Brain 18F-FDG PET for the diagnosis of autoimmune encephalitis: a systematic review and a meta-analysis

doi:10.21203/rs.3.rs-243472/v1

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Brain 18F-FDG PET for the diagnosis of autoimmune encephalitis: a systematic review and a meta-analysis

https://doi.org/10.21203/rs.3.rs-243472/v1

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published 07 Mar, 2021

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Objective: To consolidate current understanding of detection sensitivity of brain ¹⁸F-FDG PET scans in the diagnosis of autoimmune encephalitis and to define specific metabolic imaging patterns for the most frequently occurring autoantibodies.

Methods: A systematic and exhaustive search ofdata available in the literature was performed by querying the PubMed/MEDLINE and Cochrane databases for the search terms: "FDG PET" and “"encephalitis" or "brain inflammation"”. Studies had to satisfy the following criteria: i. include at least one patient suspected or diagnosed with autoimmune encephalitis according to the current recommendations, ii. be an original case-report iii. specifically present ¹⁸F-FDG PET and/or morphologic imaging findings. The diagnostic ¹⁸F-FDG PET detection sensitivity in autoimmune encephalitis was determined for all cases reported in the literature and a meta-analysis, according to the PRISMA method, was performed on a subset of these, which included PET scans for at least 10 patients, and whose quality was assessed with the QUADAS-2 tool.

Results: The search strategy identified 1113 articles. The detection sensitivity of ¹⁸F-FDG PET was 90%, based on 176 publications and 720 patients and 80% [75%-84%] by meta-analysis based on 21 publications and 444 patients. We also report specific brain ¹⁸F-FDG PET imaging patterns for the main encephalitis autoantibody subtypes.

Conclusion and Relevance: Brain ¹⁸F-FDG PET has a high detection sensitivity and should be included in future diagnostic autoimmune encephalitis recommendations. Specific metabolic ¹⁸F-FDG PET patterns corresponding to the main autoimmune encephalitis autoantibody subtypes further enhance the value of this diagnostic.

Nuclear Medicine & Medical Imaging

meta-analysis

autoimmune encephalitis

brain 18F-FDG PET

autoantibody

Encephalitis is defined as a debilitating neurological disorder that develops as a rapidly progressive encephalopathy caused by brain inflammation ¹. Even though this pathology is relatively rare ², its prognosis is poor, entailing serious irreversible sequelae and death in up to 7–12% of cases ^3,4.

Encephalitis can be subdivided into two main etiologies: infectious (40–52% of cases⁵) and immune mediated (about 21%⁴), which also include the paraneoplastic syndromes, with the remaining cases of unknown origin(s) ^6,7,8,9. Our current study focuses on autoimmune encephalitis, including paraneoplastic encephalitis, associated with onconeuronal antibodies.

Autoimmune encephalitis is characterized by the presence of autoantibodies (aAbs) against neuronal targets ¹⁰. We reviewed encephalitis by aAb subtype, in terms of onconeuronal and non-onconeuronal Abs, since this classification appears to more closely reflect the clinical presentation ¹¹.

The diagnosis of autoimmune encephalitis is currently based on the clinical and paraclinical criteria defined by Graus et al. in 2016 ¹. Clinical criteria alone are often inadequate to diagnose autoimmune encephalitis, due to the lack of specificity of symptoms presented by patients ¹². A number of paraclinical tools have therefore been recommended to initially evaluate suspected autoimmune encephalitis cases. These evaluations involve standard biochemistry and immunology tests, to measure the intrathecal synthesis of anti-neuronal-Abs from lumbar punctures. However, it is not uncommon to obtain results several weeks after sampling, moreover, there is no guarantee that these tests will detect any aAbs in CSF at all. This has prompted a search for adjunct diagnostic tools such as EEG and MRI. But EEG results are often non-specific and MRI has a limited 25–50% sensitivity ^10,13. Because encephalitis patients may suffer severe and sometimes irreversible neurological sequelae, the early initiation of specific treatments and early follow-up of responses to these treatments ¹⁴ are key. This need underscores the importance of finding an early biomarker.

