Central nervous system (CNS) infections remain a significant cause of morbidity and mortality worldwide, with complex pathophysiology and diverse clinical presentations. Early and accurate diagnosis is paramount in optimizing therapeutic strategies and improving patient outcomes. However, conventional neuroimaging modalities, such as magnetic resonance imaging (MRI) and computed tomography (CT), have inherent limitations in specificity and sensitivity when detecting certain CNS infections or delineating their extent[1, 2]. Advancements in neuroimaging, particularly with the introduction of magnetization transfer imaging (MTI), promise enhanced diagnostic accuracy by providing unique contrast mechanisms sensitive to tissue microstructural changes invisible to routine imaging[3].

CNS infections involve a wide range of causes, including bacterial, viral, fungal, and parasitic agents. Detecting and classifying these infections is difficult because traditional imaging often shows nonspecific changes such as brain swelling, meningeal enhancement, or mass effects that can resemble other conditions like tumours or inflammatory diseases. The variable and complex nature of infectious lesions makes imaging interpretation even harder. CT scans, although commonly available, have limited soft tissue detail and are not ideal for detailed assessment. Conventional MRI offers better soft tissue contrast but often cannot specifically identify changes in tissue microstructure, which are important in early infection. Additionally, routine imaging methods may not clearly differentiate between active infection, inflammation, or tissue damage from normal variations, highlighting the need for advanced imaging techniques to improve accuracy[1, 2].

Magnetization transfer imaging has emerged as a promising approach that complements existing MRI sequences. MTI leverages the exchange of magnetization between protons bound to macromolecules and free water protons, translating these interactions into quantifiable imaging contrast that reflects underlying tissue integrity and macromolecular content[³]. Importantly, MTI can detect early microstructural alterations such as myelin loss, inflammation, or gliosis, which are frequently involved in infectious processes but not readily visualized with standard MRI[4]. Since its clinical introduction in the 1990s, MTI has gained traction in neuroradiology, becoming an essential tool for improved tissue characterization in various CNS disorders including multiple sclerosis, tumours, and infections[5].

This review aims to provide a comprehensive overview of magnetization transfer imaging, focusing on its applications in detecting and characterizing CNS infections. We will discuss the fundamental biophysical principles of MT imaging, review imaging protocols, and highlight clinical findings from tuberculosis, viral, and fungal CNS infections. Additionally, the review covers the differentiation of infections from neoplastic and inflammatory lesions, advances in quantitative MT techniques, and the role of MTI in monitoring treatment response and prognosis. By integrating recent research findings and outlining future perspectives, this article seeks to delineate the potential and challenges of MT imaging in enhancing diagnostic precision and clinical management of CNS infections[6].

A comprehensive literature search was carried out using PubMed, Scopus, Web of Science, and Google Scholar to identify studies on magnetization transfer imaging (MTI) in central nervous system infections. Keywords and MeSH terms such as “magnetization transfer imaging,” “magnetization transfer ratio,” “quantitative magnetization transfer,” “CNS infections,” “tuberculous meningitis,” “HIV,” “progressive multifocal leukoencephalopathy,” and “fungal infections” were used in various combinations. Only English-language articles including original research, reviews, and clinical or experimental studies with relevant imaging data were considered, while case reports without imaging, non-CNS studies, and unrelated articles were excluded. Titles, abstracts, and full texts were screened, and additional references were retrieved from bibliographies of selected papers. Data on study design, patient population, imaging protocols, MT metrics, and clinical applications were extracted. The findings were synthesized narratively due to heterogeneity of study methods and outcomes.

Magnetization transfer imaging (MTI) relies on the exchange of magnetization between free water protons and those bound to macromolecules like proteins, lipids, and myelin. Off-resonance RF pulses selectively saturate the bound proton pool, transferring this effect to free water protons and reducing the MRI signal, which forms the basis of magnetization transfer contrast quantified as the magnetization transfer ratio (MTR)[3] as shown in [Fig. 1]. MTR indicates macromolecular density and integrity, serving as a sensitive marker for microstructural changes such as demyelination, edema, and gliosis. Advanced quantitative metrics, including pool size ratio (PSR) and exchange rates, provide better tissue characterization by accounting for confounding factors affecting MTR, thus enhancing biological specificity[7]. Biophysical models, such as two-pool exchange models, further assist in MT signal interpretation and protocol optimization[8].

