Brain volume in infants with metopic synostosis: Less white matter volume with an accelerated growth pattern in early life

Metopic synostosis patients are at risk for neurodevelopmental disorders despite a negligible risk of intracranial hypertension. To gain insight into the underlying pathophysiology of metopic synostosis and associated neurodevelopmental disorders, we aimed to investigate brain volumes of non-syndromic metopic synostosis patients using preoperative MRI brain scans. MRI brain scans were processed with HyperDenseNet to calculate total intracranial volume (TIV), total brain volume (TBV), total grey matter volume (TGMV), total white matter volume (TWMV) and total cerebrospinal fluid volume (TCBFV). We compared global brain volumes of patients with controls corrected for age and sex using linear regression. Lobe-specific grey matter volumes were assessed in secondary analyses. We included 45 metopic synostosis patients and 14 controls (median age at MRI 0.56 years [IQR 0.36] and 1.1 years [IQR 0.47], respectively). We found no significant differences in TIV, TBV, TGMV or TCBFV in patients compared to controls. TWMV was significantly smaller in patients (-62,233 mm3 [95% CI = -96,968; -27,498], Holm-corrected p = 0.004), and raw data show an accelerated growth pattern of white matter in metopic synostosis patients. Grey matter volume analyses per lobe indicated increased cingulate (1378 mm3 [95% CI = 402; 2355]) and temporal grey matter (4747 [95% CI = 178; 9317]) volumes in patients compared to controls. To conclude, we found smaller TWMV with an accelerated white matter growth pattern in metopic synostosis patients, similar to white matter growth patterns seen in autism. TIV, TBV, TGMV and TCBFV were comparable in patients and controls. Secondary analyses suggest larger cingulate and temporal lobe volumes. These findings suggest a generalized intrinsic brain anomaly in the pathophysiology of neurodevelopmental disorders associated with metopic synostosis.

UCSQ Method Applied on 3D Photogrammetry: Non-Invasive Objective Differentiation Between Synostotic and Positional Plagiocephaly

OBJECTIVE

Objective differentiation between unilateral coronal synostosis (UCS) and positional posterior plagiocephaly (PPP) based on 3D photogrammetry according to Utrecht Cranial Shape Quantificator (UCSQ).

DESIGN

Retrospective study.

SETTING

Primary craniofacial center.

PATIENTS, PARTICIPANTS

Thirty-two unoperated patients (17 UCS; 15 PPP) (age < 1 year).

INTERVENTIONS

Extraction of variables from sinusoid curves derived using UCSQ: asymmetry ratio forehead and occiput peak, ratio of gradient forehead and occiput peak, location forehead and occiput peak.

MAIN OUTCOME MEASURE(S)

Variables, derived using 3D photogrammetry, were analyzed for differentiation between UCS and PPP.

RESULTS

Frontal peak was shifted to the right side of the head in left-sided UCS (mean x-value 207 [192-220]), and right-sided PPP (mean x-value 210 [200-216]), and to the left in right-sided UCS (mean x-value 161 [156-166]), and left-sided PPP (mean x-value 150 [144-154]). Occipital peak was significantly shifted to the right side of the head in left-sided PPP (mean x-value 338 [336-340]) and to the left in right-sided PPP (mean x-value 23 [14-32]). Mean x-value of occipital peak was 9 (354-30) in left- and 2 (350-12) in right-sided UCS. Calculated ratio of gradient of the frontal peak is, in combination with the calculated asymmetry ratio of the frontal peak, a distinctive finding.

CONCLUSIONS

UCSQ objectively captures shape of synostotic and positional plagiocephaly using 3D photogrammetry, we therefore developed a suitable method to objectively differentiate UCS from PPP using radiation-free methods.

Diabetes and hypertension are related to amyloid-beta burden in the population-based Rotterdam Study

Higher vascular disease burden increases the likelihood of developing dementia, including Alzheimer's disease. Better understanding the association between vascular risk factors and Alzheimer's disease pathology at the predementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (Aβ) plaques in participants from the population-based Rotterdam Study. Vascular risk factors (hypertension, hypercholesterolaemia, diabetes, obesity, physical inactivity and smoking) were assessed 13 (2004-2008) and 7 years (2009-2014) prior to 18F-florbetaben PET (2018-2021) in 635 dementia-free participants. Vascular risk factors were associated with binary amyloid PET status or continuous PET readouts (standard uptake value ratios, SUVrs) using logistic and linear regression models, respectively, adjusted for age, sex, education, APOE4 risk allele count and time between vascular risk and PET assessment. Participants' mean age at time of amyloid PET was 69 years (range: 60-90), 325 (51.2%) were women and 190 (29.9%) carried at least one APOE4 risk allele. The adjusted prevalence estimates of an amyloid-positive PET status markedly increased with age [12.8% (95% CI 11.6; 14) in 60-69 years versus 35% (36; 40.8) in 80-89 years age groups] and APOE4 allele count [9.7% (8.8; 10.6) in non-carriers versus 38.4% (36; 40.8) to 60.4% (54; 66.8) in carriers of one or two risk allele(s)]. Diabetes 7 years prior to PET assessment was associated with a higher risk of a positive amyloid status [odds ratio (95% CI) = 3.68 (1.76; 7.61), P < 0.001] and higher standard uptake value ratios, indicating more severe Aβ pathology [standardized beta = 0.40 (0.17; 0.64), P = 0.001]. Hypertension was associated with higher SUVr values in APOE4 carriers (mean SUVr difference of 0.09), but not in non-carriers (mean SUVr difference 0.02; P = 0.005). In contrast, hypercholesterolaemia was related to lower SUVr values in APOE4 carriers (mean SUVr difference -0.06), but not in non-carriers (mean SUVr difference 0.02). Obesity, physical inactivity and smoking were not related to amyloid PET measures. The current findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer's disease in a general population of older non-demented adults. As these conditions respond well to lifestyle modification and drug treatment, further research should focus on the preventative effect of early risk management on the development of Alzheimer's disease neuropathology.

A Diffusion Tensor Imaging Analysis of Frontal Lobe White Matter Microstructure in Trigonocephaly Patients

BACKGROUND

Children with trigonocephaly are at risk for neurodevelopmental disorders. The aim of this study is to investigate white matter properties of the frontal lobes in young, unoperated patients with metopic synostosis as compared to healthy controls using diffusion tension imaging (DTI).