¹⁸F-Fluoro-deoxy-glucose (¹⁸F-FDG) Position Emission Tomography (PET) is a functional brain imaging technique used to visualize neuronal glycolytic metabolic activity which increases during brain inflammation. Importantly, neurological alterations are associated with lower metabolic activity in specific areas of the brain ¹⁵. ¹⁸F-FDG PET has also been shown to be superior to morphological imaging in the early diagnosis of autoimmune encephalitis ¹⁵. The increasing number of publications studying the results of brain ¹⁸F-FDG PET in autoimmune encephalitis over the past decade is in dire need of consolidation ^13–24. The literature is saturated with isolated case-reports and retrospective studies conducted on a small number of patients, leaving the role of PET in the initial assessment of the disease unclear.

Several previous brain ¹⁸F-FDG PET in autoimmune encephalitis reviews have attempted to report on the additional benefits of this approach ^13,15−25, but most of these studies focus on the clinical presentation, diagnostic work up, treatments and outcomes even though they all mention ¹⁸F-FDG-PET as a useful investigational tool ^14,16,22,25. Conversely, some reviews do focus on distinct ¹⁸F-FDG-PET imaging patterns associated of the most commonly detected autoantibodies ^{13,15, 18–21,24}, albeit without providing a systematic or exhaustive review of cases in the literature or a meta-analysis.

Our current systematic and exhaustive literature search completed by a meta-analysis aims to consolidate current understanding of detection sensitivity of ¹⁸F-FDG PET brain scans in patients diagnosed with autoimmune encephalitis, according to the recommended guidelines (PICOS), and to better define specific metabolic imaging patterns associated with the most commonly occurring autoantibodies.

We queried PubMed/MEDLINE and Cochrane databases, from inception till August 12, 2020, for the search terms: "FDG PET" and “"encephalitis" or "brain inflammation"” to address the specific PICOS question: the diagnostic sensitivity of brain ¹⁸F-FDG PET in cortical auto-immune encephalitis. Our systematic and exhaustive search, and meta-analysis, were conducted according to the PRISMA statement ²⁶.

Studies had to satisfy the following criteria: i. include at least one pediatric or adult patient suspected or diagnosed with cortical autoimmune encephalitis (all aAbs including Rasmussen's encephalitis because of its highly probable autoimmune mediation, and aAb associated paraneoplastic syndromes) according to the currently recommended criteria and independently of PET results, ii. be an original case-report (reviews and letters to the editor were excluded), iii. specifically present ¹⁸F-FDG PET and/or morphologic imaging findings.

Encephalitis unrelated to cortical autoimmune etiologies (please see Fig. 1 for details) were excluded. All studies satisfying these inclusion criteria were included in the systematic review.

The final selection was performed manually to ensure that all inclusion criteria were satisfied by two independent observers (MB and AV).

We report the number of ¹⁸F-FDG PET and MRI scans used from each publication, based on one initial diagnosis scan per patient. A true positive scan was defined as specific abnormalities detected in a patient with suspected encephalitis, and the remaining negative scans were considered as false negatives. This allowed the autoimmune encephalitis detection sensitivity to be calculated for both ¹⁸F-FDG PET and MRI. To provide a more accurate level of detection sensitivity of encephalitis for MRI and limiting the risk of bias, the analysis was extended to publications with only MRI data to calculate the MRI detection sensitivity. A systematic compilation of ¹⁸F-FDG PET detected abnormalities was subsequently determined for each individual aAb. Extractions were repeated, and a final consensus analysis performed (MB and AV).

To confirm results of detection sensitivity obtained from our systematic and exhaustive literature search, and to limit the potential bias of overestimating performances linked to the high proportion of published case reports examined, we performed a meta-analysis of ¹⁸F-FDG PET performances for the diagnosis of autoimmune encephalitis based on publications analyzing at least 10 patients by PET. The quality of each study was evaluated according to the quality assessment of diagnostic accuracy studies 2 (QUADAS-2) tool by 2 independent investigators (MB and AV); discrepancies were resolved by consensus. Fixed-effect models were performed for the overall analysis and for the aAb analysis. Sensitivities and 95% confidence intervals are summarized in forest plots. We used the metafor package of R software version 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Heterogeneity was evaluated with I².

