2f:I[703058,["/_next/static/immutable/chunks/3bhq_5eh1d760.js","/_next/static/immutable/chunks/1855-ogyi8eh4.js","/_next/static/immutable/chunks/2pfsjpn6k6zlg.js","/_next/static/immutable/chunks/26c7v3_3uwnwu.js","/_next/static/immutable/chunks/25a3ozcrvi1ff.js","/_next/static/immutable/chunks/2r4wx50nvjh_4.js","/_next/static/immutable/chunks/23fsw06hsi5b1.js","/_next/static/immutable/chunks/06_yt270h41rg.js","/_next/static/immutable/chunks/3ezsiz-7shkna.js","/_next/static/immutable/chunks/20x2y96ldu5wx.js","/_next/static/immutable/chunks/2lxntcm3pd1_h.js","/_next/static/immutable/chunks/00dgco8irq3jw.js","/_next/static/immutable/chunks/00nwe-kq0rboc.js","/_next/static/immutable/chunks/2051ffx3xzio9.js"],"PaperListPageClient"] 30:T493,The discovery cohort comprised 446 children with ADHD (mean [SD] age, 11.5 [2.6] years; 339 male [76.0%]) and 708 controls (mean [SD] age, 11.0 [2.3] years; 429 male [60.6%]), whereas the validation cohort included 554 children with ADHD (mean [SD] age, 10.1 [2.8]; 372 male [67.1%]) and 123 controls (mean [SD] age, 10.1 [3.0]; 70 male [56.9%]). ADHD exhibited atypical hub organization across all 3 topological metrics, with significant case-control differences primarily localized to a covarying multimetric component in the orbitofrontal cortex. Three biotypes emerged: severe-combined with emotional dysregulation (widespread medial prefrontal cortex-pallidum alterations, n = 142), predominantly hyperactive/impulsive (anterior cingulate cortex-pallidum circuit alterations, n = 177), and predominantly inattentive (superior frontal gyrus alterations, n = 127), each characterized by distinct clinical profiles and longitudinal trajectories. These neural profiles of each biotype showed distinct neurochemical and functional correlates. Critically, the core findings were replicated in the validation cohort, demonstrating robust generalizability.31:Tb5d,Attention-deficit/hyperactivity disorder (ADHD) is characterized by considerable clinical heterogeneity, and existing classification frameworks constrain the development of neurobiologically informed subtyping approaches. To investigate whether normative modeling of topological properties derived from brain morphometry similarity networks can provide robust stratification markers for children with ADHD. This case-control study leveraged multisite cross-sectional neurodevelopmental datasets with a longitudinal follow-up cognitive assessment for a subset. Morphometric similarity networks were constructed and normative models were developed for 3 topological metrics: degree centrality, nodal efficiency, and participation coefficient. Through semisupervised clustering, putative biotypes were delineated and their clinical profiles were examined. Brain profiles of these biotypes were further contextualized in terms of their neurochemical and functional correlates using large-scale databases, and model generalizability was assessed with external validation performed in an independent transdiagnostic cohort. Study data were analyzed from November 2023 to January 2025. Normative modeling of topological properties derived from brain morphometry. Topological deviations in morphometric similarity networks derived from brain structural image. The discovery cohort comprised 446 children with ADHD (mean [SD] age, 11.5 [2.6] years; 339 male [76.0%]) and 708 controls (mean [SD] age, 11.0 [2.3] years; 429 male [60.6%]), whereas the validation cohort included 554 children with ADHD (mean [SD] age, 10.1 [2.8]; 372 male [67.1%]) and 123 controls (mean [SD] age, 10.1 [3.0]; 70 male [56.9%]). ADHD exhibited atypical hub organization across all 3 topological metrics, with significant case-control differences primarily localized to a covarying multimetric component in the orbitofrontal cortex. Three biotypes emerged: severe-combined with emotional dysregulation (widespread medial prefrontal cortex-pallidum alterations, n = 142), predominantly hyperactive/impulsive (anterior cingulate cortex-pallidum circuit alterations, n = 177), and predominantly inattentive (superior frontal gyrus alterations, n = 127), each characterized by distinct clinical profiles and longitudinal trajectories. These neural profiles of each biotype showed distinct neurochemical and functional correlates. Critically, the core findings were replicated in the validation cohort, demonstrating robust generalizability. Results of this case-control study reveal that the integration