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Ozawa Y, Nagata H, Ueda T, Oshima Y, Hamabuchi N, Yoshikawa T, Takenaka D, Ohno Y. Chest Magnetic Resonance Imaging: Advances and Clinical Care. Clin Chest Med 2024; 45:505-529. [PMID: 38816103 DOI: 10.1016/j.ccm.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.
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Affiliation(s)
- Yoshiyuki Ozawa
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Takahiro Ueda
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Yuka Oshima
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Nayu Hamabuchi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan
| | - Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan; Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
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Kay FU, Madhuranthakam AJ. MR Perfusion Imaging of the Lung. Magn Reson Imaging Clin N Am 2024; 32:111-123. [PMID: 38007274 DOI: 10.1016/j.mric.2023.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2023]
Abstract
Lung perfusion assessment is critical for diagnosing and monitoring a variety of respiratory conditions. MRI perfusion provides a radiation-free technique, making it an ideal choice for longitudinal imaging in younger populations. This review focuses on the techniques and applications of MRI perfusion, including contrast-enhanced (CE) MRI and non-CE methods such as arterial spin labeling (ASL), fourier decomposition (FD), and hyperpolarized 129-Xenon (129-Xe) MRI. ASL leverages endogenous water protons as tracers for a non-invasive measure of lung perfusion, while FD offers simultaneous measurements of lung perfusion and ventilation, enabling the generation of ventilation/perfusion mapsHyperpolarized 129-Xe MRI emerges as a novel tool for assessing regional gas exchange in the lungs. Despite the promise of MRI perfusion techniques, challenges persist, including competition with other imaging techniques and the need for additional validation and standardization. In conditions such as cystic fibrosis and lung cancer, MRI has displayed encouraging results, whereas in diseases like chronic obstructive pulmonary disease, further validation remains necessary. In conclusion, while MRI perfusion techniques hold immense potential for a comprehensive, non-invasive assessment of lung function and perfusion, their broader clinical adoption hinges on technological advancements, collaborative research, and rigorous validation.
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Affiliation(s)
- Fernando U Kay
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.
| | - Ananth J Madhuranthakam
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, North Campus 2201 Inwood Road, Dallas, TX 75390-8568, USA
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Ohno Y, Ozawa Y, Nagata H, Ueda T, Yoshikawa T, Takenaka D, Koyama H. Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications. Invest Radiol 2024; 59:38-52. [PMID: 37707840 DOI: 10.1097/rli.0000000000001017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
ABSTRACT Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.
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Affiliation(s)
- Yoshiharu Ohno
- From the Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ohno); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ohno and H.N.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y. Ozawa and T.U.); Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi, Hyogo, Japan (T.Y., D.T.); and Department of Radiology, Advanced Diagnostic Medical Imaging, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (H.K.)
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Wucherpfennig L, Kauczor HU, Eichinger M, Wielpütz MO. [Magnetic resonance imaging of the lung : State of the art]. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:849-862. [PMID: 37851088 DOI: 10.1007/s00117-023-01229-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/04/2023] [Indexed: 10/19/2023]
Abstract
Due to the low proton density of the lung parenchyma and the rapid signal decay at the air-tissue interfaces, for a long time the lungs were difficult to access using magnetic resonance imaging (MRI); however, technical advances could address most of these obstacles. Pulmonary alterations associated with tissue proliferation ("plus pathologies"), can now be detected with high diagnostic accuracy because of the locally increased proton density. Compared to computed tomography (CT), MRI provides a comprehensive range of functional imaging procedures (respiratory mechanics, perfusion and ventilation). In addition, as a radiation-free noninvasive examination modality, it enables repeated examinations for assessment of the course or monitoring of the effects of treatment, even in children. This article discusses the technical aspects, gives suggestions for protocols and explains the role of MRI of the lungs in the routine assessment of various diseases.
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Affiliation(s)
- Lena Wucherpfennig
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Deutschland
- Translational Lung Research Center Heidelberg (TLRC), Deutsches Zentrum für Lungenforschung (DZL), Im Neuenheimer Feld 130.3, 69120, Heidelberg, Deutschland
- Klinik für Diagnostische und Interventionelle Radiologie mit Nuklearmedizin, Thoraxklinik am Universitätsklinikum Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Deutschland
| | - Hans-Ulrich Kauczor
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Deutschland
- Translational Lung Research Center Heidelberg (TLRC), Deutsches Zentrum für Lungenforschung (DZL), Im Neuenheimer Feld 130.3, 69120, Heidelberg, Deutschland
- Klinik für Diagnostische und Interventionelle Radiologie mit Nuklearmedizin, Thoraxklinik am Universitätsklinikum Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Deutschland
| | - Monika Eichinger
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Deutschland
- Translational Lung Research Center Heidelberg (TLRC), Deutsches Zentrum für Lungenforschung (DZL), Im Neuenheimer Feld 130.3, 69120, Heidelberg, Deutschland
- Klinik für Diagnostische und Interventionelle Radiologie mit Nuklearmedizin, Thoraxklinik am Universitätsklinikum Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Deutschland
| | - Mark O Wielpütz
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Heidelberg, Im Neuenheimer Feld 420, 69120, Heidelberg, Deutschland.
- Translational Lung Research Center Heidelberg (TLRC), Deutsches Zentrum für Lungenforschung (DZL), Im Neuenheimer Feld 130.3, 69120, Heidelberg, Deutschland.
- Klinik für Diagnostische und Interventionelle Radiologie mit Nuklearmedizin, Thoraxklinik am Universitätsklinikum Heidelberg, Röntgenstr. 1, 69126, Heidelberg, Deutschland.
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Yang B, Gao Y, Lu J, Wang Y, Wu R, Shen J, Ren J, Wu F, Xu H. Quantitative analysis of chest MRI images for benign malignant diagnosis of pulmonary solid nodules. Front Oncol 2023; 13:1212608. [PMID: 37601669 PMCID: PMC10436991 DOI: 10.3389/fonc.2023.1212608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
Background In this study, we developed and validated machine learning (ML) models by combining radiomic features extracted from magnetic resonance imaging (MRI) with clinicopathological factors to assess pulmonary nodule classification for benign malignant diagnosis. Methods A total of 333 consecutive patients with pulmonary nodules (233 in the training cohort and 100 in the validation cohort) were enrolled. A total of 2,824 radiomic features were extracted from the MRI images (CE T1w and T2w). Logistic regression (LR), Naïve Bayes (NB), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) classifiers were used to build the predictive models, and a radiomics score (Rad-score) was obtained for each patient after applying the best prediction model. Clinical factors and Rad-scores were used jointly to build a nomogram model based on multivariate logistic regression analysis, and the diagnostic performance of the five prediction models was evaluated using the area under the receiver operating characteristic curve (AUC). Results A total of 161 women (48.35%) and 172 men (51.65%) with pulmonary nodules were enrolled. Six important features were selected from the 2,145 radiomic features extracted from CE T1w and T2w images. The XGBoost classifier model achieved the highest discrimination performance with AUCs of 0.901, 0.906, and 0.851 in the training, validation, and test cohorts, respectively. The nomogram model improved the performance with AUC values of 0.918, 0.912, and 0.877 in the training, validation, and test cohorts, respectively. Conclusion MRI radiomic ML models demonstrated good nodule classification performance with XGBoost, which was superior to that of the other four models. The nomogram model achieved higher performance with the addition of clinical information.
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Affiliation(s)
- Bin Yang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yeqi Gao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yefu Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ren Wu
- Department of Medical Imaging, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Jie Shen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jialiang Ren
- Department of Pharmaceuticals Diagnostics, GE Healthcare, Beijing, China
| | - Feiyun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hai Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Broncano J, Steinbrecher K, Marquis KM, Raptis CA, Royuela Del Val J, Vollmer I, Bhalla S, Luna A. Diffusion-weighted Imaging of the Chest: A Primer for Radiologists. Radiographics 2023; 43:e220138. [PMID: 37347699 DOI: 10.1148/rg.220138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2023]
Abstract
Diffusion-weighted imaging (DWI) is a fundamental sequence not only in neuroimaging but also in oncologic imaging and has emerging applications for MRI evaluation of the chest. DWI can be used in clinical practice to enhance lesion conspicuity, tissue characterization, and treatment response. While the spatial resolution of DWI is in the order of millimeters, changes in diffusion can be measured on the micrometer scale. As such, DWI sequences can provide important functional information to MRI evaluation of the chest but require careful optimization of acquisition parameters, notably selection of b values, application of parallel imaging, fat saturation, and motion correction techniques. Along with assessment of morphologic and other functional features, evaluation of DWI signal attenuation and apparent diffusion coefficient maps can aid in tissue characterization. DWI is a noninvasive noncontrast acquisition with an inherent quantitative nature and excellent reproducibility. The outstanding contrast-to-noise ratio provided by DWI can be used to improve detection of pulmonary, mediastinal, and pleural lesions, to identify the benign nature of complex cysts, to characterize the solid portions of cystic lesions, and to classify chest lesions as benign or malignant. DWI has several advantages over fluorine 18 (18F)-fluorodeoxyglucose PET/CT in the assessment, TNM staging, and treatment monitoring of lung cancer and other thoracic neoplasms with conventional or more recently developed therapies. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. Supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article.
