Athinoula A. Martinos Center for Biomedical Imaging

To evaluate the use of the Model Predictive Filtering (MPF) method to improve temporal resolution of magnetic resonance temperature imaging (MRTI) for monitoring laser interstitial thermal therapy (LITT) ablations. Using a Green's function method for solving differential equations, a treatment-specific power matrix Q was derived from a LITT heating and used in the Pennes bioheat equation (PBHE) to model a subsequent higher power heating and supplement subsampled k-space data. This MPF method was evaluated using both 3D segmented EPI data and a tissue mimicking phantom and clinical LITT treatment data after retrospective subsampling. Reconstruction accuracy was assessed via thermal dose and analysis of the hottest voxel and region-of-voxels over time. In the phantom data, temporal resolution equivalent to a 12-slice acquisition was produced with larger fields-of-view (24 and 36 slices, R = 2 and 3) with good hottest voxel-over-time accuracy and 240 CEM43 volume agreement (Dice similarity coefficient, DSC 0.7). In the in vivo data, MPF reconstruction showed excellent 240 CEM43 volume agreement for both orthogonal slices (DSC 0.9 for R = 2 and 3). The sagittal and coronal slices showed excellent hottest voxel accuracy for subsampling of R 3, with an RMSE ≤ 1°C. Hottest voxel RMSE remained within 1°C-3°C up to a subsampling factor of 5. The MPF algorithm allowed for large field-of-view (FOV) volumetric temperature imaging without decreasing temporal resolution in phantom heatings. Bi-planar clinical treatment data reconstruction showed good accuracy for the application of MPF to in vivo data.

The glymphatic system (GS) clears brain waste via cerebrospinal fluid (CSF), mainly during sleep. We developed GS-FlexNIRS, a compact, wireless, low-cost LED-based near-infrared spectroscopy (NIRS) device that measures hemoglobin and water content to monitor CSF-related oscillations. By incorporating long-wavelength LEDs (890–1050 nm) and a spectral-aware fitting algorithm, the system accurately separates water and hemoglobin signals. Validation in phantoms showed ±10% accuracy for water fraction and hemoglobin agreement with a commercial FD-NIRS system. Preliminary sleep studies are underway. GS-FlexNIRS enables non-invasive, longitudinal monitoring of GS function and holds promise for early detection of dysfunction linked to Alzheimer’s and related diseases.

Low-level light therapy (LLLT) has been shown to modulate recovery in patients with traumatic brain injury (TBI). However, the longitudinal impact of LLLT on brain metabolites has not been studied. The purpose of this study was to use MR spectroscopic imaging to assess the metabolic response of LLLT in patients with moderate TBI at acute (within 1 week), subacute (2-3 weeks), and late-subacute (3 months) recovery phases. This is a secondary analysis of a prospective single-site double-blind sham-controlled study conducted in patients with moderate TBI. Participants were randomized for LLLT and sham treatment. Three-Tesla 2D MR spectroscopic imaging was acquired. Our focus of investigation was the metabolic change in the corpus callosum (CC) and the changes in mIns/NAA, representing the combined effect of elevated neuroinflammation (mIns) and decreased neuronal/axonal health (NAA). A linear mixed-effects model was constructed to quantify the association between mIns/NAA and treatment, scan, and the interaction between treatment and scan. Thirty-four participants (18 men, age 49 ± 17 [range, 20-79]; 15 LLLT, 19 sham) were included in the final data set and were scanned at the following time points: acute (n=24), subacute (n=27), and late subacute (n=23). The mIns/NAA ratio in the CC of the sham-treated participants increased over time. Sham-treated participants revealed a significant increase in mIns/NAA from the acute to the late subacute phases (0.19; 95% CI, 0.09-0.29; P Holm = .005). mIns/NAA stayed relatively stable in participants undergoing LLLT treatment (all P Holm > .64). Consequently, mIns/NAA was significantly higher in the sham-treated participants compared with the LLLT-treated participants during the late subacute phase of recovery (-0.31; 95% CI, -0.50 to -0.12; P Holm = .019). Despite the small sample size, MR spectroscopic imaging indicates a metabolic response in participants treated with LLLT compared with those receiving sham treatment. This potentially suggests a neuroprotective and anti-inflammatory effect from the acute administration of LLLT in individuals with moderate TBI.

