Pineocytoma with diffuse dissemination to the leptomeninges

Pineal parenchymal tumors are rare. Of the three types of pineal parenchymal tumors, pineocytomas are the least aggressive and are not known to diffusely disseminate. In this paper, we report the successful treatment of a case of pineocytoma with diffuse leptomeningeal relapse following initial stereotactic radiotherapy. A 39-year-old female presented with headaches, balance impairment, urinary incontinence, and blunted affect. A pineal mass was discovered on magnetic resonance imaging (MRI). A diagnosis of pineocytoma was established with an endoscopic pineal gland biopsy, and the patient received stereotactic radiotherapy. Ten years later, she developed diffuse leptomeningeal dissemination. The patient was then successfully treated with craniospinal radiation therapy. Leptomeningeal spread may develop as late as 10 years after initial presentation of pineocytoma. Our case demonstrates the importance of long-term follow-up of patients with pineal parenchymal tumors following radiation therapy, and the efficacy of craniospinal radiation in the treatment of leptomeningeal dissemination

A spatio-temporal atlas of the developing fetal brain with spina bifida aperta

Background: Spina bifida aperta (SBA) is a birth defect associated with severe anatomical changes in the developing fetal brain. Brain magnetic resonance imaging (MRI) atlases are popular tools for studying neuropathology in the brain anatomy, but previous fetal brain MRI atlases have focused on the normal fetal brain. We aimed to develop a spatio-temporal fetal brain MRI atlas for SBA. Methods: We developed a semi-automatic computational method to compute the first spatio-temporal fetal brain MRI atlas for SBA. We used 90 MRIs of fetuses with SBA with gestational ages ranging from 21 to 35 weeks. Isotropic and motion-free 3D reconstructed MRIs were obtained for all the examinations. We propose a protocol for the annotation of anatomical landmarks in brain 3D MRI of fetuses with SBA with the aim of making spatial alignment of abnormal fetal brain MRIs more robust. In addition, we propose a weighted generalized Procrustes method based on the anatomical landmarks for the initialization of the atlas. The proposed weighted generalized Procrustes can handle temporal regularization and missing annotations. After initialization, the atlas is refined iteratively using non-linear image registration based on the image intensity and the anatomical land-marks. A semi-automatic method is used to obtain a parcellation of our fetal brain atlas into eight tissue types: white matter, ventricular system, cerebellum, extra-axial cerebrospinal fluid, cortical gray matter, deep gray matter, brainstem, and corpus callosum. Results: An intra-rater variability analysis suggests that the seven anatomical land-marks are sufficiently reliable. We find that the proposed atlas outperforms a normal fetal brain atlas for the automatic segmentation of brain 3D MRI of fetuses with SBA. Conclusions: We make publicly available a spatio-temporal fetal brain MRI atlas for SBA, available here: https://doi.org/10.7303/syn25887675. This atlas can support future research on automatic segmentation methods for brain 3D MRI of fetuses with SBA

Label-Set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

Deep neural networks have increased the accuracy of automatic segmentation, however their accuracy depends on the availability of a large number of fully segmented images. Methods to train deep neural networks using images for which some, but not all, regions of interest are segmented are necessary to make better use of partially annotated datasets. In this paper, we propose the first axiomatic definition of label-set loss functions that are the loss functions that can handle partially segmented images. We prove that there is one and only one method to convert a classical loss function for fully segmented images into a proper label-set loss function. Our theory also allows us to define the leaf-Dice loss, a label-set generalisation of the Dice loss particularly suited for partial supervision with only missing labels. Using the leaf-Dice loss, we set a new state of the art in partially supervised learning for fetal brain 3D MRI segmentation. We achieve a deep neural network able to segment white matter, ventricles, cerebellum, extra-ventricular CSF, cortical gray matter, deep gray matter, brainstem, and corpus callosum based on fetal brain 3D MRI of anatomically normal fetuses or with open spina bifida. Our implementation of the proposed label-set loss functions is available at https://github.com/LucasFidon/label-set-loss-functions

