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Ahmed HS, Gupta D, Aluru DR, Nellaiappan R, Dasan TA. Effect of information delivery techniques in reducing pre-procedural anxiety in computed tomography. Curr Probl Diagn Radiol 2024:S0363-0188(24)00118-X. [PMID: 39019712 DOI: 10.1067/j.cpradiol.2024.07.015] [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: 02/12/2024] [Revised: 05/08/2024] [Accepted: 07/08/2024] [Indexed: 07/19/2024]
Abstract
OBJECTIVES Patients undergoing medical procedures often experience heightened anxiety, which can affect their experience and overall health. The current study aimed at looking at a quality improvement initiative to compare written and audiovisual information delivery methods to reduce anxiety prior to Computed Tomography (CT). METHODS In this prospective interventional study, we assessed state and trait anxiety in patients scheduled for their first CT scan. Three PDSA cycles were carried out over six months, with each cycle lasting for two months each. The participants were divided into three groups, the baseline, written, and audiovisual intervention groups. Anxiety levels were assessed using the State-Trait Anxiety Inventory (STAI) questionnaire. State anxiety is a temporary emotional response, while trait anxiety reflects enduring personality characteristics. RESULTS The mean age of participants was 43.26 years (SD 15.07) in the baseline group, 39.9 years (SD 14.72) in the written group, and 48.59 years (SD 13.54) in the audiovisual group. For state anxiety, the baseline mean was 58.4 (SD 6.9), notably reduced to 43.2 (SD 5.5) with written intervention and to 38.6 (SD 7.7) with audiovisual intervention (p < 0.001). Trait anxiety scores remained relatively stable in all groups (p = 0.31). CONCLUSION Both written and audiovisual interventions successfully alleviate pre-imaging anxiety in patients undergoing CT scans. The findings underscore the superior efficacy of audiovisual materials in achieving a more substantial reduction in state anxiety compared to written information. These findings are particularly relevant in resource limited settings where simple interventions show significant improvements.
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Affiliation(s)
- H Shafeeq Ahmed
- Department of Radio-diagnosis, Bangalore Medical College and Research Institute, K.R Road, Bangalore, Karnataka 560002, India.
| | - Deeksha Gupta
- Department of Radio-diagnosis, Bangalore Medical College and Research Institute, K.R Road, Bangalore, Karnataka 560002, India
| | - Deepika Reddy Aluru
- Department of Radio-diagnosis, Bangalore Medical College and Research Institute, K.R Road, Bangalore, Karnataka 560002, India
| | - Rohit Nellaiappan
- Department of Radio-diagnosis, Bangalore Medical College and Research Institute, K.R Road, Bangalore, Karnataka 560002, India
| | - T Arul Dasan
- Department of Radio-diagnosis, Bangalore Medical College and Research Institute, K.R Road, Bangalore, Karnataka 560002, India
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de Frémont GM, Monaya A, Chassagnon G, Bouam S, Canniff E, Cohen P, Casadevall M, Mouthon L, Le Guern V, Revel MP. Lung fibrosis is uncommon in primary Sjögren's disease: A retrospective analysis of computed tomography features in 77 patients. Diagn Interv Imaging 2024; 105:183-190. [PMID: 38262872 DOI: 10.1016/j.diii.2024.01.003] [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] [Received: 12/04/2023] [Revised: 12/29/2023] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Abstract
PURPOSE The purpose of this study was to describe lung abnormalities observed on computed tomography (CT) in patients meeting the 2016 American College of Rheumatology/European League Against Rheumatism (EULAR) classification criteria for primary Sjögren's disease (pSD). MATERIALS AND METHODS All patients with pSD seen between January 2009 and December 2020 in the day care centre of our National Reference Center for rare systemic autoimmune diseases, who had at least one chest CT examination available for review and for whom the cumulative EULAR Sjögren's Syndrome Disease Activity Index (cumESSDAI) could be calculated were retrospectively evaluated. CT examinations were reviewed, together with clinical symptoms and pulmonary functional results. RESULTS Seventy-seven patients (73 women, four men) with a median age of 51 years at pSD diagnosis (age range: 17-79 years), a median follow-up time of 6 years and a median cumESSDAI of 7 were included. Sixty-six patients (86%) had anti-SSA antibodies. Thirty-three patients (33/77; 43%) had respiratory symptoms, without significant alteration in pulmonary function tests. Forty patients (40/77; 52%) had abnormal lung CT findings of whom almost half of them had no respiratory symptoms. Abnormalities on chest CT were more frequently observed in patients with anti-SSA positivity and a history of lymphoma. Air cysts (28/77; 36%) and mosaic perfusion (35/77; 35%) were the predominant abnormalities, whereas lung fibrosis was observed in five patients (5/77; 6%). CONCLUSION More than half of patients with pSD have abnormal CT findings, mainly air cysts and mosaic perfusion, indicative of small airways disease, whereas lung fibrosis is rare, observed in less than 10% of such patients.
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Affiliation(s)
- Grégoire Martin de Frémont
- Université Paris Cité, Faculté de Médecine, 75006 paris, France; Department of Internal Medicine, Centre de Référence des Maladies Auto-immunes et Systémiques Rares d'Ile de France, Hôpital Cochin, AP-HP, 75014 Paris, France
| | | | - Guillaume Chassagnon
- Université Paris Cité, Faculté de Médecine, 75006 paris, France; Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Samir Bouam
- Department of Medical Informatics, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Emma Canniff
- Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Pascal Cohen
- Department of Internal Medicine, Centre de Référence des Maladies Auto-immunes et Systémiques Rares d'Ile de France, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Marion Casadevall
- Department of Internal Medicine, Centre de Référence des Maladies Auto-immunes et Systémiques Rares d'Ile de France, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Luc Mouthon
- Université Paris Cité, Faculté de Médecine, 75006 paris, France; Department of Internal Medicine, Centre de Référence des Maladies Auto-immunes et Systémiques Rares d'Ile de France, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Véronique Le Guern
- Department of Internal Medicine, Centre de Référence des Maladies Auto-immunes et Systémiques Rares d'Ile de France, Hôpital Cochin, AP-HP, 75014 Paris, France
| | - Marie-Pierre Revel
- Université Paris Cité, Faculté de Médecine, 75006 paris, France; Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France.
