Imaging biomarkers for detection and longitudinal monitoring of ventricular abnormalities from birth to childhood

Abstract

This narrative review examines the use of imaging biomarkers for diagnosing and monitoring hydrocephalus from birth through childhood. Early detection and longitudinal follow-up are essential for guiding timely interventions and assessing treatment outcomes. Cranial ultrasound and magnetic resonance imaging (MRI) are the primary imaging modalities, providing critical insights into ventricular size, cerebrospinal fluid dynamics, and neurodevelopmental implications. Key parameters, including Evans’ index, Levene’s index, and the Cella Media index, as well as volumetric and diffusion-based MRI techniques, have been explored for their diagnostic and prognostic value. Advances in automated image analysis and artificial intelligence have further improved measurement precision and reproducibility. Despite these developments, challenges remain in standardizing imaging protocols and establishing normative reference values across different pediatric populations. This review highlights the strengths and limitations of current imaging approaches, emphasizing the need for consistent methodologies to enhance diagnostic accuracy and optimize patient management in hydrocephalus.

Key Words: Hydrocephalus; Imaging biomarkers; Pediatric neuroimaging; Cranial ultrasound; Magnetic resonance imaging; Artificial intelligence; Ventricular indices

Core Tip: This narrative review highlights the role of imaging biomarkers in diagnosing and monitoring hydrocephalus from birth through childhood. It explores the utility of cranial ultrasound and magnetic resonance imaging, with emphasis on key ventricular indices, volumetric analysis, and diffusion-based techniques. The integration of artificial intelligence enhances measurement precision and reproducibility, addressing interobserver variability. The review also discusses the need for standardized imaging protocols and reliable normative values to improve diagnostic consistency. By synthesizing recent advancements, it underscores the importance of longitudinal imaging in assessing neurodevelopmental outcomes and optimizing patient management.

INTRODUCTION

Hydrocephalus is a complex neurological condition characterized by an abnormal accumulation of cerebrospinal fluid (CSF) within the ventricular system, leading to increased intracranial pressure and progressive ventricular dilation, which can cause significant structural and functional brain changes. While it can occur at any stage of life, its effects are particularly pronounced in early development, especially during the neonatal period, when the brain is still in critical stages of maturation. Without timely diagnosis and effective management, hydrocephalus can lead to severe and potentially irreversible neurodevelopmental impairments.

The identification of robust imaging parameters to diagnose and monitor hydrocephalus from birth through childhood is critical for guiding timely interventions and evaluating treatment outcomes. These parameters are invaluable in tracking ventricular size, assessing CSF dynamics, and identifying signs of progressive ventricular enlargement. Early and ongoing assessment of these biomarkers helps clinicians make informed decisions about surgical or medical interventions, such as ventriculoperitoneal shunts or endoscopic third ventriculostomy, and their long-term effectiveness.

Imaging modalities play a central role in the management of hydrocephalus across the pediatric age spectrum. Cranial ultrasound (CUS), widely used in neonates due to its safety, portability, and ability to provide bedside imaging, is indispensable for initial evaluations and routine follow-ups in the neonatal population[1-3]. For older children and in more complex cases, magnetic resonance imaging (MRI) offers superior resolution, allowing detailed assessment of ventricular anatomy, white matter changes, and CSF flow[4]. Advances in imaging technologies, such as phase-contrast MRI[5] and automated volumetric analyses[6], have further refined the ability to diagnose and monitor hydrocephalus, providing critical information on disease progression and treatment outcomes.

This narrative review focuses on the imaging biomarkers and parameters that are essential for diagnosing and monitoring hydrocephalus from birth to adolescence. It provides an overview of their clinical applications, recent technological advancements, and the ongoing challenges in achieving standardized imaging protocols and reliable normative data. By exploring these aspects, the review aims to contribute to a better understanding of hydrocephalus management across the pediatric age range.

IMAGING MODALITIES FOR VENTRICULAR ASSESSMENT

CUS

CUS remains the cornerstone imaging modality for the evaluation of ventricular abnormalities in neonates, particularly preterm infants. Its widespread use is driven by its accessibility, non-invasiveness, and the ability to perform bedside imaging in real time. This makes CUS an ideal tool for routine screening and early diagnosis in neonatal intensive care units.

