Design and Implementation of a Cloud PACS Architecture.

The limitations of the classic PACS (picture archiving and communication system), such as the backward-compatible DICOM network architecture and poor security and maintenance, are well-known. They are challenged by various existing solutions employing cloud-related patterns and services. However, a full-scale cloud-native PACS has not yet been demonstrated. The paper introduces a vendor-neutral cloud PACS architecture. It is divided into two main components: a cloud platform and an access device. The cloud platform is responsible for nearline (long-term) image archive, data flow, and backend management. It operates in multi-tenant mode. The access device is responsible for the local DICOM (Digital Imaging and Communications in Medicine) interface and serves as a gateway to cloud services. The cloud PACS was first implemented in an Amazon Web Services environment. It employs a number of general-purpose services designed or adapted for a cloud environment, including Kafka, OpenSearch, and Memcached. Custom services, such as a central PACS node, queue manager, or flow worker, also developed as cloud microservices, bring DICOM support, external integration, and a management layer. The PACS was verified using image traffic from, among others, computed tomography (CT), magnetic resonance (MR), and computed radiography (CR) modalities. During the test, the system was reliably storing and accessing image data. In following tests, scaling behavior differences between the monolithic Dcm4chee server and the proposed solution are shown. The growing number of parallel connections did not influence the monolithic server's overall throughput, whereas the performance of cloud PACS noticeably increased. In the final test, different retrieval patterns were evaluated to assess performance under different scenarios. The current production environment stores over 450 TB of image data and handles over 4000 DICOM nodes.

Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson's Disease.

Parkinson's disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative movement disorders associated with cognitive dysfunction. The Luria's Alternating Series Test (LAST) is a clinical tool sensitive to both graphomotor problems and perseverative tendencies that may suggest the dysfunction of prefrontal and/or frontostriatal areas and may be used in PD and PSP assessment. It requires the participant to draw a series of alternating triangles and rectangles. In the study, two clinical groups-51 patients with PD and 22 patients with PSP-were compared to 32 neurologically intact seniors. Participants underwent neuropsychological assessment. The LAST was administered in a paper and pencil version, then scanned and preprocessed. The series was automatically divided into characters, and the shapes were recognized as rectangles or triangles. In the feature extraction step, each rectangle and triangle was regarded both as an image and a two-dimensional signal, separately and as a part of the series. Standard and novel features were extracted and normalized using characters written by the examiner. Out of 71 proposed features, 51 differentiated the groups (p < 0.05). A classifier showed an accuracy of 70.5% for distinguishing three groups.

Immunogenicity of the BNT162b2 mRNA COVID-19 vaccine in older residents of a long-term care facility: relation with age, frailty and prior infection status.

Clinical and biological assessment of the COVID-19 vaccine efficacy in the frail population is of crucial importance. The study focuses on measuring the levels of anti-SARS-CoV-2 IgG antibodies before and after BNT162b2 mRNA COVID-19 vaccination among long-term care facility (LTCF) elderly residents. We conducted a prospective, single-center, observational study among LTCF residents. The study protocol was based on three blood sample acquisitions: first taken at baseline-5 days before the first dose of the vaccine, second-20 days after the first dose, and third-12 days after the second shot of the vaccine. The comparison was made for two cohorts: patients with and without prior COVID-19 infection. The data was collected from January to March 2021. A total number of 78 LTCF residents (55 women and 23 men) aged 62-104, 85.72 ± 7.59 years (mean ± SD), were enrolled in the study. All study participants were investigated for the presence of SARS-CoV-2 anti-spike (S) protein IgG, using a chemiluminescent immunoassay. Frailty was assessed with the Clinical Frailty Scale. Among elderly COVID-19 survivors in LTCF, a single dose of vaccine significantly increased anti-SARS-CoV-2 IgG antibody levels. IgG concentration after a single and double dose was comparable, which may suggest that elderly COVID-19 survivors do not require a second dose of vaccine. For residents without a previous history of COVID-19, two doses are needed to achieve an effective serological response. The level of anti-SARS-CoV-2 IgG antibodies after vaccination with BNT162b2 mRNA COVID-19 did not correlate with the frailty and age of the studied individuals.

Video-based time assessment in 360 degrees turn Berg balance test.

The Great Geriatric Problems include dementia syndromes, locomotion disorders, and falls. In geriatrics, one of the most commonly used methods for assessing the balance of seniors is the Berg Balance Scale (BBS). It is a set of 14 exercises that reflect daily activates. In this paper focused on the 11th Berg Balance Test, a novel method is introduced, based on the time of rotation calculated using the CamShift algorithm. The method is tested on 57 recordings of seniors. The average relative error of presented method is 4.74%, which refers to the average absolute error at the level of 0.83 s.

Leg movement tracking in automatic video-based one-leg stance evaluation.

Falls are a major risk in elder population. Early diagnosis is therefore an important step towards increasing the safety of elders. One of the common diagnostic tests is the Berg Balance Scale (BBS), consisting of 14 exercises arranged from the easiest (sitting-to-standing) to the most demanding (one-leg stance). In this study a novel approach to the automatic assessment of the time in which the patient can remain in the one-leg stance position without loosing balance is introduced. The data is collected using a regular video camera. No markers, special garments, or system calibration are required. Two groups are examined. The first group consists of 16 students: healthy, young adults (12 female, 4 male, avg. 20yrs±1). The second group consists of 50 elders (39 female, 11 male, avg. 78.8yrs±5.9). Data (short, one minute recordings) are collected in a controlled environment using a digital video recorder (50fps, 1920×1080) fixed to a tripod. Data are processed off-line. First, the region of interest is determined. Next, the Kanade-Lucas-Tomasi tracking is performed. Best tracks are selected based on the registered vertical movement and two tracks are obtained corresponding to the left and right leg movements. Tracks are later subjected to the sparse signal baseline estimation, denoising and thresholding to detect the raised leg. Results are compared frame-wise to the ground truth reference obtained in the manual processing procedure. Both legs are evaluated in the elder group (in all cases several attempts featuring both legs were registered), resulting in 89.18%±11.27% DICE, 93.07%±5.43% sensitivity and 96.94%±6.11% specificity values for both legs. The signal of a single leg is evaluated in the student group (in all cases only one attempt was needed to perform the full examination) resulting in 98.96%±1.2% DICE, 98.78%±1.65% sensitivity and 98.73%±2.69% specificity values. This is the first step towards a video-based system enabling the automatic assessment of the four last, most vital tasks of the Berg Balance Scale evaluation.

Frailty phenotype and the role of levodopa challenge test in geriatric inpatients with mild parkinsonian signs.

Deficiency in dopaminergic system function may be one of the hypothetical reasons of the frailty syndrome but its role still remains unclear. The aim of our study was to assess the frailty phenotype prevalence in geriatric inpatients with mild parkinsonian signs (MPS) and to investigate levodopa test in the frail patients with MPS. We examined 118 participants: 90 with MPS and 28 in control group (without MPS). The frailty syndrome presence was evaluated by the Fried criteria. Deficiency in dopaminergic system function was assessed by one of the modifications of an acute levodopa challenge test (LCT): in MPS group every patient was examined by performing Up and Go Test and also Step Test before and 3 h after taking 125 mg of Madopar (levodopa + benserazide). Sixty-nine study subjects (58%) met criteria for frailty. Fifty-five participants in MPS group (61.1% of MPS group) and fourteen (50%) in control group. All of the patients that scored positive in walk speed criterion of frailty were frail. When all MPS patients were considered, the number of components scored positive for frailty was directly related to the walk speed (r = -0.70, p < 0.0001). In MPS group LCT scores were significantly higher for frailty patients compared to non-frailty (p = 0.0027). When all MPS patients were considered, the number of components scored positive for frailty was directly related LCT score (r = 0.37, p = 0.0004). There was a relationship between LCT and walk speed (r = -0.31, p = 0.0032). Our observations provide new information about the relationship between frailty and MPS, suggest the need for increased awareness of frailty in MPS patients and conversely. Our study provides data for a discussion on pathophysiological background of the frailty syndrome (FS), emphasizing the theories of the important impact of dopaminergic system deficit and encourages further research on the role of LCT in measuring it.

Spatial and dynamical handwriting analysis in mild cognitive impairment.

