РАЗРАБОТКА ПРОГРАММНЫХ СРЕДСТВ МАТЕМАТИЧЕСКОГО ИМИТАЦИОННОГО МОДЕЛИРОВАНИЯ НА ОСНОВЕ КЛИНИЧЕСКИХ ДАННЫХ И ФАНТОМНЫХ ИССЛЕДОВАНИЙ ДЛЯ ОЦЕНКИ ПЕРФУЗИИ ГОЛОВНОГО МОЗГА И ПОВЫШЕНИЯ КАЧЕСТВА ИЗОБРАЖЕНИЙ ПРИ ОФЭКТ/КТ С 99MTC-ГМПАО

Abstract

Purpose: To develop a software package Virtual examination of brain perfusion by the method of SPECT/CT with 99mTc-HMPAO (Teoxime) and its practical application to study the conditions for achieving the best image quality in clinical studies of patients. Material and methods: The studies were performed using clinical data and the method of computer simulation. Clinical data of single-photon emission computed tomography combined with X-ray computed tomography (SPECT/CT) with 99mTc-hexamethylpropyleneamine oxime (99mTc-Teoxime, produced by DIAMED LLC) of a patient with an ischemic stroke of the right frontal cortex were obtained on a two-detector gamma-camera NM/CT 670 DR GE Discovery (USA) using high-resolution low-energy collimators (LEHR). The measured data were processed using specialized software Q.Brain and Q.Volumetrix MI on a Xeleris 4.0 DR workstation from GE Healthcare (USA) to obtain reconstructed axial tomographic slices. To carry out simulation computer simulation of the procedure of examination of perfusion of GM by the method of SPECT/CT has developed a software package that includes a mathematical Hoffman phantom with the ability to simulate clinical cases of hypoperfusion of different localization and size (Virtual Patient), modeling the collection of “raw” projection data and an image reconstruction program based on the OSEM algorithm (Ordered Subset Expectation Maximization). An important advantage of the mathematical modeling method is the ability to assess the quality of the reconstructed image by calculating the root-mean-square error when compared with a given phantom. In numerical experiments, the dependence of the reconstruction error on the parameters of the OSEM algorithm (on the number of subgroups – subsets, and on the number of iterations) was investigated in order to determine the conditions for achieving the best image quality. A statistical stop criterion was developed and tested. Results: For the first time, a software package was developed and tested that allows us to investigate errors in the reconstruction algorithm, which is a great difficulty when using clinical research methods. A criterion for stopping iterations is proposed when using the OSEM reconstruction algorithm – minimizing the functional deviation of the chi-square function from the target value, while the detector pixels with non-zero values are combined into blocks according to the 2×2 scheme. There is a reliable good correlation between the proposed stop criterion and the minimum of the root-mean-square error of image reconstruction. This makes it possible to introduce this criterion into the clinical practice of using computational tools for reconstructing sections of the SPECT to obtain the best image. The simulation results demonstrated the possibility of reducing the time of data recording, during which the patient must remain motionless, at least twice. Conclusion: The method of computer simulation developed in this work is a practically useful technology that helps optimize the use of SPECT to achieve the best possible results of brain imaging in patients.