Song Soo Kim

Chronic Obstructive Pulmonary Disease: Lobe-based Visual Assessment of Volumetric CT by Using Standard Images—Comparison with Quantitative CT and Pulmonary Function Test in the COPDGene Study

PURPOSE To provide a new detailed visual assessment scheme of computed tomography (CT) for chronic obstructive pulmonary disease (COPD) by using standard reference images and to compare this visual assessment method with quantitative CT and several physiologic parameters. MATERIALS AND METHODS This research was approved by the institutional review board of each institution. CT images of 200 participants in the COPDGene study were evaluated. Four thoracic radiologists performed independent, lobar analysis of volumetric CT images for type (centrilobular, panlobular, and mixed) and extent (on a six-point scale) of emphysema, the presence of bronchiectasis, airway wall thickening, and tracheal abnormalities. Standard images for each finding, generated by two radiologists, were used for reference. The extent of emphysema, airway wall thickening, and luminal area were quantified at the lobar level by using commercial software. Spearman rank test and simple and multiple regression analyses were performed to compare the results of visual assessment with physiologic and quantitative parameters. RESULTS The type of emphysema, determined by four readers, showed good agreement (κ = 0.63). The extent of the emphysema in each lobe showed good agreement (mean weighted κ = 0.70) and correlated with findings at quantitative CT (r = 0.75), forced expiratory volume in 1 second (FEV(1)) (r = -0.68), FEV(1)/forced vital capacity (FVC) ratio (r = -0.74) (P < .001). Agreement for airway wall thickening was fair (mean κ = 0.41), and the number of lobes with thickened bronchial walls correlated with FEV(1) (r = -0.60) and FEV(1)/FVC ratio (r = -0.60) (P < .001). CONCLUSION Visual assessment of emphysema and airways disease in individuals with COPD can provide reproducible, physiologically substantial information that may complement that provided by quantitative CT assessment.

Development of an Automatic Classification System for Differentiation of Obstructive Lung Disease using HRCT

The motivation is to introduce new shape features and optimize the classifier to improve performance of differentiating obstructive lung diseases, based on high-resolution computerized tomography (HRCT) images. Two hundred sixty-five HRCT images from 82 subjects were selected. On each image, two experienced radiologists selected regions of interest (ROIs) representing area of severe centrilobular emphysema, mild centrilobular emphysema, bronchiolitis obliterans, or normal lung. Besides 13 textural features, additional 11 shape features were employed to evaluate the contribution of shape features. To optimize the system, various ROI size (16 × 16, 32 × 32, and 64 × 64 pixels) and other classifier parameters were tested. For automated classification, the Bayesian classifier and support vector machine (SVM) were implemented. To assess cross-validation of the system, a five-folding method was used. In the comparison of methods employing only the textural features, adding shape features yielded the significant improvement of overall sensitivity (7.3%, 6.1%, and 4.1% in the Bayesian and 9.1%, 7.5%, and 6.4% in the SVM, in the ROI size 16 × 16, 32 × 32, 64 × 64 pixels, respectively; t test, P < 0.01). After feature selection, most of cluster shape features were survived ,and the feature selected set shows better performance of the overall sensitivity (93.5 ± 1.0% in the SVM in the ROI size 64 × 64 pixels; t test, P < 0.01). Adding shape features to conventional texture features is much useful to improve classification performance of obstructive lung diseases in both Bayesian and SVM classifiers. In addition, the shape features contribute more to overall sensitivity in smaller ROI.

Acute and chronic complications of aortic intramural hematoma on follow-up computed tomography: incidence and predictor analysis.

