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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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2
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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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3
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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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Selvam M, Chandrasekharan A, Sadanandan A, Anand VK, Murali A, Krishnamurthi G. Radiomics as a non-invasive adjunct to Chest CT in distinguishing benign and malignant lung nodules. Sci Rep 2023; 13:19062. [PMID: 37925565 PMCID: PMC10625576 DOI: 10.1038/s41598-023-46391-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 10/31/2023] [Indexed: 11/06/2023] Open
Abstract
In an observational study conducted from 2016 to 2021, we assessed the utility of radiomics in differentiating between benign and malignant lung nodules detected on computed tomography (CT) scans. Patients in whom a final diagnosis regarding the lung nodules was available according to histopathology and/or 2017 Fleischner Society guidelines were included. The radiomics workflow included lesion segmentation, region of interest (ROI) definition, pre-processing, and feature extraction. Employing random forest feature selection, we identified ten important radiomic features for distinguishing between benign and malignant nodules. Among the classifiers tested, the Decision Tree model demonstrated superior performance, achieving 79% accuracy, 75% sensitivity, 85% specificity, 82% precision, and 90% F1 score. The implementation of the XGBoost algorithm further enhanced these results, yielding 89% accuracy, 89% sensitivity, 89% precision, and an F1 score of 89%, alongside a specificity of 85%. Our findings highlight tumor texture as the primary predictor of malignancy, emphasizing the importance of texture-based features in computational oncology. Thus, our study establishes radiomics as a powerful, non-invasive adjunct to CT scans in the differentiation of lung nodules, with significant implications for clinical decision-making, especially for indeterminate nodules, and the enhancement of diagnostic and predictive accuracy in this clinical context.
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Affiliation(s)
- Minmini Selvam
- Department of Radiology and Imaging Sciences, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600 116, India.
| | - Anupama Chandrasekharan
- Department of Radiology and Imaging Sciences, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600 116, India
| | - Abjasree Sadanandan
- Department of Engineering Design, Indian Institute of Technology-Madras, Chennai, 600 036, India
| | - Vikas Kumar Anand
- Department of Engineering Design, Indian Institute of Technology-Madras, Chennai, 600 036, India
| | - Arunan Murali
- Department of Radiology and Imaging Sciences, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, 600 116, India
| | - Ganapathy Krishnamurthi
- Department of Engineering Design, Indian Institute of Technology-Madras, Chennai, 600 036, India
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Ohno Y, Ozawa Y, Nagata H, Bando S, Cong S, Takahashi T, Oshima Y, Hamabuchi N, Matsuyama T, Ueda T, Yoshikawa T, Takenaka D, Toyama H. Area-Detector Computed Tomography for Pulmonary Functional Imaging. Diagnostics (Basel) 2023; 13:2518. [PMID: 37568881 PMCID: PMC10416899 DOI: 10.3390/diagnostics13152518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/22/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023] Open
Abstract
An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Diagnostic Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan;
| | - Yoshiyuki Ozawa
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Hiroyuki Nagata
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan;
| | - Shuji Bando
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Shang Cong
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Tomoki Takahashi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Yuka Oshima
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Nayu Hamabuchi
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takahiro Matsuyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
| | - Takeshi Yoshikawa
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi 673-0021, Hyogo, Japan
| | - Daisuke Takenaka
- Department of Diagnostic Radiology, Hyogo Cancer Center, Akashi 673-0021, Hyogo, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, Toyoake 470-1192, Aichi, Japan; (Y.O.)
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State of the Art: Lung Cancer Staging Using Updated Imaging Modalities. Bioengineering (Basel) 2022; 9:bioengineering9100493. [PMID: 36290461 PMCID: PMC9598500 DOI: 10.3390/bioengineering9100493] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/15/2022] [Accepted: 09/16/2022] [Indexed: 11/17/2022] Open
Abstract
Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.
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Zhao Y, Hubbard L, Malkasian S, Abbona P, Molloi S. Contrast timing optimization of a two-volume dynamic CT pulmonary perfusion technique. Sci Rep 2022; 12:8212. [PMID: 35581304 PMCID: PMC9114423 DOI: 10.1038/s41598-022-12016-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 04/21/2022] [Indexed: 11/12/2022] Open
Abstract
The purpose of this study is to develop and validate an optimal timing protocol for a low-radiation-dose CT pulmonary perfusion technique using only two volume scans. A total of 24 swine (48.5 ± 14.3 kg) underwent contrast-enhanced dynamic CT. Multiple contrast injections were made under different pulmonary perfusion conditions, resulting in a total of 141 complete pulmonary arterial input functions (AIFs). Using all the AIF curves, an optimal contrast timing protocol was developed for a first-pass, two-volume dynamic CT perfusion technique (one at the base and the other at the peak of AIF curve). A subset of swine was used to validate the prospective two-volume pulmonary perfusion technique. The prospective two-volume perfusion measurements were quantitatively compared to the previously validated retrospective perfusion measurements with t-test, linear regression, and Bland–Altman analysis. As a result, the pulmonary artery time-to-peak (\documentclass[12pt]{minimal}
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\begin{document}$${T}_{PA}$$\end{document}TPA) was related to one-half of the contrast injection duration (\documentclass[12pt]{minimal}
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\begin{document}$$\frac{{T}_{Inj}}{2}$$\end{document}TInj2) by \documentclass[12pt]{minimal}
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\begin{document}$${T}_{PA}=1.01\frac{{T}_{Inj}}{2}+1.01$$\end{document}TPA=1.01TInj2+1.01 (r = 0.95). The prospective two-volume perfusion measurements (PPRO) were related to the retrospective measurements (PRETRO) by PPRO = 0.87PRETRO + 0.56 (r = 0.88). The CT dose index and size-specific dose estimate of the two-volume CT technique were estimated to be 28.4 and 47.0 mGy, respectively. The optimal timing protocol can enable an accurate, low-radiation-dose two-volume dynamic CT perfusion technique.
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Affiliation(s)
- Yixiao Zhao
- Department of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA
| | - Logan Hubbard
- Department of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA
| | - Shant Malkasian
- Department of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA
| | - Pablo Abbona
- Department of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA
| | - Sabee Molloi
- Department of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
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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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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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Yan Q, Yi Y, Shen J, Shan F, Zhang Z, Yang G, Shi Y. Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses. Cancer Cell Int 2021; 21:539. [PMID: 34663307 PMCID: PMC8522214 DOI: 10.1186/s12935-021-02195-1] [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] [Received: 03/07/2021] [Accepted: 09/04/2021] [Indexed: 12/30/2022] Open
Abstract
Background Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions. Methods 73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer’s agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs. Results 107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49–0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%. Conclusions The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.
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Affiliation(s)
- Qinqin Yan
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Yinqiao Yi
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Jie Shen
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Fei Shan
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China
| | - Zhiyong Zhang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China.
| | - Yuxin Shi
- Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, China.
