Buprenorphine and Surface-based Brain Morphometry: Impacts on Cortical Thickness, Depth, and Gyrification in Patients with Opioid Use Disorder

Abstract

Background:

Opioid use disorder (OUD) is associated with structural brain alterations. Buprenorphine maintenance treatment (BMT)’s impact on brain morphology remains underexplored. We examined the effect of BMT on surface-based morphometry (SBM) metrics- cortical thickness, sulcal depth, gyrification, and fractal dimension, in a longitudinal controlled design.

Methods:

Twenty-five men with OUD and age- and education-matched participants in the control group were recruited. Participants underwent T1-weighted MRI scans immediately after starting BMT and after six months of treatment. SBM metrics were analyzed using the Computational Anatomy Toolbox 12 (CAT12), employing threshold-free cluster enhancement (TFCE) and family-wise error correction.

Results:

At baseline, individuals with OUD had greater cortical thickness in superior parietal and occipital regions and reduced thickness in the inferior temporal gyrus versus participants in the control group. After six months, significant cortical thickness reductions were observed in the occipital pole, cuneus, and occipito-temporal gyri, and calcarine sulcus in both hemispheres; sulcal depth, gyrification, and fractal dimension remained unchanged. We observed negative correlations between buprenorphine dosage and change in cortical depth in the parahippocampal region (r = –0.53, p = .007) and temporal pole (r = –0.55, p = .005), and positive correlations with fractal dimension in the medial orbitofrontal cortex (r = 0.53, p = .006) and gyrification in the lateral orbital region (r = 0.56, p = .004).

Conclusion:

BMT is associated with a generalized cortical thinning in sensory regions, while dose-dependent changes are observed in memory, emotional regulation, and cognitive control regions, highlighting neuroadaptive processes in overall treatment and medication-specific effects.

Key Message:

• BMT leads to cortical thinning in occipito-temporal regions, suggesting treatment-related brain changes.

• Buprenorphine dose correlates with structural changes in frontal, temporal, and insular areas.

• BMT may support targeted neuroplasticity in circuits linked to emotion and cognition

Opioid use disorder (OUD) is associated with structural and functional brain alterations. Chronic opioid exposure disrupts the brain’s reward circuitry, particularly the mesolimbic pathway involving the ventral tegmental area (VTA) and nucleus accumbens, leading to dysregulated dopamine signaling and compulsive drug-seeking behavior.^1,2 Opioids also impair the prefrontal cortex, affecting executive functions such as decision-making and impulse control. ² Structural changes include both gray and white matter alterations. White matter changes may stem from myelin degradation, mitochondrial dysfunction, and neuronal apoptosis, while gray matter loss may result from hypoxia secondary to opioid-induced respiratory depression.^3,4

Meta-analyses of neuroimaging studies have found significantly lower frontotemporal gray matter volumes ⁵ and white matter microstructural abnormalities in frontal and limbic areas ⁵ in individuals with OUD compared to controls. Some of these alterations—mainly white matter abnormalities—may partially recover with abstinence, but other changes, such as persistent reductions in parieto-occipital gray matter volume and functional connectivity, often remain.^6–8 These findings are based on serial imaging of participants over different abstinence durations (three days to five years). However, such prolonged abstinence without medication is rare in clinical settings.

Research evaluating brain changes in individuals receiving opioid agonist maintenance treatment (OAMT) is limited. One study found that one year of methadone maintenance resulted in dose-dependent reductions in white matter integrity, as indicated by decreased fractional anisotropy and increased radial diffusivity, correlated with impulsivity. ⁹ Another study reported more pronounced white matter abnormalities in individuals on methadone compared to abstinent peers. ¹⁰ Smaller gray matter volumes in cingulate, insular, and parietal regions were also found in those on long-term methadone. ¹¹ Methadone may exert these effects via apoptosis, oxidative stress, or chronic cerebral hypoperfusion.^12,13

Surface-based morphometry (SBM) offers higher sensitivity in detecting localized cortical thinning and better captures cortical thickness, gyrification, and sulcal depth.^14–16 These metrics provide complementary insights—cortical thickness reflects neuroplasticity, ¹⁷ while sulcal depth, gyrification, and fractal dimension are more stable and shaped by neurodevelopment.^18,19

No studies to date have investigated structural brain changes in individuals on buprenorphine, a partial opioid agonist with a safer respiratory profile than methadone.

Aim

This study aimed to investigate the longitudinal effects of buprenorphine-naloxone maintenance treatment on cortical brain structure in individuals with OUD, using SBM metrics such as cortical thickness, sulcal depth, and gyrification.

Objectives

This study used SBM to evaluate cortical changes in individuals with OUD at buprenorphine-naloxone treatment initiation and after six months. An age- and education-matched control group was included to assess whether cortical morphometry metrics normalize, persist, or worsen with treatment.

Methods

This was a longitudinal, controlled observational study. All research participants provided written informed consent to participate in the study. The study was approved by the Institute’s extramural Ethics Committee (#IEC-11/2017-752).

