Classification of Chronic Hydrocephalus in Adults: A Systematic Review and Analysis

Deep Learning-Based Models for Ventricular Segmentation in Hydrocephalus: A Systematic Review and Meta-Analysis

BACKGROUND

Ventricular segmentation is a critical step in neuroimaging data evaluation, particularly in hydrocephalus. Current methods are mainly based on 2-dimensional measurements and ratios. Traditional manual and semiautomatic ventricular segmentation are time-consuming, operator-based, and lack flexibility in handling numerous radiological features. Recently, deep learning (DL) models have been developed to perform ventricular segmentation and have shown promising outcomes. The objective of the current study was to evaluate the performance of DL-based models in ventricular segmentation in the hydrocephalus setting.

METHODS

On December 5, 2024, a systematic search was conducted using an individualized search query in 4 electronic databases: PubMed, Embase, Scopus, and Web of Science. Studies that reported the mean dice similarity coefficient (DSC) of DL-based models in ventricular segmentation in patients with hydrocephalus were included. The mean DSC for the best-performance model was extracted.

RESULTS

Twenty-four studies with 2911 patients were included. The mean DSC ranged from 0.671 to 0.99 across the best-performance models. The meta-analysis revealed a pooled mean DSC of 0.89 (95% CI: 0.84-92). The subgroup analysis yielded a pooled mean DSC of 0.88 (95% CI: 0.80-0.96) for magnetic resonance imaging-based models, 0.91 (95% CI: 0.86-0.95) for computed tomography-based models, and 0.84 (95% CI: 0.81-0.87) for ultrasound-based best-performance DL-based models.

CONCLUSIONS

DL-based models have demonstrated favorable outcomes in ventricular segmentation in patients with hydrocephalus. Application of these models in clinical practice can optimize the treatment protocol and enhance the clinical outcomes of hydrocephalus patients.

Practical brain MRI guidelines for anti-Aβ antibody treatment in early symptomatic Alzheimer's disease

PURPOSE

These guidelines aim to support magnetic resonance imaging (MRI) diagnosis in patients receiving anti-amyloid β (Aβ) antibody treatment without restricting treatment eligibility.

MATERIALS AND METHODS

These guidelines were collaboratively established by Japan Radiological Society, The Japanese Society of Neuroradiology, and Japanese Society for Magnetic Resonance in Medicine by reviewing existing literature and the results of clinical trials.

RESULTS

Facility standards should comply with the "Optimal Use Promotion Guidelines" of Japan, and physicians should possess comprehensive knowledge of amyloid-related imaging abnormalities (ARIA) and expertise in brain MRI interpretation. The acquisition of knowledge regarding amyloid-related imaging abnormalities, brain MRI, anti-Aβ antibody introduction, and post-treatment diagnosis are also recommended.

CONCLUSION

These guidelines facilitate the accurate diagnosis and effective management of ARIA; ensure the safe administration of anti-Aβ drugs; and provide a framework for MRI facilities, includes staffing requirements and the use of MRI management systems.

Hydrocephalus Pathophysiology and Epidemiology

Adult hydrocephalus is a common neurologic condition with an estimated prevalence of 85 per 100,000 globally, caused by abnormal cerebrospinal fluid (CSF) accumulation within the cerebral ventricles. Subtypes include idiopathic normal pressure hydrocephalus, posthemorrhagic, postinfectious, posttraumatic, and tumor-associated forms. Its pathophysiology involves glymphatic dysfunction, neuroinflammation, vascular compromise, and impaired CSF absorption. Despite advances in treatment, significant gaps remain in understanding its epidemiology, particularly in regards to regional variability and comorbidities, alongside unresolved questions about glymphatic pathways and neurodegenerative overlap. Standardized diagnostic and therapeutic frameworks are urgently needed.

Adult Hydrocephalus: Natural History, Clinical Outcomes, Quality of Life, and Health Economics

Adult hydrocephalus comprise a family of disorders characterized by a cerebrospinal fluid dynamic disturbance and a shared core symptomatology. Idiopathic normal pressure hydrocephalus (iNPH) has gained an increasing scientific attention over the past decades and is the most studied type of adult hydrocephalus. While knowledge of iNPH have accumulated and expanded, literature is still meagre in other, more uncommon adult hydrocephalus. In this focused review, we describe the most important advances in the literature on natural course, outcomes, quality of life and health economics with a focus on iNPH, the type of adult hydrocephalus where substantial research data exist.

