Original Article
Lung nodules assessment in ultra-low-dose CT with iterative reconstruction compared to conventional dose CT
Abstract
Background: To retrospectively assess whether the low-voltage lung CT scan coupled with iterative reconstruction algorithms can be an optimal scanning method for measuring the size and density of lung nodules in cancer patients.
Methods: Eighty two cancer patients receiving both chest scan with low-voltage (80 kV) and abdomen CT scan with standard voltage (120 kV) were enrolled in this study. Lung nodules were measured manually and semi-automatically by two different computer-aided diagnosis (CAD) systems. The nodules were then divided into large-, medium- and small-size groups based on their largest diameter. Additionally, the nodules were categorized into three different groups according to their density: calcified, solid and partial-solid nodules. The 3D volumes, average diameter and CT value of lung nodules were measured using the two CAD semi-automated systems, and the CT values were compared with regards to the different tube voltages. Furthermore, the accuracy and reliability of CAD systems were validated in the large nodules.
Results: The scores of subjective evaluation indicated that the quality of lung nodule images yielded optimal clinical diagnostic value for both 80 kV (2.35±0.054) and 120 kV (2.51±0.053) scanning methods, with a strong inter-observer consistency (Kappa =0.848 and 0.829, respectively). Intraclass correlation coefficient (ICC) and Bland-Altman plot revealed that two CAD systems produced the consistent results. Mean CT values of large nodules (n=18) were significantly different between 80 and 120 kV (−28.11±47.39 vs. −39.61±43.32 HU, P<0.05). Notably, the CT value of 80 kV was 33.96% higher than that of 120 kV. Moreover, the volumes of 66 solid lung nodules demonstrated a statistically significant difference (1.68%) between 80 kV group (740.89±156.97 mm3) and 120 kV group (753.48±157.92 mm3, P<0.05). Furthermore, significant differences were observed in the CT values of large nodules between 80 and 120 kV groups (25.64±12.67 vs. 13.89±9.78 HU, P<0.05), but not the maximum diameters (12.08±1.56 vs. 12.13±1.56 mm, P>0.05).
Conclusions: Our study suggests that detection of lung nodules with ultra-low-dose CT can yield an excellent image quality and optimal diagnostic values as compared to the standard dose CT. Therefore, CT scan with low voltage of 80 kV CT scan can be leveraged to improve the diagnosis and surveillance of lung nodules measured less than 30 mm in diameter. Further investigation with a larger sample size is warranted to confirm our findings, particularly the increased CT values of large nodules and the greater volume of solid nodules after exposure to low-dose CT scan.
Methods: Eighty two cancer patients receiving both chest scan with low-voltage (80 kV) and abdomen CT scan with standard voltage (120 kV) were enrolled in this study. Lung nodules were measured manually and semi-automatically by two different computer-aided diagnosis (CAD) systems. The nodules were then divided into large-, medium- and small-size groups based on their largest diameter. Additionally, the nodules were categorized into three different groups according to their density: calcified, solid and partial-solid nodules. The 3D volumes, average diameter and CT value of lung nodules were measured using the two CAD semi-automated systems, and the CT values were compared with regards to the different tube voltages. Furthermore, the accuracy and reliability of CAD systems were validated in the large nodules.
Results: The scores of subjective evaluation indicated that the quality of lung nodule images yielded optimal clinical diagnostic value for both 80 kV (2.35±0.054) and 120 kV (2.51±0.053) scanning methods, with a strong inter-observer consistency (Kappa =0.848 and 0.829, respectively). Intraclass correlation coefficient (ICC) and Bland-Altman plot revealed that two CAD systems produced the consistent results. Mean CT values of large nodules (n=18) were significantly different between 80 and 120 kV (−28.11±47.39 vs. −39.61±43.32 HU, P<0.05). Notably, the CT value of 80 kV was 33.96% higher than that of 120 kV. Moreover, the volumes of 66 solid lung nodules demonstrated a statistically significant difference (1.68%) between 80 kV group (740.89±156.97 mm3) and 120 kV group (753.48±157.92 mm3, P<0.05). Furthermore, significant differences were observed in the CT values of large nodules between 80 and 120 kV groups (25.64±12.67 vs. 13.89±9.78 HU, P<0.05), but not the maximum diameters (12.08±1.56 vs. 12.13±1.56 mm, P>0.05).
Conclusions: Our study suggests that detection of lung nodules with ultra-low-dose CT can yield an excellent image quality and optimal diagnostic values as compared to the standard dose CT. Therefore, CT scan with low voltage of 80 kV CT scan can be leveraged to improve the diagnosis and surveillance of lung nodules measured less than 30 mm in diameter. Further investigation with a larger sample size is warranted to confirm our findings, particularly the increased CT values of large nodules and the greater volume of solid nodules after exposure to low-dose CT scan.