One of the key strengths of CUS is its ability to provide real-time measurements of ventricular size and morphology, which are essential for assessing and monitoring changes in hydrocephalus. These metrics are essential for assessing ventricular size and monitoring the progression of hydrocephalus or other conditions. Recent advances, such as the use of very high-frequency transducers, have further enhanced the spatial resolution of CUS, enabling a more detailed evaluation of small structures, including the periventricular white matter and subtle ventricular abnormalities[1].

Contrast-enhanced transfontanellar ultrasound (CEUS) has been explored as an imaging technique in neonates and infants, offering both qualitative and quantitative assessments of cerebral perfusion. This method shows promise in detecting abnormalities such as ischemia, hemorrhage, and intracranial shunts, due to its ability to visualize microvascular perfusion dynamics[7]. While CEUS has potential as an alternative to MRI or computed tomography (CT) in critically ill neonates, limitations such as the lack of standardized protocols, concerns about safety, and the off-label status of contrast agents hinder its widespread clinical adoption.

Additionally, ultrafast Doppler imaging plays a key role in evaluating cerebral vascularization and hemodynamics, enabling detailed measurements of resistivity indices across vessels of various sizes. Unlike conventional Doppler methods, ultrafast Doppler offers higher sensitivity and spatial resolution, facilitating the discrimination between arteries and veins with greater precision. These capabilities are particularly valuable for identifying and monitoring conditions such as white matter injuries in neonates, where early detection of cerebrovascular abnormalities is crucial[8]. Furthermore, the integration of automated classification algorithms enhances the reliability and reproducibility of these assessments, offering potential for real-time applications[9].

Three-dimensional CUS (3D CUS) has emerged as a promising tool for volumetric assessment of the ventricular system, addressing some of the limitations of traditional two-dimensional (2D) measurements. Studies have demonstrated that 3D CUS can provide more accurate estimations of ventricular volume, with better interobserver reliability compared to standard 2D metrics. However, correlations between 2D and 3D measurements have shown only moderate agreement, suggesting that ventricular size assessment based solely on linear dimensions may not fully capture progressive changes in hydrocephalus[10]. The ability to acquire volumetric data using bedside 3D ultrasound offers a valuable alternative to MRI, particularly for serial monitoring in preterm infants. Despite these advantages, high costs and the need for specialized equipment currently limit its widespread implementation in routine clinical practice.

Emerging techniques such as transfontanellar elastography offer a novel approach to evaluating the mechanical properties of brain tissue, with potential applications in assessing intracranial pressure and tissue elasticity in hydrocephalus. Ultrasound shear wave elastography has demonstrated feasibility and reproducibility in neonatal imaging, showing differences in stiffness between deep gray nuclei and periventricular white matter across gestational age groups. Moreover, increased stiffness detected in pathological conditions such as intraparenchymal hemorrhage highlights its potential for identifying intracranial abnormalities efficiently and safely[11,12].

MRI

MRI offers unparalleled spatial resolution and structural detail, making it an essential tool for the evaluation of ventricular anatomy and CSF flow. MRI is particularly advantageous in detecting subtle abnormalities that may not be visible on ultrasound, such as early white matter damage or complex anatomical changes in the ventricular system.

Advanced MRI techniques, such as diffusion tensor imaging (DTI) and phase-contrast MRI, are important tools for both structural and functional assessment in pediatric hydrocephalus. DTI is particularly useful for evaluating white matter microstructural integrity, helping to identify disruptions linked to neurodevelopmental impairments in affected children. Metrics such as fractional anisotropy and diffusivity allow for the detection of brain tissue alterations caused by the disease, providing a better understanding of its impact on neural connectivity[13,14]. In addition, phase-contrast MRI serves as a non-invasive method for quantifying CSF flow dynamics, particularly in children with ventriculomegaly. Studies have demonstrated that hyper-oscillating CSF flow patterns in the Sylvian aqueduct correlate with reduced brain compliance and clinical symptoms such as increased intracranial pressure[5].

