Association between prenatal alcohol exposure and children's facial shape: a prospective population-based cohort study.

STUDY QUESTION: Is there an association between low-to-moderate levels of prenatal alcohol exposure (PAE) and children's facial shape? SUMMARY ANSWER: PAE before and during pregnancy, even at low level (<12 g of alcohol per week), was found associated with the facial shape of children, and these associations were found attenuated as children grow older. WHAT IS KNOWN ALREADY: High levels of PAE during pregnancy can have significant adverse associations with a child's health development resulting in recognizably abnormal facial development. STUDY DESIGN, SIZE, DURATION: This study was based on the Generation R Study, a prospective cohort from fetal life onwards with maternal and offspring data. We analyzed children 3-dimensional (3D) facial images taken at ages 9 (n = 3149) and 13 years (n = 2477) together with the data of maternal alcohol consumption. PARTICIPANTS/MATERIALS, SETTING, METHODS: We defined six levels of PAE based on the frequency and dose of alcohol consumption and defined three tiers based on the timing of alcohol exposure of the unborn child. For the image analysis, we used 3D graph convolutional networks for non-linear dimensionality reduction, which compressed the high-dimensional images into 200 traits representing facial morphology. These 200 traits were used for statistical analysis to search for associations with PAE. Finally, we generated heatmaps to display the facial phenotypes associated with PAE. MAIN RESULTS AND THE ROLE OF CHANCE: The results of the linear regression in the 9-year-old children survived correction for multiple testing with false discovery rate (FDR). In Tier 1 where we examined PAE only before pregnancy (exposed N = 278, unexposed N = 760), we found three traits survived FDR correction. The lowest FDR-P is 1.7e-05 (beta = 0.021, SE = 0.0040) in Trait #29; In Tier 2b where we examine any PAE during first trimester (exposed N = 756; unexposed N = 760), we found eight traits survived FDR correction. The lowest FDR-P is 9.0e-03 (beta = -0.013, SE = 0.0033) in Trait #139. Moreover, more statistically significant facial traits were found in higher levels of PAE. No FDR-significant results were found in the 13-year-old children. We map these significant traits back to the face, and found the most common detected facial phenotypes included turned-up nose tip, shortened nose, turned-out chin, and turned-in lower-eyelid-related regions. LIMITATIONS, REASONS FOR CAUTION: We had no data for alcohol consumption more than three months prior to pregnancy and thus do not know if maternal drinking had chronic effects. The self-reported questionnaire might not reflect accurate alcohol measurements because mothers may have denied their alcohol consumption. WIDER IMPLICATIONS OF THE FINDINGS: Our results imply that facial morphology, such as quantified by the approach we proposed here, can be used as a biomarker in further investigations. Furthermore, our study suggests that for women who are pregnant or want to become pregnant soon, should quit alcohol consumption several months before conception and completely during pregnancy to avoid adverse health outcomes in the offspring. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by Erasmus Medical Centre, Rotterdam, the Erasmus University Rotterdam, and the Netherlands Organization for Health Research. V.W.V.J. reports receipt of funding from the Netherlands Organization for Health Research (ZonMw 90700303). W.J.N. is a founder, a scientific lead, and a shareholder of Quantib BV. TRIAL REGISTRATION NUMBER: N/A.

Radiomics approach to distinguish between well differentiated liposarcomas and lipomas on MRI.

