Journal of Thoracic Imaging最新文献

{"title":"Acute Lung Injury.","authors":"Nupur Verma, Bruno Hochhegger, Sanjay Mukhopadhyay, Pedro Paulo Teixeira E Silva Torres, Tan-Lucien Mohammed","doi":"10.1097/RTI.0000000000000820","DOIUrl":"10.1097/RTI.0000000000000820","url":null,"abstract":"<p><p>Acute lung injury (ALI) is acute pulmonary inflammation with underlying pathology of disruption of the pulmonary vasculature endothelial and alveolar epithelial barriers. ALI is not an uncommon diagnosis and has a myriad of causes including pulmonary infection, (including sepsis), drugs, connective tissue disease, and polytrauma. Patients present clinically with hypoxemia with imaging supportive of bilateral pulmonary findings without pulmonary edema. The imaging findings in ALI mirror pathologic changes, with a transition from an early (\"exudative\") phase to a later fibroblast-rich (\"organizing\" or \"proliferative\") phase to, in some cases, a fibrotic phase. The diagnosis of ALI is separate from, but can clinically overlap in presentation with, acute respiratory distress syndrome and is characterized by diffuse alveolar damage and organizing pneumonia patterns on pathology. Clinical management is most often supportive and can include corticosteroids, mechanical ventilation, and careful fluid management, with the goal of preserving and recovering lung function.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142803039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Azygos Esophageal Recess Is Not to Be Missed in Screening Lung Cancer With LDCT.","authors":"Mario Mascalchi, Edoardo Cavigli, Giulia Picozzi, Diletta Cozzi, Giulia Raffaella De Luca, Stefano Diciotti","doi":"10.1097/RTI.0000000000000813","DOIUrl":"10.1097/RTI.0000000000000813","url":null,"abstract":"<p><strong>Purpose: </strong>Lesion overlooking and late diagnostic workup can compromise the efficacy of low-dose CT (LDCT) screening of lung cancer (LC), implying more advanced and less curable disease stages. We hypothesized that the azygos esophageal recess (AER) of the right lower lobe (RLL) might be an area prone to lesion overlooking in LC screening.</p><p><strong>Materials and methods: </strong>Two radiologists reviewed the LDCT examinations of all the screen-detected incident LCs observed in the active arm of 2 randomized clinical trials: ITALUNG and national lung screening trial. Those in the AER were compared with those in the remainder of the RLL for possible differences in diagnostic lag according to the Lung-RADS 1.1 recommendations, size, stage, and mortality.</p><p><strong>Results: </strong>Six (11.7%) of 51 screen-detected incident LCs of the RLL were located in the AER. The diagnostic lag time was significantly longer ( P =0.046) in the AER LC (mean 14±9 mo) than in the LC in the remaining RLL (mean 7.3±1 mo). Size and stage at diagnosis were not significantly different. All 6 subjects with LC in the AER and 16 (35.5%) of 45 subjects with LC in the remaining RLL ( P =0.004) died of LC after a median follow-up of 12 years.</p><p><strong>Conclusion: </strong>Our retrospective study indicates that AER might represent a lung region of the RLL prone to have early LC overlooked due to detection or interpretation errors with possible detrimental consequences for the subject undergoing LC screening.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142299688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pulmonary Embolism Survival Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data.","authors":"Zhusi Zhong, Helen Zhang, Fayez H Fayad, Andrew C Lancaster, John Sollee, Shreyas Kulkarni, Cheng Ting Lin, Jie Li, Xinbo Gao, Scott Collins, Colin F Greineder, Sun H Ahn, Harrison X Bai, Zhicheng Jiao, Michael K Atalay","doi":"10.1097/RTI.0000000000000831","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000831","url":null,"abstract":"<p><strong>Purpose: </strong>Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using computed tomography pulmonary angiography (CTPA), clinical data, and PE Severity Index (PESI) scores to predict PE survival.</p><p><strong>Materials and methods: </strong>In total, 918 patients (median age 64 y, range 13 to 99 y, 48% male) with 3978 CTPAs were identified via retrospective review across 3 institutions. To predict survival, an AI model was used to extract disease-related imaging features from CTPAs. Imaging features and clinical variables were then incorporated into independent DL models to predict survival outcomes. Cross-modal fusion CoxPH models were used to develop multimodal models from combinations of DL models and calculated PESI scores. Five multimodal models were developed as follows: (1) using CTPA imaging features only, (2) using clinical variables only, (3) using both CTPA and clinical variables, (4) using CTPA and PESI score, and (5) using CTPA, clinical variables, and PESI score. Performance was evaluated using the concordance index (c-index). Kaplan-Meier analysis was performed to stratify patients into high-risk and low-risk groups. Additional factor-risk analysis was conducted to account for right ventricular (RV) dysfunction.