Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity.

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Correlation between the regional brain volume and glymphatic system activity in progressive supranuclear palsy.

INTRODUCTION: Tau protein accumulation in the brain is thought to be one of the causes of progressive supranuclear palsy (PSP). The glymphatic system was discovered a decade ago as a waste drainage system in the brain that promotes the elimination of amyloid-beta and tau protein. We here evaluated the relationships between glymphatic system activity and regional brain volumes in PSP patients. METHOD: Subjects were 24 patients with PSP and 42 healthy participants who underwent diffusion tensor imaging (DTI). We computed the diffusion tensor image analysis along the perivascular space (DTI­ALPS) index as a proxy of glymphatic system activity, and estimated the relationships between the DTI­ALPS index and regional brain volume in PSP patients by whole-brain and region-of-interest analyses, including analyses of the midbrain and third and lateral ventricles. RESULTS: The DTI­ALPS index was significantly lower in patients with PSP, compared with healthy subjects. Further, there were significant correlations between the DTI­ALPS index and the regional brain volumes in the midbrain tegmentum, pons, right frontal lobe, and lateral ventricles in patients with PSP. CONCLUSIONS: Our data suggest that the DTI­ALPS index is a good biomarker for PSP and might be effective to distinguish PSP from other neurocognitive disorders.

Dural and Leptomeningeal Diseases: Anatomy, Causes, and Neuroimaging Findings.

Meningeal lesions can be caused by various conditions and pose diagnostic challenges. The authors review the anatomy of the meninges in the brain and spinal cord to provide a better understanding of the localization and extension of these diseases and summarize the clinical and imaging features of various conditions that cause dural and/or leptomeningeal enhancing lesions. These conditions include infectious meningitis (bacterial, tuberculous, viral, and fungal), autoimmune diseases (vasculitis, connective tissue diseases, autoimmune meningoencephalitis, Vogt-Koyanagi-Harada disease, neuro-Behçet syndrome, Susac syndrome, and sarcoidosis), primary and secondary tumors (meningioma, diffuse leptomeningeal glioneuronal tumor, melanocytic tumors, and lymphoma), tumorlike diseases (histiocytosis and immunoglobulin G4-related diseases), medication-induced diseases (immune-related adverse effects and posterior reversible encephalopathy syndrome), and other conditions (spontaneous intracranial hypotension, amyloidosis, and moyamoya disease). Although meningeal lesions may manifest with nonspecific imaging findings, correct diagnosis is important because the treatment strategy varies among these diseases. ©RSNA, 2023 Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. Quiz questions for this article are available through the Online Learning Center.

Imaging Features of Ectopic Tissues and Their Complications: Embryologic and Anatomic Approach.

Ectopic tissue is an anatomic abnormality in which tissue develops in an area outside its normal location. It is primarily caused by abnormalities during the process of embryologic development. Although the majority of individuals with ectopic tissues remain asymptomatic, various symptoms and associated complications can occur. Failure in normal embryologic development leads to loss of normal physiologic function or may result in harmful functions such as ectopic hormonal secretion in the ectopic pituitary adenoma. Ectopic tissues may also frequently mimic tumors. For example, developmental abnormalities in the pharyngeal pouches may result in an ectopic parathyroid gland and ectopic thymus, both of which are frequently misdiagnosed as tumors. Adequate knowledge of embryology is essential for understanding the differential diagnoses of ectopic tissues and facilitating appropriate management. The authors summarize the embryologic development and pathogenesis of ectopic tissues by using illustrations to facilitate a deeper understanding of embryologic development and anatomy. Characteristic imaging findings (US, CT, MRI, and scintigraphy) are described for ectopic tissues of the brain, head, neck, thorax, abdomen, and pelvis by focusing on common conditions that radiologists may encounter in daily practice and their differential diagnoses. ©RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.

Clinical and neuroimaging findings in patients with lissencephaly/subcortical band heterotopia spectrum: a magnetic resonance conventional and diffusion tensor study.

