Comparative Analysis of CT Findings and Clinical Outcomes in Adult Patients With Disseminated and Localized Pulmonary Nocardiosis.

BACKGROUND: Pulmonary nocardiosis is a rare opportunistic infection with occasional systemic dissemination. This study aimed to investigate the computed tomography (CT) findings and prognosis of pulmonary nocardiosis associated with dissemination. METHODS: We conducted a retrospective analysis of patients diagnosed with pulmonary nocardiosis between March 2001 and September 2023. We reviewed the chest CT findings and categorized them based on the dominant CT findings as consolidation, nodules and/or masses, consolidation with multiple nodules, and nodular bronchiectasis. We compared chest CT findings between localized and disseminated pulmonary nocardiosis and identified significant prognostic factors associated with 12-month mortality using multivariate Cox regression analysis. RESULTS: Pulmonary nocardiosis was diagnosed in 75 patients, of whom 14 (18.7%) had dissemination, including involvement of the brain in 9 (64.3%) cases, soft tissue in 3 (21.4%) cases and positive blood cultures in 3 (21.4%) cases. Disseminated pulmonary nocardiosis showed a higher frequency of cavitation (64.3% vs. 32.8%, P = 0.029) and pleural effusion (64.3% vs. 29.5%, P = 0.014) compared to localized infection. The 12-month mortality rate was 25.3%. The presence of dissemination was not a significant prognostic factor (hazard ratio [HR], 0.80; confidence interval [CI], 0.23-2.75; P = 0.724). Malignancy (HR, 9.73; CI, 2.32-40.72; P = 0.002), use of steroid medication (HR, 3.72; CI, 1.33-10.38; P = 0.012), and a CT pattern of consolidation with multiple nodules (HR, 4.99; CI, 1.41-17.70; P = 0.013) were associated with higher mortality rates. CONCLUSION: Pulmonary nocardiosis with dissemination showed more frequent cavitation and pleural effusion compared to cases without dissemination, but dissemination alone did not affect the mortality rate of pulmonary nocardiosis.

Surgical Outcomes in Non-Small Cell Lung Cancer with Distant Metastasis: The Prognostic Significance of Delayed Metastasis Diagnosis.

BACKGROUND: The diagnosis of distant metastasis on preoperative examinations for non-small cell lung cancer (NSCLC) can be challenging, leading to surgery for some patients with uncertain metastasis. This study evaluated the prognostic impact of delayed diagnosis of metastasis on patients who underwent upfront surgery. METHODS: The study enrolled patients who underwent lobectomy or pneumonectomy for NSCLC between June 2010 and December 2017 and evaluated the presence of distant metastasis before surgery. Overall survival (OS) for patients with stage IV cancer was compared with that for patients without metastasis, and the prognostic factors were analyzed. RESULTS: Of 3046 patients (mean age, 63 years; 1770 men), 100 (3.3 %) had distant metastasis, diagnosed preoperatively in 1.4 % (42/3046) and postoperatively in 1.9 % (58/3046) of the patients. The two most common metastasis sites diagnosed after surgery were contralateral lung (22/58, 37.9 %) and ipsilateral pleura (16/58, 27.6 %). The OS (median, 42.7 months) for the patients with stage IV cancer diagnosed postoperatively was comparable with that for the patients with stage IIIB cancer (P = 0.865), whereas the OS (median OS, 91.7 months) for the patients with stage IV cancer diagnosed preoperatively was better than for the patients with stage IIIB cancer (P = 0.001). Among the patients with distant metastasis, squamous cell type (hazard ratio [HR], 3.15; P = 0.002) and systemic treatment for metastasis (HR, 2.42; P = 0.002) were independent predictors of worse OS. CONCLUSIONS: Among NSCLC patients undergoing upfront surgery, the OS for the patients with stage IV cancer diagnosed postoperatively was comparable with that for the patients with stage IIIB cancer. For patients with stage IV disease, squamous cell type and systemic treatment for metastasis were prognostic factors for poorer OS.