COMPARISON BETWEEN CUS AND MRI AT DIFFERENT STAGES OF DEVELOPMENT

While CUS remains indispensable for routine evaluations in neonates, its limitations in detecting subtle lesions, such as mild white matter abnormalities, are well documented. Nevertheless, its high predictive value for severe injuries like grade III and IV hemorrhages and hydrocephalus underscores its relevance in neonatal care. MRI, in contrast, proves essential in scenarios requiring detailed anatomical evaluation or prognostic insights, particularly in cases of suspected white matter injury or complex ventricular abnormalities. Despite its logistical challenges, including cost and the need for sedation in young children, MRI serves as a critical complement to CUS in tailoring management strategies for pediatric hydrocephalus. Together, these modalities ensure a robust diagnostic approach, adapting to the needs of patients as they progress through different stages of development[15,16]. Key imaging biomarkers are shown in Table 1.

Table 1 Summary of key imaging biomarkers for hydrocephalus assessment and their clinical applicability.

Biomarker	Benefits	Applicability
Levene’s index	Tailored for neonates (≤ 40 weeks of gestational age); correlates with gestational age. Useful for defining early intervention thresholds (e.g., > 4 mm above the 97th percentile)	Used in preterm infants via transfontanellar ultrasound. Requires population-specific nomograms
Thalamo-occipital distance	Assesses posterior ventricular dilation. Pathological values vary by population and age (e.g., > 24 mm is considered pathological in some studies)	Measured via parasagittal ultrasound or MRI. Complements anteriorly focused indices
Evans’ index	Simple and quick measurement; considers cranial size proportionality. Widely used in clinical practice	Applicable in MRI, CT, and transfontanellar ultrasound. Lacks standardized pediatric cut-off values
Cella media index	Relates ventricular size to brain tissue volume. Normal values > 4; correlates with third ventricle size	Applied in MRI/CT. Useful for assessing global ventricular dilation
Fronto-occipital horn ratio	Evaluates global ventricular dilation (includes frontal and occipital horns). The mean value in healthy individuals is approximately 0.37; a value above 0.44 indicates pathology	Validated in MRI, CT, and ultrasound. Age-independent reference ranges
Bicaudate index	Focuses on frontal horn size; useful for assessing ventricular symmetry	Limited to MRI/CT (technical challenges in ultrasound). Less reliable in asymmetry or congenital malformations
Anteroposterior lateral ventricle index	Measures the anteroposterior ventricular diameter relative to intracranial size. Has potential for detecting subtle pathological changes	Used in MRI/CT (axial plane reconstruction based on the AC-PC line). Not yet validated in pediatric populations, but it shows promise
Volumetric analysis	Quantifies total CSF volume; detects progressive changes that may be missed by linear indices. Shows better correlation with functional impairment	Requires high-resolution MRI and specialized software. Limited by cost and clinical workflow constraints

CSF: Cerebrospinal fluid; MRI: Magnetic resonance imaging; CT: Computed tomography; AC-PC: Anterior commissure-posterior commissure.

COMPARISON OF DIRECT VENTRICULAR MEASUREMENTS AND INDICES

Direct measurements of ventricular structures, such as the thickness of the anterior horns or the diameter of the third ventricle, are valuable tools for diagnosing and monitoring hydrocephalus due to their simplicity and ease of acquisition. However, compared to indices like the Evans’ index or bicaudate ratio, direct measurements are less comprehensive, as indices account for proportional relationships, making them less dependent on patient size and age. This is particularly important given the variability in cranial and body size not only between age groups but also among children of the same age. Incorporating parameters such as age, weight, and cranial perimeter can help contextualize direct measurements, improving their reproducibility and clinical reliability[17].

Levene’s index

Levene’s index is a quantitative measure used to assess the size of the lateral ventricles in neonates, particularly during the first 40 weeks of gestational age[18]. It is calculated on a coronal plane at the level of the foramen of Monro by measuring the distance from the midline (falx cerebri) to the lateral wall of the anterior horn of the lateral ventricles on both sides (Figure 1)[3].

