Abstract
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.
Keywords: Molecular imaging, Personalized medicine, Gastrointestinal cancers, Positron emission tomography-computed tomography
Core Tip: In this study, we explored the important role of molecular imaging methods including single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, photoacoustic imaging, magnetic resonance imaging in gastrointestinal cancers (GIC). These techniques require a forward-looking attitude and clear objectives, which will ultimately guarantee the efficient utilization of these promising tools for identifying GIC characteristics, assessing treatment effectiveness, and providing guidance for therapy and monitoring. By incorporating these sophisticated imaging and molecular technologies into the therapeutic process, medical professionals can customize treatment approaches for each patient, track the effectiveness of treatment, and make well-informed choices on ongoing care.
INTRODUCTION
The World Health Organization reported that gastrointestinal (GI) malignancies account for 26.3% of diagnosed cancers and 35.4% cancer-related deaths globally. Colorectal, stomach, liver, esophagus, and pancreatic neoplasms account for 10.2%, 5.7%, 4.7%, 3.2%, and 2.5% of new cancer cases, respectively. In terms of mortality, GI malignancies account for one-third of all cancer fatalities. Colorectal, stomach, liver, esophageal, and pancreatic cancers (PC) account for 9.2%, 8.2%, 8.2%, 5.3%, and 4.5% of cancer mortality, respectively[1].
"Molecular Imaging" refers to a non-invasive medical imaging technique that allows for the characterization, visualization, and assessment of biological activities in malignancies at both molecular and cellular scales[2-6]. Molecular imaging, unlike anatomic imaging techniques, focuses on the expression status or physiological activity of certain molecules inside of an organ or tissue[7]. Single-photon emission computed tomography (SPECT)[8,9], positron emission tomography (PET)[10,11], magnetic resonance spectroscopy[12], photoacoustic imaging[13,14], magnetic resonance imaging (MRI)[15], optical imaging (optical bioluminescence, optical fluorescence)[16,17], chemical exchange saturation transfer[18], near-infrared fluorescence[19,20], and multimodal imaging[21] including PET-magnetic resonance and also PET-computed tomography (CT)[22,23], are some of the techniques used for molecular imaging.
With the advancement of molecular imaging in recent years, molecular imaging has become a crucial technique for diagnosing, assessing, and treating GI cancer cases. It can identify lesions and define the type of early lesions more precisely than conventional anatomic imaging since cancerous cells have a high metabolic rate, cell surface markers, cell cycle regulators, growth factors, or DNA-binding transcription factors[24,25]. For instance, PET-MRI has higher accuracy compared with CT and endoscopic ultrasound for staging and detecting occult metastases of gastric cancer (GC)[26,27]. Also, PET-CT has a better accuracy than contrast CT for evaluating the stage of liver cancer[28]. Accordingly, the Centers for Medicare and Medicaid Services in the United States reimburse most oncological indications of PET. These indications include staging or restaging gastric, colorectal, esophageal, and other GI malignancies[29].
Personalized medicine (PM) is a concept that attempts to provide the proper management to the appropriate patient at the ideal moment[30]. PM might be closely tied to molecular imaging, considering molecular imaging has the potential to help in determining therapeutic targets and choosing patients to identify individuals likely to benefit from targeted treatment[31]. It can also be used in assessing drug pharmacokinetics and directing doses to guide medication dosing and minimize harmful effects by evaluating drug transport, delivery, and clearance in cancerous or normal cells[32]. During the last few years, molecular classifications have progressed from histology-based to genomic, epigenomic, and transcriptome data, revealing novel prognostic indicators and assisting in therapy selection[33-35]. Understanding the complicated molecular alterations associated with abdominal malignancies, particularly colon and pancreatic tumors, is progressing. Molecular imaging agents can detect changes in cancer induced by genetic mutations[36].
Regardless of the number of papers or meta-analyses published on this topic, a complete review in narrative form addresses the significance of molecular imaging and personalized treatment in GI tumors. This article tries to illuminate the ever-changing landscape of GI cancer research by digging into the nuances of classifications, advances in genomics, and the correlation between agents and genetic variables. Finally, the study aims to bridge the gap between imaging, individualized care, and the complexity involved with cancer. It provides insight into accuracy, therapy techniques, and their possible impact on patient outcomes.
IMPACT OF MOLECULAR IMAGING ON PROGNOSIS AND DIAGNOSIS OF GI CANCER AND THE ROLE IN PM
PM is a new branch of medicine that attempts to improve diagnosis accuracy and treatment efficacy. Molecular imaging, a visualization of the metabolic activity and localization of the lesions that are not evident at the structural imaging level, is widely employed in numerous illnesses, notably cancer treatment. Imaging is often divided into three categories: functional, molecular, and anatomical imaging. Tumors are visualized and measured using anatomical imaging methods including ultrasound, CT, and MRI. In contrast, such procedures do not offer information and can be difficult when tumors share physical properties with adjacent tissues[37]. Functional imaging measures processes such as blood flow changes, allows us to greater comprehend disease dynamics in angiogenic cancer therapy[38-41]. On the one hand, molecular imaging enables us to visualize processes at the cellular and molecular levels. It gives information regarding activities such as enzyme processes and receptor numbers, allowing for a more in-depth understanding of cancer development. With advances in genomes, proteomics, and targeted drug discovery, molecular imaging has emerged as a tool for cancer detection, staging, therapy response prediction, and effectiveness monitoring. Despite laboratory approaches that provide snapshots of cancer biology, molecular imaging offers a dynamic understanding of how tumors progress in laboratory settings[42].
