Naoki Sugihara

Adaptive Iterative Dose Reduction Using 3D Processing for Reduced- and Low-Dose Pulmonary CT: Comparison With Standard-Dose CT for Image Noise Reduction and Radiological Findings

OBJECTIVE The purpose of this study was to determine the utility of adaptive iterative dose reduction using 3D processing (AIDR 3D) for image noise reduction and assessment of radiologic findings obtained with reduced- and low-dose chest CT in patients with various pulmonary diseases. SUBJECTS AND METHODS Chest CT examinations at three different tube current settings and using 16- and 64-MDCT scanners were performed for 37 patients. Standard-dose (150 mAs) data were reconstructed as thin-section CT without AIDR 3D, and low-dose (25 mAs) and reduced-dose (50 mAs) data were reconstructed as thin-section CT without and with AIDR 3D. To compare image quality, image noises at all CT doses were quantitatively assessed by region of interest measurements. For comparison of radiologic finding assessments, likelihoods of occurrence of emphysema, ground-glass opacity, reticular opacity, bronchiectasis, honeycomb pattern, and nodules were evaluated on a 5-point scale. Then, image noise and agreements of radiologic findings between standard-dose CT and others were statistically evaluated. RESULTS The image quality scores of reduced- and low-dose CT without AIDR 3D were significantly lower than those of both protocols with AIDR 3D and standard-dose CT (p<0.05). All intermethod agreements for emphysema, ground-glass opacity, bronchiectasis, honeycomb pattern, and nodules, except for those observed on low-dose CT without AIDR 3D, were almost perfect (κ>0.81). CONCLUSION AIDR 3D is useful for image noise reduction and assessment of radiologic findings obtained with reduced- and low-dose CT for patients with various pulmonary diseases.

Emphysema quantification by low-dose CT: potential impact of adaptive iterative dose reduction using 3D processing.

OBJECTIVE The purpose of this study is to investigate the effect of a novel reconstruction algorithm, adaptive iterative dose reduction using 3D processing, on emphysema quantification by low-dose CT. MATERIALS AND METHODS Twenty-six patients who had undergone standard-dose (150 mAs) and low-dose (25 mAs) CT scans were included in this retrospective study. Emphysema was quantified by several quantitative measures, including emphysema index given by the percentage of lung region with low attenuation (lower than -950 HU), the 15th percentile of lung density, and size distribution of low-attenuation lung regions, on standard-dose CT images reconstructed without adaptive iterative dose reduction using 3D processing and on low-dose CT images reconstructed both without and with adaptive iterative dose reduction using 3D processing. The Bland-Altman analysis was used to assess whether the agreement between emphysema quantifications on low-dose CT and on standard-dose CT was improved by the use of adaptive iterative dose reduction using 3D processing. RESULTS For the emphysema index, the mean differences between measurements on low-dose CT and on standard-dose CT were 1.98% without and -0.946% with the use of adaptive iterative dose reduction using 3D processing. For 15th percentile of lung density, the mean differences without and with adaptive iterative dose reduction using 3D processing were -6.67 and 1.28 HU, respectively. For the size distribution of low-attenuation lung regions, the ranges of the mean relative differences without and with adaptive iterative dose reduction using 3D processing were 21.4-85.5% and -14.1% to 11.2%, respectively. For 15th percentile of lung density and the size distribution of low-attenuation lung regions, the agreement was thus improved by the use of adaptive iterative dose reduction using 3D processing. CONCLUSION The use of adaptive iterative dose reduction using 3D processing resulted in greater consistency of emphysema quantification by low-dose CT, with quantification by standard-dose CT.

Hepatic CT perfusion measurements: a feasibility study for radiation dose reduction using new image reconstruction method.

OBJECTIVES To assess the effects of image reconstruction method on hepatic CT perfusion (CTP) values using two CT protocols with different radiation doses. MATERIALS AND METHODS Sixty patients underwent hepatic CTP and were randomly divided into two groups. Tube currents of 210 or 250 mA were used for the standard dose group and 120 or 140 mA for the low dose group. The higher currents were selected for large patients. Demographic features of the groups were compared. CT images were reconstructed by using filtered back projection (FBP), image filter (quantum de-noising, QDS), and adaptive iterative dose reduction (AIDR). Hepatic arterial and portal perfusion (HAP and HPP, ml/min/100ml) and arterial perfusion fraction (APF, %) were calculated using the dual-input maximum slope method. ROIs were placed on each hepatic segment. Perfusion and Hounsfield unit (HU) values, and image noises (standard deviations of HU value, SD) were measured and compared between the groups and among the methods. RESULTS There were no significant differences in the demographic features of the groups, nor were there any significant differences in mean perfusion and HU values for either the groups or the image reconstruction methods. Mean SDs of each of the image reconstruction methods were significantly lower (p<0.0001) for the standard dose group than the low dose group, while mean SDs for AIDR were significantly lower than those for FBP for both groups (p=0.0006 and 0.013). Radiation dose reductions were approximately 45%. CONCLUSIONS Image reconstruction method did not affect hepatic perfusion values calculated by dual-input maximum slope method with or without radiation dose reductions. AIDR significantly reduced images noises.