Figure 1 Levene’s index. Coronal ultrasound and coronal magnetic resonance imaging (MRI) images at the level of the foramen of Monro illustrating Levene’s index. The measurement corresponds to the distance from the midline to the lateral wall of the anterior horn of the lateral ventricle (yellow arrow). A: Normal Levene’s index in a preterm infant (33 + 4 weeks) on coronal ultrasound; B: Normal Levene’s index in a 3-year-old child on coronal fluid-attenuated inversion recovery (FLAIR) MRI; C: Increased Levene’s index in a preterm infant (26 + 1 weeks) with hydrocephalus secondary to germinal matrix hemorrhage on coronal ultrasound; D: Increased Levene’s index in a 3-year-old child with asymmetric biventricular hydrocephalus due to perinatal ischemia on coronal FLAIR MRI.

Reference values vary depending on gestational age. Some authors suggest that hydrocephalus treatment should be considered when this distance exceeds 4 mm above the 97^th percentile[19,20]. However, it is essential to develop updated reference nomograms tailored to neonatal populations with shared phylogenetic characteristics to ensure standardized values for each group[3].

Thalamo-occipital distance

This index measures the distance between the posterior edge of the thalamus at its junction with the choroid plexus and the outermost point of the occipital horn of the lateral ventricle in the parasagittal plane[20] (Figure 2).

Figure 2 Thalamo-occipital distance. Parasagittal ultrasound and sagittal magnetic resonance imaging (MRI) images illustrating the thalamo-occipital distance. The measurement corresponds to the distance between the posterior edge of the thalamus at its junction with the choroid plexus and the most external point of the occipital horn of the lateral ventricle (yellow arrow). A: Normal thalamo-occipital distance in a preterm infant (33 + 4 weeks) on parasagittal ultrasound; B: Normal thalamo-occipital distance in a 3-year-old child on sagittal T2-weighted MRI; C: Increased thalamo-occipital distance in a preterm infant (26 + 1 weeks) with hydrocephalus secondary to germinal matrix hemorrhage on parasagittal ultrasound; D: Increased thalamo-occipital distance in a 3-year-old child with asymmetric biventricular hydrocephalus due to perinatal ischemia on sagittal T1-weighted MRI.

Although some authors consider a thalamo-occipital distance greater than 24 mm to be pathological[19,21], reference values can vary depending on the specific population and gestational age[22].

Evans’ index

Evans’ index is a simple neuroimaging measurement used to assess the relative size of the lateral ventricles in proportion to the cranial size. It is calculated by dividing the maximum width of the frontal horns of the lateral ventricles by the maximum inner diameter of the skull in the same axial plane on brain MRI or CT scans[23] (Figure 3). In pediatric patients, it is also applied using transfontanellar ultrasound[3,24], where it is obtained from a strict coronal plane.

Figure 3 Evans’ index. Axial T2-weighted magnetic resonance imaging illustrating Evans’ index. It is calculated by dividing the maximum width of the frontal horns of the lateral ventricles (yellow arrow) by the maximum cranial width (white arrow) in the same axial plane. A: Normal Evans’ index in a 4-year-old girl with a 4-week history of headache; B: Increased Evans’ index in a 15-year-old boy with supratentorial hydrocephalus due to an epidermoid cyst in the pineal gland.

In adults, ventricular dilation is generally assumed when this index exceeds 0.3. However, in the pediatric population, standardized cutoff values are not well established, as they tend to vary depending on the specific population studied[25].

Anterior-posterior lateral ventricle diameter index

The anterior-posterior lateral ventricle diameter index is another quantitative measure used to assess lateral ventricle size. To calculate this index, an axial image must be reconstructed based on the anterior commissure-posterior commissure line (Figure 4). Once this plane is obtained, the most caudal axial slice that includes the entire body of the lateral ventricle, without including the thalami, is selected. In this slice, the maximum anteroposterior diameter of the lateral ventricle is measured and divided by the maximum intracranial anteroposterior diameter, measured along the falx cerebri.

