Association of Genetic Polymorphisms with Abdominal Aortic Aneurysm in the Processes of Apoptosis, Inflammation, and Cholesterol Metabolism.

Background and Objectives: This study aims to identify the minor allele of the single nucleotide polymorphisms (SNPs) DAB2IP rs7025486, IL6R rs2228145, CDKN2BAS rs10757278, LPA rs3798220, LRP1 rs1466535, and SORT1 rs599839 in order to assess the risk of abdominal aortic aneurysm (AAA) formation and define the linkage among these SNPs. Materials and Methods: A case-control study with AAA patients (AAA group) and non-AAA controls (control group) was carried out in a study population. DNA was isolated from whole blood samples; the SNPs were amplified using PCR and sequenced. Results: In the AAA group of 148 patients, 87.2% of the patients were male, 64.2% had a history of smoking, and 18.2% had relatives with AAA. The mean ± SD of age, BMI, and aneurysmal diameter in the AAA group were 74.8 ± 8.3 years, 27.6 ± 4.6 kg/m2, and 56.2 ± 11.8 mm, respectively. In comparison with 50 non-AAA patients, there was a significantly elevated presence of the SNPs DAB2IP rs7025486[A], CDKN2BAS rs10757278[G], and SORT1 rs599839[G] in the AAA group (p-values 0.040, 0.024, 0.035, respectively), while LPA rs3798220[C] was significantly higher in the control group (p = 0.049). A haplotype investigation showed that the SNPs DAB2IP, CDKN2BAS, and IL6R rs2228145[C] were significantly elevated in the AAA group (p = 0.037, 0.037, and 0.046) with minor allele frequencies (MAF) of 25.5%, 10.6%, and 15.4%, respectively. Only DAB2IP and CDKN2BAS showed significantly higher occurrences of a mutation (p = 0.028 and 0.047). Except for LPA, all SNPs were associated with a large aortic diameter in AAA (p < 0.001). Linkage disequilibrium detection showed that LPA to DAB2IP, to IL6R, to CDKN2BAS, and to LRP1 rs1466535[T] had D' values of 70.9%, 80.4%, 100%, and 100%, respectively. IL6R to LRP1 and to SORT1 had values for the coefficient of determination (r2) of 3.9% and 2.2%, respectively. Conclusions: In the investigated study population, the SNPs CDKN2BAS rs10757278, LPA rs3798220, SORT1 rs599839, DAB2IP rs7025486, and IL6R rs2228145 were associated with the development of abdominal aortic aneurysms. Individuals with risk factors for atherosclerosis and/or a family history of AAA should be evaluated using genetic analysis.

Evaluation of Ocular Perfusion in Patients with End-Stage Renal Disease Receiving Hemodialysis Using Optical Coherence Tomography Angiography.

Hemodialysis (HD) is known to affect ocular blood flow. This case-control study aims to evaluate macular and peripapillary vasculature in patients with end-stage renal disease (ESRD) receiving HD in comparison to matched controls. A total of 24 eyes of 24 ESRD patients receiving HD and 24 eyes of 24 healthy, age- and gender-matched control subjects were prospectively included in this study. Optical coherence tomography angiography was used to image the superficial (SCP), deep (DCP), and choriocapillary (CC) macular vascular plexus, as well as the radial peripapillary capillaries (RPC) of the optic disc. In addition, retinal thickness (RT) and retinal volume (RV) were compared between both groups. Flow density (FD) values of each retinal layer and data of parameters related to the foveal avascular zone (FAZ), as well as RT and RV, were analyzed using Mann-Whitney U tests. There was no significant difference in FAZ parameters between the two groups. Whole en face FD of the SCP and CC was noticeably reduced in the HD group in comparison to the control group. FD was negatively correlated with the duration of HD treatment. RT and RV were significantly smaller in the study group than in controls. Retinal microcirculation appears altered in patients with ESRD undergoing HD. Concurrently, the DCP appears more resilient towards hemodynamic changes in comparison to the other microvascular retinal layers. OCTA is a useful, non-invasive tool to investigate retinal microcirculation in ESRD patients.

