T1 Mapping From MPRAGE Acquisitions: Application to the Measurement of the Concentration of Nanoparticles in Tumors for Theranostic Use.

BACKGROUND: The measurement of the concentration of theranostic agents in vivo is essential for the assessment of their therapeutic efficacy and their safety regarding healthy tissue. To this end, there is a need for quantitative T1 measurements that can be obtained as part of a standard clinical imaging protocol applied to tumor patients. PURPOSE: To generate T1 maps from MR images obtained with the magnetization-prepared rapid gradient echo (MPRAGE) sequence. To evaluate the feasibility of the proposed approach on phantoms, animal and patients with brain metastases. STUDY TYPE: Pilot. PHANTOM/ANIMAL MODEL/POPULATION: Solutions containing contrast agents (chelated Gd3+ and iron nanoparticles), male rat of Wistar strain, three patients with brain metastases. FIELD STRENGTH/SEQUENCE: A 3-T and 7-T, saturation recovery (SR), and MPRAGE sequences. ASSESSMENT: The MPRAGE T1 measurement was compared to the reference SR method on phantoms and rat brain at 7-T. The robustness of the in vivo method was evaluated by studying the impact of misestimates of tissue proton density. Concentrations of Gd-based theranostic agents were measured at 3-T in gray matter and metastases in patients recruited in NanoRad clinical trial. STATISTICAL TESTS: A linear model was used to characterize the relation between T1 measurements from the MPRAGE and the SR acquisitions obtained in vitro at 7-T. RESULTS: The slope of the linear model was 0.966 (R2  = 0.9934). MPRAGE-based T1 values measured in the rat brain were 1723 msec in the thalamus. MPRAGE-based T1 values measured in patients in white matter and gray matter amounted to 747 msec and 1690 msec. Mean concentration values of Gd3+ in metastases were 61.47 µmol. DATA CONCLUSION: The T1 values obtained in vitro and in vivo support the validity of the proposed approach. The concentrations of Gd-based theranostic agents may be assessed in patients with metastases within a standard clinical imaging protocol using the MPRAGE sequence. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 1.

Neurovascular multiparametric MRI defines epileptogenic and seizure propagation regions in experimental mesiotemporal lobe epilepsy.

OBJECTIVE: Improving the identification of the epileptogenic zone and associated seizure-spreading regions represents a significant challenge. Innovative brain-imaging modalities tracking neurovascular dynamics during seizures may provide new disease biomarkers. METHODS: With use of a multi-parametric magnetic resonance imaging (MRI) analysis at 9.4 Tesla, we examined, elaborated, and combined multiple cellular and cerebrovascular MRI read-outs as imaging biomarkers of the epileptogenic and seizure-propagating regions. Analyses were performed in an experimental model of mesial temporal lobe epilepsy (MTLE) generated by unilateral intra-hippocampal injection of kainic acid (KA). RESULTS: In the ipsilateral epileptogenic hippocampi, tissue T1 and blood-brain barrier (BBB) permeability to gadolinium were increased 48-72 hours post-KA, as compared to sham and contralateral hippocampi. BBB permeability endured during spontaneous focal seizures (4-6 weeks), along with a significant increase of apparent diffusion coefficient (ADC) and blood volume fraction (BVf). Simultaneously, ADC and BVf were augmented in the contralateral hippocampus, a region characterized by electroencephalographic seizure spreading, discrete histological neurovascular cell modifications, and no tissue sclerosis. We next asked whether combining all the acquired MRI parameters could deliver criteria to classify the epileptogenic from the seizure-spreading and sham hippocampi in these experimental conditions and over time. To differentiate sham from epileptogenic areas, the automatic multi-parametric classification provided a maximum accuracy of 97.5% (32 regions) 48-72 hours post-KA and of 100% (60 regions) at spontaneous seizures stage. To differentiate sham, epileptogenic, and seizure-spreading areas, the accuracies of the automatic classification were 93.1% (42 regions) 48-72 hours post-KA and 95% (80 regions) at spontaneous seizure stage. SIGNIFICANCE: Combining multi-parametric MRI acquisition and machine-learning analyses delivers specific imaging identifiers to segregate the epileptogenic from the contralateral seizure-spreading hippocampi in experimental MTLE. The potential clinical value of our findings is critically discussed.

A pericyte-glia scarring develops at the leaky capillaries in the hippocampus during seizure activity.