Figure 4 Anteroposterior lateral ventricle index. Axial T2-weighted magnetic resonance imaging illustrating the anteroposterior lateral ventricle index (ALVI). It is calculated by dividing the maximum anteroposterior diameter of the lateral ventricle (yellow arrow) by the maximum anteroposterior intracranial diameter (white arrow) in the same plane. A: Normal ALVI in a 3-year-old child; B: Increased ALVI in a 3-year-old child with asymmetric biventricular hydrocephalus due to perinatal ischemia.

This index has been used in adult populations, where a value greater than 0.5 is considered pathological[26,27]. Although its use has not yet been validated in pediatric patients, it holds potential as a useful biomarker for future applications.

Cella media index

The Cella media index is a neuroimaging tool used in neuroradiology to assess the size of the lateral ventricles relative to brain tissue. It is calculated by dividing the biparietal diameter of the skull by the maximum external diameter of the central portions of the lateral ventricles (Cella media) (Figure 5).

Figure 5 Cella media index. Axial T2-weighted magnetic resonance imaging illustrating the Cella media index. It is calculated by dividing the biparietal cranial diameter (white arrow) by the maximum external diameter of the central portions of the lateral ventricles (yellow arrow). A: Normal Cella media index in a 6-year-old girl with absence seizures and headache; B: Increased Cella media index in a 3-year-old boy with hydrocephalus due to compression from an arachnoid cyst in the right cerebellopontine angle.

A Cella media index greater than 4 is generally considered normal, while lower values may suggest ventricular dilation. Although reference values for the Cella media index are generally considered stable[28,29], studies have reported variations across different age groups[30]. Additionally, its correlation with third ventricle size supports its reliability as a biomarker for ventricular dilation[29].

Fronto-occipital horn ratio

Unlike other indices, such as Evans’ index, which focuses solely on the size of the frontal horns of the lateral ventricles, the Fronto-occipital horn ratio (FOHR) takes into account both the frontal and occipital horns, providing a more comprehensive assessment of global ventricular dilation.

To calculate this index, the maximum diameter of both the frontal and occipital horns of the lateral ventricles is measured in the same axial plane at the level of the foramen of Monro. The sum of these measurements is then divided by twice the maximum intracranial biparietal diameter[31] (Figure 6).

Figure 6 Fronto-occipital horn ratio. Axial T2-weighted magnetic resonance imaging illustrating the Fronto-occipital horn ratio (FOHR). It is calculated by adding the maximum diameters of the frontal (yellow arrow) and occipital (orange arrow) horns of the lateral ventricles at the level of the foramen of Monro and dividing this sum by twice the maximum intracranial biparietal diameter (white arrow). A: Normal FOHR in an 11-year-old girl with a 3-week history of headache; B: Increased FOHR in a 1-week-old full-term neonate with hydrocephalus due to intraventricular hemorrhage.

In healthy pediatric patients, the mean FOHR is approximately 0.37, with a 95% confidence interval ranging from 0.36 to 0.38, regardless of age[31]. A value exceeding 0.44 is considered indicative of ventricular enlargement[32].

Bicaudate index

The Bicaudate index is a neuroimaging tool used to assess the size of the frontal horns of the lateral ventricles in relation to the transverse diameter of the brain. To calculate this index, the distance between the most lateral portions of the frontal horns of the lateral ventricles at the level of the caudate nuclei is measured and then divided by the transverse brain diameter at the same level (along the same reference line used for ventricular measurements) in the axial plane on CT or MRI[33] (Figure 7).

Figure 7 Bicaudate index. Axial T2-weighted magnetic resonance imaging illustrating the bicaudate index. It is calculated by dividing the distance between the most lateral portions of the frontal horns of the lateral ventricles at the level of the caudate nuclei (yellow arrow) by the transverse brain diameter at the same level (white arrow). A: Normal bicaudate index in a 3-year-old child; B: Increased bicaudate index in a 3-year-old child with asymmetric biventricular hydrocephalus due to perinatal ischemia.

