Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticlePediatric Neuroimaging
Open Access

DTI of Opioid-Exposed Fetuses Using ComBat Harmonization: A Bi-Institutional Study

J.A. Dudley, U.D. Nagaraj, S. Merhar, F.T. Mangano, B.M. Kline-Fath, X. Ou, A. Acheson and W. Yuan
American Journal of Neuroradiology August 2023, DOI: https://doi.org/10.3174/ajnr.A7951
J.A. Dudley
aFrom the Department of Radiology and Medical Imaging (J.A.D., U.D.N., B.M.K.-F., W.Y.)
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for J.A. Dudley
U.D. Nagaraj
aFrom the Department of Radiology and Medical Imaging (J.A.D., U.D.N., B.M.K.-F., W.Y.)
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for U.D. Nagaraj
S. Merhar
bPerinatal Institute, Division of Neonatology (S.M.)
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for S. Merhar
F.T. Mangano
cDepartment of Neurosurgery (F.T.M.), Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for F.T. Mangano
B.M. Kline-Fath
aFrom the Department of Radiology and Medical Imaging (J.A.D., U.D.N., B.M.K.-F., W.Y.)
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for B.M. Kline-Fath
X. Ou
eDepartments of Radiology (X.O.)
fPediatrics (X.O.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for X. Ou
A. Acheson
gPsychiatry (A.A.), University of Arkansas for Medical Sciences, Little Rock, Arkansas
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for A. Acheson
W. Yuan
aFrom the Department of Radiology and Medical Imaging (J.A.D., U.D.N., B.M.K.-F., W.Y.)
dUniversity of Cincinnati College of Medicine (J.A.D., U.D.N., S.M., F.T.M., B.M.K.-F., W.Y.), Cincinnati, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for W. Yuan
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Abstract

BACKGROUND AND PURPOSE: The underlying mechanisms leading to altered cognitive, behavioral, and vision outcomes in children with prenatal opioid exposure are yet to be fully understood. Some studies suggest WM alterations in infants and children with prenatal opioid exposure; however, the time course of WM changes is unknown. We aimed to evaluate differences in diffusion tensor imaging MRI parameters in the brain between opioid exposed fetuses and normal controls.

MATERIALS AND METHODS: This is a pilot, prospective cohort study in which subjects in the third trimester of pregnancy underwent fetal DTI of the brain with 20 noncolinear diffusion directions and a b-value of 500 s/mm2 at 2.5-mm isotropic resolution.

RESULTS: The study included a total of 26 fetuses, 11 opioid-exposed (mean gestational age, 32.61 [SD, 2.35] weeks) and 15 unexposed controls (mean gestational age, 31.77 [SD, 1.68] weeks). After we adjusted for gestational age, fractional anisotropy values were significantly higher in opioid-exposed fetuses relative to controls in 8 WM tracts: the bilateral lemniscus (left: P = .017; right: P = .020), middle cerebellar peduncle (P = .027), left inferior cerebellar peduncle (P = .026), right sagittal stratum (P = .040), right fornix stria terminalis (P = .022), right inferior fronto-occipital fasciculus (P = .011), and the right uncinate fasciculus (P = .033). Significant alteration was also identified in other DTI indices involving a series of brain regions.

CONCLUSIONS: Our data demonstrate initial evidence of cerebral WM microstructural differences between opioid-exposed fetuses and unexposed controls. Further studies in larger patient populations will be needed to fully understand these findings.

ABBREVIATIONS:

AD
axial diffusivity
FA
fractional anisotropy
GA
gestational age
MD
mean diffusivity
RD
radial diffusivity
SSFSE
single-shot fast spin-echo
SVR
slice-to-volume registration

Opioid use during pregnancy remains a common problem in the United States, with 7% of pregnant women reporting the use of prescription opioid pain relievers during pregnancy and 0.8% of women having an opioid-related diagnosis at the time of delivery.1,2 Children with prenatal opioid exposure overall demonstrate lower educational achievement, compromised development, and higher rates of behavioral issues by school age.3⇓-5 However, the underlying neural mechanisms leading to these poor outcomes are still unknown. There is a growing body of literature describing neonatal brain differences in opioid-exposed infants, including lower regional brain volumes, increased WM injury, and alterations in functional connectivity.6⇓⇓⇓⇓-11 It is unknown whether these changes are present before birth.