Subject Selection and Settings

Twenty-five right-handed individuals with OUD were recruited from the outpatient services at the addiction treatment center of the institute. Inclusion criteria included individuals of any sex (however, we could enroll only men because of the unavailability of participants with other sex in the treatment center during the study period), those over 18 years of age, diagnosed with opioid dependence per the International Classification of Diseases, 10th edition, and those who had begun buprenorphine (naloxone) treatment for OUD but received less than seven days of treatment. Right-handedness was determined using the Edinburgh Handedness Inventory. Participants were excluded if they had a history of any other drug/alcohol use disorder (except tobacco), any history of head trauma or neurological disease, a history of intellectual disability or language communication abnormalities, prior history of receiving opioid agonist maintenance therapy, or claustrophobia or any contraindications for MRI examination. A qualified psychiatrist made the diagnosis.

We also recruited 25 healthy participants in the control group, without a known history of medical, neurological, or psychiatric conditions, from the community, who were matched per age, sex, and years of education. A frequency match was performed to balance the matched variables between the OUD and participants in the control group. The participants in the control group did not have a lifetime history of drug and tobacco use. However, they might have had recreational alcohol use, which did not meet a single criterion for alcohol dependence. Enrollment was done between March 2020 and November 2022.

Follow-up

All individuals with OUD were followed up after at least six months of Buprenorphine maintenance treatment (BMT). A trained psychiatrist delivered BMT. The frequency of dispensing BMT was once a week for the first three months, followed by once every two weeks in the next three months. All individuals with OUD underwent a monthly routine urine chromatographic immune assay to screen for non-prescription opioid use (e.g., heroin, tramadol) and buprenorphine, to check for adherence to BMT. The second scan was performed after at least six months of BMT initiation, when the patients were on a stable dose of buprenorphine (i.e., no dosage change in the last month) and abstinent from non-prescription opioids (as evidenced by subjective reporting and negative urine screens in the previous three occasions).

Image Aacquisition

Examinations for individuals with OUD, Controls, and the 6-month follow-up (BMT) were conducted using three Tesla MRI systems equipped with standard head coils. 3T Magnetom Verio (OUD, controls and six follow-ups) (Siemens Healthineers, Germany) and 3T Philips Ingenia (19 follow-up) scanner were used with the following parameters: 3D T1 weighted imaging having 208 slices with repetition time (TR) of 2300 ms, echo time (TE) of 2.96 ms, field of view (FOV) of 256 mm, flip angle of 9 degrees, voxel size of 1x1x1 mm. Before analysis, all MRI scans were pre-processed to account for scanner-specific calibration. This included co-registration of baseline and follow-up images to ensure that any inter-scanner variability was minimized.

SBM Data Processing

For all analyses, preprocessing was conducted using the Computational Anatomy Toolbox (CAT12, Structural Brain Mapping Group, University of Jena, Germany) within SPM12 (Statistical Parametric Mapping) in MATLAB (MathWorks Inc., Sherborn, MA, USA). The preprocessing pipeline included bias-field correction, tissue segmentation, intensity normalization, and spatial registration to the IXI555 template in MNI152 space. ¹⁷ However, to account for the different objectives of our analyses, preprocessing steps were adjusted as follows:

Longitudinal (Pre- Versus Post-treatment) Analysis

Images were co-registered within subjects to ensure alignment between pre- and post-treatment scans, followed by within-subject intensity normalization to minimize inter-scan variability.

Between-group Analyses (OUD Pre-treatment Versus Control, OUD Post-treatment Versus Control)

Images were processed separately for each group and subsequently registered to the common template. No longitudinal co-registration was applied in these between-group analyses to maintain the independence of the control sample.

Affine preprocessing steps included inhomogeneity correction and brain extraction. The “Destrieux” cortical atlas, based on gross neuroanatomical boundaries like sulci and fissures, was adapted to individual anatomy for brain localization. ²⁰

The study employed threshold-free cluster enhancement (TFCE) for the analysis of SBM metrics, including cortical depth, thickness, gyrification, and fractal dimension. TFCE is a robust statistical method designed to enhance cluster-like structures in neuroimaging data. TFCE enhances the statistical power of detecting true signal changes by considering both the height of the statistical map and the extent of spatial clusters. This approach mitigates the limitations associated with traditional cluster-based methods, which often depend on arbitrary threshold settings. TFCE thus provides a more sensitive and accurate detection of spatial patterns in neuroimaging data.

Statistical Analysis

We presented descriptive statistics to characterize the study sample and compared the demographic variables (age, SES) of individuals with OUD versus controls using Chi-Square and t-tests. Statistical analyses were conducted using the General Linear Model (GLM) framework implemented in CAT12. To account for multiple comparisons across the cortical surface, we employed TFCE, a non-parametric method that enhances signal detection without requiring arbitrary cluster-size thresholds. family-wise error (FWE) correction was then applied at p < .05 to control for Type I error across all SBM metrics.

While all reported results in tables reflect FWE-corrected p values, the figures displaying statistical brain maps show uncorrected log-p values for visualization purposes. These maps illustrate the spatial extent of observed effects but should be interpreted cautiously, as only FWE-corrected results should be considered statistically significant.