</p><p><strong>Results: </strong>For both data sets, the multimodal models incorporating CTPA features, clinical variables, and PESI score achieved higher c-indices than PESI alone. Following the stratification of patients into high-risk and low-risk groups by models, survival outcomes differed significantly (both P<0.001). A strong correlation was found between high-risk grouping and RV dysfunction.</p><p><strong>Conclusions: </strong>Multiomic DL models incorporating CTPA features, clinical data, and PESI achieved higher c-indices than PESI alone for PE survival prediction.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143812346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging and Clinical Features of Nodular Pulmonary Amyloidosis.","authors":"Fei Li, Junting Li, Yanyan Li, Danting Shang, Xingyi Hou, Yanli He, Gangfeng Li","doi":"10.1097/RTI.0000000000000830","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000830","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the clinical and computed tomography (CT) features of nodular pulmonary amyloidosis (NPA) to enhance our understanding of the disease and improve the ability to differentiate it from other similar conditions.</p><p><strong>Materials and methods: </strong>A retrospective analysis was conducted on the clinical data, chest CT imaging findings, and pathologic characteristics of 13 patients with NPA in our hospital from April 2014 to April 2024. All 13 patients underwent chest CT plain scan examination. The basic data, medical history, clinical manifestations, and lung lesion features on chest CT imaging were analyzed and summarized.</p><p><strong>Results: </strong>Among the 13 patients, there were 3 males (23.08%) and 10 females (76.92%). Their ages ranged from 37 to 68 years, with a mean age of (57.85±8.40) years and a median age of 59 years. Three (23.08%) patients had cough and sputum, while the others (76.92%) had no clinical symptoms. Before surgery, 6 patients underwent chest CT scans, and NPA changes in size, shape, and density were observed. Six cases (46.15%) were located in the left lung (4 in the upper lobe and 2 in the lower lobe), and 7 cases (53.85%) in the right lung (3 in the upper lobe, 2 in the middle lobe, and 2 in the lower lobe). Seven cases (53.85%) of NPA were round or oval, while 6 cases (46.15%) were irregularly shaped. Out of the NPA cases, 11 (84.62%) were solid nodules with well-defined boundaries, including 2 cases of solid nodules with surrounding calcification. In addition, 2 cases presented as solid nodules with cavities. Ten cases (76.92%) had multiple cystic lesions in the bilateral lungs, in which 7 cases had more than 10 cysts with obvious cyst walls, and 1 case showed a solid nodule on the cyst wall. During the postoperative follow-up, 1 patient experienced an increase in the size of the original nodule and the appearance of new solid nodules. Subsequent surgery revealed mucosal-associated lymphoid tissue lymphoma (MALT). The remaining patients were followed up regularly, and their conditions remained stable.</p><p><strong>Conclusions: </strong>NPA is more common in middle-aged and elderly people and is more likely to occur in women. Most cases are asymptomatic, and bilateral lungs can be involved. For nodules with multiple pulmonary cysts found by chest CT, the possibility of NPA should be considered, and further histopathologic examination is needed to confirm the diagnosis. Most patients with NPA have a good long-term prognosis after surgical resection, but some patients require further investigation and close follow-up due to underlying causes.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143796892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bronchial Arterial Chemoembolization With Drug-eluting Beads Versus With Gelfoam Particles for Advanced Nonsmall-cell Lung Cancer.","authors":"Xuedong Sun, Yanjing Han, Qi Wang, Tianhao Su, Yuefeng Hu, Jian Wei, Zhiyuan Zhang, Siwei Yang, Long Jin","doi":"10.1097/RTI.0000000000000829","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000829","url":null,"abstract":"<p><strong>Background: </strong>Bronchial arterial chemoembolization (BACE), as a safe and effective minimally invasive treatment method, is increasingly being accepted by more and more patients with advanced nonsmall-cell lung cancer (NSCLC). In recent years, drug-eluting beads (DEB)-BACE has also been applied in the field of lung cancer. It is still unclear which is more recommended due to the limited number of comparative studies between conventional BACE (C-BACE) and DEB-BACE.