Structural Image Analysis Research Articles

Comparison of Structural Behavior Following Bone Scaffold Implantation in Multi-Resolution Proximal Femur Images.

Bone scaffolds are increasingly regarded as viable alternatives to autografts and allografts in clinical settings. However, their effectiveness can vary based on certain anatomical characteristics, highlighting the importance of image-based structural analysis. High-resolution imaging is crucial to accurately assess the performance of bone scaffolds. Despite this, the resolution of current clinical medical images is constrained by concerns regarding radiation exposure. The efficacy of these analyses can be improved by quantitatively evaluating the similarities and differences between low- and high-resolution images. This study quantitatively compared the structural behavior of bone scaffolds using both high- and low-resolution images. This study downscaled a high-resolution image, implanted a bone scaffold, and conducted finite element analysis. The findings suggest that the resolution needed for accurate structural analysis of skeletal images varies based on the implantation site of the scaffold. Additionally, it was found that the less influence the loading conditions have, the higher the resolution required to accurately assess the structural behavior.

Methods for Image Analysis of Intracellular Structures of Actin Labeled with Phalloidin

A cell is a complex three-dimensional system, which possesses a number of highly dynamic structures with extended, rugged, and uneven morphology. The actin cytoskeleton consists of fibrillar and globular actin, as well as auxiliary proteins that regulate organization. The shape and the rearrangements of actin cytoskeleton are closely related to functioning of the cell. The ability to characterize these changes allows scientists to confirm or refute any hypotheses in the research. Obtaining a numerical equivalent of the actin cytoskeleton organization could help compare actin structures in biological experiments (example: exposure to biologically active substances). The review summarizes methods for analyzing images of intracellular actin structures labeled with phalloidin using ImageJ. The methods considered make it possible to obtain a quantitative characteristic of the organization of actin structures for further evaluation and comparison of experimental results.

Surface-based morphometry of the cerebral cortex in cognitive impairments of varying severity in patients with age-related cerebral small vessel disease

BACKGROUND: Analysis of structural magnetic resonance images is essential to assessing the main substrate of cognitive impairment in sporadic age-related cerebral small vessel disease, accounting for up to 45% of all dementia cases. Variations in the results of magnetic resonance morphometry applied in cerebral small vessel disease require extensive studies and clinical correlation. AIM: To assess cerebral atrophy features in cognitive impairment in patients with cerebral small vessel disease by surface-based morphometry. MATERIALS AND METHODS: A prospective study was conducted to assess patients with cerebral small vessel disease and cognitive impairments of varying severity levels (subjective, moderate, and dementia) and sex- and age-matched groups of volunteers. The assessment included the analysis of signs of cerebral small vessel disease based on the results of magnetic resonance imaging with the computation of general cerebral small vessel disease index and processing T1 multiplanar reconstruction images by surface-based morphometry to quantify general and regional brain parameters, including the thickness of the cerebral cortex. RESULTS: The main group consisted of 173 patients with cerebral small vessel disease, whereas the control group included 47 healthy volunteers. As the severity of brain structural changes and cognitive impairments increased, a significant (p 0.05) decrease in the cortical thickness of certain regions following a similar pattern was reported, particularly in the cingulate gyri, mainly their posterior sections; medial and middle sections of the frontal lobes, various areas of the insular cortex, and temporoparietal areas, particularly the supramarginal gyri. The brain volumes (overall, gray matter, and white matter volumes) in cerebral small vessel disease were significantly different only in controls but not between patients with cognitive impairment of different severity levels. The hyperintense white matter volume was significantly different between patients with dementia and moderate cognitive impairment, dementia, and subjective cognitive impairment (p 0.0001). CONCLUSIONS: The results confirm secondary/mixed atrophy in cerebral small vessel disease. The clarification of the severity level of cognitive impairment in cerebral small vessel disease based on atrophy data is limited by the wide variety of regions with significant cortical thinning. Thus, the quantification of the cortex can only be a supplementary method in predicting cerebral small vessel disease progression.