Objective: To ascertain the incidence of acute and chronic complications of aortic intramural hematoma (IMH) and to analyze the predictors of the development of each complication. Materials and Methods: This retrospective study includes 107 consecutive patients diagnosed with aortic IMH by means of computed tomography (CT) during the period from January 1998 to December 2003 and followed up with serial CT examinations (median follow-up period, 320 days). There were 36 patients with type A and 71 with type B IMH. Initial and follow-up CT scans were reviewed, with special attention given to the development of complications, such as increase in the thickness of IMH, clinical and hemodynamic evolution requiring urgent surgery, and development of aortic dissection and/or aneurysm. If each complication developed within 30 days after the initial episode, we classified it as an acute complication; the others were classified as chronic complications. The time interval between the initial and the subsequent CT examination showing each complication was recorded. To identify the predictors of each complication, we analyzed the demographic and CT findings with regard to the following factors: age, sex, maximum thickness of the hematoma, maximum aortic diameter on initial CT examination, ulcerlike projection (ULP) on initial and follow-up CT examinations, and the degree of atherosclerosis. The Cox proportional hazards regression model with stepwise multivariate analyses was used to determine the significant predictors of each complication. Results: Sixteen patients had acute complications consisting of aortic dissection (n = 7), aortic aneurysm (n = 6), and acute clinical and hemodynamic evolution requiring operation (n = 3). Three additional patients with aortic dissection (n = 1) and aneurysm (n = 2) underwent emergency surgery. Twenty-three patients with chronic complications had aortic dissection (n = 3), and aortic aneurysm (n = 20). Cox proportional hazards regression model revealed that the maximal diameter of involved aorta is the only significant predictor of the development of acute complications (P = 0.006), whereas the age (P = 0.040), type A IMH (P = 0.015), presence of ULP (P = 0.015), and newly developed ULP as revealed on follow-up CT examination (P = 0.032) were significant predictors of the development of chronic complications. With regard to the aortic dissection in 10 patients (9.3%; type A/B ratio, 5:5; median time interval, 34 days), Cox proportional hazards regression model revealed that the maximal thickness of the hematoma is the only significant predictor (P = 0.018). Twenty-one saccular and 5 fusiform aneurysms (24.3%) developed, as revealed on follow-up CT examinations (median time interval, 180 days). The presence of ULP (P = 0.030), type A (P = 0.038) and the maximal thickness of the hematoma (P = 0.017) were significant predictors for the development of an aneurysm. Conclusions: The maximum thickness of a hematoma on the initial CT is the significant factor predicting the development of aortic dissection and aortic aneurysm. Patients with type A IMH and ULP, as revealed by initial and short-term follow-up CT examinations, should be carefully followed up with subsequent CT examination to monitor the development of an aortic aneurysm, which is a relatively common chronic complication of IMH.

Performance testing of several classifiers for differentiating obstructive lung diseases based on texture analysis at high-resolution computerized tomography (HRCT)

Machine classifiers have been used to automate quantitative analysis and avoid intra-inter-reader variability in previous studies. The selection of an appropriate classification scheme is important for improving performance based on the characteristics of the data set. This paper investigated the performance of several machine classifiers for differentiating obstructive lung diseases using texture analysis on various ROI (region of interest) sizes. 265 high-resolution computerized tomography (HRCT) images were taken from 92 subjects. On each image, two experienced radiologists selected ROIs with various sizes representing area of severe centrilobular emphysema (PLE, n=63), mild centrilobular emphysema (CLE, n=65), bronchiolitis obliterans (BO, n=70) or normal lung (NL, n=67). Four machine classifiers were implemented: naïve Bayesian classifier, Bayesian classifier, ANN (artificial neural net) and SVM (support vector machine). For a testing method, 5-fold cross-validation methods were used and each validation was repeated 20 times. The SVM had the best performance in overall accuracy (in ROI size of 32x32 and 64x64) (t-test, p<0.05). There was no significant overall accuracy difference between Bayesian and ANN (t-test, p<0.05). The naïve Bayesian method performed significantly worse than the other classifiers (t-test, p<0.05). SVM showed the best performance for classification of the obstructive lung diseases in this study.

Radiation dose reduction of chest CT with iterative reconstruction in image space - Part I: studies on image quality using dual source CT.