Label-Set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation

Deep neural networks have increased the accuracy of automatic segmentation, however their accuracy depends on the availability of a large number of fully segmented images. Methods to train deep neural networks using images for which some, but not all, regions of interest are segmented are necessary to make better use of partially annotated datasets. In this paper, we propose the first axiomatic definition of label-set loss functions that are the loss functions that can handle partially segmented images. We prove that there is one and only one method to convert a classical loss function for fully segmented images into a proper label-set loss function. Our theory also allows us to define the leaf-Dice loss, a label-set generalisation of the Dice loss particularly suited for partial supervision with only missing labels. Using the leaf-Dice loss, we set a new state of the art in partially supervised learning for fetal brain 3D MRI segmentation. We achieve a deep neural network able to segment white matter, ventricles, cerebellum, extra-ventricular CSF, cortical gray matter, deep gray matter, brainstem, and corpus callosum based on fetal brain 3D MRI of anatomically normal fetuses or with open spina bifida. Our implementation of the proposed label-set loss functions is available at https://github.com/LucasFidon/label-set-loss-functions

Developmental Coordination Disorder: Disruption of the Cerebello-Cerebral Network evidenced by SPECT

Little is known about the neurobiological substrate of developmental coordination disorder (DCD), a neuro-developmental syndrome with significant, negative impact on the motor, cognitive and affective level throughout lifespan. This paper reports the clinical, neurocognitive and neuroradiological findings of a 19-year-old patient with typical DCD. As demonstrated by mild ataxia and a close semiological correspondence with the recently acknowledged ‘cerebellar cognitive affective syndrome’, clinical and neurocognitive investigations unambiguously indicated functional disruption of the cerebellum. Structural MRI of the brain confirmed cerebellar involvement revealing a slight anterior/superior asymmetry of vermal fissures consistent with rostral vermisdysplasia. Although this abnormality of vermal fissuration is generally considered an incidental neuroradiological finding without any clinical relevance, a potentially subtle impact on the developmental level has never been formally excluded. In addition to a generally decreased perfusion of the cerebellum, a quantified Tc-99m-ECD SPECT disclosed functional suppression of the anatomoclinically suspected supratentorial regions involved in the execution of planned actions, visuo-spatial processing and affective regulation. Based on these findings, it is hypothesised that the cerebellum is crucially implicated in the pathophysiologcial mechanisms of DCD, reflecting disruption of the cerebello-cerebral network involved in the execution of planned actions, visuo-spatial cognition and affective regulation

Identifying brain changes related to cognitive aging using VBM and visual rating scales

Aging is often associated with changes in brain structures as well as in cognitive functions. Structural changes can be visualized with Magnetic Resonance Imaging (MRI) using voxel-based grey matter morphometry (VBM) and visual rating scales to assess atrophy level. Several MRI studies have shown that possible neural correlates of cognitive changes can be seen in normal aging. It is still not fully understood how cognitive function as measured by tests and demographic factors are related to brain changes in the MRI. We recruited 55 healthy elderly subjects aged 50–79 years. A battery of cognitive tests was administered to all subjects prior to MRI scanning. Our aim was to assess correlations between age, sex, education, cognitive test performance, and the said two MRI-based measures. Our results show significant differences in VBM grey matter volume for education level (≤ 12 vs. > 12 years), with a smaller amount of grey matter volume in subjects with lower educational levels, and for age in interaction with education, indicating larger grey matter volume for young, higher educated adults. Also, grey matter volume was found to be correlated with working memory function (Digit Span Backward). Furthermore, significant positive correlations were found between visual ratings and both age and education, showing larger atrophy levels with increasing age and decreasing level of education. These findings provide supportive evidence that MRI-VBM detects structural differences for education level, and correlates with educational level and age, and working memory task performance.</p

Lobar and segmental liver atrophy associated with hilar cholangiocarcinoma and the impact of hilar biliary anatomical variants: a pictorial essay

The radiological features of lobar and segmental liver atrophy and compensatory hypertrophy associated with biliary obstruction are important to recognise for diagnostic and therapeutic reasons. Atrophied lobes/segments reduce in volume and usually contain crowded dilated bile ducts extending close to the liver surface. There is often a “step” in the liver contour between the atrophied and non-atrophied parts. Hypertrophied right lobe or segments enlarge and show a prominently convex or “bulbous” visceral surface. The atrophied liver parenchyma may show lower attenuation on pre-contrast computed tomography (CT) and CT intravenous cholangiography (CT-IVC) and lower signal intensity on T1-weighted magnetic resonance imaging (MRI). Hilar biliary anatomical variants can have an impact on the patterns of lobar/segmental atrophy, as the cause of obstruction (e.g. cholangiocarcinoma) often commences in one branch, leading to atrophy in that drainage region before progressing to complete biliary obstruction and jaundice. Such variants are common and can result in unusual but explainable patterns of atrophy and hypertrophy. Examples of changes seen with and without hilar variants are presented that illustrate the radiological features of atrophy/hypertrophy

Power estimation for non-standardized multisite studies

AbstractA concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions