{"title":"Risk and Time to Diagnosis of Lung Cancer in Incidental Pulmonary Nodules.","authors":"Mark M Hammer","doi":"10.1097/rti.0000000000000768","DOIUrl":"https://doi.org/10.1097/rti.0000000000000768","url":null,"abstract":"To determine the risk of lung cancer in incidental pulmonary nodules, as well as the time until cancer growth is detected.","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"31 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138683291","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}
Cristina Marrocchio, Stephen M Humphries, David A Lynch
{"title":"Chest Computed Tomography Findings in Unilateral Pulmonary Fibrosis Secondary to Chronic Hypoperfusion.","authors":"Cristina Marrocchio, Stephen M Humphries, David A Lynch","doi":"10.1097/rti.0000000000000764","DOIUrl":"https://doi.org/10.1097/rti.0000000000000764","url":null,"abstract":"Unilateral lung fibrosis is uncommon and few cases secondary to parenchymal hypoperfusion have been reported, requiring further understanding of this entity. This study aims to report the chest computed tomography (CT) findings of patients with unilateral lung fibrosis related to parenchymal hypoperfusion observed in our institution.","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"56 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138682870","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}
Andrew C. Lancaster, Mitchell E. Cardin, Jan A. Nguyen, Tej I. Mehta, Dilek Oncel, Harrison X. Bai, Keira A. Cohen, Cheng Ting Lin
{"title":"Utilizing Deep Learning and Computed Tomography to Determine Pulmonary Nodule Activity in Patients With Nontuberculous Mycobacterial-Lung Disease","authors":"Andrew C. Lancaster, Mitchell E. Cardin, Jan A. Nguyen, Tej I. Mehta, Dilek Oncel, Harrison X. Bai, Keira A. Cohen, Cheng Ting Lin","doi":"10.1097/rti.0000000000000745","DOIUrl":"https://doi.org/10.1097/rti.0000000000000745","url":null,"abstract":"To develop and evaluate a deep convolutional neural network (DCNN) model for the classification of acute and chronic lung nodules from nontuberculous mycobacterial-lung disease (NTM-LD) on computed tomography (CT).\u0000 \u0000 \u0000 \u0000 We collected a data set of 650 nodules (316 acute and 334 chronic) from the CT scans of 110 patients with NTM-LD. The data set was divided into training, validation, and test sets in a ratio of 4:1:1. Bounding boxes were used to crop the 2D CT images down to the area of interest. A DCNN model was built using 11 convolutional layers and trained on these images. The performance of the model was evaluated on the hold-out test set and compared with that of 3 radiologists who independently reviewed the images.\u0000 \u0000 \u0000 \u0000 The DCNN model achieved an area under the receiver operating characteristic curve of 0.806 for differentiating acute and chronic NTM-LD nodules, corresponding to sensitivity, specificity, and accuracy of 76%, 68%, and 72%, respectively. The performance of the model was comparable to that of the 3 radiologists, who had area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy of 0.693 to 0.771, 61% to 82%, 59% to 73%, and 60% to 73%, respectively.\u0000 \u0000 \u0000 \u0000 This study demonstrated the feasibility of using a DCNN model for the classification of the activity of NTM-LD nodules on chest CT. The model performance was comparable to that of radiologists. This approach can potentially and efficiently improve the diagnosis and management of NTM-LD.","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"16 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135876266","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 Features of Idiopathic Interstitial Lung Diseases.","authors":"Kiran Batra, Traci N Adams","doi":"10.1097/RTI.0000000000000728","DOIUrl":"10.1097/RTI.0000000000000728","url":null,"abstract":"<p><p>Idiopathic interstitial pneumonias (IIPs) are a group of diffuse parenchymal lung diseases of unclear etiology and are distinguished from diffuse parenchymal lung diseases of known cause, such as connective tissue disease-related interstitial lung diseases or hypersensitivity pneumonitis by history, physical exam, imaging, serologic testing, and, when necessary, histopathology. The 2013 American Thoracic Society (ATS)/European Respiratory Society (ERS) guidelines are the most widely accepted classification of IIPs and include the following diagnoses: idiopathic pulmonary fibrosis, idiopathic nonspecific interstitial pneumonia, cryptogenic organizing pneumonia, acute interstitial pneumonia, idiopathic lymphocytic interstitial pneumonia, idiopathic pleuro-parenchymal fibroelastosis, respiratory bronchiolitis-interstitial lung disease, and desquamative interstitial pneumonia. The gold standard for diagnosis of IIP involves multidisciplinary discussion among pulmonologists, radiologists, and pathologists. The focus of this review will be to discuss the imaging features of the most common IIPs and the role of multidisciplinary discussion as the gold standard for diagnosis.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"S19-S29"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10242558","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}
Justin T Stowell, Andy Abril, Andras Khoor, Augustine S Lee, Hassan Z Baig