PURPOSE: To clarify brain abnormalities on magnetic resonance imaging (MRI) and its clinical implications in lissencephaly/subcortical band heterotopia (LIS/SBH) spectrum patients. METHODS: The clinical severity and classification according to Di Donato were retrospectively reviewed in 23 LIS/SBH spectrum patients. The morphological and signal abnormalities of the brainstem, corpus callosum, and basal ganglia were also assessed. The brainstem distribution pattern of the corticospinal tract (CST) was analyzed by diffusion tensor imaging (DTI) and categorized into two types: normal pattern, in which the CST and medial lemniscus (ML) are separated by the dorsal portion of the transverse pontine fiber, and the abnormal pattern, in which the CST and ML are juxtaposed on the dorsal portion of a single transverse pontine fiber. Correlations between MR grading score and potential additional malformative findings of the brain and clinical symptoms were investigated. RESULTS: All patients with grade 3 (n = 5) showed brainstem deformities, signal abnormalities of pontine surface and had a tendency of basal ganglia deformity and callosal hypoplasia whereas those abnormalities were rarely seen in patients with grade 1 and 2 (n = 18). For DTI analysis, the patients with grade 3 LIS/SBH had typically abnormal CST, whereas the patients with grade 1 and 2 LIS/SBH had normal CST. The classification was well correlated with CST and brainstem abnormalities and clinical severity. CONCLUSION: MR assessment including DTI analysis may be useful in assessing the clinical severity in LIS/BH spectrum and may provide insight into its developmental pathology.

Localization of the central sulcus using the distinctive high signal intensity of the paracentral lobule on T1-weighted images.

PURPOSE: The central sulcus is an important landmark in the brain. This study aimed to investigate the distinctive signal of the paracentral lobule (PL) on T1-weighted images (T1WIs; the white PL sign) and evaluate its usefulness as a new method of identifying the central sulcus. METHODS: T1WIs of the brain of 96 participants (age, 58.9 ± 17.9 years; range, 8-87 years) scanned at 3-T MR system were retrospectively reviewed. First, we qualitatively analyzed the signal of the cortex of the PL by comparing it with that of the ipsilateral superior frontal gyrus on a 4-point grading score. Second, we compared the cortical signal intensity and gray/white-matter contrast between the PL and superior frontal gyrus. Third, we evaluated the usefulness of the PL signal for identifying the central sulcus. RESULTS: The PL cortex was either mildly hyperintense (grade 2) or definitely hyperintense (grade 3) in comparison with that of superior frontal cortex in all participants. The signal intensity of the PL cortex was significantly higher than that of the superior frontal cortex (p < 0.001), whereas the gray/white-matter contrast of the PL was weaker than that of the superior frontal gyrus (p < 0.001). The central sulci were identified with 94.3% accuracy (181/192) using the new method. CONCLUSION: The white PL sign may be helpful in identifying the central sulcus, and this approach can be recognized as a new method for identification of the central sulcus.

The Usefulness of Computer-Aided Detection of Brain Metastases on Contrast-Enhanced Computed Tomography Using Single-Shot Multibox Detector: Observer Performance Study.

OBJECTIVE: This study aimed to test the usefulness of computer-aided detection (CAD) for the detection of brain metastasis (BM) on contrast-enhanced computed tomography. METHODS: The test data set included whole-brain axial contrast-enhanced computed tomography images of 25 cases with 62 BMs and 5 cases without BM. Six radiologists from 3 institutions with 2 to 4 years of experience independently reviewed the cases, both in conditions with and without CAD assistance. Sensitivity, positive predictive value, number of false positives, and reading time were compared between the conditions using paired t tests. Subanalysis was also performed for groups of lesions divided according to size. A P value <0.05 was considered statistically significant. RESULTS: With CAD, sensitivity significantly increased from 80.4% to 83.9% ( P = 0.04), whereas positive predictive value significantly decreased from 88.7% to 84.8% ( P = 0.03). Reading time with and without CAD was 112 and 107 seconds, respectively ( P = 0.38), and the number of false positives was 10.5 with CAD and 7.0 without CAD ( P = 0.053). Sensitivity significantly improved for 6- to 12-mm lesions, from 71.2% without CAD to 80.3% with CAD ( P = 0.02). The sensitivity of the CAD (95.2%) was significantly higher than that of any reader (with CAD: P = 0.01; without CAD: P = 0.005). CONCLUSIONS: Computer-aided detection significantly improved BM detection sensitivity without prolonging reading time while marginally increased the false positives.