Landslide Indications Based on Geological Structure Image and Field Analysis Cipatat District, West Bandung District, West Java Province

Abstract The area has a limestone lithology of the Rajamandala Formation and is included in the karst landscape. It has a fault zone located in the north and south of the Cipatat Area. The method used is studio observation in the form of geological alignment, field observation to measure the direction and slope of the geological structure in the research area in the form of fractures and faults to determine the direction of the main stress. Then, an analysis was carried out using a rose diagram. The results of the form of a geological structure alignment map along with field data and its analysis. The main results obtained confirm that the geological structure of the Cipatat area is west-east which is controlled by the Karangpanganten fault, and lithological information is obtained that the research area is limestone of the Rajamandala Formation. from these data it shows that the Cipatat area is prone to landslides because it is controlled by tectonics and lithology that are less compact.

Temporal atrophy together with verbal encoding impairment is highly predictive for cognitive decline in typical Alzheimer's dementia - a retrospective follow-up study.

The increasing prevalence of Alzheimer's disease (AD) has created an urgent need for rapid and cost-effective methods to diagnose and monitor people at all stages of the disease. Progressive memory impairment and hippocampal atrophy are key features of the most common so-called typical variant of AD. However, studies evaluating detailed cognitive measures combined with region of interest (ROI)-based imaging markers of progression over the long term in the AD dementia (ADD) stage are rare. We conducted a retrospective longitudinal follow-up study in patients with mild to moderate ADD (aged 60-92 years). They underwent magnetic resonance imaging (MRI; 3 Tesla, MPRAGE) as well as clinical and neuropsychological examination (Consortium to Establish a Registry for Alzheimer's Disease [CERAD] -Plus test battery) at baseline and at least one follow-up visit. ROI-based brain structural analysis of baseline MRIs was performed using the Computational Anatomy Toolbox (CAT) 12. Clinical dementia progression (progression index [PI]) was measured by the annual decline in the Mini Mental State Examination (MMSE) scores. MRI, demographic, and neuropsychological data were included in univariate and multiple linear regression models to predict the PI. 104 ADD patients (age 63 to 90 years, 73% female, mean MMSE score 22.63 ± 3.77, mean follow-up 4.27 ± 2.15 years) and 32 age- and gender-matched cognitively intact controls were included. The pattern of gray matter (GM) atrophy and the cognitive profile were consistent with the amnestic/typical variant of ADD in all patients. Deficits in word list learning together with temporal lobe GM atrophy had the highest predictive value for rapid cognitive decline in the multiple linear regression model, accounting for 25.4% of the PI variance. Our results show that temporal atrophy together with deficits in the encoding of verbal material, rather than in immediate or delayed recall, is highly predictive for rapid cognitive decline in patients with mild to moderate amnestic/typical ADD. These findings point to the relevance of combining detailed cognitive and automated structural imaging analyses to predict clinical progression in patients with ADD.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI

PurposeHigh PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and therefore predict if a lesion would be PSMA positive. Therefore, we aimed to train a neural network based on PSMA PET/MRI scans to predict increased prostatic PSMA uptake based on the axial T2-weighted sequence alone.Material and methodsAll patients undergoing simultaneous PSMA PET/MRI for PCa staging or biopsy guidance between April 2016 and December 2020 at our institution were selected. To increase the specificity of our model, the prostatic beds on PSMA PET scans were dichotomized in positive and negative regions using an SUV threshold greater than 4 to generate a PSMA PET map. Then, a C-ENet was trained on the T2 images of the training cohort to generate a predictive prostatic PSMA PET map.ResultsOne hundred and fifty-four PSMA PET/MRI scans were available (133 [68Ga]Ga-PSMA-11 and 21 [18F]PSMA-1007). Significant cancer was present in 127 of them. The whole dataset was divided into a training cohort (n = 124) and a test cohort (n = 30). The C-ENet was able to predict the PSMA PET map with a dice similarity coefficient of 69.5 ± 15.6%.ConclusionIncreased prostatic PSMA uptake on PET might be estimated based on T2 MRI alone. Further investigation with larger cohorts and external validation is needed to assess whether PSMA uptake can be predicted accurately enough to help in the interpretation of mpMRI.