METHODS

Preoperative DTI data sets of 46 patients with trigonocephaly with a median age of 0.49 (interquartile range: 0.38) years were compared with 21 controls with a median age of 1.44 (0.98) years. White matter metrics of the tracts in the frontal lobe were calculated using FMRIB Software Library (FSL). The mean value of tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were estimated for each subject and compared to healthy controls. By linear regression, FA and MD values per tract were assessed by trigonocephaly, sex, and age.

RESULTS

The mean FA and MD values in the frontal lobe tracts of untreated trigonocephaly patients, younger than 3 years, were not significantly different in comparison to controls, where age showed to be a significant associated factor.

CONCLUSIONS

Microstructural parameters of white matter tracts of the frontal lobe of patients with trigonocephaly are comparable to those of controls aged 0-3 years.

Cerebral cortex maldevelopment in syndromic craniosynostosis

AIM

To assess the relationship of surface area of the cerebral cortex to intracranial volume (ICV) in syndromic craniosynostosis.

METHOD

Records of 140 patients (64 males, 76 females; mean age 8y 6mo [SD 5y 6mo], range 1y 2mo-24y 2mo) with syndromic craniosynostosis were reviewed to include clinical and imaging data. Two hundred and three total magnetic resonance imaging (MRI) scans were evaluated in this study (148 patients with fibroblast growth factor receptor [FGFR], 19 patients with TWIST1, and 36 controls). MRIs were processed via FreeSurfer pipeline to determine total ICV and cortical surface area (CSA). Scaling coefficients were calculated from log-transformed data via mixed regression to account for multiple measurements, sex, syndrome, and age. Educational outcomes were reported by syndrome.

RESULTS

Mean ICV was greater in patients with FGFR (1519cm³ , SD 269cm³ , p=0.016) than in patients with TWIST1 (1304cm³ , SD 145cm³ ) or controls (1405cm³ , SD 158cm³ ). CSA was related to ICV by a scaling law with an exponent of 0.68 (95% confidence interval [CI] 0.61-0.76) in patients with FGFR compared to 0.81 (95% CI 0.50-1.12) in patients with TWIST1 and 0.77 (95% CI 0.61-0.93) in controls. Lobar analysis revealed reduced scaling in the parietal (0.50, 95% CI 0.42-0.59) and occipital (0.67, 95% CI 0.54-0.80) lobes of patients with FGFR compared with controls. Modified learning environments were needed more often in patients with FGFR.

INTERPRETATION

Despite adequate ICV in FGFR-mediated craniosynostosis, CSA development is reduced, indicating maldevelopment, particularly in parietal and occipital lobes. Modified education is also more common in patients with FGFR.

New method for quantification of the relative severity and (a)symmetry of isolated metopic synostosis

Trigonocephaly is the result of premature fusion of the metopic suture and its severity can vary widely. However, there is no gold standard for quantification of the severity. This study was performed to quantify severity using the Utrecht Cranial Shape Quantifier (UCSQ) and to assess forehead symmetry. Nineteen preoperative non-syndromic trigonocephaly patients (age ≤1 year) were included for the analysis of severity and symmetry. Severity according to the UCSQ was based on the following combined variables: forehead width and relative skull elongation. The UCSQ was compared to the most established quantification methods. A high correlation was found between the UCSQ and visual score (r=0.71). Moderate to negligible correlation was found between the UCSQ and frontal angle, binocular distance, inter-ocular distance, and frontal stenosis. Additionally, correlation between the visual score and these established quantification methods was negligible. Assessment of the frontal peak (a)symmetry (ratio of right to left triangle area in the curve) showed a mean right versus left triangle area ratio of 1.4 (range 0.9-2.4). The results suggest that the UCSQ is appropriate for the quantification of severity based on the high correlation with clinical judgement. Furthermore, a larger triangle area right than left was unexpectedly found, indicating forehead asymmetry.

Quantification of Severity of Unilateral Coronal Synostosis

OBJECTIVES

Severity of unilateral coronal synostosis (UCS) can vary. Quantification is important for treatment, expectations of treatment and natural outcome, and education of the patient and parents.

DESIGN

Retrospective study.

SETTING

Primary craniofacial center.

PATIENTS, PARTICIPANTS

Twenty-three preoperative patients with unilateral coronal craniosynostosis (age < 2 years).

INTERVENTION

Utrecht Cranial Shape Quantifier (UCSQ) was used to quantify severity using the variables: asymmetry ratio of frontal peak and ratio of frontal peak gradient.

MAIN OUTCOME MEASURES(S)

The UCSQ variables were combined and related to visual score using Pearson correlation coefficient; UCSQ and visual score were additionally compared to Di Rocco classification by one-way analysis of variance or Kruskal-Wallis test. All measurements were made on computed tomography scans.

RESULTS

Good correlation between UCSQ and visual score was found (r = 0.67). No statistically significant differences were found between group means of UCSQ in the 3 categories of Di Rocco classification (F _2,20 = 0.047; P > .05). Kruskal-Wallis test showed no significant differences between group means of visual score in the 3 categories of Di Rocco classification (Kruskal-Wallis H (2) = 0.871; P > .05).

CONCLUSIONS

Using UCSQ, we can quantify UCS according to severity using characteristics, it outperforms traditional methods and captures the whole skull shape. In future research, we can apply UCSQ to 3D-photogrammetry due to the utilization of external landmarks.

Intracranial hypertension and cortical thickness in syndromic craniosynostosis

AIM

To evaluate the impact of risk factors for intracranial hypertension (ICH) on cerebral cortex thickness in syndromic craniosynostosis.

METHOD

ICH risk factors including papilloedema, hydrocephalus, obstructive sleep apnea (OSA), cerebellar tonsillar position, occipitofrontal circumference (OFC) curve deflection, age, and sex were collected from the records of patients with syndromic craniosynostosis (Apert, Crouzon, Pfeiffer, Muenke, Saethre-Chotzen syndromes) and imaging. Magnetic resonance images were analysed and exported for statistical analysis. A linear mixed model was developed to determine correlations with cerebral cortex thickness changes.