Objective To determine whether the image quality (IQ) is improved with iterative reconstruction in image space (IRIS), and whether IRIS can be used for radiation reduction in chest CT. Materials and Methods Standard dose chest CT (SDCT) in 50 patients and low dose chest CT (LDCT) in another 50 patients were performed, using a dual-source CT, with 120 kVp and same reference mAs (50 mAs for SDCT and 25 mAs for LDCT) employed to both tubes by modifying a dual-energy scan mode. Full-dose data were obtained by combining the data from both tubes and half-dose data were separated from a single tube. These were reconstructed by using a filtered back projection (FBP) and IRIS: full-dose FBP (F-FBP); full-dose IRIS (F-IRIS); half-dose FBP (H-FBP) and half-dose IRIS (H-IRIS). Objective noise was measured. The subjective IQ was evaluated by radiologists for the followings: noise, contrast and sharpness of mediastinum and lung. Results Objective noise was significantly lower in H-IRIS than in F-FBP (p < 0.01). In both SDCT and LDCT, the IQ scores were highest in F-IRIS, followed by F-FBP, H-IRIS and H-FBP, except those for sharpness of mediastinum, which tended to be higher in FBP. When comparing CT images between the same dose and different reconstruction (F-IRIS/F-FBP and H-IRIS/H-FBP) algorithms, scores tended to be higher in IRIS than in FBP, being more distinct in half-dose images. However, despite the use of IRIS, the scores were lower in H-IRIS than in F-FBP. Conclusion IRIS generally helps improve the IQ, being more distinct at the reduced radiation. However, reduced radiation by half results in IQ decrease even when using IRIS in chest CT.

Improved correlation between CT emphysema quantification and pulmonary function test by density correction of volumetric CT data based on air and aortic density.

OBJECTIVES To determine the improvement of emphysema quantification with density correction and to determine the optimal site to use for air density correction on volumetric computed tomography (CT). METHODS Seventy-eight CT scans of COPD patients (GOLD II-IV, smoking history 39.2±25.3 pack-years) were obtained from several single-vendor 16-MDCT scanners. After density measurement of aorta, tracheal- and external air, volumetric CT density correction was conducted (two reference values: air, -1,000 HU/blood, +50 HU). Using in-house software, emphysema index (EI) and mean lung density (MLD) were calculated. Differences in air densities, MLD and EI prior to and after density correction were evaluated (paired t-test). Correlation between those parameters and FEV1 and FEV1/FVC were compared (age- and sex adjusted partial correlation analysis). RESULTS Measured densities (HU) of tracheal- and external air differed significantly (-990 ± 14, -1016 ± 9, P<0.001). MLD and EI on original CT data, after density correction using tracheal- and external air also differed significantly (MLD: -874.9 ± 27.6 vs. -882.3 ± 24.9 vs. -860.5 ± 26.6; EI: 16.8 ± 13.4 vs. 21.1 ± 14.5 vs. 9.7 ± 10.5, respectively, P<0.001). The correlation coefficients between CT quantification indices and FEV1, and FEV1/FVC increased after density correction. The tracheal air correction showed better results than the external air correction. CONCLUSION Density correction of volumetric CT data can improve correlations of emphysema quantification and PFT.

Quantitative computed tomography measurements to evaluate airway disease in chronic obstructive pulmonary disease: Relationship to physiological measurements, clinical index and visual assessment of airway disease