CT-guided percutaneous transthoracic needle biopsy for anterior mediastinal lymphoma: the role of PET/CT.

BACKGROUND: Computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) is not recommended as the diagnostic modality of choice for anterior mediastinal lymphoma, despite its advantages of minimal invasiveness and easy accessibility. PURPOSE: To identify the modifiable risk factors for non-diagnostic results from CT-guided PTNB for anterior mediastinal lymphoma. MATERIAL AND METHODS: This retrospective study identified CT-guided PTNB for anterior mediastinal lesions diagnosed as lymphoma between May 2007 and December 2021. The diagnostic sensitivity and complications were investigated. The appropriateness of PTNB targeting was evaluated using positron emission tomography (PET)/CT and images from intra-procedural CT-guided PTNB. Targeting was considered inappropriate when the supposed trajectory of the cutting needle was within a region of abnormally low metabolism. The risk factors for non-diagnostic results were determined using logistic regression analysis. RESULTS: A total of 67 PTNBs in 60 patients were included. The diagnostic sensitivity for lymphoma was 76.1% (51/67), with an immediate complication rate of 4.5% (3/67). According to the PET/CT images, PTNB targeting was inappropriate in 10/14 (71.4%) of the non-diagnostic PTNBs but appropriate in all diagnostic PTNBs (P <0.001). Inappropriate targeting was the only significant risk factor for non-diagnostic results (odds ratio = 203.69; 95% confidence interval = 8.17-999.99; P = 0.001). The number of specimen acquisitions was not associated with non-diagnostic results (P = 0.40). CONCLUSIONS: Only inappropriate targeting of the non-viable portion according to PET/CT was an independent risk factor for non-diagnostic results. Acquiring PET/CT scans before biopsy and targeting the viable portion on PET/CT may help improve the diagnostic sensitivity of PTNB.

Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease.

The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable.

Deep Learning-Based CT Reconstruction Kernel Conversion in the Quantification of Interstitial Lung Disease: Effect on Reproducibility.

RATIONALE AND OBJECTIVES: The effect of different computed tomography (CT) reconstruction kernels on the quantification of interstitial lung disease (ILD) has not been clearly demonstrated. The study aimed to investigate the effect of reconstruction kernels on the quantification of ILD on CT and determine whether deep learning-based kernel conversion can reduce the variability of automated quantification results between different CT kernels. MATERIALS AND METHODS: Patients with ILD or interstitial lung abnormality who underwent noncontrast high-resolution CT between June 2022 and September 2022 were retrospectively included. Images were reconstructed with three different kernels: B30f, B50f, and B60f. B60f was regarded as the reference standard for quantification, and B30f and B50f images were converted to B60f images using a deep learning-based algorithm. Each disease pattern of ILD and the fibrotic score were quantified using commercial software. The effect of kernel conversion on measurement variability was estimated using intraclass correlation coefficient (ICC) and Bland-Altman method. RESULTS: A total of 194 patients were included in the study. Application of different kernels induced differences in the quantified extent of each pattern. Reticular opacity and honeycombing were underestimated on B30f images and overestimated on B50f images. After kernel conversion, measurement variability was reduced (mean difference, from -2.0 to 3.9 to -0.3 to 0.4%, and 95% limits of agreement [LOA], from [-5.0, 12.7] to [-2.7, 2.1]). The fibrotic score for converted B60f from B50f images was almost equivalent to the original B60f (ICC, 1.000; mean difference, 0.0; and 95% LOA [-0.4, 0.4]). CONCLUSION: Quantitative CT analysis of ILD was affected by the application of different kernels, but deep learning-based kernel conversion effectively reduced measurement variability, improving the reproducibility of quantification.

Long-Term Follow-Up of Interstitial Lung Abnormality: Implication in Follow-Up Strategy and Risk Thresholds.

