Abstract

T1 mapping can potentially quantitatively assess the intrinsic properties of tumors. B1 correction can reduce the magnetic field inhomogeneity. To assess the repeatability and reproducibility of B1 -corrected T1 mapping for lung cancer and the ability to identify pathological types. Prospective reproducibility study. Sixty lung cancer patients (22 with emphysema) with a total of 60 lesions (adenocarcinoma [n=23], squamous cell carcinoma [n=19], and small-cell lung cancer [SCLC] [n=18]). A 3 T/B1 -corrected 3D variable flip angle T1 mapping and free-breathing diffusion-weighted imaging. Intraobserver, interobserver, and test-retest reproducibility of minimum, maximum, mean, and SD of lung tumor T1 values were assessed. The correlation between mean T1 and apparent diffusion coefficient (ADC) and differences between different histological types of lung cancer were evaluated. Intraclass correlation coefficients (ICCs), within-subject coefficients of variation (WCVs), Bland-Altman plots, Pearson's correlation coefficient (r), and analysis of variance (ANOVA). A P value <0.05 was considered to be statistically significant. No significant differences were found in minimum, maximum, mean, and SD T1 values for repeated measurements (intraobserver and interobserver) and repeated examinations (P=0.103-0.979). All parameters showed good intraobserver, interobserver and test-retest reproducibility (ICC, 0.780-0.978), except the maximum T1 value (ICC, 0.645-0.922). The mean T1 exhibited the best reproducibility and repeatability, with an average difference <6% for repeated measurements, <8% for repeated scans in lung cancer patients, and<10% for repeated scans in those with emphysema. The mean T1 correlated moderately with ADC (r=-0.580, -0.516, and -0.511 for observers A, B, and C). Both mean T1 and mean ADC were significantly different in SCLC patients compared with those in adenocarcinoma and squamous cell carcinoma patients. The mean T1 from B1 -corrected T1 mapping is a repeatable parameter with the potential to identify histological types of lung cancer and thus may be a promising imaging biomarker for characterizing lung cancer. 1 TECHNICAL EFFICACY: Stage 2.

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