In CNS infections, MT sensitively detects tissue macromolecular changes caused by host-pathogen interactions. Myelin disruption decreases MTR due to reduced macromolecular proton pools, while edema and gliosis alter water content and macromolecular environments, affecting MT signals. These changes often occur before conventional imaging abnormalities, allowing early detection of pathology[3] the correlation between MT changes and histopathology supports its role as a surrogate marker of tissue integrity[4]. Studies show MTI-detectable microstructural damage such as Wallerian degeneration and gliosis that are not visible on T1- or T2-weighted MRI[9].

Technical parameters such as RF pulse design, including amplitude, offset frequency, and duration, significantly influence MT contrast. Techniques like selective inversion recovery (SIR) and bSSFP enhance acquisition and quantitative accuracy[10]. MRI field strength impacts image quality, with 3T systems offering better SNR and resolution but requiring calibration for field inhomogeneities[11]. Under optimized conditions, MTR and qMT parameters show acceptable reproducibility, supporting MTI’s utility in longitudinal CNS disease monitoring[12] as shown in [Table. 1].  

Tuberculous infections of the CNS, including tuberculous meningitis (TBM) and tuberculous encephalitis, pose significant diagnostic challenges due to the often-indolent onset and heterogeneous imaging features. MT imaging has demonstrated superior sensitivity in detecting meningeal involvement by tuberculosis compared to conventional MRI sequences. Pre-contrast T1-weighted MT images provide exceptional visibility of thickened meninges characteristic of TBM, a feature rarely evident on routine MRI. Elevated meningeal enhancement on post-contrast MT images further aids in assessment, as shown in [Fig. 2]. Quantitative magnetization transfer ratios derived from affected meninges in TBM patients show significant increases relative to non-tuberculous meningitis, reflecting the unique macromolecular and cellular composition of tuberculous exudates and inflammatory infiltration[6]. MTI also facilitates evaluation of cerebrospinal fluid (CSF) spaces and perilesional parenchymal changes in tuberculous infections, revealing alterations not readily identified on traditional imaging, thereby improving diagnostic confidence[1].

Early detection of tuberculous lesions is crucial for timely intervention. MT imaging’s enhanced sensitivity enables visualization of granulomatous lesions that may be subtle or occult on conventional MRI scans. This sensitivity is vital for identifying early pathology and differentiating tuberculous granulomas from neoplastic or other infectious masses. The combination of MTI with other advanced MRI modalities such as diffusion-weighted imaging and proton magnetic resonance spectroscopy offers comprehensive tissue characterization, assessing lesion cellularity, necrosis, and metabolic profiles in tandem with macromolecular integrity captured by MTR values[1]. In particular, contrast-enhanced MT imaging improves the contrast-to-noise ratio, enhancing visualization of small or deep-seated lesions and facilitating accurate differential diagnosis[13].

MT ratio changes in tuberculous lesions correlate with treatment response and disease progression, making MTI a promising tool for monitoring therapy effectiveness. Decreasing MTR values in lesions may reflect ongoing demyelination, edema, or necrosis, whereas stabilizing or increasing ratios could indicate recovery or successful resolution. Such dynamic changes support the incorporation of MT imaging into clinical monitoring protocols for CNS TB[6]. However, challenges remain for widespread clinical adoption, including limited availability of MTI in resource-constrained settings often burdened by tuberculosis, variability in imaging protocols, and the need for standardized quantitative thresholds. Additionally, overlapping MT signatures between tuberculous and other granulomatous or inflammatory lesions warrant cautious interpretation, underscoring the necessity for multimodal imaging and clinical correlation[2].

