الفهرس 
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Abstract
Rectal cancer is considered as a major cause of cancer-related death. It is considered as a frequent malignancy worldwide, where patients benefit in overall survival from early diagnosis.
Tumors with different clinicopathological characteristics suggest the different biological behavior and prognosis. The poor prognostic factors such as poor differentiation, high degree of TNM stage, EMVI, and PNI play key roles in influencing the choice of therapies, especially for adjuvant radiation and specific chemotherapy protocols.
According to National Comprehensive Cancer Network (NCCN) Clinical Practice Guideline, patients with cT1N0M0 stage disease can be treated by transanal endoscopic microsurgery while advanced stages can receive different types of treatment as chemotherapy, radiotherapy and surgical resection.
MRI plays a fundamental role in rectal cancer risk stratification. Preoperative assessment of rectal cancer mainly relies on MRI which not only detect rectal cancer but also characterize tumors.
New MRI techniques may provide both morphological and functional parameters that can be correlated with measurements of tumor biology. For this reason, new MRI techniques could have the potential to identify, quantify, and assess different cancer biomarkers.
DWI as a non-invasive MRI technique can be used to reflect the biological characteristics of a tissue by ADC values.
DWI has proven valuable in detecting malignant tissue, in the rectum, as well as in other organs, so it is helpful in the preoperative diagnosis and guiding the choice of therapies.
It has been reported that ADC is a useful imaging biomarker in the diagnosis, differentiation, predicting tumor treatment response, and preoperative microvascular invasion
Combination of minimum and mean ADC values helps in grading of many tumors accurately
Some studies had demonstrated that minimum ADC values were more likely to reflect the density of tumor cells than the mean ADC values which can hereby be described as a marker to identify specific tumor biological features and potentially predict tumor behavior.