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Nishiyama Y, Yabuuchi K, Nishiyama Y, Kambara Y, Ikushima Y, Enishi T. Crossed raised arm position improves the flow of contrast medium in torso contrast-enhanced computed Tomography. Radiography (Lond) 2024; 30:681-687. [PMID: 38364708 DOI: 10.1016/j.radi.2024.02.004] [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] [Received: 11/13/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/18/2024]
Abstract
INTRODUCTION This retrospective cohort study examined the effects of the crossed raised arm (CRA) position in contrast-enhanced computed tomography (CECT) on contrast medium influx and image quality relative to the conventional position. METHODS Contrast medium influx into the collateral veins on CECT images was evaluated in 92 participants. The CT values of the pulmonary artery, descending aorta, and spleen were obtained in both positions and compared. Anatomical changes in the diameters and area of the subclavian vein and costoclavicular distance were also analyzed. RESULTS Contras 27 and 6 patients in the conventional and CRA positions, respectively. The influx risk ratio in the CRA position versus that in the conventional position was 0.22 (95% confidence interval, 0.10-0.51). Elevations in the median CT value of the pulmonary artery, descending aorta, and spleen in the CRA position were 7.0% (p < .001), 7.4% (p < .001), and 9.8% (p < .001), respectively. Enlargements in the major and minor diameters of the subclavian vein, subclavian vein area, and costoclavicular distance in the CRA position versus those in the conventional position were 19.3% (p < .001), 28.1% (p < .001), 53.6%, and 30.0% (p < .001), respectively. CONCLUSION The CRA position effectively prevented contrast medium influx into the collateral veins due to SVS and increased CT values in the target organs in CECT. The diameters and area of the subclavian vein and costoclavicular distance were enlarged at the thoracic outlet, which improved the flow of the contrast medium into the targeted organs. IMPLICATIONS FOR PRACTICE The CRA position can contribute to obtaining better CECT images during common clinical assessments at no additional cost.
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Affiliation(s)
- Y Nishiyama
- Department of Radiology, Tokushima Municipal Hospital 2-34 Kitajosanjima, Tokushima 7700812, Japan.
| | - K Yabuuchi
- Department of Radiology, Tokushima Municipal Hospital 2-34 Kitajosanjima, Tokushima 7700812, Japan.
| | - Y Nishiyama
- Graduate School of Biomedical Sciences, Tokushima University 3-18-15 Kuramoto, Tokushima 7708503, Japan.
| | - Y Kambara
- Department of Radiology, Tokushima Municipal Hospital 2-34 Kitajosanjima, Tokushima 7700812, Japan.
| | - Y Ikushima
- Department of Radiology, Tokushima Municipal Hospital 2-34 Kitajosanjima, Tokushima 7700812, Japan.
| | - T Enishi
- Department of Rehabilitation Medicine, Tokushima Municipal Hospital 2-34 Kitajosanjima, Tokushima 7700812, Japan.
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Liu CC, Cheng YF, Ke PC, Chen YL, Lin CM, Wang BY. Prediction of Surgical Outcome by Tumor Volume Doubling Time via Stereo Imaging Software in Early Non-Small Cell Lung Cancer. Cancers (Basel) 2023; 15:3952. [PMID: 37568768 PMCID: PMC10417538 DOI: 10.3390/cancers15153952] [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: 06/25/2023] [Revised: 07/28/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Volume doubling time (VDT) has been proven to be a powerful predictor of lung cancer progression. In non-small cell lung cancer patients receiving sublobar resection, the discussion of correlation between VDT and surgery was absent. We proposed to investigate the surgical outcomes according to VDT. METHODS We retrospectively studied 96 cases post sublobar resection from 2012 to 2018, collecting two chest CT scans preoperatively of each case and calculating the VDT. The receiver operating characteristic curve was constructed to identify the optimal cut-off point of VDTs as 133 days. We divided patients into two groups: VDT < 133 days and VDT ≥ 133 days. Univariable and multivariable analyses were performed for comparative purposes. RESULTS Univariable and multivariable analyses revealed that the consolidation and tumor diameter ratio was the factor of overall survival (OS), and VDT was the only factor of disease-free survival (DFS). The five year OS rates of patients with VDTs ≥ 133 days and VDTs < 133 days, respectively, were 89.9% and 71.9%, and the five year DFS rates were 95.9% and 61.5%. CONCLUSION As VDT serves as a powerful prognostic predictor and provides an essential role in planning surgical procedures, the evaluation of VDT preoperatively is highly suggested.
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Affiliation(s)
- Chia-Chi Liu
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Ya-Fu Cheng
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Pei-Cing Ke
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Yi-Ling Chen
- Surgery Clinical Research Center, Changhua Christian Hospital, Changhua 50006, Taiwan;
| | - Ching-Min Lin
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
| | - Bing-Yen Wang
- Division of Thoracic Surgery, Department of Surgery, Changhua Christian Hospital, Changhua 50006, Taiwan; (C.-C.L.); (Y.-F.C.); (P.-C.K.); (C.-M.L.)
- Surgery Clinical Research Center, Changhua Christian Hospital, Changhua 50006, Taiwan;
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 40227, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80756, Taiwan
- Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung 40227, Taiwan
- Center for General Education, Ming Dao University, Changhua 52345, Taiwan
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Ko JJ, Banerji S, Blais N, Brade A, Clelland C, Schellenberg D, Snow S, Wheatley-Price P, Yuan R, Melosky B. Follow-Up Imaging Guidelines for Patients with Stage III Unresectable NSCLC: Recommendations Based on the PACIFIC Trial. Curr Oncol 2023; 30:3817-3828. [PMID: 37185402 PMCID: PMC10137068 DOI: 10.3390/curroncol30040289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/13/2023] [Accepted: 03/25/2023] [Indexed: 04/03/2023] Open
Abstract
The PACIFIC trial showed a survival benefit with durvalumab through five years in stage III unresectable non-small cell lung cancer (NSCLC). However, optimal use of imaging to detect disease progression remains unclearly defined for this population. An expert working group convened to consider available evidence and clinical experience and develop recommendations for follow-up imaging after concurrent chemotherapy and radiation therapy (CRT). Voting on agreement was conducted anonymously via online survey. Follow-up imaging was recommended for all suitable patients after CRT completion regardless of whether durvalumab is received. Imaging should occur every 3 months in Year 1, at least every 6 months in Year 2, and at least every 12 months in Years 3–5. Contrast computed tomography was preferred; routine brain imaging was not recommended for asymptomatic patients. The medical oncologist should follow-up during Year 1 of durvalumab therapy, with radiation oncologist involvement if pneumonitis is suspected; medical and radiation oncologists can subsequently alternate follow-up. Some patients can transition to the family physician/community primary care team at the end of Year 2. In Years 1–5, patients should receive information regarding smoking cessation, comorbidity management, vaccinations, and general follow-up care. These recommendations provide guidance on follow-up imaging for patients with stage III unresectable NSCLC whether or not they receive durvalumab consolidation therapy.
