OBJECTIVE: To evaluate the diagnostic accuracy of dynamic contrast-enhanced (DCE) magnetic resonance (MR) and diffusion-weighted imaging (DWI) sequences for defining benignity or malignancy of solitary pulmonary lesions (SPL). METHODS: First, 54 consecutive patients with SPL, clinically staged (CT and PET or integrated PET-CT) as N0M0, were included in this prospective study. An additional 3-Tesla MR examination including DCE and DWI was performed 1 day before the surgical procedure. Histopathology of the surgical specimen served as the standard of reference. Subsequently, this functional method of SPL characterisation was validated with a second cohort of 54 patients. RESULTS: In the feasibility group, 11 benign and 43 malignant SPL were included. Using the combination of conventional MR sequences with visual interpretation of DCE-MR curves resulted in a sensitivity, specificity and accuracy of 100%, 55% and 91%, respectively. These results can be improved by DWI (with a cut-off value of 1.52 × 10(-3) mm(2)/s for ADChigh) leading to a sensitivity, specificity and accuracy of 98%, 82% and 94%, respectively. In the validation group these results were confirmed. CONCLUSION: Visual DCE-MR-based curve interpretation can be used for initial differentiation of benign from malignant SPL, while additional quantitative DWI-based interpretation can further improve the specificity. KEY POINTS: • Magnetic resonance imaging is increasingly being used to help differentiate lung lesions. • Solitary pulmonary lesions (SPL) are accurately characterised by combining DCE-MRI and DWI. • Visual DCE-MRI assessment facilitates the diagnostic throughput in patients with SPL. • DWI provides additional information in inconclusive DCE-MRI (type B pattern).
OBJECTIVE: To evaluate the diagnostic accuracy of dynamic contrast-enhanced (DCE) magnetic resonance (MR) and diffusion-weighted imaging (DWI) sequences for defining benignity or malignancy of solitary pulmonary lesions (SPL). METHODS: First, 54 consecutive patients with SPL, clinically staged (CT and PET or integrated PET-CT) as N0M0, were included in this prospective study. An additional 3-Tesla MR examination including DCE and DWI was performed 1 day before the surgical procedure. Histopathology of the surgical specimen served as the standard of reference. Subsequently, this functional method of SPL characterisation was validated with a second cohort of 54 patients. RESULTS: In the feasibility group, 11 benign and 43 malignant SPL were included. Using the combination of conventional MR sequences with visual interpretation of DCE-MR curves resulted in a sensitivity, specificity and accuracy of 100%, 55% and 91%, respectively. These results can be improved by DWI (with a cut-off value of 1.52 × 10(-3) mm(2)/s for ADChigh) leading to a sensitivity, specificity and accuracy of 98%, 82% and 94%, respectively. In the validation group these results were confirmed. CONCLUSION: Visual DCE-MR-based curve interpretation can be used for initial differentiation of benign from malignant SPL, while additional quantitative DWI-based interpretation can further improve the specificity. KEY POINTS: • Magnetic resonance imaging is increasingly being used to help differentiate lung lesions. • Solitary pulmonary lesions (SPL) are accurately characterised by combining DCE-MRI and DWI. • Visual DCE-MRI assessment facilitates the diagnostic throughput in patients with SPL. • DWI provides additional information in inconclusive DCE-MRI (type B pattern).
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
Authors: Stanley E K Loh; Donald D F Wu; Sudhakar K Venkatesh; Cheng Kang Ong; Eugene Liu; Kar Yin Seto; Anil Gopinathan; Lenny K A Tan Journal: Ann Acad Med Singapore Date: 2013-06 Impact factor: 2.473
Authors: Shin Matsuoka; Andetta R Hunsaker; Ritu R Gill; Francine L Jacobson; Yoshiharu Ohno; Samuel Patz; Hiroto Hatabu Journal: Magn Reson Imaging Clin N Am Date: 2008-05 Impact factor: 2.266
Authors: Ning Chang; Xiao-Hui Wang; Long-Biao Cui; Hong Yin; Tao Jiang; Fu-Lin Chen; Li-Peng Liu; Jian Zhang Journal: Transl Lung Cancer Res Date: 2019-12
Authors: Selina Tsim; Catherine A Humphreys; Gordon W Cowell; David B Stobo; Colin Noble; Rosemary Woodward; Caroline A Kelly; Laura Alexander; John E Foster; Craig Dick; Kevin G Blyth Journal: Lung Cancer Date: 2018-02-03 Impact factor: 5.705