BACKGROUND: Well differentiated liposarcoma (WDLPS) can be difficult to distinguish from lipoma. Currently, this distinction is made by testing for MDM2 amplification, which requires a biopsy. The aim of this study was to develop a noninvasive method to predict MDM2 amplification status using radiomics features derived from MRI. METHODS: Patients with an MDM2-negative lipoma or MDM2-positive WDLPS and a pretreatment T1-weighted MRI scan who were referred to Erasmus MC between 2009 and 2018 were included. When available, other MRI sequences were included in the radiomics analysis. Features describing intensity, shape and texture were extracted from the tumour region. Classification was performed using various machine learning approaches. Evaluation was performed through a 100 times random-split cross-validation. The performance of the models was compared with the performance of three expert radiologists. RESULTS: The data set included 116 tumours (58 patients with lipoma, 58 with WDLPS) and originated from 41 different MRI scanners, resulting in wide heterogeneity in imaging hardware and acquisition protocols. The radiomics model based on T1 imaging features alone resulted in a mean area under the curve (AUC) of 0·83, sensitivity of 0·68 and specificity of 0·84. Adding the T2-weighted imaging features in an explorative analysis improved the model to a mean AUC of 0·89, sensitivity of 0·74 and specificity of 0·88. The three radiologists scored an AUC of 0·74 and 0·72 and 0·61 respectively; a sensitivity of 0·74, 0·91 and 0·64; and a specificity of 0·55, 0·36 and 0·59. CONCLUSION: Radiomics is a promising, non-invasive method for differentiating between WDLPS and lipoma, outperforming the scores of the radiologists. Further optimization and validation is needed before introduction into clinical practice.

ANTECEDENTES: Es difícil distinguir los liposarcomas bien diferenciados (well-differentiated liposarcomas, WDLPS) de los lipomas. En la actualidad, esta distinción se realiza mediante la prueba de amplificación del gen MDM2 por biopsia. El objetivo de este estudio fue predecir de forma no invasiva el estado de amplificación del gen MDM2 para diferenciar los lipomas de los WDLPS utilizando características radiómicas a partir de la resonancia magnética. MÉTODOS: Se incluyeron los pacientes remitidos al instituto Erasmus MC entre 2009-2018 por un lipoma MDM2 negativo o WDLPS MDM2 positivo y las resonancias magnéticas potenciadas en T1 correspondientes antes del tratamiento. Cuando estaban disponibles, se incluyeron otras secuencias de MRI en el análisis radiómico. Se describieron la intensidad, forma y textura de la región tumoral. Para la clasificación se utilizaron varios modelos de aprendizaje automático (machine learning). La evaluación se realizó mediante una validación cruzada aleatoria 100x. Se comparó el rendimiento de los modelos con la clasificación realizada por tres radiólogos expertos. RESULTADOS: Se incluyeron 116 pacientes (58 lipomas, 58 WDLPS) y 41 aparatos de MRI, con una gran heterogeneidad en las técnicas y protocolos para la adquisición de imágenes. El modelo radiómico basado únicamente en las características de las imagen en T1 dio como resultado una AUC media de 0,83, con una sensibilidad de 0,68 y una especificidad de 0,84. Un análisis adicional incorporando las imágenes ponderadas en T2 mejoró el modelo con una AUC media de 0,89, una sensibilidad de 0,74 y una especificidad de 0,88. Los tres radiólogos obtuvieron una AUC de 0,74/0,72/0,61, una sensibilidad de 0,74/0,91/0,64 y una especificidad de 0,55/0,36/0,59, respectivamente. CONCLUSIÓN: La radiómica es un método prometedor y no invasivo para diferenciar entre WDLPS y lipomas, superando la valoración de los radiólogos. Sin embargo, se necesita la optimización y validación de esta técnica antes de su introducción en la práctica clínica diaria.

A spatio-temporal reference model of the aging brain.