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Can dynamic imaging, using 18F-FDG PET/CT and CT perfusion differentiate between benign and malignant pulmonary nodules? Radiol Oncol 2021; 55:259-267. [PMID: 34051709 PMCID: PMC8366734 DOI: 10.2478/raon-2021-0024] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/24/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The aim of the study was to derive and compare metabolic parameters relating to benign and malignant pulmonary nodules using dynamic 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG) PET/CT, and nodule perfusion parameters derived through perfusion computed tomography (CT). PATIENTS AND METHODS Twenty patients with 21 pulmonary nodules incidentally detected on CT underwent a dynamic 18F-FDG PET/CT and a perfusion CT. The maximum standardized uptake value (SUVmax) was measured on conventional 18F-FDG PET/CT images. The influx constant (Ki ) was calculated from the dynamic 18F-FDG PET/CT data using Patlak model. Arterial flow (AF) using the maximum slope model and blood volume (BV) using the Patlak plot method for each nodule were calculated from the perfusion CT data. All nodules were characterized as malignant or benign based on histopathology or 2 year follow up CT. All parameters were statistically compared between the two groups using the nonparametric Mann-Whitney test. RESULTS Twelve malignant and 9 benign lung nodules were analysed (median size 20.1 mm, 9-29 mm) in 21 patients (male/female = 11/9; mean age ± SD: 65.3 ± 7.4; age range: 50-76 years). The average SUVmax values ± SD of the benign and malignant nodules were 2.2 ± 1.7 vs. 7.0 ± 4.5, respectively (p = 0.0148). Average Ki values in benign and malignant nodules were 0.0057 ± 0.0071 and 0.0230 ± 0.0155 min-1, respectively (p = 0.0311). Average BV for the benign and malignant nodules were 11.6857 ± 6.7347 and 28.3400 ± 15.9672 ml/100 ml, respectively (p = 0.0250). Average AF for the benign and malignant nodules were 74.4571 ± 89.0321 and 89.200 ± 49.8883 ml/100g/min, respectively (p = 0.1613). CONCLUSIONS Dynamic 18F-FDG PET/CT and perfusion CT derived blood volume had similar capability to differentiate benign from malignant lung nodules.
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Weir-McCall JR, Harris S, Miles KA, Qureshi NR, Rintoul RC, Dizdarevic S, Pike L, Cheow HK, Gilbert FJ. Impact of solitary pulmonary nodule size on qualitative and quantitative assessment using 18F-fluorodeoxyglucose PET/CT: the SPUTNIK trial. Eur J Nucl Med Mol Imaging 2021; 48:1560-1569. [PMID: 33130961 PMCID: PMC8113131 DOI: 10.1007/s00259-020-05089-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE To compare qualitative and semi-quantitative PET/CT criteria, and the impact of nodule size on the diagnosis of solitary pulmonary nodules in a prospective multicentre trial. METHODS Patients with an SPN on CT ≥ 8 and ≤ 30 mm were recruited to the SPUTNIK trial at 16 sites accredited by the UK PET Core Lab. Qualitative assessment used a five-point ordinal PET-grade compared to the mediastinal blood pool, and a combined PET/CT grade using the CT features. Semi-quantitative measures included SUVmax of the nodule, and as an uptake ratio to the mediastinal blood pool (SURBLOOD) or liver (SURLIVER). The endpoints were diagnosis of lung cancer via biopsy/histology or completion of 2-year follow-up. Impact of nodule size was analysed by comparison between nodule size tertiles. RESULTS Three hundred fifty-five participants completed PET/CT and 2-year follow-up, with 59% (209/355) malignant nodules. The AUCs of the three techniques were SUVmax 0.87 (95% CI 0.83;0.91); SURBLOOD 0.87 (95% CI 0.83; 0.91, p = 0.30 versus SUVmax); and SURLIVER 0.87 (95% CI 0.83; 0.91, p = 0.09 vs. SUVmax). The AUCs for all techniques remained stable across size tertiles (p > 0.1 for difference), although the optimal diagnostic threshold varied by size. For nodules < 12 mm, an SUVmax of 1.75 or visual uptake equal to the mediastinum yielded the highest accuracy. For nodules > 16 mm, an SUVmax ≥ 3.6 or visual PET uptake greater than the mediastinum was the most accurate. CONCLUSION In this multicentre trial, SUVmax was the most accurate technique for the diagnosis of solitary pulmonary nodules. Diagnostic thresholds should be altered according to nodule size. TRIAL REGISTRATION ISRCTN - ISRCTN30784948. ClinicalTrials.gov - NCT02013063.
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Affiliation(s)
- J R Weir-McCall
- Department of Radiology, Biomedical Research Centre, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK
- Department of Radiology, Royal Papworth Hospital, Cambridge, UK
| | - S Harris
- Public Health Sciences and Medical Statistics, University of Southampton, Southampton, UK
| | - K A Miles
- Institute of Nuclear Medicine, University College London, London, UK
| | - N R Qureshi
- Department of Radiology, Royal Papworth Hospital, Cambridge, UK
| | - R C Rintoul
- Department of Thoracic Oncology, Royal Papworth Hospital / Department of Oncology, University of Cambridge, Cambridge, UK
| | - S Dizdarevic
- Departments of Imaging and Nuclear Medicine and Respiratory Medicine, Brighton and Sussex University Hospitals NHS Trust, Brighton and Sussex Medical School, Brighton, UK
| | - L Pike
- King's College London and Guy's & St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Heok K Cheow
- Addenbrookes Hospital, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Fiona J Gilbert
- Department of Radiology, Biomedical Research Centre, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK.
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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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15
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Ohno Y, Seo JB, Parraga G, Lee KS, Gefter WB, Fain SB, Schiebler ML, Hatabu H. Pulmonary Functional Imaging: Part 1-State-of-the-Art Technical and Physiologic Underpinnings. Radiology 2021; 299:508-523. [PMID: 33825513 DOI: 10.1148/radiol.2021203711] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Over the past few decades, pulmonary imaging technologies have advanced from chest radiography and nuclear medicine methods to high-spatial-resolution or low-dose chest CT and MRI. It is currently possible to identify and measure pulmonary pathologic changes before these are obvious even to patients or depicted on conventional morphologic images. Here, key technological advances are described, including multiparametric CT image processing methods, inhaled hyperpolarized and fluorinated gas MRI, and four-dimensional free-breathing CT and MRI methods to measure regional ventilation, perfusion, gas exchange, and biomechanics. The basic anatomic and physiologic underpinnings of these pulmonary functional imaging techniques are explained. In addition, advances in image analysis and computational and artificial intelligence (machine learning) methods pertinent to functional lung imaging are discussed. The clinical applications of pulmonary functional imaging, including both the opportunities and challenges for clinical translation and deployment, will be discussed in part 2 of this review. Given the technical advances in these sophisticated imaging methods and the wealth of information they can provide, it is anticipated that pulmonary functional imaging will be increasingly used in the care of patients with lung disease. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Yoshiharu Ohno
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Joon Beom Seo
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Grace Parraga
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Kyung Soo Lee
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Warren B Gefter
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Sean B Fain
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Mark L Schiebler
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
| | - Hiroto Hatabu
- From the Department of Radiology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Aichi, Japan (Y.O.); Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan (Y.O.); Department of Radiology, Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea (J.B.S.); Department of Medicine, Robarts Research Institute, and Department of Medical Biophysics, Western University, London, Canada (G.P.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, Korea (K.S.L.); Department of Radiology, Penn Medicine, University of Pennsylvania, Philadelphia, Pa (W.B.G.); Departments of Medical Physics and Radiology (S.B.F., M.L.S.), UW-Madison School of Medicine and Public Health, Madison, Wis; and Center for Pulmonary Functional Imaging, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St, Boston, MA 02215 (H.H.)
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Ohno Y, Hanamatsu S, Obama Y, Ueda T, Ikeda H, Hattori H, Murayama K, Toyama H. Overview of MRI for pulmonary functional imaging. Br J Radiol 2021; 95:20201053. [PMID: 33529053 DOI: 10.1259/bjr.20201053] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Morphological evaluation of the lung is important in the clinical evaluation of pulmonary diseases. However, the disease process, especially in its early phases, may primarily result in changes in pulmonary function without changing the pulmonary structure. In such cases, the traditional imaging approaches to pulmonary morphology may not provide sufficient insight into the underlying pathophysiology. Pulmonary imaging community has therefore tried to assess pulmonary diseases and functions utilizing not only nuclear medicine, but also CT and MR imaging with various technical approaches. In this review, we overview state-of-the art MR methods and the future direction of: (1) ventilation imaging, (2) perfusion imaging and (3) biomechanical evaluation for pulmonary functional imaging.
