Efficient automatic correction and segmentation based 3D visualization of magnetic resonance images

In the recent years, the demand for automated processing techniques for digital medical image volumes has increased substantially. Existing algorithms, however, still often require manual interaction, and newly developed automated techniques are often intended for a narrow segment of processing needs. The goal of this research was to develop algorithms suitable for fast and effective correction and advanced visualization of digital MR image volumes with minimal human operator interaction. This research has resulted in a number of techniques for automated processing of MR image volumes, including a novel MR inhomogeneity correction algorithm derivative surface fitting (dsf), automatic tissue detection algorithm (atd), and a new fast technique for interactive 3D visualization of segmented volumes called gravitational shading (gs). These newly developed algorithms provided a foundation for the automated MR processing pipeline incorporated into the UniViewer medical imaging software developed in our group and available to the public. This allowed the extensive testing and evaluation of the proposed techniques. Dsf was compared with two previously published methods on 17 digital image volumes. Dsf demonstrated faster correction speeds and uniform image quality improvement in this comparison. Dsf was the only algorithm that did not remove anatomic detail. Gs was compared with the previously published algorithm fsvr and produced rendering quality improvement while preserving real-time frame-rates. These results show that the automated pipeline design principles used in this dissertation provide necessary tools for development of a fast and effective system for the automated correction and visualization of digital MR image volumes

Clinical and morphological characteristics of myocardial infarction, developed after operations on the heart and lurge vessels

The aim of this study was to investigate the leading causes of the development of postoperative acute myocardial infarction and assess their significance in tanatogeneze. The foundation works as a clinical pathoanatomical comparisons carried out in 23 cases of death after adult cardiac operations in the offices and Vascular Surgery of Chelyabinsk Oblast Hospital for the period 2005-2007 d. It was found that the development of intra- and postoperative myocardial infarction in cardiosurgery practice is the result of a complex set of causal factors leading to the absolute coronary insufficiency. Lead importance here is the nature of the surgical pathology of the heart and large vessels, the actual surgery, the presence of risk factors such as angina, hypertension, diabetes mellitus.Целью исследования являлось изучение ведущих причин развития острых послеоперационных инфарктов миокарда и оценка их значимости в танатогенезе. Основой работы послужили клинико- атологоанатомические сопоставления, проведенные в 23 случаях смерти взрослых после операций в отделениях кардиохирургии и сосудистой хирургии Челябинской областной клинической больницы за период 2005-2007 гг. Установлено, что развитие интра- и послеоперационных инфарктов миокарда в кардиохирургической практике является следствием сложного комплекса причинных факторов, приводящих к абсолютной коронарной недостаточности. Ведущее значение здесь имеет характер хирургической патологии сердца и крупных сосудов, собственно оперативное вмешательство, наличие таких факторов риска как стенокардия, гипертоническая болезнь, сахарный диабет

A feasibility study to evaluate early treatment response of brain metastases one week after stereotactic radiosurgery using perfusion weighted imaging

BACKGROUND: To explore if early perfusion-weighted magnetic resonance imaging (PWI) may be a promising imaging biomarker to predict local recurrence (LR) of brain metastases after stereotactic radiosurgery (SRS). METHODS: This is a prospective pilot study of adult brain metastasis patients who were treated with SRS and imaged with PWI before and 1 week later. Relative cerebral blood volume (rCBV) parameter maps were calculated by normalizing to the mean value of the contralateral white matter on PWI. Cox regression was conducted to explore factors associated with time to LR, with Bonferroni adjusted p\u3c0.0006 for multiple testing correction. LR rates were estimated with the Kaplan-Meier method and compared using the log-rank test. RESULTS: Twenty-three patients were enrolled from 2013 through 2016, with 22 evaluable lesions from 16 patients. After a median follow-up of 13.1 months (range: 3.0-53.7), 5 lesions (21%) developed LR after a median of 3.4 months (range: 2.3-5.7). On univariable analysis, larger tumor volume (HR 1.48, 95% CI 1.02-2.15, p = 0.04), lower SRS dose (HR 0.45, 95% CI 0.21-0.97, p = 0.04), and higher rCBV at week 1 (HR 1.07, 95% CI 1.003-1.14, p = 0.04) had borderline association with shorter time to LR. Tumors \u3e2.0cm3 had significantly higher LR than if ≤2.0cm3: 54% vs 0% at 1 year, respectively, p = 0.008. A future study to confirm the association of early PWI and LR of the high-risk cohort of lesions \u3e2.0cm3 is estimated to require 258 patients. CONCLUSIONS: PWI at week 1 after SRS may have borderline association with LR. Tumors \u3c2.0cm3 have low risk of LR after SRS and may be low-yield for predictive biomarker studies. Information regarding sample size and potential challenges for future imaging biomarker studies may be gleaned from this pilot study