of normative modeling with semisupervised clustering provided both dimensional and categorical insights into ADHD heterogeneity, identifying 3 distinct ADHD biotypes with unique clinical-neural profiles that advance the understanding of ADHD's neurobiological complexity and lay the groundwork for personalized management.32:T1034, Importance Attention-deficit/hyperactivity disorder (ADHD) is characterized by considerable clinical heterogeneity, and existing classification frameworks constrain the development of neurobiologically informed subtyping approaches. Objective To investigate whether normative modeling of topological properties derived from brain morphometry similarity networks can provide robust stratification markers for children with ADHD. Design, Settings, and Participants This case-control study leveraged multisite cross-sectional neurodevelopmental datasets with a longitudinal follow-up cognitive assessment for a subset. Morphometric similarity networks were constructed and normative models were developed for 3 topological metrics: degree centrality, nodal efficiency, and participation coefficient. Through semisupervised clustering, putative biotypes were delineated and their clinical profiles were examined. Brain profiles of these biotypes were further contextualized in terms of their neurochemical and functional correlates using large-scale databases, and model generalizability was assessed with external validation performed in an independent transdiagnostic cohort. Study data were analyzed from November 2023 to January 2025. Exposures Normative modeling of topological properties derived from brain morphometry. Main Outcomes and Measures Topological deviations in morphometric similarity networks derived from brain structural image. Results The discovery cohort comprised 446 children with ADHD (mean [SD] age, 11.5 [2.6] years; 339 male [76.0%]) and 708 controls (mean [SD] age, 11.0 [2.3] years; 429 male [60.6%]), whereas the validation cohort included 554 children with ADHD (mean [SD] age, 10.1 [2.8]; 372 male [67.1%]) and 123 controls (mean [SD] age, 10.1 [3.0]; 70 male [56.9%]). ADHD exhibited atypical hub organization across all 3 topological metrics, with significant case-control differences primarily localized to a covarying multimetric component in the orbitofrontal cortex. Three biotypes emerged: severe-combined with emotional dysregulation (widespread medial prefrontal cortex-pallidum alterations, n = 142), predominantly hyperactive/impulsive (anterior cingulate cortex-pallidum circuit alterations, n = 177), and predominantly inattentive (superior frontal gyrus alterations, n = 127), each characterized by distinct clinical profiles and longitudinal trajectories. These neural profiles of each biotype showed distinct neurochemical and functional correlates. Critically, the core findings were replicated in the validation cohort, demonstrating robust generalizability. Conclusions and Relevance Results of this case-control study reveal that the integration of normative modeling with semisupervised clustering provided both dimensional and categorical insights into ADHD heterogeneity, identifying 3 distinct ADHD biotypes with unique clinical-neural profiles that advance the understanding of ADHD’s neurobiological complexity and lay the groundwork for personalized management. 25:[[["$","script","0",{"type":"application/ld+json","dangerouslySetInnerHTML":{"__html":"{\"@context\":\"https://schema.org\",\"@type\":\"CollectionPage\",\"name\":\"Structural MRI Neuroimaging: modality Research & Clinical Takeaways\",\"description\":\"Explore peer-reviewed papers on Structural MRI Neuroimaging (modality). Clinician-written summaries and actionable practice insights. 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Key case-control brain differences localized to the orbitofrontal cortex. Findings replicated in the validation cohort.","limitations":"- Cross-sectional design for the main sample limits causal inference; longitudinal data only available for a subset.\n- Male-predominant sample (76% in discovery cohort) may limit generalizability to females.\n- Multisite data introduces potential site-related noise despite normative modeling controls.","practice_takeaway":"ADHD in children is not neurobiologically uniform — three brain-based biotypes with distinct clinical profiles and trajectories can be identified using structural MRI. 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