RESULTS

In total, 171 scans from 107 patients (83 males, 88 females [including repeated scans], mean age 8y 10mo, range 1y 1mo-34y, SD 5y 9mo) were evaluated. Mean cortical thickness in this cohort was 2.78mm (SD 0.17). Previous findings of papilloedema (p=0.036) and of hydrocephalus (p=0.007) were independently associated with cortical thinning. Cortical thickness did not vary significantly by sex (p=0.534), syndrome (p=0.896), OSA (p=0.464), OFC (p=0.375), or tonsillar position (p=0.682).

INTERPRETATION

Detection of papilloedema or hydrocephalus in syndromic craniosynostosis is associated with significant changes in cortical thickness, supporting the need for preventative rather than reactive treatment strategies.

WHAT THIS PAPER ADDS

Papilloedema is associated with thinning of the cerebral cortex in syndromic craniosynostosis, independently of hydrocephalus.

Introducing a new method for classifying skull shape abnormalities related to craniosynostosis

We present a novel technique for classification of skull deformities due to most common craniosynostosis. We included 5 children of every group of the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, and right- and left-sided anterior plagiocephaly) and additionally 5 controls. Our outline-based classification method is described, using the software programs OsiriX, MeVisLab, and Matlab. These programs were used to identify chosen landmarks (porion and exocanthion), create a base plane and a plane at 4 cm, segment outlines, and plot resulting graphs. We measured repeatability and reproducibility, and mean curves of groups were analyzed. All raters achieved excellent intraclass correlation scores (0.994-1.000) and interclass correlation scores (0.989-1.000) for identifying the external landmarks. Controls, scaphocephaly, trigonocephaly, and brachycephaly all have the peak of the forehead in the middle of the curve (180°). In contrary, in anterior plagiocephaly, the peak is shifted (to the left of graph in right-sided and vice versa). Additionally, controls, scaphocephaly, and trigonocephaly have a high peak of the forehead; scaphocephaly has the lowest troughs; in brachycephaly, the width/frontal peak ratio has the highest value with a low frontal peak.Conclusion: We introduced a preliminary study showing an objective and reproducible methodology using CT scans for the analysis of craniosynostosis and potential application of our method to 3D photogrammetry. What is Known: • Diagnosis of craniosynostosis is relatively simple; however, classification of craniosynostosis is difficult and current techniques are not widely applicable. What is New: • We introduce a novel technique for classification of skull deformities due to craniosynostosis, an objective and reproducible methodology using CT scans resulting in characteristic curves. The method is applicable to all 3D-surface rendering techniques. • Using external landmarks and curve analysis, specific and characteristic curves for every type of craniosynostosis related to the specific skull deformities are found.

Carotid Plaque Morphology and Ischemic Vascular Brain Disease on MRI

BACKGROUND AND PURPOSE

Vulnerable carotid plaque components are reported to increase the risk of cerebrovascular events. Yet, the relation between plaque composition and subclinical ischemic brain disease is not known. We studied, in the general population, the association between carotid atherosclerotic plaque characteristics and ischemic brain disease on MR imaging.

MATERIALS AND METHODS

From the population-based Rotterdam Study, 951 participants underwent both carotid MR imaging and brain MR imaging. The presence of intraplaque hemorrhage, lipid core, and calcification and measures of plaque size was assessed in both carotid arteries. The presence of plaque characteristics in relation to lacunar and cortical infarcts and white matter lesion volume was investigated and adjusted for cardiovascular risk factors. Stratified analyses were conducted to explore effect modification by sex. Additional analyses were conducted per carotid artery in relation to vascular brain disease in the ipsilateral hemisphere.

RESULTS

Carotid intraplaque hemorrhage was significantly associated with the presence of cortical infarcts (OR, 1.9; 95% confidence interval, 1.1-3.3). None of the plaque characteristics were related to the presence of lacunar infarcts. Calcification was the only characteristic that was associated with higher white matter lesion volume. There was no significant interaction by sex.

CONCLUSIONS

The presence of carotid intraplaque hemorrhage on MR imaging is independently associated with MR imaging-defined cortical infarcts, but not with lacunar infarcts. Plaque calcification, but not vulnerable plaque components, is related to white matter lesion volume.

The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

Objectives

Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer’s disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI).

Method

MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus.

Results

We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors.

Conclusions

Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI.

Key Points

• PCC functioning during episodic memory relates to hippocampal functioning in MCI.

• PCC functioning during episodic memory does not relate to hippocampal structure in MCI.

• Functional network changes are an important predictor of PCC functioning in MCI.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-017-4768-1) contains supplementary material, which is available to authorized users.

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.

Small cortical infarcts: prevalence, determinants, and cognitive correlates in the general population

BACKGROUND

Cortical brain infarcts are defined as infarcts involving cortical gray matter, but may differ considerably in size. It is unknown whether small cortical infarcts have a similar clinical phenotype as larger counterparts. We investigated prevalence, determinants, and cognitive correlates of small cortical infarcts in the general population and compared these with large cortical infarcts and lacunar infarcts.

METHODS

Four thousand nine hundred five nondemented individuals (age 63·95 ± 10·99) from a population-based study were included. Infarcts were rated on magnetic resonance imaging and participants were classified according to mean infarct diameter into small (≤15 mm in largest diameter) or large (>15 mm) cortical infarcts, lacunar infarcts, or a combination of subtypes. Spatial distribution maps were created for manually labeled small and large infarcts. Participants underwent cognitive testing. Analyses were performed using multinomial regression and analysis of covariance.

RESULTS

Three hundred eighty-one (7·8%) persons had any infarct on magnetic resonance imaging, among whom 54 with small (1·1%) and 77 (1·6%) with large cortical infarcts. Small cortical infarcts were mainly localized in external watershed areas, whereas large cortical infarcts were localized primarily in large arterial territories. Age (odds ratio = 1·06; 95% confidence interval = 1·02, 1·09), male gender (1·98; 1·01, 3·92), and smoking (2·55; 1·06, 6·14) were determinants of small cortical infarcts. Participants with these infarcts had worse scores in delayed memory, processing speed, and attention tests than persons without infarcts, even after adjustment for cardiovascular risk factors.

CONCLUSIONS

In the elderly, small cortical infarcts appear as frequent as large infarcts but in different localization. Our results suggest that small cortical infarcts share cardiovascular risk factors and cognitive correlates with large cortical, but also with lacunar infarcts.