Viral infections of the CNS, especially those related to human immunodeficiency virus (HIV), have been extensively studied using MT imaging due to the microstructural brain changes associated with infection and immune response. Longitudinal MT imaging in simian immunodeficiency virus (SIV) models, which closely mirror human HIV neuropathology, reveals progressive reductions in magnetization transfer ratios across brain regions, reflective of demyelination, neuronal loss, and neuroinflammation. Such MTR declines correlate strongly with immunologic biomarkers, including reductions in CD4+ T cell counts and elevations in CD8+ cells, suggesting a link between viral load, immune system status, and brain tissue integrity[4]. These findings affirm the sensitivity of MT imaging for detecting diffuse white matter damage in HIV-associated neurocognitive disorders (HAND), even when conventional imaging appears normal[14]. Shown in [Fig. 3].

Progressive multifocal leukoencephalopathy (PML), a demyelinating disease caused by the JC virus, represents a critical viral CNS infection wherein early detection significantly influences prognosis. MT imaging improves identification of PML lesions by revealing microstructural disruptions and demyelination with higher sensitivity than conventional MRI. Importantly, MTI aids in distinguishing PML from other demyelinating or infectious diseases through unique magnetization transfer profiles associated with oligodendrocyte loss and gliosis[15]. Furthermore, longitudinal MT imaging facilitates monitoring of lesion evolution and treatment responses, providing clinicians with valuable biomarkers for therapy effectiveness in viral encephalopathies[16].

MT imaging is often integrated with diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) for a nuanced evaluation of neuro-infections. While MTI assesses the integrity of macromolecular structures and myelin, DTI explores axonal integrity through fractional anisotropy and diffusivity measures, and MRS evaluates metabolic alterations. This multimodal approach enriches diagnostic accuracy and provides insights into cognitive impairment pathogenesis associated with viral CNS infections[14]. Despite advances, challenges remain, such as variability in MT measurements, technical demands of quantitative imaging, and the overlap of MT alterations with other neurodegenerative processes, motivating continued research and methodological refinement[16].

Fungal infections of the CNS have become increasingly prevalent, especially among immunocompromised populations. These infections present distinctive challenges due to the variable virulence of fungal strains and complex immune interactions that impact the macromolecular environment of affected CNS tissues. Fungal invasion may result in meningitis, abscess formation, encephalitis, or vascular complications, each associated with characteristic changes in tissue macromolecular content detectable through MT imaging[17]. MTI’s sensitivity to such macromolecular alterations offers potential for earlier and more specific identification of fungal lesions compared to routine MRI or CT imaging[2]. However, fungal infections often mimic neoplastic or bacterial pathology radiologically, and distinguishing them relies on the integration of clinical, laboratory, and advanced imaging findings.

Clinical studies on MTI in fungal CNS infections remain limited, but preliminary evidence suggests MTI can effectively delineate meningeal involvement and parenchymal changes such as gliosis or abscess capsules, manifested by altered MTR values within affected regions. These imaging markers may correlate with disease severity and clinical outcomes, though systematic correlation is lacking[2].

Comparisons between MTI and conventional MRI in fungal infections highlight MTI’s superior contrast for macromolecular disruption but also emphasize difficulties in conclusively differentiating infectious etiologies without adjunct imaging or histopathology. Shown in [Fig. 4].

Future prospects in this domain call for larger-scale, prospective studies to validate MTI parameters as reliable biomarkers of fungal CNS involvement. Integration of MT imaging with other advanced MR modalities, including diffusion techniques and molecular imaging agents targeted at fungal metabolism, may potentiate diagnostic precision[17]. Further exploration into MTI’s role in monitoring antifungal therapy response is warranted, with the promise of tailoring treatment strategies based on dynamic imaging biomarkers.

