Evaluation of atlas-based segmentation of hippocampi in healthy humans

Introduction and aim

Region of interest (ROI)-based functional magnetic resonance imaging (fMRI) data analysis relies on extracting signals from a specific area which is presumed to be involved in the brain activity being studied. The hippocampus is of interest in many functional connectivity studies for example in epilepsy as it plays an important role in epileptogenesis. In this context, ROI may be defined using different techniques. Our study aims at evaluating the spatial correspondence of hippocampal ROIs obtained using three brain atlases with hippocampal ROI obtained using an automatic segmentation algorithm dedicated to the hippocampus.

Material and methods

High-resolution volumetric T1-weighted MR images of 18 healthy volunteers (five females) were acquired on a 3T scanner. Individual ROIs for both hippocampi of each subject were segmented from the MR images using an automatic hippocampus and amygdala segmentation software called SACHA providing the gold standard ROI for comparison with the atlas-derived results. For each subject, hippocampal ROIs were also obtained using three brain atlases: PickAtlas available as a commonly used software toolbox; automated anatomical labeling (AAL) atlas included as a subset of ROI into PickAtlas toolbox and a frequency-based brain atlas by Hammers et al. The levels of agreement between the SACHA results and those obtained using the atlases were assessed based on quantitative indices measuring volume differences and spatial overlap. The comparison was performed in standard Montreal Neurological Institute space, the registration being obtained with SPM5 (http://www.fil.ion.ucl.ac.uk/spm/).

Results

The mean volumetric error across all subjects was 73% for hippocampal ROIs derived from AAL atlas; 20% in case of ROIs derived from the Hammers atlas and 107% for ROIs derived from PickAtlas. The mean false-positive and false-negative classification rates were 60% and 10% respectively for the AAL atlas; 16% and 32% for the Hammers atlas and 6% and 72% for the PickAtlas.

Conclusion

Though atlas-based ROI definition may be convenient, the resulting ROIs may be poor representations of the hippocampus in some studies critical to under- or oversampling. Performance of the AAL atlas was inferior to that of the Hammers atlas. Hippocampal ROIs derived from PickAtlas are highly significantly smaller, and this results in the worst performance out of three atlases. It is advisable that the defined ROIs should be verified with knowledge of neuroanatomy before using it for further data analysis.     

Computational anatomy with the SPM software

An overview of computational procedures for examining neuroanatomical variability is presented. The review focuses on approaches that can be applied using the SPM software package, beginning by explaining briefly how statistical parametric mapping is usually applied to functional imaging data. The review then proceeds to discuss volumetry, with an emphasis on voxel-based morphometry, and the pre-processing steps involved using the SPM software. Most volumetric studies involve univariate approaches, with a correction for some global measure, such as total brain volume. In contrast, the overall form of the brain may be more accurately modeled using multivariate approaches. Such models of anatomical variability may prove accurate enough for computer assisted diagnoses.     

3D Slicer as an image computing platform for the Quantitative Imaging Network

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside.     

Automated segmentation of lateral ventricles from human and primate magnetic resonance images using cognition network technology

Automatic segmentation of different types of tissue from magnetic resonance images is of great importance for clinical and research applications, particularly large-scale and longitudinal studies of brain pathology. We developed a fully automated algorithm for the segmentation of lateral ventricles from cranial magnetic resonance images. This problem is of interest in the study of schizophrenia, dementia and other neuropsychiatric disorders. Our algorithm achieves comparable results to expert human raters. The theoretical approach, which is based on an emerging object-oriented technology that has been adapted and evaluated to process 3D data for the first time, may, in the future, be transferred to other important problems of magnetic resonance image analysis like gray/white matter segmentation.     

Structure-biodistribution relation of neutral Tc(CO)3-complexes with tridentate N-substituted derivatives of aminoethylglycine and phenylenediamine

Derivatives of ethylenediamine-N-acetic acid (EDAA = N-aminoethylglycine = AEG) and ortho-phenylenediamine-N-acetic acid (PDAA) with uncharged substituents on one or both of the amines form neutral complexes with a [^99mTc(CO)₃]⁺-moiety. We studied the influence of different modifications at the amines (e.g., with methyl, ethyl, butyl or benzyl groups) on the behaviour of the ^99mTc(CO)₃-complexes in vivo in mice, with special focus on blood-brain barrier (BBB) passage. The complexes have been characterised by reversed phase HPLC, log P, electrophoresis and some of them also by LC-MS. Log P values of the ^99mTc-tricarbonyl complexes varied from −0.52 (AEG) to 2.5 (N,N′-dibenzyl-EDAA). With increasing lipophilicity, more of the activity was found in liver and intestines as compared to kidneys and urine for the more polar complexes. Brain uptake was found for the ^99mTc(CO)₃-complexes with N,N′-dibutyl-ethylenediamine-N-acetic acid (0.34% of I.D. after 2 min) and ortho-phenylenediamine-N-acetic acid (0.22% of I.D. after 2 min).     