Study design

The search initially identified 1,113 publications, of which 528 were excluded because they involved non-autoimmune mediated encephalitis. A further 256 publications reporting on non-original cases (reviews, clinical and epidemiologic descriptions) were excluded. 329 full-text publications were finally reviewed and considered for autoimmune encephalitis ¹⁸F-FDG PET and MRI detection sensitivity. Among these, 176 publications, representing 720 patients, were considered in the PET detection sensitivity calculation, whereas 320 publications (167 publications with both MRI and PET and 153 publications with MRI only, corresponding to 3239 patients) were considered for the MRI detection sensitivity. Among the 176 publications considered in the PET detection sensitivity, 120 were single case reports. For analysis of specific metabolic patterns of the most commonly occurring aAbs, 13 publications were subsequently excluded because they lacked descriptive details of aAb-related anomalies, leaving 163 studies, corresponding to 543 patients, in the analysis.

The study design is summarized as a flowchart (Fig. 1). Supplemental Table 1 details all publications finally included in the analysis of our systematic and exhaustive literature search. The meta-analysis was based on 444 cases from 21 publications ^27–47 each involving at least 10 patients with available brain ¹⁸F-FDG PET data. QUADAS-2 results are shown in Supplemental Fig. 1.

As detailed in Table 1, brain ¹⁸F-FDG PET is associated with an autoimmune encephalitis diagnostic sensitivity of 90%. This compares to an MRI diagnostic sensitivity of 61% (for MRIs with a corresponding brain ¹⁸F-FDG PET) and a sensitivity of 56% when all MRIs were included.

Table 1

Overall performance of PET and MRI detection sensitivity from a systematic and exhaustive search of the autoimmune encephalitis literature
Imaging modality	Number of patients with encephalitis	Number of patients with scans suggestive of encephalitis
¹⁸F-FDG PET^a	720	645 (90%)
MRI in study with PET^a	942	579 (61%)
MRI^b	3,239	1,822 (56%)
^a in 176 publications with at least ¹⁸F-FDG PET imaging; ^b in 320 publications with at least MRI

Furthermore, as reported in Fig. 2, forest plots of the meta-analysis showed a detection sensitivity of 80% [75%-84%], with a heterogeneity index (I²) of 57%. This heterogeneity falls to 21% when considering specific aAbs.

Brain ¹⁸F-FDG PET metabolic patterns by specific aAb

1. VGKC (Voltage-Gated Potassium Channel) aAbs

Autoimmune encephalitis involving VGKC aAbs is the form most extensively analyzed by brain ¹⁸F-FDG PET in the literature (n = 180 cases, Table 2). These aAbs are directed against cell surface antigens. They can be further classified into: anti-LGI1-Abs (Leucine-rich glioma inactivated 1) and anti-CASPR2-Abs (Contactin-associated protein-like 2).

