Quantification of Resection Margin following Sublobar Resection in Lung Cancer Patients through Pre- and Post-Operative CT Image Comparison: Utilizing a CT-Based 3D Reconstruction Algorithm.

Sublobar resection has emerged as a standard treatment option for early-stage peripheral non-small cell lung cancer. Achieving an adequate resection margin is crucial to prevent local tumor recurrence. However, gross measurement of the resection margin may lack accuracy due to the elasticity of lung tissue and interobserver variability. Therefore, this study aimed to develop an objective measurement method, the CT-based 3D reconstruction algorithm, to quantify the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. An automated subvascular matching technique was first developed to ensure accuracy and reproducibility in the matching process. Following the extraction of matched feature points, another key technique involves calculating the displacement field within the image. This is particularly important for mapping discontinuous deformation fields around the surgical resection area. A transformation based on thin-plate spline is used for medical image registration. Upon completing the final step of image registration, the distance at the resection margin was measured. After developing the CT-based 3D reconstruction algorithm, we included 12 cases for resection margin distance measurement, comprising 4 right middle lobectomies, 6 segmentectomies, and 2 wedge resections. The outcomes obtained with our method revealed that the target registration error for all cases was less than 2.5 mm. Our method demonstrated the feasibility of measuring the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. Further validation with a multicenter, large cohort, and analysis of clinical outcome correlation is necessary in future studies.

2024 multidisciplinary consensus on image-guided lung tumor ablation from the Taiwan Academy of Tumor Ablation.

In this article, the multidisciplinary team of the Taiwan Academy of Tumor Ablation, who have expertise in treating lung cancer, present their perspectives on percutaneous image-guided thermal ablation (IGTA) of lung tumors. The modified Delphi technique was applied to reach a consensus on clinical practice guidelines concerning ablation procedures, including a comprehensive literature review, selection of panelists, creation of a rating form and survey, and arrangement of an in-person meeting where panelists agreed or disagreed on various points. The conclusion was a final rating and written summary of the agreement. The multidisciplinary expert team agreed on 10 recommendations for the use of IGTA in the lungs. These recommendations include terms and definitions, line of treatment planning, modality, facility rooms, patient anesthesia settings, indications, margin determination, post-ablation image surveillance, qualified centers, and complication ranges. In summary, IGTA is a safe and feasible approach for treating primary and metastatic lung tumors, with a relatively low complication rate. However, decisions regarding the ablation technique should consider each patient's specific tumor characteristics.

Clinical Variables and Radiomics Features for Predicting Pneumothorax in Patients Undergoing CT-guided Transthoracic Core Needle Biopsy.

Purpose To develop a prediction model combining both clinical and CT texture analysis radiomics features for predicting pneumothorax complications in patients undergoing CT-guided core needle biopsy. Materials and Methods A total of 424 patients (mean age, 65.6 years ± 12.7 [SD]; 232 male, 192 female) who underwent CT-guided core needle biopsy between January 2021 and October 2022 were retrospectively included as the training data set. Clinical and procedure-related characteristics were documented. Texture analysis radiomics features were extracted from the subpleural lung parenchyma traversed by needle. Moderate pneumothorax was defined as a postprocedure air rim of 2 cm or greater. The prediction model was developed using logistic regression with backward elimination, presented by linear fusion of the selected features weighted by their coefficients. Model performance was assessed using the area under the receiver operating characteristic curve (AUC). Validation was conducted in an external cohort (n = 45; mean age, 58.2 years ± 12.7; 19 male, 26 female) from a different hospital. Results Moderate pneumothorax occurred in 12.0% (51 of 424) of the training cohort and 8.9% (four of 45) of the external test cohort. Patients with emphysema (P < .001) or a longer needle path length (P = .01) exhibited a higher incidence of moderate pneumothorax in the training cohort. Texture analysis features, including gray-level co-occurrence matrix cluster shade (P < .001), gray-level run-length matrix low gray-level run emphasis (P = .049), gray-level run-length matrix run entropy (P = .003), gray-level size-zone matrix gray-level variance (P < .001), and neighboring gray-tone difference matrix complexity (P < .001), showed higher values in patients with moderate pneumothorax. The combined clinical-radiomics model demonstrated satisfactory performance in both the training (AUC 0.78, accuracy = 71.9%) and external test cohorts (AUC 0.86, accuracy 73.3%). Conclusion The model integrating both clinical and radiomics features offered practical diagnostic performance and accuracy for predicting moderate pneumothorax in patients undergoing CT-guided core needle biopsy. Keywords: Biopsy/Needle Aspiration, Thorax, CT, Pneumothorax, Core Needle Biopsy, Texture Analysis, Radiomics, CT Supplemental material is available for this article. © RSNA, 2024.