Investigating the paracrine and juxtacrine abilities of adipose-derived stromal cells in angiogenesis triple cell co-cultures

The pro-angiogenic abilities of adipose-derived stromal cells (ASCs) make them attractive candidates for cellular therapy, especially for ischemic disease indications. However, details regarding the underlying mechanisms remain elusive. Therefore, this study aimed to investigate paracrine and juxtacrine abilities of ASCs in angiogenesis triple cell co-cultures by detailed image analysis of the vascular-like structures. Fibroblast-endothelial cell co-cultures were established, and ASCs were added directly or indirectly through inserts. The cultures were treated with antibodies or subjected to analyses using ELISA and RT2 PCR Arrays. The model consistently generated vascular-like structures. ASCs increased the total branch lengths equally well in paracrine and juxtacrine conditions, by increasing the number of branches and average branch lengths (ABL). In contrast, addition of VEGF to the model increased the number of branches, but not the ABL. Still, ASCs increased the VEGF levels in supernatants of paracrine and juxtacrine co-cultures, and anti-VEGF treatment decreased the sprouting. ASCs themselves up-regulated collagen type V in response to paracrine signals from the co-cultures. The results suggest that ASCs initiate sprouting through secretion of several paracrine factors, among which VEGF is identified, but VEGF alone does not recapitulate the paracrine actions of ASCs. By employing neutralizing antibodies and dismantling common model outputs using image analysis, the triple cell co-culture is an attractive tool for discovery of the paracrine factors in ASCs’ secretome which act in concert with VEGF to improve angiogenesis.

Automatic classification of AD pathology in FTD phenotypes using natural speech.

Screening for Alzheimer's disease neuropathologic change (ADNC) in individuals with atypical presentations is challenging but essential for clinical management. We trained automatic speech-based classifiers to distinguish frontotemporal dementia (FTD) patients with ADNC from those with frontotemporal lobar degeneration (FTLD). We trained automatic classifiers with 99 speech features from 1 minute speech samples of 179 participants (ADNC=36, FTLD=60, healthy controls [HC]=89). Patients' pathology was assigned based on autopsy or cerebrospinal fluid analytes. Structural network-based magnetic resonance imaging analyses identified anatomical correlates of distinct speech features. Our classifier showed 0.88 0.03 area under the curve (AUC) for ADNC versusFTLD and 0.93 0.04 AUC for patients versusHC. Noun frequency and pause rate correlated with gray matter volume loss in the limbic and salience networks, respectively. Brief naturalistic speech samples can be used for screening FTD patients for underlying ADNC in vivo. This work supports the future development of digital assessment tools for FTD. We trained machine learning classifiers for frontotemporal dementia patients using natural speech. We grouped participants by neuropathological diagnosis (autopsy) or cerebrospinal fluid biomarkers. Classifiers well distinguished underlying pathology (Alzheimer's disease vs. frontotemporal lobar degeneration) in patients. We identified important features through an explainable artificial intelligence approach. This work lays the groundwork for a speech-based neuropathology screening tool.

Brain Functional Connectivity Changes in Rapid Eye Movement Sleep Behavior Disorder

The idiopathic rapid eye movement sleep behavior disorder (iRBD) has been reported as prodromal biomarker for neurodegenerative synucleinopathies. To early detect neurodegeneration in preclinical stage, pathophysiological changes of iRBD have been studied in many ways including structural magnetic resonance imaging (MRI), functional MRI (fMRI), and connectivity analyses. This review summarizes functional connectivity studies using resting-state fMRI in iRBD patients focused on motor-related network, compensatory mechanism of synucleinopathies, cognitive dysfunction, and non-motor symptoms.