Differentiating infectious from neoplastic and inflammatory CNS lesions remains a cornerstone issue in neuroimaging. Magnetization transfer imaging enhances lesion characterization by amplifying contrast-to-noise ratios, particularly when combined with gadolinium-based contrast agents. Comparative studies have demonstrated that gadolinium-enhanced MTI significantly improves tissue contrast in CNS tumours and infections, enabling detection of pathological tissue beyond gross lesion margins apparent on conventional sequences[13]. MTI reveals macromolecular alterations related to edema, tumour infiltration, or inflammatory cell infiltration that extend into ostensibly normal-appearing tissue, thereby improving delineation and diagnostic accuracy[3]. Distinctive enhancement patterns and MTR profiles can differentiate infectious meningitis from neoplastic causes of meningeal involvement, refining differential diagnoses[7].

MTI also permits discrimination between infectious and autoimmune neuroinflammatory lesions. For example, patients with neuropsychiatric systemic lupus erythematosus (NPSLE) exhibit characteristic MT ratio reductions reflecting microscopic brain damage, which differ quantitatively and qualitatively from infectious causes[5]. Research has further identified associations between MT parameters and specific autoantibodies, highlighting the role of MTI in detecting subtle diffuse brain injury in inflammatory states[⁵]. In demyelinating diseases such as multiple sclerosis, MT ratio changes correspond to gliosis, demyelination, and axonal degeneration, assisting in differentiating inflammatory demyelination from infectious pathology[6].

Optimizing diagnostic accuracy often requires a combination of imaging approaches. MTI combined with diffusion-weighted imaging (DWI) and MRS integrates microstructural, diffusion, and metabolic information, collectively enhancing lesion characterization[13]. Development of quantitative MTI protocols offers robust tissue characterization to overcome limitations of qualitative assessments alone[4]. Nonetheless, overlapping imaging features among infections, tumours, and inflammatory lesions occasionally complicate interpretation, underscoring the importance of multimodal imaging and clinical context for precise diagnosis[1, 2, 11].

Quantitative magnetization transfer imaging (qMT) provides detailed characterization of tissue microstructure through mathematical modelling of magnetization exchange processes. Parameters derived from qMT include the pool size ratio reflecting relative macromolecular content and exchange rates between bound and free proton pools, offering deeper insights beyond conventional MTR measurements[7]. Techniques such as selective inversion recovery (SIR) and balanced steady-state free precession (bSSFP) have been refined to maximize signal-to-noise ratios and measurement efficiency. These approaches allow for accurate and rapid quantification of qMT parameters, facilitating clinical feasibility[8, 10].

Despite advances, reproducibility remains crucial for clinical translation. Studies demonstrate acceptable inter- and intra-subject variability for key qMT measurements when standardized protocols and correction methods for B1 inhomogeneities are employed[12]. This reliability supports applications in detecting subtle microstructural changes invisible to standard imaging, including alterations in normal-appearing white matter found in patients with CNS infections or neurodegenerative conditions[4, 11]. Furthermore, qMT imaging shows strong correlation with myelin content and axonal integrity, reinforcing its biological relevance in tissue characterization[4, 6].

Clinical implementation demands technical refinement including optimization of field strength usage, sequence parameters, and efficient scan times to fit into routine workflows[11]. Post-processing techniques involving image calibration and bias correction improve standardization across imaging centers, ensuring cross-study comparability[2, 9]. Integration of qMT into clinical neuroradiology promises improved diagnostic precision, longitudinal monitoring, and therapeutic assessment in CNS infectious pathologies.

MT imaging offers valuable biomarkers for assessing therapeutic response and lesion evolution in CNS infections. Serial MT measurements reveal dynamic MTR changes corresponding with demyelination and subsequent remyelination or repair processes. For example, in acute optic neuritis often associated with infectious or autoimmune etiologies, MTI tracks early MTR decreases due to axonal transection and myelin loss, followed by later increases reflecting remyelination, aligning with clinical and electrophysiological metrics[4, 6]. Similar principles apply to CNS infections such as neuro-AIDS and tuberculosis, where MTR changes correspond with neurodegeneration and tissue repair mechanisms[4].

Longitudinal MTI also identifies perilesional gliosis progression and lesion resolution. In patients with cerebral cyst cerci-related epilepsy, persistent perilesional gliosis detected by MTI correlates with seizure recurrence and treatment challenges, highlighting its prognostic value[1, 2]. MT abnormalities have been linked with cognitive impairment severity and clinical outcomes in viral encephalopathies, reinforcing the clinical utility of MT metrics as surrogate markers for neurological disability[14]. Such prognostic indicators assist clinicians in treatment planning and risk stratification.

Nevertheless, challenges exist in standardizing MTI-based biomarkers across diverse clinical settings due to variations in imaging protocols, scanner hardware, and patient populations. Longitudinal multi-centre studies are necessary to validate predictive MTI models and incorporate them into clinical guidelines. Additionally, combining MT measures with other biomarkers such as neuropsychological assessments and fluid biomarkers promises comprehensive patient management strategies.

The combination of MTI with other advanced imaging techniques enhances diagnostic accuracy and pathophysiological understanding of CNS infections. Diffusion tensor imaging (DTI) complements MTI by assessing axonal integrity and connectivity through metrics such as fractional anisotropy and mean diffusivity. Simultaneous use of MT and DTI provides a comprehensive picture of myelin and axonal pathology in neuro-infections[4, 6]. Magnetic resonance spectroscopy (MRS) adds metabolic insights, detecting biochemical alterations such as lactate accumulation or N-acetyl aspartate reductions, which, when combined with MT metrics, afford a multidimensional assessment of infectious brain lesions[1]. Together, these modalities facilitate differentiation of complex lesions and improve clinical decision-making.

Novel imaging techniques related to MTI are being developed. Although chemical exchange saturation transfer (CEST) imaging is not yet widely applied in CNS infections, it offers group-specific contrast sensitive to exchangeable protons in metabolites and proteins, contributing an additional layer of molecular imaging[4]. Ultra-high field MRI enhances spatial resolution and signal fidelity, improving visualization of subtle microstructural brain abnormalities relevant to infectious pathology[6, 10]. Additionally, emerging pulse sequences based on polarization transfer and steady-state free precession, such as INEPT-SSFP, aim to boost signal-to-noise ratios and imaging efficiency in MTI applications, potentially broadening its clinical utility[11].

These advancements contribute to contextually rich imaging biomarkers, facilitating personalized medicine approaches in neuroinfectious diseases. Quantitative imaging parameters can inform tailored treatment strategies by monitoring neuroinflammation, immune responses, and tissue recovery. The integration of machine learning and artificial intelligence into MT image analysis may further improve lesion classification accuracy, predictive modelling, and clinical workflow efficiency, heralding a new era in infectious disease neuroimaging.

Quantitative magnetization transfer (qMT) imaging offers a major advancement over conventional MTR by enabling reproducible, tissue-specific quantification of macromolecular content, thereby improving diagnostic accuracy and supporting longitudinal assessments[6]. To reduce inter-site variability and promote clinical adoption, Van der Weijden et al. proposed standardized protocols using Gaussian-shaped saturation pulses, 8–12 offset frequencies (1–50 kHz), and Bloch–Siegert B1 correction, which reduced pulse shape variability from 32% to 8%, offset frequency from 25% to 6%, and B1 correction from 15% to 3%[6].

Integrating MTI with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) enhances tissue characterization. Zhao et al. demonstrated that combining FA with MTR in HIV-associated neurocognitive disorder (HAND) distinguished axonal loss (↓FA, preserved MTR) from demyelination (↓MTR, preserved FA) with an AUC of 0.94[8]. Similarly, in HSV encephalitis, MTI with NODDI revealed dendritic injury, with ODI changes correlating with MT metrics[9].

Artificial intelligence further accelerates MTI applications. CNNs achieved 94% accuracy in PML lesion segmentation, reducing processing time from 45 to 2 minutes. Random forest models predicted HAND progression (AUC 0.89) using MTR, CD4 count, and viral load[10].

