quantitative ct
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PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0256194
Author(s):  
Shengkun Peng ◽  
Lingai Pan ◽  
Yang Guo ◽  
Bo Gong ◽  
Xiaobo Huang ◽  
...  

Objectives COVID-19 and Non-Covid-19 (NC) Pneumonia encountered high CT imaging overlaps during pandemic. The study aims to evaluate the effectiveness of image-based quantitative CT features in discriminating COVID-19 from NC Pneumonia. Materials and methods 145 patients with highly suspected COVID-19 were retrospectively enrolled from four centers in Sichuan Province during January 23 to March 23, 2020. 88 cases were confirmed as COVID-19, and 57 patients were NC. The dataset was randomly divided by 3:2 into training and testing sets. The quantitative CT radiomics features were extracted and screened sequentially by correlation analysis, Mann-Whitney U test, the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and backward stepwise LR with minimum AIC methods. The selected features were used to construct the LR model for differentiating COVID-19 from NC. Meanwhile, the differentiation performance of traditional quantitative CT features such as lesion volume ratio, ground glass opacity (GGO) or consolidation volume ratio were also considered and compared with Radiomics-based method. The receiver operating characteristic curve (ROC) analysis were conducted to evaluate the predicting performance. Results Compared with traditional CT quantitative features, radiomics features performed best with the highest Area Under Curve (AUC), sensitivity, specificity and accuracy in the training (0.994, 0.942, 1.0 and 0.965) and testing sets (0.977, 0.944, 0.870, 0.915) (Delong test, P < 0.001). Among CT volume-ratio based models using lesion or GGO component ratio, the model combining CT lesion score and component ratio performed better than others, with the AUC, sensitivity, specificity and accuracy of 0.84, 0.692, 0.853, 0.756 in the training set and 0.779, 0.667, 0.826, 0.729 in the testing set. The significant difference of the most selected wavelet transformed radiomics features between COVID-19 and NC might well reflect the CT signs. Conclusions The differentiation between COVID-19 and NC could be well improved by using radiomics features, compared with traditional CT quantitative values.


2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Daisuke Yamada ◽  
Sachiko Ohde ◽  
Ryosuke Imai ◽  
Kengo Ikejima ◽  
Masaki Matsusako ◽  
...  

Abstract Background Quantitative evaluation of radiographic images has been developed and suggested for the diagnosis of coronavirus disease 2019 (COVID-19). However, there are limited opportunities to use these image-based diagnostic indices in clinical practice. Our aim in this study was to evaluate the utility of a novel visually-based classification of pulmonary findings from computed tomography (CT) images of COVID-19 patients with the following three patterns defined: peripheral, multifocal, and diffuse findings of pneumonia. We also evaluated the prognostic value of this classification to predict the severity of COVID-19. Methods This was a single-center retrospective cohort study of patients hospitalized with COVID-19 between January 1st and September 30th, 2020, who presented with suspicious findings on CT lung images at admission (n = 69). We compared the association between the three predefined patterns (peripheral, multifocal, and diffuse), admission to the intensive care unit, tracheal intubation, and death. We tested quantitative CT analysis as an outcome predictor for COVID-19. Quantitative CT analysis was performed using a semi-automated method (Thoracic Volume Computer-Assisted Reading software, GE Health care, United States). Lungs were divided by Hounsfield unit intervals. Compromised lung (%CL) volume was the sum of poorly and non-aerated volumes (− 500, 100 HU). We collected patient clinical data, including demographic and clinical variables at the time of admission. Results Patients with a diffuse pattern were intubated more frequently and for a longer duration than patients with a peripheral or multifocal pattern. The following clinical variables were significantly different between the diffuse pattern and peripheral and multifocal groups: body temperature (p = 0.04), lymphocyte count (p = 0.01), neutrophil count (p = 0.02), c-reactive protein (p < 0.01), lactate dehydrogenase (p < 0.01), Krebs von den Lungen-6 antigen (p < 0.01), D-dimer (p < 0.01), and steroid (p = 0.01) and favipiravir (p = 0.03) administration. Conclusions Our simple visual assessment of CT images can predict the severity of illness, a resulting decrease in respiratory function, and the need for supplemental respiratory ventilation among patients with COVID-19.


2021 ◽  
Vol 12 ◽  
Author(s):  
Xingli Liu ◽  
Ling Wang ◽  
Meng Gao ◽  
Gang Wang ◽  
Kai Tang ◽  
...  

Background and PurposeA high-altitude environment was known to have a negative effect on bone and lead to a higher incidence of hip fracture. However, the dependence of muscle composition on altitude is unclear. Thus, we aimed to compare muscle density and area in plateau and low altitude area and to determine the effect of the altitude on these outcomes.MethodsCommunity dwelling adults over 60 years old living in Beijing (elevation 50 m; 300 subjects,107 men and 193 women) or Kunming (elevation 2000 m; 218 subjects,83 men and 135 women) for more than 10 years were enrolled. Quantitative CT was performed in all subjects and cross-sectional area and attenuation measured in Hounsfield units (HU) were determined for the trunk, gluteus, and mid-thigh muscles.ResultsCompared to Beijing, Kunming adults were slimmer (Beijing men vs Kunming men: 25.08 ± 2.62 vs 23.94 ± 3.10kg/m2, P=0.013; Beijing women vs Kunming women: 25.31 ± 3.1 vs 23.98 ± 3.54 kg/m2, P= 0.001) and had higher muscle density in the L2-trunk and gluteus maximus muscles after adjustment for age and BMI (L2-trunk muscles: Beijing men 29.99 ± 4.17 HU vs Kunming men 37.35 ± 4.25 HU, P&lt; 0.0001; Beijing women 27.37 ± 3.76 HU vs Kunming women 31.51 ± 5.12 HU, P&lt; 0.0001; Gluteus maximus muscle: Beijing men 35.11 ± 6.54 HU vs Kunming men 39.36 ± 4.39 HU, P= 0.0009; Beijing women 31.47 ± 6.26 HU vs Kunming women 34.20 ± 5.87 HU P=0.0375). Age was similar in both cohorts and no differences were observed in the gluteus medius and minimus muscle or the mid-thigh muscle, either in the area or density.ConclusionsCompared with Beijing, the adults in Kunming had higher muscle density of the gluteus maximus and L2 trunk muscles, showing that living at a higher altitude might be beneficial to muscle quality.