OBJECTIVE: Inflammatory cerebrovascular damage occurs in epilepsy. Here, we tested the hypothesis that a pericyte-glia scar forms around the outer wall of hippocampal capillaries in a model of temporal lobe epilepsy associated with hippocampal sclerosis. We studied the participation of stromal cells expressing platelet-derived growth factor receptor beta (PDGFRß) and extracellular matrix modifications to the perivascular scar during epileptogenesis. METHODS: We used NG2DsRed/C57BL6 mice and induced status epilepticus (SE) followed by epileptogenesis and spontaneous recurrent seizures (SRS) by means of unilateral intrahippocampal injection of kainic acid (KA). For pharmacological assessment, we used organotypic hippocampal cultures (OHCs) where ictal electrographic activity was elicited by KA or bicuculline. RESULTS: NG2DsRed pericytes, GFAP astroglia, and IBA1 microglia are reactive and converge to form a pericapillary multicellular scar in the CA hippocampal regions during epileptogenesis and at SRS. The capillaries are leaky as indicated by fluorescein entering the parenchyma from the peripheral blood. Concomitantly, PDGFRß transcript and protein levels were significantly increased. Within the regional scar, a fibrotic-like PDGFRß mesh developed around the capillaries, peaking at 1 week post-SE and regressing, but not resolving, at SRS. Abnormal distribution or accumulation of extracellular matrix collagens III/IV occurred in the CA regions during seizure progression. PDGFRß/DAPI cells were in direct contact with or adjacent to the damaged NG2DsRed pericytes at the capillary interface, consistent with the notion of stromal cell reactivity or fibroblast formation. Inducing electrographic activity in OHCs was sufficient to augment PDGFRß reactivity around the capillaries. The latter effect was pharmacologically mimicked by treating OHCs with the PDGFRß agonist PDGF-BB and it was diminished by the PDGFRß inhibitor imatinib. SIGNIFICANCE: The reported multicellular activation and scar are traits of perivascular inflammation and hippocampal sclerosis in experimental epilepsy, with an implication for neurovascular dysfunction. Modulation of PDGFRß could be exploited to target inflammation in this chronic disease setting.

Quantifying gadolinium-based nanoparticle uptake distributions in brain metastases via magnetic resonance imaging.

AGuIX, a novel gadolinium-based nanoparticle, has been deployed in a pioneering double-blinded Phase II clinical trial aiming to assess its efficacy in enhancing radiotherapy for tumor treatment. This paper moves towards this goal by analyzing AGuIX uptake patterns in 23 patients. A phantom was designed to establish the relationship between AGuIX concentration and longitudinal ( T 1 ) relaxation. A 3T MRI and MP2RAGE sequence were used to generate patient T 1 maps. AGuIX uptake in tumors was determined based on longitudinal relaxivity. AGuIX (or placebo) was administered to 23 patients intravenously at 100 mg/kg 1-5 hours pre-imaging. Each of 129 brain metastases across 23 patients were captured in T 1 maps and examined for AGuIX uptake and distribution. Inferred AGuIX recipients had average tumor uptakes between 0.012 and 0.17 mg/ml, with a mean of 0.055 mg/ml. Suspected placebo recipients appeared to have no appreciable uptake. Tumors presented with varying spatial AGuIX uptake distributions, suspected to be related to differences in accumulation time and patient-specific bioaccumulation factors. This research demonstrates AGuIX's ability to accumulate in brain metastases, with quantifiable uptake via T 1 mapping. Future analyses will extend these methods to complete clinical trial data (~ 134 patients) to evaluate the potential relationship between nanoparticle uptake and possible tumor response following radiotherapy.Clinical Trial Registration Number: NCT04899908.Clinical Trial Registration Date: 25/05/2021.

Bayesian Inverse Regression for Vascular Magnetic Resonance Fingerprinting.

Standard parameter estimation from vascular magnetic resonance fingerprinting (MRF) data is based on matching the MRF signals to their best counterparts in a grid of coupled simulated signals and parameters, referred to as a dictionary. To reach a good accuracy, the matching requires an informative dictionary whose cost, in terms of design, storage and exploration, is rapidly prohibitive for even moderate numbers of parameters. In this work, we propose an alternative dictionary-based statistical learning (DB-SL) approach made of three steps: 1) a quasi-random sampling strategy to produce efficiently an informative dictionary, 2) an inverse statistical regression model to learn from the dictionary a correspondence between fingerprints and parameters, and 3) the use of this mapping to provide both parameter estimates and their confidence indices. The proposed DB-SL approach is compared to both the standard dictionary-based matching (DBM) method and to a dictionary-based deep learning (DB-DL) method. Performance is illustrated first on synthetic signals including scalable and standard MRF signals with spatial undersampling noise. Then, vascular MRF signals are considered both through simulations and real data acquired in tumor bearing rats. Overall, the two learning methods yield more accurate parameter estimates than matching and to a range not limited to the dictionary boundaries. DB-SL in particular resists to higher noise levels and provides in addition confidence indices on the estimates at no additional cost. DB-SL appears as a promising method to reduce simulation needs and computational requirements, while modeling sources of uncertainty and providing both accurate and interpretable results.

MP3: Medical Software for Processing Multi-Parametric Images Pipelines.

This article presents an open source software able to convert, display, and process medical images. It differentiates itself from the existing software by its ability to design complex processing pipelines and to wisely execute them on a large databases. An MP3 pipeline can contain unlimited homemade or ready-made processes and can be carried out with a parallel execution system. As a viewer, MP3 allows display of up to four images together and to draw Regions Of Interest (ROI). Two applications showing the strengths of the software are presented as examples: a preclinical study involving Magnetic Resonance Imaging (MRI) data and a clinical one involving Computed Tomography (CT) images. MP3 is downloadable at https://github.com/nifm-gin/MP3.