There are no standardized reference values for this index. As with other ventricular indices, its application in transfontanellar ultrasound is technically challenging, limiting its use primarily to CT and MRI. Moreover, since it assumes ventricular symmetry, its diagnostic reliability decreases in cases of asymmetry or congenital ventricular malformations.

VOLUMETRIC ANALYSIS IN VENTRICULAR ASSESSMENT

Volumetric analysis provides a more comprehensive evaluation of ventricular size by quantifying the total volume of CSF within the ventricular system, rather than relying on isolated linear dimensions. Unlike traditional indices, which measure specific distances or ratios from a single imaging slice, volumetric techniques assess the entire ventricular space, offering a more accurate representation of global ventricular enlargement.

One of the key advantages of volumetric measurements is their ability to detect subtle changes in ventricular expansion that may not be apparent using linear indices. This is particularly relevant in conditions such as chronic ventriculomegaly, where progressive ventricular dilation may occur without abrupt changes in shape that would be captured by traditional measurements. Additionally, volumetric assessments better correlate with functional impairment, providing a stronger link between radiological findings and clinical symptoms[34].

Despite these benefits, volumetric analysis has limitations that have slowed its widespread adoption. The technique requires high-resolution imaging, specialized software, and longer processing times, making it less practical in routine clinical workflows. Variability in segmentation protocols and differences in reference standards between institutions can also affect reproducibility.

LONGITUDINAL MONITORING AND NEURODEVELOPMENTAL OUTCOMES

Longitudinal imaging plays a crucial role in the assessment and management of hydrocephalus, providing valuable information about ventricular changes over time. Serial imaging allows clinicians to monitor disease progression, assess treatment response, and detect early signs of complications, such as shunt malfunction or progressive ventricular dilation. The ability to track ventricular size and fluid distribution over extended periods helps refine clinical decision-making, ensuring timely intervention when necessary. In addition to structural assessments, emerging evidence suggests that incorporating physiological parameters, such as cerebral oxygenation, cerebral blood flow, and cerebral metabolic rate of oxygen consumption, may improve the ability to predict long-term outcomes[35].

A key advantage of serial imaging is its capacity to reveal gradual ventricular changes that may not be apparent in a single imaging study. In some cases, ventricular dilation may remain stable for long periods, while in others, subtle enlargement can signal the need for closer monitoring or therapeutic adjustments. Tracking these variations is particularly important in infants and young children, whose brains are still developing and adapting to shifts in intracranial fluid homeostasis. However, current studies on longitudinal monitoring in pediatric hydrocephalus are limited in scope, often focusing on small cohorts or specific age groups. Expanding research across a broader pediatric population is essential to establish standardized imaging norms that can guide clinical management in different developmental stages.

Some studies have found that traditional ventricular indices show limited direct correlation with intracranial pressure[36,37], while optic nerve sheath diameter has demonstrated a moderate association with pressure dynamics[37]. These findings suggest that intracranial pressure monitoring in hydrocephalus may benefit from incorporating multiple imaging biomarkers rather than relying solely on ventricular size.

Furthermore, post-treatment brain growth, as assessed by longitudinal imaging, has been associated with better neurodevelopmental outcomes, suggesting that brain volume recovery could serve as a useful biomarker for treatment success. Studies indicate that infants with greater brain growth following intervention exhibit improved cognitive and motor development[38,39]. In addition, progressive ventricular enlargement, particularly when accompanied by white matter abnormalities, has been linked to an increased risk of neurodevelopmental impairment. Neonatal MRI findings have shown that white matter injury, including periventricular volume loss, signal abnormalities, and corpus callosal thinning, strongly predict cognitive and motor deficits later in childhood[40].

INTEGRATION OF AUTOMATED IMAGE ANALYSIS AND ARTIFICIAL INTELLIGENCE

The application of artificial intelligence (AI) and machine learning in the diagnosis and management of hydrocephalus has gained significant attention due to its potential to improve accuracy, reproducibility, and efficiency in imaging-based assessments[41]. These technologies offer automated solutions for ventricular segmentation, volumetric analysis, and prediction of disease progression, reducing reliance on manual measurements, which are often time-consuming and prone to interobserver variability[42].