2021 ◽  
pp. 028418512110630
Author(s):  
Shihao Huang ◽  
Xuan Cui ◽  
Heli Han ◽  
Yuan Zhang ◽  
Bing Gao ◽  
...  

Background Gemstone spectral computed tomography (GSCT) has been used to measure bone mineral density (BMD) in human vertebrae and animal models gradually. Purpose To investigate the effect of scanning protocols for BMD measurements by GSCT using the European spine phantom (ESP) and its accuracy and precision. Material and Methods The ESP number 145 containing three hydroxyapatite (HAP) inserts with densities of 50, 100, and 200 mg/cm3 were labeled as L1, L2, and L3, respectively. Quantitative CT (QCT) protocol and 14 groups of scanning protocols configured by GSCT were used to repeatedly scan the ESP 10 times. Their measurements were compared with the true values of ESP and their relative standard deviation and relative error were calculated. Results The measured values of the three inserts at different exposure levels were statistically significant ( P < 0.05). The measured values in the 0.8 s/r 260 mA group, 0.5 s/r 630 mA group, and 0.6 s/r 640 mA group were not significantly different from the actual ESP values for L1 and L2. However, the measured values at all the parameters were significantly different from the actual values for the L3. Conclusion CT gemstone spectral imaging can accurately and quantitatively measure the HAP value of ESP, but the results of BMD will be affected by the scanning protocols. The best scanning parameter of ESP measured by GSCT was 0.8 s/r 260 mA, taking dose into consideration, and the measurement accuracy of vertebrae with low BMD was higher than that of QCT under this parameter.


2021 ◽  
Author(s):  
Junzhong Liu ◽  
Yuzhen Wang ◽  
Xinhua Wang ◽  
Minfeng Sun

Abstract Objective: The purpose of this study was to compare imaging features between COVID-19 and mycoplasma pneumonia (MP).Materials and Methods: The data of patients with mild COVID-19 and MP who underwent chest computed tomography (CT) examination from February 1, 2020 to April 17, 2020 were retrospectively analyzed. The Pneumonia-CT-LKM-PP model based on a deep learning algorithm was used to automatically quantify the number, volume, and involved lobes of pulmonary lesions, and longitudinal changes in quantitative parameters were assessed in three CT follow-ups.Results: A total of 10 patients with mild COVID-19 and 13 patients with MP were included in this study. There was no difference in lymphocyte counts at baseline between the two groups (1.43±0.45 vs 1.44±0.50, p=0.279). C-reactive protein levels were significantly higher in MP group than in COVID-19 group (p<0.05). The number, volume, and involved lobes of pulmonary lesions reached a peak in 7-14 days in the COVID-19 group, but there was no peak or declining trend over time in the MP group (p<0.05).Conclusion: Based on the longitudinal changes of quantitative CT, pulmonary lesions peaked at 7-14 days in patients with COVID-19, and this may be useful to distinguish COVID-19 from MP and evaluate curative effects and prognosis.


2021 ◽  
pp. 2101613
Author(s):  
Anton Schreuder ◽  
Colin Jacobs ◽  
Nikolas Lessmann ◽  
Mireille JM Broeders ◽  
Mario Silva ◽  
...  

PurposeA baseline CT scan for lung cancer (LC) screening may reveal information indicating that certain LC screening participants can be screened less, and instead require dedicated early cardiac and respiratory clinical input. We aimed to develop and validate competing death (CD) risk models using CT information to identify participants with a low LC and a high CD risk.MethodsParticipant demographics and quantitative CT measures of LC, cardiovascular disease, and chronic obstructive pulmonary disease were considered for deriving a logistic regression model for predicting five-year CD risk using a sample from the National Lung Screening Trial (n=15 000). Multicentric Italian Lung Detection data was used to perform external validation (n=2287).ResultsOur final CD model outperformed an external pre-scan model (CDRAT) in both the derivation (Area under the curve=0.744 [95% confidence interval=0.727 to 0.761] and 0.677 [0.658 to 0.695], respectively) and validation cohorts (0.744 [0.652 to 0.835] and 0.725 [0.633 to 0.816], respectively). By also taking LC incidence risk into consideration, we suggested a risk threshold where a subgroup (6258/23 096, 27%) was identified with a number needed to screen to detect one LC of 216 (versus 23 in the remainder of the cohort) and ratio of 5.41 CDs per LC case (versus 0.88). The respective values in the validation cohort subgroup (774/2287, 34%) were 129 (versus 29) and 1.67 (versus 0.43).ConclusionsEvaluating both LC and CD risks post-scan may improve the efficiency of LC screening and facilitate the initiation of multidisciplinary trajectories among certain participants.


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