Publications by authors named "Jean Pierre Pruvo"

In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original 3D model that leverages the strengths of domain translation and straightforward application of style transfer methods for multicenter brain MR image harmonization.

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Purpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency brain MRI reports. Materials and Methods All consecutive emergency brain MRI reports written in 2022 from a French quaternary center were retrospectively reviewed. Two radiologists identified MRI scans that were performed in the emergency department for headaches.

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Article Synopsis
  • - Catatonia is a psychomotor syndrome with various motor and behavioral symptoms, and benzodiazepines are the primary treatment, working for about 70% of patients; however, the reasons for resistance in some cases are still unclear.
  • - Researchers developed machine learning models using clinical evaluations and brain MRI data from 65 catatonic patients to predict responses to benzodiazepine treatment, classifying them into responders and non-responders.
  • - The models showed improved accuracy when incorporating neuroimaging data, identifying key factors—such as the duration of the syndrome and brain volume in specific areas—that help predict which patients are likely to not respond to treatment.
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Background: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a preferred treatment for parkinsonian patients with severe motor fluctuations. Proper targeting of the STN sensorimotor segment appears to be a crucial factor for success of the procedure. The recent introduction of directional leads theoretically increases stimulation specificity in this challenging area but also requires more precise stimulation parameters.

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In multicenter MRI studies, pooling the imaging data can introduce site-related variabilities and can therefore bias the subsequent analyses. To harmonize the intensity distributions of brain MR images in a multicenter dataset, unsupervised deep learning methods can be employed. Here, we developed a model based on cycle-consistent adversarial networks for the harmonization of T1-weighted brain MR images.

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Article Synopsis
  • Systemic lupus erythematosus (SLE) is an autoimmune disease that can affect various organs, including the brain, and researchers used an AI model called BrainAGE to assess brain aging in SLE patients.
  • The study involved 70 female SLE patients and 24 healthy controls, utilizing MRI scans and neuropsychological tests to calculate BrainAGE scores.
  • Results showed that SLE patients had significantly higher BrainAGE scores than controls, which were linked to cognitive impairments like slower reaction times and lower mental flexibility, indicating potential neuronal damage.
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This review describes targeted magnetic resonance imaging (tMRI) of small changes in the T and the spatial properties of normal or near normal appearing white or gray matter in disease of the brain. It employs divided subtracted inversion recovery (dSIR) and divided reverse subtracted inversion recovery (drSIR) sequences to increase the contrast produced by small changes in T by up to 15 times compared to conventional T-weighted inversion recovery (IR) sequences such as magnetization prepared-rapid acquisition gradient echo (MP-RAGE). This increase in contrast can be used to reveal disease with only small changes in T in normal appearing white or gray matter that is not apparent on conventional MP-RAGE, T-weighted spin echo (T-wSE) and/or fluid attenuated inversion recovery (T-FLAIR) images.

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First-episode psychosis (FEP) is defined as the first occurrence of delusions, hallucinations, or psychic disorganization of significant magnitude, lasting more than 7 days. Evolution is difficult to predict since the first episode remains isolated in one third of cases, while recurrence occurs in another third, and the last third progresses to a schizo-affective disorder. It has been suggested that the longer psychosis goes unnoticed and untreated, the more severe the probability of relapse and recovery.

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Background: Polycystic ovary syndrome (PCOS) is the most common reproductive-endocrine disorder affecting between 5 and 18% of women worldwide. An elevated frequency of pulsatile luteinizing hormone (LH) secretion and higher serum levels of anti-Müllerian hormone (AMH) are frequently observed in women with PCOS. The origin of these abnormalities is, however, not well understood.

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Background: Iron content is increased in the substantia nigra of persons with Parkinson's disease and may contribute to the pathophysiology of the disorder. Early research suggests that the iron chelator deferiprone can reduce nigrostriatal iron content in persons with Parkinson's disease, but its effects on disease progression are unclear.

