Prognostic Utility of Disproportionately Enlarged Subarachnoid Space Hydrocephalus in Idiopathic Normal Pressure Hydrocephalus Treated with Ventriculoperitoneal Shunt Surgery: A Systematic Review and Meta-analysis

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.

Preoperative imaging biomarkers combined with tap test for predicting shunt surgery outcome in idiopathic normal pressure hydrocephalus: a multicenter retrospective study

Objectives

The study aims to investigate the predictive performance of preoperative imaging features combined with tap test for the outcomes of ventriculoperitoneal (VP) shunt in idiopathic normal pressure hydrocephalus (iNPH).

Methods

In this multicenter retrospective study, 166 iNPH patients who underwent VP shunt surgery between August 2019 and November 2023 were included. Preoperative clinical characteristics and imaging features were collected. Preoperative clinical assessment and at least 3 months of postoperative follow-up were performed. Multivariable logistic regression, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were used to evaluate predictive performance.

Results

Out of 166 total patients, 96 were responders and 70 non-responders. The tap test showed significant difference between two group (p < 0.01). Multivariable logistic regression identified that a positive disproportionately enlarged subarachnoid space (DESH) sign (OR = 0.09, 95% CI: 0.04-0.22, p < 0.001) and a sharper callosal angle (CA) (OR = 0.97, 95% CI: 0.95-1.00, p = 0.02) were associated with symptom improvement after shunt. The sensitivity, specificity, and AUC of tap test were 0.64, 0.60, and 0.62, respectively. Combining CA and the tap test increased sensitivity to 0.85, while combining DESH, CA, and the tap test improved specificity and AUC to 0.67 and 0.72, respectively.

Conclusion

The findings suggest that the imaging features DESH and CA, when combined with the tap test, enhance the prediction of VP shunt outcomes in iNPH patients. Despite the improved predictive capability, further research focusing on innovative biomarkers for VP shunt is warranted.

Automated Idiopathic Normal Pressure Hydrocephalus Diagnosis via Artificial Intelligence-Based 3D T1 MRI Volumetric Analysis

BACKGROUND AND PURPOSE

Idiopathic normal pressure hydrocephalus (iNPH) is reversible dementia that is underdiagnosed. The purpose of this study was to develop an automated diagnostic method for iNPH using artificial intelligence techniques with a T1-weighted MRI scan.

MATERIALS AND METHODS

We quantified iNPH, Parkinson disease, Alzheimer disease, and healthy controls on T1-weighted 3D brain MRI scans using 452 scans for training and 110 scans for testing. Automatic component measurement algorithms were developed for the Evans index, Sylvian fissure enlargement, high-convexity tightness, callosal angle, and normalized lateral ventricle volume. XGBoost models were trained for both automated measurements and manual labels for iNPH prediction.

RESULTS

A total of 452 patients (200 men; mean age, 73.2 [SD, 6.5] years) were included in the training set. Of the 452 patients, 111 (24.6%) had iNPH. We obtained area under the curve (AUC) values of 0.956 for automatically measured high-convexity tightness and 0.830 for Sylvian fissure enlargement. Intraclass correlation values of 0.824 for the callosal angle and 0.924 for the Evans index were measured. By means of the decision tree of the XGBoost model, the model trained on manual labels obtained an average cross-validation AUC of 0.988 on the training set and 0.938 on the unseen test set, while the fully automated model obtained a cross-validation AUC of 0.983 and an unseen test AUC of 0.936.

CONCLUSIONS

We demonstrated a machine learning algorithm capable of diagnosing iNPH from a 3D T1-weighted MRI that is robust to the failure. We propose a method to scan large numbers of 3D T1-weighted MRIs with minimal human intervention, making possible large-scale iNPH screening.

Diagnostic importance of disproportionately enlarged subarachnoid space hydrocephalus and Callosal Angle measurements in the context of normal pressure hydrocephalus: A useful tool for clinicians

Hydrocephalus is a clinical and neurologic condition characterized by an abnormal accumulation of cerebrospinal fluid (CSF). Currently, idiopathic Normal Pressure Hydrocephalus (iNPH) is recognized as a late-onset neurologic disorder defined by a clinical triad of gait disturbance, urinary incontinence, and dementia. Imaging studies often reveal a disproportionate increase in subarachnoid space and ventricular size relative to brain volume, with normal CSF pressure during lumbar puncture. Recent developments in neuroimaging have led to the establishment of criteria for diagnosing and managing iNPH, incorporating the concept of Disproportionately Enlarged Subarachnoid-space Hydrocephalus (DESH). Distinguishing iNPH from the natural neurological aging process and other forms of dementia, wherein brain atrophy and hydrocephalus ex vacuo can be observed, can present challenges for both neurologists and neuroradiologists. Despite DESH becoming a radiologic criterion for diagnosing iNPH in some guidelines, its recognition remains limited.

