Delta Radiomics can predict complete pathological response in rectal cancer patients
PO-1759
Abstract
Delta Radiomics can predict complete pathological response in rectal cancer patients
Authors: Antonio Angrisani1, Teresa Di Pietro1, Emma D’Ippolito1, Valerio Nardone1, Angelo Sangiovanni1, Alfonso Reginelli2, Cesare Guida3, Salvatore Cappabianca1
1"L. Vanvitelli" University of Campania, Precision Medicine - Radiotherapy Unit, Naples, Italy; 2"L. Vanvitelli" University of Campania, Precision Medicine - Radiology Unit, Naples, Italy; 3Ospedale del Mare, Radiotherapy, Naples, Italy
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Purpose or Objective
The
present study was designed to evaluate MRI delta texture analysis (D-TA) in
predicting the outcome in terms of the complete pathological response of
patients with locally advanced rectal cancer undergoing neoadjuvant
chemoradiotherapy (C-RT) followed by surgery.
Material and Methods
We
performed a retrospective analysis on 100 patients with locally advanced rectal
adenocarcinoma undergoing C-RT and radical surgery in three different centers
between January 2013 and December 2019. The gross tumor volume (GTV) was
evaluated at both baselines and after C-RT MRI and contoured on T2, DWI, and
ADC sequences. Multiple texture parameters were extracted with LifeX Software,
and D-TA was calculated as the percentage variations in the two-time
points. By performing univariate
analysis and multivariate analysis (logistic regression), these TA parameters
were then correlated with patients' pathological outcomes. Complete
pathological response (pCR, with no viable cancer cells: TRG 0) was chosen as
the statistical end-point. ROC Curves were calculated on the three different
datasets.
Results
In
the whole cohort, 21 patients (21%) showed a pCR. At univariate analysis and
binary logistic analysis, the only parameter that resulted significantly
correlated with pCR in the Training dataset was ADC GLCM-Entropy. The binary
logistic regression was repeated in the two Validation Dataset. AUC for pCR was
0.87 in the Training Dataset and respectively 0.92 and 0.88 in the two Validation
Datasets.
Conclusion
Our
results suggest that D-TA has a significant role in the prediction of pCR, thus
this method may lead to select patients who may potentially avoid surgery. However,
further analysis with prospective and multicenter trials is warranted.