Specific features of designing a database for neuro-oncological 3D MRI images to be used in training artificial intelligence

The research was aimed at analyzing current approaches to the organization and design methodology of visualization database built on the basis of computer vision. Such approaches are necessary for effective development of diagnostic systems using artificial intelligence (AI). A training data set of high quality is a mandatory prerequisite for that. Material and methods. The paper presents the technology for designing an annotated database (SBT Dataset) that contains about 1000 clinical cases based on the archived data acquired by the Federal Neurosurgical Center, Novosibirsk, Russia including data on patients with astrocytoma, glioblastoma, meningioma, neurinoma, and patients with metastases of somatic tumors. Each case is represented by a preoperative MRI. The Results and Discussion. The dataset was built (SBT Dataset) containing segmented 3D MRI images of 5 types of brain tumors with 991 verified observations. Each case is represented by four MRI sequences T1-WI, T1C (with Gd-contrast), T2-WI and T2-FLAIR with histological and histochemical postoperative confirmation. Tumors segmentation with verification of the tumor core elements boundaries and perifocal edema was approved by two certified experienced neuroradiologists. Conclusion. The database built during the research is comparable in its volume and quality (verification level) with the state-of-the-art databases. The methodological approaches proposed in this paper were focused on designing the high-quality medical computer vision systems. The database was used to create artificial intelligence systems with the “physician assistant” functions for preoperative MRI diagnostics in neurosurgery

СВОЙСТВА ДЕМИНЕРАЛИЗОВАННОГО КОСТНОГО МАТРИКСА ДЛЯ БИОИНЖЕНЕРИИ ТКАНЕЙ

The purpose. Determination of tissues of physico-mechanical properties of demineralized bone matrix of spongy and compact human bone important for bioengineering.Material and Methods.The methods for studying micromorphological, piezoelectric and transport properties, adapted for measuring the materials of potential scaffolds.Results. The results of studying the physico-mechanical properties of the demineralized bone matrix of spongy and compact human bones are presented. It is shown that the demineralized spongy bone possesses the best characteristics of the pore system for the colonization of matrix cells. The tensile strength and modulus of elasticity of samples from the demineralized heads of the femurs extracted during the initial hip arthroplasty vary widely. The modulus of elasticity varied from 50 to 250 MPa, and the ultimate strength was from 1.1 to 5.5 MPa.Conclusion. Methods for measuring micromorphological, piezoelectric and transport properties for materials of potential matrices were developed and / or adapted. It is shown that in the samples of materials from the human bone, these characteristics, as a rule, vary considerably. Proceeding from this, it becomes obvious that the development of protocols of measurement methods of the above listed properties is an important work for the creation of technology of bioengineering of tissue implants for reconstructive surgery. Цель. Определение значимых для биоинженерии тканей физико-механических свойств деминерализованного костного матрикса губчатой и компактной кости человека.Материалы и методы. Перечислены методы исследования микроморфологических, пьезоэлектрических и транспортных свойств, адаптированные для измерения у материалов потенциальных матриц.Результаты. Приведены результаты исследования физико-механических свойств деминерализованного костного матрикса губчатой и компактной кости человека. Показано, что деминерализованная губчатая кость обладает наилучшими характеристиками поровой системы для заселения матриксов клетками. Предел прочности и модуль упругости образцов из деминерализованных головок бедренных костей, извлеченных в ходе первичного эндопротезирования тазобедренного сустава, изменяются в широких пределах. Модуль упругости изменялся от 50 до 250 МПа, а предел прочности – от 1,1 до 5,5 МПа.Заключение. Были отработаны и/или адаптированы методы измерений микроморфологических, пьезоэлектрических и транспортных свойств у материалов потенциальных матриц. Показано, что у образцов материалов из кости человека данные характеристики, как правило, значительно варьируют. Исходя из этого, становится очевидным, что отработка протоколов методов измерения вышеперечисленных свойств является важной работой для создания технологии биоинженерии тканевых имплантатов для восстановительной хирургии.

AN L-SYSTEM FOR MODELING OF UNIDIMENSIONALLY GROWING FLAT PLANT TISSUES

In this work, a mathematical model and its implementation are proposed for computational simulation of one-dimensional symplastic growth of tissues. We modified the formal grammar of differential L-systems, and in this grammar, we described a dynamic model of symplastic growth with regard to its biomechanics. The results of the simulation of linear leaf blade growth are compared with those for a free-growing cell population. It is shown that in the model proposed symplastic growth causes a greater deviation of the actual cell length from its isosmotic length than in freely growing cells

MODELING OF PLANT EMBRYO MORPHODYNAMICS AT EARLY DEVELOPMENTAL STAGES

Embryo morphodynamics at early developmental stages of Arabidopsis thaliana was studied. First, a pipeline was elaborated from confocal microscopy and tissue 3D reconstruction to cell lineage tree reconstruction and numerical simulation of growing embryo mechanics. Tentative results of its use are presented

Software for brain tumor diagnosis on magnetic resonance imaging

BACKGROUND: The main reason for the development and implementation of artificial intelligence (AI) technologies in neuro-oncology is the high prevalence of brain tumors reaching up to 200 cases per 100,000 population. The incidence of a primary focus in the brain is 5%10%; however, 60%70% of those who die from malignant neoplasms have metastases in the brain. Magnetic resonance imaging (MRI) is the most common method for primary non-invasive diagnosis of brain tumors and monitoring disease progression. One of the challenges is the classification of tumor types and determination of clinical parameters (size and volume) for the conduct, diagnosis, and treatment procedures, including surgery. AIM: To develope a software module for the differential diagnosis of brain neoplasms on MRI images. METHODS: The software module is based on the developed Siberian Brain Tumor Dataset (SBT), which contains information on over 1000 neurosurgical patients with fully verified (histologically and immunohistochemically) postoperative diagnoses. The data for research and development was presented by the Federal Neurosurgical Center (Novosibirsk). The module uses two- and three-dimensional computer vision models with pre-processed MRI sequence data included in the following packages: pre-contrast T1-weighted image (WI), post-contrast T1-WI, T2-WI, and T2-WI with fluid-attenuated inversion-recovery technique. The models allow to detect and recognize with high accuracy 4 types of neoplasms, such as meningioma, neurinoma, glioblastoma, and astrocytoma, and segment and distinguish components and sizes: ET (tumor core absorbing Gd-containing contrast), TC (tumor core) = ET + Necr (necrosis) + NenTu, and WT (whole tumor) = TC + Ed (peritumoral edema). RESULTS: The developed software module shows high segmentation results on SBT by Dice metric for ET 0.846, TC 0.867, WT 0.9174, Sens 0.881, and Spec 1.000 areas. The testing and validation were done at the international BraTS Challenge 2021 competition. The test dataset yielded DiceET 0.86588, DiceTC 0.86932, and DiceWT 0.921 values, placing the developed software module in the top ten. According to the classification, the results demonstrate high accuracy rates of up to 92% in patient analysis (up to 89% in slice analysis), a very high potential, and a perspective for future research in this area. CONCLUSIONS: The developed software module may be used for training specialists and in clinical diagnostics