Methods: We conducted a multicenter, phase 2, randomized, double-blind trial involving participants with newly diagnosed Parkinson's disease who had never received levodopa.

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Pediatric neuroradiology is a subspecialty within radiology, with possible pathways to train within the discipline from neuroradiology or pediatric radiology. Formalized pediatric neuroradiology training programs are not available in most European countries. We aimed to construct a European consensus document providing recommendations for the safe practice of pediatric neuroradiology.

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Article Synopsis
  • The study aimed to analyze how brain iron is distributed in different subtypes of early-onset Alzheimer's disease (EOAD) using an imaging method called quantitative susceptibility mapping (QSM).
  • Researchers compared MRI data from 68 EOAD patients and 43 healthy controls, assessing brain volume ratios to classify EOAD subtypes and examine iron levels in specific brain regions.
  • Results showed higher iron levels in EOAD patients, especially in deep gray nuclei and limbic structures, and highlighted that different EOAD subtypes displayed unique iron distribution patterns, which may help in identifying patients with atypical Alzheimer's presentations.
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Background And Objectives: Acute optic neuritis (ON) is a classical presenting symptom of multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), and anti-MOG-associated disorders. The resulting visual impairment is variable and can be severe. Clinicians are in need of predictive biomarkers to optimize the management of acute ON.

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Predicted age difference (PAD) is a score computed by subtracting chronological age from "brain" age, which is estimated using neuroimaging data. The goal of this study was to evaluate the PAD as a marker of phenotypic heterogeneity and severity among early-onset Alzheimer's disease (EOAD) patients. We first used 3D T1-weighted (3D-T1) magnetic resonance images (MRI) of 3,227 healthy subjects aged between 18 and 85 years to train, optimize, and evaluate the brain age model.

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Introduction: Mucormycosis are infections caused by molds of the order Mucorales. These opportunistic infections are rare, difficult to diagnose, and have a poor prognosis. We aimed to describe common radiographic patterns that may help to diagnose cerebral mucormycosis and search for histopathological correlations with imaging data.

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Objective: To determine whether functional MRI connectivity can predict long-term cognitive function 36 months after minor stroke.

Methods: Seventy-two participants with first-ever stroke were included at baseline and followed up for 36 months. A ridge regression machine learning algorithm was developed and used to predict cognitive scores 36 months poststroke on the basis of the functional networks measured using MRI at 6 months (referred to here as the poststroke cognitive impairment [PSCI] network).

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Objectives: To compare brain MRI findings in progressive multifocal leukoencephalopathy (PML) associated to rituximab and natalizumab treatments and HIV infection.

Materials And Methods: In this retrospective, multicentric study, we analyzed brain MRI exams from 72 patients diagnosed with definite PML: 32 after natalizumab treatment, 20 after rituximab treatment, and 20 HIV patients. We compared T2- or FLAIR-weighted images, diffusion-weighted images, T2*-weighted images, and contrast enhancement features, as well as lesion distribution, especially gray matter involvement.

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Objective: To evaluate the ability of intereye retinal thickness difference (IETD) measured by optical coherence tomography (OCT) to detect asymptomatic optic nerve involvement in clinically isolated syndrome (CIS).

Methods: We conducted a cross-sectional study of patients who recently presented a CIS (≤4.5 months).

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Background: Patients treated at off-hours for acute conditions have increased mortality rates. This effect has been poorly evaluated in patients treated by mechanical thrombectomy (MT).

Objective: This study aimed at comparing outcomes between patients treated at off-hours and at working hours by MT for acute stroke due to large-vessel occlusion in the anterior circulation, in a well-organised network.

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Objective: To evaluate the frequency of asymptomatic optic nerve lesions and their role in the asymptomatic retinal neuroaxonal loss observed in multiple sclerosis (MS).

Methods: We included patients with remitting-relapsing MS in the VWIMS study (Analysis of Neurodegenerative Process Within Visual Ways In Multiple Sclerosis) (ClinicalTrials.gov Identifier: 03656055).

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