Automated Atlas-Based Segmentation of Brain Structures in MR Images: Application to a Population-Based Imaging Study

The final type of segmentationmethod is atlas-based segmentation (sometimes also called label propagation). In this approach, additional knowledge is introduced through an atlas image, in which an expert has labeled the brain structures of interest. The atlas is first registered to the target image, and the resulting transformation is then used to deform the atlas labels to the coordinate system of the target image. During registration the similarity between the warped atlas image and the target image is maximized, while at the same time the deformation is constrained to ensure that the spatial information of the atlas is maintained

IT Infrastructure to Support the Secondary Use of Routinely Acquired Clinical Imaging Data for Research

We propose an infrastructure for the automated anonymization, extraction and processing of image data stored in clinical data repositories to make routinely acquired imaging data available for research purposes. The automated system, which was tested in the context of analyzing routinely acquired MR brain imaging data, consists of four modules: subject selection using PACS query, anonymization of privacy sensitive information and removal of facial features, quality assurance on DICOM header and image information, and quantitative imaging biomarker extraction. In total, 1,616 examinations were selected based on the following MRI scanning protocols: dementia protocol (246), multiple sclerosis protocol (446) and open question protocol (924). We evaluated the effectiveness of the infrastructure in accessing and successfully extracting biomarkers from routinely acquired clinical imaging data. To examine the validity, we compared brain volumes between patient groups with positive and negative diagnosis, according to the patient reports. Overall, success rates of image data retrieval and automatic processing were 82.5 %, 82.3 % and 66.2 % for the three protocol groups respectively, indicating that a large percentage of routinely acquired clinical imaging data can be used for brain volumetry research, despite image heterogeneity. In line with the literature, brain volumes were found to be significantly smaller (p-value <0.001) in patients with a positive diagnosis of dementia (915 ml) compared to patients with a negative diagnosis (939 ml). This study demonstrates that quantitative image biomarkers such as intracranial and brain volume can be extracted from routinely acquired clinical imaging data. This enables secondary use of clinical images for research into quantitative biomarkers at a hitherto unprecedented scale

The influence of cerebral small vessel disease on default mode network deactivation in mild cognitive impairment

Introduction Cerebral small vessel disease (CSVD) is thought to contribute to cognitive dysfunction in patients with mild cognitive impairment (MCI). The underlying mechanisms, and more specifically, the effects of CSVD on brain functioning in MCI are incompletely understood. The objective of the present study was to examine the effects of CSVD on brain functioning, activation and deactivation, in patients with MCI using task-related functional MRI (fMRI). Methods We included 16 MCI patients with CSVD, 26 MCI patients without CSVD and 25 controls. All participants underwent a physical and neurological examination, neuropsychological testing, structural MRI, and fMRI during a graded working memory paradigm. Results MCI patients with and without CSVD had a similar neuropsychological profile and task performance during fMRI, but differed with respect to underlying (de)activation patterns. MCI patients with CSVD showed impaired deactivation in the precuneus/posterior cingulate cortex, a region known to be involved in the default mode network. In MCI patients without CSVD, brain activation depended on working memory load, as they showed relative 'hyperactivation' during vigilance, and 'hypoactivation' at a high working memory load condition in working memory related brain regions. Conclusions We present evidence that the potential underlying mechanism of CSVD affecting cognition in MCI is through network interference. The observed differences in brain activation and deactivation between MCI patients with and without CSVD, who had a similar 'clinical phenotype', support the view that, in patients with MCI, different types of pathology can contribute to cognitive impairment through different pathways

Hyperthermia critical tissues automatic segmentation of head and neck CT images using atlas registration and graph cuts