Cross-scanner reproducibility and harmonization of a diffusion MRI structural brain network: A traveling subject study of multi-b acquisition.

Characterization of brain networks by diffusion MRI (dMRI) has rapidly evolved, and there are ongoing movements toward data sharing and multi-center studies. To extract meaningful information from multi-center data, methods to correct for the bias caused by scanner differences, that is, harmonization, are urgently needed. In this work, we report the cross-scanner differences in structural network analyses using data from nine traveling subjects (four males and five females, 21-49 years-old) who underwent scanning using four 3T scanners (public database available from the Brain/MINDS Beyond Human Brain MRI project (http://mriportal.umin.jp/)). The reliability and reproducibility were compared to those of data from another set of four subjects (all males, 29-42 years-old) who underwent scan-rescan (interval, 105-147 days) with the same scanner as well as scan-rescan data from the Human Connectome Project database. The results demonstrated that the reliability of the edge weights and graph theory metrics was lower for data including different scanners, compared to the scan-rescan with the same scanner. Besides, systematic differences between scanners were observed, indicating the risk of bias in comparing networks obtained from different scanners directly. We further demonstrate that it is feasible to reduce inter-scanner variabilities while preserving the inter-subject differences among healthy individuals by modeling the scanner effects at the level of network matrices, when traveling-subject data are available for calibration between scanners. The present data and results are expected to serve as a basis for developing and evaluating novel harmonization methods.

Forward-projected Model-based Iterative Reconstruction SoluTion in Temporal Bone Computed Tomography: A Comparison Study of All Reconstruction Modes.

OBJECTIVE: Identify appropriate reconstruction modes of Forward-projected model-based Iterative Reconstruction SoluTion (FIRST) in temporal bone computed tomography (CT) and investigate the contribution of spatial resolution and noise to the visual assessment. METHODS: Sixteen temporal bone CT images were reconstructed. Two blinded radiologists assessed 8 anatomical structures and classified the visual assessment. These visual scores were compared across reconstruction modes among each anatomical structure. Visual scores and contrast-to-noise ratio, noise power spectrum (NPS) at low (NPSLow) and high (NPSHigh) spatial frequencies, and 50% modulation transfer function relationships were evaluated. RESULTS: Visual scores differed significantly for the stapedius muscle and osseous spiral lamina, with CARDIAC SHARP, BONE, and LUNG modes for the osseous spiral lamina scoring highest. Visual scores significantly positively correlated with NPSLow, NPSHigh, and 50% modulation transfer function but negatively with contrast-to-noise ratio. CONCLUSIONS: Modes providing higher spatial resolution and lower noise reduction showed an improved visual assessment of CT images reconstructed with FIRST.

Super-resolution Deep Learning Reconstruction for 3D Brain MR Imaging: Improvement of Cranial Nerve Depiction and Interobserver Agreement in Evaluations of Neurovascular Conflict.

