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
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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