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Affiliation(s)
- Yoshiharu Ohno
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan.,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Satomu Hanamatsu
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Yuki Obama
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Takahiro Ueda
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Hirotaka Ikeda
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Hidekazu Hattori
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, Toyoake, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University, School of Medicine, Toyoake, Japan
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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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Grob D, Oostveen LJ, Jacobs C, Scholten E, Prokop M, Schaefer-Prokop CM, Sechopoulos I, Brink M. Pulmonary nodule enhancement in subtraction CT and dual-energy CT: A comparison study. Eur J Radiol 2020; 134:109443. [PMID: 33310553 DOI: 10.1016/j.ejrad.2020.109443] [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: 08/18/2020] [Revised: 11/10/2020] [Accepted: 11/25/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To compare nodule enhancement on subtraction CT iodine maps to that on dual-energy CT iodine maps using CT datasets acquired simultaneously. METHODS A previously-acquired set of lung subtraction and dual-energy CT maps consisting of thirty patients with 95 solid pulmonary nodules (≥4 mm diameter) was used. Nodules were annotated and segmented on CT angiography, and mean nodule enhancement in the iodine maps calculated. Three radiologists scored nodule visibility with both techniques on a 4-point scale. RESULTS Mean nodule enhancement was higher (p < 0.001) at subtraction CT (34.9 ± 12.9 HU) than at dual-energy CT (25.4 ± 21.0 HU). Nodule enhancement at subtraction CT was judged more often to be "highly visible" for each observers (p < 0.001) with an area under the curve of 0.81. CONCLUSIONS Subtraction CT is able to depict iodine enhancement in pulmonary nodules better than dual-energy CT.
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Affiliation(s)
- Dagmar Grob
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Luuk J Oostveen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Colin Jacobs
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Ernst Scholten
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Mathias Prokop
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Cornelia M Schaefer-Prokop
- Department of Radiology and Nuclear Medicine, Meander Medical Centre, Maatweg 3, 3813 TZ, Amersfoort, the Netherlands.
| | - Ioannis Sechopoulos
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
| | - Monique Brink
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands.
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Matsukiyo R, Ohno Y, Matsuyama T, Nagata H, Kimata H, Ito Y, Ogawa Y, Murayama K, Kato R, Toyama H. Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions. Jpn J Radiol 2020; 39:186-197. [PMID: 33037956 DOI: 10.1007/s11604-020-01045-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 09/11/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To determine the image quality improvement including vascular structures using deep learning reconstruction (DLR) for ultra-high-resolution CT (UHR-CT) and area-detector CT (ADCT) compared to a commercially available hybrid-iterative reconstruction (IR) method. MATERIALS AND METHOD Thirty-two patients suspected of renal cell carcinoma underwent dynamic contrast-enhanced (CE) CT using UHR-CT or ADCT systems. CT value and contrast-to-noise ratio (CNR) on each CT dataset were assessed with region of interest (ROI) measurements. For qualitative assessment of improvement for vascular structure visualization, each artery was assessed using a 5-point scale. To determine the utility of DLR, CT values and CNRs were compared among all UHR-CT data by means of ANOVA followed by Bonferroni post hoc test, and same values on ADCT data were also compared between hybrid IR and DLR methods by paired t test. RESULTS For all arteries except the aorta, the CT value and CNR of the DLR method were significantly higher compared to those of the hybrid-type IR method in both CT systems reconstructed as 512 or 1024 matrixes (p < 0.05). CONCLUSION DLR has a higher potential to improve the image quality resulting in a more accurate evaluation for vascular structures than hybrid IR for both UHR-CT and ADCT.
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Affiliation(s)
- Ryo Matsukiyo
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Yoshiharu Ohno
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan. .,Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Takahiro Matsuyama
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Hiroyuki Nagata
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Hirona Kimata
- Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi, 324-8550, Japan
| | - Yuya Ito
- Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi, 324-8550, Japan
| | - Yukihiro Ogawa
- Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi, 324-8550, Japan
| | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Ryoichi Kato
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University School of Medicine, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
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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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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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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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23
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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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Yan Q, Yang S, Shen J, Lu S, Shan F, Shi Y. 3T magnetic resonance for evaluation of adult pulmonary tuberculosis. Int J Infect Dis 2020; 93:287-294. [PMID: 32062060 DOI: 10.1016/j.ijid.2020.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 01/17/2020] [Accepted: 02/09/2020] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVES To evaluate image quality and detection rate of four 3T magnetic resonance imaging (MRI) sequences and MRI performances in pulmonary tuberculosis (TB) when compared to computed tomography (CT). METHODS Forty patients with pulmonary tuberculosis separately underwent CT and 3T-MRI with T1-weighted free-breathing star-volumetric interpolated breath-hold examination (Star-VIBE) and standard VIBE, T2-weighted two-dimensional fast BLADE turbo spin-echo (2D-fBLADE TSE) and three-dimensional isotropic turbo spin-echo (3D-SPACE). Four MRI sequences were compared in terms of detection rate and image quality, which consisted of signal to noise ratio (SNR), contrast to noise ratio (CNR) and 5-point scoring scale. The total sensitivity was also compared between CT and MRI. Inter-observer agreement on 5-point scoring scale was calculated by Cohen's kappa (k). SNR, CNR and 5-point scoring scale were compared using two-tailed pared t-test. Using CT as a reference, the MRI detection rate of pulmonary abnormality was evaluated by Pearson's Chi-square test. Furthermore, the sizes of the nodules (≥5 mm) were compared using intraclass correlation coefficient. RESULTS In this study, Free-breathing Star-VIBE had significantly better SNR and identical CNR compared with standard VIBE. 2D-fBLADE TSE had statistically higher SNR but uniform or inferior CNR compared with 3D-SPACE. Inter-observers showed excellent agreement on 5-point scoring scale. The average score of Star-VIBE and VIBE had no difference. The average score of 2D-fBLADE TSE was higher than 3D-SPACE. There were no statistical differences in the detection rates of non-calcified parenchymal lesions between Star-VIBE and standard VIBE, 2D-fBALDE TSE and 3D-SPACE. MRI is comparable to CT in detecting consolidation, cavity, non-calcified nodules of ≥5 mm and tree-in-bud signs compared to CT. MRI detected non-calcified nodules of <5 mm, 5-10 mm, ≥10 mm and calcified nodules with sensitivity of 69.6%, 90.6%, 100% and 89.5% respectively. In addition, the sizes of the nodules (≥5 mm) had statistical consistency. MRI is more sensitive in detecting caseous necrosis, liquefaction, active cavity, abnormalities of lymph nodes and pleura. CONCLUSIONS T1-weighted free-breathing Star-VIBE and T2-weighted 2D-fBLADE TSE, both with satisfactory image quality, are suitable for patients with pulmonary TB who need long-term follow-ups in clinical routine, especially for children, young women and pregnant women.