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Albers J, Wagner WL, Fiedler MO, Rothermel A, Wünnemann F, Di Lillo F, Dreossi D, Sodini N, Baratella E, Confalonieri M, Arfelli F, Kalenka A, Lotz J, Biederer J, Wielpütz MO, Kauczor HU, Alves F, Tromba G, Dullin C. High resolution propagation-based lung imaging at clinically relevant X-ray dose levels. Sci Rep 2023; 13:4788. [PMID: 36959233 PMCID: PMC10036329 DOI: 10.1038/s41598-023-30870-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 03/02/2023] [Indexed: 03/25/2023] Open
Abstract
Absorption-based clinical computed tomography (CT) is the current imaging method of choice in the diagnosis of lung diseases. Many pulmonary diseases are affecting microscopic structures of the lung, such as terminal bronchi, alveolar spaces, sublobular blood vessels or the pulmonary interstitial tissue. As spatial resolution in CT is limited by the clinically acceptable applied X-ray dose, a comprehensive diagnosis of conditions such as interstitial lung disease, idiopathic pulmonary fibrosis or the characterization of small pulmonary nodules is limited and may require additional validation by invasive lung biopsies. Propagation-based imaging (PBI) is a phase sensitive X-ray imaging technique capable of reaching high spatial resolutions at relatively low applied radiation dose levels. In this publication, we present technical refinements of PBI for the characterization of different artificial lung pathologies, mimicking clinically relevant patterns in ventilated fresh porcine lungs in a human-scale chest phantom. The combination of a very large propagation distance of 10.7 m and a photon counting detector with [Formula: see text] pixel size enabled high resolution PBI CT with significantly improved dose efficiency, measured by thermoluminescence detectors. Image quality was directly compared with state-of-the-art clinical CT. PBI with increased propagation distance was found to provide improved image quality at the same or even lower X-ray dose levels than clinical CT. By combining PBI with iodine k-edge subtraction imaging we further demonstrate that, the high quality of the calculated iodine concentration maps might be a potential tool for the analysis of lung perfusion in great detail. Our results indicate PBI to be of great value for accurate diagnosis of lung disease in patients as it allows to depict pathological lesions non-invasively at high resolution in 3D. This will especially benefit patients at high risk of complications from invasive lung biopsies such as in the setting of suspected idiopathic pulmonary fibrosis (IPF).
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Affiliation(s)
- Jonas Albers
- Department for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany
- Biological X-ray imaging, European Molecular Biology Laboratory, Hamburg Unit c/o DESY, Hamburg, Germany
| | - Willi L Wagner
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
| | - Mascha O Fiedler
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
- Department of Anaesthesiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Anne Rothermel
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
| | - Felix Wünnemann
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
| | | | - Diego Dreossi
- Elettra-Sincrotrone Trieste S.C.p.A., Trieste, Italy
| | - Nicola Sodini
- Elettra-Sincrotrone Trieste S.C.p.A., Trieste, Italy
| | - Elisa Baratella
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | | | - Fulvia Arfelli
- Department of Physics, University of Trieste and INFN, Trieste, Italy
| | - Armin Kalenka
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
- Department of Anaesthesiology and Intensive Care Medicine, District Hospital Bergstrasse, Heppenheim, Germany
- Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Joachim Lotz
- Department for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany
| | - Jürgen Biederer
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
- Faculty of Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
- Faculty of Medicine, University of Latvia, Riga, Latvia
| | - Mark O Wielpütz
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany
| | - Frauke Alves
- Department for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany
- Department for Haematology and Medical Oncology, University Medical Center Goettingen, Goettingen, Germany
- Translational Molecular Imaging, Max-Plank-Institute for Multidisciplinary Sciences, Goettingen, Germany
| | | | - Christian Dullin
- Department for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany.
- Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.
- Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), University Heidelberg, Heidelberg, Germany.
- Translational Molecular Imaging, Max-Plank-Institute for Multidisciplinary Sciences, Goettingen, Germany.
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Katz SI, Straus CM, Roshkovan L, Blyth KG, Frauenfelder T, Gill RR, Lalezari F, Erasmus J, Nowak AK, Gerbaudo VH, Francis RJ, Armato SG. Considerations for Imaging of Malignant Pleural Mesothelioma: A Consensus Statement from the International Mesothelioma Interest Group. J Thorac Oncol 2023; 18:278-298. [PMID: 36549385 DOI: 10.1016/j.jtho.2022.11.018] [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: 08/02/2022] [Revised: 11/13/2022] [Accepted: 11/17/2022] [Indexed: 12/24/2022]
Abstract
Malignant pleural mesothelioma (MPM) is an aggressive primary malignancy of the pleura that presents unique radiologic challenges with regard to accurate and reproducible assessment of disease extent at staging and follow-up imaging. By optimizing and harmonizing technical approaches to imaging MPM, the best quality imaging can be achieved for individual patient care, clinical trials, and imaging research. This consensus statement represents agreement on harmonized, standard practices for routine multimodality imaging of MPM, including radiography, computed tomography, 18F-2-deoxy-D-glucose positron emission tomography, and magnetic resonance imaging, by an international panel of experts in the field of pleural imaging assembled by the International Mesothelioma Interest Group. In addition, modality-specific technical considerations and future directions are discussed. A bulleted summary of all technical recommendations is provided.
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Affiliation(s)
- Sharyn I Katz
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
| | - Christopher M Straus
- Department of Radiology, University of Chicago Pritzker School of Medicine, Chicago, Illinois
| | - Leonid Roshkovan
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Kevin G Blyth
- Institute of Cancer Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Thomas Frauenfelder
- Institute for Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Ritu R Gill
- Department of Radiology, Beth Israel Lahey Health, Harvard Medical School, Boston, Massachusetts
| | - Ferry Lalezari
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jeremy Erasmus
- Department of Radiology, MD Anderson Cancer Center, Houston, Texas
| | - Anna K Nowak
- Medical School, University of Western Australia, Perth, Australia
| | - Victor H Gerbaudo
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Roslyn J Francis
- Medical School, University of Western Australia, Perth, Australia; Department of Nuclear Medicine, Sir Charles Gairdner Hospital, Perth, Australia
| | - Samuel G Armato
- Department of Radiology, University of Chicago Pritzker School of Medicine, Chicago, Illinois
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Chang S, Jung JI, Beck KS. Low Tube Voltage Chest Computed Tomography With Enhancement Using Low-Concentration Iodinated Contrast Media: Comparison of 240 mg/mL Versus 300 mg/mL Iodinated Contrast Media. Can Assoc Radiol J 2023; 74:127-136. [PMID: 35593132 DOI: 10.1177/08465371221102631] [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: 01/11/2023] Open
Abstract
Purpose: To evaluate the image quality of low voltage chest computed tomography with enhancement (CECT) using low-concentration-iodine contrast media (LCCM). Method: From 9 December to 19 December 2019, three different protocols were used for 263 patients undergoing chest CECT. Chest CECT was done using routine (300 mgI/ml contrast media with 100 kVp) protocol (group 1), LCCM (240 mgI/ml contrast media)-100 kVp protocol (group 2) and LCCM-80 kVp protocol (group 3) in 91, 97 and 75 patients, respectively. The overall diagnostic acceptability, anatomical depiction, noise and contrast-related artifacts were assessed. Additionally, the mean attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and figure of merit (FOM) in the aorta and the main pulmonary trunk were measured. Results: The overall diagnostic acceptability scores were not significantly different between groups 1 and 2 (P = .261); group 3 demonstrated significantly lower overall diagnostic acceptability score compared with group 1 (P = .011) or group 2 (P < .001). However, in CECT with iterative reconstruction (IR), the overall diagnostic acceptability scores did not show significant difference among 3 groups. Group 3 showed significantly lower effective radiation dose compared with group 1 (2.33 vs 1.22 mSv, P < .001) or group 2 (2.28 vs .22 mSv, P < .001). Conclusions: In 100 kVp chest CECT, the image quality of using 240 mg/mL iodinated contrast media is comparable to that using 300 mg/mL iodine contrast media, regardless of application of IR; with IR, chest CECT using 80 kVp and 240 mg/mL iodinated contrast media results in acceptable image quality and lower radiation dose.