Table 2

Summary of encephalitis cases with PET abnormalities by aAb subtype identified from a systematic and exhaustive search of the literature
	Antibody	n			Hypermetabolism only	Hypometabolism only	Association of hyper and hypometabolism	Site of hyper metabolism : n (%)	Site of hypo metabolism : n (%)	References (refer to the supplemental Table 1)
	Antibody	n			N (%)	N (%)	N (%)	Site of hyper metabolism : n (%)	Site of hypo metabolism : n (%)	References (refer to the supplemental Table 1)
Non-onconeuronal antibodies	VGKC	LGI1		123	95 (77%)	14 (11%)	14 (11%)	-BG : 81 (66%) -MTL : 82 (67%) -Other : 8 (7%)	-BG : 2 (2%) -MTL : 8 (7%) - Diffuse cortical : 10 (8%) - Cerebellum : 3 (2%) -Other : 18 (15%)	(10, 28, 40, 44, 55, 62, 64, 67, 69, 99, 123, 125, 132, 147, 158, 166, 167, 172, 177, 179, 205, 209, 214, 229, 245, 258, 260, 268, 281, 309, 327)
		CASPR2		12	4 (33%)	5 (42%)	3 (25%)	-BG : 2 (17%) -MTL : 7 (58%) -Other : 3 (25%)	-BG : 0 -MTL : 1 (8%) - Diffuse cortical : 3 (25%) - Cerebellum : 3 (25%) -Other : 6 (50%)	(17, 19, 31, 39, 64, 159, 198, 205, 242, 255, 311)
		Undetermined		45	17 (38%)	21 (47%)	7 (16%)	-BG : 11 (24%) -MTL: 14 (31%) -Other : 3 (7%)	-BG : 1 (2%) -MTL : 14 (31%) - Diffuse cortical : 11 (24%) - Cerebellum : 0 -Other : 11 (24%)	(17, 42, 57, 74, 91, 117, 142, 171, 187, 203, 204, 217, 244, 253, 268, 294, 314)
	NMDAR^a	124			20 (16%)	37 (30%)	67 (54%)	-BG : 58 (47%) -MTL : 25 (20%) -Other : 117 (95%)*	-BG : 42 (34%) -MTL: 5 (4%) - Diffuse cortical : 77 (62%) - Cerebellum : 26 (21%) -Other : 34 (27%)	(10, 15, 17, 20, 43, 70, 71, 90, 98, 100, 107, 115, 121, 126, 133, 136, 148, 154, 160, 165, 180, 184, 189, 190, 197, 199, 205, 206, 207, 217, 220, 225, 226, 234, 238, 239, 241, 249, 268, 284, 290, 294, 299, 309, 312, 323)
	GAD	36			8 (22%)	22 (61%)	6 (17%)	-BG : 2 (6%) -MTL: 5 (14%) -Other : 4 (11%)	-BG : 0 -MTL : 22 (61%) - Diffuse cortical : 5 (14%) - Cerebellum : 1 (3%) -Other : 6 (17%)	(10, 17, 50, 62, 73, 168, 268, 273, 280, 294, 313)
	GABA	17			11 (65%)	4 (24%)	2 (12%)	-BG : 2 (12%) -MTL : 11 (65%) -Other : 3 (18%)	-BG : 0 -MTL : 3 (18%) - Diffuse cortical : 1 (6%) - Cerebellum : 0 -Other : 2 (12%)	(137, 174, 179, 222, 277, 329)
	AMPAR	5			2 (40%)	3 (60%)	0	-BG : 0 -MTL : 1 (20%) -Other : 1 (20%)	-BG : 1 (20%) -MTL : 0 - Diffuse cortical : 2 (40%) - Cerebellum : 0 -Other : 1 (20%)	(155, 270, 310, 312)
	More rare	TPO/TG	5		2 (40%)	3 (60%)	0	-BG : 0 -MTL : 1 (20%) -Other : 2 (40%)	- BG : 0 -MTL : 0 - Diffuse cortical : 2 (40%) - Cerebellum : 0 -Other : 1 (20%)	(69, 75, 99, 149, 212, 228)
		DPPX	2		0	2 (100%)	0	-BG : 0 -MTL : 0 -Other : 0	- BG : 1 (50%) -MTL : 1 (50%) - Diffuse cortical : 0 - Cerebellum : 0 -Other : 1 (50%)	(150, 233)
		VGCC	2		1 (50°%)	1 (50%)	0	-BG : 0 -MTL : 1 (50%) -Other : 1 (50%)	- BG : 0 -MTL : 0 - Diffuse cortical : 0 - Cerebellum : 0 -Other : 1 (50%)	(113, 322)
		AChR	2		0	2 (100%)	0	-BG : 0 -MTL : 0 -Other : 0	- BG : 0 -MTL : 1 (50%) - Diffuse cortical : 1 (50%) - Cerebellum : 0 -Other : 1 (50%)	(268)
		Amphiphysin ^c	0^c		0	0	0	-BG : 0 -MTL : 0 -Other : 0	- BG : 0 -MTL : 0 - Diffuse cortical : 0 - Cerebellum : 0 -Other : 0	(179)