Adult Hydrocephalus Clinical Subtypes

Adult hydrocephalus comprises 4 pragmatic categories: (1) transition; (2) unrecognized congenital; (3) acquired; and (4) suspected idiopathic normal pressure hydrocephalus. Each of these groups has unique clinical presentations and care needs that require the involvement of adult neurosurgeons for diagnosis and treatment. Patients in all 4 of these categories benefit from longitudinal care for monitoring of their symptoms or assessing response to treatment.

Regional brain volume changes in Hakim's disease versus Alzheimer's and mild cognitive impairment

Idiopathic normal-pressure hydrocephalus (Hakim's disease) is characterized by ventricular enlargement and disproportionately enlarged subarachnoid space hydrocephalus, leading to localized brain deformation. Differentiating regional brain volume changes in Hakim's disease from those in Alzheimer's disease, Hakim's disease with Alzheimer's disease, and mild cognitive impairment provides insights into disease-specific mechanisms. This study aimed to identify disease-specific patterns of brain volume changes in Hakim's disease, Alzheimer's disease, Hakim's disease with Alzheimer's disease, and mild cognitive impairment and compare them with those in cognitively healthy individuals using an advanced artificial intelligence-based brain segmentation tool. The study included 970 participants, comprising 52 patients with Hakim's disease, 256 with Alzheimer's disease, 25 with Hakim's disease with Alzheimer's disease, 163 with mild cognitive impairment, and 474 healthy controls. The intracranial spaces were segmented into 100 brain and 7 CSF subregions from 3D T1-weighted MRIs using brain subregion analysis. The volume ratios of these regions were compared among the groups using Glass's Δ, referencing 400 healthy controls aged ≥50 years. Hakim's disease exhibited significant volume reduction in the supramarginal gyrus of the parietal lobe and the paracentral gyrus of the frontal lobe. Alzheimer's disease exhibited prominent volume loss in the hippocampus and temporal lobe, particularly in the entorhinal cortex, fusiform gyrus, and inferior temporal gyrus. Hakim's disease with Alzheimer's disease showed significant volume reductions in the supramarginal gyrus of the parietal lobe, similar to Hakim's disease, whereas temporal lobe volumes were relatively preserved compared with those in Alzheimer's disease. Patients with mild cognitive impairment aged ≥70 years had comparable regional brain volume ratios with healthy controls in the same age group. The Hakim's disease and Hakim's disease with Alzheimer's disease groups were characterized by volume reductions in the frontal and parietal lobes caused by disproportionately enlarged subarachnoid space hydrocephalus-related compression compared with temporal lobe atrophy observed in the Alzheimer's disease group. These disease-specific morphological changes highlight the need for longitudinal studies to clarify the causes of compression and atrophy.

What is idiopathic in normal pressure hydrocephalus?

INTRODUCTION

Normal pressure hydrocephalus (NPH) can be caused by acquired events - e.g. subarachnoid hemorrhage, meningitis, or trauma - or can be "idiopathic" (iNPH) when no clear cause is identifiable. The entity and nosology of iNPH has received renewed attention and has recently gone through scrutiny and academic debate.

EVIDENCE ACQUISITION

Authors searched PubMed using the following keywords: "adult hydrocephalus," "alfa synuclein," "Alzheimer's disease," "beta-amyloid," "cerebrospinal fluid," "cilia," "CSF," "genes," "hydrocephalus," "idiopathic," "Lewy Body Dementia," "phosphorylated tau," "shunt responsiveness".

EVIDENCE SYNTHESIS

During the past decades several studies have reshaped our view of iNPH, examples are the identification of monogenic forms of iNPH caused by genes involved in the structure and function of cilia or the discovery of the glymphatic system. This review will discuss the causes of iNPH and particularly the relationship with neurodegeneration in terms of: 1) coincidental association; 2) iNPH predisposing to neurodegeneration, 3. neurodegeneration predisposing to iNPH, and 4. independent processes (genetic and environmental) predisposing to both. Based on the gathered evidence, a unified model is then presented, characterized by three sequential events: impairment of CSF dynamic, occurrence of reversible signs, occurrence of irreversible signs.

