With the ongoing COVID-19 pandemic decreasing availability of polymerase chain reaction with reverse transcription and the snowballing growth of medical imaging, especially the number of chest computed tomography (CT) scans being performed, methods to augment and automate the image analysis, increasing productivity and minimizing human error are of particular importance. The creation of high-quality datasets is essential for the development and validation of artificial intelligence algorithms. Such technologies have sufficient accuracy in diagnosing COVID-19 in medical imaging. The presented large-scale dataset contains anonymized human CT scans with COVID-19 features as well as normal studies. Some studies were tagged by radiologists using binary pixel masks of regions of interest (e.g., characteristic areas of consolidation and ground-glass opacities). CT data were acquired between March 1, 2020, and April 25, 2020, and provided by municipal hospitals in Moscow, Russia. The presented dataset is licensed under Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).

В 2017 г. в г. Москве начат проект «Московский скрининг рака легкого» путем применения низкодозной компьютерной томографии (НДКТ), направленный на проведение селективного скрининга злокачественных новообразований (ЗНО) легкого в амбулаторно-поликлиническом звене. Основная задача проекта: повысить выявляемость рака легкого на ранних стадиях и в перспективе снизить смертность от этого заболевания. Цель исследования: оценить значимость случайных находок, выявляемых в процессе селективного скрининга рака легкого методом НДКТ в г. Москве. Материал и методы. В ретроспективное исследование включены случайно отобранные 254 НДКТ, выполненные в рамках программы скрининга. При повторном просмотре изображений и протоколов учитывали все патологические находки (кроме очагов в легких, оцененных по классификации «LungRADS-2014»). Результаты. При анализе распространенности и характера случайных находок, выявляемых при НДКТ-скрининге, установлено, что в большинстве случаев такие находки имеют высокую клиническую и/или прогностическую значимость. Наиболее часто выявляются (% от числа лиц со случайными находками): кальциноз коронарных артерий ‒ 49,3%; утолщение стенок бронхов ‒ 34,9%; бронхоэктазы ‒ 34,9%; эмфизема ‒ 21,6%. При первичных интерпретациях результатов НДКТ недостаточное внимание уделяется описанию патологических изменений, кроме классифицируемых по «Lung RADS-2014» очагов. Требуется дальнейшая научно-методическая работа по организации выявления и обоснованной маршрутизации лиц со случайными находками. Выводы. Случайные находки встречаются в 87,1% случаев при проведении селективного скрининга рака легкого методом НДКТ. Наиболее часто случайные находки локализуются в сердечно-сосудистой (75,4%) и дыхательной (68,3%) системах, при этом они носят клинически и прогностически значимый характер.

The article presents an overview of qualitative and quantitative methods for coronary calcification assessment by computed tomography (CT). Coronary calcium is one of the well-known predictors of coronary artery disease and its complications. Coronary artery calcification is a common significant finding on routine and low-dose CT. In the review, the Coronary Artery Calcium Data and Reporting System (CAC-DRS) and the Coronary Artery Disease Reporting and Data System (CAD-RADS) are analyzed. Recommendations are given for the further management of patients with stable or acute chest pain in accordance with the CAD-RADS classification. The main aim of CAD-RADS is the standardization of accounting for coronary computed tomography angiography (CCTA) results for facilitating the interpretation by clinicians and subsequent management of patients. Such an approach should lead to an increase of healthcare quality.

Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia). Two consecutive scans with CT and LDCT were performed in a single visit. Reading was performed by ten radiologists with 3–25 years’ experience. The study included 230 patients, and statistical analysis showed LDCT with a sharp kernel as the most reliable protocol (percentage agreement 74.35 ± 43.77%), but its advantage was marginal. There was no significant correlation between radiologists’ experience and average percentage agreement for all four evaluated protocols. Regarding the radiation exposure, CTDI_vol was 3.6 ± 0.64 times lower for LDCT. In conclusion, CT and LDCT with soft and sharp reconstructions are equally reliable for COVID-19 reporting using the “CT 0-4” scale. The LDCT protocol allows for a significant decrease in radiation exposure but may be restricted by body mass index.

Rationale. Quantitative CT (QCT) bone densitometry with asynchronous calibration not require a phantom during the scan procedure. Based on calibration data it converts X-ray density in HU to bone mineral density (BMD). Given the large number of CT studies performed on patients at risk of osteoporosis, there is a need for a hands-on method capable of assessing BMD in a short period of time without tailored software or protocols. Goal. To develop a method for QCT bone densitometry using an PHK (PHantom Kalium), to compare the volume BMD measurements with the QCT data with asynchronous calibration provided by software from a reputable developer. Methods. The studies were performed at 64-slice CT unit with body scanning parameters. The BMD was measured using two techniques: 1) QCT with asynchronous calibration using software from a reputable developer; 2) QCT using a PHK phantom (QCT-PHK). For convert the HU to BMD values, we scanned the PHK phantom and calculate correction factor. Phantom contains “vertebrae” filled with potassium hydrogen phosphate in different concentrations. In both methods, the BMD values measured for LI–II, and sometimes for ThXII, LIII. Results. The study enrolled 65 subjects (11 male and 54 female patients); median age 69.0 years. A comparison of the vertebrae BMD measured by QCT and QCT-PHK revealed a significant linear Pearson correlation r = 0.977 (p < 0.05). The Bland–Altman analysis demonstrated a lack of relationship between the difference in measurements and the average BMD and a systematic BMD; bias of +4.50 mg/ml in QCT vs. QCT-PHK. Differences in the division into groups osteoporosis / osteopenia / norm according to the ACR criteria for the two methods were not significant. Conclusion. The developed asynchronous QCT-PHK method measure BMD comparable to the widely used QCT with asynchronous calibration. This method can be used for opportunistic screening for osteoporosis.