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Affiliation(s)
- Jordi Broncano
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Kacie Steinbrecher
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Kaitlin M Marquis
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Constantin A Raptis
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Javier Royuela Del Val
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Ivan Vollmer
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Sanjeev Bhalla
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
| | - Antonio Luna
- From the Cardiothoracic Imaging Unit (J.B.) and Department of Radiology (J.B., J.R.d.V.), Hospital San Juan de Dios, HT-RESSALTA, HT Médica, Avenida el Brillante No. 36, 14012 Córdoba, Spain; Cardiothoracic Imaging Section, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (K.S., K.M.M., C.A.R., S.B.); Cardiothoracic Imaging Section, Department of Radiology, Hospital Clínic de Barcelona, Barcelona, Spain (I.V.); and MRI Section, Department of Radiology, Clínica Las Nieves, HT-SERCOSA, HT Médica, Jaén, Spain (A.L.)
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Gilbert FJ, Harris S, Miles KA, Weir-McCall JR, Qureshi NR, Rintoul RC, Dizdarevic S, Pike L, Sinclair D, Shah A, Eaton R, Clegg A, Benedetto V, Hill JE, Cook A, Tzelis D, Vale L, Brindle L, Madden J, Cozens K, Little LA, Eichhorst K, Moate P, McClement C, Peebles C, Banerjee A, Han S, Poon FW, Groves AM, Kurban L, Frew AJ, Callister ME, Crosbie P, Gleeson FV, Karunasaagarar K, Kankam O, George S. Dynamic contrast-enhanced CT compared with positron emission tomography CT to characterise solitary pulmonary nodules: the SPUtNIk diagnostic accuracy study and economic modelling. Health Technol Assess 2022; 26:1-180. [PMID: 35289267 DOI: 10.3310/wcei8321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Current pathways recommend positron emission tomography-computerised tomography for the characterisation of solitary pulmonary nodules. Dynamic contrast-enhanced computerised tomography may be a more cost-effective approach. OBJECTIVES To determine the diagnostic performances of dynamic contrast-enhanced computerised tomography and positron emission tomography-computerised tomography in the NHS for solitary pulmonary nodules. Systematic reviews and a health economic evaluation contributed to the decision-analytic modelling to assess the likely costs and health outcomes resulting from incorporation of dynamic contrast-enhanced computerised tomography into management strategies. DESIGN Multicentre comparative accuracy trial. SETTING Secondary or tertiary outpatient settings at 16 hospitals in the UK. PARTICIPANTS Participants with solitary pulmonary nodules of ≥ 8 mm and of ≤ 30 mm in size with no malignancy in the previous 2 years were included. INTERVENTIONS Baseline positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography with 2 years' follow-up. MAIN OUTCOME MEASURES Primary outcome measures were sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computerised tomography. Incremental cost-effectiveness ratios compared management strategies that used dynamic contrast-enhanced computerised tomography with management strategies that did not use dynamic contrast-enhanced computerised tomography. RESULTS A total of 380 patients were recruited (median age 69 years). Of 312 patients with matched dynamic contrast-enhanced computer tomography and positron emission tomography-computerised tomography examinations, 191 (61%) were cancer patients. The sensitivity, specificity and diagnostic accuracy for positron emission tomography-computerised tomography and dynamic contrast-enhanced computer tomography were 72.8% (95% confidence interval 66.1% to 78.6%), 81.8% (95% confidence interval 74.0% to 87.7%), 76.3% (95% confidence interval 71.3% to 80.7%) and 95.3% (95% confidence interval 91.3% to 97.5%), 29.8% (95% confidence interval 22.3% to 38.4%) and 69.9% (95% confidence interval 64.6% to 74.7%), respectively. Exploratory modelling showed that maximum standardised uptake values had the best diagnostic accuracy, with an area under the curve of 0.87, which increased to 0.90 if combined with dynamic contrast-enhanced computerised tomography peak enhancement. The economic analysis showed that, over 24 months, dynamic contrast-enhanced computerised tomography was less costly (£3305, 95% confidence interval £2952 to £3746) than positron emission tomography-computerised tomography (£4013, 95% confidence interval £3673 to £4498) or a strategy combining the two tests (£4058, 95% confidence interval £3702 to £4547). Positron emission tomography-computerised tomography led to more patients with malignant nodules being correctly managed, 0.44 on average (95% confidence interval 0.39 to 0.49), compared with 0.40 (95% confidence interval 0.35 to 0.45); using both tests further increased this (0.47, 95% confidence interval 0.42 to 0.51). LIMITATIONS The high prevalence of malignancy in nodules observed in this trial, compared with that observed in nodules identified within screening programmes, limits the generalisation of the current results to nodules identified by screening. CONCLUSIONS Findings from this research indicate that positron emission tomography-computerised tomography is more accurate than dynamic contrast-enhanced computerised tomography for the characterisation of solitary pulmonary nodules. A combination of maximum standardised uptake value and peak enhancement had the highest accuracy with a small increase in costs. Findings from this research also indicate that a combined positron emission tomography-dynamic contrast-enhanced computerised tomography approach with a slightly higher willingness to pay to avoid missing small cancers or to avoid a 'watch and wait' policy may be an approach to consider. FUTURE WORK Integration of the dynamic contrast-enhanced component into the positron emission tomography-computerised tomography examination and the feasibility of dynamic contrast-enhanced computerised tomography at lung screening for the characterisation of solitary pulmonary nodules should be explored, together with a lower radiation dose protocol. STUDY REGISTRATION This study is registered as PROSPERO CRD42018112215 and CRD42019124299, and the trial is registered as ISRCTN30784948 and ClinicalTrials.gov NCT02013063. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 17. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Fiona J Gilbert
- Department of Radiology, University of Cambridge School of Clinical Medicine, Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Scott Harris
- Public Health Sciences and Medical Statistics, University of Southampton, Southampton, UK
| | - Kenneth A Miles
- Department of Radiology, University of Cambridge School of Clinical Medicine, Biomedical Research Centre, University of Cambridge, Cambridge, UK
- Department of Radiology, Royal Papworth Hospital, Cambridge, UK
| | - Jonathan R Weir-McCall
- Department of Radiology, University of Cambridge School of Clinical Medicine, Biomedical Research Centre, University of Cambridge, Cambridge, UK
| | - Nagmi R Qureshi
- Department of Radiology, Royal Papworth Hospital, Cambridge, UK
| | - Robert C Rintoul
- Department of Thoracic Oncology, Royal Papworth Hospital, Cambridge, UK
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Sabina Dizdarevic
- Departments of Imaging and Nuclear Medicine and Respiratory Medicine, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
- Brighton and Sussex Medical School, Brighton, UK
| | - Lucy Pike
- King's College London and Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Donald Sinclair
- King's College London and Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Andrew Shah
- Radiation Protection Department, East and North Hertfordshire NHS Trust, Stevenage, UK
| | - Rosemary Eaton
- Radiation Protection Department, East and North Hertfordshire NHS Trust, Stevenage, UK
| | - Andrew Clegg
- Faculty of Health and Wellbeing, University of Central Lancashire, Preston, UK
| | - Valerio Benedetto
- Faculty of Health and Wellbeing, University of Central Lancashire, Preston, UK
| | - James E Hill
- Faculty of Health and Wellbeing, University of Central Lancashire, Preston, UK
| | - Andrew Cook
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Dimitrios Tzelis
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Luke Vale
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Lucy Brindle
- School of Health Sciences, University of Southampton, Southampton, UK
| | - Jackie Madden
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Kelly Cozens
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Louisa A Little
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Kathrin Eichhorst
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Patricia Moate
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Chris McClement
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
| | - Charles Peebles
- Department of Radiology and Respiratory Medicine, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Anindo Banerjee
- Department of Radiology and Respiratory Medicine, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Sai Han
- West of Scotland PET Centre, Gartnavel Hospital, Glasgow, UK
| | - Fat Wui Poon
- West of Scotland PET Centre, Gartnavel Hospital, Glasgow, UK
| | - Ashley M Groves
- Institute of Nuclear Medicine, University College London, London, UK
| | - Lutfi Kurban
- Department of Radiology, Aberdeen Royal Hospitals NHS Trust, Aberdeen, UK
| | - Anthony J Frew
- Departments of Imaging and Nuclear Medicine and Respiratory Medicine, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
- Brighton and Sussex Medical School, Brighton, UK
| | - Matthew E Callister
- Department of Respiratory Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Philip Crosbie
- North West Lung Centre, University Hospital of South Manchester, Manchester, UK
| | - Fergus V Gleeson
- Department of Radiology, Churchill Hospital, Oxford, UK
- University of Oxford, Oxford, UK
| | | | - Osei Kankam
- Department of Thoracic Medicine, East Sussex Healthcare NHS Trust, Saint Leonards-on-Sea, UK
| | - Steve George
- University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Southampton Clinical Trials Unit, University of Southampton, Southampton, UK
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Bak SH, Kim C, Kim CH, Ohno Y, Lee HY. Magnetic resonance imaging for lung cancer: a state-of-the-art review. PRECISION AND FUTURE MEDICINE 2022. [DOI: 10.23838/pfm.2021.00170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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9
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Hamabuchi N, Hattori H, Tsukamoto T, Nomura M, Ota S, Inui Y, Kikukawa K, Imaizumi K, Kondo M, Hoshikawa Y, Toyama H, Ohno Y. A Case of Multiple Sclerosing Pneumocytomas With Calcifications: Added Functional-based Information With Dynamic Contrast-enhanced Perfusion Magnetic Resonance Imaging. J Thorac Imaging 2021; 36:W109-W114. [PMID: 34310519 DOI: 10.1097/rti.0000000000000604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | - Masashi Kondo
- Respiratory Medicine
- Center for Clinical Trial and Research Support
| | | | | | - Yoshiharu Ohno
- Departments of Radiology
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi Prefecture, Japan
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10
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Liu H, Chen R, Tong C, Liang XW. MRI versus CT for the detection of pulmonary nodules: A meta-analysis. Medicine (Baltimore) 2021; 100:e27270. [PMID: 34678861 PMCID: PMC8542155 DOI: 10.1097/md.0000000000027270] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/31/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Computed tomography (CT) is the current gold standard for the detection of pulmonary nodules but has high radiation burden. In contrast, many radiologists tried to use magnetic resonance imaging (MRI) to replace CT because MRI has no radiation burden associated. Due to the lack of high-level evidence of comparison of the diagnostic accuracy of MRI versus CT for detecting pulmonary nodules, it is unknown whether CT can be replaced successfully by MRI. Therefore, the aim of this study was to compare the diagnostic accuracy of MRI versus CT for detecting pulmonary nodules. METHODS Electronic databases PubMed, EmBase, and Cochrane Library were systematically searched from their inception to September 2017 to identify studies in which CT/MRI was used to diagnose pulmonary nodules. According to true positive, true negative, false negative, and false positive extracted from the included studies, we calculate the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the curve (AUC) using Stata version 14.0 software (STATA Corp, TX). RESULTS A total of 8 studies involving a total of 653 individuals were included. The pooled sensitivity, specificity, PLR, NLR, and AUC were 0.91 (95% confidence interval [CI]: 0.80-0.96), 0.76 (95%CI: 0.58-0.87), 3.72 (95%CI: 2.05-6.76), 0.12 (95%CI: 0.06-0.27), and 0.91 (95%CI: 0.88-0.93) for MRI respectively, while the pooled sensitivity, specificity, PLR, NLR, and AUC for CT were 1.00 (95%CI: 0.95-1.00), 0.99 (95%CI: 0.78-1.00), 79.35 (95%CI: 3.68-1711.06), 0.00 (95%CI: 0.00-0.06), and 1.00 (95%CI: 0.99-1.00), respectively. Further, we compared the diagnostic accuracy of CT versus MRI and found that compared with MRI, CT shows statistically higher sensitivity (odds ratio [OR] for MRI vs CT: 0.91; 95%CI: 0.85-0.98; P value .010), specificity (OR: 0.82; 95%CI: 0.69-0.97; P value .019), PLR (OR: 0.29; 95%CI: 0.10-0.83; P value 0.02), AUC (OR: 0.91; 95%CI: 0.89-0.94; P value < .001), and lower NLR (OR: 8.72; 95%CI: 1.57-48.56; P value .013). CONCLUSION Our study suggested both CT and MRI have a high diagnostic accuracy in diagnosing pulmonary nodules, while CT was superior to MRI in sensitivity, specificity, PLR, NLR, and AUC, indicating that in terms of the currently available evidence, MRI could not replace CT in diagnosing pulmonary nodules.