Fetal MR imaging, which has become an accessible tool for the clinical evaluation of the developing brain, has the potential to answer some of these questions.12 Pilot studies using fetal MR imaging have described smaller brain sizes in fetuses with prenatal opioid exposure.13 DTI, a technique sensitive to WM abnormalities, has yielded growing evidence suggesting that opioid exposure may impact WM development in children as early as the neonatal period; however, WM microstructure in utero of opioid-exposed fetuses remains to be explored.14⇓-16 Fetal DTI has historically been challenging due to artifacts from excessive fetal motion. With recent advances in imaging data-processing and analysis, including slice-to-volume registration (SVR), fetal DTI has become more robust and reliable, making it possible to extend the study of WM microstructure into the prenatal period.17 This study aimed to assess WM integrity on the basis of in utero DTI from fetuses with opioid exposure during gestation.

MATERIALS AND METHODS

Study Design and Patients

This prospective study was approved by the institutional review board at each institution. Written informed consent was obtained from all study participants. Participants were recruited from the Cincinnati Children’s Hospital Medical Center (CCHMC) and the University of Arkansas for Medical Sciences (UAMS) from July 1, 2020, through December 31, 2021. Women in the third trimester of pregnancy with and without opioid use during the current pregnancy were recruited to undergo fetal MR imaging for investigational purposes only. Opioid and other substance use (or lack thereof) during the current pregnancy was determined by maternal self-report and maternal chart review. Substantial opioid use was defined as daily reported opioid use during most of the pregnancy to date, with most patients on a daily opioid-use disorder maintenance medication such as buprenorphine or methadone. Patients were recruited through a combination of flyers seeking volunteers in obstetrics and substance abuse clinics, e-mails to hospital employees seeking volunteers, and by connecting with previous research participants who agreed to be contacted for future research studies.

Eligibility for enrollment was determined by a study coordinator by telephone interview. Inclusion criteria included being at least 18 years of age, singleton pregnancy, and gestational age (GA) of at least 26 weeks. Exclusion criteria included an inability to supply the name of at least 1 additional person to contact if the participant could not be reached, a known genetic disorder, fetal abnormality identified on prenatal sonography, a nonviable fetus, contraindications to MR imaging, and the inability of the participant to enter the magnet bore due to body habitus. During this telephone interview, the study coordinator also informed potential participants that they would undergo a further interview regarding opioid exposure at the time of the fetal MR imaging appointment.

MR Imaging Acquisition

Fetal MR imaging examinations were performed using a 3T MR imaging system (Ingenia; Philips Healthcare) at CCHMC and a 3T system (Magnetom Prisma; Siemens) at UAMS. Both sites used a phased array abdominal imaging coil. Sedation was not used. Patients were placed in the left lateral decubitus position unless they reported feeling more comfortable in the supine position.

Examinations included localizer sequences followed by sagittal steady-state free precession images through the uterus with 5-mm-thick interleaved contiguous slices. T2 HASTE/single-shot fast spin-echo (SSFSE) images of the fetal brain were obtained in the axial, sagittal, and coronal planes with 2-mm-thick interleaved contiguous slices. Fetal DTI data were acquired in 20 noncolinear diffusion directions with a b-value of 500 s/mm2 and resolution of 2.5 mm isotropic.

MR Imaging Data-Processing and Analysis

Orthogonally-acquired 2D stacks of T2 HASTE/ SSFSE images were motion-corrected and reconstructed into a single volumetric image with 1-mm3 isotropic resolution using the niftymic toolkit deployed in a docker image (https://hub.docker.com/r/renbem/niftymic), which additionally calculated an affine-registration matrix to a GA-matched template.18 Rigid-body transformation matrices describing the coregistration of the b=0 diffusion image to the reconstructed T2 HASTE image were calculated using the FMRIB Software Library (FSL; www.fmrib.ox.ac.uk/fsl), Version 6.0.4. DTI processing was performed using FSL as well. SVR was used to correct for excessive head motion and artifacts in the fetal DTI. Each acquired EPI section was individually aligned to a target estimation of the 3D fetal brain anatomy so that all data could be projected from the scanner coordinates to anatomic coordinates that are static relative to the fetal brain. DTI measures, including fractional anisotropy (FA) and mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), respectively, were extracted from WM regions derived from a nonlinear registration of the Johns Hopkins University WM atlas (Mori et al,19 2005) into a GA-matched template space (Fig 1).20

FIG 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIG 1.

