Publications by authors named "E S Akhmad"

4 Publications

  • Page 1 of 1

Chest MRI of patients with COVID-19.

Magn Reson Imaging 2021 06 13;79:13-19. Epub 2021 Mar 13.

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department, Moscow, Russia. Electronic address:

During the pandemic of novel coronavirus infection (COVID-19), computed tomography (CT) showed its effectiveness in diagnosis of coronavirus infection. However, ionizing radiation during CT studies causes concern for patients who require dynamic observation, as well as for examination of children and young people. For this retrospective study, we included 15 suspected for COVID-19 patients who were hospitalized in April 2020, Russia. There were 4 adults with positive polymerase chain reaction (PCR) test for COVID-19. All patients underwent magnetic resonance imaging (MRI) examinations using MR-LUND PROTOCOL: Single-shot Fast Spin Echo (SSFSE), LAVA 3D and IDEAL 3D, Echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and Fast Spin Echo (FSE) T2 weighted imaging (T2WI). On T2WI changes were identified in 9 (60,0%) patients, on DWI - in 5 (33,3%) patients. In 5 (33,3%) patients lesions of the parenchyma were visualized on T2WI and DWI simultaneously. At the same time, 4 (26.7%) patients had changes in lung tissue only on T2WI. (P(McNemar) = 0,125; OR = 0,00 (95%); kappa = 0,500). In those patients who had CT scan, the changes were comparable to MRI. The results showed that in case of CT is not available, it is advisable to conduct a chest MRI for patients with suspected or confirmed COVID-19. Considering that T2WI is a fluid-sensitive sequence, if imaging for the lung infiltration is required, we can recommend the abbreviated MRI protocol consisting of T2 and T1 WI. These data may be applicable for interpreting other studies, such as thoracic spine MRI, detecting signs of viral pneumonia of asymptomatic patients. MRI can detect features of viral pneumonia.
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http://dx.doi.org/10.1016/j.mri.2021.03.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955570PMC
June 2021

[Artificial intelligence for diagnosis of vertebral compression fractures using a morphometric analysis model, based on convolutional neural networks].

Probl Endokrinol (Mosk) 2020 Oct 24;66(5):48-60. Epub 2020 Oct 24.

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies.

Background: Pathological low-energy (LE) vertebral compression fractures (VFs) are common complications of osteoporosis and predictors of subsequent LE fractures. In 84% of cases, VFs are not reported on chest CT (CCT), which calls for the development of an artificial intelligence-based (AI) assistant that would help radiology specialists to improve the diagnosis of osteoporosis complications and prevent new LE fractures.

Aims: To develop an AI model for automated diagnosis of compression fractures of the thoracic spine based on chest CT images.

Materials And Methods: Between September 2019 and May 2020 the authors performed a retrospective sampling study of ССТ images. The 160 of results were selected and anonymized. The data was labeled by seven readers. Using the morphometric analysis, the investigators received the following metric data: ventral, medial and dorsal dimensions. This was followed by a semiquantitative assessment of VFs degree. The data was used to develop the Comprise-G AI mode based on CNN, which subsequently measured the size of the vertebral bodies and then calculates the compression degree. The model was evaluated with the ROC curve analysis and by calculating sensitivity and specificity values.

Results: Formed data consist of 160 patients (a training group - 100 patients; a test group - 60 patients). The total of 2,066 vertebrae was annotated. When detecting Grade 2 and 3 maximum VFs in patients the Comprise-G model demonstrated sensitivity - 90,7%, specificity - 90,7%, AUC ROC - 0.974 on the 5-FOLD cross-validation data of the training dataset; on the test data - sensitivity - 83,2%, specificity - 90,0%, AUC ROC - 0.956; in vertebrae demonstrated sensitivity - 91,5%, specificity - 95,2%, AUC ROC - 0.981 on the cross-validation data; for the test data sensitivity - 79,3%, specificity - 98,7%, AUC ROC - 0.978.

Conclusions: The Comprise-G model demonstrated high diagnostic capabilities in detecting the VFs on CCT images and can be recommended for further validation.
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http://dx.doi.org/10.14341/probl12605DOI Listing
October 2020

Diffusion processes modeling in magnetic resonance imaging.