Emphysema Quantification by Combining Percentage and Size Distribution of Low-Attenuation Lung Regions

OBJECTIVE The purpose of this study was to investigate efficacy of two types of emphysema quantification: percentage of low-attenuation lung regions (%LA); and size distribution of these regions. On a log-log plot, cumulative frequency-size distribution of low-attenuation lung regions can be fitted by a straight line whose slope (D) has been reported to reflect diffusing capacity. In this study, %LA and D were compared with pulmonary function test (PFT) parameters, especially with ratio of diffusing capacity of carbon monoxide to effective alveolar ventilation (i.e., DLCO/VA). MATERIALS AND METHODS Thin-section unenhanced CT images were acquired from 30 patients (25 men, five women; mean [SD] age, 70.1 ± 12.1 years), of whom 25 had received diagnosis of COPD, and %LA and D were calculated at 20 thresholds, ranging from -995 to -900 HU. To determine utility of %LA and D, we used Pearsons correlation for emphysema quantification and PFT. Significance of the coefficients was determined with Bonferroni correction (p < 0.0025). Finally, the relationships between emphysema quantification and DLCO/VA were examined by linear models and Akaike information criterion (AIC). RESULTS The correlation coefficients for %LA and DLCO/VA were statistically significant at all the thresholds (optimal coefficient, -0.761). The correlation coefficients for D and DLCO/VA were statistically significant at the thresholds from -945 to -900 HU (optimal coefficient, -0.646). AIC values showed that the most accurate prediction of DLCO/VA was obtained by the model incorporating both %LA and D. CONCLUSION Both %LA and D showed significant correlation with DLCO/VA. Combining %LA and D resulted in more accurate evaluation of DLCO/VA than did using %LA or D alone.

Comparison of computer-aided detection (CADe) capability for pulmonary nodules among standard-, reduced- and ultra-low-dose CTs with and without hybrid type iterative reconstruction technique

PURPOSE To directly compare the effect of a reconstruction algorithm on nodule detection capability of the computer-aided detection (CADe) system using standard-dose, reduced-dose and ultra-low dose chest CTs with and without adaptive iterative dose reduction 3D (AIDR 3D). MATERIALS AND METHODS Our institutional review board approved this study, and written informed consent was obtained from each patient. Standard-, reduced- and ultra-low-dose chest CTs (250 mA, 50 mA and 10 mA) were used to examine 40 patients, 21 males (mean age ± standard deviation: 63.1 ± 11.0 years) and 19 females (mean age, 65.1 ± 12.7 years), and reconstructed as 1 mm-thick sections. Detection of nodule equal to more than 4 mm in dimeter was automatically performed by our proprietary CADe software. The utility of iterative reconstruction method for improving nodule detection capability, sensitivity and false positive rate (/case) of the CADe system using all protocols were compared by means of McNemars test or signed rank test. RESULTS Sensitivity (SE: 0.43) and false-positive rate (FPR: 7.88) of ultra-low-dose CT without AIDR 3D was significantly inferior to those of standard-dose CTs (with AIDR 3D: SE, 0.78, p < .0001, FPR, 3.05, p < .0001; and without AIDR 3D: SE, 0.80, p < .0001, FPR: 2.63, p < .0001), reduced-dose CTs (with AIDR 3D: SE, 0.81, p < .0001, FPR, 3.05, p < .0001; and without AIDR 3D: SE, 0.62, p < .0001, FPR: 2.95, p < .0001) and ultra-low-dose CT with AIDR 3D (SE, 0.79, p < .0001, FPR, 4.88, p = .0001). CONCLUSION The AIDR 3D has a significant positive effect on nodule detection capability of the CADe system even when radiation dose is reduced.

Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study

Background Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention. Purpose To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom. Material and Methods A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270–10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference. Results SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05). Conclusion In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.

Dynamic Contrast-Enhanced Perfusion Area-Detector CT: Preliminary Comparison of Diagnostic Performance for N Stage Assessment With FDG PET/CT in Non–Small Cell Lung Cancer

OBJECTIVE The objective of our study was to directly compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion area-detector CT (ADCT) and FDG PET/CT for differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with non-small cell lung carcinoma (NSCLC). SUBJECTS AND METHODS Seventy-seven consecutive patients, 45 men (mean age ± SD, 70.4 ± 5.9 years) and 32 women (71.2 ± 7.7 years), underwent dynamic first-pass CE-perfusion ADCT at two or three different positions for covering the entire thorax, FDG PET/CT, surgical treatment, and pathologic examination. From all ADCT data for each of the subjects, a whole-chest perfusion map was computationally generated using the dual- and single-input maximum slope and Patlak plot methods. For quantitative N stage assessment, perfusion parameters and the maximum standardized uptake value (SUVmax) for each lymph node were determined by measuring the relevant ROI. ROC curve analyses were performed for comparing the diagnostic capability of each of the methods on a per-node basis. N stages evaluated by each of the indexes were then statistically compared with the final pathologic diagnosis by means of chi-square and kappa statistics. RESULTS The area under the ROC curve (Az) values of systemic arterial perfusion (Az = 0.89), permeability surface (Az = 0.78), and SUVmax (Az = 0.85) were significantly larger than the Az values of total perfusion (Az = 0.70, p < 0.05) and distribution volume (Az = 0.55, p < 0.05). For each of the threshold values, agreement for systemic arterial perfusion calculated using the dual-input maximum slope model was substantial (κ = 0.70, p < 0.0001), and agreement for SUVmax was moderate (κ = 0.60, p < 0.0001). CONCLUSION Dynamic first-pass CE-perfusion ADCT is as useful as FDG PET/CT for the differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with NSCLC.