Analysis of Spinal Ischemia after Frozen Elephant Trunk for Acute Aortic Dissection: An Observational, Single-Center Study.

BACKGROUND: This observational study aimed to evaluate the perioperative risk factors for spinal cord ischemia (SCI) in patients who underwent aortic repair with the frozen elephant trunk technique (FET) after acute aortic Stanford A dissection. METHODS: From May 2015 to April 2019, 31 patients underwent aortic arch replacement with the FET technique, and spinal ischemia was observed in 4 patients. The risk factors for postoperative SCI were analyzed. RESULTS: The mean age of patients with acute aortic dissection was 57.1 years, and 29.4% were female. Four patients developed SCI. There were no significant differences in characteristics such as age and body mass index. The female gender was associated with most of the SCI cases in the univariate analysis (75%, p = 0.016). Known perioperative and intraoperative risk factors were not related to postoperative SCI in our study. Patients who developed SCI had increased serum postoperative creatinine levels (p = 0.03). Twenty-four patients showed complete false lumen thrombosis up to zones 3-4, five patients up to zones 5-6 and two patients up to zones 7-9, which correlates with the postoperative development of SCI (p = 0.02). The total number of patent intercostal arteries was significantly reduced postoperatively in SCI patients (p = 0.044). CONCLUSIONS: Postoperative acute kidney injury, the reduction in patent intercostal arteries after surgery and the extension of false lumen thrombosis up to and beyond zone 5 may play a significant role in the development of clinically relevant spinal cord injury after FET.

Snare-Dragging Technique to Target the Hypogastric Artery in an Iliac Bifurcation Dissection.

PURPOSE: To describe snare-assisted vessel targeting to selectively overcome a dissection in the iliac bifurcation and gain antegrade access to the hypogastric artery (HA). TECHNIQUE: The technique is demonstrated in a 64-year-old woman with an asymptomatic Crawford type III thoracoabdominal aneurysm. A 2-stage endovascular repair, consisting of a thoracic endovascular aortic repair (TEVAR) and a branched endovascular aortic repair was planned. In the control angiography after TEVAR, a disrupted plaque with consequent dissection in the right iliac bifurcation was detected. The perfusion of the common iliac artery and external iliac artery resulted impaired. The targeting of the right HA through a contralateral antegrade approach failed, whereas an ipsilateral retrograde approach was possible but unsuitable for therapeutic purposes. Using the catheter of the retrograde ipsilateral access, a snare from a contralateral crossover was cached and dragged into the HA, allowing the targeting of the vessels and further endovascular therapy with angioplasty and stenting. Follow-up 8 months postoperatively demonstrated the patency of the stents and well-preserved perfusion in the right iliac bifurcation. CONCLUSION: The snare-dragging technique can be used to gain access to vessels presenting challenging conformations or dissections. This application may be a valuable support for complex endovascular treatment in a variety of patients. CLINICAL IMPACT: The snare-dragging technique can be used to gain access to vessels presenting challenging conformations or dissections. It allows the catheterization to be establish from the easiest and safest approach and then "transferred" from one access to the other. It avoids the risk of repeated loss of catheterization due to unstable and unfavorable working angles, and it saves time and radiation. It permits different material combinations, adapting to the available resources and materials. We believe that the current technique may increase the strategy spectrum available for endovascular therapy and complex endovascular procedures.

Impact of Frozen and Conventional Elephant Trunk on Aortic New-Onset Thrombus and Inflammatory Response.

(1) Aim: The primary endpoint of this study was to evaluate the impact of frozen elephant trunk (FET) and conventional elephant trunk (CET) on aortic mural thrombus. The secondary endpoint was to investigate the incidence of persistent inflammatory response (IR) in the form of post-implantation syndrome (PIS) or persistent fever without infection focus after FET and CET, respectively, as well as the risk factors associated with its occurrence. (2) Methods: A single-center, retrospective, observational study of 57 consecutive patients treated with FET and CET between April 2015 and June 2020 was performed. Demographics, procedural data, perioperative laboratory exams as well as vital parameters were recorded. Pre- and postoperative computer tomography angiography (CTA) scans were analyzed with a dedicated software. IR was defined as the presence of continuous fever (>38°, lasting > 24 h) and leukocytosis (white blood cell count > 12 × 1000/µL) developing after surgery in the absence of an infection focus. (3) Results: Fifty-seven consecutive patients (mean age 58.4 ± 12.6 years, 36.8% females) treated with FET (66.6%) or CET (33.3%) for acute aortic dissection (56.1%), post-dissection-aneurysm (19.2%) or aortic aneurysm (24.5%) were included. The median thrombus volume on CTA preoperatively was 10.1 cm3 (range 2−408 cm3). After surgery, the median new-onset mural thrombus was 9.7 cm3 (range 0.2−376 cm3). Nineteen (33.3%) patients developed IR; patients with IR were significantly younger (p = 0.027), less frequently of female gender (p = 0.003) and more frequently affected from acute dissection (p = 0.002) and stayed in the intensive care unit (ICU) significantly longer (p = 0.033) than those without IR. Postoperatively, the volume of new-onset thrombus was significantly greater in the IR group (84.4 vs. 3.2 cm3, p < 0.001). (4) Conclusions: In the context of CET and FET, the persistent inflammatory response occurred in 33.3% of the patients with persistent fever without infection focus. IR was associated with a higher volume of new-onset thrombus and significantly prolonged ICU stay. Further studies to investigate these observations are needed.

Volume Changes in the Descending Aorta after Frozen Elephant Trunk and Conventional Hemi-Arch Repair after Acute Type A Aortic Dissection.

The aim of this study was to compare the mortality rates, re-intervention rates, and volumetric changes in aortas following surgery, in terms of the true lumen and false lumen changes, using conventional hemi-arch repair (CET) and frozen elephant trunk (FET) techniques. During the period from 2015 to 2018, 66 patients underwent surgical treatment for acute aortic dissection (Debakey type 1). Demographic and procedure-related data were evaluated. We measured volumetric change before surgical treatment, at discharge, and at 12- and 24-month time points based on computed tomography angiography. The study cohort was divided into two groups (FET vs. CET). The mean age of the patients was 56.9 ± 9.4 years in the FET group versus 63.6 ± 11 years in the CET group (p = 0.063). The mean follow-up time was 24 ± 6 and 25 ± 5 months for the FET and CET groups, respectively. There were no significant differences between the two groups in terms of the medical histories of the cohorts. The results showed a significant increase in true lumen volume after the FET procedure (within 24 months postoperatively; p = 0.005), and no significant changes in total (p = 0.392) or false lumen (p = 0.659) volumes were noted. After the CET procedure, there were significant increases in total and false lumen volumes (p = 0.013, p = 0.042), while no significant change in true lumen was observed (p = 0.219). The volume increase in true lumen after the FET procedure was higher compared to the CET group at all postoperative time points (at discharge, 12 months, and 24 months) without significant evidence (p = 0.416, p = 0.422, p = 0.268). At two years, the volume increase in false lumen was significantly higher among the CET group compared to the FET group (p = 0.02). The Kaplan-Meier curve analysis showed that patients who underwent the CET procedure underwent significantly more re-interventions due to false lumen expansion of the descending aorta (p = 0.047). Present study results indicate that the true and false lumen changes in the aorta following the FET and CET procedures were different. FET led to a significant increase in true lumen volume, while false lumen volume remained stable; however, after the CET procedure, significant false lumen enlargement was noted at mid-term follow-up time points. The re-intervention rate after CET was higher due to false lumen expansion.

SGLT2 Inhibitors and Peripheral Vascular Events: A Review of the Literature.

Fifty articles comprising 18 randomized controlled trials (RCTs), 16 observational studies, and 16 meta-analyses on the safety and effectiveness of sodium-glucose cotransporter 2 inhibitors were evaluated in the current review. Only one-fourth of the cohorts of recent trials had peripheral arterial disease (PAD), whereas this subgroup was at high risk for amputations. Despite a remarkable heterogeneity of RCTs, only 2 trials on canagliflozin suggested excess amputation rates, whereas several observational studies generated conflicting conclusions and remained short on possible explanations. Preliminary evidence from observational research suggested that patients with PAD may even benefit from SGLT-2 inhibitor treatment due to lower observed heart failure hospitalization rates.

Convolutional neural networks to predict brain tumor grades and Alzheimer's disease with MR spectroscopic imaging data.

PURPOSE: To evaluate the value of convolutional neural network (CNN) in the diagnosis of human brain tumor or Alzheimer's disease by MR spectroscopic imaging (MRSI) and to compare its Matthews correlation coefficient (MCC) score against that of other machine learning methods and previous evaluation of the same data. We address two challenges: 1) limited number of cases in MRSI datasets and 2) interpretability of results in the form of relevant spectral regions. METHODS: A shallow CNN with only one hidden layer and an ad-hoc loss function was constructed involving two branches for processing spectral and image features of a brain voxel respectively. Each branch consists of a single convolutional hidden layer. The output of the two convolutional layers is merged and fed to a classification layer that outputs class predictions for the given brain voxel. RESULTS: Our CNN method separated glioma grades 3 and 4 and identified Alzheimer's disease patients using MRSI and complementary MRI data with high MCC score (Area Under the Curve were 0.87 and 0.91 respectively). The results demonstrated superior effectiveness over other popular methods as Partial Least Squares or Support Vector Machines. Also, our method automatically identified the spectral regions most important in the diagnosis process and we show that these are in good agreement with existing biomarkers from the literature. CONCLUSION: Shallow CNNs models integrating image and spectral features improved quantitative and exploration and diagnosis of brain diseases for research and clinical purposes. Software is available at https://bitbucket.org/TeslaH2O/cnn_mrsi.

Deep learning for Alzheimer's disease diagnosis: A survey.

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a progressive decline in cognitive abilities. Since AD starts several years before the onset of the symptoms, its early detection is challenging due to subtle changes in biomarkers mainly detectable in different neuroimaging modalities. Developing computer-aided diagnostic models based on deep learning can provide excellent opportunities for the analysis of different neuroimage modalities along with other non-image biomarkers. In this survey, we perform a comparative analysis of about 100 published papers since 2019 that employ basic deep architectures such as CNN, RNN, and generative models for AD diagnosis. Moreover, about 60 papers that have applied a trending topic or architecture for AD are investigated. Explainable models, normalizing flows, graph-based deep architectures, self-supervised learning, and attention mechanisms are considered. The main challenges in this body of literature have been categorized and explained from data-related, methodology-related, and clinical adoption aspects. We conclude our paper by addressing some future perspectives and providing recommendations to conduct further studies for AD diagnosis.

Embolization for Type Ia Endoleak after EVAR for Abdominal Aortic Aneurysms: A Systematic Review of the Literature.

(1) Successful endovascular repair for abdominal aortic aneurysms is based on the complete exclusion of the aneurysm sac from the systemic circulation. Type Ia endoleak (ELIA) is defined as the persistent perfusion of the aneurysm sac due to incomplete proximal sealing between aorta and endograft, with a consequent risk of rupture and death. Endoleak embolization has been sporadically reported as a viable treatment for ELIA. (2) A systematic literature search in PubMed of all publications in English about ELIA embolization was performed until February 2022. Research methods and reporting were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Data regarding patient numbers, technical success (endoleak absence at control angiography), reinterventions, clinical and imaging follow-up, and outcomes were collected and examined by two independent authors. (3) Twenty-one papers (12 original articles, 9 case reports) reported on 126 patients (age range 58-96 years) undergoing ELIA embolization 0-139 months after the index procedure. Indication for embolization was most often founded on unfavorable anatomy and patient comorbidities. Embolic agents used include liquid embolic agents, coils, plugs and combinations thereof. Technical success in this highly selected cohort ranged from 67-100%; the postprocedural complication rate within 30 days was 0-24%. ELIA recurrence was reported as 0-42.8%, with a secondary ELIA-embolization-intervention success rate of 50-100%. At a follow-up at 0-68 months, freedom from sac enlargement amounted to 76-100%, freedom from ELIA to 66.7-100%. (4) Specific literature about ELIA embolization is scant. ELIA embolization is a valuable bailout strategy for no-option patients; the immediate technical success rate is high and midterm and long-term outcomes are acceptable.

Encoder-decoder models for chest X-ray report generation perform no better than unconditioned baselines.

High quality radiology reporting of chest X-ray images is of core importance for high-quality patient diagnosis and care. Automatically generated reports can assist radiologists by reducing their workload and even may prevent errors. Machine Learning (ML) models for this task take an X-ray image as input and output a sequence of words. In this work, we show that ML models for this task based on the popular encoder-decoder approach, like 'Show, Attend and Tell' (SA&T) have similar or worse performance than models that do not use the input image, called unconditioned baseline. An unconditioned model achieved diagnostic accuracy of 0.91 on the IU chest X-ray dataset, and significantly outperformed SA&T (0.877) and other popular ML models (p-value < 0.001). This unconditioned model also outperformed SA&T and similar ML methods on the BLEU-4 and METEOR metrics. Also, an unconditioned version of SA&T obtained by permuting the reports generated from images of the test set, achieved diagnostic accuracy of 0.862, comparable to that of SA&T (p-value ≥ 0.05).

Post-implantation syndrome after frozen elephant trunk is associated with the volume of new-onset aortic thrombus.

BACKGROUND: Post-implantation syndrome (PIS) is defined as non-infectious continuous fever and a concomitant rise in inflammatory markers shortly after endovascular aortic repair. PIS occurrence after hybrid procedures, such as the frozen elephant trunk (FET) technique, has not been adequately investigated. The current study aims to define the incidence of PIS after the FET and to identify possible risk factors associated with its occurrence. METHODS: The clinical charts of 59 patients undergoing the FET between February 2015 and April 2020 were reviewed retrospectively. The occurrence of PIS was defined as the presence of fever (>38 °C lasting longer than one day during the hospitalisation) and leucocytosis (white blood cell count >12,000/µL). Patients with concomitant conditions possibly leading to fever and/or leucocytosis were excluded. Beside demographic and procedure-related data, serum/plasma inflammatory markers were evaluated before surgery and daily up to seven days postoperatively. Computed tomography scans (CT) were examined to calculate the volume of pre-existent and new-onset mural thrombus after the FET. RESULTS: Thirty-eight patients met the inclusion criteria. The study cohort was divided into two groups based on the occurrence of PIS (17 cases; 44.7%). Patients with PIS were significantly younger than those without PIS (53.5±8.9 vs. 62.5±9.6 years; P=0.005). Female patients were less likely to develop PIS (5.2% vs. 26.3%, P=0.018). Patients with PIS had a higher volume of new-onset thrombus in the postoperative CT (P<0.001). Patients treated for post-dissection aneurysm had, postoperatively, significantly more thrombus material developed in a false lumen (P=0.02). Among the PIS markers, CRP (C-reactive protein) levels on the third postoperative day were independently associated with the volume of new-onset thrombus (P=0.011). After multivariate analysis, the volume of new-onset thrombus (P=0.028) and age (P=0.036) remained the variable associated with a statistically significant increased incidence of PIS. CONCLUSIONS: PIS can occur after the frozen elephant trunk procedure. The volume of new-onset thrombus seems to be associated with an increased incidence of PIS. These findings need to be confirmed in larger patient cohorts.

Evaluating diagnostic content of AI-generated radiology reports of chest X-rays.