PURPOSE To correlate currently available quantitative CT measurements for airway disease with physiological indices and the body-mass index, airflow obstruction, dyspnea, and exercise capacity (BODE) index in patients with chronic obstructive pulmonary disease (COPD). MATERIALS AND METHODS This study was approved by our institutional review board (IRB number 2778). Written informed consent was obtained from all subjects. The subjects included 188 current and former cigarette smokers from the COPDGene cohort who underwent inspiratory and expiratory CT and also had physiological measurements for the evaluation of airflow limitation, including FEF25-75%, airway resistance (Raw), and specific airway conductance (sGaw). The BODE index was used as the index of clinical symptoms. Quantitative CT measures included % low attenuation areas [% voxels≤950 Hounsfield unit (HU) on inspiratory CT, %LAA-950ins], percent gas trapping (% voxels≤-856HU on expiratory CT, %LAA -856exp), relative inspiratory to expiratory volume change of voxels with attenuation values from -856 to -950HU [Relative Volume Change (RVC)-856 to -950], expiratory to inspiratory ratio of mean lung density (E/I-ratio MLD), Pi10, and airway wall thickness (WT), luminal diameter (LD) and airway wall area percent (WA%) in the segmental, subsegmental and subsubsegmental bronchi on inspiratory CT. Correlation coefficients were calculated between the QCT measurements and physiological measurements in all subjects and in the subjects with mild emphysema (%LAA-950ins <10%). Univariate and multiple variable analysis for the BODE index were also performed. Adjustments were made for age, gender, smoking pack years, FEF25-75%, Raw, and sGaw. RESULTS Quantitative CT measurements had significant correlations with physiological indices. Among them, E/I-ratio MLD had the strongest correlations with FEF25-75% (r=-0.648, <0.001) and sGaw (r=-0.624, <0.001) while in the subjects with mild emphysema subsegmental WA% and segmental WA% had the strongest correlation with FEF25-75% (r=-0.669, <0.001) and sGaw (r=-0.638, <0.001), respectively. The multiple variable analyses showed that RVC-856 to -950 was an independent predictor of the BODE index showing the highest R2 (0.468) as an independent variable among the QCT measurements. CONCLUSION Quantitative CT measurements of gas trapping such as E/I-ratio MLD, correlate better with physiological indices for airway disease than those of airway such as WA% or LD. In mild emphysema, however, quantitative CT measurements of airway correlate better with the physiological indices. RVC-856 to -950 is a predictor of the BODE index.

Relationships between diffusing capacity for carbon monoxide (DLCO), and quantitative computed tomography measurements and visual assessment for chronic obstructive pulmonary disease

PURPOSE To evaluate the relationships between DLCO, and Quantitative CT (QCT) measurements and visual assessment of pulmonary emphysema and to test the relative roles of visual and quantitative assessment of emphysema. MATERIALS AND METHODS The subjects included 199 current and former cigarette smokers from the COPDGene cohort who underwent inspiratory and expiratory CT and also had diffusing capacity for carbon monoxide corrected for alveolar volume (DLCO/VA). Quantitative CT measurements included % low attenuation areas (%LAA-950ins=voxels ≤-950 Hounsfield unit (HU), %LAA-910ins, and %LAA-856ins), mean CT attenuation and 15th percentile HU value on inspiratory CT, and %LAA-856exp (voxels ≤-856 HU on expiratory CT). The extent of emphysema was visually assessed using a 5-point grading system. Univariate and multiple variable linear regression analyses were employed to evaluate the correlations between DLCO/VA and QCT parameters and visual extent of emphysema. RESULTS The DLCO/VA correlated most strongly with 15th percentile HU (R(2)=0.440, p<0.001) closely followed by %LAA-950ins (R(2)=0.417, p<0.001) and visual extent of emphysema (R(2)=0.411, p<0.001). Multiple variable analysis showed that visual extent of emphysema and 15th percentile HU were independent significant predictors of DLCO/VA at an R(2) of 0.599. CONCLUSIONS 15th percentile HU seems the best parameter to represent the respiratory condition of COPD. Visual and Quantitative CT assessment of emphysema provide complementary information to QCT analysis.

Linear Fat Deposition in the Middle Layer of the Left Ventricular Myocardium: Computed Tomographic Findings

We report here a case of streaky fat deposition in the middle layer of the left ventricular myocardium, without any underlying etiology, and this was seen on computed tomography coronary angiography. This report suggests that left ventricular middle layer fat deposition should be investigated in order to determine its etiology, the pathogenesis and the prognosis.

Successful percutaneous coronary intervention in an anomalous origin of the right coronary artery from the ascending aorta above the left sinus of the valsalva.

The anomalous origin of the right coronary artery (RCA) is a rare condition. Most RCA anomalies are usually found incidentally, but these findings have clinical significance because many patients, particularly young ones, present with sudden death, myocardial ischemia and syncope without other symptoms. We describe a case of a 39-year-old male patient that presented with effort chest pain and was diagnosed with anomalous RCA that originated from the ascending aorta with prior history of repairing ruptured sinus valsalva and ventricular septal defect. The anomalous origin of RCA was identified by multidetector computed tomography (MDCT). Successful percutaneous coronary intervention was performed guided by MDCT coronary images and intravascular ultrasound.