Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease

Objective@#To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. @*Materials and Methods@#This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1–7 according to acquisition conditions. CT images in groups 2–7 were converted into the target CT sty le (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. @*Results@#Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2–7 improved after CT conversion (original vs. converted: 0.63vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists’ scores were significantly higher (P < 0.001) and less variable on converted CT. @*Conclusion@#CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

Computed Tomography and Magnetic Resonance Imaging Features of a Huge Cavernous Hemangioma in the Pleural Space: A Case Report

A 44-year-old male with a huge left pleural mass was admitted due to chest discomfort. Chest computed tomography showed a large pleural mass with punctate calcification and serpentine-shaped enhancement in the left pleural space. Magnetic resonance imaging showed markedly high signal intensity with septa on fat-suppressed T2-weighted imaging (WI) and gradual peripheral delayed enhancement on dynamic-enhancing T1-WI. With hemangioma as the suspected diagnosis, the entire mass was surgically removed carefully and the final histopathological diagnosis was confirmed to be a cavernous hemangioma. Cavernous hemangioma of the pleural space is a rare benign vascular tumor. Precise radiologic diagnosis is important before the surgical operation of hemangiomas because of risk of massive hemorrhage requiring meticulous bleeding control.

The Impact of Iterative Reconstruction in Low-Dose Computed Tomography on the Evaluation of Diffuse Interstitial Lung Disease

OBJECTIVE: To evaluate the impact of iterative reconstruction (IR) on the assessment of diffuse interstitial lung disease (DILD) using CT. MATERIALS AND METHODS: An American College of Radiology (ACR) phantom (module 4 to assess spatial resolution) was scanned with 10–100 effective mAs at 120 kVp. The images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), with blending ratios of 0%, 30%, 70% and 100%, and model-based iterative reconstruction (MBIR), and their spatial resolution was objectively assessed by the line pair structure method. The patient study was based on retrospective interpretation of prospectively acquired data, and it was approved by the institutional review board. Chest CT scans of 23 patients (mean age 64 years) were performed at 120 kVp using 1) standard dose protocol applying 142–275 mA with dose modulation (high-resolution computed tomography [HRCT]) and 2) low-dose protocol applying 20 mA (low dose CT, LDCT). HRCT images were reconstructed with FBP, and LDCT images were reconstructed using FBP, ASIR, and MBIR. Matching images were randomized and independently reviewed by chest radiologists. Subjective assessment of disease presence and radiological diagnosis was made on a 10-point scale. In addition, semi-quantitative results were compared for the extent of abnormalities estimated to the nearest 5% of parenchymal involvement. RESULTS: In the phantom study, ASIR was comparable to FBP in terms of spatial resolution. However, for MBIR, the spatial resolution was greatly decreased under 10 mA. In the patient study, the detection of the presence of disease was not significantly different. The values for area under the curve for detection of DILD by HRCT, FBP, ASIR, and MBIR were as follows: 0.978, 0.979, 0.972, and 0.963. LDCT images reconstructed with FBP, ASIR, and MBIR tended to underestimate reticular or honeycombing opacities (-2.8%, -4.1%, and -5.3%, respectively) and overestimate ground glass opacities (+4.6%, +8.9%, and +8.5%, respectively) compared to the HRCT images. However, the reconstruction methods did not differ with respect to radiologic diagnosis. CONCLUSION: The diagnostic performance of LDCT with MBIR was similar to that of HRCT in typical DILD cases. However, caution should be exercised when comparing disease extent, especially in follow-up studies with IR.

Single Nodular Opacity of Granulomatous Pneumocystis Jirovecii Pneumonia in an Asymptomatic Lymphoma Patient

The radiologic findings of a single nodule from Pneumocystis jirovecii pneumonia (PJP) have been rarely reported. We described a case of granulomatous PJP manifesting as a solitary pulmonary nodule with a halo sign in a 69-year-old woman with diffuse large B cell lymphoma during chemotherapy. The radiologic appearance of the patient suggested an infectious lesion such as angioinvasive pulmonary aspergillosis or lymphoma involvement of the lung; however, clinical manifestations were not compatible with the diseases. The nodule was confirmed as granulomatous PJP by video-assisted thoracoscopic surgery biopsy.

