An advanced diffusion-MRI project developing non-invasive measures of cortical glial activation in multiple sclerosis. It compares imaging markers with PET and tissue findings to characterize neuroinflammation and changes in cortical microstructure.
Project abstract
Project Summary Neuroinflammation by means of glial (microglia and astrocytes) activation is thought to play a key role in the pathogenesis of several psychiatric and neurodegenerative disorders of different etiology including depression, schizophrenia, Alzheimer’s disease and multiple sclerosis (MS). Still, current noninvasive methods to detect and characte…Read the full abstractCollapse abstract
Project Summary Neuroinflammation by means of glial (microglia and astrocytes) activation is thought to play a key role in the pathogenesis of several psychiatric and neurodegenerative disorders of different etiology including depression, schizophrenia, Alzheimer’s disease and multiple sclerosis (MS). Still, current noninvasive methods to detect and characterize neuroinflammation in vivo are limited. Positron emission tomography (PET)- based targeting of the 18kDa translocator protein (TSPO), which is overexpressed in activated glial cells but otherwise present at very low levels in the healthy brain, is the current gold-standard for imaging in vivo glial activation in the human brain. PET imaging, however, is associated with radiation exposure, which limits its use in children and child-bearing women, and over time. Microglia and astrocytes are dynamic cells able to change morphology and function following “activation” from a variety of pathological insults. Advanced magnetic resonance (MR) diffusion weighted imaging (DWI) is a sensitive approach for non- invasive measurement of intra- and extra-cellular microstructural changes associated with glial activation. We have developed a novel DWI multi-compartment microstructural model (MCM) for imaging microglia and astrocyte activation, which we validated in an experimental rat model of grey matter (GM) inflammation. Here, we propose to translate this model to the study of cortical glial activation in healthy controls and patients with MS, and to validate in vivo findings in post-mortem MS brain tissue. MS is a chronic inflammatory and neurodegenerative disorder of the central nervous system that represents the leading cause of non-traumatic neurological disability in young adults in the US. There is solid evidence that extensive microglia activation is a main pathological feature of cortical pathology in MS. Our overall hypothesis is that MCM-derived indices are sensitive to cortical microstructural changes related to glial activation as evidenced by a strong correlation with TSPO levels on PET with 11C-PBR28, a second generation TSPO radioligand, and by neuropathological verification. A non-invasive methodology that allows investigating and characterizing the contribution of neuroinflammation in the GM will have a tremendous impact in clarifying disease mechanisms in MS, as well as in a wide- spectrum of neurological and psychiatric conditions.
Research connections
Publications
2025
Frontiers in neuroinformatics
INTRODUCTION: Neuroinflammation, a pathophysiological process involved in numerous disorders, is typically imaged using [11C]PBR28 (or TSPO) PET. However, this technique is limited by high costs and ionizing radiation, restricting its widespread clinical use. MRI, a more accessible alternative, is commonly used for structural or functional imaging, but when…Read the full abstractCollapse abstract
INTRODUCTION: Neuroinflammation, a pathophysiological process involved in numerous disorders, is typically imaged using [11C]PBR28 (or TSPO) PET. However, this technique is limited by high costs and ionizing radiation, restricting its widespread clinical use. MRI, a more accessible alternative, is commonly used for structural or functional imaging, but when used using traditional approaches has limited sensitivity to specific molecular processes. This study aims to develop a deep learning model to generate TSPO PET images from structural MRI data collected in human subjects.
METHODS: A total of 204 scans, from participants with knee osteoarthritis (n = 15 scanned once, 15 scanned twice, 14 scanned three times), back pain (n = 40 scanned twice, 3 scanned three times), and healthy controls (n = 28, scanned once), underwent simultaneous 3 T MRI and [11C]PBR28 TSPO PET scans. A 3D U-Net model was trained on 80% of these PET-MRI pairs and validated using 5-fold cross-validation. The model's accuracy in reconstructed PET from MRI only was assessed using various intensity and noise metrics.
RESULTS: The model achieved a low voxel-wise mean squared error (0.0033 ± 0.0010) across all folds and a median contrast-to-noise ratio of 0.0640 ± 0.2500 when comparing true to reconstructed PET images. The synthesized PET images accurately replicated the spatial patterns observed in the original PET data. Additionally, the reconstruction accuracy was maintained even after spatial normalization.
DISCUSSION: This study demonstrates that deep learning can accurately synthesize TSPO PET images from conventional, T1-weighted MRI. This approach could enable low-cost, noninvasive neuroinflammation imaging, expanding the clinical applicability of this imaging method.
2025
Brain, behavior, and immunity
Recent evidence suggests that chronic pain patients exhibit elevated brain levels of the neuroinflammation marker 18 kDa translocator protein (TSPO). However, the clinical significance of brain TSPO elevations, and their responses to pain interventions, remain unknown. To explore these questions, we studied patients with knee osteoarthritis (KOA) undergoing…Read the full abstractCollapse abstract
Recent evidence suggests that chronic pain patients exhibit elevated brain levels of the neuroinflammation marker 18 kDa translocator protein (TSPO). However, the clinical significance of brain TSPO elevations, and their responses to pain interventions, remain unknown. To explore these questions, we studied patients with knee osteoarthritis (KOA) undergoing total knee arthroplasty (TKA), a procedure which is curative for most, but carries a relatively high risk of persistent post-surgical pain. Pre-surgical KOA patients (n = 41) and healthy controls (n = 22) underwent brain positron emission tomography/magnetic resonance imaging, using the TSPO radioligand [11C]PBR28. A subset of KOA patients (n = 27) returned for a second scan one-year post-TKA. When compared groups, pre-surgical KOA patients exhibited widespread [11C]PBR28 PET signal elevations (Standardized Uptake Value Ratio), with pituitary uptake positively correlating with knee pain severity (rho = 0.51; p = 0.003). A voxel-wise paired t-test revealed that while most brain regions showed no change post-surgery, the [11C]PBR28 PET signal significantly decreased in the thalamus and caudate, reaching control levels. Additionally, a Support Vector Machine model based on pre-surgical imaging, clinical, and demographic features, achieved a correlation of rho = 0.487 (p = 0.001) between the predicted and actual pain improvement. Top predictive features included [11C]PBR28 uptake in the pituitary gland, cuneal cortex, amygdala and other regions. This study suggests that neuroinflammation 1) is widespread in KOA and, in some regions, 2) is linked to pain severity, 3) undergoes normalization following TKA, and 4) can predict post-surgical TKA outcomes. Understanding the neuroinflammatory mechanisms in KOA and post-surgical pain may guide targeted interventions and improve patient outcomes.
2024
eLife
Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartm…Read the full abstractCollapse abstract
Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.