Evaluation of imaging indicators in differentiating idiopathic normal pressure hydrocephalus from Alzheimer's disease

BACKGROUND

There are currently many imaging indicators for idiopathic normal pressure hydrocephalus (iNPH). However, their diagnostic performance has not been well compared, especially in differentiating iNPH from Alzheimer's disease (AD). This study aimed to evaluate the diagnostic performance of these imaging indicators in differentiating iNPH from AD.

METHODS

We retrospectively collected patients with iNPH from the West China Hospital between June 2016 and December 2023. Age-sex-matched patients with AD and healthy controls (HCs) are included as controls (ChiCTR2300070078, March 2023). Twelve imaging indicators were evaluated on MRI, including disproportionately enlarged subarachnoid space hydrocephalus (DESH), Evans' index (EI), callosal angle, z-EI, temporal horn, dilated Sylvian fissure, focal sulcal dilation, tight high convexity, deep white matter hyperintensities, periventricular hyperintensities, DESH scale, and Simplified Radscale. We analyzed the receiver operating characteristic curves and calculated the sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy.

RESULTS

A total of 46 patients with iNPH (mean age: 73.1 ± 6.5; 35 males), 46 patients with AD (mean age: 73.0 ± 6.6; 35 males), and 46 HCs (mean age: 73.0 ± 5.9; 35 males) were included. The largest area under the receiver operating characteristic curve (AUC) was found in EI (0.93; 95 % CI: 0.89-0.98) and z-EI (0.93; 95 % CI: 0.87-0.98). DESH scale ≥ 6 had the highest specificity (93 %, 43/46).

CONCLUSION

EI and z-EI had the best diagnostic performance in differentiating iNPH from AD. The DESH scale could assist in diagnosing iNPH due to its high specificity.

Relationship between disproportionately enlarged subarachnoid-space hydrocephalus and white matter tract integrity in normal pressure hydrocephalus

Normal pressure hydrocephalus (NPH) patients had altered white matter tract integrities on diffusion tensor imaging (DTI). Previous studies suggested disproportionately enlarged subarachnoid space hydrocephalus (DESH) as a prognostic sign of NPH. We examined DTI indices in NPH subgroups by DESH severity and clinical symptoms. This retrospective case-control study included 33 NPH patients and 33 age-, sex-, and education-matched controls. The NPH grading scales (0-12) were used to rate neurological symptoms. Patients with NPH were categorized into two subgroups, high-DESH and low-DESH groups, by the average value of the DESH scale. DTI indices, including fractional anisotropy, were compared across 14 regions of interest (ROIs). The high-DESH group had increased axial diffusivity in the lateral side of corona radiata (1.43 ± 0.25 vs. 1.72 ± 0.25, p = 0.04), and showed decreased fractional anisotropy and increased mean, and radial diffusivity in the anterior and lateral sides of corona radiata and the periventricular white matter surrounding the anterior horn of lateral ventricle. In patients with a high NPH grading scale, fractional anisotropy in the white matter surrounding the anterior horn of the lateral ventricle was significantly reduced (0.36 ± 0.08 vs. 0.26 ± 0.06, p = 0.03). These data show that DESH may be a biomarker for DTI-detected microstructural alterations and clinical symptom severity.

Risk estimation for idiopathic normal-pressure hydrocephalus: development and validation of a brain morphometry-based nomogram

OBJECTIVES

To develop and validate a nomogram based on MRI features for predicting iNPH.

METHODS

Patients aged  ≥ 60 years (clinically diagnosed with iNPH, Parkinson's disease, or Alzheimer's disease or healthy controls) who underwent MRI including three-dimensional T1-weighted volumetric MRI were retrospectively identified from two tertiary referral hospitals (one hospital for derivation set and the other for validation set). Clinical and imaging features for iNPH were assessed. Deep learning-based brain segmentation software was used for 3D volumetry. A prediction model was developed using logistic regression and transformed into a nomogram. The performance of the nomogram was assessed with respect to discrimination and calibration abilities. The nomogram was internally and externally validated.

RESULTS

A total of 452 patients (mean age ± SD, 73.2 ± 6.5 years; 200 men) were evaluated as the derivation set. One hundred eleven and 341 patients were categorized into the iNPH and non-iNPH groups, respectively. In multivariable analysis, high-convexity tightness (odds ratio [OR], 35.1; 95% CI: 4.5, 275.5), callosal angle  < 90° (OR, 12.5; 95% CI: 3.1, 50.0), and normalized lateral ventricle volume (OR, 4.2; 95% CI: 2.7, 6.7) were associated with iNPH. The nomogram combining these three variables showed an area under the curve of 0.995 (95% CI: 0.991, 0.999) in the study sample, 0.994 (95% CI: 0.990, 0.998) in the internal validation sample, and 0.969 (95% CI: 0.940, 0.997) in the external validation sample.

CONCLUSION

A brain morphometry-based nomogram including high-convexity tightness, callosal angle  < 90°, and normalized lateral ventricle volume can help accurately estimate the probability of iNPH.