TMEM106B influences volume of left-sided temporal lobe and interhemispheric structures in the general population

BACKGROUND

Frontotemporal lobar degeneration is a neurodegenerative disease characterized by brain atrophy of the frontal and anterior temporal lobes. The associated frontotemporal dementia syndromes are clinically heterogeneous, and the pattern of affected cortical regions varies among subtypes. The TMEM106B rs1990622 polymorphism is associated with frontotemporal lobar degeneration, but little is known about how it affects the brain.

METHODS

We investigated the rs1990622 polymorphism in relation to regional brain volumes to identify potential structures through which TMEM106B confers risk for frontotemporal lobar degeneration. In 4413 nondemented and stroke-free participants from the population-based Rotterdam Study, 150 cortical brain structures and 6 commissural regions were segmented from magnetic resonance imaging.

RESULTS

A distinct pattern of association was found between rs1990622 and gray matter volume of left-sided temporal brain regions important for language processing, including the superior temporal gyrus (β=-88.8 μL per risk allele, p=7.64×10(-5)), which contains Wernicke's area. The risk allele was also associated with a smaller anterior commissure cross-sectional area (β=-.167 mm2 per risk allele, p=4.90×10(-5)) and posterior part of the corpus callosum (β=-15.3 μL per risk allele, p=1.23×10(-5)), both of which contain temporal lobe commissural tracts.

CONCLUSIONS

The asymmetric, predominantly left-sided involvement suggests an effect of TMEM106B on functions lateralized to the dominant hemisphere, such as language. These results show that, in nondemented persons, TMEM106B influences the volume of temporal brain regions that are important for language processing.

Apolipoprotein E genotype influences spatial distribution of cerebral microbleeds

In cerebral amyloid angiopathy patients, microbleeds often cluster, mostly occipital, and are associated with apolipoprotein E (APOE) genotype. Microbleeds also frequently occur in the asymptomatic, general population. In this population, we investigated spatial distribution of microbleeds and whether this is influenced by APOE genotype. In 292 persons with microbleeds, we labeled microbleeds on baseline and follow-up magnetic resonance images. We calculated distance between incident and prevalent microbleeds within and between persons and performed lobar segmentation on the magnetic resonance images. Subsequently, we investigated proximity and lobar distribution in strata of APOE genotype. Microbleeds occurred closer within persons than between persons (-42.2 mm, 95% confidence interval, -44.6 to -39.9; p < 0.001). Microbleeds within APOE ε2 and ε4 carriers occurred closer than those in persons with ε3ε3 genotype (-11.9 mm, 95% confidence interval, -24.4 to 0.6; p = 0.06). Persons with ε2 and ε4 alleles had a larger proportion of microbleeds in the occipital lobe than persons with ε3ε3 genotype. Similar to cerebral amyloid angiopathy patients, microbleeds in the general population cluster and the distribution is affected by APOE genotype.

Brain cortical thickness in the general elderly population: the Rotterdam Scan Study

Cortical thickness is considered a potentially relevant marker for neurodegenerative diseases. However, the relationship of demographic and vascular risk factors with cortical thickness remains unclear. In a population-based sample of 1022 non-demented elderly persons (mean age 68.4±7.3 years), we examined aging effects on global and lobar cortical thickness and the relationship with demographic variables and cardiovascular risk factors. We used a validated model-based approach to calculate mean cortical thickness (μm) in brain MR-images. We found that women had a significant thicker cortex than men (p<0.01). Further, with increasing age, cortical thickness decreased (approximately 0.2% per year), with the largest age effects for the occipital and temporal lobes, and the decrease in the frontal lobe being more apparent in men than in women (p-interaction<0.001). Additionally, higher education, higher diastolic blood pressure and larger intra-cranial volume were related to a larger cortical thickness, whilst diabetes mellitus and higher HDL cholesterol levels were related to a thinner cortex.

The relation of uric acid to brain atrophy and cognition: the Rotterdam Scan Study

BACKGROUND

Uric acid has been associated with focal vascular brain disease. However, it is unknown whether uric acid also relates to global brain changes such as brain atrophy. We therefore studied the relation of uric acid to brain atrophy and whether this is accompanied by worse cognitive function.

METHODS

In 814 persons of the population-based Rotterdam Study (mean age 62.0 years), we studied the relation of uric acid levels to brain tissue atrophy and cognition using linear regression models adjusted for age, sex and putative confounders. Brain atrophy was assessed using automated processing of magnetic resonance imaging. Cognition was assessed using a validated neuropsychological test battery and we computed compound scores of cognitive domains.

RESULTS

Higher uric acid levels were associated with white matter atrophy [difference in Z-score of white matter volume per standard deviation increase in uric acid: -0.07 (95% CI: -0.12; -0.01)], but not with gray matter atrophy. This was particularly marked when comparing hyperuricemic to normouricemic persons [Z-score difference: -0.27 (-0.43; -0.11)]. Worse cognition was primarily found in persons with hyperuricemia [-0.28 (-0.48; -0.08)].

CONCLUSIONS

Hyperuricemia is related to white matter atrophy and worse cognition.

Atherosclerotic calcification relates to cognitive function and to brain changes on magnetic resonance imaging

BACKGROUND

Increasing evidence suggests a role of atherosclerosis in the pathogenesis of cognitive impairment and dementia. Calcification volume measured with computed tomography (CT) is a valid marker of atherosclerosis. This study investigates associations of atherosclerosis (measured using CT) at four locations with cognition and brain changes on magnetic resonance imaging (MRI).

METHODS

To quantify calcification volume, 2414 nondemented people from the Rotterdam Study underwent CT of the coronary arteries, aortic arch, extracranial carotid arteries, and intracranial carotid arteries. To assess global cognition and performance on memory, executive function, information processing speed, and motor speed, they also underwent neuropsychological tests. In a random subgroup of 844 participants, brain MRI was performed. Automated segmentation and quantification of brain MRI scans yielded brain tissue volumes in milliliters. Diffusion tensor imaging was used to measure the microstructural integrity of the white matter. Relationships of atherosclerotic calcification with cognition, brain tissue volumes, and diffusion tensor imaging measures were assessed with linear regression models and adjusted for relevant confounders.

