.0 ± 0.0, P < 0.001). CONCLUSION: FIRST reconstruction yielded superior abdominal CTA images as compared with FBP or AIDR 3D reconstruction.

Phantom Study of In-Stent Restenosis at High-Spatial-Resolution CT.

Purpose To examine the diagnostic performance of high-spatial-resolution (HSR) CT with 0.25-mm section thickness for evaluating renal artery in-stent restenosis. Materials and Methods A 0.05-mm wire phantom and vessel phantoms with renal stents with in-stent stenotic sections of varying diameters were scanned with both an HSR CT scanner equipped with 160-section multi-detector rows (0.25-mm section thickness) and a conventional CT scanner. The wire phantom was used to analyze modulation transfer function (MTF). With the vessel phantoms, the error rates were calculated as the absolute difference between the measured diameters and true diameters divided by the true diameters at the narrowing sections. For qualitative evaluation, overall image quality and diagnostic accuracy for evaluating stenosis in three stages were assessed by two radiologists. Statistical analyses included the paired t test, Wilcoxon signed-rank test, and McNemar test. Results HSR CT achieved 24.3 line pairs per centimeter ± 0.5 (standard deviation) and 29.1 line pairs per centimeter ± 0.4 at 10% and 2% MTF, respectively; and conventional CT was 12.5 line pairs per centimeter ± 0.1 and 14.3 line pairs per centimeter ± 0.1 at 10% and 2% MTF, respectively. The mean error rate of the measured diameter at HSR CT (8.0% ± 5.8) was significantly lower than that at at conventional CT (16.9% ± 9.3; P < .001). Image quality at HSR CT was significantly better than that at conventional CT (P < .001), but HSR CT was not significantly superior to conventional CT in terms of diagnostic accuracy. Conclusion Compared with conventional CT, high-spatial-resolution CT achieved spatial resolutions of up to 29 line pairs per centimeter at 2% modulation transfer function and yielded improved measurement accuracy for the evaluation of in-stent restenosis in a phantom study of renal artery stents. Published under a CC BY 4.0 license.

Low-Dose Pelvic Computed Tomography Using Adaptive Iterative Dose Reduction 3-Dimensional Algorithm: A Phantom Study.

OBJECTIVE: To evaluate the image quality and radiation dose reduction in pelvic computed tomography (CT) achieved with an adaptive iterative dose reduction 3-dimensional (AIDR 3D) algorithm using a phantom model. METHODS: Two phantoms were scanned using a 320-detector row CT scanner with 8 tube current levels, and the images were reconstructed with a standard filtered back projection (FBP) algorithm and with an AIDR 3D algorithm. RESULTS: Compared with FBP, AIDR 3D reduced image noise and improved contrast-to-noise ratios. The diagnostic performance for detection of low-contrast targets of AIDR 3D images obtained with 100 mA at 120 kVp was almost as good as that of the FBP images obtained with 200 mA. CONCLUSIONS: The AIDR 3D algorithm substantially reduced image noise and improved the image quality of pelvic CT images compared with those obtained with the FBP algorithm and can thus be considered a promising technique for low-dose pelvic CT examinations.

Abundant epicardial adipose tissue surrounding the left atrium predicts early rather than late recurrence of atrial fibrillation after catheter ablation.

PURPOSE: Epicardial adipose tissue (EAT) surrounding the left atrium has been reported to have a pro-arrhythmic influence on atrial myocardium and to play an important role in the pathophysiology of atrial fibrillation (AF). The purpose of this study was to explore whether the abundance of EAT correlates with early and late recurrences of AF after ablation. METHODS: We included 53 consecutive patients with drug-refractory AF scheduled for ablation. Early and late recurrences were defined as atrial tachyarrhythmias within and after 3 months following the ablation procedure, respectively. The total and left atrial EAT volumes were obtained by 320-detector-row multislice computed tomography. RESULTS: During a follow-up period of 16 ± 4 months, early and late recurrences occurred in 29 (55 %) and 12 (23 %) patients, respectively. The left atrial EAT volume was larger in patients with than without early recurrence (35.1 ± 13.1 vs. 25.0 ± 9.5 cm(3), p = 0.002); however, there was no difference in the total EAT volume between the two groups (98.5 ± 45.7 vs. 94.5 ± 35.2 cm(3), p = 0.72). A multivariate analysis revealed that a large left atrial EAT volume, persistent AF, and large left atrial volume were independent predictors of early recurrence. Conversely, there was no significant difference in left atrial (29.3 ± 14.6 vs. 29.7 ± 11.7 cm(3), p = 0.93) and total EAT (91.0 ± 50.1 vs. 97.9 ± 37.0 cm(3), p = 0.66) volumes between patients with and without late recurrence. CONCLUSIONS: The abundance of left atrial EAT independently predicted early recurrence after AF ablation; on the contrary, it did not have an impact on late recurrence. Left atrial EAT may have a pro-arrhythmic influence, especially in the early post-ablation phase.

