We describe a rare case of extralobar pulmonary sequestration with hemorrhagic infarction in a 10-year-old boy who presented with acute abdominal pain and fever. In our case, internal branching linear architecture, lack of enhancement in the peripheral portion of the lesion with internal hemorrhage, and vascular pedicle were well visualized on preoperative magnetic resonance imaging that led to successful preoperative diagnosis of extralobar pulmonary sequestration with hemorrhagic infarction probably due to torsion.
Abdominal Pain/etiology ; Bronchopulmonary Sequestration/*diagnosis/surgery ; Child ; Fever/etiology ; Humans ; Magnetic Resonance Imaging/*methods ; Male ; Pulmonary Infarction/*diagnosis/surgery ; Torsion Abnormality/complications

As the majority of incidentally detected lesions in the anterior mediastinum is small nodules with soft tissue appearance, the differential diagnosis has typically included thymic neoplasm and prevascular lymph node, with benign cyst. Overestimation or misinterpretation of these lesions can lead to unnecessary surgery for ultimately benign conditions. Diagnosing mediastinal cysts using MRI serves as a problem-solving modality in distinguishing between surgical and nonsurgical anterior mediastinal lesions. The pitfalls of MRI evaluation for anterior mediastinal cystic lesions are as follows: first, we acknowledge the limitation of T2-weighted images for evaluating benign cystic lesions. Due to variable contents within benign cystic lesions, such as hemorrhage, T2 signal intensity may be variable. Second, owing to extensive necrosis and cystic changes, the T2 shine-through effect may be seen on diffusion-weighted images (DWI), and small solid portions might be missed on enhanced images.Therefore, both enhancement and DWI with apparent diffusion coefficient values should be considered. An algorithm will be suggested for the diagnostic evaluation of anterior mediastinal cystic lesions, and finally, a management strategy based on MRI features will be suggested.

OBJECTIVE: To determine the predictive factors for treatment responsiveness in patients with chronic obstructive pulmonary disease (COPD) at 1-year follow-up by performing quantitative analyses of baseline CT scans. MATERIALS AND METHODS: COPD patients (n = 226; 212 men, 14 women) were recruited from the Korean Obstructive Lung Disease cohort. Patients received a combination of inhaled long-acting beta-agonists and corticosteroids twice daily for 3 months and subsequently received medications according to the practicing clinician's decision. The emphysema index, air-trapping indices, and airway parameter (Pi10), calculated using both full-width-half-maximum and integral-based half-band (IBHB) methods, were obtained with baseline CT scans. Clinically meaningful treatment response was defined as an absolute increase of ≥ 0.225 L in the forced expiratory volume in 1 second (FEV1) at the one-year follow-up. Multivariate logistic regression analysis was performed to investigate the predictors of an increase in FEV1, and receiver operating characteristic (ROC) analysis was performed to evaluate the performance of the suggested models. RESULTS: Treatment response was noted in 47 patients (20.8%). The mean FEV1 increase in responders was 0.36 ± 0.10 L. On univariate analysis, the air-trapping index (ATI) obtained by the subtraction method, ATI of the emphysematous area, and IBHB-measured Pi10 parameter differed significantly between treatment responders and non-responders (p = 0.048, 0.042, and 0.002, respectively). Multivariate analysis revealed that the IBHB-measured Pi10 was the only independent variable predictive of an FEV1 increase (p = 0.003). The adjusted odds ratio was 1.787 (95% confidence interval: 1.220–2.619). The area under the ROC curve was 0.641. CONCLUSION: Measurement of standardized airway dimensions on baseline CT by using a recently validated quantification method can predict treatment responsiveness in COPD patients.
Adrenal Cortex Hormones ; Cohort Studies ; Emphysema ; Follow-Up Studies ; Forced Expiratory Volume ; Humans ; Logistic Models ; Lung Diseases, Obstructive ; Male ; Methods ; Multivariate Analysis ; Odds Ratio ; Pulmonary Disease, Chronic Obstructive ; ROC Curve ; Tomography, X-Ray Computed

OBJECTIVE: The aim of our study was to develop and validate a convolutional neural network (CNN) architecture to convert CT images reconstructed with one kernel to images with different reconstruction kernels without using a sinogram. MATERIALS AND METHODS: This retrospective study was approved by the Institutional Review Board. Ten chest CT scans were performed and reconstructed with the B10f, B30f, B50f, and B70f kernels. The dataset was divided into six, two, and two examinations for training, validation, and testing, respectively. We constructed a CNN architecture consisting of six convolutional layers, each with a 3 × 3 kernel with 64 filter banks. Quantitative performance was evaluated using root mean square error (RMSE) values. To validate clinical use, image conversion was conducted on 30 additional chest CT scans reconstructed with the B30f and B50f kernels. The influence of image conversion on emphysema quantification was assessed with Bland–Altman plots. RESULTS: Our scheme rapidly generated conversion results at the rate of 0.065 s/slice. Substantial reduction in RMSE was observed in the converted images in comparison with the original images with different kernels (mean reduction, 65.7%; range, 29.5–82.2%). The mean emphysema indices for B30f, B50f, converted B30f, and converted B50f were 5.4 ± 7.2%, 15.3 ± 7.2%, 5.9 ± 7.3%, and 16.8 ± 7.5%, respectively. The 95% limits of agreement between B30f and other kernels (B50f and converted B30f) ranged from −14.1% to −2.6% (mean, −8.3%) and −2.3% to 0.7% (mean, −0.8%), respectively. CONCLUSION: CNN-based CT kernel conversion shows adequate performance with high accuracy and speed, indicating its potential clinical use.
Dataset ; Emphysema ; Ethics Committees, Research ; Image Processing, Computer-Assisted ; Machine Learning ; Multidetector Computed Tomography ; Retrospective Studies ; Tomography, X-Ray Computed

OBJECTIVE: To retrospectively investigate whether tumor size assessment on multiplanar reconstruction (MPR) CT images better reflects pathologic T-stage than evaluation on axial images and evaluate the additional value of measurement in three-dimensional (3D) space. MATERIALS AND METHODS: From 1661 patients who had undergone surgical resection for primary lung cancer between June 2013 and November 2016, 210 patients (145 men; mean age, 64.4 years) were randomly selected and 30 were assigned to each pathologic T-stage. Two readers independently measured the maximal lesion diameters on MPR CT. The longest diameters on 3D were obtained using volume segmentation. T-stages determined on CT images were compared with pathologic T-stages (overall and subgroup—Group 1, T1a/b; Group 2, T1c or higher), with differences in accuracy evaluated using McNemar's test. Agreement between readers was evaluated with intraclass correlation coefficients (ICC). RESULTS: The diagnostic accuracy of MPR measurements for determining T-stage was significantly higher than that of axial measurement alone for both reader 1 (74.3% [156/210] vs. 63.8% [134/210]; p = 0.001) and reader 2 (68.1% [143/210] vs. 61.9% [130/210]; p = 0.049). In the subgroup analysis, diagnostic accuracy with MPR diameter was significantly higher than that with axial diameter in only Group 2 (p < 0.05). Inter-reader agreements for the ICCs on axial and MPR measurements were 0.98 and 0.98. The longest diameter on 3D images showed a significantly lower performance than MPR, with an accuracy of 54.8% (115/210) (p < 0.05). CONCLUSION: Size measurement on MPR CT better reflected the pathological T-stage, specifically for T1c or higher stage lung cancer. Measurements in a 3D plane showed no added value.
Humans ; Lung Neoplasms ; Lung ; Male ; Multidetector Computed Tomography ; Neoplasm Staging ; Retrospective Studies