Study of T2 mapping in quantifying and discriminating uterine lesions under different magnetic field strengths: 1.5 T vs. 3.0 T

Abstract

Background MRI is the best imaging tool for the evaluation of uterine tumors, but conventional MRI diagnosis results rely on radiologists and contrast agents (if needed). As a new objective, reproducible and contrast-agent free quantification technique, T2 mapping has been applied to a number of diseases, but studies on the evaluation of uterine lesions and the influence of magnetic field strength are few. Therefore, the aim of this study was to systematically investigate and compare the performance of T2 mapping as a nonenhanced imaging tool in discriminating common uterine lesions between 1.5 T and 3.0 T MRI systems. Methods A total of 50 healthy subjects and 126 patients with suspected uterine lesions were enrolled in our study, and routine uterine MRI sequences with additional T2 mapping sequences were performed. T2 maps were calculated by monoexponential fitting using a custom code in MATLAB. T2 values of normal uterine structures in the healthy group and lesions (benign: adenomyosis, myoma, endometrial polyps; malignant: cervical cancer, endometrial carcinoma) in the patient group were collected. The differences in T2 values between 1.5 T MRI and 3.0 T MRI in any normal structure or lesion were compared. The comparison of T2 values between benign and malignant lesions was also performed under each magnetic field strength, and the diagnostic efficacies of the T2 value obtained through receiver operating characteristic (ROC) analysis were compared between 1.5 T and 3.0 T. Results The mean T2 value of any normal uterine structure or uterine lesion under 3.0 T MRI was significantly lower than that under 1.5 T MRI (p < 0.05). There were significant differences in T2 values between each lesion subgroup under both 1.5 T and 3.0 T MRI. Moreover, the T2 values of benign lesions (71.1 ± 22.0 ms at 1.5 T and 63.4 ± 19.1 ms at 3.0 T) were also significantly lower than those of malignant lesions (101.1 ± 4.5 ms at 1.5 T and 93.5 ± 5.1 ms at 3.0 T) under both field strengths. In the aspect of differentiating benign from malignant lesions, the area under the curve of the T2 value under 3.0 T (0.94) was significantly higher than that under 1.5 T MRI (0.90) (p = 0.02). Conclusion T2 mapping can be a potential tool for quantifying common uterine lesions, and it has better performance in distinguishing benign from malignant lesions under 3.0 T MRI.

MRI Quantitative Mapping Sequences of Renal Masses: Preliminary Results and its Potential Usefulness

“…Even if the image quality of the T2 mapping is always inferior to that of the T1m, it was always possible to record a value. For oncologic imaging, the potential usefulness of T2 mapping has been previously studied in a wide range of different malignancies such as gynecological tumors [12], brain tumors [13], prostate carcinoma [14], breast tumors [15] and lung tumors [16]. To our knowledge, only two papers have demonstrated on a 1.5T the potential usefulness of native T1 and T2 mapping for the distinction between lower and higher grades of ccRCC and suggested that it could be a helpful addition to multiparametric imaging.…”

Detection and Quantitative Assessment of Arthroscopically Proven Long Biceps Tendon Pathologies Using T2 Mapping

“…Finally, it should be mentioned that the T2 values analyzed in this study and the resulting diagnostic parameters are representative only of a field strength of 3.0 Tesla. Some studies comparing cardiac and uterine T2 mapping sequences at 1.5 and 3.0 Tesla found significant field strength-dependent differences in the mean T2 values [50,51]. While explicit studies on the cartilaginous tissue of tendinous structures are lacking, this effect might also be applicable to musculoskeletal imaging.…”

The Role of Native T1 and T2 Mapping Times in Identifying PD-L1 Expression and the Histological Subtype of NSCLCs

“…T2 mapping instead is able to calculate the T2 time, i.e., the transverse relaxation time of water protons, displaying it voxel-vice on a parametric map [ 9 ]. It has been applied mainly to the characterization of myocardium-related diseases [ 16 , 17 ], but also to many other clinical conditions, including prostate tumors [ 18 ], breast tumors [ 19 ], ovarian cancer [ 20 ], uterine lesions [ 21 ], and osteoarthritis [ 22 ].…”