Rationale: The optimal follow-up computed tomography (CT) interval for detecting the progression of interstitial lung abnormality (ILA) is unknown. Objectives: To identify optimal follow-up strategies and extent thresholds on CT relevant to outcomes. Methods: This retrospective study included self-referred screening participants aged 50 years or older, including nonsmokers, who had imaging findings relevant to ILA on chest CT scans. Consecutive CT scans were evaluated to determine the dates of the initial CT showing ILA and the CT showing progression. Deep learning-based ILA quantification was performed. Cox regression was used to identify risk factors for the time to ILA progression and progression to usual interstitial pneumonia (UIP). Measurements and Main Results: Of the 305 participants with a median follow-up duration of 11.3 years (interquartile range, 8.4-14.3 yr), 239 (78.4%) had ILA on at least one CT scan. In participants with serial follow-up CT studies, ILA progression was observed in 80.5% (161 of 200), and progression to UIP was observed in 17.3% (31 of 179), with median times to progression of 3.2 years (95% confidence interval [CI], 3.0-3.4 yr) and 11.8 years (95% CI, 10.8-13.0 yr), respectively. The extent of fibrosis on CT was an independent risk factor for ILA progression (hazard ratio, 1.12 [95% CI, 1.02-1.23]) and progression to UIP (hazard ratio, 1.39 [95% CI, 1.07-1.80]). Risk groups based on honeycombing and extent of fibrosis (1% in the whole lung or 5% per lung zone) showed significant differences in 10-year overall survival (P = 0.02). Conclusions: For individuals with initially detected ILA, follow-up CT at 3-year intervals may be appropriate to monitor radiologic progression; however, those at high risk of adverse outcomes on the basis of the quantified extent of fibrotic ILA and the presence of honeycombing may benefit from shortening the interval for follow-up scans.

Sublobar resection in non-small cell lung cancer: patient selection criteria and risk factors for recurrence.

OBJECTIVE: To validate selection criteria for sublobar resection in patients with lung cancer with respect to recurrence, and to investigate predictors for recurrence in patients for whom the criteria are not suitable. METHODS: Patients who underwent sublobar resection for lung cancer between July 2010 and December 2018 were retrospectively included. The criteria for curative sublobar resection were consolidation-to-tumor ratio ≤0.50 and size ≤3.0 cm in tumors with a ground-glass opacity (GGO) component (GGO group), and size of ≤2.0 cm and volume doubling time ≥400 days in solid tumors (solid group). Cox regression was used to identify predictors for time-to-recurrence (TTR) in tumors outside of these criteria (non-curative group). RESULTS: Out of 530 patients, 353 were classified into the GGO group and 177 into the solid group. In the GGO group, the 2-year recurrence rates in curative and non-curative groups were 2.1 and 7.7%, respectively (p = 0.054). In the solid group, the 2-year recurrence rates in curative and non-curative groups were 0.0 and 28.6%, respectively (p = 0.03). Predictors of 2-year TTR after non-curative sublobar resection were pathological nodal metastasis (hazard ratio [HR], 6.63; p = 0.02) and lymphovascular invasion (LVI; HR, 3.28; p = 0.03) in the GGO group, and LVI (HR, 4.37; p < 0.001) and fibrosis (HR, 3.18; p = 0.006) in the solid group. CONCLUSION: The current patient selection criteria for sublobar resection are satisfactory. LVI was a predictor for recurrence after non-curative resection. ADVANCES IN KNOWLEDGE: This result supports selection criteria of patients for sublobar resection. LVI may help predict recurrence after non-curative sublobar resection.

Prognostic Implications of Synchronous Subsolid Nodules in Patients with Resected Subsolid Lung Adenocarcinoma.