In addition to the primary longitudinal comparison (pre- versus post-treatment within the OUD group), we conducted between-group comparisons (individuals with control versus OUD pre-treatment and control versus OUD post-treatment). The primary rationale for the control versus post-treatment comparison was to explore whether cortical structure in the OUD group moved closer to or remained distinct from controls following BMT. However, this comparison is inherently influenced by between-subject variability and potential scanner effects. Therefore, findings from this analysis should be interpreted cautiously and considered exploratory rather than conclusive evidence of treatment-related changes.

To assess the relationship between buprenorphine dosage and SBM metrics, we performed correlation analyses on brain regions that exhibited significant changes in pre- versus post-treatment comparisons (p < .05, FWE-corrected). This data-driven approach ensured that the selected areas were directly relevant to the observed treatment-related effects rather than being arbitrarily chosen based on prior literature. Pearson’s correlation coefficients were computed between the change in mean regional SBM metrics and daily buprenorphine dose, with a significance threshold of p < .01 to adjust for multiple comparisons.

Results

Clinical and Demographic Characteristics of the Study Sample

The study included 25 right-handed individuals with OUD. The average age was 28.04 years (SD = 5.08), and the mean duration of opioid use was 5.25 years (SD = 2.97). Most participants were single (56%) and of lower socioeconomic status (56%). The primary type of opioid used was heroin (72%), and the primary route of administration was intravenous (40%). The individuals with OUD and controls did not differ in age, years of education, and socioeconomic status (Supplementary Tables S1–S3).

Changes in the SBM Metrics in Participants Undergoing BMT

We compared the SBM metrics (cortical depth, thickness, gyrification, and fractal dimension) of participants immediately after initiating BMT and after at least six months of continued treatment. Statistical analyses were conducted using TFCE statistics, with significance levels at p < .05 and p < .01.

Cortical Thickness

Decreased thickness was observed in both hemispheres. Regions involved in the left hemisphere were the occipital pole, the cuneus gyrus, the medial occipito-temporal gyrus (lingual), and the calcarine sulcus, with p values ranging from .02 to .049, with cluster sizes indicating substantial regional involvement. In the right hemisphere, significant changes were observed in the medial occipito-temporal gyrus (lingual), the occipital pole, the cuneus gyrus, the calcarine sulcus, the inferior occipital gyrus, the middle occipital gyrus, the precuneus, the parieto-occipital sulcus, the sub parietal sulcus, and the posterior-dorsal cingulate gyrus, with p values as low as .008 and cluster sizes up to 826.

There were no significant differences (Table 1 and Figure 1) in cortical depth, fractal dimension, and gyrification after six months of treatment (in comparison with pre-treatment data) in both groups.

Table 1.

Comparison of SBM Metrics Between Participants with OUD and BMT (Pre and Post Starting Buprenorphine).

Metric	Left Hemisphere (LH)	Effects-positive/Negative	Cluster	Cluster-size	Overlap of Atlas Region	Atlas Region	p Value	Right Hemisphere (RH)	Effects-positive/Negative	Cluster	Cluster-size	Overlap of Atlas Region	Atlas Region	p Value
Cortical thickness	LH	Positive OUD>BMT	1	186	85%	Occipital pole	.022	RH	Positive OUD>BMT	1	826	37%	Lingual gyrus, lingual part of the medial occipito-temporal gyrus,	.009
					14%	Cuneus						37%	Occipital pole
			2	164	92%	Lingual gyrus, lingual part of the medial occipito-temporal gyrus,	.020					11%	Cuneus
					5%	Calcarine sulcus						5%	Calcarine sulcus
					2%	Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus						5%	Inferior occipital gyrus (O3) and sulcus
			3	2	50%	Cuneus	.049					3%	Middle occipital gyrus (O2, lateral occipital gyrus)
					50%	Calcarine sulcus						2%	Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus
			4	2	100%	Calcarine sulcus	.049
										2	111	57%	Precuneus	.035
												24%	Parieto-occipital sulcus (or fissure)
												14%	Subparietal sulcus
												5%	Posterior-dorsal part of the cingulate gyrus (dPCC)

Figure 1. Changes in the Cortical Thickness in Participants Undergoing Buprenorphine Maintenance Treatment (BMT).

Dorsal, medial, and lateral views of the left hemisphere (LH) and right hemisphere (RH). The figure shows brain regions with significant statistical differences between persons with OUD and BMT (p < .05; uncorrected-TFCE_log_p). The color bar indicates the strength of the regions, significantly higher (OUD > BMT) in cortical thickness. No brain regions were significantly lower (BMT > OUD) in cortical thickness. No significant statistical differences were found in sulcal depth, cortical gyrification and fractal dimension.