Both normal aging and neurodegenerative disorders such as Alzheimer's disease (AD) cause morphological changes of the brain. It is generally difficult to distinguish these two causes of morphological change by visual inspection of magnetic resonance (MR) images. To facilitate making this distinction and thus aid the diagnosis of neurodegenerative disorders, we propose a method for developing a spatio-temporal model of morphological differences in the brain due to normal aging. The method utilizes groupwise image registration to characterize morphological variation across brain scans of people with different ages. To extract the deformations that are due to normal aging we use partial least squares regression, which yields modes of deformations highly correlated with age, and corresponding scores for each input subject. Subsequently, we determine a distribution of morphologies as a function of age by fitting smooth percentile curves to these scores. This distribution is used as a reference to which a person's morphology score can be compared. We validate our method on two different datasets, using images from both cognitively normal subjects and patients with Alzheimer disease (AD). Results show that the proposed framework extracts the expected atrophy patterns. Moreover, the morphology scores of cognitively normal subjects are on average lower than the scores of AD subjects, indicating that morphology differences between AD subjects and healthy subjects can be partly explained by accelerated aging. With our methods we are able to assess accelerated brain aging on both population and individual level. A spatio-temporal aging brain model derived from 988 T1-weighted MR brain scans from a large population imaging study (age range 45.9-91.7y, mean age 68.3y) is made publicly available at www.agingbrain.nl.

Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms.

Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10-08, ß=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10-03, ß=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.

Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group.

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

Added value of multiphase CTA imaging for thrombus perviousness assessment.

PURPOSE: Thrombus perviousness has been associated with favorable functional outcome in acute ischemic stroke (AIS) patients. Measuring thrombus perviousness on CTA may be suboptimal due to potential delay in contrast agent arrival in occluded arteries at the moment of imaging. Dynamic sequences acquired over time can potentially overcome this issue. We investigate if dynamic CTA has added value in assessing thrombus perviousness. METHODS: Prospectively collected image data of AIS patients with proven occlusion of the anterior or posterior circulation with thin-slice multi-phase CTA (MCTA) and non-contrast CT were co-registered (n = 221). Thrombus attenuation increase (TAI; a perviousness measure) was measured for the arterial, venous, and delayed phase of the MCTA and time-invariant CTAs (TiCTA). Associations with favorable clinical outcome (90-day mRS ≤ 2) were assessed using univariate and multivariable regressions and calculating areas under receiver operating curves (AUC). RESULTS: TAI determined from the arterial phase CTA was superior in the association with favorable outcome with OR = 1.21 per 10 HU increase (95%CI 1.04-1.41, AUC 0.62, p = 0.014) compared to any other phase (venous 1.14(95%CI 1.01-1.30, AUC 0.58, p = 0.033), delayed 1.046(95%CI 0.919-1.19, AUC 0.53, p = 0.50)), and TiCTA (1.15(95%CI 1.02-1.30, AUC 0.60, p = 0.022). In the multivariable model, only TAI on arterial phase was significantly associated with favorable outcome (aOR 1.59, 95%CI 1.04-2.43, p = 0.032). CONCLUSION: Association between TAI with functional outcome was optimal on arterial-phase CTA such that dynamic CTA imaging has no additional benefits in current thrombus perviousness assessment, thereby suggesting that the delay of contrast arrival at the clot is a key variable for patient functional outcome.

Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.

The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen's d=-0.14, % difference=-1.24). This effect was driven by patients with recurrent MDD (Cohen's d=-0.17, % difference=-1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen's d=-0.20, % difference=-1.85) and a trend toward smaller amygdala (Cohen's d=-0.11, % difference=-1.23) and larger lateral ventricles (Cohen's d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.

Structural and diffusion MRI measures of the hippocampus and memory performance.

Hippocampal atrophy on MRI and changes in diffusion tensor imaging (DTI) measures of the hippocampus have been reported in patients with Alzheimer's disease. We examined the association between hippocampal volumes, DTI measures of the hippocampus and memory performance in 892 non-demented persons (age ≥ 55 years) across different age groups. Hippocampal volume was segmented on 3D volumetric MRI scans. The segmentations were co-registered to mean diffusivity (MD) and fractional anisotropy (FA) maps to yield mean hippocampal MD and FA measurements. Higher MD of the hippocampus was associated with impaired verbal memory performance. In all persons ≥ 55 years, a higher MD of the hippocampus was associated with a worse memory performance. Hippocampal volumes were very weakly positively associated with delayed recall and only in persons > 65 years. FA of the hippocampus was not associated with memory performance. Follow-up studies will be needed to determine whether higher MD of hippocampus at younger ages could be an earlier marker of incident Alzheimer's disease than hippocampal volume.