Background For multiple subsolid nodules (SSNs) observed at lung CT, current management focuses on removal of the dominant (≥6 mm) nodule and monitoring of remaining SSNs. Whether the presence of these synchronous SSNs is related to postoperative patient outcomes has not been well established. Purpose To evaluate the prognostic value of single versus multiple synchronous SSNs at preoperative CT in patients with resected subsolid lung adenocarcinoma nodules. Materials and Methods This retrospective study included patients who underwent lobectomy or sublobar resection for lung adenocarcinoma manifesting as an SSN and clinical stage IA from January 2010 to December 2017. The radiologic features of the resected SSN (dominant nodule) and synchronous SSNs were assessed on preoperative CT scans. The effects of synchronous SSNs on time to secondary intervention, time to recurrence (TTR), and overall survival (OS) were evaluated using Cox regression analysis. Results Of the 684 included patients (mean age, 60.9 years ± 9.5 [SD]; 389 female), 515 (75.3%) had a single SSN and 169 (24.7%) had multiple SSNs on preoperative CT scans. During follow-up (median, 71.8 months), 38 secondary interventions were performed, primarily due to growth of synchronous SSNs (21 of 38) or metachronous nodules (14 of 38). As the number of synchronous SSNs greater than or equal to 6 mm in size increased, the time to secondary intervention decreased (P < .001). No association was observed between synchronous SSNs and TTR (P = .53) or OS (P = .65), but these measures were associated with features of the resected nodule, specifically solid portion size for TTR (P = .01) and histologic subtype for TTR and OS (P < .001 for both). Conclusion In patients with subsolid lung adenocarcinoma, the presence of synchronous SSNs on preoperative CT scans was not associated with TTR or OS, but the presence of synchronous SSNs greater than or equal to 6 mm in size was associated with an increased likelihood of secondary intervention. © RSNA, 2023 Supplemental material is available for this article.

Automated CT quantification of interstitial lung abnormality and interstitial lung disease according to the Fleischner Society in patients with resectable lung cancer: prognostic significance.

OBJECTIVE: To assess the prognostic significance of automatically quantified interstitial lung abnormality (ILA) according to the definition by the Fleischner Society in patients with resectable non-small-cell lung cancer (NSCLC). METHODS: Patients who underwent lobectomy or pneumonectomy for NSCLC between January 2015 and December 2019 were retrospectively included. Preoperative CT scans were analyzed using the commercially available deep-learning-based automated quantification software for ILA. According to quantified results and the definition by the Fleischner Society and multidisciplinary discussion, patients were divided into normal, ILA, and interstitial lung disease (ILD) groups. RESULTS: Of the 1524 patients, 87 (5.7%) and 20 (1.3%) patients had ILA and ILD, respectively. Both ILA (HR, 1.81; 95% CI: 1.25-2.61; p = .002) and ILD (HR, 5.26; 95% CI: 2.99-9.24; p < .001) groups had poor recurrence-free survival (RFS). Overall survival (OS) decreased (HR 2.13 [95% CI: 1.27-3.58; p = .004] for the ILA group and 7.20 [95% CI: 3.80-13.62, p < .001] for the ILD group) as the disease severity increased. Both quantified fibrotic and non-fibrotic ILA components were associated with poor RFS (HR, 1.57; 95% CI: 1.12-2.21; p = .009; and HR, 1.11; 95% CI: 1.01-1.23; p = .03) and OS (HR, 1.59; 95% CI: 1.06-2.37; p = .02; and HR, 1.17; 95% CI: 1.03-1.33; and p = .01) in normal and ILA groups. CONCLUSIONS: The automated CT quantification of ILA based on the definition by the Fleischner Society predicts outcomes of patients with resectable lung cancer based on the disease category and quantified fibrotic and non-fibrotic ILA components. CLINICAL RELEVANCE STATEMENT: Quantitative CT assessment of ILA provides prognostic information for lung cancer patients after surgery, which can help in considering active surveillance for recurrence, especially in those with a larger extent of quantified ILA. KEY POINTS: • Of the 1524 patients with resectable lung cancer, 1417 (93.0%) patients were categorized as normal, 87 (5.7%) as interstitial lung abnormality (ILA), and 20 (1.3%) as interstitial lung disease (ILD). • Both ILA and ILD groups were associated with poor recurrence-free survival (hazard ratio [HR], 1.81, p = .002; HR, 5.26, p < .001, respectively) and overall survival (HR, 2.13; p = .004; HR, 7.20; p < .001). • Both quantified fibrotic and non-fibrotic ILA components were associated with recurrence-free survival and overall survival in normal and ILA groups.

