Evidence map›Paper›PMID 42584478›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Distinguishing autoimmune encephalitis from its mimics using brain [¹⁸F]-FDG PET: real-world study.

Hélène Rostand, Fiene Marie Kuijper, Cristina Birzu, Alberto Picca, Clémence Marois, Alice Laurenge, Antoine Rogeau, Vincent Navarro, Louis Cousyn, Vincent Davy and 3 more

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Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Hélène RostandDepartment of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, Paris, France.
Fiene Marie KuijperDepartment of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, Paris, France.
Cristina BirzuFrench Reference Centre on Paraneoplastic Neurological Syndromes and Autoimmune Encephalitis, France MeLiS Institute -UCBL-CNRS UMR 5284 - INSERM U1314, Université Claude Bernard Lyon 1, Hospices Civils de Lyon, Hôpital Neurologique, Bron, France.
Alberto PiccaDepartment of Neuro-oncology, Reference Centre on Paraneoplastic Neurological Syndromes and Autoimmune Encephalitis. Sorbonne Université, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, UMR S 1127, Inserm U 1127, CNRS UMR 7225, ICM- Paris Brain Institute, Paris, France.
Clémence MaroisNeuro-Intensive Care Unit, Assistance Publique Hôpitaux de Paris (AP-HP), Sorbonne Université, Hôpital de la Pitié- Salpêtrière, Paris, France.
Alice LaurengeDepartment of Neuro-oncology, Reference Centre on Paraneoplastic Neurological Syndromes and Autoimmune Encephalitis. Sorbonne Université, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, UMR S 1127, Inserm U 1127, CNRS UMR 7225, ICM- Paris Brain Institute, Paris, France.
Antoine RogeauDepartment of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, Paris, France.
Vincent NavarroDepartment of Neurology, Epilepsy Unit, Reference Center of rare epilepsies, Pitié- Salpêtrière Hospital, and Paris Brain Institute, Assistance Publique Hôpitaux de Paris (AP-HP), Sorbonne Université, ERN-Epicare, ICM, Paris, France.
Louis CousynDepartment of Neurology, Epilepsy Unit, Reference Center of rare epilepsies, Pitié- Salpêtrière Hospital, and Paris Brain Institute, Assistance Publique Hôpitaux de Paris (AP-HP), Sorbonne Université, ERN-Epicare, ICM, Paris, France.
Vincent DavyDepartment of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, Paris, France.
Alain GironLaboratoire d'Imagerie Biomédicale, Sorbonne Université, INSERM, CNRS, Paris, France.
Dimitri PsimarasDepartment of Neuro-oncology, Reference Centre on Paraneoplastic Neurological Syndromes and Autoimmune Encephalitis. Sorbonne Université, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, UMR S 1127, Inserm U 1127, CNRS UMR 7225, ICM- Paris Brain Institute, Paris, France.
Aurélie KasDepartment of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, Paris, France. aurelie.kas@aphp.fr.ORCID http://orcid.org/0000-0001-9463-3658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnosing autoimmune encephalitis (AE) remains challenging due to heterogeneous clinical presentations, frequent seronegativity, and limited MRI sensitivity. We evaluated the diagnostic performance of brain [¹⁸F]-FDG PET/CT in a real-world cohort of patients with suspected AE.

methodsConsecutive patients referred for [¹⁸F]-FDG PET/CT for suspected AE between January 2020 and July 2023 were retrospectively included. Final diagnoses were established using international criteria, expert consensus, and follow-up. PET findings were assessed visually, with voxel-wise and regional analyses, compared with 54 healthy controls, and stratified by age and treatment.

resultsAmong 141 patients (48 ± 21 years), 33% had AE, 43% differential diagnoses (DD), and 24% remained undetermined. Of AE cases, 70% were definite, 63% seropositive, and 35% had supportive MRI findings. AE showed cortical hypometabolism with mesiotemporal lobe (MTL), basal ganglia, cerebellum, midbrain, and insula hypermetabolism (p < 0.05). Compared with DD, AE exhibited lower occipital/prefrontal and higher MTL, insular, and midbrain metabolism (p < 0.001), with good discrimination versus DD (AUC 0.82-0.83). MTL hypermetabolism, alone or with cortical hypometabolism, emerged as the most specific feature, whereas other regional metrics and ratios were less reliable (AUC ≤ 0.73). Accuracy of visual PET analysis was high in patients under 40 years (positive/negative predictive values 82%/81%) and declined with age to 81%/69% at 40-65 years and 79%/64% over 65 years.

conclusions[¹⁸F]-FDG PET/CT identifies a characteristic metabolic signature of AE and differentiates it from relevant mimics, supporting its role as a complementary diagnostic biomarker, particularly in younger patients.

Indexed as

Autoimmune encephalitisBrain [¹⁸F]-FDG PETNeuroinflammationSPM12

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.