Comparison of SBM Metrics Between Participants with OUD at Baseline and Controls: Cortical Thickness

The OUD group showed larger cortical thickness in the left hemisphere, including the superior frontal gyrus, postcentral sulcus, precuneus, and central sulcus (p values = .009–.05, clusters up to 2830), and in the right hemisphere, involving the parieto-occipital sulcus, calcarine sulcus, and occipital pole (p values = .01–.05, clusters up to 1539). Thinner regions were observed in the left hemisphere, notably in the inferior and middle temporal gyri (p values = .026–.04, clusters up to 131) (Figures 1–3; Supplementary Table S4).

Figure 3. Comparison of Cortical Thickness Between Participants on BMT and Controls.

Dorsal, medial, and lateral views of the left hemisphere (LH) and right hemisphere (RH). The figure shows brain regions with significant statistical differences between persons on BMT and Controls (p < .05; uncorrected-TFCE_log_p). The color bar indicates regions significantly higher (hot tone; BMT > Controls) or lower (cold tone; Controls > BMT) in cortical thickness. No brain regions showed substantially lower cortical thickness (Controls > BMT). The color bar for cortical thickness indicates the strength of regions that are significantly higher (BMT > Controls).

Figure 2. Comparison of Cortical Thickness Between Participants with OUD and Controls.

Dorsal, medial, and lateral views of the left hemisphere (LH) and right hemisphere (RH). The figure shows brain regions with significant statistical differences between persons with OUD and controls (p < .05; uncorrected-TFCE_log_p). The color bar indicates regions significantly higher (hot tone; OUD > Controls) or lower (cold tone; Controls > OUD) in cortical thickness.

Cortical Depth

The OUD group showed significantly higher sulcal depths in the left hemisphere, including the superior temporal gyrus, circular insula sulci, lateral fissure, subcentral gyrus, middle frontal gyrus, and temporal transverse sulcus (p values = .001–.05, clusters up to 3522). In the right hemisphere, increased depths were found in the superior temporal sulcus, central sulcus, and precentral sulcus (p values = .0002–.05, clusters up to 11,000). Lower sulcal depth in the left hemisphere was noted in the occipital inferior gyrus, fusiform gyrus, and occipital pole (p values = .01–.03, clusters up to 208).

Gyrification

The OUD group showed significantly higher gyrification than controls, especially in the left hemisphere, including the lingual gyrus, occipital pole, cuneus, calcarine sulcus, parahippocampal gyrus, and subparietal sulcus (p values = .01–.05, clusters up to 1023). In the right hemisphere, increased gyrification was found in the pericallosal sulcus, cingulate gyri, superior frontal gyrus, precuneus, and temporal pole (p values = .005–.05, clusters up to 3011). Lower gyrification was observed in the ventral cingulate gyrus and circular insula sulci (p value = .04, cluster-size 1).

Fractal Dimension

Fractal dimension analysis revealed significantly higher values in the OUD group, especially in the left hemisphere, including the superior frontal, orbital, rectus, middle frontal, and mid-anterior cingulate gyri (p values = .0002–.05, clusters up to 1993). In the right hemisphere, higher values were found in the middle frontal gyrus, central sulcus, postcentral gyrus, precuneus, and superior parietal gyrus (p values = .0002–.05, clusters up to 5488). Lower fractal dimensions in both hemispheres involved the inferior frontal gyrus, precentral sulcus, subparietal sulcus, and dorsal cingulate gyrus (p values = .006–.05, clusters up to 316) (Supplementary Figure S1 and Table S5).

Comparison of SBM Metrics Between Participants with OUD on BMT for Six Months and Controls

Cortical Thickness

Participants on BMT showed significantly higher cortical thickness in the left hemisphere across regions, including the central sulcus, superior frontal gyrus, precuneus, cingulate gyrus, and others, with p values ranging from .0002 to .05 and cluster sizes from 1 to 17,200. In the right hemisphere, similar increases were observed, including the temporal middle gyrus and parahippocampal gyrus, with p values from .0002 to .04 and cluster sizes from 1 to 14,499 (Table 2).

Table 2.

Comparison of Cortical Thickness Between Participants on BMT and Controls.