高级脑活动的功能性核磁共振成像

功能性核磁共振成像技术可以显示大脑各个区域内静脉毛细血管中血液氧合状态所起的磁共振信号的小变化。使用ｆＭＲＩ的方法，可以在正常的活体上无损伤地实现大脑活动的功能定位，时空分辨率可分别达到秒和毫米数量级，尽管目前还面临一系列技术的困难，ｆＭＲＩ已经日益成为观察大脑活动，研究有脑的拓扑结构，进而揭示脑和思维关系的一种重要方法。     

Quantification of venous blood signal contribution to BOLD functional activation in the auditory cortex at 3 T

Most modern techniques for functional magnetic resonance imaging (fMRI) rely on blood-oxygen-level-dependent (BOLD) contrast as the basic principle for detecting neuronal activation. However, the measured BOLD effect depends on a transfer function related to neurophysiological changes accompanying electrical neural activation. The spatial accuracy and extension of the region of interest are determined by vascular effect, which introduces incertitude on real neuronal activation maps. Our efforts have been directed towards the development of a new methodology that is capable of combining morphological, vascular and functional information; obtaining new insight regarding foci of activation; and distinguishing the nature of activation on a pixel-by-pixel basis. Six healthy volunteers were studied in a parametric auditory functional experiment at 3 T; activation maps were overlaid on a high-resolution brain venography obtained through a novel technique. The BOLD signal intensities of vascular and nonvascular activated voxels were analyzed and compared: it was shown that nonvascular active voxels have lower values for signal peak (P<10(-7)) and area (P<10(-8)) with respect to vascular voxels. The analysis showed how venous blood influenced the measured BOLD signals, supplying a technique to filter possible venous artifacts that potentially can lead to misinterpretation of fMRI results. This methodology, although validated in the auditory cortex activation, maintains a general applicability to any cortical fMRI study, as the basic concepts on which it relies on are not limited to this cortical region. The results obtained in this study can represent the basis for new methodologies and tools that are capable of adding further characterization to the BOLD signal properties.     

基于微创光学参数(优化散射系数)测试的创伤性脑水肿甘露醇疗效评估研究

通过近红外光谱技术对创伤性脑水肿治疗效果进行了评估。首先采用Feeney’s自由落体撞击法建立SD大鼠创伤性脑水肿模型。然后利用两种不同剂量的甘露醇进行脱水治疗,同时应用自制的近红外(near infrared spectroscopy: NIRs)微创探头对脑组织进行在体实时监测,作为对比同时采用干湿比重法测量各监测时间点的脑水含量。最后根据近红外光谱技术实时监测的数据分析给药前后脑组织皮质优化散射系数(Reduced Scattering Coefficient: μ′_s)的变化规律,并结合脑水含量的变化情况,评估了不同剂量的甘露醇治疗创伤性脑水肿的疗效。根据实验结果得到结论：大脑皮层局部优化散射系数可以作为甘露醇疗效的实时评估参考指标参数,并且这种方法可以在体实时监测而不需处死动物,为将来颅脑损伤的实时疗效评估提出了一种方法。     

Artifacts in magnetic resonance imaging after surgical resection of brain tumors

Background

Since the advent of magnetic resonance imaging, metal artifacts have posed an important diagnostic problem in different fields of medicine. However, this has not been systematically studied in patients undergoing surgery for brain tumors.

Objective

This study was planned to assess whether metal artifacts can occur in patients undergoing brain surgery without metallic implants.

Methods

Of 40 individuals who could be included because of having a pre- and postoperative MRI and a postoperative computed tomography (CT) scan or a conventional skull X-ray for the detection of metallic artifacts, 26 patients agreed to participate in this study and gave informed consent.

Results

Twenty-six subjects, 12 males and 14 females, with an age range of 12 to 54 years, were included in the study. Four patients were found to have gross metal particles in their postoperative brain CTs and were excluded. Of the remaining 22 subjects, 7 patients (31.8%) had metallic artifacts.

Conclusion

Our study showed that simple bone drilling or chiseling during surgical manipulation of skull bones may result in separation of very tiny metal particles which can remain in the surgical site and cause artifacts in postoperative MRIs. This finding appeared to be independent of factors such as age, sex, tumor/incision site, tumor size, pathologic tumor type, total radiation dose, operation–MRI time interval and sequence of MRI.     

Brain MRI lesion volume measurement reproducibility is not dependent on the disease burden in patients with multiple sclerosis

We evaluated the potential effect of the lesion burden on the reproducibility of repeated lesion volume (LV) measurements from brain magnetic resonance imaging (MRI) scans of patients with multiple sclerosis (MS). Dual-echo, conventional spin echo brain MRI scans were obtained from 107 patients with MS. On proton density-weighted images, LV was assessed three times by the same raters, using a semi-automated, local thresholding technique for lesion segmentation. Mean LV (MLV) was 16.1 mL (range = 0.7–57.3 mL). The mean intra-observer coefficient of variation (COV) for the three measurement replicates was 2.6% (range = 0.2–7.2%). The intra-observer measurement variance (Var) increased with MLV and the fitted model was Var = 0.00187 MLV^1.84. This indicates that LV measurements can be considered as measures whose variances are proportional to the square of their mean values, i.e., these measures have constant COV. Using a semi-automated, local thresholding segmentation technique, the reproducibility of LV measurements from brain MRI scans of patients with MS is not significantly influenced by varying lesion burdens.