		IgLON5	1		1 (100%)	0	0	-BG : 1 (100%) -MTL : 0 -Other : 1 (100%)***	- BG : 0 -MTL : 0 - Diffuse cortical : 0 - Cerebellum : 0 -Other : 0	(324)
		mGluR5	3		0	3 (100%)	0	-BG : 0 -MTL : 0 -Other : 0	- BG : 0 -MTL : 0 - Diffuse cortical : 2 (67%) - Cerebellum : 1 (33%) -Other : 0	(271)
		IgG4	1		0	0	1 (100%)	-BG : 1 (100%) -MTL : 0 -Other : 0	- BG : 0 -MTL : 0 - Diffuse cortical : 0 - Cerebellum : 0 -Other : 1 (100%)	(25)
		Neuropile	1		0	1	0	-BG : 0 -MTL : 0 -Other : 0	- BG : 0 -MTL : 0 - Diffuse cortical : 1 (100%) - Cerebellum : 0 -Other : 0	(10)
Onconeuronal antibodies	Hu	11			6 (55%)	3 (27%)	2 (18%)	-BG : 1 (9%) -MTL : 6 (55%) -Other : 4 (36%)	-BG : 0 -MTL: 2 (18%) - Diffuse cortical : 5 (45%) - Cerebellum : 1 (9%) -Other : 0	(17, 63, 116, 146, 176, 245, 250, 268)
	Ma ½	7			3 (43%)	3 (43%)	0	-BG : 0 -MTL: 2 (29%) -Other : 1 (17%)	-BG : 0 -MTL : 3 (43%) - Diffuse cortical : 3 (43%) - Cerebellum : 0 -Other : 0	(10, 36, 62, 216, 252, 268)
	Yo	2			0	2 (100%)	0	-BG : 0 -MTL : 0 -Other : 0	-BG : 0 -MTL : 0 - Diffuse cortical : 0 - Cerebellum : 2 (100%) -Other : 0	(68, 282)
	CMRP5	2			0	2 (100%)	0	-BG : 0 -MTL : 0 -Other : 0	-BG : 2 (100%) -MTL : 1 (50%) - Diffuse cortical : 0 - Cerebellum : 0 -Other : 0	(302, 318)
	CV2^d	0^d			0	0	0	-BG : 0 -MTL : 0 -Other : 0	-BG :0 -MTL :0 - Diffuse cortical :0 - Cerebellum :0 -Other :0	(62)
	Ri	1			0	1 (100%)	0	-BG : 0 -MTL : 0 -Other: 0	-BG : 0 -MTL : 1 (100%) - Diffuse cortical : 0 - Cerebellum : 0 -Other : 0	(17)
	Unprecised	10			4 (40%)	0	6 (60%)	-BG : 0 -MTL : 9 (90%) -Other : 1 (10%)	-BG : 0 -MTL :0 - Diffuse cortical : 6 (60%) - Cerebellum : 0 -Other :0	(191, 240)
Rasmussen encephalitis^b		36			8 (22%)	25 (69%)	3 (8%)	-BG : 2 (6%) -MTL : 1 (3%) -Other : 14 (39%)	- BG : 5 (14%) -MTL : 0 - Diffuse cortical : 17 (47%) - Cerebellum : 0 -Other : 21 (58%)**	(35, 37, 47, 58, 78, 83, 102, 144, 183, 223, 303, 304, 307)
No antibodies		50			12 (24%)	22 (44%)	16 (39%)	-BG : 6 (12%) -MTL : 23 (46%) -Other : 13 (26%)	- BG : 1 (2%) -MTL : 16 (32%) - Diffuse cortical : 16 (32%) - Cerebellum : 2 (4%) -Other : 15 (30%)	(10, 11, 17 ,50, 52, 53, 62, 79, 92, 120, 130, 135, 196, 205, 208, 211, 250, 257, 283, 293, 295, 305)
n = number of PET with abnormal findings. ^a hypermetabolism predominant in frontal and temporal lobes associated with hypometabolism in posterior areas. ^b hemispheric hypometabolism. ^c normal findings on visual examination but abnormal metabolism in left MTL on semi-quantitative assessment. ^d normal findings. BG: basal ganglia; MTL: mesial temporal lobe; NMDAR = N-Methyl-D-Asparate Receptor ; VGKC = Voltage-gated potassium channel ; LGI1 = Leucine-rich glioma inactivated 1 ; CASPR2 = Contactin-associated protein-like 2 ; GAD = Glutamic Acid Decarboxylase ; GABA = Gamma-aminobutyric acid ; AMPAR = Alpha-Amino-3-Hydroxyl-5-Methyl-4-Isoxazolepropionic acid ; TPO = Thyroid peroxidase ; TG = thyreoglobulin ; DPPX = dipeptidyl-peptidase–like protein 6 ; VGCC = P/Q-type voltage-gated calcium channel ; AChR = anti-acetylcholine receptor ; IgLON5 = immunoglobulin-like cell adhesion molecule 5 ; mGluR5 = metabotropic glutamate receptor 5 ; IgG4 = immunoglobulin G4.