Metric	Hemisphere RH/LH	Effects-positive/Negative	Cluster	Cluster-size	Overlap of Atlas Region	Atlas Region	p Value	RH	Effects-positive/Negative	Cluster	Cluster-size	Overlap of Atlas Region	Atlas Region	p Value
Cortical thickness	LH	Positive BMT>controls	1	17200	5%	Central sulcus (Rolando’s fissure)	<.001	RH	Positive BMT>controls	1	14499	5%	Superior frontal gyrus	<.001
					5%	Postcentral sulcus						4%	Central sulcus (Rolando’s fissure)
					4%	Superior frontal gyrus						4%	Calcarine sulcus
					4%	Precuneus						3%	Inferior temporal gyrus
					3%	Calcarine sulcus						3%	Pericallosal sulcus (S of corpus callosum)
					3%	Superior segment of the circular sulcus of the insula						3%	Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus
					3%	Anterior part of the cingulate gyrus and sulcus (ACC)						3%	Middle-posterior part of the cingulate gyrus and sulcus (pMCC)
					3%	Middle-posterior part of the cingulate gyrus and sulcus (pMCC)						3%	Anterior part of the cingulate gyrus and sulcus (ACC)
					3%	Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus						3%	Lingual gyrus, ligual part of the medial occipito-temporal gyrus,
					3%	Parieto-occipital sulcus (or fissure)						3%	Middle-anterior part of the cingulate gyrus and sulcus (aMCC)
					3%	Superior parietal lobule						3%	Precuneus
					2%	Pericallosal sulcus (S of corpus callosum)						2%	Occipital pole
					2%	Lingual gyrus, lingual part of the medial occipito-temporal gyrus,						2%	Temporal pole
					2%	Inferior temporal gyrus						2%	Superior segment of the circular sulcus of the insula
					2%	Middle-anterior part of the cingulate gyrus and sulcus (aMCC)						2%	Lateral occipito-temporal gyrus
					2%	Intraparietal sulcus (interparietal sulcus) and transverse parietal sulci						2%	Paracentral lobule and sulcus
					2%	Middle frontal gyrus						2%	Middle temporal gyrus
					2%	Superior frontal sulcus						2%	Precentral gyrus
					2%	Temporal pole						2%	Parahippocampal gyrus, parahippocampal part of the medial occipito-temporal gyrus,
					2%	Orbital gyri						2%	Parieto-occipital sulcus (or fissure)
					2%	Parahippocampal gyrus, parahippocampal part of the medial occipito-temporal gyrus,						2%	Superior occipital sulcus and transverse occipital sulcus
					2%	Middle temporal gyrus						2%	Inferior segment of the circular sulcus of the insula
					2%	Subparietal sulcus						2%	Inferior occipital gyrus (O3) and sulcus
					2%	Postcentral gyrus						2%	Middle occipital gyrus (O2, lateral occipital gyrus)
					2%	Lateral occipito-temporal gyrus						2%	Cuneus
					2%	Cuneus						2%	Superior parietal lobule
					2%	Lateral aspect of the superior temporal gyrus						2%	Superior frontal sulcus
					2%	Inferior segment of the circular sulcus of the insula						2%	Intraparietal sulcus (interparietal sulcus) and transverse parietal sulci
					2%	Paracentral lobule and sulcus						2%	Posterior-dorsal part of the cingulate gyrus (dPCC)
					2%	Superior occipital gyrus						2%	Orbital gyri
					1%	Marginal branch (or part) of the cingulate sulcus						1%	Postcentral gyrus
					1%	Precentral gyrus						1%	Inferior temporal sulcus
					1%	Superior occipital sulcus and transverse occipital sulcus						1%	Long insular gyrus and central sulcus of the insula
					1%	Orbital sulci (H-shaped sulci)						1%	Anterior transverse collateral sulcus
					1%	Inferior frontal sulcus						1%	Superior occipital gyrus
					1%	Inferior occipital gyrus (O3) and sulcus						1%	Posterior ramus (or segment) of the lateral sulcus
					1%	Posterior-dorsal part of the cingulate gyrus (dPCC)						1%	Superior temporal sulcus (parallel sulcus)
					1%	Middle occipital gyrus (O2, lateral occipital gyrus)						1%	Lateral occipito-temporal sulcus
					1%	Long insular gyrus and central sulcus of the insula						1%	Subparietal sulcus
					1%	Short insular gyri						1%	Marginal branch (or part) of the cingulate sulcus
					1%	Occipital pole						1%	Anterior segment of the circular sulcus of the insula
			2	11	64%	Postcentral gyrus	.043					1%	Middle occipital sulcus and lunatus sulcus
					36%	Central sulcus (Rolando’s fissure)						1%	Orbital sulci (H-shaped sulci)
			3	4	100%	Inferior part of the precentral sulcus	.049			2	86	100%	Postcentral sulcus	.040
			4	1	100%	Posterior-ventral part of the cingulate gyrus (vPCC, isthmus of the cingulate gyrus)	.010			3	1	100%	Postcentral sulcus	.031

Cortical Depth

In the BMT group, lower sulcal depths were found in regions like the superior parietal gyrus, precuneus, superior occipital gyrus, cuneus, pericallosal sulcus, and postcentral sulcus in both hemispheres, with p values ranging from .002 to .05 and cluster sizes from 1 to 1,571. Greater depths were noted in the left hemisphere in areas including the insular sulci, lateral fissure, orbital gyri, superior temporal gyrus (planum polare), and transverse temporal gyrus, with p values from .003 to .04 and cluster sizes from 19 to 2025. Similar regions in the right hemisphere showed positive effects, with additional involvement in the superior circular sulcus of the insula and precentral sulcus, with p values from .01 to .05 and cluster sizes from 1 to 2,137.

Gyrification

The BMT group showed significantly higher gyrification compared to controls, particularly in the left hemisphere, including the superior temporal sulcus, superior frontal gyrus, central sulcus, inferior parietal gyrus, and other regions, with p values ranging from .0002 to .05 and cluster sizes from 1 to 11,805. In the right hemisphere, increased gyrification extended to regions such as the superior frontal gyrus, temporal superior gyrus, and precuneus gyrus, with p values from .0002 to .04 and cluster sizes up to 15,112. Lower gyrification indices were observed in the anterior and inferior circular sulci of the insula, with p values from .009 to .05 and cluster sizes from 33 to 809.