Radiology reports are of core importance for the communication between the radiologist and clinician. A computer-aided radiology report system can assist radiologists in this task and reduce variation between reports thus facilitating communication with the medical doctor or clinician. Producing a well structured, clear, and clinically well-focused radiology report is essential for high-quality patient diagnosis and care. Despite recent advances in deep learning for image caption generation, this task remains highly challenging in a medical setting. Research has mainly focused on the design of tailored machine learning methods for this task, while little attention has been devoted to the development of evaluation metrics to assess the quality of AI-generated documents. Conventional quality metrics for natural language processing methods like the popular BLEU score, provide little information about the quality of the diagnostic content of AI-generated radiology reports. In particular, because radiology reports often use standardized sentences, BLEU scores of generated reports can be high while they lack diagnostically important information. We investigate this problem and propose a new measure that quantifies the diagnostic content of AI-generated radiology reports. In addition, we exploit the standardization of reports by generating a sequence of sentences. That is, instead of using a dictionary of words, as current image captioning methods do, we use a dictionary of sentences. The assumption underlying this choice is that radiologists use a well-focused vocabulary of 'standard' sentences, which should suffice for composing most reports. As a by-product, a significant training speed-up is achieved compared to models trained on a dictionary of words. Overall, results of our investigation indicate that standard validation metrics for AI-generated documents are weakly correlated with the diagnostic content of the reports. Therefore, these measures should be not used as only validation metrics, and measures evaluating diagnostic content should be preferred in such a medical context.

Generalized Convolution Spectral Mixture for Multitask Gaussian Processes.

Multitask Gaussian processes (MTGPs) are a powerful approach for modeling dependencies between multiple related tasks or functions for joint regression. Current kernels for MTGPs cannot fully model nonlinear task correlations and other types of dependencies. In this article, we address this limitation. We focus on spectral mixture (SM) kernels and propose an enhancement of this type of kernels, called multitask generalized convolution SM (MT-GCSM) kernel. The MT-GCSM kernel can model nonlinear task correlations and dependence between components, including time and phase delay dependence. Each task in MT-GCSM has its GCSM kernel with its number of convolution structures, and dependencies between all components from different tasks are considered. Another constraint of current kernels for MTGPs is that components from different tasks are aligned. Here, we lift this constraint by using inner and outer full cross convolution between a base component and the reversed complex conjugate of another base component. Extensive experiments on two synthetic and three real-life data sets illustrate the difference between MT-GCSM and previous SM kernels as well as the practical effectiveness of MT-GCSM.

Multioutput Convolution Spectral Mixture for Gaussian Processes.

Multioutput Gaussian processes (MOGPs) are an extension of Gaussian processes (GPs) for predicting multiple output variables (also called channels/tasks) simultaneously. In this article, we use the convolution theorem to design a new kernel for MOGPs by modeling cross-channel dependencies through cross convolution of time-and phase-delayed components in the spectral domain. The resulting kernel is called multioutput convolution spectral mixture (MOCSM) kernel. The results of extensive experiments on synthetic and real-life data sets demonstrate the advantages of the proposed kernel and its state-of-the-art performance. MOCSM enjoys the desirable property to reduce to the well-known spectral mixture (SM) kernel when a single channel is considered. A comparison with the recently introduced multioutput SM kernel reveals that this is not the case for the latter kernel, which contains quadratic terms that generate undesirable scale effects when the spectral densities of different channels are either very close or very far from each other in the frequency domain.

Effectiveness of Intra-Arterial Aneurysm Sac Embolization for Type Ia Endoleak after Endovascular Aneurysm Repair.

PURPOSE: To evaluate the effectiveness and durability of intra-arterial aneurysm sac embolization for the treatment of type Ia endoleak after endovascular aneurysm repair (EVAR). MATERIALS AND METHODS: From February 2011 to December 2016, 22 patients underwent embolization of a type Ia endoleak after EVAR. Four patients (18%) were treated during the index EVAR and 18 (82%) in follow-up. Five patients (23%) were treated urgently and 17 (77%) electively. The embolization was performed with the use of liquid embolic agent, coils, and/or plugs. Adjunctive neck procedures were performed in 55% (n = 12) of the patients. The primary endpoint of this study was freedom from sac enlargement. Key secondary endpoints were technical success and freedom from endoleak-related reinterventions. RESULTS: Technical success was 100%. The 30-day mortality was 5% (n = 1; acute coronary syndrome). At a mean follow-up of 15.4 months (range 0.1-65.4) the freedom from sac enlargement rate was 76% (16 out of 21). Reintervention-free survival rates at 6, 12, and 24 months were 80%, 68% and 68%, respectively. CONCLUSIONS: In patients with persistent type Ia endoleak the embolization of the aneurysm sac with or without adjunctive neck procedures can be safely performed, leading to acceptable clinical and radiologic outcomes.