Structural and functional changes following brain surgery in pediatric patients with intracranial space-occupying lesions.

We explored the structural and functional changes of the healthy hemisphere of the brain after surgery in children with intracranial space-occupying lesions. We enrolled 32 patients with unilateral intracranial space-occupying lesions for brain imaging and cognitive assessment. Voxel-based morphometry and surface-based morphometry analyses were used to investigate the structural images of the healthy hemisphere. Functional images were analyzed using regional homogeneity, amplitude of low-frequency fluctuations, and fractional-amplitude of low-frequency fluctuations. Voxel-based morphometry and surface-based morphometry analysis used the statistical model built into the CAT 12 toolbox. Paired t-tests were used for functional image and cognitive test scores. For structural image analysis, we used family-wise error correction of peak level (p < 0.05), and for functional image analysis, we use Gaussian random-field theory correction (voxel p < 0.001, cluster p < 0.05). We found an increase in gray matter volume in the healthy hemisphere within six months postoperatively, mainly in the frontal lobe. Regional homogeneity and fractional-amplitude of low-frequency fluctuations also showed greater functional activity in the frontal lobe. The results of cognitive tests showed that psychomotor speed and motor speed decreased significantly after surgery, and reasoning increased significantly after surgery. We concluded that in children with intracranial space-occupying lesions, the healthy hemisphere exhibits compensatory structural and functional effects within six months after surgery. This effect occurs mainly in the frontal lobe and is responsible for some higher cognitive compensation. This may provide some guidance for the rehabilitation of children after brain surgery.

Association between cortical thickness and cognitive ability in very preterm school-age children

Very preterm children, born before 32 weeks of gestation, are at risk for impaired cognitive function, mediated by several risk factors. Cognitive impairment can be measured by various neurodevelopmental assessments and is closely associated with structural alterations of brain morphometry, such as cortical thickness. However, the association between structural alterations and high-order cognitive function remains unclear. This study aimed to investigate the neurodevelopmental associations between brain structural changes and cognitive abilities in very preterm and full-term children. Cortical thickness was assessed in 37 very preterm and 24 full-term children aged 6 years. Cortical thickness analysis of structural T1-weighted images was performed using Advanced Normalization Tools. Associations between cortical thickness and the Wechsler Intelligence Scale for Children were evaluated by regression analysis based on ordinary least square estimation. Compared with full-term children, very preterm children showed significant differences in cortical thickness, variously associated with cognitive abilities in several brain regions. Perceptual reasoning indices were broadly correlated with cortical thickness in very preterm and full-term children. These findings provide important insights into neurodevelopment and its association with cortical thickness, which may serve as a biomarker in predictive models for neurodevelopmental diagnosis of high-order cognitive function.

Signature Verification System Using SSIM In Image Processing

The verification of signatures is an essential function in several domains, including financial, legal, and administrative processes. Thanks to advancements in image processing, automatic signature verification methods have become more popular. Using structural similarities and image analysis, the proposed research offers a novel approach to signature verification. To compare and assess signatures, it uses the SSIM index. The procedure begins with pre-processing the signature pictures to improve their quality and eliminate any artifacts or noise that may have been obtained from Adobe's stock library. Then, the structural similarity between the reference signature and the input signature is calculated. The perceptual resemblance of two images is measured using structure, contrast, and brightness. The goal of the proposed research is to use this measure to record the signature's structural features and spot changes or deviations. The SSIM value that comes out of the comparison is checked against a threshold that has already been set. To validate an input signature, the calculated similarity must be greater than a certain threshold. The document is marked as suspicious or possibly falsified if it does not comply. Experimental results have shown that the method is effective in differentiating between authentic and counterfeit signatures. By doing away with the need for subjective human judgment and physical examination, this technology provides a reliable and unbiased way to authenticate signatures. Increased automation and trust in signature authentication systems are possible because to the proposed method's encouraging results in accurately differentiating genuine signatures from fakes.