CT findings as predictive factors for treatment failure in Mycobacterium abscessus complex lung disease: a retrospective cohort study.

PURPOSE: Mycobacterium abscessus complex (MABC) commonly causes lung disease (LD) and has a high treatment failure rate of around 50%. In this study, our objective is to investigate specific CT patterns for predicting treatment prognosis and monitoring treatment response, thus providing valuable insights for clinical physicians in the management of MABC-LD treatment. METHODS: We retrospectively assessed 34 patients with MABC-LD treated between January 2015 and December 2020. CT scores for bronchiectasis, cellular bronchiolitis, consolidation, cavities, and nodules were measured at initiation and after treatment. The ability of the CT scores to predict treatment outcomes was analyzed in logistic regression analyses. RESULTS: The CT scoring system had excellent inter-reader agreement (all intraclass correlation coefficients, > 0.82). The treatment failure (TF) group (17/34; 50%) had higher cavitation diameter (p = 0.049) and extension (p = 0.041) at initial CT and higher cavitation diameter (p = 0.049) and extension (p =0 .045), consolidation (p = 0.022), and total (p = 0.013) scores at follow-up CT than the treatment success (TS) group. The changes of total score and consolidation score (p = 0.049 and 0.024, respectively) increased in the TF group more than the TS group between the initial and follow-up CT. Multivariable logistic regression analysis showed initial cavitation extension, follow-up consolidation extension, and change in consolidation extension (adjusted odds ratio: 2.512, 2.495, and 9.094, respectively, per 1-point increase; all p < 0.05) were significant predictors of treatment failure. CONCLUSIONS: A high pre-treatment cavitation extension score and an increase in the consolidation extension score during treatment on CT could be alarm signs of treatment failure requiring tailor the treatment of MABC-LD carefully.

Hemorrhage risk prediction after computed tomography-guided lung biopsy: Clinical parameters and quantitative pulmonary vascular analysis.

BACKGROUND/PURPOSE: We evaluated the utility of combining quantitative pulmonary vasculature measures with clinical factors for predicting pulmonary hemorrhage after computed tomography (CT)-guided lung biopsy. METHODS: Patients who underwent CT-guided lung biopsy were retrospectively included in this study. Clinical and radiographic vasculature variables were evaluated as predictors of pulmonary hemorrhage. The radiographic pulmonary vascular analysis included vessel count, density, diameter, and area, and also blood volume in small vessels with a cross-sectional area ≤5 mm2 (BV5) and total blood vessel volume (TBV) in the lungs. Univariate and multivariate logistic regressions were used to identify the independent risk factors of higher-grade pulmonary hemorrhage and establish the prediction model presented as a nomogram. RESULTS: The study included 126 patients; discovery cohort n = 103, and validation cohort n = 23. All pulmonary hemorrhage, higher-grade (grade ≥2) pulmonary hemorrhage, and hemoptysis occurred in 42.9%, 15.9%, and 3.2% of patients who underwent CT-guided lung biopsies. In the discovery cohort, patients with larger lesion depth (p = 0.013), higher vessel density (p = 0.033), and higher BV5 (p = 0.039) were more likely to experience higher-grade hemorrhage. The nomogram prediction model for higher-grade hemorrhage built by the discovery cohort showed similar performance in the validation cohort. CONCLUSIONS: Higher-grade pulmonary hemorrhage may occur after CT-guided lung biopsy. Lesion depth, vessel density, and BV5 are independent risk factors for higher-grade pulmonary hemorrhage. Nomograms integrating clinical parameters and radiographic pulmonary vasculature measures offer enhanced capability for assessing hemorrhage risk following CT-guided lung biopsy, thereby facilitating improved patient clinical care.

Dual-energy computed tomography for evaluating nodal staging in lung adenocarcinoma: correlation with surgical pathology.