RATIONALE AND OBJECTIVES: To determine if super-resolution deep learning reconstruction (SR-DLR) improves the depiction of cranial nerves and interobserver agreement when assessing neurovascular conflict in 3D fast asymmetric spin echo (3D FASE) brain MR images, as compared to deep learning reconstruction (DLR). MATERIALS AND METHODS: This retrospective study involved reconstructing 3D FASE MR images of the brain for 37 patients using SR-DLR and DLR. Three blinded readers conducted qualitative image analyses, evaluating the degree of neurovascular conflict, structure depiction, sharpness, noise, and diagnostic acceptability. Quantitative analyses included measuring edge rise distance (ERD), edge rise slope (ERS), and full width at half maximum (FWHM) using the signal intensity profile along a linear region of interest across the center of the basilar artery. RESULTS: Interobserver agreement on the degree of neurovascular conflict of the facial nerve was generally higher with SR-DLR (0.429-0.923) compared to DLR (0.175-0.689). SR-DLR exhibited increased subjective image noise compared to DLR (p ≥ 0.008). However, all three readers found SR-DLR significantly superior in terms of sharpness (p < 0.001); cranial nerve depiction, particularly of facial and acoustic nerves, as well as the osseous spiral lamina (p < 0.001); and diagnostic acceptability (p ≤ 0.002). The FWHM (mm)/ERD (mm)/ERS (mm-1) for SR-DLR and DLR was 3.1-4.3/0.9-1.1/8795.5-10,703.5 and 3.3-4.8/1.4-2.1/5157.9-7705.8, respectively, with SR-DLR's image sharpness being significantly superior (p ≤ 0.001). CONCLUSION: SR-DLR enhances image sharpness, leading to improved cranial nerve depiction and a tendency for greater interobserver agreement regarding facial nerve neurovascular conflict.

The glymphatic system as a potential biomarker and therapeutic target in secondary progressive multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a refractory immune-mediated inflammatory disease of the central nervous system, and some cases of the major subtype, relapsing-remitting (RR), transition to secondary progressive (SP). However, the detailed pathogenesis, biomarkers, and effective treatment strategies for secondary progressive multiple sclerosis have not been established. The glymphatic system, which is responsible for waste clearance in the brain, is an intriguing avenue for investigation and is primarily studied through diffusion tensor image analysis along the perivascular space (DTI-ALPS). This study aimed to compare DTI-ALPS indices between patients with RRMS and SPMS to uncover potential differences in their pathologies and evaluate the utility of the glymphatic system as a possible biomarker. METHODS: A cohort of 26 patients with MS (13 RRMS and 13 SPMS) who met specific criteria were enrolled in this prospective study. Magnetic resonance imaging (MRI), including diffusion MRI, 3D T1-weighted imaging, and relaxation time quantification, was conducted. The ALPS index, a measure of glymphatic function, was calculated using diffusion-weighted imaging data. Demographic variables, MRI metrics, and ALPS indices were compared between patients with RRMS and those with SPMS. RESULTS: The ALPS index was significantly lower in the SPMS group. Patients with SPMS exhibited longer disease duration and higher Expanded Disability Status Scale (EDSS) scores than those with RRMS. Despite these differences, the correlations between the EDSS score, disease duration, and ALPS index were minimal, suggesting that the impact of these clinical variables on ALPS index variations was negligible. DISCUSSION: Our study revealed the potential microstructural and functional differences between RRMS and SPMS related to glymphatic system impairment. Although disease severity and duration vary among subtypes, their influence on ALPS index differences appears to be limited. This highlights the stronger association between SP conversion and changes in the ALPS index. These findings align with those of previous research, indicating the involvement of the glymphatic system in the progression of MS. CONCLUSION: Although the causality remains uncertain, our study suggests that a reduced ALPS index, reflecting glymphatic system dysfunction, may contribute to MS progression, particularly in SPMS. This suggests the potential of the ALPS index as a diagnostic biomarker for SPMS and underscores the potential of the glymphatic system as a therapeutic target to mitigate MS progression. Future studies with larger cohorts and pathological validation are necessary to confirm these findings. This study provides new insights into the pathogenesis of SPMS and the potential for innovative therapeutic strategies.

Magnetic resonance imaging features of complete androgen insensitivity syndrome in comparison to Mayer-Rokitansky-Küster-Hauser syndrome.