CONCLUSIONS

Almost 70 years after its description, a growing literature on its basic mechanisms is clarifying that iNPH is a syndrome with pathogenetic mechanisms arising from different causes. The paradigm shift has been recognizing that iNPH is not just a CSF disorder but rather a brain disorder expressing with ventriculomegaly. Finally, the better understanding of what causes iNPH support the proposal of changing its name into "Hakim's disease."

Is normal pressure hydrocephalus a movement disorder?

Idiopathic normal pressure hydrocephalus (iNPH) represents a nosographic entity characterized by phenotypic variability. In this context, the need arises to differentiate iNPH from neurological conditions characterized by impairment in mobility and cognition, including atypical and secondary parkinsonism, with which it shares several common aspects. In this review we will discuss clinical evidence supporting different iNPH clinical phenotypes mimicking Parkinson's disease and secondary/atypical parkinsonism, indicating iNPH as a neurological condition that should be considered by movement disorders specialists. We will also propose a preliminary diagnostic algorithm combining clinical, imaging and biological markers leading to a multidimensional diagnosis of iNPH associated with parkinsonism.

Hakim's disease: an update on idiopathic normal pressure hydrocephalus

INTRODUCTION

Idiopathic normal pressure hydrocephalus (iNPH) increases with age but is still underdiagnosed and undertreated. In the last decade, iNPH research has expanded into understanding broader contributions to iNPH, the role of cerebrospinal fluid (CSF), and imaging biomarkers to aid early detection, help diagnosis and differentiation from iNPH mimics, and aid with outcome prediction.

EVIDENCE ACQUISITION

We performed a literature search on the PubMed database. English language articles published between 2015-2024 were included. The strategies focused on iNPH and specific terms related to the topics of this review.

EVIDENCE SYNTHESIS

We first addressed the ambiguity of current classification terminology and reviewed the newly proposed classification system. This review has shown that prevalence is higher than previously reported. We have reviewed imaging and found numerous highly sensitive and specific imaging markers to aid diagnosis and differentiate from common mimics. CSF biomarkers have revealed that amyloid β and tau levels were lower in iNPH patients, which helped with differentiation from iNPH mimics, and that other emerging inflammatory markers need to be studied further. We also found numerous promising genetic markers in familial iNPH involved in cilial dysfunction, neuroinflammation, and neurodegeneration. Literature also reported the frequent presence of spinal stenosis, and studies reported better iNPH outcomes when these were addressed.

CONCLUSIONS

This has shown that there is a need for the development of a structured and standardized classification system, iNPH assessment protocol with standardized testing, and standardized biomarkers to aid diagnosis and treatment, and that this needs an interdisciplinary team approach.

The eagle-wing finding in FP-CIT SPECT, as a characteristic finding in patients with DESH- type iNPH

PURPOSE

Although dopamine transporter (DAT) imaging has been reported to be useful for differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from its mimics, the radiological findings of DAT imaging in iNPH have not been established. We investigated [123I] N-ω-fluoropropyl-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (FP-CIT) single photon emission computed tomography (SPECT) images from patients with disproportionately enlarged subarachnoid-space hydrocephalus (DESH)-type iNPH to understand the characteristics of DAT images of iNPH.

METHODS

We retrospectively collected 11 DESH-type iNPH patients without comorbidities who underwent FP-CIT SPECT imaging. The patients' FP-CIT SPECT were examined using both visual and quantitative evaluations. Visual assessment used Kahraman et al.'s five-step grading, and quantitative assessment used DaTView and MIM software to calculate specific binding ratios (SBRs) for four volumes of interest (VOIs): the entire striatum, caudate nucleus, anterior putamen, and posterior putamen. Intergroup comparisons were made between the DESH group and a normal control (NC) group adjusted for age and sex.

RESULTS

The visual assessment classified 91% of DESH patients as showing grade 4 'eagle-wing' on FP-CIT SPECT, with a Kappa coefficient of 0.601. The median SBR was lower in the DESH group than in the NC group for all four VOIs, and significantly lower in the anterior and posterior putamen (p < 0.05).

CONCLUSION

In DESH-type iNPH, FP-CIT SPECT imaging typically shows the 'eagle-wing' finding due to decreased DAT concentration in the putamen. Our results enhance the utility of FP-CIT SPECT in diagnosing iNPH and distinguishing it from mimics.