Genetic risk factors for cerebral small-vessel disease in hypertensive patients from a genetically isolated population.

BACKGROUND: Asymptomatic cerebral lesions on MRI such as white matter lesions (WML), lacunes and microbleeds are commonly seen in older people. We examined the role of a series of candidate genes involved in blood pressure regulation and amyloid metabolism. MATERIALS AND METHODS: The study was embedded in a family-based cohort sampled from a Dutch genetically isolated population. We selected individuals between 55 and 75 years of age with hypertension (N=129). Volumes of WML and presence of lacunes and microbleeds were assessed with MRI. We studied three genes involved in blood pressure regulation (angiotensin, angiotensin II type 1 receptor, α-adducin) and two genes involved in the amyloid pathway (apolipoprotein E (APOE) and sortilin-related receptor gene (SORL1)). RESULTS: All participants had WML (median volume, 3.1 ml; interquartile range, 1.5-6.5 ml); lacunar infarcts were present in 15.5% and microbleeds in 23.3%. Homozygosity for the APOE ε4 allele was associated with lacunes (OR, 4.8; 95% CI, 1.2 to 19.3). Individuals carrying two copies of the variant allele of four single nucleotide polymorphism (SNPs) located at the 3'-end of SORL1 (rs1699102, rs3824968, rs2282649, rs1010159) had significantly more often microbleeds (highest OR, 6.87; 95% CI, 1.78 to 26.44). CONCLUSION: The association of SORL1 with microbleeds suggests that the amyloid cascade is involved in the aetiology of microbleeds in populations with hypertension.

Calcium scoring in unenhanced and enhanced CT data of the aorta-iliacal arteries: impact of image acquisition, reconstruction, and analysis parameter settings.

BACKGROUND: Several studies have been published on the matter of abdominal aortic and iliac calcifications and the association to clinical entities such as diabetes mellitus and renal failure. However, comparing of these studies is questionable since quantification methods for atherosclerosis differ. PURPOSE: To evaluate the effect of image acquisition settings, reconstruction parameters, and analysis methods on calcium quantification in the abdominal aorta. MATERIAL AND METHODS: Calcium scores were retrospectively determined on standardized abdominal CT scans of 15 patients. Two researchers obtained calcium scores with 10 different lower thresholds (LT) (130, 145, 160, 175, 200, 300, 400, 500, 600, 1000) in CT scans with and without contrast enhancement, with slice thicknesses (ST) varying between 2.0-5.0 mm for the non-contrast-enhanced series and between 1.0-5.0 mm for the contrast-enhanced series. In addition calcium scores obtained with two convolution kernels (B10f, B20f) were compared. Inter-observer variability was calculated. RESULTS: Calcium scoring at higher STs is overestimated compared to smaller STs and this effect was more pronounced with increasing calcium loads. Concerning the convolution kernel, scores obtained with kernel B10f were overestimated compared to kernel B20f. Increase of LT resulted in a decrease of the calcium score and scoring in contrast-enhanced series resulted in higher scores compared to non-contrast-enhanced series. These effects are more apparent in patients with higher calcium loads. Calcium scoring reproducibility with the reference standard is limited for the aorta-iliac trajectory, whereas scoring with the remaining settings is reproducible. CONCLUSION: Scores obtained with different settings cannot be compared. The inter-observer reproducibility was limited using the reference standard and practical difficulties were substantial. Scoring with higher LT, ST, and contrast enhancement is faster and has less practical difficulties.

Recurrent inference machines as inverse problem solvers for MR relaxometry.