Illustration of atlas-based WM regions outlined in coronal, axial, and sagittal directions. The examples of the brain regions include the following: 1) middle cerebellar peduncle; 2) genu, body, and splenium of the corpus callosum; and 3) bilateral anterior and posterior limbs of the internal capsule.

Statistical Analysis

Before being pooled for group-difference testing, multisite DTI data were harmonized using the ComBat approach, a statistical correction strategy that minimizes the intercenter effect resulting from scanner differences while preserving physiologic features.21 Group differences in FA, AD, MD, or RD in each atlas region were assessed using a FSL General Linear Model framework (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM) with opioid exposure status as a categoric predictor variable, GA as a continuous predictor variable (mean centered), and the DTI metrics as the dependent variables.

RESULTS

Description of Patient Sample

Forty-one mothers completed the MR imaging session: 28 from CCHMC (13 opioid-exposed, 15 controls) and 13 from UAMS (4 opioid-exposed, 9 controls). Of these scans, fetal DTI data of 15 mothers were excluded due to poor image quality (11 from CCHMC: 4 opioid-exposed, 7 controls; 4 from UAMS: 2 opioid-exposed, 2 controls). Thus, a total of 26 fetuses, including 11 opioid-exposed (GA: 32.61 [SD, 2.35] weeks; 9 from CCHMC, 2 from UAMS) and 15 unexposed controls (GA: 31.77 [SD, 1.68] weeks; P = .30; 8 from CCHMC, 7 from UAMS), were included in the final analyses. Other demographic characteristics are provided in the Table. No significant differences in fetal motion between the 2 groups were identified using analysis of average framewise displacement in millimeters (Wilcoxon rank-sum test, P = .96). All fetal brain MRIs were interpreted as having normal signal and morphology by the study radiologists.

View this table:
  • View inline
  • View popup

Demographic information and additional substance exposure

Fetal DTI Findings

After adjusting for GA, FA values were significantly higher in opioid-exposed fetuses relative to controls in 8 WM regions (Fig 2). These significant regions included the bilateral lemniscus (left: P = .017; right: P = .020), the middle cerebellar peduncle (P = .027), the left inferior cerebellar peduncle (P = .026) and the right sagittal stratum (P = .040), the fornix (P = .022), the inferior fronto-occipital fasciculus (P = .011), and the uncinate fasciculus (P = .033). MD was significantly higher for exposed fetuses relative to controls in the left anterior limb of the internal capsule (P = .037) and the left uncinate fasciculus (P = .013) but significantly lower for exposed relative to controls in the left sagittal stratum (P = .035). AD was significantly higher for exposed fetuses relative to controls in 11 WM regions (Fig 3). These regions were the following: the middle cerebellar peduncle (P = .019), the pontine crossing tract (P = .043), the left medial lemniscus (P = .049), the anterior and posterior limbs of the internal capsule (P = .007, P = .018, respectively), the left anterior corona radiata (P = .002), the right external capsule (P = .027), the right cingulum hippocampus (P = .034), the right stria terminalis of the fornix (P = .021), the left inferior fronto-occipital fasciculus (P = .035), and the left uncinate fasciculus (P = .006). RD was significantly lower for exposed subjects relative to controls in the left sagittal stratum (P = .025).

FIG 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIG 2.

Plots of FA, adjusted for age, by group in 8 deep WM structures showing opioid-exposed fetuses with higher FA compared with controls.

FIG 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
FIG 3.

Plots of AD, adjusted for age, by group in 11 deep WM structures showing opioid-exposed fetuses with higher AD compared with controls.

DISCUSSION

This is a prospective study in which the use of ComBat harmonization allowed bi-institutional data use. There is a paucity of literature examining prenatal imaging of patients with in utero opioid exposure, and to the best of the authors’ knowledge, there are no previously published works examining DTI data in human fetuses with in utero opioid exposure. In this study, we observed statistically significantly increased FA values in opioid-exposed fetuses compared with healthy controls in 8 WM regions in the cerebrum, cerebellum, and brainstem after adjusting for GA. We also observed statistically significant alterations in AD in 11 different WM regions, MD in 3 regions, and RD in 1 region in the exposed fetuses relative to controls.

