OBJECTIVE(S) \& HYPOTHESIS(ES) Objective: Evaluate area under curve (AUC) of BRIDGE in predicting overall survival (OS) for CRC patients. Compare the AUC of BRIDGE with clinical prediction models in predicting survival status for CRC patients. Evaluate the sensitivity, specificity, positive prediction value (PPV) and negative prediction value (NPV)of BRIDGE in predicting OS for CRC patients.
Hypothesis: BRIDGE achieves an AUC over 0.80 in predicting OS for CRC patients. BRIDGE is superior to clinical prediction models in terms of AUC in predicting OS for CRC patients.
BACKGROUND \& RATIONALE Colorectal cancer (CRC), with annually increasing incidence and mortality worldwide, has become the second leading cause of cancer-related death. The gastrointestinal (GI) tract comprises a complex ecosystem with extensive interactions between normal or neoplastic epithelial cells with immune, neuronal, and other cell types, as well as microorganisms and metabolites within the gut lumen. Specifically, the intricate relationship between the GI tract and the central nervous system (CNS), collectively known as the brain-gut axis, plays a pivotal role in the pathogenesis of gastrointestinal disorders and neoplasm. For instance, chronic stress increased the risk of colon cancer via activating the COX-2/PEG2 system and promoted tumor cell dissemination by remodeling lymph vasculature. The bidirectional communications of the brain-gut axis are generally found to be mediated by neurotransmitters, inflammatory cytokines, metabolites, or gut microbiota. Nonetheless, the spotlight has shone primarily on the brain-gut crosstalk mechanisms in experimental cellular or animal models, with less attention paid to the structural and functional alterations on the brain networks at the patient level.
The evolution of functional neuroimaging modalities and neuroscience technologies has enabled accurate delineation of CNS activities. Specifically, nuclear medicine imaging technology using 2-18F fluoro-2-deoxy-D-glucose (18F-FDG) to adopt whole-body imaging information, is the optimal in vivo method for the investigation of regional human brain metabolism and associations with systemic disorders. The investigators have previously identified the neuronal metabolic-ventricular dyssynchronization axis which might related to major arrhythmic events using myocardial perfusion imaging and the brain 18F-FDG positron emission tomography (PET). Given the potential dual interactions of the brain-gut axis, identification of specific brain regions associated with CRC development and progression might lead to a better understanding of the disease's neurobiological underpinnings and inform the development of targeted therapeutic strategies. Hence, this study was structured to elucidate the role of neuro-metabolism and its potential mediator in regulating CRC tumorigenesis and metastasis. By delving into the neurometabolic-gut axis in CRC, the resulting mechanistic insights might be leveraged to identify diagnostic and prognostic biomarkers and to develop novel therapeutic interventions for CRC patients.
Previously, investigators have constructed a BRIDGE based on retrospective datasets. The study is conducted to further prospectively verify the clinical applicability and generalizability of BRIDGE in predicting OS for CRC patients. The prediction performance of BRIDGE will be evaluated in a prospective dataset, and compared to conventional clinical-based prediction models in the trial, which might potentially provide important evidence for the feasibility and clinical value of integration of brain images for artificial intelligence-aided GI cancer medicine.
The primary accuracy endpoint in the study is the AUC, a significant indicator of classification performance of a binary classifier, which has been widely used to evaluate model performance in the field of machine learning.
METHODOLOGY Inclusion Criteria
1\. Age ≥ 18 years. 2. Have pathologically confirmed as colorectal adenocarcinoma. 3. Have been diagnosed as colorectal cancer (CRC) by PET/CT. 4. Images of PET/CT sequences are available. Exclusion Criteria
1. Has a concomitant additional malignancy that is processing or requires active treatment. Exceptions include basal cell carcinoma of the skin, squamous cell carcinoma of the skin that has undergone potentially curative therapy or in situ cervical cancer.
2. Have a history of cerebrovascular disease (CVD), refers to a general term for a class of diseases in which cerebrovascular lesions lead to brain dysfunction, including cerebrovascular stenosis, brain localized or diffuse brain dysfunction caused by various cerebrovascular lesions such as vascular occlusion, cerebrovascular rupture, cerebrovascular malformations, or cerebrovascular injuries in doctoral dissertations of Capital Medical University, mainly including ischemic stroke and hemorrhagic stroke, defined as cerebrovascular diseases caused by organic brain injury with sudden onset, rapid onset of localized or diffuse brain function defects as clinical features.
Have a major neuropsychiatric abnormality, or had a life expectancy of fewer than 3 months.
3. Have a history of mental illness, including but not limited to parkinsonism, depression, anxiety, schizophrenia, or dementia.
4. Have a history of severe head trauma.
5. Have a history or current evidence of any condition, laboratory abnormality, or substance abuse disorders that might confound the results of trial or interfere with the subject's participation for the full duration of the trial.
6. Have a history of acute cardiovascular events within 4 weeks before enrollment, including but not limited to acute coronary syndrome, acute decompensated heart failure, and malignant arrhythmia; have a non-tumor condition limiting life expectancy to less than 1 year.
7. Have an active autoimmune disease that has required systemic treatment in past 2 years (i.e., with use of disease modifying agents, corticosteroids or immunosuppressive drugs). Replacement therapy (i.e., thyroxine, insulin, or physiologic corticosteroid replacement therapy for adrenal or pituitary insufficiency) is not considered a form of systemic treatment.
8. Have a diagnosis of immunodeficiency or is receiving chronic systemic steroid therapy or any other form of immunosuppressive therapy within 7 days prior to treatment initiation.
9. Have an active infection requiring systemic therapy.
10. Be pregnant or breastfeeding or expecting to conceive or father children within the projected duration of the trial.
11. Lack of images of PET/CT, or insufficient quality of PET/CT images to obtain measurements.
12. Be currently participating in an additional trial and receiving study therapy. Subject Withdrawal/Discontinuation Criteria The subject discontinues/withdraws study during the trial. Basic Information Collection and Serial Number Generation Once enrollment, the basic information including demographics and baseline clinical characteristics of each subject will be recorded. A unique tracking number will be generated randomly for each subject that will be used to identify the subject for all procedures in the trial.
Imaging Data Collection and Process PET/CT Imaging Collection and Anonymization For each subject, initial tumor imaging by PET/CT should have been performed within 1-2 weeks after enrolled. The process for imaging collection and transmission is manipulated in a uniform imaging protocol by radiologists and technicians in participating institutions. The whole series of PET/CT scans should be exported as DICOM files and completely anonymized with unique tracking number before uploaded to the designated cloud platform.
PET/CT Imaging Quality Control Images of PET/CT scans acquired in sites will be downloaded and reviewed by an independent radiologist experienced in PET/CT in the central laboratory to ensure high image quality
