Published online Aug 26, 2021. doi: 10.12998/wjcc.v9.i24.6987
Peer-review started: January 1, 2021
First decision: January 24, 2021
Revised: March 1, 2021
Accepted: July 6, 2021
Article in press: July 6, 2021
Published online: August 26, 2021
Processing time: 235 Days and 0.4 Hours
The accuracy of discriminating pT3a from pT3b-c rectal cancer using high-resolution magnetic resonance imaging remains unsatisfactory. Indeed, the mean and median apparent diffusion coefficient (ADC) values are not always significantly sensitive to small changes or precise status of the tumor owing to the intrinsic chaotic environment of tumors.
Texture analysis (TA) could improve the discrimination of pT3a rectal adenocarcinomas from pT3b-c tumors, but pT3 subclasses of rectal cancer have not been previously determined by ADC maps.
To investigate the value of TA on ADC maps in differentiating pT3a rectal adenocarcinomas from pT3b-c tumors.
This case-control study assessed patients with pT3 rectal adenocarcinoma, who underwent DWI between October 2016 and December 2018. First-order (ADC values, skewness, kurtosis, and uniformity) and second-order (energy, entropy, inertia, and correlation) texture features were derived from whole-lesion ADC maps. Receiver operating characteristic (ROC) curves were used to determine the diagnostic value for pT3b-c tumors.
Totally 59 patients (34 men and 25 women) were included, with a median age of 66 years (range, 41-85 years). Thirty patients had pT3a, 24 had pT3b, and five had pT3c. Skewness was significantly lower in the pT3a stage than in pT3b-c tumors. In addition, energy and entropy were significantly different between pT3a rectal adenocarcinomas and pT3b-c tumors. For differentiating pT3a rectal adenocarcinomas from pT3b-c tumors, the areas under the curves (AUCs) of skewness, energy, and entropy were 0.686, 0.657, and 0.747, respectively. Logistic regression analysis of all three features yielded a greater AUC (0.775) in differentiating pT3a rectal adenocarcinomas from pT3b-c tumors (69.0% sensitivity and 83.3% specificity).
TA features derived from ADC maps might potentially differentiate pT3a rectal adenocarcinomas from pT3b-c tumors, especially skewness, energy, and entropy and their combination.
Future studies should include T2WI-based TA, since high-resolution T2WI plays a pivotal role in the preoperative staging of rectal cancer, and b-values should also be taken into account. In addition, features with long-term clinical applicability should be assessed. Finally, large multicenter studies are needed to confirm and increase the generalizability of the above findings.