Age-related changes in brain structure include atrophy of the brain parenchyma and white matter changes of presumed vascular origin. Enlargement of the ventricles may occur due to atrophy or impaired ...cerebrospinal fluid (CSF) circulation. The co-occurrence of these changes in neurodegenerative diseases and in aging brains often requires investigators to take both into account when studying the brain, however, automated segmentation of enlarged ventricles and white matter hyperintensities (WMHs) can be a challenging task. Here, we present a hybrid multi-atlas segmentation and convolutional autoencoder approach for joint ventricle parcellation and WMH segmentation from magnetic resonance images (MRIs). Our fully automated approach uses a convolutional autoencoder to generate a standardized image of grey matter, white matter, CSF, and WMHs, which, in conjunction with labels generated by a multi-atlas segmentation approach, is then fed into a convolutional neural network to parcellate the ventricular system. Hence, our approach does not depend on manually delineated training data for new data sets. The segmentation pipeline was validated on both healthy elderly subjects and subjects with normal pressure hydrocephalus using ground truth manual labels and compared with state-of-the-art segmentation methods. We then applied the method to a cohort of 2401 elderly brains to investigate associations of ventricle volume and WMH load with various demographics and clinical biomarkers, using a multiple regression model. Our results indicate that the ventricle volume and WMH load are both highly variable in a cohort of elderly subjects and there is an independent association between the two, which highlights the importance of taking both the possibility of enlarged ventricles and WMHs into account when studying the aging brain.
Objectives
Idiopathic normal pressure hydrocephalus (INPH) is a neurodegenerative disorder characterized by excess cerebrospinal fluid (CSF) in the ventricles, which can be diagnosed by invasive CSF ...drainage test and treated by shunt placement. Here, we aim to investigate the diagnostic and prognostic power of systematic volumetric analysis based on brain structural MRI for INPH.
Methods
We performed a retrospective study with a cohort of 104 probable INPH patients who underwent CSF drainage tests and another cohort of 41 INPH patients who had shunt placement. High-resolution T1-weighted images of the patients were segmented using an automated pipeline into 283 structures that are grouped into different granularity levels for volumetric analysis. Volumes at multi-granularity levels were used in a recursive feature elimination model to classify CSF drainage responders and non-responders. We then used pre-surgical brain volumes to predict Tinetti and MMSE scores after shunting, based on the least absolute shrinkage and selection operator.
Results
The classification accuracy of differentiating the CSF drainage responders and non-responders increased as the granularity increased. The highest diagnostic accuracy was achieved at the finest segmentation with a sensitivity/specificity/precision/accuracy of 0.89/0.91/0.84/0.90 and an area under the curve of 0.94. The predicted post-surgical neurological scores showed high correlations with the ground truth, with
r
= 0.80 for Tinetti and
r
= 0.88 for MMSE. The anatomical features that played important roles in the diagnostic and prognostic tasks were also illustrated.
Conclusions
We demonstrated that volumetric analysis with fine segmentation could reliably differentiate CSF drainage responders from other INPH-like patients, and it could accurately predict the neurological outcomes after shunting.
Key Points
• We performed a fully automated segmentation of brain MRI at multiple granularity levels for systematic volumetric analysis of idiopathic normal pressure hydrocephalus (INPH) patients.
• We were able to differentiate patients that responded to CSF drainage test with an accuracy of 0.90 and area under the curve of 0.94 in a cohort of 104 probable INPH patients, as well as to predict the post-shunt gait and cognitive scores with a coefficient of 0.80 for Tinetti and 0.88 for MMSE.
• Feature analysis showed the inferior lateral ventricle, bilateral hippocampus, and orbital cortex are positive indicators of CSF drainage responders, whereas the posterior deep white matter and parietal subcortical white matter were negative predictors.
Magnetic resonance (MR) images with both high resolutions and high signal-to-noise ratios (SNRs) are desired in many clinical and research applications. However, acquiring such images takes a long ...time, which is both costly and susceptible to motion artifacts. Acquiring MR images with good in-plane resolution and poor through-plane resolution is a common strategy that saves imaging time, preserves SNR, and provides one viewpoint with good resolution in two directions. Unfortunately, this strategy also creates orthogonal viewpoints that have poor resolution in one direction and, for 2D MR acquisition protocols, also creates aliasing artifacts. A deep learning approach called SMORE that carries out both anti-aliasing and super-resolution on these types of acquisitions using no external atlas or exemplars has been previously reported but not extensively validated. This paper reviews the SMORE algorithm and then demonstrates its performance in four applications with the goal to demonstrate its potential for use in both research and clinical scenarios. It is first shown to improve the visualization of brain white matter lesions in FLAIR images acquired from multiple sclerosis patients. Then it is shown to improve the visualization of scarring in cardiac left ventricular remodeling after myocardial infarction. Third, its performance on multi-view images of the tongue is demonstrated and finally it is shown to improve performance in parcellation of the brain ventricular system. Both visual and selected quantitative metrics of resolution enhancement are demonstrated.
Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols ...were refined by several iterations of intra- and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T2 of individual white matter tracts. Distinctive features in FA and T2 were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.
Numerous brain disorders are associated with ventriculomegaly, including both neuro-degenerative diseases and cerebrospinal fluid disorders. Detailed evaluation of the ventricular system is important ...for these conditions to help understand the pathogenesis of ventricular enlargement and elucidate novel patterns of ventriculomegaly that can be associated with different diseases. One such disease is normal pressure hydrocephalus (NPH), a chronic form of hydrocephalus in older adults that causes dementia. Automatic parcellation of the ventricular system into its sub-compartments in patients with ventriculomegaly is quite challenging due to the large variation of the ventricle shape and size. Conventional brain labeling methods are time-consuming and often fail to identify the boundaries of the enlarged ventricles. We propose a modified 3D U-Net method to perform accurate ventricular parcellation, even with grossly enlarged ventricles, from magnetic resonance images (MRIs). We validated our method on a data set of healthy controls as well as a cohort of 95 patients with NPH with mild to severe ventriculomegaly and compared with several state-of-the-art segmentation methods. On the healthy data set, the proposed network achieved mean Dice similarity coefficient (DSC) of 0.895 ± 0.03 for the ventricular system. On the NPH data set, we achieved mean DSC of 0.973 ± 0.02, which is significantly (p < 0.005) higher than four state-of-the-art segmentation methods we compared with. Furthermore, the typical processing time on CPU-base implementation of the proposed method is 2 min, which is much lower than the several hours required by the other methods. Results indicate that our method provides: 1) highly robust parcellation of the ventricular system that is comparable in accuracy to state-of-the-art methods on healthy controls; 2) greater robustness and significantly more accurate results on cases of ventricular enlargement; and 3) a tool that enables computation of novel imaging biomarkers for dilated ventricular spaces that characterize the ventricular system.
The objective of this study was to test the hypothesis that bitemporal hemianopsia (BHA) is the most common visual field (VF) defect in patients with pituitary macroadenoma and to assess the degree ...of optic pathway compression necessary to produce visual defects.
We reviewed the MRI findings and medical records of 119 patients with pituitary macroadenoma who had undergone formal assessment of VFs. We then evaluated the degree of optic pathway displacement caused by the pituitary macroadenoma, as observed on MR images. The classifications of optic pathway displacement included no contact, abutment but no displacement, mild displacement (< 3 mm), and moderate displacement (≥ 3 mm). Qualitative analysis classified VFs as normal or as having defects that were monocular, bitemporal, mixed (bitemporal with additional defects), homonymous, or nonspecific.
A total of 89 of 115 patients had an abnormal VF. Only one patient had true BHA. The most common defects were bitemporal or mixed defects (in 49 of 115 patients 42.6%), likely because more than just the chiasm is often compressed by the pituitary macroadenoma. Classification of optic pathway displacement by the pituitary macroadenoma was as follows: 23 patients had no contact, eight had abutment but no displacement, 27 had mild displacement, and 57 had moderate displacement. In 78 of the 92 patients (84.8%) with pituitary macroadenoma that had contact with the optic pathway, contact was with the optic chiasm and the prechiasmal optic nerve. Of the 49 patients with bitemporal or mixed defects, 42 had moderate displacement of the optic pathway caused by their tumors.
BHA is exceedingly uncommon in patients with pituitary macroadenoma. However, although bitemporal and mixed defects are the most common abnormal VF findings, they were found in only 42.6% of patients. Such defects rarely occur if the tumor displaces the optic pathway less than 3 mm from baseline.
Introduction
Gruber’s ligament (GL), a surgical landmark, extends from the lateral upper clivus to the petrous apex (PA), forming the superior boundary of Dorello’s canal (DC). It overlies the ...interdural segment of the abducens nerve (CN VI). High-resolution 3D skull base MRI (SB-MRI) demonstrates anatomic details visible to the surgeon, but not well seen on traditional cross-sectional imaging. The aim of this study was to demonstrate visualization of the GL and its relationship to CN VI utilizing contrast enhanced high-resolution SB-MRI.
Methods
Two neuroradiologists retrospectively reviewed in consensus the SB-MRIs of 27 skull base sides, among 14 patients. GL detection rate, confidence of detection, and GL length were recorded. When GL was successfully identified, the position of the interdural segment of CN VI within DC was recorded.
Results
GL was readily identified in 16 skull base sides (59%), identified with some difficulty in 2 skull base sides (7%), and failed to be identified in 9 skull base sides (33%). The mean GL length was 7.1 mm (4.5–9.3 mm). Among the 18 cases where GL was successfully identified, CN VI was readily identified in all cases (100%), coursing the lateral third of DC in 72% of sides, and middle third in the remaining 28% of sides.
Conclusion
GL can be identified in approximately two-thirds of cases utilizing 3D high resolution SB-MRI. CN VI passes most commonly along the lateral third of DC. This is the first report demonstrating visualization of GL and its relation to CN VI, on imaging.
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