Alterations in DTI indices in children with prenatal exposure to opioids have been described in multiple age ranges and in association with various substances. There are studies describing alterations in neonates, infants, and school-aged children.16,22⇓-24 However, some of these changes are not consistently found in all studies in terms of the direction of alterations. For example, 1 study described decreased FA in prenatal methadone-exposed infants compared with controls.23 Another more recent study described significantly increased FA values in neonates (37- to 49-weeks’ postmenstrual age) with prenatal opioid exposure.25 The authors of this study also noted increased FA values in infants with prenatal exposure to cocaine and marijuana. Some of these previous works revealed region-specific direction changes in DTI parameters in the same cohort, reflecting the complexity of the underlying mechanisms of injury as a result of prenatal substance abuse on the developing brain.15,26

While our study potentially contributes one of the only descriptions of altered DTI parameters on fetal MR imaging in prenatal opioid exposure, the clinical significance of these results is preliminary in nature. Previous work examining the relationship between DTI and histology has demonstrated that, in general, abnormally lower FA values and higher MD, AD, and/or RD values are often interpreted as damage to the myelin sheath and axonal membrane. However, higher FA and lower MD, AD, and/or RD values can also be attributed to extracellular space compression, cytotoxic edema, or inflammation.27,28 In the present study, we identified multiple WM regions with abnormally higher FA, driven mainly by the increase of AD, a result that seems to be in line with the latter scenario. Increased expression of inflammatory genes has also been demonstrated in infants with prenatal opioid exposure compared with unexposed controls, making the underlying inflammatory processes a potential explanation for our findings.29 However, contrary to the direction of changes observed in these studies, 1 mouse model study demonstrating increased serum inflammatory biomarkers described reduced WM FA on ex vivo DTI of the brain with decreased axial diffusivity.30 Also, the interpretation of underlying neuropathology and its potential association with substance abuse during fetal life is complicated by the rapid fetal brain development and maturation process. Furthermore, our statistical analysis of group differences assumed a linear relationship in the developmental trajectory for DTI, which may not be accurate.

The current literature in fetal DTI is evolving, and while some studies have reported a linear or at least monotonic relationship between DTI and age, other studies have revealed a more complicated temporal process. For example, as reported in a study by Zanin et al,31 the potential relationship between DTI and age may vary as determined by different phases during fetal brain maturation. While no significant age correlation was found for DTI in our data, this finding could be due to the limited sample size in our study, which did not allow further exploration of this relation. Therefore, future studies with larger sample sizes are critical in elucidating underlying injury mechanisms along with spatiotemporal progression in the fetal brain with opioid exposure.32

Our study has limitations. One of the major limitations of this study is the relatively small sample size. The issue was partially addressed through bi-institutional collaboration and the use of ComBat harmonization. However, additional studies in larger patient populations will be needed to further understand and validate these results. Another limitation commonly encountered in fetal imaging is motion artifacts, which are one of main challenges faced in fetal DTI performance. Despite using SVR to improve image quality, multiple patients had to be excluded for excessive fetal motion in this study. Super resolution reconstruction methods have been shown to improve the image and data quality by scanning in multiple orthogonal planes and show promise for future studies though they come at the cost of increased imaging time.33 Finally, one of the main limitations of this study relates to the opioid-exposed patient population and the potential for confounding variables. In the opioid-exposed cohort, 54.5% (6/11) of mothers had reported prenatal exposure to nicotine, other illicit drugs, or both, which can affect brain development. Also, fetal brain development may have been impacted by a range of additional factors such as maternal nutrition, stress, and other environmental factors.

CONCLUSONS

This study demonstrates the feasibility of the application of fetal DTI, a highly challenging technique, to quantitatively assess WM integrity in opioid-exposed fetuses. Our multisite data show widespread WM regions with significant DTI abnormalities in the patients, which we hypothesize to be due to prenatal opioid exposure causing impairment during the complex series of neurogenic events (neurogenesis, neuronal migration, synapsis, axonal growth, myelination) in the fetal development and maturation process. Early detection of such abnormalities as well as their progression will provide critical data to inform prenatal counseling, treatment, and intervention strategies with the ultimate aim of optimizing long-term outcomes.

Footnotes

  • This work was supported by the Schubert Research Clinic Clinical Research Feasibility Fund, Cincinnati Children’s Radiology Pilot Fund, and grants CCHMC R34-DA050268 and R34-DA050261 from Phase I of the HEALthy Brain and Child Development Study.

  • Disclosure forms provided by the authors are available with the full text and PDF of this article at www.ajnr.org.