Fractal Dimension

Fractal dimension analysis revealed significantly greater values in the BMT group in the left hemisphere, including regions like the superior parietal gyrus, central sulcus, precentral gyrus, and superior frontal gyrus, with p values ranging from .0002 to .04 and cluster sizes up to 1,613. In the right hemisphere, increased fractal dimensions were observed in the calcarine sulcus, cuneus gyrus, and middle frontal gyrus, with p values from .0002 to .04 and cluster sizes up to 493. However, lower fractal dimensions were also noted in both hemispheres, including the lingual gyrus, occipital pole, and temporal pole, with p values from .0002 to .05 and cluster sizes up to 2,340 (Supplementary Figure S2 and Table S6).

Correlation Between Buprenorphine Dose and SBM Metrics

Significant correlations (p < .01) between the change in buprenorphine dosage (initial dose versus dose at six months) and SBM metrics were observed across multiple brain regions.

For cortical depth, significant negative correlations were identified in the parahippocampal region (r = –0.53, p = .007), right planum polare of the superior temporal gyrus (r = –0.54, p = .006), right temporal pole (r = –0.55, p = .005), left superior segment of the circular sulcus of the insula (r = –0.52, p = .008), left anterior transverse collateral sulcus (r = –0.56, p = .004), and right middle occipital sulcus and lunatus sulcus (r = 0.51, p = .009).

For fractal dimension, a significant positive correlation was seen in the right medial orbital sulcus (olfactory sulcus) (r = 0.53, p = .006).

In gyrification, significant positive correlations were observed in the left lateral orbital sulcus (r = 0.56, p = .004), right suborbital sulcus (r = 0.55, p = .005), and left lateral occipito-temporal sulcus (r = 0.58, p = .002) (Table 3 and Supplementary Figure S3).

Table 3.

Correlation Between Buprenorphine Dose and Change in SBM Metrics.

Metrics	Region	BNX Dose
		Pearson Correlation (r)	Sig. (2-tailed)
Change in thickness (FUP-BL)	Left long insular gyrus and central sulcus of the insula	0.46	0.02
	Left short insular gyri	0.41	0.04
	Right superior occipital gyrus	0.39	0.05
	Left planum polare of the superior temporal gyrus	0.41	0.04
	Right posterior transverse collateral sulcus	0.47	0.02
	Right medial orbital sulcus (olfactory sulcus)	0.40	0.05
Change in depth (FUP-BL)	Right fronto-marginal gyrus (of Wernicke) and sulcus	0.42	0.04
	Left orbital part of the inferior frontal gyrus	0.39	0.05
	Right lingual gyrus, lingual part of the medial occipito-temporal gyrus	–0.41	0.05
	Right parahippocampal gyrus, parahippocampal part of the medial occipito-temporal gyrus	–0.53	0.01**
	Left straight gyrus, gyrus rectus	–0.46	0.02
	Left planum polare of the superior temporal gyrus	0.43	0.03
	Right planum polare of the superior temporal gyrus	–0.54	0.01**
	Right temporal pole	–0.55	0.01**
	Left superior segment of the circular sulcus of the insula	–0.52	0.01**
	Left anterior transverse collateral sulcus	–0.56	0.01**
	Right middle occipital sulcus and lunatus sulcus	0.51	0.01**
	Left medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus	–0.47	0.02
Change in fractal dimension (FUP-BL)	Right opercular part of the inferior frontal gyrus	0.41	0.04
	Right superior occipital gyrus	0.43	0.03
	Left calcarine sulcus	0.41	0.04
	Right medial orbital sulcus (olfactory sulcus)	0.53	0.01**
	Left orbital sulci (H-shaped sulci)	0.46	0.02
Change in gyrification (FUP-BL)	Right middle-anterior part of the cingulate gyrus and sulcus (amcc)	0.41	0.04
	Right middle frontal gyrus	0.40	0.05
	Left middle occipital gyrus (lateral occipital gyrus)	0.40	0.05
	Left orbital gyri	0.41	0.04
	Right inferior frontal sulcus	0.46	0.02
	Left lateral occipito-temporal sulcus	0.58	0.01**
	Left lateral orbital sulcus	0.56	0.01**
	Right parieto-occipital sulcus (or fissure)	0.41	0.04
	Right suborbital sulcus (sulcus rostrales, supraorbital sulcus)	0.55	0.01**