Abstract Accurate, non-invasive HPV status prediction in oropharyngeal squamous cell carcinoma (OPSCC) is essential for risk stratification and treatment planning, yet current imaging methods lack sufficient sensitivity. We developed a novel framework combining 3D Masked Autoencoder (MAE) self-supervised learning (SSL) pretraining on a Swin Transformer encoder with 33 slice-aggregated asymmetry features (airway effacement, mass effect, midline shift, hypodensity metrics). In a multiinstitutional cohort (n = 173) using five-fold cross-validation and holdout testing, the combined model achieved CV AUC 0.909 (95% CI 0.850–0.957) and holdout AUC 0.828 (95% CI 0.643–0.964), outperforming ablations (SSL-only: 0.703/0.636; asymmetry-only: 0.545/0.588). At a highsensitivity threshold, it reached 100% sensitivity and 100% NPV. This establishes a new benchmark for imaging-based HPV prediction in OPSCC without segmentation, enabling reliable non-invasive risk assessment.

We developed a dynamic B0 shimming approach using a 46-channel AC/DC shim array to correct phase errors caused by eddy currents from diffusion-encoding gradients in diffusion-prepared MRI, enabling high b value imaging without the SNR loss from the use of a magnitude stabilizer. A 46-channel AC/DC shim array and corresponding amplifier system were built. Spin echo prescans with and without diffusion preparation were then used to rapidly measure eddy current-induced phase differences. These phase maps were used as targets in an optimization framework to compute compensatory shim currents for multi-shot 3D diffusion-prepared acquisitions. The proposed method allows flexible use of the AC/DC shim array to correct undesirable eddy current effects in diffusion-prepared MRI. Phantom and in vivo experiments demonstrate whole-brain, cardiac-gated, multi-shot 3D diffusion-prepared imaging without the use of magnitude stabilizers. The approach enables preservation of full SNR while achieving reliable diffusion encoding at b values up to 2000 s/mm2. This work demonstrates a new strategy for applying an AC/DC shim array to compensate for eddy current-induced phase errors in diffusion-prepared MRI. By eliminating the need for a magnitude stabilizer, it enables efficient high-quality diffusion imaging with full signal sensitivity retained.

We investigated whether sleep microstructures show spatial differences in young children with autism compared with typically developing peers. 32-channel electroencephalography (EEG) during natural sleep after 5-6 h of partial sleep deprivation was recorded from 53 children (26 with autism, 27 typically developing; 1.1-5.1 years). Quantified EEG features included spindle density, frequency, morphology, slow oscillations and the relative power of infraslow oscillations (0.005-0.03 Hz). Clinical associations were examined using the Autism Diagnostic Observation Schedule, the Childhood Autism Rating Scale and the Gesell Developmental Schedules. Children with autism showed greater modulation of spindle frequency by the phase of slow oscillations at a right frontal scalp electrode (F8). An infraslow peak slightly below 0.02 Hz was present in both groups. Although group differences in infraslow power did not remain significant after correction for multiple comparisons, infraslow power correlated positively with autism severity in males, over posterior and temporal regions. These findings indicate that sleep microstructures in early childhood reflect thalamocortical and cortical dysfunction with sex-specific clinical associations.

ABSTRACT Fear extinction processes are central to the pathology and treatment of anxiety disorders. Emerging evidence implicates rapid eye movement (REM) sleep in the consolidation of extinction memory. Separately, converging theory and empirical work suggest that vagally mediated heart rate variability (VmHRV) serves as a peripheral index of cortico–subcortical regulatory capacity relevant to extinction circuitry. On this basis, we tested the hypothesis that VmHRV during REM sleep would be associated with the retention of extinction memory in individuals with generalized anxiety disorder (GAD). Participants underwent a validated two-day fear conditioning and extinction paradigm. Subjective extinction retention (sERI) was quantified during a recall test 24 hours after learning and ambulatory polysomnography was recorded on the intervening night. As hypothesized, higher REM VmHRV was significantly associated with better extinction retention. This association remained robust after controlling psychotropic medication use and REM density. In contrast, VmHRV during SWS or wakefulness, as well as other REM sleep measures, were not associated with extinction retention. These findings identify REM VmHRV as a significant predictor of extinction memory retention in GAD, extending prior findings in trauma-exposed individuals. We propose that reduced vagal tone indexes compromised prefrontal inhibitory control over amygdala and noradrenergic circuits, thereby impairing REM sleep-dependent consolidation. These results position VmHRV during REM sleep as a potential transdiagnostic biomarker of extinction memory processing and suggest that interventions enhancing vagal tone could improve treatment outcomes in anxiety disorders.