  • J.A. Dudley and U.D. Nagaraj contributed equally to this work.

Indicates open access to non-subscribers at www.ajnr.org

References

  1. 1.↵
    1. Ko JY,
    2. D’Angelo DV,
    3. Haight SC, et al
    . Vital signs: prescription opioid pain reliever use during pregnancy: 34 U.S. jurisdictions, 2019. MMWR Morb Mortal Wkly Rep 2020;69:897–903 doi:10.15585/mmwr.mm6928a1 pmid:32673301
    CrossRefPubMed
  2. 2.↵
    1. Hirai AH,
    2. Ko JY,
    3. Owens PL, et al
    . Neonatal abstinence syndrome and maternal opioid-related diagnoses in the US, 2010-2017. JAMA 2021;325:146–55 doi:10.1001/jama.2020.24991 pmid:33433576
    CrossRefPubMed
  3. 3.↵
    1. Larson JJ,
    2. Graham DL,
    3. Singer LT, et al
    . Cognitive and behavioral impact on children exposed to opioids during pregnancy. Pediatrics 2019;144:e20190 doi:10.1542/peds.2019-0514 pmid:31320466
    CrossRefPubMed
  4. 4.↵
    1. Lee SJ,
    2. Woodward LJ,
    3. Henderson JMT
    . Educational achievement at age 9.5 years of children born to mothers maintained on methadone during pregnancy. PLoS One 2019;14:e0223685–20 doi:10.1371/journal.pone.0223685
    CrossRefPubMed
  5. 5.↵
    1. Jaekel J,
    2. Kim HM,
    3. Lee SJ, et al
    . Emotional and behavioral trajectories of 2 to 9 years old children born to opioid-dependent mothers. Res Child Adolesc Psychopathol 2021;49:443–57 doi:10.1007/s10802-020-00766-w pmid:33433780
    CrossRefPubMed
  6. 6.↵
    1. Merhar SL,
    2. Parikh NA,
    3. Braimah A, et al
    . White matter injury and structural anomalies in infants with prenatal opioid exposure. AJNR Am J Neuroradiol 2019;40:2161–65 doi:10.3174/ajnr.A6282 pmid:31624119
    Abstract/FREE Full Text
  7. 7.↵
    1. Merhar SL,
    2. Kline JE,
    3. Braimah A, et al
    . Prenatal opioid exposure is associated with smaller brain volumes in multiple regions. Pediatr Res 2021;90:397–402 doi:10.1038/s41390-020-01265-w pmid:33177677
    CrossRefPubMed
  8. 8.↵
    1. Merhar SL,
    2. Jiang W,
    3. Parikh NA, et al
    . Effects of prenatal opioid exposure on functional networks in infancy. Dev Cogn Neurosci 2021;51:100996 doi:10.1016/j.dcn.2021.100996 pmid:34388637
    CrossRefPubMed
  9. 9.↵
    1. Radhakrishnan R,
    2. Vishnubhotla R. V,
    3. Zhao Y, et al
    . Global brain functional network connectivity in infants with prenatal opioid exposure. Front Pediatr 2022;10:847037 doi:10.3389/fped.2022.847037 pmid:35359894
    CrossRefPubMed
  10. 10.↵
    1. Radhakrishnan R,
    2. Elsaid NMH,
    3. Sadhasivam S, et al
    . Resting state functional MRI in infants with prenatal opioid exposure-a pilot study. Neuroradiology 2021;63:585–91 doi:10.1007/s00234-020-02552-3 pmid:32978671
    CrossRefPubMed
  11. 11.↵
    1. Radhakrishnan R,
    2. Vishnubhotla R. V,
    3. Guckien Z, et al
    . Thalamocortical functional connectivity in infants with prenatal opioid exposure correlates with severity of neonatal opioid withdrawal syndrome. Neuroradiology 2022;64:1649–59 doi:10.1007/s00234-022-02939-4 pmid:35410397
    CrossRefPubMed
  12. 12.↵
    1. Griffiths PD,
    2. Bradburn M,
    3. Campbell MJ, et al
    ; MERIDIAN collaborative group. Use of MRI in the diagnosis of fetal brain abnormalities in utero (MERIDIAN): a multicentre, prospective cohort study. Lancet 2017;389:538–46 doi:10.1016/S0140-6736(16)31723-8 pmid:27988140
    CrossRefPubMed
  13. 13.↵
    1. Nagaraj UD,
    2. Kline-Fath BM,
    3. Zhang B, et al
    . MRI findings in third-trimester opioid-exposed fetuses with focus on brain measurements: a prospective multicenter case-control study. AJR Am J Roentgenol 2023;220:418–27 doi:10.2214/AJR.22.28357 pmid:36169547
    CrossRefPubMed
  14. 14.↵
    1. Hornburg KJ,
    2. Slosky LM,
    3. Cofer G, et al
    . Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice. NMR Biomed 2023;36;e4842 doi:10.1002/nbm.4842 pmid:36259728
    CrossRefPubMed
  15. 15.↵
    1. Grecco GG,
    2. Shahid SS,
    3. Atwood BK, et al
    . Alterations of brain microstructures in a mouse model of prenatal opioid exposure detected by diffusion MRI. Sci Rep 2022;12:17085 doi:10.1038/s41598-022-21416-9 pmid:36224335
    CrossRefPubMed
  16. 16.↵
    1. Vishnubhotla R. V,
    2. Zhao Y,
    3. Wen Q, et al
    . Brain structural connectome in neonates with prenatal opioid exposure. Front Neurosci 2022;16:952322 doi:10.3389/fnins.2022.952322 pmid:36188457
    CrossRefPubMed
  17. 17.↵
    1. Ebner M,
    2. Wang G,
    3. Li W, et al
    . An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. Neuroimage 2020;206:116324 doi:10.1016/j.neuroimage.2019.116324 pmid:31704293
