Type:
Educational Exhibit
Keywords:
Hybrid Imaging, Lung, Nuclear medicine, CT, PET-CT, Biopsy, Staging, Cancer, Neoplasia, Pathology
Authors:
S. M. I. Y. Shalaby, E. Darwish, M. Gamal, A. Rashad, E. Neri
DOI:
10.26044/ecr2022/C-10341
Findings and procedure details
This cross-sectional study included forty patients, with (nine) females (22.5 %) and 31 males (77.5%). Ages ranged between 35 and 88 years with the mean age of 62.95 years ±10.01SD. The study included (25) 62.5% patients with adenocarcinoma, (12) 30% patients with squamous cell carcinoma and (30) 7.5% patients with large cell carcinoma The (T) staging of the described primary lung masses were: (9) 22.5% with T1, (11) 27.5% with T2, (14) 35% with T3 and (6) 15% with T4 primary mass staging. Figure (1) shows two patients with SCC and adenocarcinoma, with size and max.SUV significantly higher in SCC than adenocarcinoma. Table (1) shows descriptive data of the whole study population.
The cases were divided into two groups based on tumor size (≤ 5 cm and ≤ 5 cm. There is no significant correlation noted between the age of the patient and the primary lung mass pathology type. Additionally, no significant statistical difference between max.SUV of the primary tumor in each age group, as shown in table (2).
There is no significant correlation between the gender of the patients and the primary lung mass pathology type. (p: 0.472). In addition, there was no significant statistical difference between mean max.SUV of males and females (P =0.472) in NSCLC as shown in table (3)
There is no significant correlation between the max.SUV and the T-stage of the primary lung mass. Table (4) shows the study population T staging.
There is a statistically significant positive correlation between the tumor size and pathology type, where SCC is the largest in size (mean 77.75 mm, SD 31.11) and adenocarcinoma measures about: (mean 38.4 mm, SD 12.54). (P value <0.001). as shown in tables (4) and (5)
Our statistical analysis concluded that the T staging is the only significant predictor for tumor SUV value and it account for the significant F statistic in statistical models: model 1, 2 and 3, yet as the R square are non-significant in model 2 and 3, so the added predictors in these models (tumor size and age) doesn’t providence significant contribution to the variance (and hence prediction) of tumor SUV.
The final regression equation is: Tumor SUV = 5.730 + (1.664 x tumor staging).