</p><p><strong>Purpose: </strong>To compare the safety and efficacy of C-BACE (BACE with gelfoam particles) and DEB-BACE for advanced NSCLC.</p><p><strong>Materials and methods: </strong>From January 2021 to April 2023, 48 consecutive patients (37 males and 11 females) with advanced NSCLC treated with DEB-BACE (group A) or C-BACE (group B) at our center were collected retrospectively in this study. There were 18 patients in group A and 30 patients in group B. The technical success rate, adverse events, objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were compared between the 2 groups.</p><p><strong>Results: </strong>The technical success rate in both groups was 100%. The median OS times were 19.5 months and 12.5 months in group A and group B, respectively (P=0.0062). The median PFS times were 13 months and 7 months in group A and group B, respectively (P=0.0072). The ORRs at 6 months were 72.2% and 46.7% in group A and group B, respectively (P=0.084). The DCRs at 6 months were 88.9% and 63.3% in group A and group B, respectively (P=0.043). Grade 1 adverse events like chest pain, and cough were common, while serious adverse events did not occur.</p><p><strong>Conclusions: </strong>BACE with DEB or gelfoam particles were equally safe. The DEB-BACE showed better survival and tumor response than C-BACE for advanced NSCLC.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143774672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Conundrum of Computed Tomography Findings in Chronic Pulmonary Aspergillosis: Insights From 103 Cases.","authors":"Mandeep Garg, Harsimran Bhatia, Inderpaul Sehgal, Shritik Devkota, Nidhi Prabhakar, Uma Debi, Rajender Kumar, Shivaprakash M Rudramurthy, Valliapan Muthu, Ritesh Agarwal","doi":"10.1097/RTI.0000000000000828","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000828","url":null,"abstract":"<p><strong>Purpose: </strong>To describe the spectrum of computed tomography (CT) findings in various chronic pulmonary aspergillosis (CPA) subtypes.</p><p><strong>Material and methods: </strong>This retrospective study analyzed the CT scans of consecutively diagnosed CPA cases. Two radiologists independently evaluated the CT findings (both qualitatively and quantitatively) to characterize the lung cavities, intracavitary contents, pericavitary opacities and fibrosis, mediastinal shift, pleural thickening, and underlying structural lung disease. Patients were then classified into CPA subtypes, and between-group differences were assessed using the sample t test, Wilcoxon test, χ2 test, and Fisher exact test.</p><p><strong>Results: </strong>Among 103 patients with CPA (mean age: 47.26 ± 1.98 y; 69 men), 77.7%, 15.5%, and 6.8% were categorized as chronic cavitary pulmonary aspergillosis, chronic fibrosing pulmonary aspergillosis (CFPA), and single/simple aspergilloma, respectively. The mean symptom duration was 2.7 ± 3.96 years, with cough being the most common symptom (86.4%). Underlying post-tubercular lung abnormalities were observed in 97.1% of the patients. Cavities were observed in all patients (100%), most commonly in the left upper lobe (68.0%). The difference in cavity number among CPA subtypes was statistically significant (P = 0.003), with 87.5% CFPA and 41.5% chronic cavitary pulmonary aspergillosis cases showing multiple cavities. The overall median cavity wall thickness was 6 mm (interquartile range: 2.8), with the highest value in the CFPA. Pericavitary fibrosis was observed in 70.9% of overall cases and in 100% of CFPA cases (P < 0.001). Intracavitary contents were identified in 89.3% of patients. The median pleural thickness was 8 mm (interquartile range: 4), which was significantly different among CPA subtypes (P = 0.001). There was excellent interobserver agreement (k = 0.94) between the two readers. Posterior intercostal lymph nodes were identified in 66%, a novel CPA observation.</p><p><strong>Conclusion: </strong>Comprehensive qualitative and quantitative assessment of CT findings improves the characterization of the CPA subtypes. The number and size of lung cavities, mediastinal shift, and pleural thickness, among other quantitative parameters, vary significantly across CPA subtypes, facilitating more accurate differentiation between them.