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Affiliation(s)
- Suyon Chang
- Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jung Im Jung
- Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kyongmin S Beck
- Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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Mahdavi MMB, Arabfard M, Rafati M, Ghanei M. A Computer-based Analysis for Identification and Quantification of Small Airway Disease in Lung Computed Tomography Images: A Comprehensive Review for Radiologists. J Thorac Imaging 2023; 38:W1-W18. [PMID: 36206107 DOI: 10.1097/rti.0000000000000683] [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: 12/14/2022]
Abstract
Computed tomography (CT) imaging is being increasingly used in clinical practice for detailed characterization of lung diseases. Respiratory diseases involve various components of the lung, including the small airways. Evaluation of small airway disease on CT images is challenging as the airways cannot be visualized directly by a CT scanner. Small airway disease can manifest as pulmonary air trapping (AT). Although AT may be sometimes seen as mosaic attenuation on expiratory CT images, it is difficult to identify diffuse AT visually. Computer technology advances over the past decades have provided methods for objective quantification of small airway disease on CT images. Quantitative CT (QCT) methods are being rapidly developed to quantify underlying lung diseases with greater precision than subjective visual assessment of CT images. A growing body of evidence suggests that QCT methods can be practical tools in the clinical setting to identify and quantify abnormal regions of the lung accurately and reproducibly. This review aimed to describe the available methods for the identification and quantification of small airway disease on CT images and to discuss the challenges of implementing QCT metrics in clinical care for patients with small airway disease.
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Affiliation(s)
- Mohammad Mehdi Baradaran Mahdavi
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran
| | - Masoud Arabfard
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran
| | - Mehravar Rafati
- Department of Medical Physics and Radiology, Faculty of paramedicine, Kashan University of Medical Sciences, Kashan, Iran
| | - Mostafa Ghanei
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran
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10
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Ali HA, Mohammad SA. Pediatric COVID-19: Correlations between Clinical and Imaging Perspectives. Pulm Med 2023; 2023:4159651. [PMID: 37179531 PMCID: PMC10171977 DOI: 10.1155/2023/4159651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 03/18/2023] [Accepted: 04/15/2023] [Indexed: 05/15/2023] Open
Abstract
Background Although SARS-CoV-2 infection primarily affects adults, the increasing emergence of infected pediatric patients has been recently reported. However, there is a paucity of data regarding the value of imaging in relation to the clinical severity of this pandemic emergency. Objectives To demonstrate the relationships between clinical and radiological COVID-19 findings and to determine the most effective standardized pediatric clinical and imaging strategies predicting the disease severity. Patients and Methods. This observational study enrolled eighty pediatric patients with confirmed COVID-19 infection. The studied patients were categorized according to the disease severity and the presence of comorbidities. Patients' clinical findings, chest X-ray, and CT imaging results were analyzed. Patients' evaluations using several clinical and radiological severity scores were recorded. The relations between clinical and radiological severities were examined. Results Significant associations were found between severe-to-critical illness and abnormal radiological findings (p = 0.009). In addition, chest X-ray score, chest CT severity score, and rapid evaluation of anamnesis, PO2, imaging disease, and dyspnea-COVID (RAPID-COVID) score were significantly higher among patients with severe infection (p < 0.001, <0.001, and 0.001) and those with comorbidities (p = 0.005, 0.002, and <0.001). Conclusions Chest imaging of pediatric patients with COVID-19 infection may be of value during the evaluation of severe cases of infected pediatric patients and in those with underlying comorbid conditions, especially during the early stage of infection. Moreover, the combined use of specific clinical and radiological COVID-19 scores are likely to be a successful measure of the extent of disease severity.
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Affiliation(s)
- Heba A. Ali
- Department of Pediatrics, Pulmonology Division, Faculty of Medicine, Ain Shams University Children's Hospital, Cairo, Egypt
| | - Shaimaa A. Mohammad
- Department of Diagnostic and Interventional Radiology and Molecular Imaging, Faculty of Medicine, Ain Shams University Hospital, Cairo, Egypt
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Choi H, Park EA, Ahn C, Kim JH, Lee W, Jeong B. Performance of 1-mm non-gated low-dose chest computed tomography using deep learning-based noise reduction for coronary artery calcium scoring. Eur Radiol 2022; 33:3839-3847. [PMID: 36520181 DOI: 10.1007/s00330-022-09300-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 08/31/2022] [Accepted: 11/13/2022] [Indexed: 12/23/2022]
Abstract
OBJECTIVE To investigate performance of 1-mm, sharp kernel, low-dose chest computed tomography (LDCT) for coronary artery calcium scoring (CACS) using deep learning (DL)-based denoising technique. METHODS This retrospective, intra-individual comparative study consisted of four image datasets of 131 participants who underwent LDCT and calcium CT on the same day between January and February 2020; 1-mm LDCT with DL, 1-mm LDCT with iterative reconstruction (IR), 3-mm LDCT, and calcium CT. CACS from calcium CT were considered as reference and CACS were categorized as 0, 1-10, 11-100, 101-400, and > 400. We compared CACS from LDCTs with that from calcium CT. RESULTS Mean CACS was 104.8 ± 249.1 and proportion of positive CACS was 45% (59/131). CACS from LDCT images tended to be underestimated than those from calcium CT: 1-mm LDCT with DL (93.5 ± 249.6, p = 0.002), 1-mm LDCT with IR (94.7 ± 249.9, p < 0.001), and 3-mm LDCT (90.3 ± 245.3, p = 0.004). All LDCT datasets showed excellent agreement with calcium CT: intraclass correlation coefficient (ICC) = 0.961 (95% confidence interval (CI), 0.945-0.972) for DL, 0.969 (95% CI, 0.956-0.978) for IR, and 0.952 (95% CI, 0.932-0.966) for 3-mm LDCT; weighted kappa for CACS classification, 0.930 (95% CI, 0.893-0.966) for 1-mm LDCT with DL, 0.908 (95% CI, 0.866-0.950) for 1-mm LDCT with IR, and 0.846 (95% CI, 0.780-0.912) for 3-mm LDCT. The accuracy of CACS classification of 1-mm LDCT with DL (90%) tended to be better than 1-mm LDCT with IR (87%) and 3-mm LDCT (84.7%) (p = 0.10). CONCLUSION DL-based noise reduction algorithm can offer reliable calcium scores in 1-mm LDCT reconstructed with sharp kernel. KEY POINTS • Deep learning (DL)-based noise reduction enables calcium scoring at 1-mm, sharp kernel reconstructed low-dose chest CT (LDCT). • Both iterative reconstruction and DL-based noise reduction underestimated calcium score, but agreement were excellent with those from calcium CT. • Accuracy of categorical classification of calcium scoring tended to be highest in 1-mm LDCT with DL compared to 1-mm LDCT with IR and 3-mm LDCT (90%, 87%, and 84.7%, p = 0.10).