** indicates p < .01.

Discussion

Our findings suggest that BMT leads to notable changes in cortical thickness, especially in the occipital and temporal regions. However, six months of BMT is unlikely to alter the sulcal depth, gyrification index, or fractal dimension. Reduced cortical thickness may reflect neuroadaptive changes during BMT. Prior research suggests that cortical thinning in substance use disorders may result from alterations in synaptic density or metabolic processes. ²⁰ However, without functional or behavioral data, the implications of these structural changes for cognition remain unclear. This pruning might also indicate normalization after pathological thickening from chronic substance use, such as inflammation or abnormal synaptic proliferation. ²¹ A reduction in thickness could signal a return to healthier brain architecture as the brain adapts to reduced drug-induced stress. Additionally, decreased cortical thickness may reflect increased neural efficiency and specialization, enhancing cognitive function by focusing specific brain regions on particular tasks and reducing cognitive load. ²² In addition, decreased thickness might indicate the downregulation of hyperactive neural circuits, improving the regulation of behavior and emotions. ²³ Buprenorphine, as a partial opioid agonist, may induce synaptic pruning through neuroplastic changes, aligning with studies showing opioid-induced neuroplasticity in regions related to sensory processing and memory.^24,25 The absence of significant changes in sulcal depth, gyrification, and fractal dimension suggests BMT primarily impacts cortical thickness but does not significantly alter more stable structural features like sulcal morphology within six months.

Clinically, the decrease in cortical thickness in specific regions may reflect a positive neuroadaptive response to BMT, potentially associated with improved cognitive and sensory functions. This could be particularly relevant for the occipital and temporal areas, which are involved in visual processing and memory, respectively. The stability of sulcal depth, gyrification, and fractal dimension suggests that BMT maintains the overall structural integrity of the brain without causing further morphological disruptions. This stability is crucial for maintaining cognitive functions and could support the long-term cognitive health of individuals undergoing BMT. ²⁶

Cortical thinning was primarily observed in the occipital and temporal lobes, including the lingual gyrus, cuneus, and calcarine sulcus. These regions are involved in visual processing, memory encoding, and perceptual integration. ²⁷ Alterations in these areas may be related to the chronic effects of opioid use on sensory and cognitive functions. However, additional research is needed to clarify the behavioral consequences of these structural changes.

Interestingly, studies on opioid dependence have reported alterations in visual and attentional networks, ²⁶ and reductions in occipital and temporal cortical volume have been documented in long-term opioid users. ⁶ Prior studies have consistently found structural brain alterations in individuals with opioid dependence. For example, opioid users show reduced gray matter volume in the frontotemporal and occipital regions, ⁵ as well as white matter integrity deficits in the frontal and limbic areas. ³ Our findings align with these reports, suggesting that BMT may influence cortical structure in these regions. However, the extent to which these changes represent neuroadaptive recovery versus persistent opioid-related alterations remains an open question.

BMT may mitigate the neurotoxic effects of chronic opioid use by promoting synaptic pruning, potentially counteracting cortical atrophy seen in OUD. ²⁸ However, the lack of changes in sulcal depth, gyrification, and fractal dimension indicates that BMT does not reverse all structural brain alterations caused by opioid use, highlighting the need for combined pharmacotherapy with cognitive and behavioral interventions. In contrast, methadone maintenance treatment (MMT) has been linked to significant changes in brain structure, including reductions in white and gray matter integrity and functional connectivity alterations.^9–11 Methadone, a full opioid agonist, has higher neurotoxic potential than buprenorphine, a partial agonist, due to its extensive brain distribution and lipid solubility, which can lead to demyelination, neuronal apoptosis, and impaired neurogenesis.^12,29,30 Methadone use is also associated with cognitive impairments in memory, executive functions, and processing speed.^31,32 BMT, conversely, may improve neurocognitive functions such as memory and executive functioning.^33,34 These findings suggest a potential advantage of BMT over MMT in preserving brain structure and function. While MMT effectively reduces OUD, its neurocognitive impact may influence treatment adherence and relapse rates.^35,36 Further research is needed to optimize maintenance therapies for OUD.

After BMT, wider areas such as the central sulcus, postcentral sulcus, superior frontal gyrus, and precuneus gyrus exhibited greater cortical thickness compared to controls, with larger clusters (BMT 17,200 versus OUD 2,830) and lower p values (BMT 0.00020–0.04860 versus OUD 0.00900–0.04920). Buprenorphine’s ability to upregulate neurotrophic factors like BDNF supports neuronal growth and synaptic plasticity. ³⁷ Increases in cortical thickness likely reflect neuroplastic adaptations due to pharmacotherapy, abstinence, or environmental factors.^38,39 While comparisons between post-treatment OUD participants and controls suggest potential increases in cortical thickness, these findings should be interpreted cautiously, as they may reflect between-group variability rather than treatment effects. Future studies with a single-scanner, larger sample size, and extended follow-up are needed to confirm whether BMT leads to sustained cortical recovery.

The changes in the cortical thickness and larger cluster sizes observed post-BMT indicate more extensive and robust neuroadaptive changes, which could contribute to better treatment adherence, reduced relapse rates, and overall improved quality of life.^26,28 The results for the other SBM metrics were somewhat mixed. Individuals on BMT continued to show lower gyrification, fractal dimension, and sulcal depth. These are considered more stable structural features of the brain, established mainly during development and less prone to change in adulthood. ¹⁸ These metrics are influenced by the fundamental architecture of the cortical surface and are less likely to be altered by short-term pharmacological interventions. The lack of change in these metrics suggests that while buprenorphine induces significant neuroplastic changes that increase cortical thickness, it does not affect the more permanent aspects of brain morphology within the six-month treatment period.

