Measuring brain glucose metabolism in order to predict response to antidepressant or placebo: A randomized clinical trial
Autor: | John Gardus, Kathryn R. Hill, Ramin V. Parsey, Elizabeth Bartlett, Christine DeLorenzo, Greg Perlman |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Oncology
MDD major depressive disorder PET Positron Emission Tomography Treatment response law.invention Escitalopram Randomized controlled trial law SSRIs selective serotonin reuptake inhibitors HDRS-17 Hamilton Depression Rating Scale FDG-PET Depression (differential diagnoses) MADRS Montgomery–Åsberg Depression Rating Scale Prediction of response vPFC ventral prefrontal cortex Brain Regular Article SCID-IV structured clinical interview for diagnosis Antidepressive Agents Treatment Outcome Neurology Major depressive disorder Antidepressant MRGlu metabolic rate of glucose uptake medicine.drug medicine.medical_specialty RN raphe nuclei Randomization Cognitive Neuroscience Computer applications to medicine. Medical informatics R858-859.7 Placebo behavioral disciplines and activities FDG-PET 2-[18F]-fluorodeoxyglucose - Positron Emission Tomography Double-Blind Method Internal medicine Dynamic imaging mental disorders medicine Humans Radiology Nuclear Medicine and imaging RC346-429 Depressive Disorder Major business.industry medicine.disease Confidence interval carbohydrates (lipids) Glucose FDG 2-[18F]-fluorodeoxyglucose 5-HT1A serotonin 1A receptor Neurology (clinical) Neurology. Diseases of the nervous system business SimE Simultaneous Estimation |
Zdroj: | NeuroImage: Clinical, Vol 32, Iss, Pp 102858-(2021) NeuroImage : Clinical |
ISSN: | 2213-1582 |
Popis: | Highlights • A clinically relevant method of predicting MDD treatment efficacy is needed. • The present investigation applies dynamic FDG-PET using blood as a reference. • FDG-PET was assessed in the raphe nuclei, ventral prefrontal cortex and insula. • Regional pretreatment metabolism does not relate to symptom severity decrease. • Predictive FDG-PET signal may not be generalizable to heterogeneous MDD cohorts. There is critical need for a clinically useful tool to predict antidepressant treatment outcome in major depressive disorder (MDD) to reduce suffering and mortality. This analysis sought to build upon previously reported antidepressant treatment efficacy prediction from 2-[18F]-fluorodeoxyglucose - Positron Emission Tomography (FDG-PET) using metabolic rate of glucose uptake (MRGlu) from dynamic FDG-PET imaging with the goal of translation to clinical utility. This investigation is a randomized, double-blind placebo-controlled trial. All participants were diagnosed with MDD and received an FDG-PET scan before randomization and after treatment. Hamilton Depression Rating Scale (HDRS-17) was completed in participants diagnosed with MDD before and after 8 weeks of escitalopram, or placebo. MRGlu (mg/(min*100 ml)) was estimated within the raphe nuclei, right insula, and left ventral Prefrontal Cortex in 63 individuals. Linear regression was used to examine the association between pretreatment MRGlu and percent decrease in HDRS-17. Additionally, the association between percent decrease in HDRS-17 and percent change in MRGlu between pretreatment scan and post-treatment scan was examined. Covariates were treatment type (SSRI/placebo), handedness, sex, and age. Depression severity decrease (n = 63) was not significantly associated with pretreatment MRGlu in the raphe nuclei (β = -2.61e-03 [-0.26, 0.25], p = 0.98), right insula (β = 0.05 [-0.23, 0.32], p = 0.72), or ventral prefrontal cortex (β = 0.06 [-0.23, 0.34], p = 0.68) where β is the standardized estimated coefficient, with a 95% confidence interval, or in whole brain voxelwise analysis (family-wise error correction, alpha = 0.05). MRGlu percent change was not significantly associated with depression severity decrease (n = 58) before multiple comparison correction in the RN (β = 0.20 [-0.07, 0.47], p = 0.15), right insula (β = 0.24 [-0.03, 0.51], p = 0.08), or vPFC (β = 0.22 [-0.06, 0.50], p = 0.12). We propose that FDG-PET imaging does not indicate a clinically relevant biomarker of escitalopram or placebo treatment response in heterogeneous major depressive disorder cohorts. Future directions include focusing on potential biologically-based subtypes of major depressive disorder by implementing biomarker stratified designs. |
Databáze: | OpenAIRE |
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