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Affiliation(s)
- Hyewon Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102 Heukseok-ro, Dongjak-gu, Seoul, 06973, Republic of Korea
| | - Eun-Ah Park
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
| | - Chulkyun Ahn
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea
- ClariPi Research, Seoul, 03088, Republic of Korea
| | - Jong-Hyo Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea
- ClariPi Research, Seoul, 03088, Republic of Korea
- Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Suwon, 16229, Republic of Korea
| | - Whal Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Baren Jeong
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
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12
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Tamam N, Sulieman A, Omer H, Toufig H, Alsaadi M, Salah H, Mattar EH, Khandaker MU, Bradley D. Assessment of breast dose and cancer risk for young females during CT chest and abdomen examinations. Appl Radiat Isot 2022; 190:110452. [DOI: 10.1016/j.apradiso.2022.110452] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 08/01/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022]
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13
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Muacevic A, Adler JR, Asad Ullah M, Azmat U, Shahwar DE, Hyder SMS. Anatomical Variations in Pulmonary Fissures on Computed Tomography (CT). Cureus 2022; 14:e32062. [PMID: 36600863 PMCID: PMC9803252 DOI: 10.7759/cureus.32062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2022] [Indexed: 12/05/2022] Open
Abstract
Objective To determine the frequency of anatomical variations in lung fissures using computed tomography (CT) at a tertiary care hospital in Karachi, Pakistan. Methods A cross-sectional study was conducted in the department of Radiology and Imaging Services at Memon Medical Institute Hospital, Karachi, between November 2021 to April 2022. Patients aged between 15 to 92 years with a completed high-resolution CT scan chest were included. Subjects with no significant structural lung disease that could alter the anatomy were analyzed. Baseline data was gathered using a pre-designed questionnaire, and two qualified radiologists assessed the CT chest images. Results A total of 382 subjects participated in this study, out of which 57.1% were males whilst 42.9% were females. The right horizontal fissure was absent in 10 (2.6%) cases. Accessory fissures were seen in 7.33%. The most common fissural variation was azygos fissure (14; 3.7%), followed by superior accessory fissure (six; 1.6%), inferior accessory fissures (four; 1%), and left horizontal fissure (four; 1%). These variations were more common in males. The significant difference was only seen in the superior accessory fissures with respect to gender (P-value<0.05). Conclusion This study showed the presence of accessory fissures in 7.33% of patients, the most common being the azygos fissure, irrespective of gender. The absence of normal right horizontal fissures was observed in 2.6% of cases.
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Keek SA, Kayan E, Chatterjee A, Belderbos JSA, Bootsma G, van den Borne B, Dingemans AMC, Gietema HA, Groen HJM, Herder J, Pitz C, Praag J, De Ruysscher D, Schoenmaekers J, Smit HJM, Stigt J, Westenend M, Zeng H, Woodruff HC, Lambin P, Hendriks L. Investigation of the added value of CT-based radiomics in predicting the development of brain metastases in patients with radically treated stage III NSCLC. Ther Adv Med Oncol 2022; 14:17588359221116605. [PMID: 36032350 PMCID: PMC9403451 DOI: 10.1177/17588359221116605] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 07/12/2022] [Indexed: 12/04/2022] Open
Abstract
Introduction: Despite radical intent therapy for patients with stage III non-small-cell
lung cancer (NSCLC), cumulative incidence of brain metastases (BM) reaches
30%. Current risk stratification methods fail to accurately identify these
patients. As radiomics features have been shown to have predictive value,
this study aims to develop a model combining clinical risk factors with
radiomics features for BM development in patients with radically treated
stage III NSCLC. Methods: Retrospective analysis of two prospective multicentre studies. Inclusion
criteria: adequately staged [18F-fluorodeoxyglucose positron
emission tomography-computed tomography (18-FDG-PET-CT), contrast-enhanced
chest CT, contrast-enhanced brain magnetic resonance imaging/CT] and
radically treated stage III NSCLC, exclusion criteria: second primary within
2 years of NSCLC diagnosis and prior prophylactic cranial irradiation.
Primary endpoint was BM development any time during follow-up (FU). CT-based
radiomics features (N = 530) were extracted from the
primary lung tumour on 18-FDG-PET-CT images, and a list of clinical features
(N = 8) was collected. Univariate feature selection
based on the area under the curve (AUC) of the receiver operating
characteristic was performed to identify relevant features. Generalized
linear models were trained using the selected features, and multivariate
predictive performance was assessed through the AUC. Results: In total, 219 patients were eligible for analysis. Median FU was 59.4 months
for the training cohort and 67.3 months for the validation cohort; 21 (15%)
and 17 (22%) patients developed BM in the training and validation cohort,
respectively. Two relevant clinical features (age and adenocarcinoma
histology) and four relevant radiomics features were identified as
predictive. The clinical model yielded the highest AUC value of 0.71 (95%
CI: 0.58–0.84), better than radiomics or a combination of clinical
parameters and radiomics (both an AUC of 0.62, 95% CIs of 0.47–076 and
0.48–0.76, respectively). Conclusion: CT-based radiomics features of primary NSCLC in the current setup could not
improve on a model based on clinical predictors (age and adenocarcinoma
histology) of BM development in radically treated stage III NSCLC
patients.
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Affiliation(s)
- Simon A Keek
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Esma Kayan
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Avishek Chatterjee
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - José S A Belderbos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Gerben Bootsma
- Department of Pulmonary Diseases, Zuyderland Hospital, Heerlen, The Netherlands
| | - Ben van den Borne
- Department of Pulmonary Diseases, Catharina Hospital, Eindhoven, The Netherlands
| | | | - Hester A Gietema
- Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Harry J M Groen
- Department of Pulmonary Diseases, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Judith Herder
- Department of Pulmonary Diseases, Meander Medical Center, Amersfoort, The Netherlands
| | - Cordula Pitz
- Department of Pulmonary Diseases, Laurentius Hospital, Roermond, The Netherlands
| | - John Praag
- Department of Radiotherapy, Erasmus MC, Rotterdam, The Netherlands
| | - Dirk De Ruysscher
- Department of Radiation Oncology (Maastro), GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Janna Schoenmaekers
- Department of Pulmonary Diseases, GROW - School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Hans J M Smit
- Department of Pulmonary Diseases, Rijnstate, Arnhem, The Netherlands
| | - Jos Stigt
- Department of Pulmonary Diseases, Isala Hospital, Zwolle, The Netherlands
| | - Marcel Westenend
- Department of Pulmonary Diseases, VieCuri, Venlo, The Netherlands
| | - Haiyan Zeng
- Department of Radiation Oncology (Maastro), GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Henry C Woodruff
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Philippe Lambin
- The D-Lab, Department of Precision Medicine, GROW - School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Lizza Hendriks
- Department of Pulmonary Diseases, GROW - School for Oncology and Reproduction, Maastricht University Medical Centre+, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands
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Taylor N, Renfrew H. Does Dose Matter? Ionising radiation exposure of the veterinary patient from Computed Tomography: A discussion. Top Companion Anim Med 2022; 51:100697. [PMID: 36002103 DOI: 10.1016/j.tcam.2022.100697] [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: 01/22/2022] [Revised: 07/23/2022] [Accepted: 07/27/2022] [Indexed: 11/27/2022]
Abstract
Advanced imaging techniques such as Computed Tomography (CT) are commonplace in human medicine and increasingly, are being utilised by the veterinary profession as scanners become more available and affordable. The benefit of CT imaging is the provision of detailed cross-sectional imaging and 3D reconstruction, but this incurs higher doses of ionising radiation to the patient. This paper reviews risks and effects associated with ionising radiation, making comparisons to human models, and a hypothetical scenario is discussed using the human risk model for age at time of exposure and increased lifetime risk of cancer with a dog to human years formula. Various issues are considered with respect to dose reduction, training, equipment and the reported 'greater need for guidance and the establishment of best practice' which may lead to future guidance from the International Commission on Radiological Protection (ICRP).
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Affiliation(s)
- Nicholas Taylor
- Imaging Department, Eastcott Veterinary Referrals, Edison Park, Hindle Way, Swindon, Wiltshire, SN33FR, UK.
| | - Helen Renfrew
- Imaging Department, Eastcott Veterinary Referrals, Edison Park, Hindle Way, Swindon, Wiltshire, SN33FR, UK
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Henning MK, Aaløkken TM, Johansen S. Contrast medium protocols in routine chest CT: a survey study. Acta Radiol 2022; 63:351-359. [PMID: 33648351 DOI: 10.1177/0284185121997111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Administration of contrast medium (CM) is an important image quality factor in computed tomography (CT) of the chest. There is no clear evidence or guidelines on CM strategies for chest CT, thus a consensus approach is needed. PURPOSE To survey the potential impact on differences in chest CT protocols, with emphasis on strategies for the administration of CM. MATERIAL AND METHODS A total of 170 respondents were included in this survey, which used two different approaches: (i) an online survey was sent to the members of the European Society of Thoracic Imaging (ESTI); and (ii) an email requesting a copy of their CT protocol was sent to all hospitals in Norway, and university hospitals in Sweden and Denmark. The survey focused on factors affecting CM protocols and enhancement in chest CT. RESULTS The overall response rate was 24% (n = 170): 76% of the respondents used a CM concentration of ≥350 mgI/mL; 52% of the respondents used a fixed CM volume strategy. Fixed strategies for injection rate and delay were also the most common approach, practiced by 73% and 57% of the respondents, respectively. The fixed delay was in the range of 20-90 s. Of the respondents, 56% used flexible tube potential strategies (kV). CONCLUSION The chest CT protocols and CM administration strategies employed by the respondents vary widely, affecting the image quality. The results of this study underline the need for further research and consensus guidelines related to chest CT.
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Affiliation(s)
- Mette Karen Henning
- Faculty of Health Sciences, Department of Life Sciences and Health, Oslo Metropolitan University, Oslo, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Trond Mogens Aaløkken
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Faulty of Medicine, University of Oslo, Oslo, Norway
| | - Safora Johansen
- Faculty of Health Sciences, Department of Life Sciences and Health, Oslo Metropolitan University, Oslo, Norway
- Department of Cancer Treatment, Oslo University Hospital, Oslo, Norway
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Botwe BO, Schandorf C, Inkoom S, Faanu A, Mensah YB, Antwi WK. Towards the establishment of national imaging practice guidelines: A preliminary study of the basic computed tomography imaging protocols in Ghana. J Med Imaging Radiat Sci 2022; 53:226-241. [DOI: 10.1016/j.jmir.2022.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/14/2022] [Accepted: 03/04/2022] [Indexed: 10/18/2022]
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Inter-Observer Agreement between Low-Dose and Standard-Dose CT with Soft and Sharp Convolution Kernels in COVID-19 Pneumonia. J Clin Med 2022; 11:jcm11030669. [PMID: 35160121 PMCID: PMC8836391 DOI: 10.3390/jcm11030669] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 01/21/2022] [Accepted: 01/24/2022] [Indexed: 12/29/2022] Open
Abstract
Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia). Two consecutive scans with CT and LDCT were performed in a single visit. Reading was performed by ten radiologists with 3–25 years’ experience. The study included 230 patients, and statistical analysis showed LDCT with a sharp kernel as the most reliable protocol (percentage agreement 74.35 ± 43.77%), but its advantage was marginal. There was no significant correlation between radiologists’ experience and average percentage agreement for all four evaluated protocols. Regarding the radiation exposure, CTDIvol was 3.6 ± 0.64 times lower for LDCT. In conclusion, CT and LDCT with soft and sharp reconstructions are equally reliable for COVID-19 reporting using the “CT 0-4” scale. The LDCT protocol allows for a significant decrease in radiation exposure but may be restricted by body mass index.
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Alshammari QT, Alrashidi O, Almutairi W, Alshammari E, Alshammari MT, CG SK, Salih M, Sulieman A, Gameraddin M, Malik BA, Alyahyawi AR. Coronary Artery Calcium Score: Current Efficacy of Cardiac CT in Patients at Hail Region, Saudi Arabia. INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH AND ALLIED SCIENCES 2022. [DOI: 10.51847/inqvelwihv] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Bae SB, Kang EJ, Choo KS, Lee J, Kim SH, Lim KJ, Kwon H. Aortic Arch Variants and Anomalies: Embryology, Imaging Findings, and Clinical Considerations. J Cardiovasc Imaging 2022; 30:231-262. [PMID: 36280266 PMCID: PMC9592245 DOI: 10.4250/jcvi.2022.0058] [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: 05/06/2022] [Revised: 07/15/2022] [Accepted: 07/17/2022] [Indexed: 11/22/2022] Open
Abstract
There is a wide spectrum of congenital anomalies or variations of the aortic arch, ranging from non-symptomatic variations that are mostly detected incidentally to clinically symptomatic variations that cause severe respiratory distress or esophageal compression. Some of these may be accompanied by other congenital heart diseases or chromosomal anomalies. The widespread use of multidetector computed tomography (CT) in clinical practice has resulted in incidental detection of several variations of the aortic arch in adults. Thus, radiologists and clinicians should be aware of the classification of aortic arch anomalies and carefully look for imaging features associated with a high risk of clinical symptoms. Understanding the embryological development of the aortic arch aids in the classification of various subtypes of aortic arch anomalies and variants. For accurate diagnosis and precise evaluation of aortic arch anomalies, cross-sectional imaging modalities, such as multidetector CT or magnetic resonance imaging, play an important role by providing three-dimensional reconstructed images. In this review, we describe the embryological development of the thoracic aorta and discuss variations and anomalies of the aortic arch along with their clinical implications.
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Affiliation(s)
- Sang Bin Bae
- Department of Radiology, College of Medicine, Dong-A University, Busan, Korea
| | - Eun-Ju Kang
- Department of Radiology, College of Medicine, Dong-A University, Busan, Korea
| | - Ki Seok Choo
- Department of Radiology, Pusan National University School of Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea
| | - Jongmin Lee
- Department of Radiology, Kyungpook National University School of Medicine, Daegu, Korea
| | - Sang Hyeon Kim
- Department of Radiology, College of Medicine, Dong-A University, Busan, Korea
| | - Kyoung Jae Lim
- Department of Radiology, College of Medicine, Dong-A University, Busan, Korea
| | - Heejin Kwon
- Department of Radiology, College of Medicine, Dong-A University, Busan, Korea
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Croft M, Lim W, Lavender N, Gormly K. Optimising CT-chest protocols and the added value of venous-phase contrast timing; Observational case-control. J Med Imaging Radiat Oncol 2021; 66:768-775. [PMID: 34799981 DOI: 10.1111/1754-9485.13350] [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: 09/17/2021] [Accepted: 11/03/2021] [Indexed: 12/25/2022]
Abstract
INTRODUCTION To optimize CT chest protocol by comparing venous contrast timing with arterial timing for contrast opacification in vessels, qualitative image quality and radiologists' satisfaction and diagnostic confidence in assessing for potential nodal, pleural and pulmonary disease in general oncology outpatients. METHOD Matched case-control study performed following CT protocol update. 92 patients with a range of primary malignancies with 2 CT chests in a 2-year period, one with an arterial phase protocol and the second in the 60 second venous phase, were included. Contrast attenuation in aorta, pulmonary artery and liver were measured. Subjective measurements assessed perivenous artefact, confidence in nodal pleural and pulmonary assessment and presence of pulmonary emboli. Statistical analysis was performed using paired and unpaired t-tests. RESULTS Venous-phase CT demonstrated more consistent enhancement of the vessels, with higher attenuation of the nodes, pulmonary and pleural lesions. There was a significant reduction in perivenous beam hardening artefact on venous-phase CT (P < 0.001). Diagnostic confidence was significantly higher for nodal assessment and pleural abnormality visibility (P < 0.001) and pleural assessment (P < 0.05). There was no significant difference in pulmonary mass visibility. There was adequate enhancement to diagnose significant pulmonary emboli (PE) with 4 incidental PEs detected on the venous phase, extending to segmental vessels. CONCLUSION Venous-phase CT chest performs better than arterial-phase on all fronts, without compromising assessment of incidental pulmonary emboli. When intravenous contrast is indicated in a routine chest CT (excluding a CT-angiogram), the default timing should be a venous or 60s phase.
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Affiliation(s)
- Michael Croft
- Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - WanYin Lim
- Royal Adelaide Hospital, Adelaide, South Australia, Australia.,Dr Jones and Partners, Eastwood, South Australia, Australia
| | - Nusha Lavender
- Dr Jones and Partners, Eastwood, South Australia, Australia
| | - Kirsten Gormly
- Dr Jones and Partners, Eastwood, South Australia, Australia.,The University of Adelaide, North Terrace, Adelaide, South Australia, Australia
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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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Afshar P, Heidarian S, Enshaei N, Naderkhani F, Rafiee MJ, Oikonomou A, Fard FB, Samimi K, Plataniotis KN, Mohammadi A. COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning. Sci Data 2021; 8:121. [PMID: 33927208 PMCID: PMC8085195 DOI: 10.1038/s41597-021-00900-3] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 03/18/2021] [Indexed: 12/12/2022] Open
Abstract
Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 2 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not controlled in a timely fashion, can rapidly incapacitate healthcare systems. The current standard diagnosis method, the Reverse Transcription Polymerase Chain Reaction (RT- PCR), is time consuming, and subject to low sensitivity. Chest Radiograph (CXR), the first imaging modality to be used, is readily available and gives immediate results. However, it has notoriously lower sensitivity than Computed Tomography (CT), which can be used efficiently to complement other diagnostic methods. This paper introduces a new COVID-19 CT scan dataset, referred to as COVID-CT-MD, consisting of not only COVID-19 cases, but also healthy and participants infected by Community Acquired Pneumonia (CAP). COVID-CT-MD dataset, which is accompanied with lobe-level, slice-level and patient-level labels, has the potential to facilitate the COVID-19 research, in particular COVID-CT-MD can assist in development of advanced Machine Learning (ML) and Deep Neural Network (DNN) based solutions.
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Affiliation(s)
- Parnian Afshar
- Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada
| | - Shahin Heidarian
- Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada
| | - Nastaran Enshaei
- Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada
| | - Farnoosh Naderkhani
- Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada
| | - Moezedin Javad Rafiee
- Department of Medicine and Diagnostic Radiology, McGill University Health Center-Research Institute, Montreal, QC, Canada
| | - Anastasia Oikonomou
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | | | - Kaveh Samimi
- Department of Radiology, Iran university of medical science, Tehran, Iran
| | | | - Arash Mohammadi
- Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada.
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Singla S, Gong M, Riley C, Sciurba F, Batmanghelich K. Improving clinical disease subtyping and future events prediction through a chest CT-based deep learning approach. Med Phys 2021; 48:1168-1181. [PMID: 33340116 PMCID: PMC7965349 DOI: 10.1002/mp.14673] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 10/30/2020] [Accepted: 12/09/2020] [Indexed: 12/20/2022] Open
Abstract
PURPOSE To develop and evaluate a deep learning (DL) approach to extract rich information from high-resolution computed tomography (HRCT) of patients with chronic obstructive pulmonary disease (COPD). METHODS We develop a DL-based model to learn a compact representation of a subject, which is predictive of COPD physiologic severity and other outcomes. Our DL model learned: (a) to extract informative regional image features from HRCT; (b) to adaptively weight these features and form an aggregate patient representation; and finally, (c) to predict several COPD outcomes. The adaptive weights correspond to the regional lung contribution to the disease. We evaluate the model on 10 300 participants from the COPDGene cohort. RESULTS Our model was strongly predictive of spirometric obstruction ( r 2 = 0.67) and grouped 65.4% of subjects correctly and 89.1% within one stage of their GOLD severity stage. Our model achieved an accuracy of 41.7% and 52.8% in stratifying the population-based on centrilobular (5-grade) and paraseptal (3-grade) emphysema severity score, respectively. For predicting future exacerbation, combining subjects' representations from our model with their past exacerbation histories achieved an accuracy of 80.8% (area under the ROC curve of 0.73). For all-cause mortality, in Cox regression analysis, we outperformed the BODE index improving the concordance metric (ours: 0.61 vs BODE: 0.56). CONCLUSIONS Our model independently predicted spirometric obstruction, emphysema severity, exacerbation risk, and mortality from CT imaging alone. This method has potential applicability in both research and clinical practice.