Progression of pulmonary cysts in Birt-Hogg-Dubé syndrome: longitudinal thoracic computed tomography study with quantitative assessment.

BACKGROUND: Birt-Hogg-Dubé (BHD) syndrome is a rare autosomal dominant disorder characterized by fibrofolliculomas, renal tumors, pulmonary cysts, and recurrent pneumothorax. Pulmonary cysts are the cause of recurrent pneumothorax, which is one of the most important factors influencing patient quality of life. It is unknown whether pulmonary cysts progress with time or influence pulmonary function in patients with BHD syndrome. This study investigated whether pulmonary cysts progress during long-term follow-up (FU) by using thoracic computed tomography (CT) and whether pulmonary function declines during FU. We also evaluated risk factors for pneumothorax in patients with BHD during FU. METHODS: Our retrospective cohort included 43 patients with BHD (25 women; mean age, 54.2 ± 11.7 years). We evaluated whether cysts progress by visual assessment and quantitative volume analysis using initial and serial thoracic CT. The visual assessment included the size, location, number, shape, distribution, presence of a visible wall, fissural or subpleural cysts, and air-cuff signs. In CT data obtained from a 1-mm section from 17 patients, the quantitative assessment was performed by measuring the volume of the low attenuation area using in-house software. We evaluated whether the pulmonary function declined with time on serial pulmonary function tests (PFT). Risk factors for pneumothorax were analyzed using multiple regression analysis. RESULTS: On visual assessment, the largest cyst in the right lung showed a significant interval increase in size (1.0 mm/year, p = 0.0015; 95% confidence interval [CI], 0.42-1.64) between the initial and final CT, and the largest cyst in the left lung also showed significant interval increase in size (0.8 mm/year, p < 0.001, 95% CI; -0.49-1.09). On quantitative assessment, cysts had a tendency to gradually increase in size. In 33 patients with available PFT data, FEV1pred%, FEV1/FVC, and VCpred% showed a statistically significant decrease with time (p < 0.0001 for each). A family history of pneumothorax was a risk factor for the development of pneumothorax. CONCLUSIONS: The size of pulmonary cysts progressed over time in longitudinal follow-up thoracic CT in patients with BHD, and pulmonary function had slightly deteriorated by longitudinal follow-up PFT.

Recurrence Patterns and Patient Outcomes in Resected Lung Adenocarcinoma Differ according to Ground-Glass Opacity at CT.

Background Although lung adenocarcinoma with ground-glass opacity (GGO) is known to have distinct characteristics, limited data exist on whether the recurrence pattern and outcomes in patients with resected lung adenocarcinoma differ according to GGO presence at CT. Purpose To examine recurrence patterns and associations with outcomes in patients with resected lung adenocarcinoma according to GGO at CT. Materials and Methods Patients who underwent CT followed by lobectomy or pneumonectomy for lung adenocarcinoma between July 2010 and December 2017 were retrospectively included. Patients were divided into two groups based on the presence of GGO: GGO adenocarcinoma and solid adenocarcinoma. Recurrence patterns at follow-up CT examinations were investigated and compared between the two groups. The effects of patient grouping on time to recurrence, postrecurrence survival (PRS), and overall survival (OS) were evaluated using Cox regression. Results Of 1019 patients (mean age, 62 years ± 9 [SD]; 520 women), 487 had GGO adenocarcinoma and 532 had solid adenocarcinoma. Recurrences occurred more frequently in patients with solid adenocarcinoma (36.1% [192 of 532 patients]) than in those with GGO adenocarcinoma (16.2% [79 of 487 patients]). Distant metastasis was the most common mode of recurrence in the group with solid adenocarcinoma and all clinical stages. In clinical stage I GGO adenocarcinoma, all regional recurrences appeared as ipsilateral lung metastasis (39.2% [20 of 51]) without regional lymph node metastasis. Brain metastasis was more frequent in patients with clinical stage I solid adenocarcinoma (16.5% [16 of 97 patients]). The presence of GGO was associated with time to recurrence and OS (adjusted hazard ratio [HR], 0.6 [P < .001] for both). Recurrence pattern was an independent risk factor for PRS (adjusted HR, 2.1 for distant metastasis [P < .001] and 3.9 for brain metastasis [P < .001], with local-regional recurrence as the reference). Conclusion Recurrence patterns, time to recurrence, and overall survival differed between patients with and without ground-glass opacity at CT, and recurrence patterns were associated with postrecurrence survival. © RSNA, 2023 Supplemental material is available for this article.