Arterial contour detectability in head CT angiography.

PURPOSE: Arterial contour extraction is essential for visualization and analysis of vasculature in CT angiography (CTA). A means for evaluating the detectability of artery contours CTA images is required. We developed and tested a new method for this purpose based on phase information from two-dimensional Fourier transforms of CTA images. The relationship between arterial contour detectability and a patient's ocular lens dose was evaluated in CTA images obtained with various tube voltages and currents. METHODS: A head phantom was designed for use as a target object containing a simulated vascular tree, filled with dilute contrast medium (10 mg iodine/ml). The head phantom was scanned using a 64-multidetector CT scanner with tube voltages of 80-140 kV and tube currents corresponding to volume CT dose index [Formula: see text] ranging from 24.4 to 72.8 mGy. Lens doses were measured using the planar silicon PIN-photodiode system. The quality of artery contours in the CTA source images was assessed using a computed detectability index. RESULTS: Lens dose increased proportionally with tube voltage and current. The use of 80 kV provided the highest contour detectability. However, for each tube voltage, the detectability of artery contours was almost constant across the CTDI(vol) values. These results were mostly consistent with the subjective recognition of artery contours on CTA images. CONCLUSIONS: A CTA protocol using 80 kV and 420 mA can reduce the radiation exposure to ocular lens by approximately 40 %, and improve the artery contour detectability compared with a routine protocol.

A detection method for streak artifacts and radiological noise in a non-uniform region in a CT image.

By using the CT images obtained by subtracting two CT images acquired under the same conditions and slice locations, we have devised a method for detecting streak artifacts in non-uniform regions and only radiological noise components in CT images. A chest phantom was scanned using 16- and 64-multidetector row helical CT scanners with various mAs values at 120kVp. The upper lung slice image was employed as a target image for evaluating the streak artifacts and radiological noise. One hundred parallel line segments with a length of 80 pixels were placed on the subtracted CT image, and the largest CT value in each CT value profile was employed as a feature variable of the streak artifacts; these feature variables were analyzed with the extreme value theory (Gumbel distribution). To detect only the radiological noise, all CT values contained in the 100 line profile were plotted on normal probability paper and the standard deviation was estimated from the inclination of its fitted line for the CT value plots. The two detection methods devised in this study were able to evaluate the streak artifacts and radiological noise in the CT images with high accuracy.

Quantitative assessment of image noise and streak artifact on CT image: comparison of z-axis automatic tube current modulation technique with fixed tube current technique.

The purpose of our study is to quantitatively assess the effects of z-axis automatic tube current modulation technique on image noise and streak artifact, by comparing with fixed tube current technique. Standard deviation of CT-values was employed as a physical index for evaluating image noise, and streak artifact was quantitatively evaluated using our devised Gumbel evaluation method. z-Axis automatic tube current modulation technique will improve image noise and streak artifact, compared with fixed tube current technique, and will make it possible to significantly reduce radiation doses at lung levels while maintaining the same image quality as fixed tube current technique.

Statistical characteristics of streak artifacts on CT images: relationship between streak artifacts and mA s values.

The purpose of this study is to investigate how streak artifacts on computed tomography (CT) images vary with reduction in radiation doses by assessing the quantitative relationship between the streak artifacts and milliampere-time product (mA s) values. A commercially available chest phantom was used to measure the streak artifacts on the CT images obtained using a 4- and 16-multidetector-row helical CT scanners with various mA s values at a constant tube voltage of 120 kVp. The cardiac slice image was employed as a target image for evaluating the streak artifacts on the CT image. Eighty parallel line segments with a length of 20 pixels were placed perpendicular to numerous streak artifacts on the cardiac slice image, and the largest difference between adjacent CT values in each of the 80 CT-value profiles of these line segments was employed as a feature variable of streak artifacts; these feature variables have been analyzed by the extreme value theory. The largest difference between adjacent CT values in each CT-value profile can be statistically modeled by a Gumbel distribution. Further, the maximum level of streak artifacts on CT images that will be tolerated for clinical use and low-dose CT screening examination was expected to be estimated using the location parameter in the Gumbel distribution.