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Affiliation(s)
- Qinqin Yan
- Shanghai Institute of Medical Imaging, Shanghai, Fudan university, Shanghai, China; Department of Radiology, Shanghai public health clinical center, Shanghai, China
| | - Shuyi Yang
- Department of Radiology, Shanghai public health clinical center, Shanghai, China
| | - Jie Shen
- Department of Radiology, Shanghai public health clinical center, Shanghai, China
| | - Shuihua Lu
- Department of Tuberculosis, Shanghai public health clinical center, Shanghai, China
| | - Fei Shan
- Department of Radiology, Shanghai public health clinical center, Shanghai, China.
| | - Yuxin Shi
- Department of Radiology, Shanghai public health clinical center, Shanghai, China.
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25
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Zhao Y, Hubbard L, Malkasian S, Abbona P, Molloi S. Dynamic pulmonary CT perfusion using first-pass analysis technique with only two volume scans: Validation in a swine model. PLoS One 2020; 15:e0228110. [PMID: 32049969 PMCID: PMC7015394 DOI: 10.1371/journal.pone.0228110] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 01/07/2020] [Indexed: 12/02/2022] Open
Abstract
PURPOSE To evaluate the accuracy of a low-dose first-pass analysis (FPA) CT pulmonary perfusion technique in comparison to fluorescent microsphere measurement as the reference standard. METHOD The first-pass analysis CT perfusion technique was validated in six swine (41.7 ± 10.2 kg) for a total of 39 successful perfusion measurements. Different perfusion conditions were generated in each animal using serial balloon occlusions in the pulmonary artery. For each occlusion, over 20 contrast-enhanced CT images were acquired within one breath (320 x 0.5mm collimation, 100kVp, 200mA or 400mA, 350ms gantry rotation time). All volume scans were used for maximum slope model (MSM) perfusion measurement, but only two volume scans were used for the FPA measurement. Both MSM and FPA perfusion measurements were then compared to the reference fluorescent microsphere measurements. RESULTS The mean lung perfusion of MSM, FPA, and microsphere measurements were 6.21 ± 3.08 (p = 0.008), 6.59 ± 3.41 (p = 0.44) and 6.68 ± 3.89 ml/min/g, respectively. The MSM (PMSM) and FPA (PFPA) perfusion measurements were related to the corresponding reference microsphere measurement (PMIC) by PMSM = 0.51PMIC + 2.78 (r = 0.64) and PFPA = 0.79PMIC + 1.32 (r = 0.90). The root-mean-square-error for the MSM and FPA techniques were 3.09 and 1.72 ml/min/g, respectively. The root-mean-square-deviation for the MSM and FPA techniques were 2.38 and 1.50 ml/min/g, respectively. The CT dose index for MSM and FPA techniques were 138.7 and 8.4mGy, respectively. CONCLUSIONS The first-pass analysis technique can accurately measure regional pulmonary perfusion and has the potential to reduce the radiation dose associated with dynamic CT perfusion for assessment of pulmonary disease.
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Affiliation(s)
- Yixiao Zhao
- Department of Radiological Sciences, University of California Irvine, Irvine, California, United States of America
| | - Logan Hubbard
- Department of Radiological Sciences, University of California Irvine, Irvine, California, United States of America
| | - Shant Malkasian
- Department of Radiological Sciences, University of California Irvine, Irvine, California, United States of America
| | - Pablo Abbona
- Department of Radiological Sciences, University of California Irvine, Irvine, California, United States of America
| | - Sabee Molloi
- Department of Radiological Sciences, University of California Irvine, Irvine, California, United States of America
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26
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Kim TJ, Kim CH, Lee HY, Chung MJ, Shin SH, Lee KJ, Lee KS. Management of incidental pulmonary nodules: current strategies and future perspectives. Expert Rev Respir Med 2019; 14:173-194. [PMID: 31762330 DOI: 10.1080/17476348.2020.1697853] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: Detection and characterization of pulmonary nodules is an important issue, because the process is the first step in the management of lung cancers.Areas covered: Literature review was performed on May 15 2019 by using the PubMed, US National Library of Medicine National Institutes of Health, and the National Center for Biotechnology information. CT features helping identify the druggable mutations and predict the prognosis of malignant nodules were presented. Technical advancements in MRI and PET/CT were introduced for providing functional information about malignant nodules. Advances in various tissue biopsy techniques enabling molecular analysis and histologic diagnosis of indeterminate nodules were also presented. New techniques such as radiomics, deep learning (DL) technology, and artificial intelligence showing promise in differentiating between malignant and benign nodules were summarized. Recently, updated management guidelines for solid and subsolid nodules incidentally detected on CT were described. Risk stratification and prediction models for indeterminate nodules under active investigation were briefly summarized.Expert opinion: Advancement in CT knowledge has led to a better correlation between CT features and genomic alterations or tumor histology. Recent advances like PET/CT, MRI, radiomics, and DL-based approach have shown promising results in the characterization and prognostication of pulmonary nodules.
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Affiliation(s)
- Tae Jung Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Cho Hee Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Ho Yun Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Myung Jin Chung
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Sun Hye Shin
- Respiratory and Critical Care Division of Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Kyung Jong Lee
- Respiratory and Critical Care Division of Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
| | - Kyung Soo Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine (SKKU-SOM), Seoul, South Korea
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Application of Radiomics in Predicting the Malignancy of Pulmonary Nodules in Different Sizes. AJR Am J Roentgenol 2019; 213:1213-1220. [PMID: 31557054 DOI: 10.2214/ajr.19.21490] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE. The purpose of this study was to investigate the utility of radiomics for predicting the malignancy of pulmonary nodules (PNs) of different sizes using unenhanced, thin-section CT images. MATERIALS AND METHODS. Patients with a single PN (n = 373) who underwent a preoperative chest CT were recruited retrospectively at Beijing Friendship Hospital from March 2015 to March 2018. Of the 373 PNs studied, 192 were benign and 181 were malignant. The lesions were classified into three groups (T1a, T1b, or T1c according to the 8th edition of the TNM staging system for lung cancer) on the basis of lesion diameters: T1a (diameter, 0-1 cm), T1b (1 cm < diameter ≤ 2 cm) and T1c (2 cm < diameter ≤ 3 cm). A total of 1160 radiomic features were extracted from PN segmentation on unenhanced CT images. We developed three radiomic models to predict PN malignancy in each group on the basis of the extracted radiomic features. Fivefold cross-validation was used to estimate AUC, accuracy, sensitivity, and specificity for indicating the performance of prediction models. RESULTS. The AUC, accuracy, sensitivity, and specificity for predicting PN malignancy in each group were 0.84, 0.77, 0.89, and 0.74 with the T1a model; 0.78, 0.73, 0.74, and 0.71 with the T1b model, and 0.79, 0.76, 0.77, and 0.73 with the T1c model, respectively. The most contributive radiomic features for predicting PN malignancy for groups T1a, T1b, and T1c were LoG_X_Uniformity, Intensity_Minimum, and Shape_SI9, respectively. CONCLUSION. Radiomic features based on unenhanced CT images can be used to predict the malignancy of pulmonary nodules. The radiomic T1a model showed superior prediction performance to the T1b and T1c models, and the best performance in terms of AUC and sensitivity was found for predicting the malignancy of T1a PN.
