Pub Date : 2024-01-01Epub Date: 2023-11-03DOI: 10.1097/RTI.0000000000000758
Se-Young Yoon, Nathan David P Concepcion, Olivia DiPrete, Sara O Vargas, Abbey J Winant, Pilar Garcia-Peña, Winnie C Chu, Joanna Kasznia-Brown, Pedro Daltro, Edward Y Lee, Bernard F Laya
A multitude of lung disorders ranging from congenital and genetic anomalies to iatrogenic complications can affect the neonate or the infant within the first year of life. Neonatal and infant chest imaging, predominantly by plain radiography and computed tomography, is frequently employed to aid in diagnosis and management; however, these disorders can be challenging to differentiate due to their broad-ranging, and frequently overlapping radiographic features. A systematic and practical approach to imaging interpretation which includes recognition of radiologic patterns, utilization of commonly accepted nomenclature and classification, as well as interpretation of imaging findings in conjunction with clinical history can not only assist radiologists to suggest the diagnosis, but also aid clinicians in management planning. The contents of this article were endorsed by the leadership of both the World Federation of Pediatric Imaging (WFPI), and the International Society of Pediatric Thoracic Imaging (ISPTI).
{"title":"Neonatal and Infant Lung Disorders: Glossary, Practical Approach, and Diagnoses.","authors":"Se-Young Yoon, Nathan David P Concepcion, Olivia DiPrete, Sara O Vargas, Abbey J Winant, Pilar Garcia-Peña, Winnie C Chu, Joanna Kasznia-Brown, Pedro Daltro, Edward Y Lee, Bernard F Laya","doi":"10.1097/RTI.0000000000000758","DOIUrl":"10.1097/RTI.0000000000000758","url":null,"abstract":"<p><p>A multitude of lung disorders ranging from congenital and genetic anomalies to iatrogenic complications can affect the neonate or the infant within the first year of life. Neonatal and infant chest imaging, predominantly by plain radiography and computed tomography, is frequently employed to aid in diagnosis and management; however, these disorders can be challenging to differentiate due to their broad-ranging, and frequently overlapping radiographic features. A systematic and practical approach to imaging interpretation which includes recognition of radiologic patterns, utilization of commonly accepted nomenclature and classification, as well as interpretation of imaging findings in conjunction with clinical history can not only assist radiologists to suggest the diagnosis, but also aid clinicians in management planning. The contents of this article were endorsed by the leadership of both the World Federation of Pediatric Imaging (WFPI), and the International Society of Pediatric Thoracic Imaging (ISPTI).</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"3-17"},"PeriodicalIF":3.3,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138048345","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}
Pub Date : 2024-01-01Epub Date: 2023-03-31DOI: 10.1097/RTI.0000000000000707
Mark C Liszewski, Pierluigi Ciet, Abbey J Winant, Edward Y Lee
Disorders of the lungs and airways are among the most common indications for diagnostic imaging in infants and children. Traditionally, chest radiograph has been the first-line imaging test for detecting these disorders and when cross-sectional imaging is necessary, computed tomography (CT) has typically been the next step. However, due to concerns about the potentially harmful effects of ionizing radiation, pediatric imaging in general has begun to shift away from CT toward magnetic resonance imaging (MRI) as a preferred modality. Several unique technical challenges of chest MRI, including motion artifact from respiratory and cardiac motion as well as low signal-to-noise ratios secondary to relatively low proton density in the lung have slowed this shift in thoracic imaging. However, technical advances in MRI in recent years, including developments in non-Cartesian MRI data sampling methods such as radial, spiral, and PROPELLER imaging and the development of ultrashort TE and zero TE sequences that render CT-like high-quality imaging with minimal motion artifact have allowed for a shift to MRI for evaluation of lung and large airways in centers with specialized expertise. This article presents a practical approach for radiologists in current practice to begin to consider MRI for evaluation of the pediatric lung and large airways and begin to implement it in their practices. The current role for MRI in the evaluation of disorders of the pediatric lung and large airways is reviewed, and example cases are presented. Challenges for MRI of the lung and large airways in children are discussed, practical tips for patient preparation including sedation are described, and imaging techniques suitable for current clinical practice are presented.