Background and Objectives Standard clinical procedure of Mild Cognitive Impairment (MCI) assessment employs time-consuming tests of psychological evaluation and requires the involvement of specialists. The employment of quantitative methods proves to be superior to clinical judgment, yet reliable, fast and inexpensive tests are not available. This study was conducted as a first step towards the development of a diagnostic tool based on handwriting. Methods In this paper the handwriting sample of a group of 37 patients with MCI (mean age 76.1±5.8) and 37 healthy controls (mean age 74.8±5.7) was collected using a Livescribe Echo Pen while completing three tasks: (1) regular writing, (2) all-capital-letters writing, and (3) single letter multiply repeated. Parameters differentiating both groups were selected in each task. Results Subjects with confirmed MCI needed more time to complete task one (median 119.5s, IQR - interquartile range - 38.1 vs. 95.1s, IQR 29.2 in control and MCI group, p-value <0.05) and two (median 84.2s, IQR 49.2 and 53.7s, IQR 30.5 in control and MCI group) as their writing was significantly slower. These results were associated with a longer time to complete a single stroke of written text. The written text was also noticeably larger in the MCI group in all three tasks (e.g. median height of the text block in task 2 being 22.3mm, IQR 12.9 in MCI and 20.2mm, IQR 8.7 in control group). Moreover, the MCI group showed more variation in the dynamics of writing: longer pause between strokes in task 1 and 2. The all-capital-letters task produced most of the discriminating features. Conclusion Proposed handwriting features are significant in distinguishing MCI patients. Inclusion of quantitative handwriting analysis in psychological assessment may be a step forward towards a fast MCI diagnosis.

Automatic brain tumour detection and neovasculature assessment with multiseries MRI analysis.

In this paper a novel multi-stage automatic method for brain tumour detection and neovasculature assessment is presented. First, the brain symmetry is exploited to register the magnetic resonance (MR) series analysed. Then, the intracranial structures are found and the region of interest (ROI) is constrained within them to tumour and peritumoural areas using the Fluid Light Attenuation Inversion Recovery (FLAIR) series. Next, the contrast-enhanced lesions are detected on the basis of T1-weighted (T1W) differential images before and after contrast medium administration. Finally, their vascularisation is assessed based on the Regional Cerebral Blood Volume (RCBV) perfusion maps. The relative RCBV (rRCBV) map is calculated in relation to a healthy white matter, also found automatically, and visualised on the analysed series. Three main types of brain tumours, i.e. HG gliomas, metastases and meningiomas have been subjected to the analysis. The results of contrast enhanced lesions detection have been compared with manual delineations performed independently by two experts, yielding 64.84% sensitivity, 99.89% specificity and 71.83% Dice Similarity Coefficient (DSC) for twenty analysed studies of subjects with brain tumours diagnosed.

Role of radiologists in CAD life-cycle.

A modern CAD (computer-aided diagnosis) system development involves a multidisciplinary team whose members are experts in medical and technical fields. This study indicates the activities of medical experts at various stages of the CAD design, testing, and implementation. Those stages include a medical analysis of the diagnostic problem, data collection, image analysis, evaluation, and clinical verification. At each stage the physicians knowledge and experience are indispensable. The final implementation involves integration with the existing Picture Archiving and Communication System. The term CAD life-cycle describes an overall process of the design, testing, and implementation of a system that in its final form assists the radiologists in their daily clinical routine. Four CAD systems (applied to the bone age assessment, Multiple Sclerosis detection, lung nodule detection, and pneumothorax measurement) developed in our laboratory are given as examples of how consecutive stages are developed by the multidisciplinary team. Specific advantages of the CAD implementation that include the daily clinical routine as well as research and education activities are discussed.

Kernelized fuzzy c-means method in fast segmentation of demyelination plaques in multiple sclerosis.

Fuzzy c-means method (FCM) is a popular tool for a fuzzy data processing. In the current study, a FCM-based method of fuzzy clustering in a kernel space has been implemented. First, a "kernel trick" is applied to the fuzzy c-means algorithm. Then, the new method is employed for a fast automated segmentation of demyelination plaques in Multiple Sclerosis (MS). The clusters in a Gaussian kernel space are analysed in the histogram context and used during the initial classification of the brain tissue. Received classification masks are then used to detect the region of interest, eliminate false positives and label MS lesions.