Can MRI contribute to pulmonary nodule analysis?

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), K^trans, K_ep, V_e 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. Data Conclusion: 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.