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11
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Tanaka Y, Ohno Y, Hanamatsu S, Obama Y, Ueda T, Ikeda H, Iwase A, Fukuba T, Hattori H, Murayama K, Yoshikawa T, Takenaka D, Koyama H, Toyama H. State-of-the-art MR Imaging for Thoracic Diseases. Magn Reson Med Sci 2021; 21:212-234. [PMID: 33952785 PMCID: PMC9199970 DOI: 10.2463/mrms.rev.2020-0184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Since thoracic MR imaging was first used in a clinical setting, it has been suggested that MR imaging has limited clinical utility for thoracic diseases, especially lung diseases, in comparison with x-ray CT and positron emission tomography (PET)/CT. However, in many countries and states and for specific indications, MR imaging has recently become practicable. In addition, recently developed pulmonary MR imaging with ultra-short TE (UTE) and zero TE (ZTE) has enhanced the utility of MR imaging for thoracic diseases in routine clinical practice. Furthermore, MR imaging has been introduced as being capable of assessing pulmonary function. It should be borne in mind, however, that these applications have so far been academically and clinically used only for healthy volunteers, but not for patients with various pulmonary diseases in Japan or other countries. In 2020, the Fleischner Society published a new report, which provides consensus expert opinions regarding appropriate clinical indications of pulmonary MR imaging for not only oncologic but also pulmonary diseases. This review article presents a brief history of MR imaging for thoracic diseases regarding its technical aspects and major clinical indications in Japan 1) in terms of what is currently available, 2) promising but requiring further validation or evaluation, and 3) developments warranting research investigations in preclinical or patient studies. State-of-the-art MR imaging can non-invasively visualize lung structural and functional abnormalities without ionizing radiation and thus provide an alternative to CT. MR imaging is considered as a tool for providing unique information. Moreover, prospective, randomized, and multi-center trials should be conducted to directly compare MR imaging with conventional methods to determine whether the former has equal or superior clinical relevance. The results of these trials together with continued improvements are expected to update or modify recommendations for the use of MRI in near future.
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Affiliation(s)
- Yumi Tanaka
- Department of Radiology, Fujita Health University School of Medicine
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine.,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University School of Medicine
| | - Yuki Obama
- Department of Radiology, Fujita Health University School of Medicine
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University School of Medicine
| | - Akiyoshi Iwase
- Department of Radiology, Fujita Health University Hospital
| | - Takashi Fukuba
- Department of Radiology, Fujita Health University Hospital
| | - Hidekazu Hattori
- Department of Radiology, Fujita Health University School of Medicine
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine
| | | | | | | | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine
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12
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Wu W, Zhou S, Hippe DS, Liu H, Wang Y, Mayr NA, Yuh WT, Xia L, Bowen SR. Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Patients with Suspected Lung Cancer. Acad Radiol 2021; 28:e27-e34. [PMID: 32102748 DOI: 10.1016/j.acra.2020.01.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 01/17/2020] [Accepted: 01/18/2020] [Indexed: 02/07/2023]
Abstract
RATIONALE AND OBJECTIVES To explore the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intensity histogram metrics, relative to time intensity curve (TIC)-derived metrics, in patients with suspected lung cancer. MATERIALS AND METHODS This retrospective study enrolled 49 patients with suspected lung cancer on routine CT imaging who underwent DCE-MRI scans and had final histopathologic diagnosis. Three TIC-derived metrics (maximum enhancement ratio, peak time [Tmax] and slope) and eight intensity histogram metrics (volume, integral, maximum, minimum, median, coefficient of variation [CoV], skewness, and kurtosis) were extracted from DCE-MRI images. TIC-derived and intensity histogram metrics were compared between benignity versus malignancy using the Wilcoxon rank-sum test. Associations between imaging metrics and malignancy risk were assessed by univariate and multivariate logistic regression odds ratios (ORs). RESULTS There were 33 malignant lesions and 16 benign lesions based on histopathology. Lower CoV (OR = 0.2 per 1-SD increase, p = 0.0006), lower Tmax (OR = 0.4 per 1-SD increase, p = 0.005), and steeper slope (OR = 2.4 per 1-SD increase, p = 0.010) were significantly associated with increased risk of malignancy. Under multivariate analysis, CoV was significantly independently associated with malignancy likelihood after accounting for either Tmax (OR = 0.3 per 1-SD increase, p = 0.007) or slope (OR = 0.3 per 1-SD increase, p = 0.011). CONCLUSION This initial study found that DCE-MRI CoV was independently associated with malignancy in patients with suspected lung cancer. CoV has the potential to help diagnose indeterminate pulmonary lesions and may complement TIC-derived DCE-MRI metrics. Further studies are warranted to validate the diagnostic value of DCE-MRI intensity histogram analysis.
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Schiebler ML, Parraga G, Gefter WB, Madore B, Lee KS, Ohno Y, Kauczor HU, Hatabu H. Synopsis from Expanding Applications of Pulmonary MRI in the Clinical Evaluation of Lung Disorders: Fleischner Society Position Paper. Chest 2020; 159:492-495. [PMID: 32941864 DOI: 10.1016/j.chest.2020.09.075] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Affiliation(s)
- Mark L Schiebler
- Department of Radiology, UW Madison School of Medicine and Public Health, Madison, WI
| | - Grace Parraga
- Department of Medical Biophysics, Department of Medicine and Robarts Research Institute, Western University, London, ON, Canada
| | - Warren B Gefter
- Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, PA
| | - Bruno Madore
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Kyung Soo Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan
| | - Hans-Ulrich Kauczor
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany
| | - Hiroto Hatabu
- Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
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14
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Hatabu H, Ohno Y, Gefter WB, Parraga G, Madore B, Lee KS, Altes TA, Lynch DA, Mayo JR, Seo JB, Wild JM, van Beek EJR, Schiebler ML, Kauczor HU. Expanding Applications of Pulmonary MRI in the Clinical Evaluation of Lung Disorders: Fleischner Society Position Paper. Radiology 2020; 297:286-301. [PMID: 32870136 DOI: 10.1148/radiol.2020201138] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Pulmonary MRI provides structural and quantitative functional images of the lungs without ionizing radiation, but it has had limited clinical use due to low signal intensity from the lung parenchyma. The lack of radiation makes pulmonary MRI an ideal modality for pediatric examinations, pregnant women, and patients requiring serial and longitudinal follow-up. Fortunately, recent MRI techniques, including ultrashort echo time and zero echo time, are expanding clinical opportunities for pulmonary MRI. With the use of multicoil parallel acquisitions and acceleration methods, these techniques make pulmonary MRI practical for evaluating lung parenchymal and pulmonary vascular diseases. The purpose of this Fleischner Society position paper is to familiarize radiologists and other interested clinicians with these advances in pulmonary MRI and to stratify the Society recommendations for the clinical use of pulmonary MRI into three categories: (a) suggested for current clinical use, (b) promising but requiring further validation or regulatory approval, and (c) appropriate for research investigations. This position paper also provides recommendations for vendors and infrastructure, identifies methods for hypothesis-driven research, and suggests opportunities for prospective, randomized multicenter trials to investigate and validate lung MRI methods.