RESULTS

With larger calcification volumes, lower cognitive scores were observed. When calcification volumes were larger, total brain volumes were also smaller. Specifically, larger coronary artery calcification volumes related to smaller gray matter volumes, and extracranial and intracranial carotid calcification volumes related to smaller white matter volumes. Larger calcification volume in all vessel beds was accompanied by worse microstructural integrity of the white matter.

CONCLUSIONS

Larger calcification volume is associated with worse cognitive performance. It also relates to smaller brain tissue volumes and worse white matter microstructural integrity, revealing possible mechanisms through which atherosclerosis may lead to poorer cognition.

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.

Genome-wide association studies of cerebral white matter lesion burden: the CHARGE consortium

OBJECTIVE

White matter hyperintensities (WMHs) detectable by magnetic resonance imaging are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMHs are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified.

METHODS

We performed a meta-analysis of genome-wide association studies (GWASs) for WMH burden in 9,361 stroke-free individuals of European descent from 7 community-based cohorts. Significant findings were tested for replication in 3,024 individuals from 2 additional cohorts.

RESULTS

We identified 6 novel risk-associated single nucleotide polymorphisms (SNPs) in 1 locus on chromosome 17q25 encompassing 6 known genes including WBP2, TRIM65, TRIM47, MRPL38, FBF1, and ACOX1. The most significant association was for rs3744028 (p(discovery) = 4.0 × 10(-9) ; p(replication) = 1.3 × 10(-7) ; p(combined) = 4.0 × 10(-15) ). Other SNPs in this region also reaching genome-wide significance were rs9894383 (p = 5.3 × 10(-9) ), rs11869977 (p = 5.7 × 10(-9) ), rs936393 (p = 6.8 × 10(-9) ), rs3744017 (p = 7.3 × 10(-9) ), and rs1055129 (p = 4.1 × 10(-8) ). Variant alleles at these loci conferred a small increase in WMH burden (4-8% of the overall mean WMH burden in the sample).

INTERPRETATION

This large GWAS of WMH burden in community-based cohorts of individuals of European descent identifies a novel locus on chromosome 17. Further characterization of this locus may provide novel insights into the pathogenesis of cerebral WMH.

Statistical analysis of minimum cost path based structural brain connectivity

Diffusion MRI can be used to study the structural connectivity within the brain. Brain connectivity is often represented by a binary network whose topology can be studied using graph theory. We present a framework for the construction of weighted structural brain networks, containing information about connectivity, which can be effectively analyzed using statistical methods. Network nodes are defined by segmentation of subcortical structures and by cortical parcellation. Connectivity is established using a minimum cost path (mcp) method with an anisotropic local cost function based directly on diffusion weighted images. We refer to this framework as Statistical Analysis of Minimum cost path based Structural Connectivity (SAMSCo) and the weighted structural connectivity networks as mcp-networks. In a proof of principle study we investigated the information contained in mcp-networks by predicting subject age based on the mcp-networks of a group of 974 middle-aged and elderly subjects. Using SAMSCo, age was predicted with an average error of 3.7 years. This was significantly better than predictions based on fractional anisotropy or mean diffusivity averaged over the whole white matter or over the corpus callosum, which showed average prediction errors of at least 4.8 years. Additionally, we classified subjects, based on the mcp-networks, into groups with low and high white matter lesion load, while correcting for age, sex and white matter atrophy. The SAMSCo classification outperformed the classification based on the diffusion measures with a classification accuracy of 76.0% versus 63.2%. We also performed a classification in groups with mild and severe atrophy, correcting for age, sex and white matter lesion load. In this case, mcp-networks and diffusion measures yielded similar classification accuracies of 68.3% and 67.8% respectively. The SAMSCo prediction and classification experiments indicate that the mcp-networks contain information regarding age, white matter lesion load and white matter atrophy, and that in case of age and white matter lesion load the mcp-network based models outperformed the predictions based on diffusion measures.

Statistical analysis of structural brain connectivity

We present a framework for statistical analysis in large cohorts of structural brain connectivity, derived from diffusion weighted MRI. A brain network is defined between subcortical gray matter structures and a cortical parcellation obtained with FreeSurfer. Connectivity is established through minimum cost paths with an anisotropic local cost function and is quantified per connection. The connectivity network potentially encodes important information about brain structure, and can be analyzed using multivariate regression methods. The proposed framework can be used to study the relation between connectivity and e.g. brain function or neurodegenerative disease. As a proof of principle, we perform principal component regression in order to predict age and gender, based on the connectivity networks of 979 middle-aged and elderly subjects, in a 10-fold cross-validation. The results are compared to predictions based on fractional anisotropy and mean diffusivity averaged over the white matter and over the corpus callosum. Additionally, the predictions are performed based on the best predicting connection in the network. Principal component regression outperformed all other prediction models, demonstrating the age and gender information encoded in the connectivity network.

White matter microstructural integrity and cognitive function in a general elderly population

CONTEXT

The role of macrostructural white matter changes, such as atrophy and white matter lesions, in cognitive decline is increasingly being recognized. However, in the elderly population, these macrostructural changes do not account for all variability in cognition. Measures reflecting white matter microstructural integrity may provide additional information to investigate the relation between white matter changes and cognition.

OBJECTIVE

To study the relation between white matter integrity and cognition in the general elderly population, using diffusion tensor imaging and taking into account macrostructural white matter changes.

DESIGN

Cross-sectional population-based study.

SETTING

A general community in the Netherlands.

PARTICIPANTS

A population-based sample of 860 persons, older than 60 years, free of dementia. We performed multisequence magnetic resonance imaging, which included diffusion tensor imaging, and extensive neuropsychological testing. Fractional anisotropy, mean diffusivity, and directional diffusivities were measured globally in white matter lesions and normal-appearing white matter.

MAIN OUTCOME MEASURES

Performance on neuropsychological tests in the following cognitive domains: memory, executive function, information processing speed, global cognition, and motor speed.

RESULTS

Regardless of macrostructural white matter changes, a higher mean diffusivity or higher axial and radial diffusivities within white matter lesions or normal-appearing white matter were related to worse performance on tasks assessing information processing speed and global cognition. In addition, diffusivity within white matter lesions related to memory, while in normal-appearing white matter, it furthermore related to executive function. Lower mean fractional anisotropy in white matter lesions or normal-appearing white matter related to worse information processing speed and motor speed.