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Affiliation(s)
- Sumedha Singla
- School of Computing and InformationUniversity of PittsburghPittsburghPA15213USA
| | - Mingming Gong
- School of Mathematics and StatisticsThe University of MelbourneParkvilleVICAustralia
| | - Craig Riley
- Chester County HospitalUniversity of Pennsylvania Health SystemWest ChesterPAUSA
| | - Frank Sciurba
- Department of MedicineUniversity of Pittsburgh Medical CenterPittsburghPA15213USA
| | - Kayhan Batmanghelich
- Department of Biomedical InformaticsUniversity of PittsburghPittsburghPA15213USA
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25
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高 琦, 朱 曼, 李 丹, 边 兆, 马 建. [CT image quality assessment based on prior information of pre-restored images]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2021; 41:230-237. [PMID: 33624596 PMCID: PMC7905247 DOI: 10.12122/j.issn.1673-4254.2021.02.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Indexed: 06/12/2023]
Abstract
OBJECTIVE We propose a CT IQA strategy based on the prior information of pre-restored images (PR-IQA) to improve the performance of IQA models. OBJECTIVE We propose a CNN-based no-reference CT IQA strategy using the prior information of image quality features in the image restoration algorithm, which is combined with the original distorted image information into the two CNNs through the pre-restored image and the residual image. Multi-information fusion was used to improve the feature extraction ability and prediction performance of CNN. We built a CT IQA dataset based on spiral CT data published by Mayo Clinic. The performance of PR- IQA was evaluated by calculating the quantitative metrics and statistical tests. The influence of different hyperparameter settings for PR-IQA was analyzed. We then compared PR-IQA with the BASELINE model based on the single CNN to evaluate the original distorted image without reference image and other eight IQA algorithms. OBJECTIVE The comparative experiment results showed that the PR-IQA model based on the prior information of 3 different image restoration algorithms (BF, NLM and BM3D) was better than all the tested IQA algorithms. Compared with the BASELINE method, the proposed method showed significantly improved performance, and the mean PLCC was increased by 12.56% and SROCC by 19.95%, and RMSE was decreased by 22.77%. OBJECTIVE The proposed PR-IQA method can make full use of the prior information of the image restoration algorithm to effectively predict the quality of CT images.
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Affiliation(s)
- 琦 高
- />南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515School of Biomedical Engineering, Southern Medical University; Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - 曼曼 朱
- />南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515School of Biomedical Engineering, Southern Medical University; Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - 丹阳 李
- />南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515School of Biomedical Engineering, Southern Medical University; Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - 兆英 边
- />南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515School of Biomedical Engineering, Southern Medical University; Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
| | - 建华 马
- />南方医科大学生物医学工程学院//广州市医用放射成像与检测技术重点实验室,广东 广州 510515School of Biomedical Engineering, Southern Medical University; Guangzhou Key Laboratory of Medical Radiation Imaging and Detection Technology, Guangzhou 510515, China
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26
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Shen C, Tsai MY, Chen L, Li S, Nguyen D, Wang J, Jiang SB, Jia X. On the robustness of deep learning-based lung-nodule classification for CT images with respect to image noise. Phys Med Biol 2020; 65:245037. [PMID: 33152716 PMCID: PMC7870572 DOI: 10.1088/1361-6560/abc812] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Robustness is an important aspect when evaluating a method of medical image analysis. In this study, we investigated the robustness of a deep learning (DL)-based lung-nodule classification model for CT images with respect to noise perturbations. A deep neural network (DNN) was established to classify 3D CT images of lung nodules into malignant or benign groups. The established DNN was able to predict malignancy rate of lung nodules based on CT images, achieving the area under the curve of 0.91 for the testing dataset in a tenfold cross validation as compared to radiologists' prediction. We then evaluated its robustness against noise perturbations. We added to the input CT images noise signals generated randomly or via an optimization scheme using a realistic noise model based on a noise power spectrum for a given mAs level, and monitored the DNN's output. The results showed that the CT noise was able to affect the prediction results of the established DNN model. With random noise perturbations at 100 mAs, DNN's predictions for 11.2% of training data and 17.4% of testing data were successfully altered by at least once. The percentage increased to 23.4% and 34.3%, respectively, for optimization-based perturbations. We further evaluated robustness of models with different architectures, parameters, number of output labels, etc, and robustness concern was found in these models to different degrees. To improve model robustness, we empirically proposed an adaptive training scheme. It fine-tuned the DNN model by including perturbations in the training dataset that successfully altered the DNN's perturbations. The adaptive scheme was repeatedly performed to gradually improve DNN's robustness. The numbers of perturbations at 100 mAs affecting DNN's predictions were reduced to 10.8% for training and 21.1% for testing by the adaptive training scheme after two iterations. Our study illustrated that robustness may potentially be a concern for an exemplary DL-based lung-nodule classification model for CT images, indicating the needs for evaluating and ensuring model robustness when developing similar models. The proposed adaptive training scheme may be able to improve model robustness.
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Affiliation(s)
- Chenyang Shen
- innovative Technology Of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75235
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Min-Yu Tsai
- innovative Technology Of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75235
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
- Department of Computer Science & Information Engineering, National Taiwan University, Taipei, Taiwan
| | - Liyuan Chen
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Shulong Li
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Dan Nguyen
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Jing Wang
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Steve B. Jiang
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
| | - Xun Jia
- innovative Technology Of Radiotherapy Computations and Hardware (iTORCH) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75235
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, 75235
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27
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Chiba Y, Yamasaki K, Ikegami H, Yatera K. Pseudoaneurysm after total arch replacement mimicking malignant lymphadenopathy. Respirol Case Rep 2020; 8:e00645. [PMID: 32832089 PMCID: PMC7438812 DOI: 10.1002/rcr2.645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/31/2020] [Accepted: 08/04/2020] [Indexed: 12/05/2022] Open
Abstract
Pseudoaneurysm should be considered in the differential diagnosis when the computed tomography (CT) findings show a mediastinal mass in patients with a history of cardiovascular surgery even if such surgery occurred over two decades previously.
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Affiliation(s)
- Yosuke Chiba
- Department of Respiratory MedicineUniversity of Occupational and Environmental Health, JapanKitakyushuJapan
| | - Kei Yamasaki
- Department of Respiratory MedicineUniversity of Occupational and Environmental Health, JapanKitakyushuJapan
| | - Hiroaki Ikegami
- Department of Respiratory MedicineUniversity of Occupational and Environmental Health, JapanKitakyushuJapan
| | - Kazuhiro Yatera
- Department of Respiratory MedicineUniversity of Occupational and Environmental Health, JapanKitakyushuJapan
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