肺部和气道疾病是婴幼儿诊断成像最常见的适应症之一。传统上,胸片是检测这些疾病的一线成像检查方法,当需要进行横断面成像时,计算机断层扫描(CT)通常是下一步检查方法。然而,由于担心电离辐射的潜在危害,儿科成像已开始从 CT 转向磁共振成像 (MRI) 作为首选方式。胸部核磁共振成像存在一些独特的技术难题,包括呼吸和心脏运动造成的运动伪影,以及肺部质子密度相对较低导致的低信噪比,这些都减缓了胸部成像的转变。然而,近年来磁共振成像技术的进步,包括非笛卡尔磁共振成像数据取样方法(如径向、螺旋和 PROPELLER 成像)的发展,以及超短 TE 和零 TE 序列的开发,这些技术可提供类似 CT 的高质量成像,同时将运动伪影降到最低。本文介绍了一种实用的方法,让放射科医生在目前的实践中开始考虑用磁共振成像评估小儿肺部和大气管,并开始在他们的实践中实施。文章回顾了磁共振成像目前在评估小儿肺部和大气管疾病中的作用,并列举了一些病例。讨论了儿童肺部和大气道核磁共振成像所面临的挑战,介绍了包括镇静在内的患者准备实用技巧,并介绍了适合当前临床实践的成像技术。
{"title":"Magnetic Resonance Imaging of Pediatric Lungs and Airways: New Paradigm for Practical Daily Clinical Use.","authors":"Mark C Liszewski, Pierluigi Ciet, Abbey J Winant, Edward Y Lee","doi":"10.1097/RTI.0000000000000707","DOIUrl":"10.1097/RTI.0000000000000707","url":null,"abstract":"<p><p>Disorders of the lungs and airways are among the most common indications for diagnostic imaging in infants and children. Traditionally, chest radiograph has been the first-line imaging test for detecting these disorders and when cross-sectional imaging is necessary, computed tomography (CT) has typically been the next step. However, due to concerns about the potentially harmful effects of ionizing radiation, pediatric imaging in general has begun to shift away from CT toward magnetic resonance imaging (MRI) as a preferred modality. Several unique technical challenges of chest MRI, including motion artifact from respiratory and cardiac motion as well as low signal-to-noise ratios secondary to relatively low proton density in the lung have slowed this shift in thoracic imaging. However, technical advances in MRI in recent years, including developments in non-Cartesian MRI data sampling methods such as radial, spiral, and PROPELLER imaging and the development of ultrashort TE and zero TE sequences that render CT-like high-quality imaging with minimal motion artifact have allowed for a shift to MRI for evaluation of lung and large airways in centers with specialized expertise. This article presents a practical approach for radiologists in current practice to begin to consider MRI for evaluation of the pediatric lung and large airways and begin to implement it in their practices. The current role for MRI in the evaluation of disorders of the pediatric lung and large airways is reviewed, and example cases are presented. Challenges for MRI of the lung and large airways in children are discussed, practical tips for patient preparation including sedation are described, and imaging techniques suitable for current clinical practice are presented.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":"57-66"},"PeriodicalIF":3.3,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9602840","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}
Pub Date : 2024-01-01Epub Date: 2023-12-21DOI: 10.1097/RTI.0000000000000769
U Joseph Schoepf, Jeffrey P Kanne, Dorith Shaham
{"title":"Editors' Recognition for Reviewing in 2023.","authors":"U Joseph Schoepf, Jeffrey P Kanne, Dorith Shaham","doi":"10.1097/RTI.0000000000000769","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000769","url":null,"abstract":"","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":"39 1","pages":"1"},"PeriodicalIF":3.3,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138809812","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}
Pub Date : 2023-11-27DOI: 10.1097/rti.0000000000000768
Mark M Hammer
To determine the risk of lung cancer in incidental pulmonary nodules, as well as the time until cancer growth is detected.
确定偶然发现的肺结节罹患肺癌的风险,以及发现癌细胞生长的时间。
{"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}
Pub Date : 2023-11-24DOI: 10.1097/rti.0000000000000764
Cristina Marrocchio, Stephen M Humphries, David A Lynch
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.