LGI1 associated encephalitis occurs most frequently and typically presents as limbic encephalitis symptoms. It generally affects men in their 40 s ^{10,18,20,21,48,49}. This is in contrast to, CASPR2 associated encephalitis which occurs in older men with a greater range of clinical expression predominantly gait disorders, neuromyotonia (sometimes associated with Morvan syndrome) and sleep disturbance ^{10,18,20,21,48,50}.

Brain ¹⁸F-FDG PET imaging is relatively similar with vast regions of hypermetabolism reported for both VGKC encephalitis entities, as detailed in Table 2. The majority of hypermetabolism are nevertheless located within the basal ganglia and mesial temporal lobes when the encephalitis is associated with anti-LGI1-Abs. It is interesting that mesial temporal lobe involvement is more frequently described in CASPR2 associated encephalitis. The meta-analysis of anti-VGKC-Ab mediated encephalitis identified a detection sensitivity of 82% [56%-94%] (supplemental Fig. 2).

2. NMDAR (N-Methyl-D-Asparate Receptor) aAbs

NMDAR encephalitis preferentially affects young women and is frequently associated with teratomas. These aAbs specifically bind to the cell surface and are often associated with autoimmune encephalitis resulting in a significant number of cases with brain ¹⁸F-FDG PET patterns in the literature (n = 124, Table 2). The clinical presentation usually progresses in four stages. The first is a prodromal phase with unspecific viral-like syndromes. This is followed by a typically psychotic phase. These two phases are usually followed by a mutic phase and finally a hyperkinetic phase with dysautonomia ^{10,18,20,21,48−51}.

The brain ¹⁸F-FDG PET patterns are clearly dependent on the phase of the disease with a mix of described hypermetabolism and hypometabolism but with a typical anteroposterior gradient, as detailed in Table 2. The high frequency of hypometabolism, mainly in associative posterior areas, reported in this entity is due to the delayed diagnosis of this encephalitis, the prodromal phase being unspecific. In most of the cases, a mixed pattern of basal ganglia hypermetabolism and diffuse cortical hypometabolism is reported. However, different patterns of hypermetabolism affecting cortical areas other than the basal ganglia and the mesial temporal lobes are also described including a significant proportion of hypometabolic regions in the cerebellum and other cortical areas, which reflects the vast differential clinical expression of this encephalitis. The NMDAR aAb meta-analysis revealed a detection sensitivity of 90% [75%-96%] (supplemental Fig. 2)

3. GAD (Glutamic Acid Decarboxylase) aAbs

Encephalitis associated with anti-GAD Abs is a relatively new entity, and thus less-well described in literature. This encephalitis is caused by aAbs directed against synaptic antigens and is principally characterized clinically by Stiff person syndrome and cerebellar ataxia ^9,10,18,49 but also more recently by refractory, mainly temporal, seizures ⁵². Consistently with this latter clinical presentation, the 36 cases reported in Table 2 exhibit brain ¹⁸F-FDG PET patterns mainly involving hypometabolism, associated with delayed diagnoses and typically affecting the mesial temporal lobes. The GAD aAb meta-analysis reported a detection sensitivity of 73% [55%-86%] (supplemental Fig. 2).

4. GABA (Gamma-AminoButyric Acid) aAbs

Similarly to GAD associated encephalitis, anti-GABA-Abs also bind to cell membrane antigens. As reported in Table 2, 17 cases with brain ¹⁸F-FDG PET are reported in the literature. In contrast to GAD associated encephalitis, those associated with anti-GABA-Abs lead to more obvious clinical symptoms, including status epilepticus and refractory epilepsy, cognitive deficits, psychiatric symptoms with depression, confusion and mutism ^{10,18,20,21,48,50}. Once again, the observed brain ¹⁸F-FDG PET patterns are related to the clinical characteristics with a majority of hypermetabolism, suggesting obvious early phase symptoms, predominantly involving the mesial temporal lobes. No data are currently available to determine the detection sensitivity of brain ¹⁸F-FDG PET associated with these aAbs.

