Persistent Cerebral 18-FDG PET Changes in Patients With Long COVID Presenting With Fatigue and Post Exertional Malaise, 2026, Ganesh et al

[forestglip]

Persistent Cerebral 18-FDG PET Changes in Patients With Long COVID Presenting With Fatigue and Post Exertional Malaise

Spoiler: Authors

Ganesh, Ravindra; Nair, Kaavya; Grach, Stephanie L.; Croghan, Ivana T.; Yadav, Siddhant; Hurt, Ryan T.; Mueller, Michael R.

Abstract
Objective
Long COVID (LC) refers to the long-term symptoms occurring after SARS-CoV-2 infection and resolution of the initial disease prodrome. While LC is increasingly recognized, knowledge about its biomarkers is still limited.

This study examines imaging findings in 18 F-FDG PET-CT scans in 40 patients with LC from an academic LC Clinic, for potential imaging biomarkers.

Methods
This study included patients aged 18 and older with confirmed positive SARS-CoV-2 PCR test and at least 28 days post-symptom onset. 18 F-FDG PET-CT scans were performed, and brain metabolic activity was compared to a control database to generate Z-scores. Participants were grouped based on their clinical phenotype and Z-scores of different brain regions were analyzed using t-tests.

Results
The study group was mainly female (70%), with a median age of 53 years, and predominantly non-Hispanic White (90%). Most had pre-existing conditions such as gastrointestinal, cardiovascular, endocrine, and psychiatric disorders.

The findings showed significant cerebral hypometabolism in 29 patients with fatigue and post-exertional malaise (PEM), particularly in the left sensorimotor cortex (p=0.0253) and bilateral primary visual cortex (right: p=0.0096, left: p=0.0016), which persisted up to two years after infection.

Conclusions
In summary, this study identified persistent cerebral hypometabolism in LC patients, especially those with fatigue with PEM, up to two years post-infection.

These results suggest that 18 F-FDG PET-CT could be a valuable tool for diagnosing and managing LC. Further research is essential to confirm these findings and improve treatment strategies for patients with LC.

Web | DOI | PDF | Journal of Primary Care & Community Health | Open Access

 

[forestglip]

There seems to be an inconsistency regarding multiple test correction. The methods seem to suggest it was used:

The Z-scores were analyzed for normality using Shapiro-Wilk test and then using an ANOVA t-test with repeated measures and Bonferroni correction for multiple comparisons and p-values were considered significant if <0.05.

But the discussion section recommends future studies use Bonferroni correction in case of false positives in this study:

Lastly, given that we simultaneously performed multiple comparisons between brain regions, there is a recognized potential for false positives. Future studies in this arena would benefit from either comparison of a smaller number of variables defined a priori based on the existing literature or using a statistical method for multiple comparisons such as the Bonferroni correction.

Table 2 includes the p-values for each region, but uses a threshold of p<0.05. It's possible they multiplied the raw p-values by the number of comparisons and compared to 0.05, which would still be Bonferroni correction, but then I would expect at least some of the p-values to be 1. There were 25 tests, so if any raw p-values were equal to or greater than 0.04, then the adjusted value would be 1 for these. Instead, the highest is 0.6477.

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It's also unclear what the methods mean by "ANOVA t-test with repeated measures", as they don't explain how ANOVA was used or what the repeated measures were. The table with results just says the p-values were based on an "Independent samples t-test".

 

[SNT Gatchaman]

Another of the limitations that may undermine the analysis —

Per our institutional standard, the 18F-FDG activity at the pons was used as the standard for normalization of the other areas of the brain, which is based on data suggesting that the metabolic activity of the pons is not significantly affected by aging or neurodegenerative diseases.

Data is conflicted as to whether the pons is metabolically involved in patients with LC, but were the pons to be metabolically involved, it would be an inappropriate comparison for normalization, affecting the geographic location, magnitude, and direction of effect.

We have no evidence that the cognitive dysfunction in LC/ME relates to the processes of aging or neurodegeneration. With whatever might be going on metabolically, I doubt the pons would be uniquely metabolically unaffected.

(Also hypometabolism here is purely indicating glucose hypometabolism, via FDG uptake. I don't know if we have any ME/CFS brain PET imaging studies using other substrates like ketones, fatty acids, amino acids. Almost certainly* we haven't, and they could be informative. The only other PET studies I've seen are using things like specific receptors or TSPO to look at microglial activation, rather than cellular metabolism per se.)

Figure 2. Representative18 F-FDG PET scan for a patient with Long COVID showing cerebral hypometabolism. The scan above shows the unprocessed18 F-FDG PET scan of the brain, and the below image has been processed to demonstrate the comparison to the age- and gender-matched normal database using the pons to normalize the comparison. This scan shows near global hypometabolism particularly pronounced in the occipital lobes, correlating with the participant’s symptoms of cognitive dysfunction and fatigue with post exertional malaise

I've arrowed the pons in red in the second panel. The scale markers aren't clear in the paper's graphic, but in the first panel will be the absolute SUV (Standardised Uptake Value) from 0 at the bottom to something like 12 at the top in red. I think the second panel is relative and reversed, running from 0 in grey at the bottom to say -10 at the top in red. So (normalised to HC/pons) the brainstem is in grey, -0, while most of the brain is -1 to -2 and the occipital cortex in green is around -4.

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* Eg recent mini-review Metabolic neuroimaging of myalgic encephalomyelitis/chronic fatigue syndrome and Long-COVID (2025) suggests only FDG PET.