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143722346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative CT-based Radiomics Model for Predicting Micropapillary/Solid Patterns in Stage I Peripheral Lung Invasive Adenocarcinoma: A Propensity Score Matching Study.","authors":"Yachao Ruan, Meirong Li, Zhan Feng, Lvbin Xie, Fangyu Sun, Fenhua Zhao, Feng Chen","doi":"10.1097/RTI.0000000000000826","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000826","url":null,"abstract":"<p><strong>Purpose: </strong>To develop and validate an accurate computed tomography-based radiomics model for predicting high-grade (micropapillary/solid) patterns in T1-stage lung invasive adenocarcinoma (IAC) after propensity score matching (PSM).</p><p><strong>Materials and methods: </strong>We enrolled 546 participants from 2 cohorts with histologically diagnosed lung IAC after complete surgical resection between January 2020 and August 2021. The patients were divided into high-grade and non-high-grade groups and matched using PSM. Matched patient HRCT images were used to delineate regions of interest from tumors and extract radiomics features, and the random forest method was used to construct a radiomics model. The area under the receiver operating characteristic curve (area under the curve) was used to evaluate the model's performance, and external validation was performed to assess the model's generalizability.</p><p><strong>Results: </strong>Before PSM, there was no statistically significant difference in age between the two groups, though nodule type and sex exhibited significant differences (P < 0.05) in both cohorts. After PSM, we matched 176 and 97 pairs of patients in the 2 cohorts. In both cohorts, sex and nodule type were equal between the two groups, with a higher percentage of males and solid nodules in both groups. Our model exhibited moderate predictive performance after PSM, with area under the curve values of 0.75 (95% CI: 0.70-0.80) and 0.71 (95% CI: 0.63-0.80) for the development and external validation cohorts, respectively.</p><p><strong>Conclusion: </strong>Although the nodule type compromised the validity of the model's performance, our results suggest that our acute computed tomography-based radiomics model could preoperatively predict micropapillary/solid patterns in patients with stage I lung IAC after PSM.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic Quantification of Abnormal Lung Parenchymal Attenuation on Chest Computed Tomography Images Using Densitometry and Texture-based Analysis.","authors":"Alysson R S Carvalho, Alan Guimarães, Rodrigo Basilio, Marco A Conrado da Silva, Sandro Colli, Carolina Galhós de Aguiar, Rafael C Pereira, Liseane G Lisboa, Bruno Hochhegger, Rosana S Rodrigues","doi":"10.1097/RTI.0000000000000804","DOIUrl":"10.1097/RTI.0000000000000804","url":null,"abstract":"<p><strong>Purpose: </strong>To compare texture-based analysis using convolutional neural networks (CNNs) against lung densitometry in detecting chest computed tomography (CT) image abnormalities.</p><p><strong>Material and methods: </strong>A U-NET was used for lung segmentation, and an ensemble of 7 CNN architectures was trained for the classification of low-attenuation areas (LAAs; emphysema, cysts), normal-attenuation areas (NAAs; normal parenchyma), and high-attenuation areas (HAAs; ground-glass opacities, crazy paving/linear opacity, consolidation). Lung densitometry also computes (LAAs, ≤-950 HU), NAAs (-949 to -700 HU), and HAAs (-699 to -250 HU). CNN-based and densitometry-based severity indices (CNN and Dens, respectively) were calculated as (LAA+HAA)/(LAA+NAA+HAA) in 812 CT scans from 176 normal subjects, 343 patients with emphysema, and 293 patients with interstitial lung disease (ILD). The correlation between CNN-derived and densitometry-derived indices was analyzed, alongside a comparison of severity indices among patient subgroups with emphysema and ILD, using the Spearman correlation and ANOVA with Bonferroni correction.</p><p><strong>Results: </strong>CNN-derived and densitometry-derived severity indices (SIs) showed a strong correlation (ρ=0.90) and increased with disease severity. CNN-SIs differed from densitometry SIs, being lower for emphysema and higher for moderate to severe ILD cases. CNN estimations for normal attenuation areas were higher than those from densitometry across all groups, indicating a potential for more accurate characterization of lung abnormalities.</p><p><strong>Conclusions: </strong>CNN outputs align closely with densitometry in assessing lung abnormalities on CT scans, offering improved estimates of normal areas and better distinguishing similar abnormalities. However, this requires higher computing power.