RESUMEN
Hypoxic-ischemic encephalopathy (HIE) is a common neurological syndrome in newborns with high mortality and morbidity. Therapeutic hypothermia (TH), which is standard of care for HIE, mitigates brain injury by suppressing anaerobic metabolism. However, more than 40% of HIE neonates have a poor outcome, even after TH. This study aims to provide metabolic biomarkers for predicting the outcomes of hypoxia-ischemia (HI) after TH using hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy. Postnatal day 10 (P10) mice with HI underwent TH at 1 h and were scanned at 6-8 h (P10), 24 h (P11), 7 days (P17), and 21 days (P31) post-HI on a 14.1-T NMR spectrometer. The metabolic images were collected, and the conversion rate from pyruvate to lactate and the ratio of lactate to pyruvate in the injured left hemisphere (kPL(L) and Lac/Pyr(L), respectively) were calculated at each timepoint. The outcomes of TH were determined by the assessments of brain injury on T2-weighted images and behavioral tests at later timepoint. kPL(L) and Lac/Pyr(L) over time between the good-outcome and poor-outcome groups and across timepoints within groups were analyzed. We found significant differences in temporal trends of kPL(L) and Lac/Pyr(L) between groups. In the good-outcome group, kPL(L) increased until P31 with a significantly higher value at P31 compared with that at P10, while the level of Lac/Pyr(L) at P31 was notably higher than those at all other timepoints. In the poor-outcome group, kPL(L) and Lac/Pyr(L) increased within 24 h. The kPL(L) value at P11 was considerably higher compared with P10. Discrete temporal changes of kPL(L) and Lac/Pyr(L) after TH between the good-outcome and poor-outcome groups were seen as early as 24 h after HI, reflecting various TH effects on brain anaerobic metabolism, which may provide insights for early screening for response to TH.
RESUMEN
Although fully automated volumetric approaches for monitoring brain tumor response have many advantages, most available deep learning models are optimized for highly curated, multi-contrast MRI from newly diagnosed gliomas, which are not representative of post-treatment cases in the clinic. Improving segmentation for treated patients is critical to accurately tracking changes in response to therapy. We investigated mixing data from newly diagnosed (n = 208) and treated (n = 221) gliomas in training, applying transfer learning (TL) from pre- to post-treatment imaging domains, and incorporating spatial regularization for T2-lesion segmentation using only T2 FLAIR images as input to improve generalization post-treatment. These approaches were evaluated on 24 patients suspected of progression who had received prior treatment. Including 26% of treated patients in training improved performance by 13.9%, and including more treated and untreated patients resulted in minimal changes. Fine-tuning with treated glioma improved sensitivity compared to data mixing by 2.5% (p < 0.05), and spatial regularization further improved performance when used with TL by 95th HD, Dice, and sensitivity (6.8%, 0.8%, 2.2%; p < 0.05). While training with ≥60 treated patients yielded the majority of performance gain, TL and spatial regularization further improved T2-lesion segmentation to treated gliomas using a single MR contrast and minimal processing, demonstrating clinical utility in response assessment.
RESUMEN
Background: T2-weighted Single Shot Fast Spin Echo (SSFSE) scans at 3 Tesla (3T) are increasingly used to image fetal pathology due to their excellent tissue contrast resolution and signal-to-noise ratio (SNR). Temperature changes that may occur in response to radio frequency (RF) pulses used for these sequences at 3T have not been studied in human fetal brains. To evaluate the safety of T2-weighted SSFSE for fetal brains at 3T, magnetic resonance (MR) thermometry was used to measure relative temperature changes in a typical clinical fetal brain MR exam. Methods: Relative temperature was estimated using sets of gradient recalled echo (GRE) images acquired before and after T2-weighted SSFSE images which lasted 27.47±8.19 minutes. Thirty-one fetuses with cardiac abnormalities, and 20 healthy controls were included in this study. Fetal brain temperature was estimated by proton resonance frequency (PRF) thermometry and compared to the estimated temperature in the gluteal muscle of the mother. Seven scans with excessive motion were excluded. Local outlier factor (LOF) was performed to remove 12 additional scans with spurious phase measurements due to motion degradation and potential field drift. Linear regression was performed to determine if temperature changes are dependent on the rate of energy deposition during the scan. Results: For the 32 participants used in the analysis, 17 with cardiac abnormalities and 15 healthy controls, the average relative fetal temperate change was 0.19±0.73 â higher than the mother, with no correlation between relative temperature change and the rate of images acquired during the scans (regression coefficient =-0.05, R-squared =0.05, P=0.22, F-statistic =1.60). The difference in the relative temperature changes between the fetal brain and mother's gluteal tissue in the healthy controls was on average 0.08 â lower and found not to be statistically different (P=0.76) to the group with cardiac abnormalities. Conclusions: Our results indicate that the estimated relative temperature changes of the fetal brain compared to the mother's gluteal tissue from RF pulses during the course of the T2-weighted SSFSE fetal MR exam are minimal. The differences in acquired phase between these regions through the exam were found not to be statistically different. These findings support that fetal brain imaging at 3T is within FDA limits and safe.