KEY POINTS

• The nomogram with MRI findings (high-convexity tightness, callosal angle, and normalized lateral ventricle volume) helped in predicting the probability of idiopathic normal-pressure hydrocephalus. • The nomogram may facilitate the prediction of idiopathic normal-pressure hydrocephalus and consequently avoid unnecessary invasive procedures such as the cerebrospinal fluid tap test, drainage test, and cerebrospinal fluid shunt surgery.

SV, Borchert R, Russo S, Eide PK. Radiological predictors of shunt response in the diagnosis and treatment of idiopathic normal pressure hydrocephalus: a systematic review and meta-analysis

BACKGROUND

Patients with the dementia subtype idiopathic normal pressure hydrocephalus (iNPH) may improve clinically following cerebrospinal fluid (CSF) diversion (shunt) surgery, though the predictors of shunt response remain debated. Currently, radiological features play an important role in the diagnosis of iNPH, but it is not well established which radiological markers most precisely predict shunt responsive iNPH.

OBJECTIVE

To conduct a systematic review and meta-analysis to identify radiological predictors of shunt responsiveness, evaluate their diagnostic effectiveness, and recommend the most predictive radiological features.

METHODS

Embase, MEDLINE, Scopus, PubMed, Google Scholar, and JSTOR were searched for original studies investigating radiological predictors of shunt response in iNPH patients. Included studies were assessed using the ROBINS-1 tool, and eligible studies were evaluated using a univariate meta-analysis.

RESULTS

Overall, 301 full-text papers were screened, of which 28 studies were included, and 26 different radiological features were identified, 5 of these met the inclusion criteria for the meta-analysis: disproportionately enlarged subarachnoid space (DESH), callosal angle, periventricular white matter changes, cerebral blood flow (CBF), and computerized tomography cisternography. The meta-analysis showed that only callosal angle and periventricular white matter changes significantly differentiated iNPH shunt responders from non-responders, though both markers had a low diagnostic odds ratio (DOR) of 1.88 and 1.01 respectively. None of the other radiological markers differentiated shunt responsive from shunt non-responsive iNPH.

CONCLUSION

Callosal angle and periventricular changes are the only diagnostically effective radiological predictors of shunt responsive iNPH patients. However, due to the DORs approximating 1, they are insufficient as sole predictors and are advised to be used only in combination with other diagnostic tests of shunt response. Future research must evaluate the combined use of multiple radiological predictors, as it may yield beneficial additive effects that may allow for more robust radiological shunt response prediction.

Value of MRI-based semi-quantitative structural neuroimaging in predicting the prognosis of patients with idiopathic normal pressure hydrocephalus after shunt surgery

OBJECTIVES

To explore the value of structural neuroimaging in predicting the prognosis of shunt surgery for idiopathic normal-pressure hydrocephalus (iNPH) using two different standard semi-quantitative imaging scales.

METHODS

A total of 47 patients with iNPH who underwent shunt surgery at our hospital between 2018 and 2020 were included in this study. The modified Rankin Scale (mRS) and iNPH grading scale (iNPHGS) were used to evaluate and quantify the clinical symptoms before and after shunt surgery. The disproportionately enlarged subarachnoid space hydrocephalus (DESH) and iNPH Radscale scores were used to evaluate the preoperative MR images. The primary endpoint was improvement in the mRS score a year after surgery, and the secondary endpoint was the iNPHGS after 1 year. The preoperative imaging features of the improved and non-improved groups were compared.

RESULTS

The rates of the primary and secondary outcomes were 59.6% and 61.7%, respectively, 1 year after surgery. There were no significant differences in preoperative DESH score, iNPH Radscale, Evans' index (EI), or callosal angle (CA) between the improved and non-improved groups. Significant correlations were observed between the severity of gait disorder and EI and the CA.

CONCLUSIONS

The value of structural neuroimaging in predicting the prognosis of shunt surgery is limited, and screening for shunt surgery candidates should not rely only on preoperative imaging findings.

KEY POINTS

• Early shunt surgery can significantly improve the clinical symptoms and prognosis of patients with idiopathic normal-pressure hydrocephalus (iNPH). • Structural imaging findings have limited predictiveness for the prognosis of patients with iNPH after shunt surgery. • Patients should not be selected for shunt surgery based on only structural imaging findings.

[Brain MRI-Based Artificial Intelligence Software in Patients with Neurodegenerative Diseases: Current Status]

The incidence of neurodegenerative diseases in the older population has increased in recent years. A considerable number of studies have been performed to characterize these diseases. Imaging analysis is an important biomarker for the diagnosis of neurodegenerative disease. Objective and reliable assessment and precise detection are important for the early diagnosis of neurodegenerative diseases. Artificial intelligence (AI) using brain MRI applied to the study of neurodegenerative diseases could promote early diagnosis and optimal decisions for treatment plans. MRI-based AI software have been developed and studied worldwide. Representatively, there are MRI-based volumetry and segmentation software. In this review, we present the development process of brain volumetry analysis software in neurodegenerative diseases, currently used and developed AI software for neurodegenerative disease in the Republic of Korea, probable uses of AI in the future, and AI software limitations.