Literature DB >> 26638164

Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region.

Natália Henz Concatto1,2, Guilherme Watte3, Edson Marchiori4, Klaus Irion5, José Carlos Felicetti6, José Jesus Camargo6, Bruno Hochhegger7.   

Abstract

OBJECTIVE: To estimate the diagnostic accuracy of signal intensity of the lesion-to-spinal cord ratio (LSR) and apparent diffusion coefficient (ADC) in diffusion-weighted (DW) magnetic resonance imaging of pulmonary nodules suspicious for lung cancer in granulomatous lung disease-endemic regions.
METHODS: Forty-nine patients with indeterminate solitary pulmonary nodules detected by chest computed tomography and histopathologically confirmed diagnoses were included in the study. DW images were analysed semiquantitatively by focusing regions of interest on the lesion and spinal cord at the same level (for LSR calculation). ADCs were estimated from ratios of the two image signal intensities. Ratios of T1 and T2 signal intensity between nodules and muscle were calculated for comparison.
RESULTS: Mean ADCs ± standard deviations for lung cancer and benign lesions were 0.9 ± 0.2 and 1.3 ± 0.2 × 10(-3) mm(2)/s, respectively. Mean LSRs were 1.4 ± 0.3 for lung cancer and 1 ± 0.1 for benign lesions. ADCs and LSRs differed significantly between malignant and benign lesions (P < 0.001). Mean T2 signal intensity ratios also differed significantly between benign and malignant lesions (0.8 ± 0.2 vs. 1.6 ± 0.2; P < 0.05).
CONCLUSIONS: DWI can help to differentiate malignant from benign lesions according to ADC and the LSR with good accuracy. KEY POINTS: • DW imaging can help differentiate malignant from benign pulmonary nodules. • ADC and LSR signal intensities had only small overlap between malignant and benign pulmonary nodules. • Mean T2 signal intensity ratios differed significantly between benign and malignant lesions.

Entities:  

Keywords:  Differentiation of malignant from benign lesions; Diffusion weighted; Granulomatous disease-endemic region; Magnetic resonance imaging; Pulmonary nodules

Mesh:

Year:  2015        PMID: 26638164     DOI: 10.1007/s00330-015-4125-1

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  15 in total

Review 1.  Magnetic resonance of the lung: a step forward in the study of lung disease.

Authors:  Bruno Hochhegger; Edson Marchiori; Klaus Irion; Arthur Soares Souza; Jackson Volkart; Adalberto S Rubin
Journal:  J Bras Pneumol       Date:  2012 Jan-Feb       Impact factor: 2.624

2.  Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society.

Authors:  Heber MacMahon; John H M Austin; Gordon Gamsu; Christian J Herold; James R Jett; David P Naidich; Edward F Patz; Stephen J Swensen
Journal:  Radiology       Date:  2005-11       Impact factor: 11.105

3.  Dynamic MRI, dynamic multidetector-row computed tomography (MDCT), and coregistered 2-[fluorine-18]-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/CT: comparative study of capability for management of pulmonary nodules.

Authors:  Yoshiharu Ohno; Hisanobu Koyama; Daisuke Takenaka; Munenobu Nogami; Yoshimasa Maniwa; Yoshihiro Nishimura; Chiho Ohbayashi; Kazuro Sugimura
Journal:  J Magn Reson Imaging       Date:  2008-06       Impact factor: 4.813

Review 4.  Magnetic resonance imaging for lung cancer.

Authors:  Hisanobu Koyama; Yoshiharu Ohno; Shinichiro Seki; Mizuho Nishio; Takeshi Yoshikawa; Sumiaki Matsumoto; Kazuro Sugimura
Journal:  J Thorac Imaging       Date:  2013-05       Impact factor: 3.000

Review 5.  A systematic review and meta-analysis of the accuracy of diffusion-weighted MRI in the detection of malignant pulmonary nodules and masses.

Authors:  Bin Li; Qiong Li; Cong Chen; Yu Guan; Shiyuan Liu
Journal:  Acad Radiol       Date:  2014-01       Impact factor: 3.173

Review 6.  Magnetic resonance imaging for lung cancer screen.

Authors:  Yi-Xiang J Wang; Gladys G Lo; Jing Yuan; Peder E Z Larson; Xiaoliang Zhang
Journal:  J Thorac Dis       Date:  2014-09       Impact factor: 2.895

Review 7.  Magnetic resonance imaging of the chest: current and new applications, with an emphasis on pulmonology.

Authors:  Marcel Koenigkam Santos; Jorge Elias; Fernando Marum Mauad; Valdair Francisco Muglia; Clóvis Simão Trad
Journal:  J Bras Pneumol       Date:  2011 Mar-Apr       Impact factor: 2.624

8.  Role of diffusion-weighted magnetic resonance imaging for predicting of tumor invasiveness for clinical stage IA non-small cell lung cancer.

