Can MRI contribute to pulmonary nodule analysis?
J Magn Reson Imaging
; 49(7): e256-e264, 2019 Jun.
Article
en En
| MEDLINE
| ID: mdl-30575193
ABSTRACT
BACKGROUND:
There is no accurate method distinguishing different types of pulmonary nodules.PURPOSE:
To investigate whether multiparametric 3T MRI biomarkers can distinguish malignant from benign pulmonary nodules, differentiate different types of neoplasms, and compare MRI-derived measurements with values from commonly used noninvasive imaging modalities. STUDY TYPE Prospective.SUBJECTS:
Sixty-eight adults with pulmonary nodules undergoing resection. SEQUENCES Respiratory triggered diffusion-weighted imaging (DWI), periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) fat saturated T2 -weighted imaging, T1 -weighted 3D volumetric interpolated breath-hold examination (VIBE) using CAIPIRINHA (controlled aliasing in parallel imaging results in a higher acceleration). ASSESSMENT/STATISTICS Apparent diffusion coefficient (ADC), T1 , T2 , T1 and T2 normalized to muscle (T1 /M and T2 /M), and dynamic contrast enhancement (DCE) values were compared with histology to determine whether they could distinguish malignant from benign nodules and discern primary from secondary malignancies using logistic regression. Predictability of primary neoplasm types was assessed using two-sample t-tests. MRI values were compared with positron emission tomography / computed tomography (PET/CT) to examine if they correlated with standardized uptake value (SUV) or CT Hounsfield unit (HU). Intra- and interreader agreements were assessed using intraclass correlations.RESULTS:
Forty-nine of 74 nodules were malignant. There was a significant association between ADC and malignancy (odds ratio 4.47, P < 0.05). ADC ≥1.3 µm2 /ms predicted malignancy. ADC, T1 , and T2 together predicted malignancy (P = 0.003). No MRI parameter distinguished primary from metastatic neoplasms. T2 predicted PET positivity (P = 0.016). T2 and T1 /M correlated with SUV (P < 0.05). Of 18 PET-negative malignant nodules, 12 (67%) had an ADC ≥1.3 µm2 /ms. With the exception of T2 , all noncontrast MRI parameters distinguished adenocarcinomas from carcinoid tumors (P < 0.05). T1 , T2 , T1 /M, and T2 /M correlated with HU and therefore can predict nodule density. Combined with ADC, washout enhancement, arrival time (AT), peak enhancement intensity (PEI), Ktrans , Kep , Ve collectively were predictive of malignancy (P = 0.012). Combined washin, washout, time to peak (TTP), AT, and PEI values predicted malignancy (P = 0.043). There was good observer agreement for most noncontrast MRI biomarkers. DATACONCLUSION:
MRI can contribute to pulmonary nodule analysis. Multiparametric MRI might be better than individual MRI biomarkers in pulmonary nodule risk stratification. LEVEL OF EVIDENCE 1 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Imagen por Resonancia Magnética
/
Nódulo Pulmonar Solitario
/
Nódulos Pulmonares Múltiples
/
Neoplasias Pulmonares
Tipo de estudio:
Diagnostic_studies
/
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Adult
/
Aged
/
Aged80
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
J Magn Reson Imaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2019
Tipo del documento:
Article
País de afiliación:
Estados Unidos