Literature DB >> 26724665

Comparative evaluation of non-contrast CAIPIRINHA-VIBE 3T-MRI and multidetector CT for detection of pulmonary nodules: In vivo evaluation of diagnostic accuracy and image quality.

Patricia Dewes1, Claudia Frellesen1, Firas Al-Butmeh1, Moritz H Albrecht1, Jan-Erik Scholtz1, Sarah C Metzger1, Thomas Lehnert1, Thomas J Vogl1, Julian L Wichmann2.   

Abstract

PURPOSE: To evaluate the diagnostic accuracy, subjective image quality, and interobserver agreement of non-contrast Controlled Aliasing In Parallel Imaging Results In Higher Acceleration (CAIPIRINHA) volumetric interpolated breath-hold examination (VIBE) 3T magnetic resonance imaging (MRI) for the detection of pulmonary nodules with intra-individual comparison to computed tomography (CT).
MATERIALS AND METHODS: We evaluated 54 patients (27 male, 27 female; mean age, 60.8 ± 11.5 years) who prospectively underwent thoracic 3T-MRI using CAIPIRINHA-VIBE sequences and chest CT. Diagnostic accuracy for the detection of lung nodules on CAIPIRINHA-VIBE MRI by three independent observers were compared to the reference standard CT. Subjective image quality was rated using a 5-point grading scale. Diagnostic accuracy was calculated and interobserver agreement was assessed using intraclass correlation coefficient (ICC).
RESULTS: Sensitivity of 3T-MRI for the detection of pulmonary lesions compared to CT was 88.1% (95% confidence interval [CI]: 0.81-0.93) and specifity was 79.1% (95% CI: 0.50-0.95). Sensitivity for lesions <5mm was 77.2% (95% CI: 0.59-0.90) and for lesions from 5 to 10mm was 87.2% (95% CI: 0.76-0.94). Sensitivity for lesions >10mm was 100%. Observer ratings regarding subjective image quality were good to excellent for 3T-MRI (1.54) and CT (1.14) with almost perfect interobserver agreement for 3T-MRI and CT (ICC=0.83, 95% CI: 0.78-0.89; ICC=0.89, 95% CI: 0.85-0.94).
CONCLUSIONS: Non-contrast CAIPIRINHA-VIBE 3T-MRI allows for the reliable detection of pulmonary lesions with a diameter >5mm in comparison with chest CT with high diagnostic accuracy, subjective image quality, and interobserver agreement.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Computed tomography; Lung; Magnetic resonance imaging; Solitary pulmonary nodule

Mesh:

Year:  2015        PMID: 26724665     DOI: 10.1016/j.ejrad.2015.11.020

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  10 in total

1.  From low-dose to no-dose: thin-section magnetic resonance imaging for evaluation of pulmonary nodules.

Authors:  Tommaso D'Angelo; Thomas J Vogl; Julian L Wichmann
Journal:  J Thorac Dis       Date:  2018-04       Impact factor: 2.895

2.  Anatomic and Functional Evaluation of Central Lymphatics With Noninvasive Magnetic Resonance Lymphangiography.

Authors:  Eun Young Kim; Hye Sun Hwang; Ho Yun Lee; Jong Ho Cho; Hong Kwan Kim; Kyung Soo Lee; Young Mog Shim; Jaeil Zo
Journal:  Medicine (Baltimore)       Date:  2016-03       Impact factor: 1.889

Review 3.  Radiological Surveillance Screening in Asymptomatic Succinate Dehydrogenase Mutation Carriers.

Authors:  Nicola Tufton; Anju Sahdev; Scott A Akker
Journal:  J Endocr Soc       Date:  2017-06-06

Review 4.  Imaging features of extranodal involvement in paediatric Hodgkin lymphoma.

Authors:  Suzanne Spijkers; Annemieke S Littooij; Paul D Humphries; Marnix G E H Lam; Rutger A J Nievelstein
Journal:  Pediatr Radiol       Date:  2018-12-05

5.  Feasibility of pulmonary MRI for nodule detection in comparison to computed tomography.

Authors:  Nan Yu; Chuangbo Yang; Guangming Ma; Shan Dang; Zhanli Ren; Shaoyu Wang; Yong Yu
Journal:  BMC Med Imaging       Date:  2020-05-20       Impact factor: 1.930

6.  Free-breathing radial 3D fat-suppressed T1-weighted gradient echo (r-VIBE) sequence for assessment of pulmonary lesions: a prospective comparison of CT and MRI.

Authors:  Nan Yu; Haifeng Duan; Chuangbo Yang; Yong Yu; Shan Dang
Journal:  Cancer Imaging       Date:  2021-12-20       Impact factor: 3.909

Review 7.  MRI versus CT for the detection of pulmonary nodules: A meta-analysis.

Authors:  Hui Liu; Rihui Chen; Chao Tong; Xian-Wen Liang
Journal:  Medicine (Baltimore)       Date:  2021-10-22       Impact factor: 1.817

8.  Free-breathing 3D Stack of Stars GRE (StarVIBE) sequence for detecting pulmonary nodules in 18F-FDG PET/MRI.

Authors:  Nils Martin Bruckmann; Julian Kirchner; Janna Morawitz; Lale Umutlu; Wolfgang P Fendler; Ken Herrmann; Ann-Kathrin Bittner; Oliver Hoffmann; Tanja Fehm; Maike E Lindemann; Christian Buchbender; Gerald Antoch; Lino M Sawicki
Journal:  EJNMMI Phys       Date:  2022-02-07

9.  A Neural Network and Optimization Based Lung Cancer Detection System in CT Images.

Authors:  Chapala Venkatesh; Kadiyala Ramana; Siva Yamini Lakkisetty; Shahab S Band; Shweta Agarwal; Amir Mosavi
Journal:  Front Public Health       Date:  2022-06-07

10.  Applying Compressed Sensing Volumetric Interpolated Breath-Hold Examination and Spiral Ultrashort Echo Time Sequences for Lung Nodule Detection in MRI.

Authors:  Yu-Sen Huang; Emi Niisato; Mao-Yuan Marine Su; Thomas Benkert; Ning Chien; Pin-Yi Chiang; Wen-Jeng Lee; Jin-Shing Chen; Yeun-Chung Chang
Journal:  Diagnostics (Basel)       Date:  2021-12-31
  10 in total

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