\u3cp\u3eOutcome optimization of hyperthermia tumor treatment in the head and neck requires accurate hyperthermia treatment planning. Hyperthermia treatment planning is based on tissue segmentation for 3D patient model generation. We present here an automatic atlas-based segmentation algorithm for the organs at risk from CT images of the head and neck. To overcome the large anatomical variability, atlas registration and intensity-based classification were combined. A cost function composed of an intensity energy term, a spatial prior energy term based on the atlas registration and a regularization term is globally minimized using graph cut. The method was evaluated by measuring Dice similarity coefficient, mean and Hausdorff surface distances with respect to manual delineation. Overall a high correspondence was found with Dice similarity coefficient higher than 0.86 and a mean distance lower than the voxel resolution.\u3c/p\u3

Tissue segmentation of head and neck CT images for treatment planning:a multiatlas approach combined with intensity modeling

\u3cp\u3ePURPOSE: Hyperthermia treatment of head and neck tumors requires accurate treatment planning, based on 3D patient models that are derived from segmented 3D images. These segmentations are currently obtained by manual outlining of the relevant tissue regions, which is a tedious and time-consuming procedure (≈ 8 h) limiting the clinical applicability of hyperthermia treatment. In this context, the authors present and evaluate an automatic segmentation algorithm for CT images of the head and neck.\u3c/p\u3e\u3cp\u3eMETHODS: The proposed method combines anatomical information, based on atlas registration, with local intensity information in a graph cut framework. The method is evaluated with respect to ground truth manual delineation and compared with multiatlas-based segmentation on a dataset of 18 labeled CT images using the Dice similarity coefficient (DSC), the mean surface distance (MSD), and the Hausdorff surface distance (HSD) as evaluation measures. On a subset of 13 labeled images, the influence of different labelers on the method's accuracy is quantified and compared with the interobserver variability.\u3c/p\u3e\u3cp\u3eRESULTS: For the DSC, the proposed method performs significantly better for the segmentation of all the tissues, except brain stem and spinal cord. The MSD shows a significant improvement for optical nerve, eye vitreous humor, lens, and thyroid. For the HSD, the proposed method performs significantly better for eye vitreous humor and brainstem. The proposed method has a significantly better score for DSC, MSD, and HSD than the multiatlas-based method for the eye vitreous humor. For the majority of the tissues (8/11) the segmentation accuracy of the proposed method is approaching the interobserver agreement. The authors' method showed better robustness to variations in atlas labeling compared with multiatlas segmentation. Moreover, the method improved the segmentation reproducibility compared with human observer's segmentations.\u3c/p\u3e\u3cp\u3eCONCLUSIONS: In conclusion, the proposed framework provides in an accurate automatic segmentation of head and neck tissues in CT images for the generation of 3D patient models, which improves reproducibility, and substantially reduces labor involved in therapy planning.\u3c/p\u3

Older age relates to worsening of fine motor skills: A population based study of middle-aged and elderly persons

Introduction: In a population-based study of 1,912 community-dwelling persons of 45 years and older we investigated the relation between age and fine motor skills using the Archimedes spiral drawing test. Also, we studied the effect of brain volume on fine motor skills. Methods: Participants were required to trace a template of a spiral on an electronic drawing board. Clinical scores from this test were obtained by visual assessment of the drawings. Quantitative measures were objectively determined from the recorded data of the drawings. As tremor is known to occur increasingly with advancing age, we also rated drawings to assess presence of tremor. Results: We found presence of a tremor in 1.3% of the drawings. In the group without tremor we found that older age was related to worse fine motor skills. Additionally, participants over the age of 75 showed increasing deviations from the template when drawing the spiral. Larger cerebral volume and smaller white matter lesion volume were related to better spiral drawing performance, whereas cerebellar volume was not related to spiral dr

Total antioxidant capacity of the diet and major neurologic outcomes in older adults

Objective: To evaluate total antioxidant capacity of the diet, measured by the ferric-reducing antioxidant power (FRAP) assay, in relation to risks of dementia and stroke, as well as key structural brain volumes, in the elderly. Methods: We prospectively studied 5,395 participants in the Rott