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Jia Y, Gong W, Zhang Z, Tu G, Li J, Xiong F, Hou H, Zhang Y, Wu M, Zhang L. Comparing the diagnostic value of 18F-FDG-PET/CT versus CT for differentiating benign and malignant solitary pulmonary nodules: a meta-analysis. J Thorac Dis 2019; 11:2082-2098. [PMID: 31285902 DOI: 10.21037/jtd.2019.05.21] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background This quantitative meta-analysis was conducted to provide an indirect comparison of the diagnostic value of computed tomography (CT) with positron emission tomography (PET)/CT for differentiating benign and malignant solitary pulmonary nodules (SPNs). Methods PubMed, Embase, and the Cochrane Library were searched to identify eligible studies throughout November 2018, which differentiated benign and malignant SPNs using CT or PET/CT. The summary sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) were calculated using bivariate generalized linear mixed model and random-effects model. The diagnostic value of CT with PET/CT was indirectly evaluated using the ratio for diagnostic parameters. Results The sensitivity, specificity, PLR, NLR, DOR, and AUC for CT were 0.94 [95% confidence interval (CI): 0.87-0.97], 0.73 (95% CI: 0.64-0.80), 3.45 (95% CI: 2.60-4.58), 0.09 (95% CI: 0.04-0.17), 32.01 (95% CI: 15.10-67.86), and 0.89 (95% CI: 0.86-0.91), respectively. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC for PET/CT were 0.89 (95% CI: 0.85-0.92), 0.78 (95% CI: 0.66-0.86), 3.97 (95% CI: 2.57-6.13), 0.15 (95% CI: 0.10-0.20), 24.04 (95% CI: 12.71-45.48), and 0.91 (95% CI: 0.89-0.94), respectively. No significant differences were observed between CT and PET/CT for sensitivity, specificity, PLR, NLR, DOR, and AUC. Conclusions This study used both CT and PET/CT with a moderate-to-high diagnostic value for differentiating benign and malignant SPNs and showed no significant differences in diagnostic parameters between CT and PET/CT.
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Affiliation(s)
- Yuzhu Jia
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Wanfeng Gong
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Zhiping Zhang
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Gaofeng Tu
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Jiapeng Li
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Fanfan Xiong
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Hongtao Hou
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Yunyi Zhang
- Department of Radiology, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Meiqian Wu
- Department of Traditional Chinese Medicine, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
| | - Liping Zhang
- Department of Traditional Chinese Medicine, Zhejiang Provincial Tongde Hospital, Hangzhou 310012, China
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Update on MR imaging of the pulmonary vasculature. Int J Cardiovasc Imaging 2019; 35:1483-1497. [PMID: 31030315 DOI: 10.1007/s10554-019-01603-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 04/11/2019] [Indexed: 01/01/2023]
Abstract
Magnetic resonance imaging (MRI) plays an increasingly important role in the non-invasive evaluation of the pulmonary vasculature. MR angiographic (MRA) techniques provide morphological information, while MR perfusion techniques provide functional information of the pulmonary vasculature. Contrast-enhanced MRA can be performed at high spatial resolution using 3D T1-weighted spoiled gradient echo sequence or at high temporal resolution using time-resolved techniques. Non-contrast MRA can be performed using 3D steady state free precession, double inversion fast spin echo, time of flight or phase contrast sequences. MR perfusion can be done using dynamic contrast-enhanced technique or using non-contrast techniques such as arterial spin labelling and time-resolved imaging of lungs during free breathing with Fourier decomposition analysis. MRI is used in the evaluation of acute and chronic pulmonary embolism, pulmonary hypertension and other vascular abnormalities, congenital anomalies and neoplasms. In this article, we review the different MR techniques used in the evaluation of pulmonary vasculature and its clinical applications.
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Grob D, Oostveen L, Rühaak J, Heldmann S, Mohr B, Michielsen K, Dorn S, Prokop M, Kachelrieβ M, Brink M, Sechopoulos I. Accuracy of registration algorithms in subtraction CT of the lungs: A digital phantom study. Med Phys 2019; 46:2264-2274. [PMID: 30888690 PMCID: PMC6849605 DOI: 10.1002/mp.13496] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 02/15/2019] [Accepted: 03/07/2019] [Indexed: 12/20/2022] Open
Abstract
Purpose The purpose of this study was to assess, using an anthropomorphic digital phantom, the accuracy of algorithms in registering precontrast and contrast‐enhanced computed tomography (CT) chest images for generation of iodine maps of the pulmonary parenchyma via temporal subtraction. Materials and methods The XCAT phantom, with enhanced airway and pulmonary vessel structures, was used to simulate precontrast and contrast‐enhanced chest images at various inspiration levels and added CT simulation for realistic system noise. Differences in diaphragm position were varied between 0 and 20 mm, with the maximum chosen to exceed the 95th percentile found in a dataset of 100 clinical subtraction CTs. In addition, the influence of whole body movement, degree of iodine enhancement, beam hardening artifacts, presence of nodules and perfusion defects in the pulmonary parenchyma, and variation in noise on the registration were also investigated. Registration was performed using three lung registration algorithms — a commercial (algorithm A) and a prototype (algorithm B) version from Canon Medical Systems and an algorithm from the MEVIS Fraunhofer institute (algorithm C). For each algorithm, we calculated the voxel‐by‐voxel difference between the true deformation and the algorithm‐estimated deformation in the lungs. Results The median absolute residual error for all three algorithms was smaller than the voxel size (1.0 × 1.0 × 1.0 mm3) for up to an 8 mm diaphragm difference, which is the average difference in diaphragm levels found clinically, and increased with increasing difference in diaphragm position. At 20 mm diaphragm displacement, the median absolute residual error after registration was 0.85 mm (interquartile range, 0.51–1.47 mm) for algorithm A, 0.82 mm (0.50–1.40 mm) for algorithm B, and 0.91 mm (0.54–1.52 mm) for algorithm C. The largest errors were seen in the paracardiac regions and close to the diaphragm. The impact of all other evaluated conditions on the residual error varied, resulting in an increase in the median residual error lower than 0.1 mm for all algorithms, except in the case of whole body displacements for algorithm B, and with increased noise for algorithm C. Conclusion Motion correction software can compensate for respiratory and cardiac motion with a median residual error below 1 mm, which was smaller than the voxel size, with small differences among the tested registration algorithms for different conditions. Perfusion defects above 50 mm will be visible with the commercially available subtraction CT software, even in poorly registered areas, where the median residual error in that area was 7.7 mm.
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Affiliation(s)
- Dagmar Grob
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Luuk Oostveen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Jan Rühaak
- Fraunhofer Institute for Medical Image Computing MEVIS, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V., Maria-Goeppert-Str. 3, 23562, Lübeck, Germany
| | - Stefan Heldmann
- Fraunhofer Institute for Medical Image Computing MEVIS, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V., Maria-Goeppert-Str. 3, 23562, Lübeck, Germany
| | - Brian Mohr
- Canon Medical Research Europe, Anderson Place 2, E6 5NP, Edinburgh, Scotland
| | - Koen Michielsen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Sabrina Dorn
- German Cancer Research Center, Heidelberg (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Mathias Prokop
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Marc Kachelrieβ
- German Cancer Research Center, Heidelberg (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Monique Brink
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Ioannis Sechopoulos
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.,Dutch Expert Center for Screening (LRCB), Wijchenseweg 101, 6538 SW, Nijmegen, The Netherlands
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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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Seki S, Fujisawa Y, Yui M, Kishida Y, Koyama H, Ohyu S, Sugihara N, Yoshikawa T, Ohno Y. Dynamic Contrast-enhanced Area-detector CT vs Dynamic Contrast-enhanced Perfusion MRI vs FDG-PET/CT: Comparison of Utility for Quantitative Therapeutic Outcome Prediction for NSCLC Patients Undergoing Chemoradiotherapy. Magn Reson Med Sci 2019; 19:29-39. [PMID: 30880291 PMCID: PMC7067914 DOI: 10.2463/mrms.mp.2018-0158] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To directly compare the utility for therapeutic outcome prediction of dynamic first-pass contrast-enhanced (CE)-perfusion area-detector computed tomography (ADCT), MR imaging assessed with the same mathematical method and 2-[fluorine-18]-fluoro-2-deoxy-d-glucose-positron emission tomography combined with CT (PET/CT) for non-small cell lung cancer (NSCLC) patients treated with chemoradiotherapy. MATERIALS AND METHODS Forty-three consecutive stage IIIB NSCLC patients, consisting of 25 males (mean age ± standard deviation: 66.6 ± 8.7 years) and 18 females (66.4 ± 8.2 years) underwent PET/CT, dynamic CE-perfusion ADCT and MR imaging, chemoradiotherapy, and follow-up examination. In each patient, total, pulmonary arterial, and systemic arterial perfusions were calculated from both perfusion data and SUVmax on PET/CT, assessed for each targeted lesion, and averaged to determine final values. Receiver operating characteristics analyses were performed to compare the utility for distinguishing responders from non-responders using Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 criteria. Overall survival (OS) assessed with each index were compared between two groups by means of the Kaplan-Meier method followed by the log-rank test. RESULTS Area under the curve (Az) for total perfusion on ADCT was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Az of total perfusion on MR imaging was significantly larger than that of pulmonary arterial perfusion (P < 0.05). Mean OS of responder and non-responder groups were significantly different for total and systemic arterial (P < 0.05) perfusion. CONCLUSION Dynamic first-pass CE-perfusion ADCT and MR imaging as well as PET/CT are useful for early prediction of treatment response by NSCLC patients treated with chemoradiotherapy.
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Affiliation(s)
- Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
| | | | | | - Yuji Kishida
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine
| | - Hisanobu Koyama
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine
| | | | | | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
| | - Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine.,Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine
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Ohno Y, Koyama H, Seki S, Kishida Y, Yoshikawa T. Radiation dose reduction techniques for chest CT: Principles and clinical results. Eur J Radiol 2018; 111:93-103. [PMID: 30691672 DOI: 10.1016/j.ejrad.2018.12.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 12/06/2018] [Accepted: 12/16/2018] [Indexed: 11/19/2022]
Abstract
Computer tomography plays a major role in the evaluation of thoracic diseases, especially since the advent of the multidetector-row CT (MDCT) technology. However, the increase use of this technique has raised some concerns about the resulting radiation dose. In this review, we will present the various methods allowing limiting the radiation dose exposure resulting from chest CT acquisitions, including the options of image filtering and iterative reconstruction (IR) algorithms. The clinical applications of reduced dose protocols will be reviewed, especially for lung nodule detection and diagnosis of pulmonary thromboembolism. The performance of reduced dose protocols for infiltrative lung disease assessment will also be discussed. Lastly, the influence of using IR algorithms on computer-aided detection and volumetry of lung nodules, as well as on quantitative and functional assessment of chest diseases will be presented and discussed.
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Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan.
| | | | - Shinichiro Seki
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan
| | - Yuji Kishida
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Japan
| | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Japan; Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Japan
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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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Imaging of pulmonary perfusion using subtraction CT angiography is feasible in clinical practice. Eur Radiol 2018; 29:1408-1414. [PMID: 30255247 PMCID: PMC6510874 DOI: 10.1007/s00330-018-5740-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Revised: 07/24/2018] [Accepted: 08/28/2018] [Indexed: 01/06/2023]
Abstract
Abstract Subtraction computed tomography (SCT) is a technique that uses software-based motion correction between an unenhanced and an enhanced CT scan for obtaining the iodine distribution in the pulmonary parenchyma. This technique has been implemented in clinical practice for the evaluation of lung perfusion in CT pulmonary angiography (CTPA) in patients with suspicion of acute and chronic pulmonary embolism, with acceptable radiation dose. This paper discusses the technical principles, clinical interpretation, benefits and limitations of arterial subtraction CTPA. Key Points • SCT uses motion correction and image subtraction between an unenhanced and an enhanced CT scan to obtain iodine distribution in the pulmonary parenchyma. • SCT could have an added value in detection of pulmonary embolism. • SCT requires only software implementation, making it potentially more widely available for patient care than dual-energy CT.
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CT perfusion imaging of lung cancer: benefit of motion correction for blood flow estimates. Eur Radiol 2018; 28:5069-5075. [PMID: 29869174 DOI: 10.1007/s00330-018-5492-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 03/30/2018] [Accepted: 04/17/2018] [Indexed: 12/18/2022]
Abstract
PURPOSE CT perfusion (CTP) imaging assessment of treatment response in advanced lung cancer can be compromised by respiratory motion. Our purpose was to determine whether an original motion correction method could improve the reproducibility of such measurements. MATERIALS AND METHODS The institutional review board approved this prospective study. Twenty-one adult patients with non-resectable non-small-cell lung cancer provided written informed consent to undergo CTP imaging. A motion correction method that consisted of manually outlining the tumor margins and then applying a rigid manual landmark registration algorithm followed by the non-rigid diffeomorphic demons algorithm was applied. The non-motion-corrected and motion-corrected images were analyzed with dual blood supply perfusion analysis software. Two observers performed the analysis twice, and the intra- and inter-observer variability of each method was assessed with Bland-Altman statistics. RESULTS The 95% limits of agreement of intra-observer reproducibility for observer 1 improved from -84.4%, 65.3% before motion correction to -33.8%, 30.3% after motion correction (r = 0.86 and 0.97, before and after motion correction, p < 0.0001 for both) and for observer 2 from -151%, 96% to -49 %, 36 % (r = 0.87 and 0.95, p < 0.0001 for both). The 95% limits of agreement of inter-observer reproducibility improved from -168%, 154% to -17%, 25%. CONCLUSION The use of a motion correction method significantly improves the reproducibility of CTP estimates of tumor blood flow in lung cancer. KEY POINTS • Tumor blood flow estimates in advanced lung cancer show significant variability. • Motion correction improves the reproducibility of CT blood flow estimates in advanced lung cancer. • Reproducibility of blood flow measurements is critical to characterize lung tumor biology and the success of treatment in lung cancer.
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Vlahos I, Stefanidis K, Sheard S, Nair A, Sayer C, Moser J. Lung cancer screening: nodule identification and characterization. Transl Lung Cancer Res 2018; 7:288-303. [PMID: 30050767 DOI: 10.21037/tlcr.2018.05.02] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.
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Affiliation(s)
- Ioannis Vlahos
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
| | | | | | - Arjun Nair
- Guy's and St Thomas' Hospital NHS Foundation Trust, London, UK
| | - Charles Sayer
- Brighton and Sussex University Hospitals Trust, Haywards Heath, UK
| | - Joanne Moser
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
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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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Quantitative CT density histogram values and standardized uptake values of FDG-PET/CT with respiratory gating can distinguish solid adenocarcinomas from squamous cell carcinomas of the lung. Eur J Radiol 2018; 100:108-115. [DOI: 10.1016/j.ejrad.2018.01.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 01/14/2018] [Accepted: 01/18/2018] [Indexed: 01/22/2023]
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Li ZZ, Huang YL, Song HJ, Wang YJ, Huang Y. The value of 18F-FDG-PET/CT in the diagnosis of solitary pulmonary nodules: A meta-analysis. Medicine (Baltimore) 2018; 97:e0130. [PMID: 29561412 PMCID: PMC5895332 DOI: 10.1097/md.0000000000010130] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Solitary pulmonary nodules (SPNs) are common imaging findings. Many studies have indicated that F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG-PET/CT) is an accurate test for distinguishing benign and malignant SPNs. The aim of this study was to investigate the value of F-FDG-PET/CT in the diagnosis of malignant SPNs. METHODS We systematically searched the PubMed and Embase databases up to March 2017, and published data on sensitivity, specificity, and other measures of diagnostic accuracy of F-FDG-PET/CT in the diagnosis of malignant SPNs were meta-analyzed. Statistical analyses were undertaken using Meta-DiSc 1.4 software and Stata version 12.0. The measures of accuracy of F-FDG-PET/CT in the diagnosis of malignant SPNs were pooled using random-effects models. RESULTS A total of 20 publications reporting 21 studies were identified. Pooled results indicated that F-FDG-PET/CT showed a diagnostic sensitivity of 0.89 (95% confidence interval [CI], 0.87-0.91) and a specificity of 0.70 (95% CI, 0.66-0.73). The positive likelihood ratio was 3.33 (95% CI, 2.35-4.71) and the negative likelihood ratio was 0.18 (95% CI, 0.13-0.25). The diagnostic odds ratio was 22.43 (95% CI, 12.55-40.07). CONCLUSIONS F-FDG-PET/CT showed insufficient sensitivity and specificity for diagnosing malignant SPNs; it cannot replace the "gold standard" pathology by resection or percutaneous biopsy. Larger studies are required for further evaluation.
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Affiliation(s)
- Zhen-Zhen Li
- Health Management Center, West China Hospital of Sichuan University
| | - Ya-Liang Huang
- Department of Nephrology and Rheumatology, Affiliated Hospital/Clinical Medical College of Chengdu University
| | - Hong-Jun Song
- Outpatient Department, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - You-Juan Wang
- Health Management Center, West China Hospital of Sichuan University
| | - Yan Huang
- Health Management Center, West China Hospital of Sichuan University
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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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Feng F, Qiang F, Shen A, Shi D, Fu A, Li H, Zhang M, Xia G, Cao P. Dynamic contrast-enhanced MRI versus 18F-FDG PET/CT: Which is better in differentiation between malignant and benign solitary pulmonary nodules? Chin J Cancer Res 2018; 30:21-30. [PMID: 29545716 DOI: 10.21147/j.issn.1000-9604.2018.01.03] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Objective To prospectively compare the discriminative capacity of dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) with that of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in the differentiation of malignant and benign solitary pulmonary nodules (SPNs). Methods Forty-nine patients with SPNs were included in this prospective study. Thirty-two of the patients had malignant SPNs, while the other 17 had benign SPNs. All these patients underwent DCE-MRI and 18F-FDG PET/CT examinations. The quantitative MRI pharmacokinetic parameters, including the trans-endothelial transfer constant (Ktrans), redistribution rate constant (Kep), and fractional volume (Ve), were calculated using the Extended-Tofts Linear two-compartment model. The 18F-FDG PET/CT parameter, maximum standardized uptake value (SUVmax), was also measured. Spearman's correlations were calculated between the MRI pharmacokinetic parameters and the SUVmax of each SPN. These parameters were statistically compared between the malignant and benign nodules. Receiver operating characteristic (ROC) analyses were used to compare the diagnostic capability between the DCE-MRI and 18F-FDG PET/CT indexes. Results Positive correlations were found between Ktrans and SUVmax, and between Kep and SUVmax (P<0.05). There were significant differences between the malignant and benign nodules in terms of the Ktrans, Kep and SUVmax values (P<0.05). The areas under the ROC curve (AUC) of Ktrans, Kep and SUVmax between the malignant and benign nodules were 0.909, 0.838 and 0.759, respectively. The sensitivity and specificity in differentiating malignant from benign SPNs were 90.6% and 82.4% for Ktrans; 87.5% and 76.5% for Kep; and 75.0% and 70.6% for SUVmax, respectively. The sensitivity and specificity of Ktrans and Kep were higher than those of SUVmax, but there was no significant difference between them (P>0.05). Conclusions DCE-MRI can be used to differentiate between benign and malignant SPNs and has the advantage of being radiation free.
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Affiliation(s)
- Feng Feng
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Fulin Qiang
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Aijun Shen
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Donghui Shi
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Aiyan Fu
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Haiming Li
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Mingzhu Zhang
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Ganlin Xia
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
| | - Peng Cao
- Department of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China
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Dynamic Contrast-Enhanced Perfusion Area-Detector CT: Preliminary Comparison of Diagnostic Performance for N Stage Assessment With FDG PET/CT in Non-Small Cell Lung Cancer. AJR Am J Roentgenol 2017; 209:W253-W262. [PMID: 28929810 DOI: 10.2214/ajr.17.17959] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE The objective of our study was to directly compare the capability of dynamic first-pass contrast-enhanced (CE) perfusion area-detector CT (ADCT) and FDG PET/CT for differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with non-small cell lung carcinoma (NSCLC). SUBJECTS AND METHODS Seventy-seven consecutive patients, 45 men (mean age ± SD, 70.4 ± 5.9 years) and 32 women (71.2 ± 7.7 years), underwent dynamic first-pass CE-perfusion ADCT at two or three different positions for covering the entire thorax, FDG PET/CT, surgical treatment, and pathologic examination. From all ADCT data for each of the subjects, a whole-chest perfusion map was computationally generated using the dual- and single-input maximum slope and Patlak plot methods. For quantitative N stage assessment, perfusion parameters and the maximum standardized uptake value (SUVmax) for each lymph node were determined by measuring the relevant ROI. ROC curve analyses were performed for comparing the diagnostic capability of each of the methods on a per-node basis. N stages evaluated by each of the indexes were then statistically compared with the final pathologic diagnosis by means of chi-square and kappa statistics. RESULTS The area under the ROC curve (Az) values of systemic arterial perfusion (Az = 0.89), permeability surface (Az = 0.78), and SUVmax (Az = 0.85) were significantly larger than the Az values of total perfusion (Az = 0.70, p < 0.05) and distribution volume (Az = 0.55, p < 0.05). For each of the threshold values, agreement for systemic arterial perfusion calculated using the dual-input maximum slope model was substantial (κ = 0.70, p < 0.0001), and agreement for SUVmax was moderate (κ = 0.60, p < 0.0001). CONCLUSION Dynamic first-pass CE-perfusion ADCT is as useful as FDG PET/CT for the differentiation of metastatic from nonmetastatic lymph nodes and assessment of N stage in patients with NSCLC.