PURPOSE: Complete androgen insensitivity syndrome (CAIS) and Mayer-Rokitansky-Küster-Hauser syndrome (MRKHS) share common clinical features such as female phenotype, vaginal hypoplasia, and primary amenorrhea. Magnetic resonance imaging (MRI) is performed to investigate the cause of primary amenorrhea. However, the MRI features are also similar in both disorders. They are ultimately diagnosed by chromosome testing, but there is a possibility of misdiagnosis if chromosome testing is not performed. This study aimed to identify MRI features that are useful for differentiating CAIS from MRKHS. METHOD: This multicenter retrospective study included 12 patients with CAIS and 19 patients with MRKHS. Three radiologists blindly evaluated the following features: (1) detection of vagina, (2) detection of nodular and cystic structures in the lateral pelvis; undescended testicles and paratesticular cysts in CAIS and rudimentary uteri and ovaries in MRKHS, (3) their location, (4) number of cysts in the cystic structures, and (5) signal intensity on diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) values of the nodular structures. Statistical comparisons were performed using Mann-Whitney U and Fisher's exact tests. RESULTS: Compared with MRKHS, the CAIS group showed significantly detectable vagina, more ventrally located nodular and cystic structures, fewer cysts within the cystic structures, and nodular structures with higher signal intensity on DWI and lower ADC values. CONCLUSIONS: MRI features of detectable vagina, location of nodular and cystic structures, number of cysts within the cystic structures, signal intensity on DWI and ADC values of the nodular structures were useful in differentiating CAIS from MRKHS.

Performance changes due to differences among annotating radiologists for training data in computerized lesion detection.

PURPOSE: The quality and bias of annotations by annotators (e.g., radiologists) affect the performance changes in computer-aided detection (CAD) software using machine learning. We hypothesized that the difference in the years of experience in image interpretation among radiologists contributes to annotation variability. In this study, we focused on how the performance of CAD software changes with retraining by incorporating cases annotated by radiologists with varying experience. METHODS: We used two types of CAD software for lung nodule detection in chest computed tomography images and cerebral aneurysm detection in magnetic resonance angiography images. Twelve radiologists with different years of experience independently annotated the lesions, and the performance changes were investigated by repeating the retraining of the CAD software twice, with the addition of cases annotated by each radiologist. Additionally, we investigated the effects of retraining using integrated annotations from multiple radiologists. RESULTS: The performance of the CAD software after retraining differed among annotating radiologists. In some cases, the performance was degraded compared to that of the initial software. Retraining using integrated annotations showed different performance trends depending on the target CAD software, notably in cerebral aneurysm detection, where the performance decreased compared to using annotations from a single radiologist. CONCLUSIONS: Although the performance of the CAD software after retraining varied among the annotating radiologists, no direct correlation with their experience was found. The performance trends differed according to the type of CAD software used when integrated annotations from multiple radiologists were used.

Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging.

Background: Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics. Objective: The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics. Methods: Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics. Results: Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology. Conclusions: This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.

Multimodal imaging analyses in neuromyelitis optica spectrum disorder with or without visual disturbance.

BACKGROUND AND PURPOSE: Neuromyelitis optica spectrum disorder is a demyelinating and inflammatory affliction that often leads to visual disturbance. Various imaging techniques, including free-water imaging, have been used to determine neuroinflammation and degeneration. Therefore, this study aimed at determining multimodal imaging differences between patients with neuromyelitis optica spectrum disorder, especially those with visual disturbance, and healthy controls. MATERIALS AND METHODS: Eighty-five neuromyelitis optica spectrum disorder patients and 89 age- and sex-matched healthy controls underwent 3-T magnetic resonance imaging (MRI). We analyzed adjusted brain-predicted age difference, voxel-based morphometry, and free-water-corrected diffusion tensor imaging (DTI) by tract-based spatial statistics in each patient group (MRI-positive/negative neuromyelitis optica spectrum disorder patients with or without a history of visual disturbance) compared with the healthy control group. RESULTS: MRI-positive neuromyelitis optica spectrum disorder patients exhibited reduced volumes of the bilateral thalamus. Tract-based spatial statistics showed diffuse white matter abnormalities in all DTI metrics in MRI-positive neuromyelitis optica spectrum disorder patients with a history of visual disturbance. In MRI-negative neuromyelitis optica spectrum disorder patients with a history of visual disturbance, voxel-based morphometry showed volume reduction of bilateral thalami and optic radiations, and tract-based spatial statistics revealed significantly lower free-water-corrected fractional anisotropy and higher mean diffusivity in the posterior dominant distributions, including the optic nerve radiation. CONCLUSION: Free-water-corrected DTI and voxel-based morphometry analyses may reflect symptoms of visual disturbance in neuromyelitis optica spectrum disorder.

