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

Clinical Relevance of Cortical Cerebral Microinfarcts on 1.5T Magnetic Resonance Imaging in the Late-Adult Population

Background and Purpose: Cortical cerebral microinfarcts (CMIs) have been linked with dementia and impaired cognition in cross-sectional studies. However, the clinical relevance of CMIs in a large population-based setting is lacking. We examine the association of cortical CMIs detected on 1.5T magnetic resonance imaging with cardiovascular risk factors, cerebrovascular disease, and brain tissue volumes. We further explore the association between cortical CMIs with cognitive decline and risk of stroke, dementia, and mortality in the general population. Methods: Two thousand one hundred fifty-six participants (age: 75.7±5.9 years, women: 55.6%) with clinical history and baseline magnetic resonance imaging (January 2009-December 2013) were included from the Rotterdam Study. Cortical CMIs were graded based on a previously validated method. Markers of cerebrovascular disease and brain tissue volumes were assessed on magnetic resonance imaging. Cognition was assessed using a detailed neuropsychological test at baseline and at 5 years of follow-up. Data on incident stroke, dementia, and mortality were included until January 2016. Results: Two hundred twenty-seven individuals (10.5%) had ≥1 cortical CMIs. The major risk factors of cortical CMIs were male sex, current smoking, history of heart disease, and stroke. Furthermore, presence of cortical CMIs was associated with infarcts and smaller brain volume. Persons with cortical CMIs showed cognitive decline in Stroop tests (color-naming and interference subtasks; β for color-naming, 0.18 [95% CI, 0.04-0.33], P interaction ≤0.001 and β for interference subtask, 1.74, [95% CI, 0.66-2.82], P interaction ≤0.001). During a mean follow-up of 5.2 years, 73 (4.3%) individuals developed incident stroke, 95 (5.1%) incident dementia, and 399 (19.2%) died. People with cortical CMIs were at an increased risk of stroke (hazard ratio, 1.18 [95% CI, 1.09-1.28]) and mortality (hazard ratio, 1.09 [95% CI, 1.00-1.19]). Conclusions: Cortical CMIs are highly prevalent in a population-based setting and are associated with cardiovascular disease, cognitive decline, and increased risk of stroke and mortality. Future investigations will have to show whether cortical CMIs are a useful biomarker to intervene upon to reduce the burden of stroke.</p

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

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 &lt; 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

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

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 valu

Mixed-location cerebral microbleeds as a biomarker of neurodegeneration in a memory clinic population

Cerebral microbleeds (CMBs) in the lobar and deep locations are associated with two distinct pathologies: cerebral amyloid angiopathy and hypertensive arteriopathy. However, the role of mixed-location CMBs in neurodegeneration remains unexplored. We investigated the associations between strictly lobar, strictly deep and mixed-location CMBs with markers of neurodegeneration. This study recruited 477 patients from a memory clinic who underwent 3T MRI scans. CMBs were categorized into strictly lobar, strictly deep and mixed-location. Cortical thickness, white matter volume and subcortical structural volumes were quantified using Free-Surfer. Linear regression models were performed to assess the association between CMBs and cerebral atrophy, and the mean difference (β) and 95% confidence intervals (CIs) were reported. In the regression analyses, mixed-location CMBs were associated with smaller cortical thickness of limbic region [β=-0.01; 95% CI=-0.02,-0.00, p=0.007) as well as with smaller accumbens volume [β=-0.01; 95% CI=-0.02,-0.00, p=0.004) and presubiculum region of hippocampus [β=-0.01; 95% CI=-0.02,-0.00, p=0.002). Strictly lobar CMBs were associated with smaller total white matter volume [β=-0.03; 95% CI=-0.04,-0.01, p<0.001] and with region specific white mat