Effect of glymphatic system function on cognitive function in patients with chronic kidney disease.

Studies have recently shown an alteration of the structural connectivity and a dysfunctional glymphatic system in patients with chronic kidney disease (CKD). In this study, we aimed to investigate the effects of the structural connectivity and glymphatic system on the cognitive function of patients with CKD. We prospectively enrolled patients with CKD and healthy controls. The CKD group was divided into two regarding their cognitive function. All patients received brain magnetic resonance imaging, including diffusion tensor imaging (DTI). We calculated the measures of structural connectivity and diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, a neuroimaging marker of the glymphatic system function, and compared the indices between groups. The mean clustering coefficient, local efficiency, and small-worldness index in patients with CKD were lower than those in healthy controls (0.125 ± 0.056 vs. 0.167 ± 0.082, p = 0.008; 1.191 ± 0.183 vs. 1.525 ± 0.651, p = 0.002; 0.090 ± 0.043 vs. 0.143 ± 0.102, p = 0.003; respectively). The DTI-ALPS index was lower in patients with CKD than in healthy controls (1.436 vs. 1.632, p < 0.001). Additionally, the DTI-ALPS index differed significantly between CKD patients with and without cognitive impairment. Notably, this index was lower in patients with CKD and cognitive impairment than in patients without cognitive impairment (1.338 vs. 1.494, p = 0.031). However, there were no differences of the structural connectivity between CKD patients with and without cognitive impairment. We found lower DTI-ALPS index in patients with CKD, which could be related with glymphatic system dysfunction. Moreover, those with cognitive impairment in the CKD group had a lower index than those without, indicating a link between the glymphatic system function and cognitive function.

Factors associated with attitudes toward research MRI in older Asian Americans.

South Asian (SA) and East Asian (EA) older adults represent the fastest-growing racial/ethnic groups of Americans at risk for dementia. While recruiting older SA adults into a brain health study, we encountered unexpected hesitancy toward structural brain magnetic resonance imaging (MRI) analysis and stigmatizing attitudes related to internal locus of control (LoC) for future dementia risks. We hypothesized that support for MRI-related research was influenced by these attitudes as well as personal MRI experience, perceived MRI safety, and concerns for personal risk for future dementia/stroke. We developed a brief cross-sectional survey to assess older adults' MRI experiences and perceptions, desire to learn of six incidental findings of increasing impact on health, and attitudes related to dementia (including LoC) and research participation. We recruited a convenience sample of 256 respondents (74% reporting as 50+) from the New Jersey/New York City area to complete the survey (offered in English, Chinese, Korean, and Spanish) and modeled the proportional odds (PO) for favorable attitudes toward research activities. Seventy-seven SA and 84 EA respondents were analyzed alongside 95 White, Black, or Hispanic adults. White (PO = 2.54, p = 0.013) and EA (PO = 2.14, p = 0.019) respondents were both more likely than SA respondents to endorse healthy volunteers' participation in research, and the difference between White and SA respondents was mediated by the latter's greater internal LoC for dementia risks. EA respondents had more worries for future dementia/stroke than SA respondents (p = 0.006) but still shared SA respondents' lower wish (measured by proportion of total) to learn of incidental MRI findings. SA-and EA compared to SA-older adults had low desire to learn of incidental MRI findings but had different attitudes toward future dementia/stroke risks. A culturally appropriate protocol to disclose incidental MRI findings may improve SA and EA participation in brain health research. Older Asian Americans have limited interest in incidental findings on research MRISouth Asians are most likely to attribute dementia to people's own behaviorsSouth Asians' attitudes mediate lower support for healthy volunteers in researchSouth and East Asians differ in dementia worries and research-related attitudes.