ENHANCING LONGITUDINAL MONITORING WITH AI

One of the most promising applications of AI in hydrocephalus management is longitudinal monitoring[41]. Tracking ventricular changes over time is essential for assessing disease progression and treatment response, yet traditional methods rely on manual measurements that may lack sensitivity to subtle variations. AI-driven tools can automate this process by integrating large-scale imaging datasets and applying deep learning models to identify early markers of deterioration. In particular, AI-powered predictive modeling has the potential to forecast ventricular dilation trends, allowing for earlier intervention and better individualized patient management[6,43].

However, the effectiveness of AI in longitudinal analysis depends on access to multicenter datasets spanning different pediatric age groups. Current studies often focus on specific cohorts, limiting the ability to establish standardized imaging norms across developmental stages. Expanding the use of AI through collaborative research networks and diverse datasets is critical to improving its applicability in routine clinical practice[44].

AI ALGORITHMS FOR VENTRICULAR MEASUREMENT

Machine learning models have been extensively developed for the segmentation of ventricular structures, enabling precise measurement of ventricular volume from MRI and CT scans[45]. Convolutional neural networks, such as U-Net, have demonstrated high accuracy in identifying and segmenting the lateral ventricles, even in complex cases where manual segmentation is challenging[41]. These models allow for objective quantification of ventricular size, which is critical for tracking hydrocephalus progression and treatment response.

ADVANTAGES: PRECISION, REPRODUCIBILITY, AND EFFICIENCY

Compared to traditional manual or semi-automated segmentation techniques, AI-driven algorithms offer several advantages. First, they enhance precision by minimizing human error and variability, providing consistent and reproducible ventricular measurements[42]. Second, automated systems significantly reduce processing time, allowing for real-time or near-real-time analysis of imaging data. Finally, AI-powered tools can integrate multiple imaging parameters, including ventricular size, CSF dynamics, and brain volume changes, to provide a more comprehensive assessment of disease progression[46].

CLINICAL APPLICATIONS AND CASE STUDIES

AI-based imaging analysis is already being applied in clinical and research settings to improve hydrocephalus diagnosis and monitoring. Recent studies have demonstrated that deep learning models can accurately differentiate between normal ventricular anatomy and pathological enlargement, aiding in early intervention planning[45,46]. Moreover, AI-driven natural language processing systems can extract relevant clinical information from radiology reports to standardize diagnostic criteria and enhance decision-making[42]. Future research should focus on integrating AI into routine clinical workflows and validating these models across diverse patient populations to ensure their widespread adoption.

CHALLENGES AND FUTURE DIRECTIONS

The diagnosis and monitoring of hydrocephalus still face several challenges that must be addressed to improve clinical outcomes. One of the most pressing issues is the need for standardized imaging protocols, as variations in MRI angulation and acquisition parameters can lead to inconsistent results and diagnostic discrepancies[47]. Establishing reliable normative values is equally critical, recognizing that pediatric neuroimaging cannot simply apply adult-based thresholds, as a child is not just a small adult. Age-specific reference ranges must be defined to enhance diagnostic precision. Additionally, institutional variability in imaging techniques and scanner calibration further complicates the interpretation of ventricular measurements, highlighting the necessity of harmonized methodologies across centers. Future advancements in technology, particularly AI-driven imaging analysis and real-time monitoring, offer promising solutions for refining diagnostic accuracy and optimizing patient management. The integration of multimodal imaging approaches could further enhance the assessment of ventricular changes, providing a more comprehensive understanding of disease progression and treatment response.

CONCLUSION

Imaging biomarkers are fundamental in the diagnosis and longitudinal monitoring of hydrocephalus, providing essential information about ventricular morphology, CSF dynamics, and neurodevelopmental outcomes. While traditional imaging techniques remain indispensable, the integration of AI and automated analysis has the potential to enhance measurement reproducibility and diagnostic efficiency. Overcoming current limitations, such as the lack of standardized imaging protocols and the need for pediatric-specific normative values, will be key to advancing the field and ensuring optimal clinical care for children with hydrocephalus.