Transient Hypoxia Model Revealed Cerebrovascular Impairment in Anemia Using BOLD MRI and Near-Infrared Spectroscopy.

BACKGROUND: Obstructive sleep apnea and nocturnal oxygen desaturations, which are prevalent in sickle cell disease (SCD) and chronic anemia disorders, have been linked to risks of stroke and silent cerebral infarcts (SCI). Cerebrovascular response to intermittent desaturations has not been well studied and may identify patients at greatest risk. PURPOSE: To investigate the cerebral dynamic response to induced desaturation in SCD patients with and without SCI, chronic anemia, and healthy subjects. STUDY TYPE: Prospective. SUBJECTS: Twenty-six SCD patients (age = 21 ± 8.2, female 46.2%), including 15 subjects without SCI and nine subjects with SCI, 15 nonsickle anemic patients (age = 22 ± 5.8, female 66.7%), and 31 controls (age = 28 ± 12.3, female 77.4%). FIELD STRENGTH/SEQUENCE: 3T, gradient-echo echo-planar imaging. ASSESSMENT: A transient hypoxia challenge of five breaths of 100% nitrogen gas was performed with blood oxygen level-dependent (BOLD) MRI and near-infrared spectroscopy (NIRS) acquisitions. Hypoxia responses were characterized by desaturation depth, time-to-peak, return-to-baseline half-life, and posthypoxia recovery in the BOLD and NIRS time courses. SCI were documented by T2 fluid-attenuation inversion recovery (FLAIR). STATISTICAL TESTS: Univariate and multivariate regressions were performed between hypoxic parameters and anemia predictors. Voxelwise two-sample t-statistic maps were used to assess the regional difference in hypoxic responses between anemic and control groups. RESULTS: Compared to controls, SCD and chronically anemic patients demonstrated significantly higher desaturation depth (P < 0.01) and shorter return-to-baseline timing response (P < 0.01). Patients having SCI had shorter time-to-peak (P < 0.01), return-to-baseline (P < 0.01), and larger desaturation depth (P < 0.01) in both white matter regions at risk and normal-appearing white matter than patients without infarcts. On multivariate analysis, desaturation depth and timing varied with age, sex, blood flow, white blood cells, and cell-free hemoglobin (r2 = 0.25 for desaturation depth; r2 = 0.18 for time-to-peak; r2 = 0.37 for return-to-baseline). DATA CONCLUSION: Transient hypoxia revealed global and regional response differences between anemic and healthy subjects. SCI was associated with extensive heterogeneity of desaturation dynamics, consistent with extensive underlying microvascular remodeling.

CEREBRAL BLOOD FLOW AND PREDICTORS OF WHITE MATTER LESIONS IN ADULTS WITH TETRALOGY OF FALLOT.

Long-term outcomes for Tetralogy of Fallot (TOF) have improved dramatically in recent years, but survivors are still afflicted by cerebral damage. In this paper, we characterized the prevalence and predictors of cerebral silent infarction (SCI) and their relationship to cerebral blood flow (CBF) in 46 adult TOF patients. We calculated both whole brain and regional CBF using 2D arterial spin labeling (ASL) images, and investigated the spatial overlap between voxel-wise CBF values and white matter hyperintensities (WMHs) identified from T2-FLAIR images. SCIs were found in 83% of subjects and were predicted by the year of the patient's first cardiac surgery and patient's age at scanning (combined r2 0.44). CBF was not different in brain regions prone to stroke compared with healthy white matter.

ORCHESTRAL FULLY CONVOLUTIONAL NETWORKS FOR SMALL LESION SEGMENTATION IN BRAIN MRI.

White matter (WM) lesion identification and segmentation has proved of clinical importance for diagnosis, treatment and neurological outcomes. Convolutional neural networks (CNN) have demonstrated their success for large lesion load segmentation, but are not sensitive to small deep WM and sub-cortical lesion segmentation. We propose to use multi-scale and supervised fully convolutional networks (FCN) to segment small WM lesions in 22 anemic patients. The multiple scales enable us to identify the small lesions while reducing many false alarms, and the multi-supervised scheme allows a better management of the unbalanced data. Compared to a single FCN (Dice score ~0.31), the performance on the testing dataset of our proposed networks achieved a Dice score of 0.78.