One of the leading causes of cancer-related death is gastrointestinal cancer, which has a significant morbidity and mortality rate. Although preoperative risk assessment is essential for directing patient care, its biological behavior cannot be accurately predicted by conventional imaging investigations. Potential pathophysiological information in anatomical imaging that cannot be visually identified can now be converted into high-dimensional quantitative image features thanks to the developing discipline of molecular imaging. In order to enable molecular tissue profile in vivo, molecular imaging has most recently been utilized to phenotype the expression of single receptors and targets of biological therapy. It is expected that molecular imaging will become increasingly important in the near future, driven by the expanding range of biological therapies for cancer. With this live molecular fingerprinting, molecular imaging can be utilized to drive expression-tailored customized therapy. The technical aspects of molecular imaging are first briefly discussed in this review, followed by an examination of the most recent research on the diagnosis, prognosis, and potential future clinical methods of molecular imaging for GI tract malignancies.

Pancreatic cancer is a common gastrointestinal tumor with increasing morbidity and mortality, and it is difficult to differentiate it from chronic mass pancreatitis. F-18-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) can be used for diagnosis of pancreatic cancer, staging, radiotherapy planning, evaluation of efficacy and recurrence, and differentiation from posttreatment fibrosis but the sensitivity and specificity of diagnosis of chronic pancreatitis are poor. Magnetic resonance imaging (MRI) not only shows the morphology, location, and size of organs and lesions but also has the advantages of low radiation, high soft tissue contrast, and multiparameter imaging, which can help determine the nature of occupying pancreatic lesions. In this study, the watershed algorithm (WA) was used to segment the abdominal images to extract images of pancreatic cancer cells and to compare the value of F-FDG PET/CT combined with MRI in the diagnosis of pancreatic occupying lesions.