    CrossRefPubMed
  18. 18.↵
    1. Gholipour A,
    2. Rollins CK,
    3. Velasco-Annis C, et al
    . A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci Rep 2017;7:476 doi:10.1038/s41598-017-00525-w pmid:28352082
    CrossRefPubMed
  19. 19.↵
    1. Mori S,
    2. Wakana S,
    3. van Zijl PC, et al
    . MRI Atlas of Human White Matter. Elsevier; 2005
  20. 20.↵
    1. Khan S,
    2. Vasung L,
    3. Marami B, et al
    . Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images. Neuroimage 2019;185:593–608 doi:10.1016/j.neuroimage.2018.08.030 pmid:30172006
    CrossRefPubMed
  21. 21.↵
    1. Fortin JP,
    2. Parker D,
    3. Tunç B, et al
    . Harmonization of multi-site diffusion tensor imaging data. Neuroimage 2017;161:149–70 doi:10.1016/j.neuroimage.2017.08.047 pmid:28826946
    CrossRefPubMed
  22. 22.↵
    1. Walhovd KB,
    2. Watts R,
    3. Amlien I, et al
    . Neural tract development of infants born to methadone-maintained mothers. Pediatr Neurol 2012;47:1–6 doi:10.1016/j.pediatrneurol.2012.04.008 pmid:22704008
    CrossRefPubMed
  23. 23.↵
    1. Monnelly VJ,
    2. Anblagan D,
    3. Quigley A, et al
    . Prenatal methadone exposure is associated with altered neonatal brain development. Neuroimage Clin 2018;18:9–14 doi:10.1016/j.nicl.2017.12.033 pmid:29326869
    CrossRefPubMed
  24. 24.↵
    1. Walhovd KB,
    2. Westlye LT,
    3. Moe V, et al
    . White matter characteristics and cognition in prenatally opiate- and polysubstance-exposed children: a diffusion tensor imaging study. AJNR Am J Neuroradiol 2010;31:894–900 doi:10.3174/ajnr.A1957 pmid:20203117
    Abstract/FREE Full Text
  25. 25.↵
    1. Peterson BS,
    2. Rosen T,
    3. Dingman S, et al
    . Associations of maternal prenatal drug abuse with measures of newborn brain structure, tissue organization, and metabolite concentrations. JAMA Pediatr 2020;174:831–42 doi:10.1001/jamapediatrics.2020.1622 pmid:32539126
    CrossRefPubMed
  26. 26.↵
    1. Lebel C,
    2. Warner T,
    3. Colby J, et al
    . White matter microstructure abnormalities and executive function in adolescents with prenatal cocaine exposure. Psychiatry Res 2013;213:161–68 doi:10.1016/j.pscychresns.2013.04.002 pmid:23769420
    CrossRefPubMed
  27. 27.↵
    1. Song SK,
    2. Sun SW,
    3. Ju WK, et al
    . Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 2003;20:1714–22 doi:10.1016/j.neuroimage.2003.07.005 pmid:14642481
    CrossRefPubMed
  28. 28.↵
    1. Niogi SN,
    2. Mukherjee P
    . Diffusion tensor imaging of mild traumatic brain injury. J Head Trauma Rehabil 2010;25:241–55 doi:10.1097/HTR.0b013e3181e52c2a pmid:20611043
    CrossRefPubMed
  29. 29.↵
    1. Yen E,
    2. Madan N,
    3. Tarui T, et al
    . Sex-specific inflammatory and white matter effects of prenatal opioid exposure: a pilot study. Pediatr Res 2023;93:604–11 doi:10.1038/s41390-022-02357-5 pmid:36280708
    CrossRefPubMed
  30. 30.↵
    1. Jantzie LL,
    2. Maxwell JR,
    3. Newville JC, et al
    . Prenatal opioid exposure: the next neonatal neuroinflammatory disease. Brain Behav Immun 2020;84:45–58 doi:10.1016/j.bbi.2019.11.007 pmid:31765790
    CrossRefPubMed
  31. 31.↵
    1. Zanin E,
    2. Ranjeva JP,
    3. Confort-Gouny S, et al
    . White matter maturation of normal human fetal brain: an in vivo diffusion tensor tractography study. Brain Behav 2011;1:95–108 doi:10.1002/brb3.17 pmid:22399089
    CrossRefPubMed
  32. 32.↵
    1. Machado-Rivas F,
    2. Afacan O,
    3. Khan S, et al
    . Tractography of the cerebellar peduncles in second- and third-trimester fetuses. AJNR Am J Neuroradiol 2021;42:194–200 doi:10.3174/ajnr.A6869 pmid:33431505
    Abstract/FREE Full Text
  33. 33.↵
    1. Machado-Rivas F,
    2. Afacan O,
    3. Khan S, et al
    . Spatiotemporal changes in diffusivity and anisotropy in fetal brain tractography. Hum Brain Mapp 2021;42:5771–84 doi:10.1002/hbm.25653 pmid:34487404
    CrossRefPubMed
  • Received April 13, 2023.
  • Accepted after revision June 25, 2023.
  • © 2023 by American Journal of Neuroradiology
PreviousNext
Back to top
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
DTI of Opioid-Exposed Fetuses Using ComBat Harmonization: A Bi-Institutional Study
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
J.A. Dudley, U.D. Nagaraj, S. Merhar, F.T. Mangano, B.M. Kline-Fath, X. Ou, A. Acheson, W. Yuan
DTI of Opioid-Exposed Fetuses Using ComBat Harmonization: A Bi-Institutional Study
American Journal of Neuroradiology Aug 2023, DOI: 10.3174/ajnr.A7951