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142299684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated 3D-Body Composition Analysis as a Predictor of Survival in Patients With Idiopathic Pulmonary Fibrosis.","authors":"Luca Salhöfer, Francesco Bonella, Mathias Meetschen, Lale Umutlu, Michael Forsting, Benedikt Michael Schaarschmidt, Marcel Klaus Opitz, Jens Kleesiek, Rene Hosch, Sven Koitka, Vicky Parmar, Felix Nensa, Johannes Haubold","doi":"10.1097/RTI.0000000000000803","DOIUrl":"10.1097/RTI.0000000000000803","url":null,"abstract":"<p><strong>Purpose: </strong>Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease, with a median survival time of 2 to 5 years. The focus of this study is to establish a novel imaging biomarker.</p><p><strong>Materials and methods: </strong>In this study, 79 patients (19% female) with a median age of 70 years were studied retrospectively. Fully automated body composition analysis (BCA) features (bone, muscle, total adipose tissue, intermuscular, and intramuscular adipose tissue) were combined into Sarcopenia, Fat, and Myosteatosis indices and compared between patients with a survival of more or less than 2 years. In addition, we divided the cohort at the median (high=≥ median, low=<median) of the respective BCA index and tested the impact on the overall survival using the Kaplan-Meier methodology, a log-rank test, and adjusted multivariate Cox-regression analysis.</p><p><strong>Results: </strong>A high Sarcopenia and Fat index and low Myosteatosis index were associated with longer median survival (35 vs. 16 mo for high vs. low Sarcopenia index, P =0.066; 44 vs. 14 mo for high vs. low Fat index, P <0.001; and 33 vs. 14 mo for low vs. high Myosteatosis index, P =0.0056) and better 5-year survival rates (34.0% vs. 23.6% for high vs. low Sarcopenia index; 47.3% vs. 9.2% for high vs. low Fat index; and 11.2% vs. 42.7% for high vs. low Myosteatosis index). Adjusted multivariate Cox regression showed a significant impact of the Fat (HR=0.71, P =0.01) and Myosteatosis (HR=1.12, P =0.005) on overall survival.</p><p><strong>Conclusion: </strong>The fully automated BCA provides biomarkers with a predictive value for the overall survival in patients with IPF.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837968/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142057111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Accuracy of Ultrasound Guidance in Transthoracic Needle Biopsy: A Systematic Review and Meta-Analysis.","authors":"Simon Lemieux, Lorence Pinard, Raphaël Marchand, Sonia Kali, Stephan Altmayer, Vicky Mai, Steeve Provencher","doi":"10.1097/RTI.0000000000000811","DOIUrl":"10.1097/RTI.0000000000000811","url":null,"abstract":"<p><strong>Purpose: </strong>To perform a systematic review and meta-analysis of relevant studies to assess the diagnostic accuracy and safety outcomes of ultrasound (US)-guided transthoracic needle biopsy (TTNB) for peripheral lung and pleural lesions.</p><p><strong>Materials and methods: </strong>A search was performed through Medline, Embase, Web of Science, and Cochrane Central from inception up to September 23, 2022 for diagnostic accuracy studies reporting US-guided TTNB (Prospero registration: CRD42021225168). The primary outcome was diagnostic accuracy, which was assessed by sensitivity, specificity, likelihood ratios (LR), and diagnostic odds ratio. Sensitivity and subgroup analyses were performed to evaluate inter-study heterogeneity. The secondary outcome was the frequency of complications. Random-effects models were used for the analyses. The risk of bias and the applicability of the included studies were assessed using the QUADAS-2 tool. Publication bias was assessed by testing the association between the natural logarithm of the diagnostic odds ratio and the effective sample size.</p><p><strong>Results: </strong>Of the 7841 citations identified, 83 independent cohorts (11,767 patients) were included in the analysis. The pooled sensitivity of US-TTNB was 88% (95% CI: 86%-91%, 80 studies). Pooled specificity was 100% (95% CI: 99%-100%, 72 studies), resulting in positive LR, negative LR, and diagnostic odds ratio of 946 (-743 to 2635), 0.12 (0.09 to 0.14), and 8141 (1344 to 49,321), respectively. Complications occurred in 4% (95% CI: 3%-5%) of the procedures, with pneumothorax being the most frequent (3%; 95% CI: 2%-3%, 72 studies) and resulting in chest tube placement in 0.4% (95% CI: 0.2%-0.7%, 64 studies) of the procedures.</p><p><strong>Conclusions: </strong>US-TTNB is an effective and safe procedure for pleural lesions and peripheral lung lesions.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142299686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}