Ultra-Low-Dose Chest CT in Patients with Neutropenic Fever and Hematologic Malignancy: Image Quality and Its Diagnostic Performance / Journal of the Korean Cancer Association, 대한암학회지

PURPOSE: The aim of this study was to evaluate the image quality of ultra-low-dose computed tomography (ULDCT) and its diagnostic performance in making a specific diagnosis of pneumonia in febrile neutropenic patients with hematological malignancy. MATERIALS AND METHODS: ULDCT was performed prospectively in 207 febrile neutropenic patients with hematological malignancy. Three observers independently recorded the presence of lung parenchymal abnormality, and also indicated the cause of the lung parenchymal abnormality between infectious and noninfectious causes. If infectious pneumonia was considered the cause of lung abnormalities, they noted the two most appropriate diagnoses among four infectious conditions, including fungal, bacterial, viral, and Pneumocystis pneumonia. Sensitivity for correct diagnoses and receiver operating characteristic (ROC) curve analysis for evaluation of diagnostic accuracy were calculated. Interobserver agreements were determined using intraclass correlation coefficient. RESULTS: Of 207 patients, 139 (67%) had pneumonia, 12 had noninfectious lung disease, and 56 had no remarkable chest computed tomography (CT) (20 with extrathoracic fever focus and 36 with no specific disease). Mean radiation expose dose of ULDCT was 0.60+/-0.15 mSv. Each observer regarded low-dose CT scans as unacceptable in only four (1.9%), one (0.5%), and three (1.5%) cases of ULDCTs. Sensitivity and area under the ROC curve in making a specific pneumonia diagnosis were 63.0%, 0.65 for reader 1; 63.0%, 0.61 for reader 2; and 65.0%, 0.62 for reader 3; respectively CONCLUSION: ULDCT, with a sub-mSv radiation dose and acceptable image quality, provides ready and reasonably acceptable diagnostic information for pulmonary infection in febrile neutropenic patients with hematologic malignancy

Interpretation of Digital Chest Radiographs: Comparison of Light Emitting Diode versus Cold Cathode Fluorescent Lamp Backlit Monitors

OBJECTIVE: To compare the diagnostic performance of light emitting diode (LED) backlight monitors and cold cathode fluorescent lamp (CCFL) monitors for the interpretation of digital chest radiographs. MATERIALS AND METHODS: We selected 130 chest radiographs from health screening patients. The soft copy image data were randomly sorted and displayed on a 3.5 M LED (2560 x 1440 pixels) monitor and a 3 M CCFL (2048 x 1536 pixels) monitor. Eight radiologists rated their confidence in detecting nodules and abnormal interstitial lung markings (ILD). Low dose chest CT images were used as a reference standard. The performance of the monitor systems was assessed by analyzing 2080 observations and comparing them by multi-reader, multi-case receiver operating characteristic analysis. The observers reported visual fatigue and a sense of heat. Radiant heat and brightness of the monitors were measured. RESULTS: Measured brightness was 291 cd/m2 for the LED and 354 cd/m2 for the CCFL monitor. Area under curves for nodule detection were 0.721 +/- 0.072 and 0.764 +/- 0.098 for LED and CCFL (p = 0.173), whereas those for ILD were 0.871 +/- 0.073 and 0.844 +/- 0.068 (p = 0.145), respectively. There were no significant differences in interpretation time (p = 0.446) or fatigue score (p = 0.102) between the two monitors. Sense of heat was lower for the LED monitor (p = 0.024). The temperature elevation was 6.7degrees C for LED and 12.4degrees C for the CCFL monitor. CONCLUSION: Although the LED monitor had lower maximum brightness compared with the CCFL monitor, soft copy reading of the digital chest radiographs on LED and CCFL showed no difference in terms of diagnostic performance. In addition, LED emitted less heat.

Reduced Radiation Dose in Diagnostic Radiology

No abstract available.