Insights Imaging 2020 Apr 28;11(1):60. Epub 2020 Apr 28.

Central Institute of Traumatology and Orthopaedics named after N. N. Priorov, 10, ul. Priorova, Moscow, 127299, Russia.

Background: The paper covers modern approaches to the evaluation of neoplastic processes with diffusion-weighted imaging (DWI) and proposes a physical model for monitoring the primary quantitative parameters of DWI and quality assurance. Models of hindered and restricted diffusion are studied.

Material And Method: To simulate hindered diffusion, we used aqueous solutions of polyvinylpyrrolidone with concentrations of 0 to 70%. We created siloxane-based water-in-oil emulsions that simulate restricted diffusion in the intracellular space. To obtain a high signal on DWI in the broadest range of b values, we used silicon oil with high T: cyclomethicone and caprylyl methicone. For quantitative assessment of our phantom, we performed DWI on 1.5T magnetic resonance scanner with various fat suppression techniques. We assessed water-in-oil emulsion as an extracorporeal source signal by simultaneously scanning a patient in whole-body DWI sequence.

Results: We developed phantom with control substances for apparent diffusion coefficient (ADC) measurements ranging from normal tissue to benign and malignant lesions: from 2.29 to 0.28 mm/s. The ADC values of polymer solutions are well relevant to the mono-exponential equation with the mean relative difference of 0.91%.

Conclusion: The phantom can be used to assess the accuracy of the ADC measurements, as well as the effectiveness of fat suppression. The control substances (emulsions) can be used as a body marker for quality assurance in whole-body DWI with a wide range of b values.
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http://dx.doi.org/10.1186/s13244-020-00863-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188746PMC
April 2020

[Application of a modified Time-SLIP MRI sequence for visualization of cerebrospinal fluid movement in the cerebral aqueduct and cervical spinal canal].

Zh Vopr Neirokhir Im N N Burdenko 2019 ;83(6):64-71

Research Institute of Healthcare Organization and Medical Management, Department of Health Care of Moscow, Moscow, Russia.

Direct visualization of rapid cerebrospinal fluid movements is a topical task of neurosurgery, which has applications such as evaluating hydrocephalus and the effectiveness of 3rd ventriculostomy.

Purpose: The study purpose was to evaluate the capabilities of a modified Time-SLIP pulse MRI sequence for visualization of fluid (CSF) movements in the phantom, healthy subject, and patient.

Material And Methods: The study was performed in a phantom simulating pulsed CSF movements, healthy volunteers (9 people), and patients without impaired CSF dynamics (12 people), whose data were used to determine mean CSF flow parameters, as well as in 1 patient after 3rd ventriculostomy. A 1.5 T MRI instrument was used. The Time-SLIP parameters were as follows: TR = 8,500 ms; TEeff = 80 ms; Thk = 5.0 mm; tag spacing = 30 mm; NEX 7; inversion time (BBTI) = 2,000/3,000 ms; no cardiosynchronization. Scanning time was 2:16 min. The estimated parameter was the length of motion (LOM) of CSF.

Results: According to a study on a phantom simulating various conditions of oscillatory fluid motion, the mean LOM determination error in the modified Time-SLIP mode was 20%. This technique provided the following LOM data for the cerebral aqueduct (median, 25-75% quartiles): 13.0 (9.5-16.0) mm for BBTI of 2,000ms and 30.2 (23.7-35.3) mm for BBTI of 3,000 ms, i.e. 2.3-fold higher. This difference may be explained by an intense turbulent current leading to rapid CSF exchange between the 3rd and 4th ventricles and prolonged CSF movement during several heart contractions. Quantitative parameters of CSF movement at the C1-C2 level were determined. Additionally, Time-SLIP was used to evaluate performance of a third ventricle fistula.

Conclusion: We have proposed a modified Time-SLIP pulse sequence that does not require cardiosynchronization. The mean relative error in determining the CSF movement distance was 20%. The mean quantitative parameters of CSF movement in the cerebral aqueduct and at the C1-C2 level were obtained. Turbulent CSF flow is found in the cerebral aqueduct, which leads to rapid exchange between the 3rd and 4th ventricles.
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http://dx.doi.org/10.17116/neiro20198306164DOI Listing
March 2020
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