Fractal-feature distance as a substitute for observer performance index in contrast-detail examination.

PURPOSE: To assess whether or not the fractal-feature distance using the box-counting algorithm can be a substitute for observer performance index. METHODS AND MATERIALS: Contrast-detail (C-D) phantom images were obtained at various mAs-values (0.5-4.0 mAs) and 140 kV(p) with a Fuji computed radiography system, and the reference image was acquired at 50 mAs; all cylindrical targets in the C-D phantom were visualized on this image. The C-D images were converted to binary images using the profile curves around the smallest cylindrical target images on the reference images. The fractal analysis was conducted using the box-counting algorithm for these binary images. The fractal-feature distances between the low-dose and reference images were calculated using the fractal dimension and the complexity. Furthermore, we performed the C-D analysis in which ten radiologists participated, and compared the fractal-feature distances with the image quality figures (IQF) derived from the C-D analysis with Markov chain. RESULTS: For all C-D phantom radiographs, the relationship between the length of the square boxes and the number of boxes to cover the positive pixels of the binary image was linear on a log-log scale (r>or=0.999). A strong linear correlation was found between the fractal-feature distance and IQF (r=0.990). CONCLUSION: We have shown that the binary image of C-D phantom can be analyzed by the box-counting algorithm and its fractal-feature distance increases as the radiation dose decreases. Furthermore, we have shown that the fractal-feature distances will be equivalent to IQFs in C-D analysis.

Quantitative assessment of the influence of anatomic noise on the detection of subtle lung nodule in digital chest radiography using fractal-feature distance.

PURPOSE: To confirm whether or not the influence of anatomic noise on the detection of nodules in digital chest radiography can be evaluated by the fractal-feature distance. MATERIALS AND METHODS: We used the square images with and without a simulated nodule which were generated in our previous observer performance study; the simulated nodule was located on the upper margin of a rib, the inside of a rib, the lower margin of a rib, or the central region between two adjoining ribs. For the square chest images, fractal analysis was conducted using the virtual volume method. The fractal-feature distances between the considered and the reference images were calculated using the pseudo-fractal dimension and complexity, and the square images without the simulated nodule were employed as the reference images. We compared the fractal-feature distances with the observer's confidence level regarding the presence of a nodule in plain chest radiograph. RESULTS: For all square chest images, the relationships between the length of the square boxes and the mean of the virtual volumes were linear on a log-log scale. For all types of the simulated nodules, the fractal-feature distance was the highest for the simulated nodules located on the central region between two adjoining ribs and was the lowest for those located in the inside of a rib. The fractal-feature distance showed a linear relation to an observer's confidence level. CONCLUSION: The fractal-feature distance would be useful for evaluating the influence of anatomic noise on the detection of nodules in digital chest radiography.

Fractal-feature distance analysis of radiographic image.

RATIONALE AND OBJECTIVES: We have conducted a fractal analysis of low-dose digital chest phantom radiographs and evaluated the relationship between the fractal-feature distance and the tube current-exposure time product. MATERIALS AND METHODS: Chest phantom radiographs were obtained at various mAs values (0.5-4.0 mAs) and 140 kVp with a computed radiography system, and the reference images were acquired at 13 mAs. The lung field images were converted to binary images after processing them using the rolling-ball technique; a fractal analysis was conducted using the box-counting method for these binary images. The fractal-feature distances between the low-dose and reference images were calculated using the fractal dimension and the complexity. RESULTS: For all binary images of lung fields, the relationship between the length of the square boxes and the number of boxes needed to cover the positive pixels of the binary image was linear on a log-log scale (r > or = 0.99). For mAs > or = 3.0, the fractal-feature distances were almost constant, whereas for mAs < or = 2.5, they increased depending on the reduction in mAs values. CONCLUSION: We have shown that a binary image of the lung field obtained from a chest phantom radiograph can be analyzed by the box-counting method and that its fractal-feature distance grows as the radiation dose declines.