Kim C, et al. Korean J Radiol. 2020 Jul;21(7):838-850. https://doi.org/10.3348/kjr.2019.0711

Automatic measurements by a deep learning algorithm of solid portions of lung cancer manifesting as subsolid lesions were comparable with manual measurements and showed good agreement with invasive... Background The solid portion size of lung cancer lesions manifesting as subsolid lesions is key in their management, but the automatic measurement of such lesions by means of a deep learning (DL) a...

Few studies have focused on clinical courses or viral loads in young asymptomatic or mild patients with COVID-19 infection. We sought to better understand the clinical course and association between viral load and prevalence of pneumonia in young COVID-19 patients with asymptomatic or mild disease severity. In this retrospective study, 106 COVID-19 young patients with asymptomatic or mild disease severity were analyzed for clinical characteristics, clinical course, prevalence of radiologically proven pneumonia and viral load. The cut-off value of viral load for presence of pneumonia was also investigated. The mean age was 28.0±9.3 years. Eleven patients (10.4%) experienced viral remission within one week of diagnosis, but one (0.9%) transferred to the hospital due to aggravation of pneumonia. Patients with pneumonia had significantly higher viral load than those without, and the cut-off value of the Ct value for presence of pneumonia were 31.38. The patients with pneumonia had significantly slower recovery times than those without. Diarrhea was significantly more common in patients with pneumonia than patients without pneumonia. In conclusion, most young asymptomatic and mildly symptomatic patients showed stable clinical course. There were significant differences in viral load and recovery times between patients with and without pneumonia.

No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra–low-dose chest computed tomography, reconstructed using deep learning–based algorithms. This is an important issue in lung cancer screening. Our study aimed to investigate the accuracy of semiautomatic volume measurement of solid nodules and ground-glass nodules, using two deep learning–based image reconstruction algorithms (Truefidelity and ClariCT.AI), compared with iterative reconstruction (ASiR-V) in low-dose and ultra–low-dose settings. We performed computed tomography scans of solid nodules and ground-glass nodules of different diameters placed in a phantom at four radiation doses (120 kVp/220 mA, 120 kVp/90 mA, 120 kVp/40 mA, and 80 kVp/40 mA). Each scan was reconstructed using Truefidelity, ClariCT.AI, and ASiR-V. The solid nodule and ground-glass nodule volumes were measured semiautomatically. The gold-standard volumes could be calculated using the diameter since all nodule phantoms are perfectly spherical. Subsequently, absolute percentage measurement errors of the measured volumes were calculated. Image noise was also calculated. Across all nodules at all dose settings, the absolute percentage measurement errors of Truefidelity and ClariCT.AI were less than 11%; they were significantly lower with Truefidelity or ClariCT.AI than with ASiR-V (all P<0.05). The absolute percentage measurement errors for the smallest solid nodule (3 mm) reconstructed by Truefidelity or ClariCT.AI at all dose settings were significantly lower than those of this nodule reconstructed by ASiR-V (all P<0.05). Furthermore, the lowest absolute percentage measurement errors for ground-glass nodules were observed with Truefidelity or ClariCT.AI at all dose settings. The absolute percentage measurement errors for ground-glass nodules reconstructed with Truefidelity at ultra–low-dose settings were significantly lower than those of all sizes of ground-glass nodules reconstructed with ASiR-V (all P<0.05). Image noise was lowest with Truefidelity (all P<0.05). In conclusion, the deep learning–based algorithms were more accurate for volume measurements of both solid nodules and ground-glass nodules than ASiR-V at both low-dose and ultra–low-dose settings.

Kim W, et al. Korean J Radiol. 2021 Apr;22:e42. https://doi.org/10.3348/kjr.2020.1164