In this paper, we propose the use of Recurrent Inference Machines (RIMs) to perform T1 and T2 mapping. The RIM is a neural network framework that learns an iterative inference process based on the signal model, similar to conventional statistical methods for quantitative MRI (QMRI), such as the Maximum Likelihood Estimator (MLE). This framework combines the advantages of both data-driven and model-based methods, and, we hypothesize, is a promising tool for QMRI. Previously, RIMs were used to solve linear inverse reconstruction problems. Here, we show that they can also be used to optimize non-linear problems and estimate relaxometry maps with high precision and accuracy. The developed RIM framework is evaluated in terms of accuracy and precision and compared to an MLE method and an implementation of the Residual Neural Network (ResNet). The results show that the RIM improves the quality of estimates compared to the other techniques in Monte Carlo experiments with simulated data, test-retest analysis of a system phantom, and in-vivo scans. Additionally, inference with the RIM is 150 times faster than the MLE, and robustness to (slight) variations of scanning parameters is demonstrated. Hence, the RIM is a promising and flexible method for QMRI. Coupled with an open-source training data generation tool, it presents a compelling alternative to previous methods.

Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis.

For the segmentation of magnetic resonance brain images into anatomical regions, numerous fully automated methods have been proposed and compared to reference segmentations obtained manually. However, systematic differences might exist between the resulting segmentations, depending on the segmentation method and underlying brain atlas. This potentially results in sensitivity differences to disease and can further complicate the comparison of individual patients to normative data. In this study, we aim to answer two research questions: 1) to what extent are methods interchangeable, as long as the same method is being used for computing normative volume distributions and patient-specific volumes? and 2) can different methods be used for computing normative volume distributions and assessing patient-specific volumes? To answer these questions, we compared volumes of six brain regions calculated by five state-of-the-art segmentation methods: Erasmus MC (EMC), FreeSurfer (FS), geodesic information flows (GIF), multi-atlas label propagation with expectation-maximization (MALP-EM), and model-based brain segmentation (MBS). We applied the methods on 988 non-demented (ND) subjects and computed the correlation (PCC-v) and absolute agreement (ICC-v) on the volumes. For most regions, the PCC-v was good ( > 0.75 ), indicating that volume differences between methods in ND subjects are mainly due to systematic differences. The ICC-v was generally lower, especially for the smaller regions, indicating that it is essential that the same method is used to generate normative and patient data. To evaluate the impact on single-subject analysis, we also applied the methods to 42 patients with Alzheimer's disease (AD). In the case where the normative distributions and the patient-specific volumes were calculated by the same method, the patient's distance to the normative distribution was assessed with the z-score. We determined the diagnostic value of this z-score, which showed to be consistent across methods. The absolute agreement on the AD patients' z-scores was high for regions of thalamus and putamen. This is encouraging as it indicates that the studied methods are interchangeable for these regions. For regions such as the hippocampus, amygdala, caudate nucleus and accumbens, and globus pallidus, not all method combinations showed a high ICC-z. Whether two methods are indeed interchangeable should be confirmed for the specific application and dataset of interest.

Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study.

PURPOSE: Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. METHODS: A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patient's CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. RESULTS: The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94 +/- 1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26 +/- 1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. CONCLUSIONS: A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/ multivendor data sets.

Orientation Prior and Consistent Model Selection Increase Sensitivity of Tract-Based Spatial Statistics in Crossing-Fiber Regions.

The goal of this paper is to increase the statistical power of crossing-fiber statistics in voxelwise analyses of diffusion-weighted magnetic resonance imaging (DW-MRI) data. In the proposed framework, a fiber orientation atlas and a model complexity atlas were used to fit the ball-and-sticks model to diffusion-weighted images of subjects in a prospective population-based cohort study. Reproducibility and sensitivity of the partial volume fractions in the ball-and-sticks model were analyzed using TBSS (tract-based spatial statistics) and compared to a reference framework. The reproducibility was investigated on two scans of 30 subjects acquired with an interval of approximately three weeks by studying the intraclass correlation coefficient (ICC). The sensitivity to true biological effects was evaluated by studying the regression with age on 500 subjects from 65 to 90 years old. Compared to the reference framework, the ICC improved significantly when using the proposed framework. Higher t-statistics indicated that regression coefficients with age could be determined more precisely with the proposed framework and more voxels correlated significantly with age. The application of a fiber orientation atlas and a model complexity atlas can significantly improve the reproducibility and sensitivity of crossing-fiber statistics in TBSS.

Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach.

PURPOSE: The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time. METHODS: A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed. RESULTS: The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel center-lines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images. CONCLUSIONS: The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research.

White matter atrophy and lesion formation explain the loss of structural integrity of white matter in aging.

The importance of macrostructural white matter changes, including white matter lesions and atrophy, in intact brain functioning is increasingly being recognized. Diffusion tensor imaging (DTI) enables measurement of the microstructural integrity of white matter. Loss of white matter integrity in aging has been reported, but whether this is inherent to the aging process itself or results from specific white matter pathology is unknown. In 832 persons aged 60 years and older from the population-based Rotterdam Study, we measured fractional anisotropy (FA) and directional diffusivities in normal-appearing white matter using DTI. All subjects' DTI measures were projected onto a common white matter skeleton to enable robust voxelwise comparison. With increasing age, multiple regions showed significant decreases in FA or increases in axial or radial diffusivity in normal-appearing white matter. However, nearly all of these regional changes were explained by either white matter atrophy or by white matter lesions; each of which related to changes in distinct brain regions. These results indicate that loss of white matter integrity in aging is primarily explained by atrophy and lesion formation and not by the aging process itself. Furthermore, white matter atrophy and white matter lesion formation relate to loss of integrity in distinct brain regions, indicating the two processes are pathophysiologically different.

Motion-compensated iterative cone-beam CT image reconstruction with adapted blobs as basis functions.

This paper presents a three-dimensional method to reconstruct moving objects from cone-beam X-ray projections using an iterative reconstruction algorithm and a given motion vector field. For the image representation, adapted blobs are used, which can be implemented efficiently as basis functions. Iterative reconstruction requires the calculation of line integrals (forward projections) through the image volume, which are compared with the actual measurements to update the image volume. In the existence of a divergent motion vector field, a change in the volumes of the blobs has to be taken into account in the forward and backprojections. An efficient method to calculate the line integral through the adapted blobs is proposed. It solves the problem, how to compensate for the divergence in the motion vector field on a grid of basis functions. The method is evaluated on two phantoms, which are subject to three different known motions. Moreover, a motion-compensated filtered back-projection reconstruction method is used, and the reconstructed images are compared. Using the correct motion vector field with the iterative motion-compensated reconstruction, sharp images are obtained, with a quality that is significantly better than gated reconstructions.

[The obligatory notification of pertussis is not effective for the protection of unvaccinated children]. / Meldingsplicht voor kinkhoest niet effectief om ongevaccineerde kinderen te beschermen.

OBJECTIVE: To determine the effectiveness of the obligatory notification of pertussis in the Netherlands and the measures based on this notification in the prevention of infection in unvaccinated or insufficiently vaccinated children. DESIGN: Descriptive, retrospective. METHOD: The period between the first day of the illness and the date of notification was calculated for all 9310 cases of pertussis that were notified in the Netherlands in 2004. A period of 21 days is the maximum during which appropriate measures can be taken in the family of the index patient to protect unprotected siblings at risk from infection. For the province of Groningen (n = 411 notified cases), it was also determined whether there were actually children that were not or insufficiently vaccinated in the immediate environment and whether preventive measures were necessary. RESULTS: In the Netherlands in 2004, 890 (10.7%) of all notified pertussis cases were notified within a three-week period after the first day of illness. In Groningen, this number was 30 (9.1%) and in none of these cases was there an insufficiently vaccinated child in the family. CONCLUSION: In an endemic situation with severe under-reporting, the obligatory notification of pertussis is not effective to prevent infection of insufficiently vaccinated children. Alternative vaccination strategies directed at the prevention of the spread of pertussis among insufficiently vaccinated children would probably be more effective and merit further investigation.