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Ohno Y, Kishida Y, Seki S, Yui M, Miyazaki M, Koyama H, Yoshikawa T. Amide proton transfer‐weighted imaging to differentiate malignant from benign pulmonary lesions: Comparison with diffusion‐weighted imaging and FDG‐PET/CT. J Magn Reson Imaging 2017; 47:1013-1021. [DOI: 10.1002/jmri.25832] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 07/20/2017] [Indexed: 02/04/2023] Open
Affiliation(s)
- Yoshiharu Ohno
- Division of Functional and Diagnostic Imaging ResearchDepartment of Radiology, Kobe University Graduate School of MedicineKobe Hyogo Japan
- Advanced Biomedical Imaging Research CenterKobe University Graduate School of MedicineKobe Hyogo Japan
| | - Yuji Kishida
- Division of RadiologyDepartment of Radiology, Kobe University Graduate School of MedicineKobe Hyogo Japan
| | - Shinichiro Seki
- Division of Functional and Diagnostic Imaging ResearchDepartment of Radiology, Kobe University Graduate School of MedicineKobe Hyogo Japan
- Advanced Biomedical Imaging Research CenterKobe University Graduate School of MedicineKobe Hyogo Japan
| | - Masao Yui
- Toshiba Medical Systems CorporationOtawara Tochigi Japan
| | - Mitsue Miyazaki
- Toshiba Medical Research Institute USAVernon Hills Illinois USA
- Department of RadiologyUniversity of California San DiegoSan Diego California USA
| | - Hisanobu Koyama
- Division of RadiologyDepartment of Radiology, Kobe University Graduate School of MedicineKobe Hyogo Japan
- Department of RadiologyOsaka Police HospitalOsaka Japan
| | - Takeshi Yoshikawa
- Division of Functional and Diagnostic Imaging ResearchDepartment of Radiology, Kobe University Graduate School of MedicineKobe Hyogo Japan
- Advanced Biomedical Imaging Research CenterKobe University Graduate School of MedicineKobe Hyogo Japan
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Wang Q, Zhang Z, Shan F, Shi Y, Xing W, Shi L, Zhang X. Intra-observer and inter-observer agreements for the measurement of dual-input whole tumor computed tomography perfusion in patients with lung cancer: Influences of the size and inner-air density of tumors. Thorac Cancer 2017; 8:427-435. [PMID: 28585375 PMCID: PMC5582470 DOI: 10.1111/1759-7714.12458] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 04/19/2017] [Accepted: 04/24/2017] [Indexed: 02/06/2023] Open
Abstract
Background This study was conducted to assess intra‐observer and inter‐observer agreements for the measurement of dual‐input whole tumor computed tomography perfusion (DCTP) in patients with lung cancer. Methods A total of 88 patients who had undergone DCTP, which had proved a diagnosis of primary lung cancer, were divided into two groups: (i) nodules (diameter ≤3 cm) and masses (diameter >3 cm) by size, and (ii) tumors with and without air density. Pulmonary flow, bronchial flow, and pulmonary index were measured in each group. Intra‐observer and inter‐observer agreements for measurement were assessed using intraclass correlation coefficient, within‐subject coefficient of variation, and Bland–Altman analysis. Results In all lung cancers, the reproducibility coefficient for intra‐observer agreement (range 26.1–38.3%) was superior to inter‐observer agreement (range 38.1–81.2%). Further analysis revealed lower agreements for nodules compared to masses. Additionally, inner‐air density reduced both agreements for lung cancer. Conclusion The intra‐observer agreement for measuring lung cancer DCTP was satisfied, while the inter‐observer agreement was limited. The effects of tumoral size and inner‐air density to agreements, especially between two observers, should be emphasized. In future, an automatic computer‐aided segment of perfusion value of the tumor should be developed.
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Affiliation(s)
- Qingle Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhiyong Zhang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China
| | - Fei Shan
- Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Yuxin Shi
- Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Wei Xing
- Department of Radiology, Third Affiliated Hospital of Suzhou University, Suzhou, China
| | - Liangrong Shi
- Department of Oncology, Third Affiliated Hospital of Suzhou University, Suzhou, China
| | - Xingwei Zhang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Medical Imaging, Shanghai, China.,Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China
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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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Dual-energy Computed Tomography for the Evaluation of Enhancement of Pulmonary Nodules≤3 cm in Size. J Thorac Imaging 2017; 32:189-197. [PMID: 28338536 DOI: 10.1097/rti.0000000000000263] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE The aim of the study was to compare the accuracies of 4 different methods of assessing pulmonary nodule enhancement to distinguish benign from malignant solid pulmonary nodules using nondynamic contrast-enhanced dual-energy computed tomography. MATERIALS AND METHODS Seventy-two patients (mean age, 62 y) underwent dual-energy chest computed tomography 3 minutes after intravenous contrast administration. Each of 118 pulmonary nodules (9±5.9 mm) were evaluated for enhancement by 4 methods: visual assessment, 3-dimensional automated postprocessing measurement tool, manually drawn region of interest with calculated iodine-related attenuation, and measurement of iodine concentration. The optimal cutoff for enhancement was defined as having the largest specificity among all cutoffs while maintaining 100% sensitivity. Accuracy of the methods was assessed with receiver operating characteristic curves. RESULTS Ninety-three of 118 pulmonary nodules were benign (79%). Visual assessment of enhancement had sensitivity and specificity of 100% and 44%, respectively. For the automated 3-dimensional measurement tool, 20 HU was found to be the optimal threshold for defining enhancement, resulting in a specificity of 71% and a sensitivity of 100%, as well as an area under the curve (AUC) of 0.87 (95% confidence interval [CI], 0.82-0.92). The AUC was 0.79 (95% CI, 0.73-0.85) for the measured enhancement using a manually drawn region of interest. When a threshold of 21 HU was used for defining enhancement, maximum specificity was obtained (56%) while maintaining 100% sensitivity. The AUC for measured iodine concentration was 0.79 (95% CI, 0.77-0.85). At a cutoff iodine concentration of 0.6 mg/mL, the sensitivity was 100% with a specificity of 57%. CONCLUSIONS Although use of automated postprocessing had the highest specificity while maintaining 100% sensitivity, there were only minor clinically relevant differences between measurement techniques given that no single technique misclassified a malignant nodule as nonenhancing.
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Ohno Y, Fujisawa Y, Koyama H, Kishida Y, Seki S, Sugihara N, Yoshikawa T. Dynamic contrast-enhanced perfusion area-detector CT assessed with various mathematical models: Its capability for therapeutic outcome prediction for non-small cell lung cancer patients with chemoradiotherapy as compared with that of FDG-PET/CT. Eur J Radiol 2016; 86:83-91. [PMID: 28027771 DOI: 10.1016/j.ejrad.2016.11.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 11/02/2016] [Accepted: 11/03/2016] [Indexed: 02/07/2023]
Abstract
PURPOSE To directly compare the capability of dynamic first-pass contrast-enhanced (CE-) perfusion area-detector CT (ADCT) and PET/CT for early prediction of treatment response, disease progression and overall survival of non-small cell carcinoma (NSCLC) patients treated with chemoradiotherapy. MATERIALS AND METHODS Fifty-three consecutive Stage IIIB NSCLC patients who had undergone PET/CT, dynamic first-pass CE-perfusion ADCT, chemoradiotherapy, and follow-up examination were enrolled in this study. They were divided into two groups: 1) complete or partial response (CR+PR) and 2) stable or progressive disease (SD+PD). Pulmonary arterial and systemic arterial perfusions and total perfusion were assessed at targeted lesions with the dual-input maximum slope method, permeability surface and distribution volume with the Patlak plot method, tumor perfusion with the single-input maximum slope method, and SUVmax, and results were averaged to determine final values for each patient. Next, step-wise regression analysis was used to determine which indices were the most useful for predicting therapeutic effect. Finally, overall survival of responders and non-responders assessed by using the indices that had a significant effect on prediction of therapeutic outcome was statistically compared. RESULTS The step-wise regression test showed that therapeutic effect (r2=0.63, p=0.01) was significantly affected by the following three factors in order of magnitude of impact: systemic arterial perfusion, total perfusion, and SUVmax. Mean overall survival showed a significant difference for total perfusion (p=0.003) and systemic arterial perfusion (p=0.04). CONCLUSION Dynamic first-pass CE-perfusion ADCT as well as PET/CT are useful for treatment response prediction in NSCLC patients treated with chemoradiotherapy.
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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.
| | | | - Hisanobu Koyama
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Yuji Kishida
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Shinichiro Seki
- Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, 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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Jiang B, Liu H, Zhou D. Diagnostic and clinical utility of dynamic contrast-enhanced MR imaging in indeterminate pulmonary nodules: a metaanalysis. Clin Imaging 2016; 40:1219-1225. [DOI: 10.1016/j.clinimag.2016.08.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 07/31/2016] [Accepted: 08/22/2016] [Indexed: 10/21/2022]
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