To investigate whether quantitative T2 mapping is complementary to [18F]FDG PET in epileptogenic zone detection, thus improving the lateralization accuracy for drug-resistant mesial temporal lobe epilepsy (MTLE) using hybrid PET/MR.We acquired routine structural MRI, T2-weighted FLAIR, whole brain T2 mapping, and [18F]FDG PET in 46 MTLE patients and healthy controls on a hybrid PET/MR scanner, followed with computing voxel-based z-score maps of patients in reference to healthy controls. Asymmetry indexes of the hippocampus were calculated for each imaging modality, which then enter logistic regression models as univariate or multivariate for lateralization. Stereoelectroencephalography (SEEG) recordings and clinical decisions were collected as gold standard.Routine structural MRI and T2w-FLAIR lateralized 47.8% (22/46) of MTLE patients, and FDG PET lateralized 84.8% (39/46). T2 mapping combined with [18F]FDG PET improved the lateralization accuracy by correctly lateralizing 95.6% (44/46) of MTLE patients. The asymmetry indexes of hippocampal T2 relaxometry and PET exhibit complementary tendency in detecting individual laterality, especially for MR-negative patients. In the quantitative analysis of z-score maps, the ipsilateral hippocampus had significantly lower SUVR (LTLE, p < 0.001; RTLE, p < 0.001) and higher T2 value (LTLE, p < 0.001; RTLE, p = 0.001) compared to the contralateral hippocampus. In logistic regression models, PET/T2 combination resulted in the highest AUC of 0.943 in predicting lateralization for MR-negative patients, followed by PET (AUC = 0.857) and T2 (AUC = 0.843).The combination of quantitative T2 mapping and [18F]FDG PET could improve lateralization for temporal lobe epilepsy.• Quantitative T2 mapping and18F-FDG PET are complementary in the characterization of hippocampal alterations of MR-negative temporal lobe epilepsy patients. • The combination of quantitative T2 and18F-FDG PET obtained from hybrid PET/MR could improve lateralization for temporal lobe epilepsy.
The image quality of single-shot echo-planar imaging (ssEPI) is affected by static magnetic field B0 inhomogeneity induced distortion. Despite previous correction methods, the B0 inhomogeneity near air/tissue interface remains a challenge. In this article, we introduce an approach to improve B0 estimation near air/tissue interface based on a high resolution structural image, then further investigate whether it would improve the correction of ssEPI based diffusion tensor imaging by analytical point spread function (PSF) method with the proposed B0 estimation. Phantom and in vivo brain experiments both demonstrated that B0 accuracy was improved near the air/tissue interface compared to the low resolution B0, and PSF corrections were superior to field map corrections, especially on signal intensity restoration.
Single-shot echoplanar imaging (EPI) sequence is a commonly-used readout scheme for functional magnetic resonance imaging (fMRI). It acquires signal in a short period of time with loud acoustic noise, which could cause discomfort for patients and even pose risk for sensitive populations, as well as confound auditory fMRI studies. Though a variety of attempts have been made toward quiet EPI scans, none has considered both the noise level and the timbre. In this study, we investigated the effect of varying echo spacing and modified gradient waveform on sound pressure level and noise spectral entropy. We then used genetic algorithm to optimize both sound pressure level and spectral entropy for single-shot EPI sequence by varying the duration of each readout unit with a sinusoidal waveform, changing the timbre significantly with increased entropy and reduced loudness. The resulting image quality were also compared with images obtained by standard EPI sequence.
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