CONCLUSIONS

Microstructural integrity of both white matter lesions and normal-appearing white matter is associated with cognitive function, regardless of white matter atrophy and white matter lesion volume. This suggests that measuring white matter integrity has added value beyond macrostructural assessment of white matter changes to study the relation between white matter and cognition.

Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences: Rotterdam Scan study

BACKGROUND AND PURPOSE

Cerebral white matter lesions and lacunar infarcts are small vessel disease-related lesions, which are associated with cognitive decline and dementia. We aimed to assess the relationship between risk factors, effect modifiers, and progression of these lesions. Furthermore, we studied the cognitive consequences of lesion progression.

METHODS

Six hundred sixty-eight people, aged 60 to 90 years, underwent repeated MRI scanning and neuropsychological testing within 3-year follow-up. We rated incident lacunar infarcts and change in periventricular and subcortical white matter lesion severity with a semiquantitative scale. We assessed the relationships between age, sex, baseline lesion load, risk factors, lesion progression, and change in cognitive function by multivariate regression analyses and additional stratified analyses.

RESULTS

Baseline lesion load, higher age, high blood pressure, and current smoking were independently associated with progression of white matter lesions. Women had more marked progression of subcortical white matter lesions and incident lacunar infarcts compared with men. Carotid atherosclerosis was associated with incident lacunar infarcts. Higher blood pressure did not contribute to lesion progression in people with already severe lesions at baseline nor in the very old. Lesion progression was associated with a paralleled decline in general cognitive function and in particular with a decreased information processing speed.

CONCLUSIONS

Higher age, female sex, cigarette smoking, elevated blood pressure, and baseline lesion load were associated with small vessel disease progression. Age and baseline lesion load influenced the risk relations with blood pressure. Progression of small vessel disease was related to a paralleled decline in cognitive function.

Brain tissue volumes in the general elderly population

We investigated how volumes of cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) varied with age, sex, small vessel disease and cardiovascular risk factors in the Rotterdam Scan Study. Participants (n=490; 60-90 years) were non-demented and 51.0% had hypertension, 4.9% had diabetes mellitus, 17.8% were current smoker and 54.0% were former smoker. We segmented brain MR-images into GM, normal WM, white matter lesion (WML) and CSF. Brain infarcts were rated visually. Volumes were expressed as percentage of intra-cranial volume. With increasing age, volumes of total brain, normal WM and total WM decreased; that of GM remained unchanged; and that of WML increased, in both men and women. Excluding persons with infarcts did not alter these results. Persons with larger load of small vessel disease had smaller brain volume, especially normal WM volume. Diastolic blood pressure, diabetes mellitus and current smoking were also related to smaller brain volume. In the elderly, higher age, small vessel disease and cardiovascular risk factors are associated with smaller brain volume, especially WM volume.

Brain tissue volumes in relation to cognitive function and risk of dementia

We investigated in a population-based cohort study the association of global and lobar brain tissue volumes with specific cognitive domains and risk of dementia. Participants (n=490; 60-90 years) were non-demented at baseline (1995-1996). From baseline brain MRI-scans we obtained global and lobar volumes of CSF, GM, normal WM, white matter lesions and hippocampus. We performed neuropsychological testing at baseline to assess information processing speed, executive function, memory function and global cognitive function. Participants were followed for incident dementia until January 1, 2005. Larger volumes of CSF and WML were associated with worse performance on all neuropsychological tests, and an increased risk of dementia. Smaller WM volume was related to poorer information processing speed and executive function. In contrast, smaller GM volume was associated with worse memory function and increased risk of dementia. When investigating lobar GM volumes, we found that hippocampal volume and temporal GM volume were most strongly associated with risk of dementia, even in persons without objective and subjective cognitive deficits at baseline, followed by frontal and parietal GM volumes.

Total cerebral blood flow and total brain perfusion in the general population: the Rotterdam Scan Study

Reduced cerebral perfusion may contribute to the development of cerebrovascular and neurodegenerative diseases. Little is known on cerebral perfusion in the general population, as most measurement techniques are too invasive for application in large groups of healthy individuals. Total cerebral blood flow (tCBF) can be noninvasively measured by magnetic resonance imaging (MRI) but is highly correlated with brain volume. We calculated total brain perfusion by dividing tCBF by brain volume, and we investigated determinants of total brain perfusion in comparison with tCBF. Secondly, we studied whether persons with a low tCBF or low total brain perfusion have a larger volume of white matter lesions (WML). This study is based on 892 persons aged 60 to 91 years from the Rotterdam Study, a population-based cohort study. We performed two-dimensional (2D) phase-contrast MRI for tCBF measurement. Brain volume and WML volume were quantitatively assessed. Cardiovascular determinants were assessed by interview and physical examination. We assessed associations between cardiovascular determinants and flow measures with linear regression models, adjusted for age and sex. Associations between tCBF or total brain perfusion and WML volume were assessed using general linear models. We found that determinants of tCBF and total brain perfusion differed largely due to the large influence of brain volume on tCBF values. Persons with low total brain perfusion had a significantly larger WML volume compared with those with high total brain perfusion. Prospective studies are required to unravel whether hypoperfusion contributes to WML formation or that tissue damage, manifested by WML, leads to brain hypoperfusion.

Brain tissue volumes and small vessel disease in relation to the risk of mortality

Brain atrophy and small vessel disease increase the risk of dementia and stroke. In a population-based cohort study (n=490; 60-90 years) we investigated how volumetric measures of atrophy and small vessel disease were related to mortality and whether this was independent of incident dementia or stroke. Brain volume and hippocampal volume were considered as measures of atrophy, whereas white matter lesions (WML) and lacunar infarcts reflected small vessel disease. We first investigated all-cause mortality in the whole cohort. In subsequent analyses we censored persons at incident dementia or incident stroke. Finally, we separately investigated cardiovascular mortality. The average follow-up was 8.4 years, during which 191 persons died. Brain atrophy and hippocampal atrophy, as well as WML increased the risk of death. The risks associated with hippocampal atrophy attenuated when censoring persons at incident dementia, but not at incident stroke. Censoring at either incident dementia or stroke did not change the risk associated with brain atrophy and WML. Moreover, WML were particularly associated with cardiovascular mortality.

Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification

Conventional k-Nearest-Neighbor (kNN) classification, which has been successfully applied to classify brain tissue in MR data, requires training on manually labeled subjects. This manual labeling is a laborious and time-consuming procedure. In this work, a new fully automated brain tissue classification procedure is presented, in which kNN training is automated. This is achieved by non-rigidly registering the MR data with a tissue probability atlas to automatically select training samples, followed by a post-processing step to keep the most reliable samples. The accuracy of the new method was compared to rigid registration-based training and to conventional kNN-based segmentation using training on manually labeled subjects for segmenting gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) in 12 data sets. Furthermore, for all classification methods, the performance was assessed when varying the free parameters. Finally, the robustness of the fully automated procedure was evaluated on 59 subjects. The automated training method using non-rigid registration with a tissue probability atlas was significantly more accurate than rigid registration. For both automated training using non-rigid registration and for the manually trained kNN classifier, the difference with the manual labeling by observers was not significantly larger than inter-observer variability for all tissue types. From the robustness study, it was clear that, given an appropriate brain atlas and optimal parameters, our new fully automated, non-rigid registration-based method gives accurate and robust segmentation results. A similarity index was used for comparison with manually trained kNN. The similarity indices were 0.93, 0.92 and 0.92, for CSF, GM and WM, respectively. It can be concluded that our fully automated method using non-rigid registration may replace manual segmentation, and thus that automated brain tissue segmentation without laborious manual training is feasible.

Evaluation of an improved technique for automated center lumen line definition in cardiovascular image data

The aim of the study was to evaluate a new method for automated definition of a center lumen line in vessels in cardiovascular image data. This method, called VAMPIRE, is based on improved detection of vessel-like structures. A multiobserver evaluation study was conducted involving 40 tracings in clinical CTA data of carotid arteries to compare VAMPIRE with an established technique. This comparison showed that VAMPIRE yields considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels, and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated definition of center lumen lines in vessels in cardiovascular image data.

C-Reactive Protein and Cerebral Small-Vessel Disease

Background— Inflammatory processes are involved in the development and consequences of atherosclerosis. Whether these processes are also involved in cerebral small-vessel disease is unknown. Cerebral white matter lesions and lacunar brain infarcts are caused by small-vessel disease and are commonly observed on MRI scans in elderly people. These lesions are associated with an increased risk of stroke and dementia. We assessed whether higher C-reactive protein (CRP) levels were related to white matter lesion and lacunar infarcts.

Methods and Results— We based our study on 1033 participants of the population-based Rotterdam Scan Study for whom complete data on CRP levels were available and who underwent brain MRI scanning. Subjects were 60 to 90 years of age and free of dementia at baseline. Six hundred thirty-six subjects had a second MRI scan on average 3.3 years later. We used multivariate regression models to assess the associations between CRP levels and markers of small-vessel disease. Higher CRP levels were associated with presence and progression of white matter lesions, particularly with marked lesion progression (ORs for highest versus lowest quartile of CRP 3.1 [95% CI 1.3 to 7.2] and 2.5 [95% CI 1.1 to 5.6] for periventricular and subcortical white matter lesion progression, respectively). These associations persisted after adjustment for cardiovascular risk factors and carotid atherosclerosis. Persons with higher CRP levels tended to have more prevalent and incident lacunar infarcts.

Conclusions— Inflammatory processes may be involved in the pathogenesis of cerebral small-vessel disease, in particular, the development of white matter lesions.

Inter-frame motion correction for MR thermometry

Noninvasive temperature measurement is feasible with MRI to monitor changes in thermal therapy. Phase shift based MR thermometry gives an estimate of the relative temperature variation between thermal and baseline images. This technique is limited, however, when applied on targets under inter-frame motion. Simple image registration and subtraction are not adequate to recover the temperature properly since the phase shift due to temperature changes is corrupted by an unwanted phase shift. In this work, the unwanted phase shift is predicted from the raw registered phase shift map itself. To estimate the unwanted phase shift, a thin plate smoothing spline is fitted to the values outside the heated region. The spline value in the heated area serves as an estimate for the offset. The estimation result is applied to correct errors in the temperature maps of an ex-vivo experiment.

Measuring progression of cerebral white matter lesions on MRI

OBJECTIVE

To evaluate the concordance of a volumetric method for measuring white matter lesion (WML) change with visual rating scales.

METHODS

The authors selected a stratified sample of 20 elderly people (mean age 72 years, range 61 to 88 years) with an MRI examination at baseline and at 3-year follow-up from the community-based Rotterdam Scan Study (RSS). Four raters assessed WML change with four different visual rating scales: the Fazekas scale, the Scheltens scale, the RSS scale, and a new visual rating scale that was designed to measure change in WML. The authors assessed concordance with a volumetric method with scatter plots and correlations, and interobserver agreement with intraclass correlation coefficients.

RESULTS

For assessment of change in WML, the Fazekas, Scheltens, and periventricular part of the RSS scale showed little correlation with volumetrics, and low interobserver agreement. The authors' new WML change scale and the subcortical part of the RSS scale showed good correlation with volumetrics. After additional training, the new WML change scale showed good interobserver agreement for measuring WML change.

CONCLUSIONS

Commonly used visual rating scales are not well suited for measuring change in white matter lesion severity. The authors' new white matter lesion change scale is more accurate and precise, and may be of use in studies focusing on progression of white matter lesions.

Model-based Roentgen stereophotogrammetry of orthopaedic implants

Attaching tantalum markers to prostheses for Roentgen stereophotogrammetry (RSA) may be difficult and is sometimes even impossible. In this study, a model-based RSA method that avoids the attachment of markers to prostheses is presented and validated. This model-based RSA method uses a triangulated surface model of the implant. A projected contour of this model is calculated and this calculated model contour is matched onto the detected contour of the actual implant in the RSA radiograph. The difference between the two contours is minimized by variation of the position and orientation of the model. When a minimal difference between the contours is found, an optimal position and orientation of the model has been obtained. The method was validated by means of a phantom experiment. Three prosthesis components were used in this experiment: the femoral and tibial component of an Interax total knee prosthesis (Stryker Howmedica Osteonics Corp., Rutherfort, USA) and the femoral component of a Profix total knee prosthesis (Smith & Nephew, Memphis, USA). For the prosthesis components used in this study, the accuracy of the model-based method is lower than the accuracy of traditional RSA. For the Interax femoral and tibial components, significant dimensional tolerances were found that were probably caused by the casting process and manual polishing of the components surfaces. The largest standard deviation for any translation was 0.19mm and for any rotation it was 0.52 degrees. For the Profix femoral component that had no large dimensional tolerances, the largest standard deviation for any translation was 0.22mm and for any rotation it was 0.22 degrees. From this study we may conclude that the accuracy of the current model-based RSA method is sensitive to dimensional tolerances of the implant. Research is now being conducted to make model-based RSA less sensitive to dimensional tolerances and thereby improving its accuracy.