Clinical and neuroimaging review of triplet repeat diseases.

Triplet repeat diseases (TRDs) refer to a group of diseases caused by three nucleotide repeats elongated beyond a pathologic threshold. TRDs are divided into the following four groups depending on the pathomechanisms, although the pathomechanisms of several diseases remain unelucidated: polyglutamine disorders, caused by a pathologic repeat expansion of CAG (coding the amino acid glutamine) located within the exon; loss-of-function repeat disorders, characterized by the common feature of a loss of function of the gene within which they occur; RNA gain-of-function disorders, involving the production of a toxic RNA species; and polyalanine disorders, caused by a pathologic repeat expansion of GCN (coding the amino acid alanine) located within the exon. Many of these TRDs manifest through neurologic symptoms; moreover, neuroimaging, especially brain magnetic resonance imaging, plays a pivotal role in the detection of abnormalities, differentiation, and management of TRDs. In this article, we reviewed the clinical and neuroimaging features of TRDs. An early diagnosis of TRDs through clinical and imaging approaches is important and may contribute to appropriate medical intervention for patients and their families.

Low-grade appendiceal mucinous neoplasm with puffer ball-like appearance: A case report.

We report a case of ruptured low-grade appendiceal mucinous neoplasm with an impressive toy puffer ball-like appearance on magnetic resonance imaging. A 79-year-old woman with lower abdominal pain underwent computed tomography scanning, revealing a 6-cm mass in the right lower abdomen. T2-weighted images showed a radial low-signal structure in the central area of the mass, which was presumed to be fibrotic. Pathology confirmed ruptured low-grade appendiceal mucinous neoplasm. The rupture point was at the tip of the appendix, coinciding with the center of radial fibrosis. The unique morphology of the puffer ball-like appearance in this case may be a characteristic of low-grade appendiceal mucinous neoplasms.

Neuroimaging of hypophysitis: etiologies and imaging mimics.

Hypophysitis is an inflammatory disease affecting the pituitary gland. Hypophysitis can be classified into multiple types depending on the mechanisms (primary or secondary), histology (lymphocytic, granulomatous, xanthomatous, plasmacytic/IgG4 related, necrotizing, or mixed), and anatomy (adenohypophysitis, infundibulo-neurohypophysitis, or panhypophysitis). An appropriate diagnosis is vital for managing these potentially life-threatening conditions. However, physiological morphological alterations, remnants, and neoplastic and non-neoplastic lesions may masquerade as hypophysitis, both clinically and radiologically. Neuroimaging, as well as imaging findings of other sites of the body, plays a pivotal role in diagnosis. In this article, we will review the types of hypophysitis and summarize clinical and imaging features of both hypophysitis and its mimickers.

Relationship between the tau protein and choroid plexus volume in Alzheimer's disease.

Tau protein accumulation in the brain is thought to be one of the causes of Alzheimer's disease (AD). Recent studies found that the choroid plexus (CP) has a role in ß-amyloid and tau protein clearance in the brain. We evaluated the relationships between CP volume and the ß-amyloid and tau protein depositions. Participants were 20 patients with AD and 35 healthy subjects who underwent MRI and PET scanning using the ß-amyloid tracer 11C-PiB and the tau/inflammatory tracer 18F-THK5351. We computed the volume of the CP and estimated the relationships between the CP volume and ß-amyloid and tau protein/inflammatory deposition by Spearman's correlation test. The CP volume was significantly positively correlated with both the standardized uptake value ratio (SUVR) of 11C-PiB and the SUVR of 18F-THK5351 in all participants. The CP volume was also significantly positively correlated with the SUVR of 18F-THK5351in patients with AD. Our data suggested that the volume of the CP was a good biomarker for the evaluation of tau deposition and neuroinflammation.