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. Author manuscript; available in PMC: 2025 May 1.
Published in final edited form as: Schizophr Res. 2024 Mar 26;267:138–140. doi: 10.1016/j.schres.2024.03.009

Identifying clinical predictors for considering brain FDG-PET imaging in patients with catatonia: a case-control study

Mohammad Ghafouri 1,*, Laura Duque 1,2,3,*, Liliana Patarroyo Rodriguez 1, Kemuel L Philbrick 1, Rodolfo Savica 4, Vanessa Pazdernik 5, John D Port 6, Teresa A Rummans 1,7, Balwinder Singh 1
PMCID: PMC11102829  NIHMSID: NIHMS1985447  PMID: 38537394

1. Introduction

Catatonia, a complex neuropsychiatric syndrome, exhibits abnormalities in motor function, behavior, and affective regulation. Neuroimaging, particularly 18F-FDG-PET, has unveiled altered neural activity in key regions like frontal lobes, basal ganglia, thalamus, and supplementary motor area (Cattarinussi et al., 2022). Despite its potential, FDG-PET is primarily used in research, not standard clinical practice for diagnosing psychiatric disorders, including catatonia (Duque et al., 2024). Additionally, there is a lack of data on naturalistic factors influencing clinicians in ordering FDG-PET for catatonia patients.

Therefore, we conducted this case-control study to investigate the clinical and diagnostic factors associated with ordering of brain FDG-PET among patients hospitalized with catatonia. Secondarily, we explored the differences in brain FDG-PET findings among catatonia subtypes—catatonia associated with psychiatric diagnoses (C-APD) versus catatonia due to another medical condition (C-AMC).

2. Methods

We included adults hospitalized at Mayo Clinic in Rochester, Minnesota, between May 1, 2001, and May 1, 2021, with catatonia diagnosis at time of admission or during hospitalization and provided research consent. Further details regarding study methodology are available in the supplement. Patients with catatonia were identified from the electronic medical records (EMR) (Kumar et al., 2023) using the ICD-10-CM codes and a keyword search of catatonia related symptoms in the EMR. Catatonia diagnosis was confirmed by manual chart review. Catatonia was classified as C-APD if the associated cause was a psychiatric illness and C-AMC if the associated cause was a medical condition. Catatonia symptoms were assessed using the Bush-Francis Catatonia Rating Scale (BFCRS) scale by reviewing EMR (Bush et al., 1996). The Clinical Global Impression (CGI) scale was used to retrospectively assess the severity of catatonia symptoms and treatment response (Guy, 1976).

Catatonia patients who underwent brain FDG-PET imaging as part of their diagnostic work-up were identified from EMR. A Behavioral Neurology expert (RS) analyzed FDG-PET images for hypometabolism using cortex ID software, blinded to patient allocation. Each patient with catatonia who underwent FDG-PET (n=9) was matched with at least 4 control subjects (n=37) by age, sex, and hospitalization year, from the same catatonia cohort without FDG-PET. Demographic, clinical, laboratory, and FDG-PET data, including hypometabolic brain regions (for cases only), were extracted.

To assess predictors for undergoing FDG-PET, we conducted univariate analyses, followed by multivariate logistic regression. Clinical variables with a statistically significant relationship to FDG-PET orders were included in a separate multivariate logistic regression. To compare brain FDG-PET findings between C-APD and C-AMC, we employed Chi-square/Fisher’s exact tests for categorical data, and Student’s t-tests/Mann-Whitney U-tests for continuous data.

3. Results

Among 250 hospitalized catatonia patients, only 3.6% (n=9) underwent brain FDG-PET, with a mean age of 57.7 years and 44% being female. These 9 cases were matched to 37 controls with catatonia who did not undergo brain FDG-PET. There were no significant differences in demographic and clinical characteristics between the cases and controls (Supplementary Table-1). Patients with schizophrenia spectrum disorders and catatonia were significantly less likely to undergo brain FDG-PET than non-schizophrenia spectrum disorders with catatonia (5.6% vs 36.4%, p=0.027). This association persisted after adjusting for age and sex (OR 0.059, 95 % CI 0.003 – 0.454, p = 0.020).

Among 9 patients who underwent FDG-PET, 5 had C-APD, and 4 had C-AMC. Overall, occipital and caudate hypometabolism were most prevalent (78%), followed by frontal lobe changes (56%), limbic system (44%), and less commonly parietal/temporal abnormalities (33%). C-AMC patients showed greater parietal and temporal hypometabolism than C-APD patients (75% vs 0%, p=.018), Table-1. There was no difference in length of stay between the 2 subtypes. Individual patient details are provided in supplementary Table-2.

TABLE 1.

Quantitative Metabolism Results by Brain Regions in C-APD vs C-AMC subgroups.

Variables C-APD n=5 C-AMC n=4 P value
Mean age (Years, SD) 56.2 ± 15.2 59.5 ± 7.0 0.68
Female: Male, n (%) 2 (40%) 2 (50%) 1
BFCRS (Value, SD) 16.6±6.3 17.3±8.3 0.90
Length of stay (days, SD) 86.2 ± 61.7 26.2 ± 15.3 0.096
Days of symptoms until diagnosis (days, SD) 24.0 ± 34.4 61.8 ± 66.1 0.35
Length of catatonia episode (days, SD) 61.0±38.3 85.5±62.6 0.52
Mood state, Depressed, n (%) 1 (20%) 3 (75%) 0.38
Mood state, Mania/hypomania, n (%) 2 (40%) 1 (25%)
Mood state, Psychosis, n (%) 2 (40%) 0 (0%)
Brain involvement regions in FDG-PET imaging Frontal, n (%) 2 (40%) 3 (75%) .294
Parietal, n (%) 0 (0%) 3 (75%) .018
Temporal, n (%) 0 (0%) 3 (75%) .018
Occipital, n (%) 4 (80%) 3 (75%) .858
Limbic, n (%) 2 (40%) 2 (50%) .765
Caudate, n (%) 4 (80%) 3 (75%) .858
Asymmetry, n (%) 1 (20%) 1 (25%) .858
Diffuse, n (%) 1 (20%) 3 (75%) .099
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4. Discussion

This study highlights that patients with schizophrenia spectrum disorders were less likely to undergo FDG-PET compared to those with other psychiatric illnesses. The observed finding may stem from the common association of catatonia with schizophrenia spectrum disorders, overlooking its manifestation across various conditions. New catatonic symptoms in patients with schizophrenia spectrum disorders might not prompt additional diagnostic testing, potentially missing atypical cases. Despite the validity of this assumption in many instances, a subset of individuals could benefit from further diagnostic evaluation.

Brain FDG-PET is a promising tool for assesing brain metabolic alterations in individuals with psychiatric disorders(Hazlett et al., 2019). C-AMD patients exhibit greater temporo-parietal hypometabolism compared to C-APC patients. Neuroimaging studies in delirium have revealed predominant involvement of parietal and temporal regions, likely reflecting underlying medical pathologies (Choi et al., 2012). The more extensive parieto-temporal changes seen in C-AMC cases may relate to the nature of the inciting structural and metabolic disease process. Prior case reports have evaluated FDG-PET findings in catatonia patients in both C-APD and C-AMC groups (Endres et al., 2020; Iseki et al., 2009; Lee et al., 2014; Pompanin et al., 2021; Truong et al., 2018) demonstrating hypometabolism affecting various brain regions. The higher occipital findings may relate to differences in catatonia manifestations and underlying etiologies in our cohort. A recent study on 33 patients with anti-NMDA receptor encephalitis, where most had catatonia, showed severe bilateral occipital and parietal hypometabolism on FDG-PET, aligning with our findings (Kerik-Rotenberg et al., 2020). The differences across studies may reflect heterogeneity in clinical presentation and etiology. Larger studies categorizing etiology may provide a more comprehensive understanding of regional abnormalities in catatonia.

Our study has several limitations including the small sample size and retrospective study design. The etiological classification of catatonia as C-AMC versus C-APD was based on available clinical data, without pathological confirmation of the associated medical conditions in some cases. Finally, CGI and BFCRS scores were retrospectively compiled through chart review and may be subject to documentation biases. The variability in regional brain metabolic abnormalities across neuroimaging studies of catatonia highlights the heterogeneity of this syndrome and the need for larger samples to categorize clinical subtypes. Linking neuroimaging findings to their clinical phenomenology may advance pathophysiological models of catatonia and enable more targeted therapeutics directed at modulating the specific neural circuit disturbances underlying catatonia symptoms.

5. Conclusion

This hypothesis generating study suggests that individuals with schizophrenia spectrum disorders may be less likely to undergo a brain FDG-PET imaging for catatonia assessment. In catatonia cases, reduced metabolic activity was notably observed in the occipital lobe, caudate, limbic system, and frontal lobes. Patterns varied by subtype, with more extensive involvement of parietal and temporal regions in patients with catatonia due to medical conditions. Further research in larger studies is needed to explore and differentiate catatonia subtypes.

Supplementary Material

Supplement

Acknowledgement:

We want to express our heartfelt thanks to the study participants.

Funding sources

This research was supported by the Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA. This publication was made possible by the Mayo Clinic CTSA through grant number UL1TR002377 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH)

Footnotes

Ethics approval: The study was approved by the Mayo Clinic Institutional Review Board.

Consent for participate: Data was only extracted for the patients who provided consent.

Conflict of interests.

Dr. Singh has received research grant support from Mayo Clinic, National Network of Depression Centers (NNDC), and Breakthrough Discoveries for thriving with Bipolar Disorder(BD2). The remaining authors report no potential competing interests.

Data availability:

The dataset generated during this study is available from the corresponding author on reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement
NIHMS1985447-supplement-Supplement.docx (30.5KB, docx)

Data Availability Statement

The dataset generated during this study is available from the corresponding author on reasonable request.

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