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Affiliation(s)
- Hiroto Hatabu
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Yoshiharu Ohno
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Warren B Gefter
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Grace Parraga
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Bruno Madore
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Kyung Soo Lee
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Talissa A Altes
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - David A Lynch
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - John R Mayo
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Joon Beom Seo
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Jim M Wild
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Edwin J R van Beek
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Mark L Schiebler
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
| | - Hans-Ulrich Kauczor
- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
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- From the Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02115 (H.H.); Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Mass (B.M.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, University of Missouri, Columbia, Mo (T.A.A.); Department of Radiology, National Jewish Health, Denver, Colo (D.A.L.); Department of Radiology, Vancouver General Hospital and University of British Colombia, Vancouver, Canada (J.R.M.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Section of Academic Radiology, University of Sheffield, Sheffield, England, United Kingdom (J.M.W.); Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, Scotland, United Kingdom (E.J.R.v.B.); Department of Radiology, UW Madison School of Medicine and Public Health, Madison, Wis (M.L.S.); and Diagnostic and Interventional Radiology, University Hospital Heidelberg, Translational Lung Research Center Heidelberg, member of the German Center of Lung Research, Heidelberg, Germany (H.U.K.)
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15
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Wu Q, Zhong L, Xie X. The value of four imaging modalities to distinguish malignant from benign solitary pulmonary nodules: a study based on 73 cohorts incorporating 7956 individuals. Clin Transl Oncol 2020; 23:296-310. [PMID: 32548796 DOI: 10.1007/s12094-020-02418-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 06/02/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND Solitary pulmonary nodules (SPNs) frequently bother oncologists. The differentiation of malignant from benign nodules with non-invasive approach remains a tough challenge. This study was designed to assess the diagnostic accuracy of dynamic computed tomography (CT), dynamic magnetic resonance imaging (MRI), fluorine 18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET), and technetium 99 m (99mTc) depreotide single photon emission computed tomography (SPECT) for SPNs. METHODS Electronic databases of MEDLINE, PubMed, EMBASE, and Cochrane Library were searched to identify relevant trials. The primary evaluation index of diagnostic accuracy was areas under the summary receiver-operating characteristic (SROC) curve. The results were analyzed utilizing Stata 12.0 statistical software. RESULTS Seventy-three trials incorporating 7956 individuals were recruited. Sensitivities, specificities, positive likelihood ratios, negative likelihood ratios, diagnostic score, diagnostic odds ratios, and areas under the SROC curve with 95% confidence intervals were, respectively, 0.92 (0.89-0.95), 0.64 (0.54-0.74), 2.60 (1.98-3.42), 0.12 (0.08-0.17), 3.10 (2.62-3.59), 22.24 (13.67-36.17), and 0.91 (0.88-0.93) for CT; 0.92 (0.86-0.95), 0.85 (0.77-0.90), 6.01 (3.90-9.24), 0.10 (0.06-0.17), 4.12 (3.41-4.82), 61.39 (30.41-123.93), and 0.94 (0.92-0.96) for MRI; 0.90 (0.86-0.93), 0.73 (0.65-0.79), 3.28 (2.56-4.20), 0.14 (0.10-0.19), 3.16 (2.69-3.64), 23.68 (14.74-38.05), and 0.90 (0.87-0.92) for 18F-FDG PET; and 0.93 (0.88-0.96), 0.70 (0.56-0.81), 3.12 (2.03-4.81), 0.10 (0.06-0.17), 3.43 (2.63-4.22), 30.74 (13.84-68.27), and 0.93 (0.91-0.95) for 99mTc-depreotide SPECT. CONCLUSION The dynamic MRI, dynamic CT, 18F-FDG PET, and 99mTc-depreotide SPECT were favorable non-invasive approaches to distinguish malignant SPNs from benign. Moreover, from the viewpoint of cost-effectiveness and avoiding radiation, the dynamic MRI was recommendable for SPNs.
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Affiliation(s)
- Q Wu
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China
| | - L Zhong
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China.,Department of Medical Oncology, The Second Hospital of Longyan, Fujian, 364000, China
| | - X Xie
- Department of Oncology, The First Affiliated Hospital of Fujian Medical University, Chazhong Road No 20, Fuzhou, 350005, Fujian, China.
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16
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Weir-McCall JR, Joyce S, Clegg A, MacKay JW, Baxter G, Dendl LM, Rintoul RC, Qureshi NR, Miles K, Gilbert FJ. Dynamic contrast-enhanced computed tomography for the diagnosis of solitary pulmonary nodules: a systematic review and meta-analysis. Eur Radiol 2020; 30:3310-3323. [PMID: 32060716 DOI: 10.1007/s00330-020-06661-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 12/12/2019] [Accepted: 01/17/2020] [Indexed: 12/19/2022]
Abstract
INTRODUCTION A systematic review and meta-analysis were performed to determine the diagnostic performance of dynamic contrast-enhanced computed tomography (DCE-CT) for the differentiation between malignant and benign pulmonary nodules. METHODS Ovid MEDLINE and EMBASE were searched for studies published up to October 2018 on the diagnostic accuracy of DCE-CT for the characterisation of pulmonary nodules. For the index test, studies with a minimum of a pre- and post-contrast computed tomography scan were evaluated. Studies with a reference standard of biopsy for malignancy, and biopsy or 2-year follow-up for benign disease were included. Study bias was assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies). The sensitivities, specificities, and diagnostic odds ratios were determined along with 95% confidence intervals (CIs) using a bivariate random effects model. RESULTS Twenty-three studies were included, including 2397 study participants with 2514 nodules of which 55.3% were malignant (1389/2514). The pooled accuracy results were sensitivity 94.8% (95% CI 91.5; 96.9), specificity 75.5% (69.4; 80.6), and diagnostic odds ratio 56.6 (24.2-88.9). QUADAS 2 assessment showed intermediate/high risk of bias in a large proportion of the studies (52-78% across the domains). No difference was present in sensitivity or specificity between subgroups when studies were split based on CT technique, sample size, nodule size, or publication date. CONCLUSION DCE-CT has a high diagnostic accuracy for the diagnosis of pulmonary nodules although study quality was indeterminate in a large number of cases. KEY POINTS • The pooled accuracy results were sensitivity 95.1% and specificity 73.8% although individual studies showed wide ranges of values. • This is comparable to the results of previous meta-analyses of PET/CT (positron emission tomography/computed tomography) diagnostic accuracy for the diagnosis of solitary pulmonary nodules. • Robust direct comparative accuracy and cost-effectiveness studies are warranted to determine the optimal use of DCE-CT and PET/CT in the diagnosis of SPNs.
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Affiliation(s)
- Jonathan R Weir-McCall
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
| | - Stella Joyce
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Andrew Clegg
- School of Health Sciences, Faculty of Health and Wellbeing, University of Central Lancashire, Lancashire, UK
| | - James W MacKay
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Gabrielle Baxter
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | | | - Robert C Rintoul
- Department of Thoracic Oncology, Royal Papworth Hospital, Cambridge, UK.,Department of Oncology, University of Cambridge, Cambridge, UK
| | - Nagmi R Qureshi
- Department of Radiology, Royal Papworth Hospital, Cambridge, UK
| | - Ken Miles
- Institute of Nuclear Medicine, University College London, London, UK
| | - Fiona J Gilbert
- Department of Radiology, University of Cambridge School of Clinical Medicine, Box 218, Level 5, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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17
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Ohno Y, Fujisawa Y, Yui M, Takenaka D, Koyama H, Sugihara N, Yoshikawa T. Solitary pulmonary nodule: Comparison of quantitative capability for differentiation and management among dynamic CE-perfusion MRI at 3 T system, dynamic CE-perfusion ADCT and FDG-PET/CT. Eur J Radiol 2019; 115:22-30. [PMID: 31084755 DOI: 10.1016/j.ejrad.2019.03.018] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 02/20/2019] [Accepted: 03/24/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE To prospectively compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion MR imaging with ultra-short TE and area-detector CT (ADCT), analyzed with the same mathematical methods, and that of FDG-PET/CT for diagnosis and management of solitary pulmonary nodules (SPNs). METHODS AND MATERIALS Our institutional review board approved this study and written informed consent was obtained from all subjects. A total 57 consecutive patients with 71 nodules prospectively underwent dynamic CE-perfusion ADCT and MR imaging with ultra-short TE, FDG-PET/CT, as well as microbacterial and/or pathological examinations. The nodules were classified into malignant nodules (n = 45) and benign nodules (n = 26). Pulmonary arterial, systemic arterial and total perfusions were determined by means of dual-input maximum slope models on ADCT and MR imaging and maximum values of standard uptake values (SUVmax) on PET/CT. Receiver operating characteristic (ROC) analysis was performed for each index, and sensitivity, specificity and accuracy were compared by McNemar's test. RESULTS Areas under the curve (Azs) of total perfusion on ADCT (Az = 0.89) and MR imaging (Az = 0.88) were significantly larger than those of systemic arterial perfusion and MR imaging (p<0.05). Accuracy of total perfusion on ADCT (87.3% [62/71]) and MR imaging (87.3% [62/71]) was significantly higher than that of systemic arterial perfusion for both methods (77.5% [55/71] p = 0.02) and SUVmax (78.9% [56/71], p = 0.03). CONCLUSION Dynamic CE-perfusion MR imaging with ultra-short TE and ADCT and have similar potential capabilities, and are superior to FDG-PET/CT in this setting.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan; Department of Radiology, Fujita Health University School of Medicine.
| | | | - Masao Yui
- Canon Medical Systems Corporation, Otawara, Japan
| | | | - Hisanobu Koyama
- Department of Radiology, Osaka Police Hospital, Osaka, Japan
| | | | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan
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18
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Raptis CA, Ludwig DR, Hammer MM, Luna A, Broncano J, Henry TS, Bhalla S, Ackman JB. Building blocks for thoracic MRI: Challenges, sequences, and protocol design. J Magn Reson Imaging 2019; 50:682-701. [PMID: 30779459 DOI: 10.1002/jmri.26677] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 01/18/2019] [Accepted: 01/19/2019] [Indexed: 12/19/2022] Open
Abstract
Thoracic MRI presents important and unique challenges. Decreased proton density in the lung in combination with respiratory and cardiac motion can degrade image quality and render poorly executed sequences uninterpretable. Despite these challenges, thoracic MRI has an important clinical role, both as a problem-solving tool and in an increasing array of clinical indications. Advances in scanner and sequence design have also helped to drive this development, presenting the radiologist with improved techniques for thoracic MRI. Given this evolving landscape, radiologists must be familiar with what thoracic MR has to offer. The first step in developing an effective thoracic MRI practice requires the creation of efficient and malleable protocols that can answer clinical questions. To do this, radiologists must have a working knowledge of the MR sequences that are used in the thorax, many of which have been adapted from use elsewhere in the body. These sequences can be broadly divided into three categories: traditional/anatomic, functional, and cine based. Traditional/anatomic sequences allow for the depiction of anatomy and pathologic processes with the ability for characterization of signal intensity and contrast enhancement. Functional sequences, including diffusion-weighted imaging, and high temporal resolution dynamic contrast enhancement, allow for the noninvasive measurement of tissue-specific parameters. Cine-based sequences can depict the motion of structures in the thorax, either with retrospective ECG gating or in real time. The purpose of this article is to review these categories, the building block sequences that comprise them, and identify basic questions that should be considered in thoracic MRI protocol design. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:682-701.
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Affiliation(s)
| | - Daniel R Ludwig
- Mallinckrodt Institute of Radiology, St. Louis, Missouri, USA
| | - Mark M Hammer
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Antonio Luna
- Health Time, Clinica Las Nieves, Jaen, Spain.,University Hospitals, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jordi Broncano
- Health Time, Hospital de la Cruz Roja and San Juan de Dios, Cordoba, Spain
| | - Travis S Henry
- University of California-San Francisco, San Francisco, California, USA
| | - Sanjeev Bhalla
- Mallinckrodt Institute of Radiology, St. Louis, Missouri, USA
| | - Jeanne B Ackman
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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19
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Basso Dias A, Zanon M, Altmayer S, Sartori Pacini G, Henz Concatto N, Watte G, Garcez A, Mohammed TL, Verma N, Medeiros T, Marchiori E, Irion K, Hochhegger B. Fluorine 18-FDG PET/CT and Diffusion-weighted MRI for Malignant versus Benign Pulmonary Lesions: A Meta-Analysis. Radiology 2018; 290:525-534. [PMID: 30480492 DOI: 10.1148/radiol.2018181159] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Purpose To perform a meta-analysis of the literature to compare the diagnostic performance of fluorine 18 fluorodeoxyglucose PET/CT and diffusion-weighted (DW) MRI in the differentiation of malignant and benign pulmonary nodules and masses. Materials and Methods Published English-language studies on the diagnostic accuracy of PET/CT and/or DW MRI in the characterization of pulmonary lesions were searched in relevant databases through December 2017. The primary focus was on studies in which joint DW MRI and PET/CT were performed in the entire study population, to reduce interstudy heterogeneity. For DW MRI, lesion-to-spinal cord signal intensity ratio and apparent diffusion coefficient were evaluated; for PET/CT, maximum standard uptake value was evaluated. The pooled sensitivities, specificities, diagnostic odds ratios, and areas under the receiver operating characteristic curve (AUCs) for PET/CT and DW MRI were determined along with 95% confidence intervals (CIs). Results Thirty-seven studies met the inclusion criteria, with a total of 4224 participants and 4463 lesions (3090 malignant lesions [69.2%]). In the primary analysis of joint DW MRI and PET/CT studies (n = 6), DW MRI had a pooled sensitivity and specificity of 83% (95% CI: 75%, 89%) and 91% (95% CI: 80%, 96%), respectively, compared with 78% (95% CI: 70%, 84%) (P = .01 vs DW MRI) and 81% (95% CI: 72%, 88%) (P = .056 vs DW MRI) for PET/CT. DW MRI yielded an AUC of 0.93 (95% CI: 0.90, 0.95), versus 0.86 (95% CI: 0.83, 0.89) for PET/CT (P = .001). The diagnostic odds ratio of DW MRI (50 [95% CI: 19, 132]) was superior to that of PET/CT (15 [95% CI: 7, 32]) (P = .006). Conclusion The diagnostic performance of diffusion-weighted MRI is comparable or superior to that of fluorine 18 fluorodeoxyglucose PET/CT in the differentiation of malignant and benign pulmonary lesions. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Schiebler in this issue.
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Affiliation(s)
- Adriano Basso Dias
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Matheus Zanon
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Stephan Altmayer
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Gabriel Sartori Pacini
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Natália Henz Concatto
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Guilherme Watte
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Anderson Garcez
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Tan-Lucien Mohammed
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Nupur Verma
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Tássia Medeiros
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Edson Marchiori
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Klaus Irion
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
| | - Bruno Hochhegger
- From the Medical Imaging Research Laboratory, LABIMED, Department of Radiology, Pavilhão Pereira Filho Hospital, Irmandade Santa Casa de Misericórdia de Porto Alegre, Av Independência 75, Porto Alegre, Brazil 90020160 (A.B.D., M.Z., S.A., G.S.P., G.W., B.H.); Department of Diagnostic Methods, Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil (A.B.D., M.Z., S.A., G.S.P., B.H.); Department of Radiology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil (N.H.C.); Post-graduate Program in Collective Health, University of Vale do Rio dos Sinos, São Leopoldo, Brazil (A.G.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (T.L.M., N.V.); Department of Radiology, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil (T.M., B.H.); Department of Radiology, Federal University of Rio de Janeiro Medical School, Rio de Janeiro, Brazil (E.M.); and Department of Radiology, Central Manchester University Hospitals, NHS Foundation Trust-Trust Headquarters, Cobbett House, Manchester Royal Infirmary, Manchester, England (K.I.)
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Ohno Y, Kauczor HU, Hatabu H, Seo JB, van Beek EJR. MRI for solitary pulmonary nodule and mass assessment: Current state of the art. J Magn Reson Imaging 2018; 47:1437-1458. [PMID: 29573050 DOI: 10.1002/jmri.26009] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 02/26/2018] [Indexed: 12/14/2022] Open
Abstract
Since the clinical introduction of magnetic resonance imaging (MRI), the chest has been one of its most challenging applications, and many physicists and radiologists have tried since the 1980s to use MR for assessment of different lung diseases as well as mediastinal and pleural diseases. Since then, however, technical advances in sequencing, scanners, and coils, adaptation of parallel imaging techniques, utilization of contrast media, and development of postprocessing tools have been reported by many basic and clinical researchers. As a result, state-of-the-art thoracic MRI is now substituted for traditional imaging techniques and/or plays a complementary role in the management of patients with various chest diseases, and especially in the detection of pulmonary nodules and in thoracic oncology. In addition, MRI has continued to be developed to help overcome the limitations of computed tomography (CT) and nuclear medicine examinations. It can currently provide not only morphological, but also functional, physiological, pathophysiological, and molecular information at 1.5T with a gradual shift from 1.5T to 3T MR systems. In this review, we focus on these recent advances in MRI for pulmonary nodule detection and pulmonary nodule and mass evaluation by using noncontrast-enhanced and contrast-enhanced techniques as well as new molecular imaging methods such as chemical exchange saturation transfer imaging for a comparison with other modalities such as single or multidetector row CT, 18F-fluoro-2-deoxyglucose positron emission tomography (FDG-PET), and/or PET/CT. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1437-1458.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Hans-Ulrich Kauczor
- Diagnostic and Interventional Radiology, University Medical Center Heidelberg, Translational Lung Research Center/German Center of Lung Research, Heidelberg, Germany
| | - Hiroto Hatabu
- Center for Pulmonary Functional Imaging, Department of Radiology, Brigham and Women's Hospital, Boston and Harvard Medical School, Boston, Massachusetts, USA
| | - Joon Beom Seo
- Department of Radiology, University of Ulsan College of Medicine, Seoul, Korea.,Division of Cardiothoracic Radiology, Department of Radiology, Asan Medical Center, Seoul, Korea
| | - Edwin J R van Beek
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