Lateral prefrontal cortex thickness is associated with stress but not cognitive fatigue in exhaustion disorder.

Impaired executive functioning, including cognitive fatigue, is a core feature of the long-term stress-related condition exhaustion disorder (ED). Recent research suggests that a key area for executive control, the lateral prefrontal cortex (LPFC), may be mechanistically linked to cognitive fatigue due to stress. Here, we therefore asked if and how stress, the LPFC and cognitive fatigue may be related in ED. We used a multimodal cross-sectional study design with high-resolution structural magnetic resonance imaging (MRI), self-reported measures, and path analysis modeling in 300 participants with ED. We found positive associations between stress and cognitive fatigue, and stress and LPFC thickness,but no association between LPFC thickness and cognitive fatigue. Furthermore, LPFC thickness did not mediate or moderate the association between stress and cognitive fatigue. These findings suggest that LPFC brain morphology is related to perceived stress levels but not cognitive fatigue, expanding previous research on the role of the LPFC in executive functioning. Moreover, the results support the notion that the LPFC may be mechanistically involved in stress-related executive function impairment but prompt further research into if and how this may be related to cognitive symptoms in ED.

The volume and structural covariance network of thalamic nuclei in patients with Wilson's disease: an investigation of the association with neurological impairment.

This study aimed to examine the volumes of thalamic nuclei and the intrinsic thalamic network in patients with Wilson's disease (WDs), and to explore the correlation between these volumes and the severity of neurological symptoms. A total of 61 WDs and 33 healthy controls (HCs) were included in the study. The volumes of 25 bilateral thalamic nuclei were measured using structural imaging analysis with Freesurfer, and the intrinsic thalamic network was evaluated through structural covariance network (SCN) analysis. The results indicated that multiple thalamic nuclei were smaller in WDs compared to HCs, including mediodorsal medial magnocellular (MDm), anterior ventral (AV), central median (CeM), centromedian (CM), lateral geniculate (LGN), limitans-suprageniculate (L-Sg), reuniens-medial ventral (MV), paracentral (Pc), parafascicular (Pf), paratenial (Pt), pulvinar anterior (PuA), pulvinar inferior (PuI), pulvinar medial (PuM), ventral anterior (VA), ventral anterior magnocellular (VAmc), ventral lateral anterior (VLa), ventral lateral posterior (VLp), ventromedial (VM), ventral posterolateral (VPL), and right middle dorsal intralaminar (MDI). The study also found a negative correlation between the UWDRS scores and the volume of the right MDm. The intrinsic thalamic network analysis showed abnormal topological properties in WDs, including increased mean local efficiency, modularity, normalized clustering coefficient, small-world index, and characteristic path length, and a corresponding decrease in mean node betweenness centrality. WDs with cerebral involvement had a lower modularity compared to HCs. The findings suggest that the majority of thalamic nuclei in WDs exhibit significant volume reduction, and the atrophy of the right MDm is closely related to the severity of neurological symptoms. The intrinsic thalamic network in WDs demonstrated abnormal topological properties, indicating a close relationship with neurological impairment.

4D spectral-spatial computational photoacoustic dermoscopy

Photoacoustic dermoscopy (PAD) is an emerging non-invasive imaging technology aids in the diagnosis of dermatological conditions by obtaining optical absorption information of skin tissues. Despite advances in PAD, it remains unclear how to obtain quantitative accuracy of the reconstructed PAD images according to the optical and acoustic properties of multilayered skin, the wavelength and distribution of excitation light, and the detection performance of ultrasound transducers. In this work, a computing method of four-dimensional (4D) spectral-spatial imaging for PAD is developed to enable quantitative analysis and optimization of structural and functional imaging of skin. This method takes the optical and acoustic properties of heterogeneous skin tissues into account, which can be used to correct the optical field of excitation light, detectable ultrasonic field, and provide accurate single-spectrum analysis or multi-spectral imaging solutions of PAD for multilayered skin tissues. A series of experiments were performed, and simulation datasets obtained from the computational model were used to train neural networks to further improve the imaging quality of the PAD system. All the results demonstrated the method could contribute to the development and optimization of clinical PADs by datasets with multiple variable parameters, and provide clinical predictability of photoacoustic (PA) data for human skin.