Idiopathic normal pressure hydrocephalus: survey on current diagnostic and therapeutic procedures in clinical practice in Germany

OBJECTIVE

Cerebrospinal fluid (CSF) shunting has become the standard treatment for idiopathic normal pressure hydrocephalus (NPH). Nevertheless, there is still disagreement on diagnostic criteria for selecting patients for surgery and optimal shunt management. The primary aim of the present study was to provide an update on the status of best practice, the use of different diagnostic algorithms and therapeutic management of idiopathic NPH in an European country. METHODS  : A standardized questionnaire with sections on the assessment of clinical symptoms and signs of NPH, diagnostic work-up, therapeutic decision making, and operative techniques was sent to 135 neurosurgical clinics in Germany that regularly perform shunt surgeries.

RESULTS

Overall, responses were received from 114/135 (84.4%) clinics. Most responders considered gait disturbance to be the hallmark clinical sign of idiopathic NPH (96%). A lumbar tap test was utilized always/ mostly by 97 centers (86%). In 43% of the centers, 30-40 ml CSF were removed with the spinal tap test. Spinal dynamic CSF studies were used by 12 centers only occasionally, and only by 1 center always for diagnostic purposes. Ventriculo-peritoneal shunting was the most frequent type of CSF diversion (> 90%). Pressure-controlled valves were used by the majority of units (95%) Overall 102 centers (93%) always/mostly used adjustable valves, and antisiphon devices were used always/ mostly in 50% of units.

CONCLUSION

The present survey demonstrates that there has been a remarkable change of practice and opinions on the diagnosis and treatment of idiopathic NPH over the past two decades in Germany. Remarkably, variabilities in practice among different centers are less common than previously and recommendations according to scientific publications and guidelines have been implemented more readily.

Assessing CT-based Volumetric Analysis via Transfer Learning with MRI and Manual Labels for Idiopathic Normal Pressure Hydrocephalus

Background

Brain computed tomography (CT) is an accessible and commonly utilized technique for assessing brain structure. In cases of idiopathic normal pressure hydrocephalus (iNPH), the presence of ventriculomegaly is often neuroradiologically evaluated by visual rating and manually measuring each image. Previously, we have developed and tested a deep-learning-model that utilizes transfer learning from magnetic resonance imaging (MRI) for CT-based intracranial tissue segmentation. Accordingly, herein we aimed to enhance the segmentation of ventricular cerebrospinal fluid (VCSF) in brain CT scans and assess the performance of automated brain CT volumetrics in iNPH patient diagnostics.

Methods

The development of the model used a two-stage approach. Initially, a 2D U-Net model was trained to predict VCSF segmentations from CT scans, using paired MR-VCSF labels from healthy controls. This model was subsequently refined by incorporating manually segmented lateral CT-VCSF labels from iNPH patients, building on the features learned from the initial U-Net model. The training dataset included 734 CT datasets from healthy controls paired with T1-weighted MRI scans from the Gothenburg H70 Birth Cohort Studies and 62 CT scans from iNPH patients at Uppsala University Hospital. To validate the model's performance across diverse patient populations, external clinical images including scans of 11 iNPH patients from the Universitatsmedizin Rostock, Germany, and 30 iNPH patients from the University of Alabama at Birmingham, United States were used. Further, we obtained three CT-based volumetric measures (CTVMs) related to iNPH.

Results

Our analyses demonstrated strong volumetric correlations (ϱ=0.91, p<0.001) between automatically and manually derived CT-VCSF measurements in iNPH patients. The CTVMs exhibited high accuracy in differentiating iNPH patients from controls in external clinical datasets with an AUC of 0.97 and in the Uppsala University Hospital datasets with an AUC of 0.99.

Discussion

CTVMs derived through deep learning, show potential for assessing and quantifying morphological features in hydrocephalus. Critically, these measures performed comparably to gold-standard neuroradiology assessments in distinguishing iNPH from healthy controls, even in the presence of intraventricular shunt catheters. Accordingly, such an approach may serve to improve the radiological evaluation of iNPH diagnosis/monitoring (i.e., treatment responses). Since CT is much more widely available than MRI, our results have considerable clinical impact.

Modeling cerebrospinal fluid dynamics across the entire intracranial space through integration of four-dimensional flow and intravoxel incoherent motion magnetic resonance imaging

BACKGROUND

Bidirectional reciprocal motion of cerebrospinal fluid (CSF) was quantified using four-dimensional (4D) flow magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) MRI. To estimate various CSF motions in the entire intracranial region, we attempted to integrate the flow parameters calculated using the two MRI sequences. To elucidate how CSF dynamics deteriorate in Hakim's disease, an age-dependent chronic hydrocephalus, flow parameters were estimated from the two MRI sequences to assess CSF motion in the entire intracranial region.