5. AMPAR (Alpha-amino-3-hydroxyl-5-Methyl-4-isoxazolePropionic Acid Receptor) aAbs

Encephalitis associated with anti-AMPAR-Abs, directed against cell membrane antigens, are poorly described with only 5 cases of brain ¹⁸F-FDG PET reported in the literature (Table 2). Most of the patients are middle-aged women, with 70% of cases presenting with diverse tumors. The typical clinical presentation involves a limbic encephalitis, memory impairment, seizures and psychiatric symptoms ^{10,18,20,21,49}. In line with these diverse clinical manifestations, the observed brain ¹⁸F-FDG PET patterns are predominantly represented by diverse hypometabolism affecting several cortical areas other than the basal ganglia, the mesial temporal lobes or the cerebellum. Similarly to the anti-GABA-Abs, no publications are available to specifically determine the detection sensitivity of brain ¹⁸F-FDG PET in this entity.

6. Onconeuronal aAbs

Onconeuronal aAbs are found in paraneoplastic encephalitis. Approximately two-thirds of cases involve anti-neuronal-Abs, with neurological symptoms preceding the diagnosis of a tumor by up to 4 years ³⁶. It is particularly useful to perform whole-body ¹⁸F-FDG PET in these entities since the search for a primitive neoplastic tumor as well as dissemination of the primary lesion can be performed at the same time. A typical clinical evolution for this encephalitis subtype remains to be described ^18,48. Brain ¹⁸F-FDG PET pattern data in the literature are scarce and is based on a total of 30 cases when all anti-neuronal-Abs are combined (Table 2). For anti-Hu-Abs, a hypermetabolism of the mesial temporal lobe is preferentially reported whereas an equivalent number of hyper or hypometabolism in the mesial temporal lobes are described for the anti-Ma ½ Abs. In cases involving unspecified aAbs, it appears that hypermetabolic and mixed patterns specifically involving the temporal lobe hypermetabolisms and diffuse cortical hypometabolisms predominate. Interestingly, for the anti-Yo-Abs, the two reported cases showed hypometabolism of the cerebellum. The onconeuronal aAb meta-analysis revealed a detection sensitivity of 75% [48%-90%] (Supplemental Fig. 2).

7. Rasmussen’s encephalitis

Rasmussen’s encephalitis presumably involves an immune-mediated mechanism even though the pathophysiology of this progressive disease remains unknown. Although recent observations do not exclusively relate to a childhood pathology, a progressive epileptic disorder due to chronic unilateral encephalitis are the two core characteristics ⁵³. Brain ¹⁸F-FDG PET is a useful imaging tool in this setting since a typical pattern of hemispheric hypometabolism, exceeding the atrophy visualized in MRI, is observed and can help to diagnose the disease.

Only 1 publication involving at least 10 patients is available for Rasmussen's encephalitis and yields a sensitivity of 100% ³¹.

Additional observations from other rare aAbs encephalitis (≤ 5 cases in the literature) are detailed in Table 2. We also report the number of encephalitic cases with no specific aAbs (n = 50). Due to the probable heterogeneity of entities in this subgroup, the related brain ¹⁸F-FDG PET patterns are also diverse with a predominance of hypometabolism.

The Fig. 3 illustrates the typical brain ¹⁸F-FDG PET patterns for the main aAbs entities of autoimmune encephalitis.

Results from our systematic and exhaustive literature search confirm the importance of brain ¹⁸F-FDG PET in the diagnosis of autoimmune encephalitis and measure an overall detection sensitivity performance of 90% which is consistent with the meta-analysis (80% [75%-84%]). These diagnostic performances seem to be consistent across the main aAbs subtypes (VGKC, NMDAR, GAD and onconeuronal aAbs, supplemental Fig. 2). The diagnostic sensitivity of ¹⁸F-FDG PET from our meta-analysis is clearly higher than that typically reported for brain MRIs (between 56 to 61% in our current study and 25 to 50% in the literature ^48,54), which underscores the importance of systematically deploying this imaging modality in the initial diagnosis of suspected encephalitis cases. This detection sensitivity for assessing autoimmune encephalitis is very helpful, since diagnosis of the disease is currently delayed due to non-specific clinical symptoms and moderate performances of biological and imaging biomarkers¹. Neurologists, radiologists and nuclear physicians should also be cognizant of the benefits of brain ¹⁸F-FDG PET in the initial diagnostic assessment of autoimmune encephalitis.