PURPOSE: To ascertain the performance of dual-energy CT (DECT) with iodine quantification in differentiating malignant mediastinal and hilar lymph nodes (LNs) from benign ones, focusing on patients with lung adenocarcinoma. MATERIALS AND METHODS: In this study, patients with suspected lung cancer received a preoperative contrast-enhanced DECT scan from Jun 2018 to Dec 2020. Quantitative DECT parameters and the size were compared between metastatic and benign LNs. Their diagnostic performances were analyzed by the ROC curves and compared by using the two-sample t test. RESULTS: 72 patients (23 men, 49 women; mean age 62.5 ± 10.1 years) fulfilled the inclusion criteria. A total of 98 LNs (67 benign, 31 metastatic) were analyzed. The iodine concentration normalized by muscle (NICmuscle) was significantly higher (P < 0.001) in metastatic LNs (4.79 ± 1.70) than in benign ones (3.00 ± 1.45). The optimal threshold of NICmuscle was 3.44, which yielded AUC: 0.798, sensitivity: 83.9%, specificity: 73.1%, accuracy: 76.5%, respectively. Applying the established size parameters with 10 mm as the threshold yielded AUC: 0.600, sensitivity: 29.0%, specificity: 91.0%, accuracy: 71.4%, respectively. The diagnostic performance of NICmuscle was significantly better (P = 0.007) than the performance obtained using the established size parameters. CONCLUSIONS: For lung adenocarcinoma, the quantitative measurement of NICmuscle derived from DECT is useful for differentiating benign and metastatic mediastinal and hilar LNs before surgical intervention.

CT findings of 144 in-hospital patients with influenza pneumonia: A retrospective analysis.

BACKGROUND/PURPOSE: Patients with influenza infection during their period of admission may have worse computed tomography (CT) manifestation according to the clinical status. This study aimed to evaluate the CT findings of in-hospital patients due to clinically significant influenza pneumonia with correlation of clinical presentations. METHODS: In this retrospective, single center case series, 144 patients were included. All in-hospital patients were confirmed influenza infection and underwent CT scan. These patients were divided into three groups according to the clinical status of the most significant management: (1) without endotracheal tube and mechanical ventilator (ETTMV) or extracorporeal membrane oxygenation (ECMO); (2) with ETTMV; (3) with ETTMV and ECMO. Pulmonary opacities were scored according to extent. Spearman rank correlation analysis was used to evaluate the correlation between clinical parameters and CT scores. RESULTS: The predominant CT manifestation of influenza infection was mixed ground-glass opacity (GGO) and consolidation with both lung involvement. The CT scores were all reach significant difference among all three groups (8.73 ± 6.29 vs 12.49 ± 6.69 vs 18.94 ± 4.57, p < 0.05). The chest CT score was correlated with age, mortality, and intensive care unit (ICU) days (all p values were less than 0.05). In addition, the CT score was correlated with peak lactate dehydrogenase (LDH) level and peak C-reactive protein (CRP) level (all p values were less than 0.05). Concomitant bacterial infection had higher CT score than primary influenza pneumonia (13.02 ± 7.27 vs 8.95 ± 5.99, p < 0.05). CONCLUSION: Thin-section chest CT scores correlated with clinical and laboratory parameters in in-hospital patients with influenza pneumonia.

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.

BACKGROUND: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread through air spaces (STAS). Thus, preoperative prediction of STAS is important for surgical planning. This study aimed to develop a STAS deep-learning (STAS-DL) prediction model in lung adenocarcinoma with tumor smaller than 3 cm and a consolidation-to-tumor (C/T) ratio less than 0.5. METHODS: The study retrospectively enrolled of 581 patients from two institutions between 2015 and 2019. The STAS-DL model was developed to extract the feature of solid components through solid components gated (SCG) for predicting STAS. The STAS-DL model was assessed with external validation in the testing sets and compared with the deep-learning model without SCG (STAS-DLwoSCG), the radiomics-based model, the C/T ratio, and five thoracic surgeons. The performance of the models was evaluated using area under the curve (AUC), accuracy and standardized net benefit of the decision curve analysis. RESULTS: The study evaluated 458 patients (institute 1) in the training set and 123 patients (institute 2) in the testing set. The proposed STAS-DL yielded the best performance compared with the other methods in the testing set, with an AUC of 0.82 and an accuracy of 74%, outperformed the STAS-DLwoSCG with an accuracy of 70%, and was superior to the physicians with an AUC of 0.68. Moreover, STAS-DL achieved the highest standardized net benefit compared with the other methods. CONCLUSION: The proposed STAS-DL model has great potential for the preoperative prediction of STAS and may support decision-making for surgical planning in early-stage, ground glass-predominant lung adenocarcinoma.