{"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}
Pub Date : 2023-11-20DOI: 10.1097/RTI.0000000000000766
Min Ji Son, Eun Ju Chun, Seung Min Yoo, Soo Jeong Lee, Charles S White
Purpose: The primary imaging modality for the diagnosis of mitral valve prolapse (MVP) is echocardiography supplemented by electrocardiography (ECG)-gated cardiac computed tomography (CT) angiography. However, we have recently encountered patients with MVP who were initially identified on non-ECG-gated enhanced chest CT. The purpose of this study is to evaluate the diagnostic accuracy of non-ECG-gated enhanced chest CT to predict the presence of MVP.
Patients and methods: Of 92 patients (surgically confirmed MVP who underwent non-ECG-gated chest CT), 27 patients were excluded for motion artifact or insufficient surgical correlation, and 65 patients were ultimately included. As a control, 65 patients with dyspnea and without MVP (non-ECG-gated chest CT and echocardiography were performed within 1 month) were randomly selected. We retrospectively analyzed an asymmetric double line sign on axial CT images for the presence of MVP. The asymmetric double line sign was defined as the presence of a linear structure, not located in the plane traversing the mitral annulus.
Results: Use of the asymmetric double line sign to predict MVP on non-ECG-gated CT showed modest sensitivity, high specificity, modest negative predictive value, and high positive predictive value of 59% (38/65), 99% (64/65), 70% (64/91), and 97% (38/39), respectively.
Conclusion: The asymmetric double line sign on non-ECG-gated enhanced chest CT may be a valuable finding to predict the presence of MVP. Familiarity with this CT finding may lead to prompt diagnosis and proper management of MVP.
{"title":"Identification of Mitral Valve Prolapse on Non-electrocardiography-gated Enhanced Chest Computed Tomography.","authors":"Min Ji Son, Eun Ju Chun, Seung Min Yoo, Soo Jeong Lee, Charles S White","doi":"10.1097/RTI.0000000000000766","DOIUrl":"https://doi.org/10.1097/RTI.0000000000000766","url":null,"abstract":"<p><strong>Purpose: </strong>The primary imaging modality for the diagnosis of mitral valve prolapse (MVP) is echocardiography supplemented by electrocardiography (ECG)-gated cardiac computed tomography (CT) angiography. However, we have recently encountered patients with MVP who were initially identified on non-ECG-gated enhanced chest CT. The purpose of this study is to evaluate the diagnostic accuracy of non-ECG-gated enhanced chest CT to predict the presence of MVP.</p><p><strong>Patients and methods: </strong>Of 92 patients (surgically confirmed MVP who underwent non-ECG-gated chest CT), 27 patients were excluded for motion artifact or insufficient surgical correlation, and 65 patients were ultimately included. As a control, 65 patients with dyspnea and without MVP (non-ECG-gated chest CT and echocardiography were performed within 1 month) were randomly selected. We retrospectively analyzed an asymmetric double line sign on axial CT images for the presence of MVP. The asymmetric double line sign was defined as the presence of a linear structure, not located in the plane traversing the mitral annulus.</p><p><strong>Results: </strong>Use of the asymmetric double line sign to predict MVP on non-ECG-gated CT showed modest sensitivity, high specificity, modest negative predictive value, and high positive predictive value of 59% (38/65), 99% (64/65), 70% (64/91), and 97% (38/39), respectively.</p><p><strong>Conclusion: </strong>The asymmetric double line sign on non-ECG-gated enhanced chest CT may be a valuable finding to predict the presence of MVP. Familiarity with this CT finding may lead to prompt diagnosis and proper management of MVP.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138048344","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}
Pub Date : 2023-11-02DOI: 10.1097/rti.0000000000000745
Andrew C. Lancaster, Mitchell E. Cardin, Jan A. Nguyen, Tej I. Mehta, Dilek Oncel, Harrison X. Bai, Keira A. Cohen, Cheng Ting Lin
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). 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. 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. 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.
{"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}
Pub Date : 2023-11-01Epub Date: 2023-07-12DOI: 10.1097/RTI.0000000000000728
Kiran Batra, Traci N Adams
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.
{"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}
Pub Date : 2023-11-01Epub Date: 2023-08-25DOI: 10.1097/RTI.0000000000000721
Justin T Stowell, Andy Abril, Andras Khoor, Augustine S Lee, Hassan Z Baig
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.
{"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}