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
DTI of Opioid-Exposed Fetuses Using ComBat Harmonization: A Bi-Institutional Study
J.A. Dudley, U.D. Nagaraj, S. Merhar, F.T. Mangano, B.M. Kline-Fath, X. Ou, A. Acheson, W. Yuan
American Journal of Neuroradiology Aug 2023, DOI: 10.3174/ajnr.A7951
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSONS
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • A Prospective Multi-Institutional Study Comparing the Brain Development in the Third Trimester between Opioid-Exposed and Nonexposed Fetuses Using Advanced Fetal MR Imaging Techniques
  • Crossref (2)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • A detailed spatiotemporal atlas of the white matter tracts for the fetal brain
    Camilo Calixto, Matheus Dorigatti Soldatelli, Camilo Jaimes, Lana Pierotich, Simon K. Warfield, Ali Gholipour, Davood Karimi
    Proceedings of the National Academy of Sciences 2025 122 1
  • A Prospective Multi-Institutional Study Comparing the Brain Development in the Third Trimester between Opioid-Exposed and Nonexposed Fetuses Using Advanced Fetal MR Imaging Techniques
    Hyuk Jin Yun, Usha D. Nagaraj, P. Ellen Grant, Stephanie L. Merhar, Xiawei Ou, Weili Lin, Ashley Acheson, Karen Grewen, Beth M. Kline-Fath, Kiho Im
    American Journal of Neuroradiology 2024 45 2

More in this TOC Section

  • fetal brain development of 10 weeks gestation
  • CHARGE fetal MRI clival cleft
  • Neuroimaging Delineation and Progression of SLSMD
Show more Pediatric Neuroimaging

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire