PMID- 33866300
OWN - NLM
STAT- MEDLINE
DCOM- 20210730
LR  - 20211223
IS  - 2213-1582 (Electronic)
IS  - 2213-1582 (Linking)
VI  - 30
DP  - 2021
TI  - Structural MRI and functional connectivity features predict current clinical 
      status and persistence behavior in prescription opioid users.
PG  - 102663
LID - S2213-1582(21)00107-8 [pii]
LID - 10.1016/j.nicl.2021.102663 [doi]
LID - 102663
AB  - Prescription opioid use disorder (POUD) has reached epidemic proportions in the 
      United States, raising an urgent need for diagnostic biological tools that can 
      improve predictions of disease characteristics. The use of neuroimaging methods 
      to develop such biomarkers have yielded promising results when applied to 
      neurodegenerative and psychiatric disorders, yet have not been extended to 
      prescription opioid addiction. With this long-term goal in mind, we conducted a 
      preliminary study in this understudied clinical group. Univariate and 
      multivariate approaches to distinguishing between POUD (n = 26) and healthy 
      controls (n = 21) were investigated, on the basis of structural MRI (sMRI) and 
      resting-state functional connectivity (restFC) features. Univariate approaches 
      revealed reduced structural integrity in the subcortical extent of a previously 
      reported addiction-related network in POUD subjects. No reliable univariate 
      between-group differences in cortical structure or edgewise restFC were observed. 
      Contrasting these mixed univariate results, multivariate machine learning 
      classification approaches recovered more statistically reliable group 
      differences, especially when sMRI and restFC features were combined in a 
      multi-modal model (classification accuracy = 66.7%, p < .001). The same 
      multivariate multi-modal approach also yielded reliable prediction of individual 
      differences in a clinically relevant behavioral measure (persistence behavior; 
      predicted-to-actual overlap r = 0.42, p = .009). Our findings suggest that sMRI 
      and restFC measures can be used to reliably distinguish the neural effects of 
      long-term opioid use, and that this endeavor numerically benefits from 
      multivariate predictive approaches and multi-modal feature sets. This can serve 
      as theoretical proof-of-concept for future longitudinal modeling of prognostic 
      POUD characteristics from neuroimaging features, which would have clearer 
      clinical utility.
CI  - Copyright (c) 2021 The Author(s). Published by Elsevier Inc. All rights reserved.
FAU - Mill, Ravi D
AU  - Mill RD
AD  - Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 
      07102, USA.
FAU - Winfield, Emily C
AU  - Winfield EC
AD  - Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 
      07102, USA.
FAU - Cole, Michael W
AU  - Cole MW
AD  - Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 
      07102, USA.
FAU - Ray, Suchismita
AU  - Ray S
AD  - Department of Health Informatics, School of Health Professions, Rutgers 
      Biomedical and Health Sciences, Newark, NJ 07103, USA. Electronic address: 
      shmita@shp.rutgers.edu.
LA  - eng
GR  - R01 AG055556/AG/NIA NIH HHS/United States
GR  - R01 MH109520/MH/NIMH NIH HHS/United States
GR  - R03 DA044496/DA/NIDA NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20210407
PL  - Netherlands
TA  - Neuroimage Clin
JT  - NeuroImage. Clinical
JID - 101597070
RN  - 0 (Analgesics, Opioid)
SB  - IM
MH  - *Analgesics, Opioid
MH  - Humans
MH  - Magnetic Resonance Imaging
MH  - Neuroimaging
MH  - *Opioid-Related Disorders/diagnostic imaging
MH  - Prescriptions
PMC - PMC8060550
OTO - NOTNLM
OT  - Addiction
OT  - Functional connectivity
OT  - Machine learning
OT  - Opioid
OT  - Resting state
OT  - Structural MRI
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2021/04/19 06:00
MHDA- 2021/07/31 06:00
PMCR- 2021/04/07
CRDT- 2021/04/18 20:55
PHST- 2020/12/14 00:00 [received]
PHST- 2021/03/24 00:00 [revised]
PHST- 2021/04/02 00:00 [accepted]
PHST- 2021/04/19 06:00 [pubmed]
PHST- 2021/07/31 06:00 [medline]
PHST- 2021/04/18 20:55 [entrez]
PHST- 2021/04/07 00:00 [pmc-release]
AID - S2213-1582(21)00107-8 [pii]
AID - 102663 [pii]
AID - 10.1016/j.nicl.2021.102663 [doi]
PST - ppublish
SO  - Neuroimage Clin. 2021;30:102663. doi: 10.1016/j.nicl.2021.102663. Epub 2021 Apr 
      7.