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Chen L, Liu D, Zhang J, Xie B, Zhou X, Grimm R, Huang X, Wang J, Feng L. Free-breathing dynamic contrast-enhanced MRI for assessment of pulmonary lesions using golden-angle radial sparse parallel imaging. J Magn Reson Imaging 2018; 48:459-468. [PMID: 29437281 DOI: 10.1002/jmri.25977] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 01/30/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been shown to be a promising technique for assessing lung lesions. However, DCE-MRI often suffers from motion artifacts and insufficient imaging speed. Therefore, highly accelerated free-breathing DCE-MRI is of clinical interest for lung exams. PURPOSE To test the performance of rapid free-breathing DCE-MRI for simultaneous qualitative and quantitative assessment of pulmonary lesions using Golden-angle RAdial Sparse Parallel (GRASP) imaging. STUDY TYPE Prospective. POPULATION Twenty-six patients (17 males, mean age = 55.1 ± 14.4) with known pulmonary lesions. FIELD STRENGTH/SEQUENCE 3T MR scanner; a prototype fat-saturated, T1 -weighted stack-of-stars golden-angle radial sequence for data acquisition and a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence for comparison. ASSESSMENT After a dual-mode GRASP reconstruction, one with 3-second temporal resolution (3s-GRASP) and the other with 15-second temporal resolution (15s-GRASP), all GRASP and BH-VIBE images were pooled together for blind assessment by two experienced radiologists, who independently scored the overall image quality, lesion delineation, overall artifact level, and diagnostic confidence of each case. Perfusion analysis was performed for the 3s-GRASP images using a Tofts model to generate the volume transfer coefficient (Ktrans ) and interstitial volume (Ve ). STATISTICAL TESTS Nonparametric paired two-tailed Wilcoxon signed-rank test; Cohen's kappa; unpaired Student's t-test. RESULTS 15s-GRASP achieved comparable image quality with conventional BH-VIBE (P > 0.05), except for the higher overall artifact level in the precontrast phase (P = 0.018). The Ktrans and Ve in inflammation were higher than those in malignant lesions (Ktrans : 0.78 ± 0.52 min-1 vs. 0.37 ± 0.22 min-1 , P = 0.020; Ve : 0.36 ± 0.16 vs. 0.26 ± 0.1, P = 0.177). Also, the Ktrans and Ve in malignant lesions were also higher than those in benign lesions (Ktrans : 0.37 ± 0.22 min-1 vs. 0.04 ± 0.04 min-1 , P = 0.001; Ve : 0.26 ± 0.12 vs. 0.10 ± 0.00, P = 0.063). DATA CONCLUSION This feasibility study demonstrated the performance of high spatiotemporal resolution free-breathing DCE-MRI of the lung using GRASP for qualitative and quantitative assessment of pulmonary lesions. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:459-468.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.,Department of Radiology, PLA 101st Hospital, Wuxi Jiangsu, China
| | - Daihong Liu
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Bing Xie
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xiaoyue Zhou
- MR Collaboration, North East Asia, Siemens Healthcare, Shanghai, China
| | | | - Xuequan Huang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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Khanduri S, Bhagat S, Shokeen P, Kumar G, Khanduri S, Singh B. Rationale of Using Dynamic Imaging for Characterization of Suspicious Lung Masses into Benign or Malignant on Contrast Enhanced Multi Detector Computed Tomography. J Clin Imaging Sci 2017; 7:24. [PMID: 28706752 PMCID: PMC5499391 DOI: 10.4103/jcis.jcis_18_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Accepted: 05/06/2017] [Indexed: 11/21/2022] Open
Abstract
Objectives: To assess the utility of dynamic imaging namely, wash-in and wash-out characteristics through multidetector contrast-enhanced computed tomography in differentiating benign and malignant pulmonary masses. Materials and Methods: Seventy-three patients who were suspected to have malignant pulmonary mass on the basis of clinical symptoms and chest radiograph were included in the study. All the patients underwent multidetector computed tomography scanning, and three series of images were obtained for each patient-noncontrast, early enhanced, and 15 min delayed enhanced scans. Computed tomography (CT) findings were assessed in terms of washin, absolute, and relative percentage washout of contrast. Biopsy of the mass was done and sent for histopathological evaluation. Sensitivity, specificity, and area under curve for diagnosing malignancy in the lung masses were calculated by considering both the wash-in and wash-out characteristics at dynamic CT and plotting the receiver operating curve after the final diagnosis which was obtained by histopathological evaluation. Results: Threshold net enhancement (washin) value of >22.5 HU had sensitivity, specificity, and diagnostic accuracy of 88.5%, 57.1%, and 82%, respectively, in predicting malignancy. Threshold relative percentage washout of <16.235% had 98.1%, 85.7%, and 94% sensitivity, specificity, and diagnostic accuracy, respectively, and threshold absolute percentage washout of <42.72% had 98.1%, 95.2%, and 95% sensitivity, specificity, and diagnostic accuracy, respectively, in predicting malignancy. Conclusion: Threshold net enhancement (washin), absolute and relative washout percentages can be used to predict malignancy with very high diagnostic yield, and possibly obviate the need of invasive procedures for diagnosis of bronchogenic carcinoma.
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Affiliation(s)
- Sachin Khanduri
- Department of Radiodiagnosis, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
| | - Saurav Bhagat
- Department of Radiodiagnosis, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
| | - Parul Shokeen
- Department of Radiodiagnosis, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
| | - Girjesh Kumar
- Department of Radiodiagnosis, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
| | - Shobha Khanduri
- Department of Histopathology and Lab Operations, SRL Diagnostic Laboratory, Lucknow, Uttar Pradesh, India
| | - Bhumika Singh
- Department of Radiodiagnosis, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India
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Ohno Y, Koyama H, Lee HY, Miura S, Yoshikawa T, Sugimura K. Contrast-enhanced CT- and MRI-based perfusion assessment for pulmonary diseases: basics and clinical applications. Diagn Interv Radiol 2017; 22:407-21. [PMID: 27523813 DOI: 10.5152/dir.2016.16123] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Assessment of regional pulmonary perfusion as well as nodule and tumor perfusions in various pulmonary diseases are currently performed by means of nuclear medicine studies requiring radioactive macroaggregates, dual-energy computed tomography (CT), and dynamic first-pass contrast-enhanced perfusion CT techniques and unenhanced and dynamic first-pass contrast enhanced perfusion magnetic resonance imaging (MRI), as well as time-resolved three-dimensional or four-dimensional contrast-enhanced magnetic resonance angiography (MRA). Perfusion scintigraphy, single-photon emission tomography (SPECT) and SPECT fused with CT have been established as clinically available scintigraphic methods; however, they are limited by perfusion information with poor spatial resolution and other shortcomings. Although positron emission tomography with 15O water can measure absolute pulmonary perfusion, it requires a cyclotron for generation of a tracer with an extremely short half-life (2 min), and can only be performed for academic purposes. Therefore, clinicians are concentrating their efforts on the application of CT-based and MRI-based quantitative and qualitative perfusion assessment to various pulmonary diseases. This review article covers 1) the basics of dual-energy CT and dynamic first-pass contrast-enhanced perfusion CT techniques, 2) the basics of time-resolved contrast-enhanced MRA and dynamic first-pass contrast-enhanced perfusion MRI, and 3) clinical applications of contrast-enhanced CT- and MRI-based perfusion assessment for patients with pulmonary nodule, lung cancer, and pulmonary vascular diseases. We believe that these new techniques can be useful in routine clinical practice for not only thoracic oncology patients, but also patients with different pulmonary vascular diseases.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology and Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
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Advanced imaging tools in pulmonary nodule detection and surveillance. Clin Imaging 2016; 40:296-301. [PMID: 26916752 DOI: 10.1016/j.clinimag.2016.01.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2015] [Revised: 01/27/2016] [Accepted: 01/29/2016] [Indexed: 11/23/2022]
Abstract
Lung cancer is a leading cause of death worldwide. The National Lung Screening Trial has demonstrated that lung cancer screening can reduce lung cancer specific and all cause mortality. With approval of national coverage for lung cancer screening, it is expected that an increase in exams related to pulmonary nodule detection and surveillance will ensue. Advanced imaging technologies for nodule detection and surveillance will be more important than ever. While computed tomography (CT) remains the modality of choice, other emerging modalities such as magnetic resonance imaging provides viable alternatives to CT.
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Cha MJ, Lee KS, Kim HS, Lee SW, Jeong CJ, Kim EY, Lee HY. Improvement in imaging diagnosis technique and modalities for solitary pulmonary nodules: from ground-glass opacity nodules to part-solid and solid nodules. Expert Rev Respir Med 2016; 10:261-78. [PMID: 26751340 DOI: 10.1586/17476348.2016.1141053] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
With advances in CT technology and the popularity of low-dose CT as a device for lung cancer screening, the detection rate of sub-solid pulmonary nodules as well as solid nodules has been increased. Distinguishing solid from sub-solid features is an essential step in the CT evaluation of solitary pulmonary nodules (SPNs) because strategies for nodule characterization and guidelines for management are different for each category. In addition to conventional CT parameters, numerous novel concepts and modalities have been developed. Although there is currently no single effective method for differentiating malignant from benign nodules, growth rate measurement using volumetry, evaluation of tumor vascularity on dynamic helical CT, dual-energy CT and MRI and physiologic evaluation with PET/CT can all be useful for nodule characterization. New techniques such as tomosynthesis can improve detection over radiography alone. The purpose of this article is to enhance our understanding of the evidence-based strategies involved in diagnosing SPNs.