METHODS

This study included 127 healthy volunteers aged ≥ 20 years and 44 patients with Hakim's disease. On 4D flow MRI for measuring CSF motion, velocity encoding was set at 5 cm/s. For the IVIM MRI analysis, the diffusion-weighted sequence was set at six b-values (i.e., 0, 50, 100, 250, 500, and 1000 s/mm2), and the biexponential IVIM fitting method was adapted. The relationships between the fraction of incoherent perfusion (f) on IVIM MRI and 4D flow MRI parameters including velocity amplitude (VA), absolute maximum velocity, stroke volume, net flow volume, and reverse flow rate were comprehensively evaluated in seven locations in the ventricles and subarachnoid spaces. Furthermore, we developed a new parameter for fluid oscillation, the Fluid Oscillation Index (FOI), by integrating these two measurements. In addition, we investigated the relationship between the measurements and indices specific to Hakim's disease and the FOIs in the entire intracranial space.

RESULTS

The VA on 4D flow MRI was significantly associated with the mean f-values on IVIM MRI. Therefore, we estimated VA that could not be directly measured on 4D flow MRI from the mean f-values on IVIM MRI in the intracranial CSF space, using the following formula; e0.2(f-85) + 0.25. To quantify fluid oscillation using one integrated parameter with weighting, FOI was calculated as VA × 10 + f × 0.02. In addition, the FOIs at the left foramen of Luschka had the strongest correlations with the Evans index (Pearson's correlation coefficient: 0.78). The other indices related with Hakim's disease were significantly associated with the FOIs at the cerebral aqueduct and bilateral foramina of Luschka. FOI at the cerebral aqueduct was also elevated in healthy controls aged ≥ 60 years.

CONCLUSIONS

We estimated pulsatile CSF movements in the entire intracranial CSF space in healthy individuals and patients with Hakim's disease using FOI integrating VA from 4D flow MRI and f-values from IVIM MRI. FOI is useful for quantifying the CSF oscillation.

Automatic assessment of disproportionately enlarged subarachnoid-space hydrocephalus from 3D MRI using two deep learning models

Background

Disproportionately enlarged subarachnoid-space hydrocephalus (DESH) is a key feature for Hakim disease (idiopathic normal pressure hydrocephalus: iNPH), but subjectively evaluated. To develop automatic quantitative assessment of DESH with automatic segmentation using combined deep learning models.

Methods

This study included 180 participants (42 Hakim patients, 138 healthy volunteers; 78 males, 102 females). Overall, 159 three-dimensional (3D) T1-weighted and 180 T2-weighted MRIs were included. As a semantic segmentation, 3D MRIs were automatically segmented in the total ventricles, total subarachnoid space (SAS), high-convexity SAS, and Sylvian fissure and basal cistern on the 3D U-Net model. As an image classification, DESH, ventricular dilatation (VD), tightened sulci in the high convexities (THC), and Sylvian fissure dilatation (SFD) were automatically assessed on the multimodal convolutional neural network (CNN) model. For both deep learning models, 110 T1- and 130 T2-weighted MRIs were used for training, 30 T1- and 30 T2-weighted MRIs for internal validation, and the remaining 19 T1- and 20 T2-weighted MRIs for external validation. Dice score was calculated as (overlapping area) × 2/total area.

Results

Automatic region extraction from 3D T1- and T2-weighted MRI was accurate for the total ventricles (mean Dice scores: 0.85 and 0.83), Sylvian fissure and basal cistern (0.70 and 0.69), and high-convexity SAS (0.68 and 0.60), respectively. Automatic determination of DESH, VD, THC, and SFD from the segmented regions on the multimodal CNN model was sufficiently reliable; all of the mean softmax probability scores were exceeded by 0.95. All of the areas under the receiver-operating characteristic curves of the DESH, Venthi, and Sylhi indexes calculated by the segmented regions for detecting DESH were exceeded by 0.97.

Conclusion

Using 3D U-Net and a multimodal CNN, DESH was automatically detected with automatically segmented regions from 3D MRIs. Our developed diagnostic support tool can improve the precision of Hakim disease (iNPH) diagnosis.