The different brain ¹⁸F-FDG PET pattern results from our exhaustive literature search underlines a similarity observed among the neurodegenerative diseases ⁵⁵, ¹⁸F-FDG PET abnormalities are strongly related to clinical symptoms. This allows typical brain ¹⁸F-FDG PET patterns to be defined. The mesial temporal lobe involvement is observed in autoimmune encephalitis associated with limbic encephalitis (VGKC, GAD, GABA aAbs). Autoimmune encephalitis associated with a variety of clinical symptoms yield mixed hyper and hypometabolic patterns (NMDAR aAbs). Hypermetabolic patterns are associated with more obvious clinical symptoms (GABA aAbs) than hypometabolic ones (GAD aAbs), but the delay between the onset of symptoms and ¹⁸F-FDG PET needs to be taken into account, as hypermetabolism is also observed in the acute phase of disease. In certain specific cases, the brain ¹⁸F-FDG PET pattern is quasi pathognomonic of an autoimmune encephalitis entity (Rasmussen’s encephalitis) with more extensive metabolic alteration than morphologic anomalies. Moreover, to reveal additional specific signs of encephalitis in paraneoplastic syndromes associated with autoimmune encephalitis, ¹⁸F-FDG PET is able to provide an extensive assessment of neoplasia by performing a whole-body ¹⁸F-FDG PET simultaneously to the brain ¹⁸F-FDG PET ^56,57.

It would have been interesting to report the specificity and accuracy of brain ¹⁸F-FDG PET imaging in autoimmune encephalitis. Indeed, some brain ¹⁸F-FDG PET patterns, especially diffuse hypometabolism, are not specific and are also observed in neurodegenerative diseases ⁵⁵. Unfortunately, false positive results or true negative cases can only be identified from well-conducted prospective studies which are rare in the current literature ^27,29. The performance and ¹⁸F-FDG PET patterns observed in our meta-analysis are mainly influenced by the time from the onset of symptoms, which is not always clearly reported in studies, thereby mistaking patterns of hyper- and hypometabolic areas, which may be related to the course of the disease ^15,58.

Overall, our current systematic and exhaustive literature search and meta-analysis focus on sensitivity diagnostic performances as well as specific brain ¹⁸F-FDG PET patterns in autoimmune encephalitis. We report the convincing performance of brain ¹⁸F-FDG PET in the diagnosis of autoimmune encephalitis, which provides a helpful diagnostic imaging tool to overcome the challenges of diagnosing this entity and underscores the importance of including diagnostic ¹⁸F-FDG PET in any future recommendations. Specific metabolic patterns corresponding to the main autoimmune encephalitis Ab subtypes value-adds to the diagnostic assessment. Further prospective studies are nevertheless required to further define performances in terms of specificity and accuracy.

Funding

None

Conflicts of interest/competing interests

The authors disclose no potential conflicts of interest related to the present work.

Ethics approval and consent to participate

This article does not contain any studies with human participants or animals performed by any of the authors.

Consent for publication

The consent has been obtained for each patient for whom their FDG PET images are included in the manuscript.

Availability of data and material

The data that support the findings of this study are available on request from the corresponding author (AV)

Code availability

Not applicable

Authors' contributions

All authors contributed significantly to the analysis and interpretation of the data (MB, MD, MBC, AV), to the writing of the manuscript (EM, AV) and to the revision of the manuscript (EG, AK, LT, AV).

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published 07 Mar, 2021

Read the published version in European Journal of Nuclear Medicine and Molecular Imaging →

Editorial decision: Accept
02 Mar, 2021
Reviewers invited by journal
26 Feb, 2021
Reviews received at journal
26 Feb, 2021
First submitted to journal
14 Feb, 2021
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14 Feb, 2021

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Brain 18F-FDG PET for the diagnosis of autoimmune encephalitis: a systematic review and a meta-analysis

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