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Affiliation(s)
- Min Jae Cha
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - Kyung Soo Lee
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - Hyun Su Kim
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - So Won Lee
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - Chae Jin Jeong
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - Eun Young Kim
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
| | - Ho Yun Lee
- a Department of Radiology and Center for Imaging Science , Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul , Korea
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Broncano J, Luna A, Sánchez-González J, Alvarez-Kindelan A, Bhalla S. Functional MR Imaging in Chest Malignancies. Magn Reson Imaging Clin N Am 2016; 24:135-155. [DOI: 10.1016/j.mric.2015.08.004] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region. Eur Radiol 2015; 26:2915-20. [PMID: 26638164 DOI: 10.1007/s00330-015-4125-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Revised: 10/13/2015] [Accepted: 11/16/2015] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To estimate the diagnostic accuracy of signal intensity of the lesion-to-spinal cord ratio (LSR) and apparent diffusion coefficient (ADC) in diffusion-weighted (DW) magnetic resonance imaging of pulmonary nodules suspicious for lung cancer in granulomatous lung disease-endemic regions. METHODS Forty-nine patients with indeterminate solitary pulmonary nodules detected by chest computed tomography and histopathologically confirmed diagnoses were included in the study. DW images were analysed semiquantitatively by focusing regions of interest on the lesion and spinal cord at the same level (for LSR calculation). ADCs were estimated from ratios of the two image signal intensities. Ratios of T1 and T2 signal intensity between nodules and muscle were calculated for comparison. RESULTS Mean ADCs ± standard deviations for lung cancer and benign lesions were 0.9 ± 0.2 and 1.3 ± 0.2 × 10(-3) mm(2)/s, respectively. Mean LSRs were 1.4 ± 0.3 for lung cancer and 1 ± 0.1 for benign lesions. ADCs and LSRs differed significantly between malignant and benign lesions (P < 0.001). Mean T2 signal intensity ratios also differed significantly between benign and malignant lesions (0.8 ± 0.2 vs. 1.6 ± 0.2; P < 0.05). CONCLUSIONS DWI can help to differentiate malignant from benign lesions according to ADC and the LSR with good accuracy. KEY POINTS • DW imaging can help differentiate malignant from benign pulmonary nodules. • ADC and LSR signal intensities had only small overlap between malignant and benign pulmonary nodules. • Mean T2 signal intensity ratios differed significantly between benign and malignant lesions.
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Pulmonary Nodule Characterization, Including Computer Analysis and Quantitative Features. J Thorac Imaging 2015; 30:139-56. [DOI: 10.1097/rti.0000000000000137] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Ohno Y, Nishio M, Koyama H, Seki S, Tsubakimoto M, Fujisawa Y, Yoshikawa T, Matsumoto S, Sugimura K. Solitary Pulmonary Nodules: Comparison of Dynamic First-Pass Contrast-enhanced Perfusion Area-Detector CT, Dynamic First-Pass Contrast-enhanced MR Imaging, and FDG PET/CT. Radiology 2015; 274:563-75. [DOI: 10.1148/radiol.14132289] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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Sommer G, Koenigkam-Santos M, Biederer J, Puderbach M. [Role of MRI for detection and characterization of pulmonary nodules]. Radiologe 2015; 54:470-7. [PMID: 24756231 DOI: 10.1007/s00117-013-2604-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Due to physical and technical limitations, magnetic resonance imaging (MRI) has hitherto played only a minor role in image-based diagnostics of the lungs. However, as a consequence of important methodological developments during recent years, MRI has developed into a technically mature and clinically well-proven method for specific pulmonary questions. OBJECTIVES AND METHODS The purpose of this article is to provide an overview on the currently available sequences and techniques for assessment of pulmonary nodules and analyzes the clinical significance according to the current literature. The main focus is on the detection of lung metastases, the detection of primary pulmonary malignancies in high-risk individuals and the differentiation between pulmonary nodules of benign and malignant character. RESULTS AND CONCLUSION The MRI technique has a sensitivity of approximately 80 % for detection of malignant pulmonary nodules compared to the reference standard low-dose computed tomography (CT) and is thus somewhat inferior to CT. Advantages of MRI on the other hand are a higher specificity in differentiating malignant and benign pulmonary nodules and the absence of ionizing radiation exposure. A systematic use of MRI as a primary tool for detection and characterization of pulmonary nodules is currently not recommended due to insufficient data. The diagnostic potential of MRI for early detection and staging of malignant pulmonary diseases, however, seems promising. Therefore, further evaluation of MRI as a secondary imaging modality in clinical trials is highly warranted.
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Affiliation(s)
- G Sommer
- Klinik für Radiologie und Nuklearmedizin, Universitätsspital Basel, Petersgraben 4, 4031, Basel, Schweiz,
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Koenigkam-Santos M, Optazaite E, Sommer G, Safi S, Heussel CP, Kauczor HU, Puderbach M. Contrast-enhanced magnetic resonance imaging of pulmonary lesions: Description of a technique aiming clinical practice. Eur J Radiol 2015; 84:185-192. [DOI: 10.1016/j.ejrad.2014.10.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Revised: 10/04/2014] [Accepted: 10/08/2014] [Indexed: 12/26/2022]
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Kim HS, Lee KS, Ohno Y, van Beek EJ, Biederer J. PET/CT versus MRI for diagnosis, staging, and follow-up of lung cancer. J Magn Reson Imaging 2014; 42:247-60. [DOI: 10.1002/jmri.24776] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Accepted: 09/27/2014] [Indexed: 12/19/2022] Open
Affiliation(s)
- Hyun Su Kim
- Department of Radiology and Center for Imaging Science; Samsung Medical Center, Sungkyunkwan University School of Medicine; Seoul Korea
| | - Kyung Soo Lee
- Department of Radiology and Center for Imaging Science; Samsung Medical Center, Sungkyunkwan University School of Medicine; Seoul Korea
| | - Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research; Department of Radiology; and Advanced Biomedical Imaging Research Centre, Kobe University Graduate School of Medicine; Kobe Japan
| | | | - Juergen Biederer
- Radiologie Darmstadt; Gross-Gerau County Hospital; Gross-Gerau Germany
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Fan L, Sher A, Kohan A, Vercher-Conejero J, Rajiah P. PET/MRI in Lung Cancer. Semin Roentgenol 2014; 49:291-303. [DOI: 10.1053/j.ro.2014.07.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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Deppen SA, Blume JD, Kensinger CD, Morgan AM, Aldrich MC, Massion PP, Walker RC, McPheeters ML, Putnam JB, Grogan EL. Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis. JAMA 2014; 312:1227-36. [PMID: 25247519 PMCID: PMC4315183 DOI: 10.1001/jama.2014.11488] [Citation(s) in RCA: 115] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
IMPORTANCE Positron emission tomography (PET) combined with fludeoxyglucose F 18 (FDG) is recommended for the noninvasive diagnosis of pulmonary nodules suspicious for lung cancer. In populations with endemic infectious lung disease, FDG-PET may not accurately identify malignant lesions. OBJECTIVES To estimate the diagnostic accuracy of FDG-PET for pulmonary nodules suspicious for lung cancer in regions where infectious lung disease is endemic and compare the test accuracy in regions where infectious lung disease is rare. DATA SOURCES AND STUDY SELECTION Databases of MEDLINE, EMBASE, and the Web of Science were searched from October 1, 2000, through April 28, 2014. Articles reporting information sufficient to calculate sensitivity and specificity of FDG-PET to diagnose lung cancer were included. Only studies that enrolled more than 10 participants with benign and malignant lesions were included. Database searches yielded 1923 articles, of which 257 were assessed for eligibility. Seventy studies were included in the analysis. Studies reported on a total of 8511 nodules; 5105 (60%) were malignant. DATA EXTRACTION AND SYNTHESIS Abstracts meeting eligibility criteria were collected by a research librarian and reviewed by 2 independent reviewers. Hierarchical summary receiver operating characteristic curves were constructed. A random-effects logistic regression model was used to summarize and assess the effect of endemic infectious lung disease on test performance. MAIN OUTCOME AND MEASURES The sensitivity and specificity for FDG-PET test performance. RESULTS Heterogeneity for sensitivity (I2 = 87%) and specificity (I2 = 82%) was observed across studies. The pooled (unadjusted) sensitivity was 89% (95% CI, 86%-91%) and specificity was 75% (95% CI, 71%-79%). There was a 16% lower average adjusted specificity in regions with endemic infectious lung disease (61% [95% CI, 49%-72%]) compared with nonendemic regions (77% [95% CI, 73%-80%]). Lower specificity was observed when the analysis was limited to rigorously conducted and well-controlled studies. In general, sensitivity did not change appreciably by endemic infection status, even after adjusting for relevant factors. CONCLUSIONS AND RELEVANCE The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous. Use of FDG-PET combined with computed tomography was less specific in diagnosing malignancy in populations with endemic infectious lung disease compared with nonendemic regions. These data do not support the use of FDG-PET to diagnose lung cancer in endemic regions unless an institution achieves test performance accuracy similar to that found in nonendemic regions.
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Affiliation(s)
- Stephen A. Deppen
- Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville TN
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville TN
| | - Jeffrey D. Blume
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville TN
| | - Clark D. Kensinger
- Department of Surgery, Vanderbilt University Medical Center, Nashville TN
| | - Ashley M. Morgan
- School of Medicine, Vanderbilt University Medical Center, Nashville TN
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville TN
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville TN
| | - Pierre P. Massion
- Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville TN
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville TN
| | - Ronald C. Walker
- Department of Medical Imaging, Tennessee Valley Healthcare System-Veterans Affairs, Nashville TN
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville TN
| | - Melissa L. McPheeters
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville TN
- Department of Medicine, Division of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville TN
| | - Joseph B. Putnam
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville TN
| | - Eric L. Grogan
- Veterans Affairs Hospital, Tennessee Valley Healthcare System, Nashville TN
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville TN
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Dynamic Contrast-Enhanced CT and MRI for Pulmonary Nodule Assessment. AJR Am J Roentgenol 2014; 202:515-29. [DOI: 10.2214/ajr.13.11888] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Patel VK, Naik SK, Naidich DP, Travis WD, Weingarten JA, Lazzaro R, Gutterman DD, Wentowski C, Grosu HB, Raoof S. A practical algorithmic approach to the diagnosis and management of solitary pulmonary nodules: part 1: radiologic characteristics and imaging modalities. Chest 2013; 143:825-839. [PMID: 23460160 DOI: 10.1378/chest.12-0960] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The solitary pulmonary nodule (SPN) is frequently encountered on chest imaging and poses an important diagnostic challenge to clinicians. The differential diagnosis is broad, ranging from benign granulomata and infectious processes to malignancy. Important concepts in the evaluation of SPNs include the definition, morphologic characteristics via appropriate imaging modalities, and the calculation of pretest probability of malignancy. Morphologic differentiation of SPN into solid or subsolid types is important in the choice of follow-up and further management. In this first part of a two-part series, we describe the morphologic characteristics and various imaging modalities available to further characterize SPN. In Part 2, we will describe the determination of pretest probability of malignancy and an algorithmic approach to the diagnosis of SPN.