Global estimation of myelination in the developing brain on the basis of magnetization transfer imaging: a preliminary study

BACKGROUND AND PURPOSE

In the developing brain, myelination occurs in an orderly and predetermined sequence. The aim of this study was to determine whether such changes can be tracked using volumetric magnetization transfer imaging.

METHODS

Three-dimensional magnetization transfer imaging was performed in 50 children (age range, 0.6-190 months) with no evidence of developmental delay or structural abnormalities. Volumetric magnetization transfer ratio (MTR) parameters generated of the whole brain were mean MTR and height and location of the MTR histogram peak. Relationships between volumetric MTR parameters and age were assessed using nonlinear regression analysis.

RESULTS

With age, all volumetric MTR parameters changed exponentially in a way that was best expressed by the function y = a + b.exp(-x/c) (P < .0001). The peak height of the MTR histogram was the parameter that changed most predictably and that continued to change for the longest period of time.

CONCLUSION

With this preliminary study, we show that by using volumetric MTR analysis, it is possible to monitor changes in the developing brain, presumably the myelination progress. This method has a potential role for detecting myelination disorders in the pediatric population, for studying the natural history of these diseases, and for monitoring the effects of treatment.

Digital automated RSA compared to manually operated RSA

The accuracy of digital Roentgen stereophotogrammetric analysis (RSA) was compared to the accuracy of a manually operated RSA system. For this purpose, we used radiographs of a phantom and radiographs of patients. The radiographs of the patients consisted of double examinations of 12 patients that had a tibial osteotomy and of double examinations of 12 patients that received a total hip prosthesis. First, the radiographs were measured manually with an accurate measurement table. Subsequently, the images were digitized by a film scanner at 150 DPI and 300 DPI resolutions and analyzed with the RSA-CMS software. In the phantom experiment, the manually operated system produced significantly better results than the digital system, although the maximum difference between the median values of the manually operated system and the digital system was as low as 0.013mm for translations and 0.033 degrees for rotations. In the radiographs of the patients, the manually operated system and the digital system produced equally accurate results: no significant differences in translations and rotations were found. We conclude that digital RSA is an accurate, fast, and user friendly alternative for manually operated RSA. Currently, digital RSA systems are being used in a growing number of clinical RSA-studies.

Detection of areas with viable remnant tumor in postchemotherapy patients with Ewing's sarcoma by dynamic contrast-enhanced MRI using pharmacokinetic modeling

An approach is presented for monitoring the effects of neoadjuvant chemotherapy in patients with Ewing's sarcoma using dynamic contrast-enhanced perfusion magnetic resonance (MR) images. For that purpose, we modify the three-compartment pharmacokinetic permeability model introduced by Tofts et al. (Magn Reson Med 1991;17:357-67) to a two-compartment model. Perfusion MR images acquired using an intravenous injection with Gadolinium (Gd-DTPA) are analyzed with this two-compartment pharmacokinetic model as well as the with an extended pharmacokinetic model that includes the (local) arrival time t(0) of the tracer as an endogenous (estimated) parameter. For each MR section, a wash-in parameter associated with each voxel is estimated twice by fitting each of the two pharmacokinetic models to the dynamic MR signal. A comparison of the two wash-in parametric images (global versus local arrival time) with matched histologic macroslices demonstrates a good correspondence between areas with viable remnant tumor and a high wash-in rate. This can be explained by the high number and permeability of the (leaking) capillaries in viable tumor tissue. The novel pharmacokinetic model based on a local arrival time of tracer results in the best fit of the wash-in rate, the most important factor discerning viable from nonviable tumor components. However, parameter estimates obtained with this model are also more sensitive to noise in the MR signal. The novel pharmacokinetic model resulted in a sensitivity between 0.22 and 0.60 and a specificity between 0.61 and 1. The model based on a global arrival time gave sensitivities between 0.33 and 0.77 and specificities between 0.58 and 0.99. Both statistics are computed as the fraction of correctly labeled voxels (viable or nonviable tumor) within a specified ROI, which delineates the tumor. We conclude that the added value of estimating the local arrival time of tracer first manifests itself for moderate noise levels in the MR signal. The novel pharmacokinetic model should moreover be preferred when pharmacokinetic modeling is applied on the average signal intensity within a ROI, where noise has less effect on the fitted parameters.

Automated calibration in vascular X-ray images using the accurate localization of catheter marker bands

RATIONALE AND OBJECTIVES

To develop a new automated calibration method for vessel measurements in vascular x-ray images.

METHODS

Radiopaque marker bands mounted equidistantly on a small catheter were acquired in vitro at five image intensifier (II) sizes in x-ray projection images. The positions of the marker centers were detected by using a Hough transform and were computed at subpixel precision by using either a novel, iterative center-of-gravity approach (CGA) or a symmetry filter. Curve-fitting procedures were used to reject false-positive marker detections and to calculate intermarker distances. The calibration factor was calculated from the true marker distance and the average of the measured distances in pixels. Results were compared statistically with a grid calibration method, which was taken as the gold standard. A simulation study was performed to assess the influence of image noise on the CGA method.

RESULTS

The iterative CGA method was convergent and faster than the symmetry-based technique. For four II sizes (17, 20, 25, and 31 cm), the results from the CGA method were not significantly different from the results obtained with grid calibration. For the II size of 38 cm, a significant difference (0.3% of the grid calibration factor) was found; however, this was caused by the quantification error in the image data and was not clinically relevant. In general, the performance of the CGA method improved with increasing signal-to-noise ratio.

CONCLUSIONS

A practical new calibration method for small catheter sizes was developed and validated for quantitative vascular arteriography.