Neurodegeneration or dysfunction in Phelan-McDermid syndrome? A multimodal approach with CSF and computational MRI

BackgroundPhelan-McDermid syndrome (PMS) is a rare multisystem disease with global developmental delay and autistic features. Genetically, the disease is based on a heterozygous deletion of chromosome 22q13.3 with involvement of at least part of the SHANK3 gene or heterozygous pathogenic variants in SHANK3. Pathophysiologically, this syndrome has been regarded as a synaptopathy, but current data suggest an additional concept, since axonal functions of neurons are also impaired, thus, the specific pathophysiological processes in this disease are not yet fully understood. Since symptoms of the autism spectrum, regression, and stagnation in development occur, we investigated whether neuroinflammatory and neurodegenerative processes may also play a role. To this end, we analysed biomarkers in cerebrospinal fluid (CSF) and parameters from magnetic resonance imaging with high-resolution structural T1w volumetry and diffusion tensor imaging analysis in 19 Phelan-McDermid syndrome patients.ResultsCSF showed no inflammation but abnormalities in tau protein and amyloid-ß concentrations, however, with no typical biomarker pattern as in Alzheimer’s disease. It could be demonstrated that these CSF changes were correlated with integrity losses of the fibres in the corticospinal tract as well as in the splenium and dorsal part of the cingulum. High CSF levels of tau protein were associated with loss of integrity of fibres in the corticospinal tract; lower levels of amyloid-ß were associated with decreasing integrity of fibre tracts of the splenium and posterior cingulate gyrus. Volumetric investigations showed global atrophy of the white matter, but not the grey matter, and particularly not in temporal or mesiotemporal regions, as is typical in later stages of Alzheimer’s disease.ConclusionsIn summary, alterations of neurodegenerative CSF markers in PMS individuals could be demonstrated which were correlated with structural connectivity losses of the corticospinal tract, the splenium, and the dorsal part of the cingulum, which can also be associated with typical clinical symptoms in these patients. These findings might represent a state of dysfunctional processes with ongoing degenerative and regenerative processes or a kind of accelerated aging. This study should foster further clinical diagnostics like tau- and amyloid-PET imaging as well as novel scientific approaches especially in basic research for further mechanistic proof.

Quantitative Characterization of Marble Natural Aging through Pore Structure Image Analysis

The goal of this study is the quantitative characterization of the degree of natural alteration of marble samples by using image analysis for the automatic characterization and comparison of the pore structure of rock samples before and after weathering. The proposed methodology is based on a pore exploration path-finding algorithm for the identification of paths developing within the porous domain of marble samples in both natural conditions and after weathering. Along each identified path, the pore radius is measured, providing a thorough description of the pore space statistical distribution. The A* path-finding approach was developed and applied to binarized images obtained from two-dimensional (2D) thin sections of marble samples in both natural conditions and after 10 years of natural decay. The results are expressed in terms of 2D porosity and statistical distributions of the pore radius of the samples preweathering and postweathering. A comparison with the information obtained from standardized laboratory tests used for the physical and mechanical characterization of stone material is also provided. From a computational point of view, the presented approach is highly parallelizable. The presented approach works wells in complex porous structures characterized by high path tortuosity, pore-size heterogeneity, and pore surface roughness. Moreover, the methodology is less affected by small-scale pore features and noise produced during image binarization, compared with other algorithms for pore structure morphological analysis such as skeleton-based and maximal ball approaches.