{"title":"The Role of Radiology in Multidisciplinary Discussion of Patients With Interstitial Lung Diseases.","authors":"Justin T Stowell, Andy Abril, Andras Khoor, Augustine S Lee, Hassan Z Baig","doi":"10.1097/RTI.0000000000000721","DOIUrl":"10.1097/RTI.0000000000000721","url":null,"abstract":"<p><p>Radiologists fulfill a vital role in the multidisciplinary care provided to patients with interstitial lung diseases and other diffuse parenchymal lung disorders. The diagnosis of interstitial lung diseases hinges on the consensus of clinical, radiology, and pathology medical subspecialists, but additional expertise from rheumatology, immunology, or hematology can be invaluable. The thin-section computed tomography (CT) features of lung involvement informs the diagnostic approach. Radiologists should be familiar with radiologic methods (including inspiratory/expiratory and prone imaging) and be well versed in the recognition of the CT features of fibrosis, assessment of the overall pattern of lung involvement, and classification according to the latest guidelines. We present a case-based review that highlights examples wherein CT features and subspecialist radiologist interpretation informed the multidisciplinary team consensus diagnosis and care pathways.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"S38-S44"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10122730","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}
Simon L F Walsh, Robert A Lafyatis, Vincent Cottin
{"title":"Imaging Features of Autoimmune Disease-Related Interstitial Lung Diseases.","authors":"Simon L F Walsh, Robert A Lafyatis, Vincent Cottin","doi":"10.1097/RTI.0000000000000734","DOIUrl":"10.1097/RTI.0000000000000734","url":null,"abstract":"<p><p>Interstitial lung diseases (ILDs) associated with autoimmune diseases show characteristic signs of imaging. Radiologic signs are also used in the identification of ILDs with features suggestive of autoimmune disease that do not meet the criteria for a specific autoimmune disease. Radiologists play a key role in identifying these signs and assessing their relevance as part of multidisciplinary team discussions. A radiologist may be the first health care professional to pick up signs of autoimmune disease in a patient referred for assessment of ILD or with suspicion for ILD. Multidisciplinary team discussion of imaging findings observed during follow-up may inform a change in diagnosis or identify progression, with implications for a patient's treatment regimen. This article describes the imaging features of autoimmune disease-related ILDs and the role of radiologists in assessing their relevance.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"S30-S37"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41180388","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":"Recent Advancements in Computed Tomography Assessment of Fibrotic Interstitial Lung Diseases.","authors":"Garima Suman, Chi Wan Koo","doi":"10.1097/RTI.0000000000000705","DOIUrl":"10.1097/RTI.0000000000000705","url":null,"abstract":"<p><p>Interstitial lung disease (ILD) is a heterogeneous group of disorders with complex and varied imaging manifestations and prognosis. High-resolution computed tomography (HRCT) is the current standard-of-care imaging tool for ILD assessment. However, visual evaluation of HRCT is limited by interobserver variation and poor sensitivity for subtle changes. Such challenges have led to tremendous recent research interest in objective and reproducible methods to examine ILDs. Computer-aided CT analysis to include texture analysis and machine learning methods have recently been shown to be viable supplements to traditional visual assessment through improved characterization and quantification of ILDs. These quantitative tools have not only been shown to correlate well with pulmonary function tests and patient outcomes but are also useful in disease diagnosis, surveillance and management. In this review, we provide an overview of recent computer-aided tools in diagnosis, prognosis, and longitudinal evaluation of fibrotic ILDs, while outlining some of the pitfalls and challenges that have precluded further advancement of these tools as well as potential solutions and further endeavors.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"S7-S18"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9602841","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":"Steady Progress in Interstitial Lung Disease.","authors":"John W Nance","doi":"10.1097/RTI.0000000000000747","DOIUrl":"10.1097/RTI.0000000000000747","url":null,"abstract":"","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"38 Suppl 1","pages":"S1"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50159087","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 Importance of Imaging in the Assessment of Interstitial Lung Diseases.","authors":"Michael B Sneider, Corey D Kershaw","doi":"10.1097/RTI.0000000000000708","DOIUrl":"10.1097/RTI.0000000000000708","url":null,"abstract":"<p><p>High-resolution computed tomography (HRCT) is an essential component of the diagnosis and assessment of patients with interstitial lung diseases (ILDs). In some cases, a diagnosis of ILD can be made solely based on a multidisciplinary discussion of HRCT findings and clinical evaluation. HRCT findings also inform prognosis and may influence treatment decisions. It is essential that high-quality HRCT images are obtained using parameters for optimum spatial resolution. Key terms used to describe HRCT findings should be used consistently among clinicians. Radiologic information should be included as part of the multidisciplinary discussion of patients with ILDs during follow-up.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"S2-S6"},"PeriodicalIF":3.3,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9955518","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":"European Society of Thoracic Imaging 2023 Berlin: Invited Abstracts","authors":"","doi":"10.1097/rti.0000000000000752","DOIUrl":"https://doi.org/10.1097/rti.0000000000000752","url":null,"abstract":"","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"23 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134974017","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}