Evaluation of Chylothorax Using Dynamic Contrast-Enhanced Magnetic Resonance Lymphangiography After Lung Cancer Surgery.

Background: To determine the role of dynamic contrast-enhanced magnetic resonance lymphangiography (DCMRL) in the management of postoperative chylothorax after lung cancer surgery. Methods and Results: Between July 2017 and November 2021, patients who developed postoperative chylothorax following pulmonary resection and mediastinal lymph node dissection were assessed and those who underwent DCMRL for the evaluation of chyle leak were evaluated. The findings of DCMRL and conventional lymphangiography were compared. The incidence of postoperative chylothorax was 0.9% (50/5587). Among the patients with chylothorax, a total of 22 patients (44.0% [22/50]; mean age, 67.6 ± 7.9 years; 15 men) underwent DCMRL. Treatment outcomes were compared between patients with conservative management (n = 10) and those with intervention (n = 12). The patients demonstrated unilateral pleural effusion, ipsilateral to the operation site, and showed right-sided dominance. The most frequent site of thoracic duct injury showing contrast media leakage was visualized at the subcarinal level. No DCMRL-related complication occurred. DCMRL showed comparable performance to conventional lymphangiography in visualizing the central lymphatics, including cisterna chyli (DCMRL vs. conventional lymphangiography, 72.7% vs. 45.5%, p = 0.25) and thoracic duct (90.9% vs. 54.5%, p = 0.13), and in localizing thoracic duct injury (90.9% vs. 54.5%, p = 0.13). On follow-up, the amount of chest tube drainage after lymphatic intervention showed a significant difference over time from that after medical treatment only (p = 0.02). Conclusion: DCMRL can provide detailed information about the leak site and the central lymphatic anatomy in patients with chylothorax after lung cancer surgery. The findings of DCMRL can guide subsequent treatment planning for optimal outcomes.

Long-term clinical course and outcomes of patients with microscopic polyangiitis-associated interstitial lung disease.

Background: Interstitial lung disease (ILD) is a significant complication associated with microscopic polyangiitis (MPA) that has a poor prognosis. However, the long-term clinical course, outcomes, and prognostic factors of MPA-ILD are not well defined. Hence, this study aimed to investigate the long-term clinical course, outcomes, and prognostic factors in patients with MPA-ILD. Methods: Clinical data of 39 patients with MPA-ILD (biopsy proven cases, n = 6) were retrospectively analyzed. High resolution computed tomography (HRCT) patterns were assessed based on the 2018 idiopathic pulmonary fibrosis diagnostic criteria. Acute exacerbation (AE) was defined as the worsening of dyspnea within 30 days, with new bilateral lung infiltration that is not fully explained by heart failure or fluid overload and that does not have identified extra-parenchymal causes (pneumothorax, pleural effusion, or pulmonary embolism). Results: The median follow-up period was 72.0 months (interquartile range: 44-117 months). The mean age of the patients was 62.7 years and 59.0% were male. Usual interstitial pneumonia (UIP) and probable usual interstitial pneumonia patterns on high resolution computed tomography were identified in 61.5 and 17.9% of the patients, respectively. During the follow-up, 51.3% of patients died, and the 5- and 10-year overall survival rates were 73.5% and 42.0%, respectively. Acute exacerbation occurred in 17.9% of the patients. The non-survivors had higher neutrophil counts in bronchoalveolar lavage (BAL) fluid and more frequent acute exacerbation than the survivors. In the multivariable Cox analysis, older age (hazard ratio [HR], 1.07; 95% confidence interval [CI], 1.01-1.14; p = 0.028) and higher BAL counts (HR, 1.09; 95% CI, 1.01-1.17; p = 0.015) were found to be the independent prognostic factors associated with mortality in patients with MPA-ILD. Conclusion: During the 6 years-follow-up, about half of patients with MPA-ILD died and approximately one-fifth experienced acute exacerbation. Our results suggest that older age and higher BAL neutrophil counts mean poor prognosis in patients with MPA-ILD.