The negative correlation between buprenorphine dose and cortical depth change in the parahippocampal region, superior temporal gyrus, temporal pole, superior insula, and collateral sulcus suggests that higher increases in dosage are linked to reduced cortical depth in these areas. These regions are critical for memory, sensory integration, and emotional regulation, indicating that dose-dependent modulation may reflect adaptive changes in sensory and affective processing. In contrast, for gyrification, positive correlations in the lateral orbital region, suborbital sulcus, and lateral occipito-temporal region indicate that increased dosage changes may promote enhanced cortical folding, which has been linked to improved cognitive flexibility. ⁴⁰ The positive correlation between buprenorphine dose and change in fractal dimension in the medial orbitofrontal cortex suggests a dose-dependent increase in cortical complexity. This region is associated with decision-making and reward processing, implying that higher dose adjustments may enhance neural integration or connectivity in these circuits. ⁴¹

The lack of overlap between regions exhibiting significant cortical thickness changes over six months of BMT and those showing dose-dependent changes in SBM metrics suggests distinct, region-specific neuroadaptive processes. While longitudinal changes in cortical thickness were primarily observed in occipital and occipito-temporal regions, dose-related SBM changes were confined to temporal, frontal, and insular areas. This non-overlap indicates that the neuroplastic effects of BMT are not uniformly distributed but may be driven by separate mechanisms: general cortical thinning may reflect adaptive or degenerative changes associated with OUD and treatment, whereas dose-dependent changes in depth, fractal dimension, and gyrification may represent targeted neuroadaptive responses to buprenorphine exposure.

One limitation of this study is the relatively short six-month observation period for structural brain changes, which may not capture long-term neuroplastic adaptations. More than one-third (36%) of OUD participants used tobacco, while the control group consisted of non-nicotine users. Nicotine use itself has been associated with neurostructural alterations, including reduced cortical thickness and decreased gray matter volume, particularly in the prefrontal cortex, anterior cingulate cortex, insula, and other brain regions involved in cognitive and emotional processing.^42–44 These effects may confound distinctions attributed solely to opioid use and buprenorphine treatment. Thus, the observed cortical morphometric differences between groups could partially reflect nicotine’s independent impact. Future studies should include control groups with matched nicotine use to isolate opioid-specific and treatment-related neuroanatomical changes better. We did not restrict recruitment to males by design; however, no female participants presented to the treatment center during the study period. This likely reflects the relatively low prevalence of OUD among women in India and the treatment-seeking patterns in public healthcare, where stigma and sociocultural barriers may disproportionately deter women from accessing care. While this limitation reflects the realities of our recruitment setting, it nevertheless constrains the generalizability of our findings. Women with OUD often exhibit distinct opioid use patterns, comorbidities, and relapse predictors compared to men, ⁴⁵ and hormonal influences are known to modulate opioid receptor sensitivity and neural plasticity. ⁴⁶ These factors potentially contribute to sex differences in brain structure and function related to OUD. Another limitation is the reliance on SBM metrics alone, without integrating other neuroimaging techniques that could provide complementary insights into white matter integrity and functional connectivity. Moreover, we did not perform psychometric assessments of depression and anxiety. Given that affective symptoms can influence neuroplasticity and cortical structure, future studies should assess whether the reported structural changes are independent of mood variations over time. Likewise, while buprenorphine was the primary medication of interest, some participants may have been prescribed adjunct medications (e.g., antidepressants, anxiolytics). However, these were not systematically recorded, which presents a potential limitation in controlling for medication effects on brain structure. The absence of a longitudinal control group makes it challenging to disentangle the specific effects of buprenorphine from other potential recovery-related changes. 56% of the OUD group and 36% of controls belonged to lower SES, with the remainder drawn from other strata. As participants were recruited from a publicly funded healthcare facility in India, this SES distribution reflects the treatment-seeking population at our center. Notably, there was no statistically significant difference in SES between the OUD and control groups, making it unlikely that SES confounded the present findings. Nevertheless, the predominance of lower SES participants may limit the generalizability of our results. Future research should purposively recruit from a broader SES spectrum and statistically adjust for SES to more definitively assess its role. Future research should prioritize larger, multi-site cohorts with more extended follow-up periods to validate cortical morphometric changes as potential biological markers for treatment monitoring. Such efforts will be crucial to translating neuroimaging findings into clinically useful biomarkers for OUD management.

Conclusions

BMT can lead to significant changes in cortical thickness, particularly in the occipital and temporal regions, while maintaining overall brain structural integrity without altering sulcal depth, gyrification, or fractal dimension within six months. Future studies should investigate the long-term effects of BMT on brain health, utilizing larger and more diverse samples, as well as extended follow-up periods. While our findings highlight dose-dependent and region-specific neuroadaptive changes with buprenorphine maintenance, larger studies are needed to establish cortical morphometric metrics as reliable biological markers to guide personalized treatment in OUD.