Choroid plexus enlargement in mild cognitive impairment on MRI: a large cohort study.

OBJECTIVES: Previous studies have shown possible choroid plexus (CP) dysfunction in Alzheimer's disease (AD) and highlighted CP enlargement on magnetic resonance imaging (MRI) as a predictive factor of AD. However, few studies have assessed the relationship between CP volume (CPV) and mild cognitive impairment (MCI). In this large elderly population study, we investigated the changes in CPV in patients with MCI using MRI above 65 years. METHODS: This cross-sectional study included 2144 participants (median age, 69 years; 60.9% females) who underwent 3T MRI; they were grouped as 218 MCI participants and 1904 cognitively healthy controls. The total intracranial volume (ICV), total brain volume (TBV), CPV, hippocampal volume (HV), and lateral ventricle volume (LVV) were calculated. RESULTS: CPV/ICV was a significant independent predictor of MCI (p < 0.01) after adjusting for potential confounders (age, sex, hypertension, hyperlipidemia, diabetes, and education level). The CPV/ICV ratio was also a significant independent predictor of MCI after adjusting for the TBV/ICV ratio (p = 0.022) or HV/ICV ratio (p = 0.017), in addition to potential confounders. The CPV was significantly correlated with the LVV (r = 0.97, p < 0.01). CONCLUSION: We identified a relationship between CPV and MCI, which could not be explained by the degree of brain atrophy. Our results support CP dysfunction in MCI. CLINICAL RELEVANCE STATEMENT: Choroid plexus volume measurement may serve as a valuable imaging biomarker for diagnosing and monitoring mild cognitive impairment. The enlargement of the choroid plexus, independent of brain atrophy, suggests its potential role in mild cognitive impairment pathology. KEY POINTS: • The study examines choroid plexus volume in relation to cognitive decline in elderly. • Enlarged choroid plexus volume independently indicates mild cognitive impairment presence. • Choroid plexus volume could be a specific biomarker for early mild cognitive impairment diagnosis.

Usefulness of pituitary high-resolution 3D MRI with deep-learning-based reconstruction for perioperative evaluation of pituitary adenomas.

PURPOSE: To evaluate the diagnostic value of T1-weighted 3D fast spin-echo sequence (CUBE) with deep learning-based reconstruction (DLR) for depiction of pituitary adenoma and parasellar regions on contrast-enhanced MRI. METHODS: We evaluated 24 patients with pituitary adenoma or residual tumor using CUBE with and without DLR, 1-mm slice thickness 2D T1WI (1-mm 2D T1WI) with DLR, and 3D spoiled gradient echo sequence (SPGR) as contrast-enhanced MRI. Depiction scores of pituitary adenoma and parasellar regions were assigned by two neuroradiologists, and contrast-to-noise ratio (CNR) was calculated. RESULTS: CUBE with DLR showed significantly higher scores for depicting pituitary adenoma or residual tumor compared to CUBE without DLR, 1-mm 2D T1WI with DLR, and SPGR (p < 0.01). The depiction score for delineation of the boundary between adenoma and the cavernous sinus was higher for CUBE with DLR than for 1-mm 2D T1WI with DLR (p = 0.01), but the difference was not significant when compared to SPGR (p = 0.20). CUBE with DLR had better interobserver agreement for evaluating adenomas than 1-mm 2D T1WI with DLR (Kappa values, 0.75 vs. 0.41). The CNR of the adenoma to the brain parenchyma increased to a ratio of 3.6 (obtained by dividing 13.7, CNR of CUBE with DLR, by 3.8, that without DLR, p < 0.01). CUBE with DLR had a significantly higher CNR than SPGR, but not 1-mm 2D T1WI with DLR. CONCLUSION: On the contrast-enhanced MRI, compared to CUBE without DLR, 1-mm 2D T1WI with DLR and SPGR, CUBE with DLR improves the depiction of pituitary adenoma and parasellar regions.

Altered structural hippocampal intra-networks in a general elderly Japanese population with mild cognitive impairment.

Although altered networks inside the hippocampus (hippocampal intra-networks) have been observed in dementia, the evaluation of hippocampal intra-networks using magnetic resonance imaging (MRI) is challenging. We employed conventional structural imaging and incident component analysis (ICA) to investigate the structural covariance of the hippocampal intra-networks. We aimed to assess altered hippocampal intra-networks in patients with mild cognitive impairment (MCI). A cross-sectional study of 2122 participants with 3T MRI (median age 69 years, 60.9% female) were divided into 218 patients with MCI and 1904 cognitively normal older adults (CNOA). By employing 3D T1-weighted imaging, voxels within the hippocampus were entered into the ICA analysis to extract the structural covariance intra-networks within the hippocampus. The ICA extracted 16 intra-networks from the hippocampal structural images, which were divided into two bilateral networks and 14 ipsilateral networks. Of the 16 intra-networks, two (one bilateral network and one ipsilateral networks) were significant predictors of MCI from the CNOA after adjusting for age, sex, education, disease history, and hippocampal volume/total intracranial volume ratio. In conclusion, we found that the relationship between hippocampal intra-networks and MCI was independent from the hippocampal volume. Our results suggest that altered hippocampal intra-networks may reflect a different pathology in MCI from that of brain atrophy.