Image Turing test and its applications on synthetic chest radiographs by using the progressive growing generative adversarial network.

The generative adversarial network (GAN) is a promising deep learning method for generating images. We evaluated the generation of highly realistic and high-resolution chest radiographs (CXRs) using progressive growing GAN (PGGAN). We trained two PGGAN models using normal and abnormal CXRs, solely relying on normal CXRs to demonstrate the quality of synthetic CXRs that were 1000 × 1000 pixels in size. Image Turing tests were evaluated by six radiologists in a binary fashion using two independent validation sets to judge the authenticity of each CXR, with a mean accuracy of 67.42% and 69.92% for the first and second trials, respectively. Inter-reader agreements were poor for the first (κ = 0.10) and second (κ = 0.14) Turing tests. Additionally, a convolutional neural network (CNN) was used to classify normal or abnormal CXR using only real images and/or synthetic images mixed datasets. The accuracy of the CNN model trained using a mixed dataset of synthetic and real data was 93.3%, compared to 91.0% for the model built using only the real data. PGGAN was able to generate CXRs that were identical to real CXRs, and this showed promise to overcome imbalances between classes in CNN training.

Differences in aortic valve area measured on cardiac CT and echocardiography in patients with aortic stenosis.

BACKGROUND: A certain proportion of patients with severe aortic stenosis (AS) present with discordant grading between different diagnostic modalities, which raises uncertainty about the true severity of AS. The aim of this study was to compare the aortic valve area (AVA) measured on CT and echocardiography and demonstrate the factors affecting AVA discrepancies. METHODS: Between June 2011 and March 2016, 535 consecutive patients (66.83±8.80 years, 297 men) with AS who underwent pre-operative cardiac CT and echocardiography for aortic valve replacement were retrospectively included. AVA was obtained by AVA on echocardiography (AVAecho) and CT (AVACT) using a measurement of the left ventricular outflow tract on each modality and correlations between those measures were evaluated. Logistic regression analysis was performed to identify factors affecting the discordance for grading severe AS. RESULTS: The AVACT and AVAecho showed a high correlation (r: 0.79, P <0.001) but AVACT was larger than the AVAecho (difference 0.26 cm2, P <0.001). By using the cut-off values of AVACT (<1.2 cm2) and AVAecho (<1.0 cm2) for diagnosing severe AS, the BSA (odds ratio [OR]: 68.03, 95% confidence interval [CI]: 5.45-849.99; P = 0.001), AVAecho (OR: 1.19, 95%CI: 1.14-1.24; P <0.001), tricuspid valve morphology (OR: 2.83, 95%CI: 1.23-6.50; P = 0.01), and normalized annulus area (OR: 1.02; 95%CI:1.02-1.03; P <0.001) were significant factors associated with the discordance between the AVAecho and AVACT. CONCLUSION: Patients with larger BSA, AVAecho, and annulus, and tricuspid valve morphology were associated with the AVA discordance between the echocardiography and CT. Complementary use of CT with echocardiography for grading severe AS could be helpful in such conditions.

MRI-Based Stepwise Approach to Anterior Mediastinal Cystic Lesions for Diagnosis and Further Management.

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. 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.

Dynamic Contrast-Enhanced Magnetic Resonance Lymphangiography and Lymphatic Interventions for Pediatric Patients with Various Lymphatic Diseases.

