Objective:

To explore the value of high-resolution magnetic resonance imaging (MRI)-based radiomics nomogram in predicting peripheral invasion (PNI) of rectal cancer.

Methods:

A total of 164 rectal cancer patients in Affiliated Tumor Hospital of Nantong University fro

m December 2016 to December 2020 were retrospectively enrolled. The lesions were delineated on highresolution oblique axial T2-weighted imaging (T2WI) layer by layer and radiomics features were extracted. Firstly

the radiomics features were initially screened by maximum correlation and minimum redundancy

then the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to screen the features again and radiomics signature was calculated. Univariate analysis was conducted on the radiomic features

clinical risk factors and MRI findings. Multivariate logistic analysis was carried out to investigate the final feature subset and thus the predicting model was established.

Results:

PNI was present in 29.9% (49/164) of rectal cancer patients. There were statistically significant differences in tumor length

histological grade

MRI reported T stage

MRI reported N stage

circumferential resection margin status and extramural vascular invasion status between the PNI positive group andPNI negative group (

P

＜0.05). While there were no statistically significant differences in other indicators. The predictive nomogram of PNI included the histological grade

extramural vascular invasion status and radiomics signature. The area under curve (AUC) was 0.88 (95% CI 0.82-0.95) in the training cohort

which was 0.88 (95% CI 0.74-1.00) in the validation cohort.

Conclusion:

T2WIbased radiomic nomogram could be helpful for the prediction of PNI preoperatively in rectal cancer patients.