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Introduction: Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem. Methods: By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. Results: Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment. Conclusion: Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.
RESUMO
OBJECTIVE: The objective of this study was to develop a computational pipeline that extracts objective features of ventriculomegaly from non-contrast CT (NCCT) for the accurate classification of idiopathic normal pressure hydrocephalus (NPH) from headache controls (HCs), Alzheimer's dementia (AD), and posttraumatic encephalomalacia (PTE). METHODS: Patients with possible NPH (n = 79) and a subset with definite NPH (DefNPH; n = 29) were retrospectively identified in the Veterans Affairs Informatics and Computing Infrastructure system, along with the AD (n = 62), PTE (n = 53), and HC (n = 59) cohorts. Image-processing pipelines were developed to extract a novel feature capturing the maximum eccentricity of the lateral ventricles (MaxEccLV), a proxy splenial angle (p-SA), the Evans indices (EI-x, -y, and -z), callosal angle, normalized maximum third-ventricle width, and CSF to brain volume ratio from their NCCT scans. The authors used t-tests to examine group differences in the features and multivariate logistic regression models for classification. Additionally, the NPH versus HC classifier was validated on external data. RESULTS: When NPH and DefNPH were compared with HC, AD, and PTE, significant differences were found in all features except the p-SA, which only significantly differed between NPH and PTE. The test-set area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.98, 100%, and 98.3% for NPH versus HC classification; 0.94, 87.3%, and 85.5% for NPH versus AD; 0.96, 92.4%, and 90.6% for NPH versus PTE; and 0.96, 94%, and 88% for NPH versus the other groups using logistic regression under five-fold cross-validation. Consistently high performance was noted for DefNPH. The NPH versus HC classifier provided an AUC of 0.84, sensitivity of 76.9%, and specificity of 90% when assessed on external data. CONCLUSIONS: Including the novel MaxEccLV, this framework computes useful features of ventriculomegaly, which had not previously been algorithmically assessed on NCCT. This framework successfully classified possible and definite NPH from HC, AD, and PTE. Following validation on larger representative cohorts, this objective and accessible tool may aid in screening for NPH and differentiating it from symptomatic mimics such as AD and PTE.
