This systematic review underscores the rapidly expanding application of quantitative susceptibility mapping (QSM) in pediatric neuroimaging, with 85% of included studies published within the last 5 years, reflecting the escalating interest in susceptibility-based biomarkers of brain development. The physiologic basis of QSM—its sensitivity to the magnetic properties of iron, myelin, calcium, and other microstructural contributors—provides a unique contrast mechanism that complements and extends conventional magnetic resonance imaging (MRI). In the developing brain, where dynamic iron redistribution, oligodendrocyte maturation, and axonal myelination evolve in tightly regulated trajectories, QSM offers a quantitative window into processes that were previously only inferable through indirect imaging proxies.

Normative pediatric studies consistently delineate age-dependent susceptibility increases across deep gray matter nuclei, particularly within the globus pallidus, putamen, and caudate. These trajectories reflect the combined influence of iron accumulation and myelin-related susceptibility changes and appear to follow nonlinear maturational curves across infancy, childhood, and adolescence. Importantly, QSM-derived normative datasets provide a quantitative scaffold against which pathological deviations can be assessed. However, the scarcity of large longitudinal cohorts remains a significant limitation; current datasets are often cross-sectional and regionally restricted. Future initiatives should prioritize multiethnic longitudinal sampling to account for demographic and environmental modifiers of susceptibility values, ensuring generalizability and clinical interpretability [12, 26, 30, 33].

Neurodevelopmental disorders constitute the most mature area of pediatric QSM research to date. In autism spectrum disorder (ASD), several studies have demonstrated regionally reduced magnetic susceptibility in subcortical structures and white matter pathways, with some findings correlating with cognitive, motor, or behavioral outcomes [25, 27, 29, 31]. These patterns may reflect altered iron metabolism, atypical myelin development, or disrupted neuroinflammatory pathways. Nevertheless, the heterogeneity of findings underscores the need for harmonized pipelines, larger samples, and the integration of QSM with genetic, metabolic, and behavioral phenotyping. In attention-deficit/hyperactivity disorder (ADHD), preliminary evidence suggests altered iron-related susceptibility within the basal ganglia [24, 28], although results remain inconsistent due to small sample sizes, divergent reconstruction methods, and substantial clinical heterogeneity [22]. Standardizing susceptibility quantification and improving motion control will be essential to resolving these inconsistencies.

Clinical applications beyond neurodevelopmental syndromes illustrate QSM’s broader diagnostic and prognostic potential. In pediatric epilepsy, QSM enhances lesion conspicuity by revealing subtle iron-related abnormalities and microstructural changes not identifiable on T1- or T2-weighted imaging. These susceptibility abnormalities may reflect hemosiderin deposition, altered myelin architecture, or chronic inflammatory changes, thereby offering valuable information for pre-surgical mapping and lesion characterization [19]. In cerebral palsy, susceptibility shifts following autologous cord-blood therapy have demonstrated diamagnetic changes consistent with increased myelin content, highlighting QSM’s potential as a quantitative biomarker of neuroregenerative treatment response [35]. Early investigations in pediatric traumatic brain injury and concussion reveal that susceptibility alterations within frontal white matter pathways may serve as predictors of persistent post-concussive symptoms, although these early findings require prospective, multi-center validation [17].

Several additional domains remain underrepresented but show promising early signals. These include pediatric neurodegeneration [16], cerebrovascular and perfusion-related disorders such as arteriovenous malformations or moyamoya disease [21, 23], and metabolic or psychiatric conditions including prenatal alcohol exposure [34, 35]. Given QSM’s sensitivity to iron dysregulation and microstructural integrity, its application across these domains may uncover novel biomarkers of disease severity, chronicity, or treatment responsiveness.

Despite encouraging progress, several barriers impede the full clinical translation of QSM in pediatric imaging. Substantial methodological heterogeneity—including differences in echo times, multi-echo acquisition design, field strengths, unwrapping and background-field removal algorithms (e.g., Laplacian-based methods, SHARP/RESHARP), and dipole inversion techniques—limits cross-study comparability. Pediatric susceptibility measurements are especially sensitive to motion artifacts; thus, motion-robust acquisition strategies (e.g., radial sampling, navigator echoes, real-time prospective motion correction) and AI-assisted reconstruction will be essential to ensure reproducible quantification. The dominance of studies conducted on 3-T MRI systems reflects the need for high signal-to-noise ratios when probing subtle susceptibility variations in small pediatric structures. Moreover, the geographic concentration of studies—largely from Asia, particularly China—highlights the need for broader international collaboration to ensure demographic, environmental, and ethnocultural diversity in normative references.

Looking ahead, critical priorities must be addressed to enable the routine clinical use of QSM in pediatric neuroradiology. First, acquisition and reconstruction workflows require standardization across vendors and institutions, supported by consensus guidelines and phantom-based quality assurance programs. Second, multi-center longitudinal studies that follow children from infancy through adolescence are essential for mapping normative susceptibility trajectories and identifying the developmental windows most sensitive to pathological divergence. Third, integrating QSM with multimodal approaches—including diffusion MRI, myelin-sensitive imaging, resting-state fMRI, MR spectroscopy, and emerging metabolic imaging tools—may offer a more comprehensive understanding of neurodevelopmental dynamics. Finally, building open-access, age-stratified normative databases and implementing automated, region-specific quantification pipelines will accelerate QSM’s adoption as a practical biomarker for diagnosis, prognosis, and monitoring therapeutic response.

So, QSM represents a powerful and increasingly mature tool in pediatric neuroimaging, capable of quantifying biologically meaningful aspects of brain development and pathology that remain inaccessible to conventional MRI. Realizing its clinical potential will require coordinated methodological standardization, expanded longitudinal datasets, multimodal integration, and widespread international collaboration. With these steps, QSM is poised to evolve from a research-focused technique to a clinically actionable biomarker across a broad spectrum of pediatric neurological disorders.