Objective  To explore the correlation between multi-parameter measurements of 64-slice spiral CT and p53 gene mutation in patients with colorectal cancer (CRC).

Methods  A retrospective study was conducted on 150 CRC patients diagnosed and treated at Huainan Yangguang Xinkang Hospital from November 2020 to April 2024, including 89 males and 61 females, with an age range of 29 to 94 years and an age of (64.3±12.0) years. Patients were divided into mutation group and non-mutation group based on p53 gene mutation status. All patients underwent 64-slice spiral CT scanning, and multi-parameter measurements of CT images were recorded. Tumor volume, tumor density, enhanced CT value, tumor maximum diameter, tumor morphology, tumor edge, and tumor enhancement mode were compared between the two groups. Chi-square test was used for comparison of counting data, and t-test was applied for comparison of measurement data conforming to normal distribution between groups. Multivariate Logistic regression analysis was conducted to evaluate independent risk factors affecting p53 mutation in CRC patients, and the diagnostic value of CT multi-parameter measurement on p53 mutation in CRC patients was examined using receiver operating characteristic (ROC) curve analysis.

Results  Among the 150 CRC patients, 52 had p53 gene mutation (mutation group), whereas 98 did not exhibit gene mutation(non-mutation group), resulting in a mutation rate of 34.67%. Compared with the non-mutation group, the tumor volume ((45.32±12.81) cm³ vs. (37.32±10.64) cm³, t=4.078, P<0.001), tumor density ((37.53±7.22) HU vs. (31.68±6.43) HU, t=5.080, P<0.001), enhanced CT value ((78.90±14.37) HU vs. (70.56±12.23) HU, t=3.737, P<0.001), and the tumor maximum diameter ((7.62±2.13) cm vs. (6.01±1.94) cm, t=4.675, P<0.001), were larger than the mutation group, The proportion of irregular tumor morphology was 59.62% (31/52) in the mutation group and 43.88% (43/98) in the non-mutation group. The difference in tumor morphology between the two groups was not statistically significant (χ²=3.366, P=0.067). The proportion of blurred tumor edge was 65.38% (34/52) in the mutation group and 24.49% (24/98) in the non-mutation group. The proportion of blurred tumor edge in the mutation group was significantly higher than that in the non-mutation group (χ²=23.957, P<0.001). The proportion of inhomogeneous tumor enhancement mode in the mutation group ( 63.46% (33/52)) was significantly higher than that in non-mutation group (20.41% (20/98)) (χ²=29.732, P<0.001). Multivariate Logistic regression analysis demonstrated that tumor volume (OR=1.165, 95%CI: 1.075–1.263), tumor density (OR=1.059, 95%CI: 1.026–1.092), enhanced CT value (OR=1.046, 95%CI: 1.004–1.090), tumor maximum diameter (OR=1.079, 95%CI: 1.035–1.124), blurred tumor edge (OR=1.900, 95%CI: 1.199–3.012), and inhomogeneous tumor enhancement mode (OR=2.077, 95%CI: 1.358–3.175) were independent risk factors for predicting p53 gene mutation (all P<0.05). ROC curve analysis revealed that the multi-parameter combination of 64-slice spiral CT exhibited high predictive efficiency for p53 gene mutation, with an area under the curve of 0.910, a sensitivity of 0.942 and a specificity of 0.796.

Conclusion  The multi-parameter measurements of 64-slice spiral CT demonstrate high efficiency in predicting p53 gene mutations in CRC patients and serve as an important reference for clinical evaluation and treatment guidance.