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Comparison of Quantitatively Analyzed Dynamic Area-Detector CT Using Various Mathematic Methods With FDG PET/CT in Management of Solitary Pulmonary Nodules. AJR Am J Roentgenol 2013; 200:W593-602. [DOI: 10.2214/ajr.12.9197] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Cano Alonso R, Herráiz Hidalgo L, Álvarez Moreno E, Paniagua Correa C, Martínez de Vega V. Role of imaging techniques in the TNM classification of non-small cell bronchogenic carcinoma. RADIOLOGIA 2012. [DOI: 10.1016/j.rxeng.2011.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Shan F, Zhang Z, Xing W, Qiu J, Yang S, Wang J, Jiang Y, Chen G. Differentiation between malignant and benign solitary pulmonary nodules: use of volume first-pass perfusion and combined with routine computed tomography. Eur J Radiol 2012; 81:3598-605. [PMID: 22608062 DOI: 10.1016/j.ejrad.2012.04.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2012] [Revised: 04/02/2012] [Accepted: 04/10/2012] [Indexed: 10/28/2022]
Abstract
PURPOSE To evaluate the capability of first-pass volume perfusion computed tomography (PCT) for differentiation of solitary pulmonary nodules (SPNs) and to compare that of combination of PCT and routine CT with CT alone for the differentiation. MATERIALS AND METHODS Our institutional review board approved this study and informed consent was obtained. With nine excluded, 65 consecutive patients having a SPN with histopathologic proof or follow-up underwent a 30s PCT using the deconvolution model were evaluated. Kruskal-Wallis tests and receiver operating characteristics (ROC) analysis were underwent. Four radiologists assessed nodules independently and retrospectively. Diagnostic capability was compared for CT alone and PCT plus CT. ROC analysis, McNemar test, and weighted kappa statistics were performed. RESULTS Significant differences were found in parameters between malignant and benign nodules (p<0.0001 for blood flow, blood volume, and permeability surface area product), SPNs were more likely to be malignant by using threshold values of more than 55 ml/100 g/min, 2.5 ml/100 g, and 10 ml/100 g/min, respectively. PCT plus CT was significantly better in overall sensitivity (93%, p=0.004) and accuracy (94%, p=0.003) compared to CT alone, not specificity (96%). Area under the curve for ROC analyses of PCT plus CT was significantly larger than that of CT alone (p=0.018). Mean weighted kappa for PCT plus CT was 0.715, that for CT alone was 0.447. CONCLUSION Volume first-pass PCT can distinguish SPNs. Using PCT plus routine CT may be more sensitive and accurate for differentiating malignant from benign nodules than CT alone and allows more confidence and constancy.
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Affiliation(s)
- Fei Shan
- Department of Radiology, Third Affiliated Hospital of Suzhou University, 185, Juqian Road, Changzhou, Zip Code: 213003, PR China.
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MRI of the lung (3/3)-current applications and future perspectives. Insights Imaging 2012; 3:373-86. [PMID: 22695943 PMCID: PMC3481076 DOI: 10.1007/s13244-011-0142-z] [Citation(s) in RCA: 98] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Revised: 11/09/2011] [Accepted: 11/17/2011] [Indexed: 01/17/2023] Open
Abstract
Background MRI of the lung is recommended in a number of clinical indications. Having a non-radiation alternative is particularly attractive in children and young subjects, or pregnant women. Methods Provided there is sufficient expertise, magnetic resonance imaging (MRI) may be considered as the preferential modality in specific clinical conditions such as cystic fibrosis and acute pulmonary embolism, since additional functional information on respiratory mechanics and regional lung perfusion is provided. In other cases, such as tumours and pneumonia in children, lung MRI may be considered an alternative or adjunct to other modalities with at least similar diagnostic value. Results In interstitial lung disease, the clinical utility of MRI remains to be proven, but it could provide additional information that will be beneficial in research, or at some stage in clinical practice. Customised protocols for chest imaging combine fast breath-hold acquisitions from a “buffet” of sequences. Having introduced details of imaging protocols in previous articles, the aim of this manuscript is to discuss the advantages and limitations of lung MRI in current clinical practice. Conclusion New developments and future perspectives such as motion-compensated imaging with self-navigated sequences or fast Fourier decomposition MRI for non-contrast enhanced ventilation- and perfusion-weighted imaging of the lung are discussed. Main Messages • MRI evolves as a third lung imaging modality, combining morphological and functional information. • It may be considered first choice in cystic fibrosis and pulmonary embolism of young and pregnant patients. • In other cases (tumours, pneumonia in children), it is an alternative or adjunct to X-ray and CT. • In interstitial lung disease, it serves for research, but the clinical value remains to be proven. • New users are advised to make themselves familiar with the particular advantages and limitations.
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Cano Alonso R, Herráiz Hidalgo L, Álvarez Moreno E, Paniagua Correa C, Martínez de Vega V. [Role of imaging techniques in the TNM classification of non-small cell bronchogenic carcinoma]. RADIOLOGIA 2012; 54:306-20. [PMID: 22226376 DOI: 10.1016/j.rx.2011.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2010] [Revised: 09/12/2011] [Accepted: 09/12/2011] [Indexed: 10/14/2022]
Abstract
The Seventh Edition of the TNM Classification for non-small cell bronchogenic carcinomas include a series of changes in the T and M descriptor, in particular a re-classification of malignant pleural and pericardial effusions and of separated tumour nodes, new tumour size cut-off values and sub-divisions of the T1-T2 and M1 categories. We review these corrections that led to the changes in the staging system that affects stages II-III. Furthermore, we describe and illustrate the role of the different imaging techniques in tumour staging (CT, PET, PET-CT and MRI), highlighting their respective indications, advantages and disadvantages, as well their complementary function.
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Affiliation(s)
- R Cano Alonso
- Departamento de Diagnóstico por la Imagen, Hospital Universitario Quirón, Madrid, España.
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45
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Luna A, Sánchez-Gonzalez J, Caro P. Diffusion-weighted imaging of the chest. Magn Reson Imaging Clin N Am 2011; 19:69-94. [PMID: 21129636 DOI: 10.1016/j.mric.2010.09.006] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Diffusion-weighted imaging (DWI) is feasible in the chest with currently available MR imaging scanners, although it is technically demanding. Although there is scarce clinical experience, the use of DWI has shown promising results in the characterization of pulmonary nodules, in lung cancer characterization and staging, and in the evaluation of mediastinal and pleural pathology. Ongoing research opens a door to noninvasive evaluation of heart fibers by means of diffusion-tensor imaging. Another area under investigation is the use of DWI of hyperpolarized gases as an early biomarker of pulmonary disease.
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Affiliation(s)
- Antonio Luna
- MR Unit, SERCOSA, Health Time Group, Clinica las Nieves, Carmelo Torres 2, 23007 Jaén, Spain.
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Sieren JC, Ohno Y, Koyama H, Sugimura K, McLennan G. Recent technological and application developments in computed tomography and magnetic resonance imaging for improved pulmonary nodule detection and lung cancer staging. J Magn Reson Imaging 2011; 32:1353-69. [PMID: 21105140 DOI: 10.1002/jmri.22383] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
This review compares the emerging technologies and approaches in the application of magnetic resonance (MR) and computed tomography (CT) imaging for the assessment of pulmonary nodules and staging of malignant findings. Included in this review is a brief definition of pulmonary nodules and an introduction to the challenges faced. We have highlighted the current status of both MR and CT for the early detection of lung nodules. Developments are detailed in this review for the management of pulmonary nodules using advanced imaging, including: dynamic imaging studies, dual energy CT, computer aided detection and diagnosis, and imaging assisted nodule biopsy approaches which have improved lung nodule detection and diagnosis rates. Recent advancements linking in vivo imaging to corresponding histological pathology are also highlighted. In vivo imaging plays a pivotal role in the clinical staging of pulmonary nodules through TNM assessment. While CT and positron emission tomography (PET)/CT are currently the most commonly clinically employed modalities for pulmonary nodule staging, studies are presented that highlight the augmentative potential of MR.
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Affiliation(s)
- Jessica C Sieren
- Department of Internal Medicine, University of Iowa, Iowa City, Iowa, USA.
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Ohno Y, Koyama H, Matsumoto K, Onishi Y, Takenaka D, Fujisawa Y, Yoshikawa T, Konishi M, Maniwa Y, Nishimura Y, Ito T, Sugimura K. Differentiation of Malignant and Benign Pulmonary Nodules with Quantitative First-Pass 320–Detector Row Perfusion CT versus FDG PET/CT. Radiology 2011; 258:599-609. [DOI: 10.1148/radiol.10100245] [Citation(s) in RCA: 96] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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VAN BEEK EJR, TCHATALBACHEV V, WILD JM. Lung magnetic resonance imaging – an update. IMAGING 2008. [DOI: 10.1259/imaging/63202218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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