Low-dose CT screening among never-smokers with or without a family history of lung cancer in Taiwan: a prospective cohort study.

BACKGROUND: In Taiwan, lung cancers occur predominantly in never-smokers, of whom nearly 60% have stage IV disease at diagnosis. We aimed to assess the efficacy of low-dose CT (LDCT) screening among never-smokers, who had other risk factors for lung cancer. METHODS: The Taiwan Lung Cancer Screening in Never-Smoker Trial (TALENT) was a nationwide, multicentre, prospective cohort study done at 17 tertiary medical centres in Taiwan. Eligible individuals had negative chest radiography, were aged 55-75 years, had never smoked or had smoked fewer than 10 pack-years and stopped smoking for more than 15 years (self-report), and had one of the following risk factors: a family history of lung cancer; passive smoke exposure; a history of pulmonary tuberculosis or chronic obstructive pulmonary disorders; a cooking index of 110 or higher; or cooking without using ventilation. Eligible participants underwent LDCT at baseline, then annually for 2 years, and then every 2 years up to 6 years thereafter, with follow-up assessments at each LDCT scan (ie, total follow-up of 8 years). A positive scan was defined as a solid or part-solid nodule larger than 6 mm in mean diameter or a pure ground-glass nodule larger than 5 mm in mean diameter. Lung cancer was diagnosed through invasive procedures, such as image-guided aspiration or biopsy or surgery. Here, we report the results of 1-year follow-up after LDCT screening at baseline. The primary outcome was lung cancer detection rate. The p value for detection rates was estimated by the χ2 test. Univariate and multivariable logistic regression analyses were used to assess the association between lung cancer incidence and each risk factor. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of LDCT screening were also assessed. This study is registered with ClinicalTrials.gov, NCT02611570, and is ongoing. FINDINGS: Between Dec 1, 2015, and July 31, 2019, 12 011 participants (8868 females) were enrolled, of whom 6009 had a family history of lung cancer. Among 12 011 LDCT scans done at baseline, 2094 (17·4%) were positive. Lung cancer was diagnosed in 318 (2·6%) of 12 011 participants (257 [2·1%] participants had invasive lung cancer and 61 [0·5%] had adenocarcinomas in situ). 317 of 318 participants had adenocarcinoma and 246 (77·4%) of 318 had stage I disease. The prevalence of invasive lung cancer was higher among participants with a family history of lung cancer (161 [2·7%] of 6009 participants) than in those without (96 [1·6%] of 6002 participants). In participants with a family history of lung cancer, the detection rate of invasive lung cancer increased significantly with age, whereas the detection rate of adenocarcinoma in situ remained stable. In multivariable analysis, female sex, a family history of lung cancer, and age older than 60 years were associated with an increased risk of lung cancer and invasive lung cancer; passive smoke exposure, cumulative exposure to cooking, cooking without ventilation, and a previous history of chronic lung diseases were not associated with lung cancer, even after stratification by family history of lung cancer. In participants with a family history of lung cancer, the higher the number of first-degree relatives affected, the higher the risk of lung cancer; participants whose mother or sibling had lung cancer were also at an increased risk. A positive LDCT scan had 92·1% sensitivity, 84·6% specificity, a PPV of 14·0%, and a NPV of 99·7% for lung cancer diagnosis. INTERPRETATION: TALENT had a high invasive lung cancer detection rate at 1 year after baseline LDCT scan. Overdiagnosis could have occurred, especially in participants diagnosed with adenocarcinoma in situ. In individuals who do not smoke, our findings suggest that a family history of lung cancer among first-degree relatives significantly increases the risk of lung cancer as well as the rate of invasive lung cancer with increasing age. Further research on risk factors for lung cancer in this population is needed, particularly for those without a family history of lung cancer. FUNDING: Ministry of Health and Welfare of Taiwan.

Discrimination of invasive lung adenocarcinoma from Lung-RADS category 2 nonsolid nodules through visual assessment: a retrospective study.

