Whole-lesion iodine map histogram analysis versus single-slice spectral CT parameters for determining novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinomas - 02/05/24

Highlights |
• | The whole-lesion iodine map histogram analysis and single-slice spectral computed tomography parameters can predict the novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinoma. |
• | Among histogram parameters, the first percentile has the highest diagnostic performance to predict the novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinoma, while among spectral parameters, iodine concentration has the highest diagnostic performance. |
• | Whole-lesion iodine map histogram analysis and single-slice spectral computed tomography parameters present not different diagnostic performances for determining the novel International Association for the Study of Lung Cancer grade of invasive non-mucinous pulmonary adenocarcinoma. |
Abstract |
Purpose |
The purpose of this study was to evaluate and compare the performances of whole-lesion iodine map histogram analysis to those of single-slice spectral computed tomography (CT) parameters in discriminating between low-to-moderate grade invasive non-mucinous pulmonary adenocarcinoma (INMA) and high-grade INMA according to the novel International Association for the Study of Lung Cancer grading system of INMA.
Materials and methods |
Sixty-one patients with INMA (34 with low-to-moderate grade [i.e., grade I and grade II] and 27 with high grade [i.e., grade III]) were evaluated with spectral CT. There were 28 men and 33 women, with a mean age of 56.4 ± 10.5 (standard deviation) years (range: 29–78 years). The whole-lesion iodine map histogram parameters (mean, standard deviation, variance, skewness, kurtosis, entropy, and 1st, 10th, 25th, 50th, 75th, 90th, and 99th percentile) were measured for each INMA. In other sessions, by placing regions of interest at representative levels of the tumor and normalizing them, spectral CT parameters (iodine concentration and normalized iodine concentration) were obtained. Discriminating capabilities of spectral CT and histogram parameters were assessed and compared using area under the ROC curve (AUC) and logistic regression models.
Results |
The 1st, 10th, and 25th percentiles of the iodine map histogram analysis, and iodine concentration and normalized iodine concentration of single-slice spectral CT parameters were significantly different between high-grade and low-to-moderate grade INMAs (P < 0.001 to P = 0.002). The 1st percentile of histogram parameters (AUC, 0.84; 95% confidence interval [CI]: 0.73–0.92) and iodine concentration (AUC, 0.78; 95% CI: 0.66–0.88) from single-slice spectral CT parameters had the best performance for discriminating between high-grade and low-to-moderate grade INMAs. At ROC curve analysis no significant differences in AUC were found between histogram parameters (AUC = 0.86; 95% CI: 0.74–0.93) and spectral CT parameters (AUC = 0.81; 95% CI: 0.74–0.93) (P = 0.60).
Conclusion |
Both whole-lesion iodine map histogram analysis and single-slice spectral CT parameters help discriminate between low-to-moderate grade and high-grade INMAs according to the novel International Association for the Study of Lung Cancer grading system, with no differences in diagnostic performances.
Le texte complet de cet article est disponible en PDF.Keywords : Biomarkers, iodine map, Lung adenocarcinoma, Spectral CT, Tumor grading
Abbreviations : AUC, CT, IASLC, IC, ICC, INMA, NIC, ROI, SD
Plan
Vol 105 - N° 5
P. 165-173 - mai 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
