Low-dose computed tomography in COVID-19: systematic review

BACKGROUND: The increased number of computed tomography scans during the COVID-19 pandemic has emphasized the task of decreasing radiation exposure of patients, since it is known to be associated with an elevated risk of cancer development. The ALARA (as low as reasonably achievable) principle, proposed by the International Commission on Radiation Protection, should be adhered to in the operation of radiation diagnostics departments, even during the pandemic. AIM: To systematize data on the appropriateness and effectiveness of low-dose computed tomography in the diagnosis of lung lesions in COVID-19. MATERIALS AND METHODS: Relevant national and foreign literature in scientific libraries PubMed and eLIBRARY, using English and Russian queries low-dose computed tomography and COVID-19, published between 2020 and 2022 were analyzed. Publications were evaluated after assessing the relevance to the review topic by title and abstract analysis. The references were further analyzed to identify articles omitted during the search that may meet the inclusion criteria. RESULTS: Published studies summarized the current data on the imaging of COVID-19 lung lesions and the use of computed tomography scans and identified possible options for reducing the effective dose. CONCLUSION: We present techniques to reduce radiation exposure during chest computed tomography and preserve high-quality diagnostic images potentially sufficient for reliable detection of COVID-19 signs. Reducing radiation dose is a valid approach to obtain relevant diagnostic information, preserving opportunities for the introduction of advanced computational analysis technologies in clinical practice

Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study

BACKGROUND: The DutchBelgian Randomized Lung Cancer Screening Trial (NELSON) used a volume-based protocol and significantly reduced the prevalence of false-positive results (2.1%). AIM: To compare the performance of manual linear diameter and semi-automated volumetric nodule measurement in the pilot project Moscow Lung Cancer Screening ultra-low-dose computed tomography pilot study. MATERIALS AND METHODS: The study included individuals with a lung nodule of at least 4 mm on baseline-computed tomography of the Moscow lung cancer screening between February 2017 and February 2018, without verified lung cancer diagnosis until 2020. The radiation dose was selected individually and did not exceed 1 mSv. All scans were assessed by three blinded readers to measure the maximum and minimum transversal nodule diameter and extrapolated volume. As a reference value of size and volume, the average value from the results of expert measurements was obtained. A false-positive nodule was defined as a nodule 6 mm/100 mm3 and a false-negative nodule as a nodule 6 mm/100 mm3. RESULTS: Overall, 293 patients were included (166 men; mean age, 64.6 5.3years); 199 lung nodules were 6 mm/100 mm3 and 94 were 6 mm/100 mm3. Regarding volumetric measurements, 32 [10.9%; 4 false-positive, 28 false-negative], 29 [9.9%; 17 false-positive, 12 false-negative], and 30 [10.2%; 6 false-positive, 24 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively. For linear diameter measurement, 92 [65.5%; 107 false-positive, 85 false-negative], 146 [49.8%; 58 false-positive, 88 false-negative], and 102 [34.8%; 23 false-positive, 79 false-negative] nodule discrepancies were reported by readers 1, 2, and 3 respectively. CONCLUSIONS: The use of lung nodule volumetry strongly reduces the number of false-positive and false-negative nodules compared with nodule diameter measurements, in an ultra-low-dose computed tomography lung cancer screening program

Erratum in “Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study” (doi: 10.17816/DD117481)

In the article "Volumetry versus linear diameter lung nodule measurement: an ultra-low-dose computed tomography lung cancer screening study" published in Digital Diagnostics journal Volume 4 Issue 1 in 2023 (doi: 10.17816/DD117481) contained an error in the paragraph with data of funding sources for the study. At the request of the authors team, the error was eliminated, the original version of the published article and the information on the journals site was replaced with the corrected one. Correct text of the changed: This paper was prepared by a group of authors as part of the research work (USIS No. 123031400009-1) in accordance with the Order issued by the Moscow Health Care Department No. 1196 dated December 21, 2022. The authors and the publisher apologize to readers for the published error and express their confidence that this mistake could not significantly affect the perception and interpretation of the results of the study described in the text of the article