Background: To demonstrate the magnetic resonance lymphangiography (MRL) imaging findings of lymphatic diseases and the clinical outcomes of lymphatic embolization in pediatric patients. Methods and Results: This retrospective study included 10 consecutive pediatric patients who underwent MRL for lymphatic diseases between June 2017 and June 2021. Nine patients underwent dynamic contrast-enhanced MRL with bilateral inguinal lymph node injection of diluted gadolinium, and one patient underwent nonenhanced MRL with a heavily T2-weighted image. The etiology of lymphatic disease was classified into three categories based on the magnetic resonance findings. The resolution of chylous fluid and weight-adjusted amounts of chylous fluid collected from a drainage tube were evaluated as outcomes. Patients were classified as postoperative lymphatic leak (n = 3), pulmonary lymphatic perfusion syndrome (n = 3), central lymphatic flow disorder (CLFD; n = 3), and primary lymphatic dysfunction (Gorham-Stout syndrome; n = 1). Three patients underwent radiological lymphatic intervention, and one CLFD patient underwent surgical intervention. In patients with postoperative lymphatic leak, the median chest tube drainage decreased significantly after the intervention [from 87.9 to 12.4 mL/(kg·d); p = 0.02]. However, in one CLFD patient, the amount of chylous fluid did not decrease until 7 days after intervention. Conclusion: The etiology of lymphatic disease in pediatrics can be recognized on MRL, and lymphatic intervention can be performed for cessation of lymphatic leak, even though the treatment outcomes may differ according to the underlying etiology. MRL can play an important role in classifying lymphatic disease, and in planning treatment on the basis of the lymphatic anatomy and underlying etiology.

Interstitial lung abnormalities (ILA) on routine chest CT: Comparison of radiologists' visual evaluation and automated quantification.

PURPOSE: We aimed to evaluate the performance of a fully automated quantitative software in detecting interstitial lung abnormalities (ILA) according to the Fleischner Society guidelines on routine chest CT compared with radiologists' visual analysis. METHOD: This retrospective single-centre study included participants with ILA findings and 1:2 matched controls who underwent routine chest CT using various CT protocols for health screening. Two thoracic radiologists independently reviewed the CT images using the Fleischner Society guidelines. We developed a fully automated quantitative tool for detecting ILA by modifying deep learning-based quantification of interstitial lung disease and evaluated its performance using the radiologists' consensus for ILA as a reference standard. RESULTS: A total of 336 participants (mean age, 70.5 ± 6.1 years; M:F = 282:54) were included. Inter-reader agreements were substantial for the presence of ILA (weighted κ, 0.74) and fair for its subtypes (weighted κ, 0.38). The quantification system for identifying ILA using a threshold of 5 % in at least one zone showed 67.6 % sensitivity, 93.3 % specificity, and 90.5 % accuracy. Eight of 20 (40 %) false positives identified by the system were underestimated by readers for ILA extent. Contrast-enhancement in a certain vendor and suboptimal inspiration caused a true false-positive on the system (all P < 0.05). The best cut-off value of abnormality extent detecting ILA on the system was 3.6 % (sensitivity, 84.8 %; specificity 92.4 %). CONCLUSIONS: Inter-reader agreement was substantial for ILA but only fair for its subtypes. Applying an automated quantification system in routine clinical practice may aid the objective identification of ILA.

Artificial Intelligence in Lung Imaging.

Recently, interest and advances in artificial intelligence (AI) including deep learning for medical images have surged. As imaging plays a major role in the assessment of pulmonary diseases, various AI algorithms have been developed for chest imaging. Some of these have been approved by governments and are now commercially available in the marketplace. In the field of chest radiology, there are various tasks and purposes that are suitable for AI: initial evaluation/triage of certain diseases, detection and diagnosis, quantitative assessment of disease severity and monitoring, and prediction for decision support. While AI is a powerful technology that can be applied to medical imaging and is expected to improve our current clinical practice, some obstacles must be addressed for the successful implementation of AI in workflows. Understanding and becoming familiar with the current status and potential clinical applications of AI in chest imaging, as well as remaining challenges, would be essential for radiologists and clinicians in the era of AI. This review introduces the potential clinical applications of AI in chest imaging and also discusses the challenges for the implementation of AI in daily clinical practice and future directions in chest imaging.