Together, acquisition standardization, multimodal integration, and AI-driven tools position qMT as a robust biomarker in CNS infections, supporting its adoption in precision neuroimaging workflows.

The integration of magnetization transfer imaging (MTI) into routine neuroimaging workflows holds substantial clinical promise for improving the management of CNS infections. By revealing microstructural damage such as demyelination, gliosis, and inflammation in normal-appearing brain tissue, MTI provides a non-invasive window into early and occult pathology that is often missed on conventional MRI sequences[3]. This allows for more timely initiation of appropriate antimicrobial or immunomodulatory therapy, which is critical in preventing irreversible neurological damage. Furthermore, MTI significantly enhances differential diagnosis, particularly in distinguishing infectious lesions from neoplastic or autoimmune pathologies, thus reducing the reliance on invasive procedures like brain biopsy[13]. Quantitative metrics such as magnetization transfer ratio 

(MTR) serve as reproducible biomarkers for disease monitoring, enabling clinicians to track treatment response and disease evolution over time[4]. These attributes support MTI as a valuable tool in precision medicine, offering tailored imaging assessments that guide individualized therapeutic decision-making.

Despite its strengths, the broader clinical adoption of MTI faces several limitations. A major challenge is the lack of standardized acquisition protocols across institutions and MRI platforms, which limits reproducibility and cross-study comparability[6, 12]. Addressing inter-scanner variability and defining normative values for MTI metrics in various CNS pathologies are essential steps toward establishing MTI as a reliable clinical biomarker. 

Future research should focus on protocol standardization to enable multi-center validation[6]; integration with complementary modalities such as diffusion tensor imaging (DTI), MR spectroscopy, and functional imaging to create multiparametric frameworks that better characterize complex infections[1, 4]; advanced computational analysis, including machine learning and artificial intelligence algorithms, to automate lesion detection, segmentation, and classification[11]; histopathological correlation studies to validate MTI findings and improve biological specificity of quantitative MT parameters[14]; and application in emerging and atypical infections, including post-COVID-19 syndromes and opportunistic infections in immunocompromised populations, to expand its diagnostic utility[8, 15]. As these technological and methodological advancements evolve, MTI is poised to play an increasingly pivotal role in the diagnosis, prognostication, and management of CNS infections, ultimately contributing to improved clinical outcomes and personalized neuroimaging strategies [Table. 3].

Magnetization transfer imaging (MTI) has emerged as a transformative neuroimaging modality with the potential to significantly advance the diagnostic and prognostic landscape of central nervous system (CNS) infections. Unlike conventional MRI techniques that often fail to visualize early or subtle pathological alterations, MTI offers unique biophysical contrast by detecting changes in tissue macromolecular content and integrity. This heightened sensitivity enables the early identification of microstructural 

processes such as demyelination, neuroinflammation, and gliosis core pathological features frequently encountered in various CNS infections[3].

Moreover, MTI plays a pivotal role in enhancing diagnostic specificity by differentiating infectious lesions from neoplastic and autoimmune pathologies, which often present overlapping radiological features on routine imaging[13]. The incorporation of quantitative biomarkers such as the magnetization transfer ratio (MTR) and pool size ratio (PSR) further enables longitudinal monitoring of disease progression and treatment efficacy, offering clinicians a non-invasive surrogate for tissue integrity and recovery dynamics[4].

By integrating MTI into standard neuroimaging protocols, clinicians can achieve more accurate characterization of infectious pathology, optimize therapeutic strategies, and improve prognostication. Taken together, MTI represents not only a diagnostic adjunct but a comprehensive imaging tool that bridges the gap between conventional radiology and microstructural tissue analysis, holding immense promise for elevating the clinical management of CNS infections.

The authors sincerely acknowledge Santosh Deemed to be University, Ghaziabad, Uttar Pradesh, India, for providing the necessary academic environment, research resources, and institutional support that facilitated the successful completion of this work. The authors also extend their gratitude to faculty members and colleagues from the Department of Radiodiagnosis for their valuable guidance and encouragement throughout the course of this study.