De-identification procedures for magnetic resonance images and the impact on structural brain measures at different ages

Surface rendering of MRI brain scans may lead to identification of the participant through facial characteristics. In this study, we evaluate three methods that overwrite voxels containing privacy-sensitive information: Face Masking, FreeSurfer defacing, and FSL defacing. We included structural T1-weighted MRI scans of children, young adults and older adults. For the young adults, test-retest data were included with a 1-week interval. The effects of the de-identification methods were quantified using different statistics to capture random variation and systematic noise in measures obtained through the FreeSurfer processing pipeline. Face Masking and FSL defacing impacted brain voxels in some scans especially in younger participants. FreeSurfer defacing left brain tissue intact in all cases. FSL defacing and FreeSurfer defacing preserved identifiable characteristics around the eyes or mouth in some scans. For all de-identification methods regional brain measures of subcortical volume, cortical volume, cortical surface area, and cortical thickness were on average highly replicable when derived from original versus de-identified scans with average regional correlations \u3e.90 for children, young adults, and older adults. Small systematic biases were found that incidentally resulted in significantly different brain measures after de-identification, depending on the studied subsample, de-identification method, and brain metric. In young adults, test-retest intraclass correlation coefficients (ICCs) were comparable for original scans and de-identified scans with average regional ICCs \u3e.90 for (sub)cortical volume and cortical surface area and ICCs \u3e.80 for cortical thickness. We conclude that apparent visual differences between de-identification methods minimally impact reliability of brain measures, although small systematic biases can occur

Ragweed pollen rain impact on allergy rate and severity in Krasnodar: a three-year non-randomised controlled study

Background. The main hay fever agent in Krasnodar Krai is ragweed pollen (Ambrosia gen.). An important alerting guide for medical practitioners and allergic citizens is the seasonal anthetic calendar and pollen peak times.Objectives. Obtaining of relevant data on ragweed pollen air contamination rate in Krasnodar in a three-year-dynamics (2018–2020) to estimate the anthetic activity correlation with abiotic and anthropogenic factors and the role of pollen indicators in allergic morbidity.Methods. We surveyed the daily average ragweed pollen values in Krasnodar air. Allergic medical visits were analysed in terms of the ragweed anthetic activity and pollen air contamination of the city.Results. A maximal daily average ragweed pollen peak occurs in August: 663.35 p.g./m3 in 2018, 209.89 p.g./m3 in 2019, 80.62 p.g./m3 in 2020. Numbers of medical visits for pollinosis per a selected municipal medical facility: 314 in 2018, 335 in 2019 and 146 in 2020, with a peak period in September--October. Analyses of the air pollution impact on ragweed pollen production revealed a correlation between the pollen rate and values of CO (correlation coefficient r-0.356), NH3 (r-0.198) and dust pollution (r-0.361) in July, August, September and October 2018–2020.Conclusion. Analyses of climatic factors uncovered clear patterns: strongest anthesis corresponds to minimal humidity (<60%), the pollen grain content diminishes with lower humidities dropping to minimal with precipitations and increases at temperatures 20 °C and above. No significant dependency was observed between air pollution and the allergic pollen content. Anthesis in ragweed moderately correlates with the rate of medical visits