Automated measurement of local white matter lesion volume

It has been hypothesized that white matter lesions at different locations may have different etiology and clinical consequences. Several approaches for the quantification of local white matter lesion load have been proposed in the literature, most of which rely on a distinction between lesions in a periventricular region close to the ventricles and a subcortical zone further away. In this work we present a novel automated method for local white matter lesion volume quantification in magnetic resonance images. The method segments and measures the white matter lesion volume in 43 regions defined by orientation and distance to the ventricles, which allows a more spatially detailed study of lesion load. The potential of the method was demonstrated by analyzing the effect of blood pressure on the regional white matter lesion volume in 490 elderly subjects taken from a longitudinal population study. The method was also compared to two commonly used techniques to assess the periventricular and subcortical lesion load. The main finding was that high blood pressure was primarily associated with lesion load in the vascular watershed area that forms the border between the periventricular and subcortical regions. It explains the associations found for both the periventricular and subcortical load computed for the same data, and that were reported in the literature. But the proposed method can localize the region of association with greater precision than techniques that distinguish between periventricular and subcortical lesions only. (C) 2011 Elsevier Inc. All rights reserved

Global and focal brain volume in long-term breast cancer survivors exposed to adjuvant chemotherapy

A limited number of studies have associated adjuvant chemotherapy with structural brain changes. These studies had small sample sizes and were conducted shortly after cessation of chemotherapy. Results of these studies indicate local gray matter volume decrease and an increase in white matter lesions. Up till now, it is unclear if non-CNS chemotherapy is associated with long-term structural brain changes. We compared focal and total brain volume (TBV) of a large set of non-CNS directed chemotherapy-exposed breast cancer survivors, on average 21 years post-treatment, to that of a population-based sample of women without a history of cancer. Structural MRI (1.5T) was performed in 184 chemotherapy-exposed breast cancer patients, mean age 64.0 (SD = 6.5) years, who had been diagnosed with cancer on average 21.1 (SD = 4.4) years before, and 368 age-matched cancer-free reference subjects from a population-based cohort study. Outcome measures were: TBV and total gray and white matter volume, and hippocampal volume. In addition, voxel based morphometry was performed to analyze differences in focal gray matter. The chemotherapy-exposed breast cancer survivors had significantly smaller TBV (-3.5 ml, P = 0.019) and gray matter volume (-2.9 ml,P = 0.003) than the reference subjects. No significant differences were observed in white matter volume, hippocampal volume, or local gray matter volume. This study shows that adjuvant chemotherapy for breast cancer is associated with long-term reductions in TBV and overall gray matter volume in the absence of focal reductions. The observed smaller gray matter volume in chemotherapyImaging Science and TechnologyApplied Science

Genetic determination of human facial morphology: links between cleft-lips and normal variation

Recent genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and other previous studies showed distinctly differing facial distance measurements when comparing unaffected relatives of NSCL/P patients with normal controls. Here, we test the hypothesis that genetic loci involved in NSCL/P also influence normal variation in facial morphology. We tested 11 SNPs from 10 genomic regions previously showing replicated evidence of association with NSCL/P for association with normal variation of nose width and bizygomatic distance in two cohorts from Germany (N=529) and the Netherlands (N=2497). The two most significant associations found were between nose width and SNP rs1258763 near the GREM1 gene in the German cohort (P=6 × 10(−4)), and between bizygomatic distance and SNP rs987525 at 8q24.21 near the CCDC26 gene (P=0.017) in the Dutch sample. A genetic prediction model explained 2% of phenotype variation in nose width in the German and 0.5% of bizygomatic distance variation in the Dutch cohort. Although preliminary, our data provide a first link between genetic loci involved in a pathological facial trait such as NSCL/P and variation of normal facial morphology. Moreover, we present a first approach for understanding the genetic basis of human facial appearance, a highly intriguing trait with implications on clinical practice, clinical genetics, forensic intelligence, social interactions and personal identity