OBJECTIVES: Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category. METHODS: This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)-guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant. RESULTS: A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively. CONCLUSIONS: The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs. CLINICAL RELEVANCE STATEMENT: The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions. KEY POINTS: • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window-visible and the bone window-invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window.

Cone-beam computed tomography image-guided percutaneous microwave ablation for lung nodules in a hybrid operating room: an initial experience.

OBJECTIVES: The experience of thermal ablation of lung lesions is limited, especially performing the procedure under localisation by cone-beam CT in the hybrid operation room (HOR). Here, we present the experience of microwave ablation (MWA) of lung nodules in the HOR. METHODS: We reviewed patients who underwent image-guide percutaneous MWA for lung nodules in the HOR under general anaesthesia between July 2020 and July 2022. The workflow in the HOR including the pre-procedure preparation, anaesthesia consideration, operation methods, and postoperative care was clearly described. RESULTS: Forty lesions in 33 patients who underwent MWA under general anaesthesia (GA) in the HOR were analysed. Twenty-seven patients had a single pulmonary nodule, and the remaining six patients had multiple nodules. The median procedure time was 41.0 min, and the median ablation time per lesion was 6.75 min. The median global operation room time was 115.0 min. The median total dose area product was 14881 µGym2. The median ablation volume was 111.6 cm3. All patients were discharged from the hospital with a median postoperative stay of 1 day. Four patients had pneumothorax, two patients had pleural effusion during the first month of outpatient follow-up, and one patient reported intercostal neuralgia during the 3-month follow-up. CONCLUSIONS: Thermal ablation of pulmonary nodules under GA in the HOR can be performed safely and efficiently if we follow the workflow provided. The procedure provides an alternative to managing pulmonary nodules in patients. CLINICAL RELEVANCE STATEMENT: Thermal ablation of pulmonary nodules under GA in the HOR can be performed safely and efficiently if the provided workflow is followed. KEY POINTS: • We tested the feasibility of microwave ablation of lung lesions performed in a hybrid operating room. • To this end, we provide a description of microwave ablation of the lung under cone-beam CT localisation. • We describe a workflow by which ablation of the pulmonary nodule can be performed safely under general anaesthesia.

Automated marker-free longitudinal infrared breast image registration by GA-PSO.

The automated marker-free longitudinal Infrared (IR) breast image registration overcomes several challenges like no anatomic fiducial markers on the body surface, blurry boundaries, heat pattern variation by environmental and physiological factors, nonrigid deformation, etc, has the ability of quantitative pixel-wise analysis with the heat energy and patterns change in a time course study. To achieve the goal, scale-invariant feature transform, Harris corner, and Hessian matrix were employed to generate the feature points as anatomic fiducial markers, and hybrid genetic algorithm and particle swarm optimization minimizing the matching errors was used to find the appropriate corresponding pairs between the 1st IR image and thenth IR image. Moreover, the mechanism of the IR spectrogram hardware system has a high level of reproducibility. The performance of the proposed longitudinal image registration system was evaluated by the simulated experiments and the clinical trial. In the simulated experiments, the mean difference of our system is 1.64 mm, which increases 57.58% accuracy than manual determination and makes a 17.4% improvement than the previous study. In the clinical trial, 80 patients were captured several times of IR breast images during chemotherapy. Most of them were well aligned in the spatiotemporal domain. In the few cases with evident heat pattern dissipation and spatial deviation, it still provided a reliable comparison of vascular variation. Therefore, the proposed system is accurate and robust, which could be considered as a reliable tool for longitudinal approaches to breast cancer diagnosis.

Clinical outcomes and risk factors of progressive pulmonary fibrosis in primary Sjögren's syndrome-associated interstitial lung disease.

BACKGROUND: To investigate the clinical outcomes and risk factors associated with progressive fibrosing interstitial lung disease (PF-ILD) in patients with primary Sjögren's syndrome-associated interstitial lung disease (pSjS-ILD). METHODS: During 2015-2021, pSjS patients with ILD were retrospectively identified. Patients were grouped into non-PF-ILD and PF-ILD. Demographics, laboratory data, pulmonary function tests (PFTs), images, survival outcomes were compared between groups. RESULTS: 153 patients with SjS-ILD were reviewed, of whom 68 having primary SjS-ILD (pSjS-ILD) were classified into non-PF-ILD (n = 34) and PF-ILD groups (n = 34). PF-ILD group had persistently lower albumin levels and a smaller decline in immunoglobulin G (IgG) levels at the 3rd month of follow-up. The multivariate logistic regression analysis revealed that persistently low albumin levels were associated with PF-ILD. At the 12th month, the PF-ILD group experienced a smaller increase in FVC and a greater decline in the diffusion capacity of carbon monoxide (DLCO) than at baseline. The 3-year overall survival rate was 91.2%, and PF-ILD group had significantly poorer 3-year overall survival rate than non-PF-ILD group (82.4% vs. 100%, p = 0.011). Poor survival was also observed among female patients with PF-ILD. CONCLUSIONS: Among patients with pSjS-ILD, the PF-ILD group had poorer 3-year survival outcomes. Persistent lower albumin level might be the risk factor of PF-ILD. Early lung function tests could be helpful for the early detection of PF-ILD.

Lung Cancer Screening in Asia: An Expert Consensus Report.

INTRODUCTION: The incidence and mortality of lung cancer are highest in Asia compared with Europe and USA, with the incidence and mortality rates being 34.4 and 28.1 per 100,000 respectively in East Asia. Diagnosing lung cancer at early stages makes the disease amenable to curative treatment and reduces mortality. In some areas in Asia, limited availability of robust diagnostic tools and treatment modalities, along with variations in specific health care investment and policies, make it necessary to have a more specific approach for screening, early detection, diagnosis, and treatment of patients with lung cancer in Asia compared with the West. METHOD: A group of 19 advisors across different specialties from 11 Asian countries, met on a virtual Steering Committee meeting, to discuss and recommend the most affordable and accessible lung cancer screening modalities and their implementation, for the Asian population. RESULTS: Significant risk factors identified for lung cancer in smokers in Asia include age 50 to 75 years and smoking history of more than or equal to 20 pack-years. Family history is the most common risk factor for nonsmokers. Low-dose computed tomography screening is recommended once a year for patients with screening-detected abnormality and persistent exposure to risk factors. However, for high-risk heavy smokers and nonsmokers with risk factors, reassessment scans are recommended at an initial interval of 6 to 12 months with subsequent lengthening of reassessment intervals, and it should be stopped in patients more than 80 years of age or are unable or unwilling to undergo curative treatment. CONCLUSIONS: Asian countries face several challenges in implementing low-dose computed tomography screening, such as economic limitations, lack of efforts for early detection, and lack of specific government programs. Various strategies are suggested to overcome these challenges in Asia.

Treatment Response Evaluation by Computed Tomography Pulmonary Vasculature Analysis in Patients With Chronic Thromboembolic Pulmonary Hypertension.

OBJECTIVE: To quantitatively assess the pulmonary vasculature using non-contrast computed tomography (CT) in patients with chronic thromboembolic pulmonary hypertension (CTEPH) pre- and post-treatment and correlate CT-based parameters with right heart catheterization (RHC) hemodynamic and clinical parameters. MATERIALS AND METHODS: A total of 30 patients with CTEPH (mean age, 57.9 years; 53% female) who received multimodal treatment, including riociguat for ≥ 16 weeks with or without balloon pulmonary angioplasty and underwent both non-contrast CT for pulmonary vasculature analysis and RHC pre- and post-treatment were included. The radiographic analysis included subpleural perfusion parameters, including blood volume in small vessels with a cross-sectional area ≤ 5 mm² (BV5) and total blood vessel volume (TBV) in the lungs. The RHC parameters included mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), and cardiac index (CI). Clinical parameters included the World Health Organization (WHO) functional class and 6-minute walking distance (6MWD). RESULTS: The number, area, and density of the subpleural small vessels increased after treatment by 35.7% (P < 0.001), 13.3% (P = 0.028), and 39.3% (P < 0.001), respectively. The blood volume shifted from larger to smaller vessels, as indicated by an 11.3% increase in the BV5/TBV ratio (P = 0.042). The BV5/TBV ratio was negatively correlated with PVR (r = -0.26; P = 0.035) and positively correlated with CI (r = 0.33; P = 0.009). The percent change across treatment in the BV5/TBV ratio correlated with the percent change in mPAP (r = -0.56; P = 0.001), PVR (r = -0.64; P < 0.001), and CI (r = 0.28; P = 0.049). Furthermore, the BV5/TBV ratio was inversely associated with the WHO functional classes I-IV (P = 0.004) and positively associated with 6MWD (P = 0.013). CONCLUSION: Non-contrast CT measures could quantitatively assess changes in the pulmonary vasculature in response to treatment and were correlated with hemodynamic and clinical parameters.

High rate of postoperative upstaging of ductal carcinoma in situ when prioritizing ultrasound evaluation of mammography-detected lesions: a single-center retrospective cohort study.

BACKGROUND: The initial diagnosis of ductal carcinoma in situ (DCIS) can be upstaged to invasive cancer after definitive surgery. This study aimed to identify risk factors for DCIS upstaging using routine breast ultrasonography and mammography (MG) and to propose a prediction model. METHODS: In this single-center retrospective study, patients initially diagnosed with DCIS (January 2016-December 2017) were enrolled (final sample size = 272 lesions). Diagnostic modalities included ultrasound-guided core needle biopsy (US-CNB), MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy. Breast ultrasonography was routinely performed for all patients. US-CNB was prioritized for lesions visible on ultrasound. Lesions initially diagnosed as DCIS on biopsy with a final diagnosis of invasive cancer at definitive surgery were defined as "upstaged." RESULTS: The postoperative upstaging rates were 70.5%, 9.7%, and 4.8% in the US-CNB, MG-guided vacuum-assisted breast biopsy, and wire-localized surgical biopsy groups, respectively. US-CNB, ultrasonographic lesion size, and high-grade DCIS were independent predictive factors for postoperative upstaging, which were used to construct a logistic regression model. Receiver operating characteristic analysis showed good internal validation (area under the curve = 0.88). CONCLUSIONS: Supplemental screening breast ultrasonography possibly contributes to lesion stratification. The low upstaging rate for ultrasound-invisible DCIS diagnosed by MG-guided procedures suggests that it is unnecessary to perform sentinel lymph node biopsy for lesions invisible on ultrasound. Case-by-case evaluation of DCIS detected by US-CNB can help surgeons determine if repeating biopsy with vacuum-assisted breast biopsy is necessary or if sentinel lymph node biopsy should accompany breast-preserving surgery. TRIAL REGISTRATION: This single-center retrospective cohort study was conducted with the approval of the institutional review board of our hospital (approval number 201610005RIND). As this was a retrospective review of clinical data, it was not registered prospectively.

Xenon-Enhanced Ventilation Computed Tomography for Functional Lung Avoidance Radiation Therapy in Patients With Lung Cancer.

PURPOSE: This phase 2 trial aimed to determine whether xenon-enhanced ventilation computed tomography (XeCT)-guided functional-lung-avoidance radiation therapy could reduce the radiation pneumonitis (RP) rate in patients with lung cancer undergoing definitive chemoradiation therapy. METHODS AND MATERIALS: Functional lung ventilation was measured via pulmonary function testing (PFT) and XeCT. A standard plan (SP) without reference to XeCT and a functional-lung-avoidance plan (fAP) optimized for lowering the radiation dose to the functional lung at the guidance of XeCT were designed. Dosimetric parameters and predicted RP risks modeled by biological evaluation were compared between the 2 plans in a treatment planning system (TPS). All patients received the approved fAP. The primary endpoint was the rate of grade ≥2 RP, and the secondary endpoints were the survival outcomes. The study hypothesis was that fAP could reduce the rate of grade ≥2 RP to 12% compared with a 30% historical rate. RESULTS: Thirty-six patients were evaluated. Xenon-enhanced total functional lung volumes positively correlated with PFT ventilation parameters (forced vital capacity, P = .012; forced expiratory volume in 1 second, P = .035), whereas they were not correlated with the diffusion capacity parameter. We observed a 17% rate of grade ≥2 RP (6 of 36 patients), which was significantly different (P = .040) compared with the historical control. Compared with the SP, the fAP significantly spared the total ventilated lung, leading to a reduction in predicted grade ≥2 RP (P = .001) by TPS biological evaluation. The median follow-up was 15.2 months. The 1-year local control (LC), disseminated failure-free survival (DFFS), and overall survival (OS) rates were 88%, 66%, and 91%, respectively. The median LC and OS were not reached, and the median DFFS was 24.0 months (95% confidence interval, 15.7-32.3 months). CONCLUSIONS: This report of XeCT-guided functional-lung-avoidance radiation therapy provided evidence showing its feasibility in clinical practice. Its benefit should be assessed in a broader multicenter trial setting.