Optimal approaches to analyzing functional MRI data in glioma patients

BACKGROUND: Resting-state fMRI is increasingly used to study the effects of gliomas on the functional organization of the brain. A variety of preprocessing techniques and functional connectivity analyses are represented in the literature. However, there so far has been no systematic comparison of how alternative methods impact observed results. NEW METHOD: We first surveyed current literature and identified alternative analytical approaches commonly used in the field. Following, we systematically compared alternative approaches to atlas registration, parcellation scheme, and choice of graph-theoretical measure as regards differentiating glioma patients (N = 59) from age-matched reference subjects (N = 163). RESULTS: Our results suggest that non-linear, as opposed to affine registration, improves structural match to an atlas, as well as measures of functional connectivity. Functionally- as opposed to anatomically-derived parcellation schemes maximized the contrast between glioma patients and reference subjects. We also demonstrate that graph-theoretic measures strongly depend on parcellation granularity, parcellation scheme, and graph density. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: Our current work primarily focuses on technical optimization of rs-fMRI analysis in glioma patients and, therefore, is fundamentally different from the bulk of papers discussing glioma-induced functional network changes. We report that the evaluation of glioma-induced alterations in the functional connectome strongly depends on analytical approaches including atlas registration, choice of parcellation scheme, and graph-theoretical measures

Mapping language function with task-based vs. resting-state functional MRI

BACKGROUND: Use of functional MRI (fMRI) in pre-surgical planning is a non-invasive method for pre-operative functional mapping for patients with brain tumors, especially tumors located near eloquent cortex. Currently, this practice predominantly involves task-based fMRI (T-fMRI). Resting state fMRI (RS-fMRI) offers an alternative with several methodological advantages. Here, we compare group-level analyses of RS-fMRI vs. T-fMRI as methods for language localization. PURPOSE: To contrast RS-fMRI vs. T-fMRI as techniques for localization of language function. METHODS: We analyzed data obtained in 35 patients who had both T-fMRI and RS-fMRI scans during the course of pre-surgical evaluation. The RS-fMRI data were analyzed using a previously trained resting-state network classifier. The T-fMRI data were analyzed using conventional techniques. Group-level results obtained by both methods were evaluated in terms of two outcome measures: (1) inter-subject variability of response magnitude and (2) sensitivity/specificity analysis of response topography, taking as ground truth previously reported maps of the language system based on intraoperative cortical mapping as well as meta-analytic maps of language task fMRI responses. RESULTS: Both fMRI methods localized major components of the language system (areas of Broca and Wernicke) although not with equal inter-subject consistency. Word-stem completion T-fMRI strongly activated Broca\u27s area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system. CONCLUSION: We demonstrate several advantages of classifier-based mapping of language representation in the brain. Language T-fMRI activated task-general (i.e., not language-specific) functional systems in addition to areas of Broca and Wernicke. In contrast, classifier-based analysis of RS-fMRI data generated maps confined to language-specific regions of the brain

De‐identification procedures for magnetic resonance images and the impact on structural brain measures at different ages

Surface rendering of MRI brain scans may lead to identification of the participant through facial characteristics. In this study, we evaluate three methods that overwrite voxels containing privacy‐sensitive information: Face Masking, FreeSurfer defacing, and FSL defacing. We included structural T1‐weighted MRI scans of children, young adults and older adults. For the young adults, test–retest data were included with a 1‐week interval. The effects of the de‐identification methods were quantified using different statistics to capture random variation and systematic noise in measures obtained through the FreeSurfer processing pipeline. Face Masking and FSL defacing impacted brain voxels in some scans especially in younger participants. FreeSurfer defacing left brain tissue intact in all cases. FSL defacing and FreeSurfer defacing preserved identifiable characteristics around the eyes or mouth in some scans. For all de‐identification methods regional brain measures of subcortical volume, cortical volume, cortical surface area, and cortical thickness were on average highly replicable when derived from original versus de‐identified scans with average regional correlations >.90 for children, young adults, and older adults. Small systematic biases were found that incidentally resulted in significantly different brain measures after de‐identification, depending on the studied subsample, de‐identification method, and brain metric. In young adults, test–retest intraclass correlation coefficients (ICCs) were comparable for original scans and de‐identified scans with average regional ICCs >.90 for (sub)cortical volume and cortical surface area and ICCs >.80 for cortical thickness. We conclude that apparent visual differences between de‐identification methods minimally impact reliability of brain measures, although small systematic biases can occur