Authors:  Naoki Kanauchi; Hiroyuki Oizumi; Tsuguo Honma; Hirohisa Kato; Makoto Endo; Jun Suzuki; Ken Fukaya; Mitsuaki Sadahiro
Journal:  Eur J Cardiothorac Surg       Date:  2009-02-11       Impact factor: 4.191

9.  Usefulness of diffusion-weighted MR imaging in the evaluation of pulmonary lesions.

Authors:  Haidong Liu; Ying Liu; Tielian Yu; Ning Ye
Journal:  Eur Radiol       Date:  2009-10-28       Impact factor: 5.315

Review 10.  Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis.

Authors:  Stephen A Deppen; Jeffrey D Blume; Clark D Kensinger; Ashley M Morgan; Melinda C Aldrich; Pierre P Massion; Ronald C Walker; Melissa L McPheeters; Joe B Putnam; Eric L Grogan
Journal:  JAMA       Date:  2014-09-24       Impact factor: 56.272

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  9 in total

1.  Letter to the editor re Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region.

Authors:  Guohua Shen; Anren Kuang
Journal:  Eur Radiol       Date:  2017-05-05       Impact factor: 5.315

2.  Reply to Letter to the Editor re: Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region.

Authors:  Natália Henz Concatto; Guilherme Watte; Edson Marchiori; Klaus Irion; José Carlos Felicetti; José Jesus Camargo; Bruno Hochhegger
Journal:  Eur Radiol       Date:  2017-05-05       Impact factor: 5.315

Review 3.  Advances in Imaging and Automated Quantification of Malignant Pulmonary Diseases: A State-of-the-Art Review.

Authors:  Bruno Hochhegger; Matheus Zanon; Stephan Altmayer; Gabriel S Pacini; Fernanda Balbinot; Martina Z Francisco; Ruhana Dalla Costa; Guilherme Watte; Marcel Koenigkam Santos; Marcelo C Barros; Diana Penha; Klaus Irion; Edson Marchiori
Journal:  Lung       Date:  2018-10-09       Impact factor: 2.584

4.  Evaluation of DWI and ADC Sequences' Diagnostic Values in Benign and Malignant Pulmonary Lesions.

Authors:  Masoud Mahdavi Rashed; Sirous Nekooei; Marzieh Nouri; Nahid Borji; Alireza Khadembashi
Journal:  Turk Thorac J       Date:  2020-11-01

5.  Enhancing the differentiation of pulmonary lymphoma and fungal pneumonia in hematological patients using texture analysis in 3-T MRI.

Authors:  Damon Kim; Thomas Elgeti; Tobias Penzkofer; Ingo G Steffen; Laura J Jensen; Stefan Schwartz; Bernd Hamm; Sebastian N Nagel
Journal:  Eur Radiol       Date:  2020-08-21       Impact factor: 5.315

6.  Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability.

Authors:  Alex Weller; Marianthi Vasiliki Papoutsaki; John C Waterton; Arturo Chiti; Sigrid Stroobants; Joost Kuijer; Matthew Blackledge; Veronica Morgan; Nandita M deSouza
Journal:  Eur Radiol       Date:  2017-04-10       Impact factor: 5.315

7.  Thoracic calcifications on magnetic resonance imaging: correlations with computed tomography.

Authors:  Juliana Fischman Zampieri; Gabriel Sartori Pacini; Matheus Zanon; Stephan Philip Leonhardt Altmayer; Guilherme Watte; Marcelo Barros; Evandra Durayski; Gustavo de Souza Portes Meirelles; Marcos Duarte Guimarães; Edson Marchiori; Arthur Soares Souza Junior; Bruno Hochhegger
Journal:  J Bras Pneumol       Date:  2019-07-29       Impact factor: 2.624

8.  Values of Apparent Diffusion Coefficient and Lesion-to-Spinal Cord Signal Intensity in Diagnosing Solitary Pulmonary Lesions: Turbo Spin-Echo versus Echo-Planar Imaging Diffusion-Weighted Imaging.

Authors:  Qiang Lei; Qi Wan; Lishan Liu; Jianfeng Hu; Wei Zuo; Jianneng Li; Guihua Jiang; Xinchun Li
Journal:  Biomed Res Int       Date:  2021-08-10       Impact factor: 3.411

9.  Differentiation of breast tuberculosis and breast cancer using diffusion-weighted, T2-weighted and dynamic contrast-enhanced magnetic resonance imaging.

Authors:  Dibuseng P Ramaema; Richard J Hift
Journal:  SA J Radiol       Date:  2018-10-25
  9 in total

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