An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification.

BACKGROUND AND OBJECTIVE: Lung cancer has the highest cancer-related mortality worldwide, and lung nodule usually presents with no symptom. Low-dose computed tomography (LDCT) was an important tool for lung cancer detection and diagnosis. It provided a complete three-dimensional (3-D) chest image with a high resolution.Recently, convolutional neural network (CNN) had flourished and been proven the CNN-based computer-aided diagnosis (CADx) system could extract the features and help radiologists to make a preliminary diagnosis. Therefore, a 3-D ResNeXt-based CADx system was proposed to assist radiologists for diagnosis in this study. METHODS: The proposed CADx system consists of image preprocessing and a 3-D CNN-based classification model for pulmonary nodule classification. First, the image preprocessing was executed to generate the normalized volumn of interest (VOI) only including nodule information and a few surrounding tissues. Then, the extracted VOI was forwarded to the 3-D nodule classification model. In the classification model, the RestNext was employed as the backbone and the attention scheme was embedded to focus on the important features. Moreover, a multi-level feature fusion network incorporating feature information of different scales was used to enhance the prediction accuracy of small malignant nodules. Finally, a hybrid loss based on channel optimization which make the network learn more detailed information was empolyed to replace a binary cross-entropy (BCE) loss. RESULTS: In this research, there were a total of 880 low-dose CT images including 440 benign and 440 malignant nodules from the American National Lung Screening Trial (NLST) for system evaluation. The results showed that our system could achieve the accuracy of 85.3%, the sensitivity of 86.8%, the specificity of 83.9%, and the area-under-curve (AUC) value was 0.9042. It was confirmed that the designed system had a good diagnostic ability. CONCLUSION: In this study, a CADx composed of the image preprocessing and a 3-D nodule classification model with attention scheme, feature fusion, and hybrid loss was proposed for pulmonary nodule classification in LDCT. The results indicated that the proposed CADx system had potential for achieving high performance in classifying lung nodules as benign and malignant.

Radiologist burnout: Trends in medical imaging utilization under the national health insurance system with the universal code bundling strategy in an academic tertiary medical centre.

PURPOSE: The utilization of diagnostic medical imaging has been growing worldwide. However, no study has investigated the trend in image utilization and the corresponding workload of radiologists under the National Healthcare Insurance (NHI) system with a code-bundling-based reimbursement strategy. We will analyse the trend in diagnostic imaging utilization and the corresponding workload of the radiologists at a single tertiary medical centre using the NHI system. MATERIALS AND METHODS: This was a retrospective study recruiting the diagnostic medical images, including X-rays, CT, and MR performed between 2005 and 2020 at a single medical centre. We investigated the change over time in image utilization and workload for interpreting the images. The two-sided Mann-Kendall test was used for the monotonic trend analysis and Sen's slope estimate was calculated for the annual mean change with the 95% confidence interval (CI). A P value < 0.05 was considered significant. RESULTS: A total of 10,069,583 examinations were performed at our institute from 2005 to 2020, including 7,821,880 X-rays, 1,665,787 CT, and 581,916 MR examinations. The numbers of examinations of X-rays, CT, and MR increased with average annual changes of 13,411.3 (95% CI = 11,875.0-14,773.8), 9,496.7 (95% CI = 8,845.3-9,828.7), and 2,417.1 (95% CI = 2,209.8-2,668.9) respectively, all P < 0.001. The proportion of cases including multiple examinations increased, growing from 21.5% (6,627 in 30,878 cases) to 43.8% (39,417 in 90,032 cases) for CT and from 8.9% (1,316 in 14,791 cases) to 15.7% (6,083 in 38,865 cases) for MR. The average time spent on interpreting each diagnostic image decreased significantly from 16.0 to 2.9 sec. (P < 0.001). CONCLUSION: Imaging utilization increased significantly under the NHI system at a medical centre. The corresponding demand for image interpretation also placed a significant workload on radiologists, potentially contributing to radiologist burnout.