Changes in retinal flow density measured by optical coherence tomography angiography in patients with carotid artery stenosis after carotid endarterectomy.

The aim of the study presented here was to evaluate retinal and optic nerve head (ONH) perfusion in patients with severe asymptomatic carotid artery stenosis (CAS) compared with healthy controls and to analyze the impact of carotid endarterectomy using optical coherence tomography angiography (OCT-A). 25 eyes of 25 patients with CAS (study group) and 25 eyes of 25 healthy controls (control group) were prospectively included in this study. OCT-A was performed using RTVue XR Avanti (Optovue, Inc, Fremont, California, USA). The flow density data in the superficial and deep retinal OCT-angiogram of the macula and in the radial peripapillary capillary network (RPC) of the ONH were extracted and analyzed. The flow density in the superficial retinal OCT angiogram of the macula and in the ONH were significantly lower in the study group compared with the control group (macula: p = 0.003) (ONH: p = 0.013). The flow density in the ONH improved significantly after carotid endarterectomy (p = 0.004). A reduced flow density was observed in patients with CAS when compared with healthy controls. The flow density also improved after carotid endarterectomy. Quantitative changes in the microvascular density, as measured using OCT-A, could well be useful in the diagnosis of CAS and the evaluation of therapy success.

Novelty Detection using Deep Normative Modeling for IMU-Based Abnormal Movement Monitoring in Parkinson's Disease and Autism Spectrum Disorders.

Detecting and monitoring of abnormal movement behaviors in patients with Parkinson's Disease (PD) and individuals with Autism Spectrum Disorders (ASD) are beneficial for adjusting care and medical treatment in order to improve the patient's quality of life. Supervised methods commonly used in the literature need annotation of data, which is a time-consuming and costly process. In this paper, we propose deep normative modeling as a probabilistic novelty detection method, in which we model the distribution of normal human movements recorded by wearable sensors and try to detect abnormal movements in patients with PD and ASD in a novelty detection framework. In the proposed deep normative model, a movement disorder behavior is treated as an extreme of the normal range or, equivalently, as a deviation from the normal movements. Our experiments on three benchmark datasets indicate the effectiveness of the proposed method, which outperforms one-class SVM and the reconstruction-based novelty detection approaches. Our contribution opens the door toward modeling normal human movements during daily activities using wearable sensors and eventually real-time abnormal movement detection in neuro-developmental and neuro-degenerative disorders.

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.

The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in computer vision, but they lack the natural ability to incorporate the anatomical location in their decision making process, hindering success in some medical image analysis tasks. In this paper, to integrate the anatomical location information into the network, we propose several deep CNN architectures that consider multi-scale patches or take explicit location features while training. We apply and compare the proposed architectures for segmentation of white matter hyperintensities in brain MR images on a large dataset. As a result, we observe that the CNNs that incorporate location information substantially outperform a conventional segmentation method with handcrafted features as well as CNNs that do not integrate location information. On a test set of 50 scans, the best configuration of our networks obtained a Dice score of 0.792, compared to 0.805 for an independent human observer. Performance levels of the machine and the independent human observer were not statistically significantly different (p-value = 0.06).

Specifying the molecular pattern of sporadic parathyroid tumorigenesis-The Y282D variant of the GCM2 gene.

OBJECTIVE: Sporadic carcinoma of the parathyroid glands is a rare malignant neoplasia. The GCM2 gene encodes a transcription factor that is crucial to embryonic parathyroid development. The Y282D variant of GCM2 exhibits increased transcriptional activity, and the presence of this variant is significantly associated with a higher prevalence of primitive hyperparathyroidism. The present study investigated the prevalence of the Y282D variant of the GCM2 gene and its association with clinical parameters in patients with a definitive histological diagnosis of sporadic parathyroid carcinoma (SPC) or atypical adenoma (AA).