الفهرس 
Colorectal CancerOnly 14 pages are availabe for public view
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Abstract
This study aimed to establish the role of textural analysis as an imaging biomarker in predicting LR & DM in LARC patients after NCRT. Patients were followed up for a median of 10 years to examine the ability of TA to predict the survival as well. Complete responders were predicted in a previous study using the same pa-tients cohort. Six textural Parameters were extracted from MRI scans of 114 LARC patients after Chemoradiation. Two of 6 texture parameters ; entropy (P= 0.033) and mean of positive pixels ( P=0.045 ) were able to predict patients who eventu-ally developed local recurrence. Five of 6 extracted texture features; SD (P=0.015) , Entropy (P=0.017) , mean of positive pixels (P=0.005) , skewness (P=0.046) , and kurtosis (P=0.019) were significantly able to predict patients who subsequently de-veloped distant metastases. Entropy (p=0.033) and MPP (p=0.045) were statisti-cally significant parameters for predicting overall survival. 5 parameters: mean (p = 0.033), SD (p = 0.048), entropy (p = 0.007), mean of positive pixels (p = 0.032), and skewness (p = 0.000) identified Complete responders after NACT.
Therefore, this thesis indicates that textural parameters extracted from MRI images of Locally advanced rectal cancer Patients(LARC) could predict important clinical outcomes such as local recurrence, liver metastasis, survival and treatment re-sponse after Neoadjuvant chemoradiation (NACT). This technique would enable the clinicians to classify the therapy for cancer patients according to their predicted clinical outcome after chemoradiotherapy; either for “wait and watch” approach for those with favorable outcomes, or further oncological/surgical treatment for the patients of high risk of recurrence and metastasis. However, more clinical, his-tological and genomic correlation studies is still required in the future research to formulate a unified protocol and precise personalized treatment algorithms.