The utilization of imaging modalities, particularly integrating anatomical and molecular or functional data, has considerably increased diagnostic accuracy, specificity, and sensitivity. PET-CT, SPECT-CT, PET-MRI, and MRI-optical imaging are some examples of this method[43-47]. A retrospective investigation showed that PET-CT performed well in tumor staging, with an 84% accuracy rate. In comparison, PET-CT obtained 76% accuracy, whereas CT alone achieved 63% and PET alone achieved 64%[44]. Although anatomic imaging has limitations, functional imaging can shed light on them, and molecular imaging could enhance cancer diagnosis and treatment monitoring. The use of modal imaging is a significant advancement since it provides a more comprehensive and accurate view of malignancies[48].
The development of imaging techniques, plays an important role in improving diagnostic skills. It emphasizes the importance of biomarkers and advanced detection methods while distinguishing between two types of probes: Exogenous probes and genetically encoded probes. Exogenous probes for PET imaging, such as 18 F labeled fluorodeoxyglucose (FDG), are designed to target cancer biomarkers. When there is inflammation, the specificity may be reduced. Various types of molecules, including antibodies and peptides, are being studied for their potential as imaging agents in techniques such as ultrasound, CT, MRI, SPECT, and PET methods[49-53].
Molecular imaging has enormous potential in clinical oncology, going beyond laboratory applications to play a crucial part in early cancer detection, and prognosis. It has the greatest impact on tumors that can be treated using non-invasive or minimally invasive approaches, boosting traditional imaging methods by highlighting minor abnormalities and detecting molecular alterations in tissues. This increased sensitivity enables more precise staging, prognostic predictions, and tailored treatment methods. As a cornerstone in clinical oncology, molecular imaging considerably improves 5-year survival rates by allowing for early detection and diagnosis of tumors, particularly in cases such as colorectal cancer (CRC), where screening programs have been implemented to reduce mortality rates. The changing landscape of genetic markers linked to tumor biology and medication responsiveness highlights molecular imaging's expanding role in influencing the future of cancer care[48].
Significantly, malignancies that can be diagnosed without surgery, such as GI cancers, benefit greatly from the use of imaging. This innovative approach gives information about the biology and progression of the lesions. It is a prognostic tool that highlights anomalies and aids in the differentiation of normal or inflammatory tissues from malignant tissue based on early molecular changes rather than evident morphological distinctions. The great precision of biomarkers is critical for collecting data from repeated investigations and comparing before and after therapy. Furthermore, molecular imaging approaches adds information to colonoscopy, while increases sensitivity and diagnostic capacities[48].
As sequencing and proteomic data, tumor vessels, and tumor stroma assessments become available, new targets may emerge for both imaging and targeted therapies. For example, fibroblasts present in tumors are potential targets worth exploring. This expanding knowledge enhances our understanding of subsets within diseases like colon and PC, which opens up possibilities for more precise targeted therapies. Changes in proteins found in tumors and the surrounding tumor environment are used as points for therapies that target molecular processes, immunotherapies, and other precision treatments. Finally, PM seeks to improve the accuracy of diagnosis while decreasing treatment failures. Molecular imaging plays a significant role in PM. Despite many parts of molecular imaging in their early stages, the ultimate aim is to use these approaches to reach superior diagnoses and treatment decisions and determine patient outcomes. Molecular imaging technologies are expected to improve much more technologically over the next few years, substantially influencing PM[54] (Figure 1, Table 1).
Table 1.
|
Imaging modalities
|
Diagnosis
|
Staging
|
Prognosis/survival
|
Metastasis
|
Recurrence
|
RtT
|
|
Liver | PET | 18F-FDG-PET-CT | Independent prognostic factor | |||||
11C-acetate vs 18F-FDG-PET | Dual-tracer PET had better sensitivity and specificity vs FDG PET alone | Dual-tracer PET-CT was superior in staging vs contrast CT | 18 F-FDG PET-CT has higher | Dual-tracer can predict recurrence after TACE | ||||
Choline vs 18F-FDG PET-CT | ||||||||
11C-choline vs. 18F-FDG PET-CT | Dual-tracer had higher sensitivity compared w/each one alone | Dual-tracer had better prognostic value compared w/each one alone | Dual- tracer was a better tool for selecting patients for resection or LT | |||||
68Ga-FAPI PET-CT vs 18F-FDG PET-CT | 68Ga-FAPI PET-CT is more sensitive vs 18F-FDG PET-CT | |||||||
18F-FAPI PET-CT vs. 18F-FDG PETCT | 18F-FAPI PET-CT was superior | 18F-FAPI PET-CT was superior | 18F-FAPI PET/CT was superior in lymph node metastasis vs. distant metastasis |
18F-FAPI PET-CT was superior for local recurrence | ||||
68Ga-LNC1007 vs 68Ga-FAPI and 18F-FDG PET-CT | 68Ga-LNC1007 PET-CT was superior | 68Ga-LNC1007 was superior in skeletal metastases, and peritoneal metastases | ||||||
MRI | DWI | Use in staging | Determining response after CT-guided HDR- B | |||||
DWI vs DCE MRI | Can evaluate responses to radiotherapy | |||||||
Colorectal | PET | 18F-FDG PET/CT | Could predict the prognosis | |||||
Dual-time-point 18F-FDG PET/CT could liver metastasis | ||||||||
68Ga-FAPI PET/CT vs 18F-FDG PET/CT | 68Ga-FAPI PET/CT was superior | 68Ga-FAPI PET/CT was superior | ||||||
Ga-DOTA-FAPI-04 PET/CT vs FDG PET/CT | Ga-DOTA-FAPI-04 PET/CT was superior | Ga-DOTA-FAPI-04 PET/CT was superior | ||||||
MRI | Whole body DWI/MRI vs CT | WB-DWI/MRI significantly outperformed CT | ||||||
Whole body DWI/MRI | Could improve diagnostic accuracy | |||||||
FDG-PET/CT vs MRI vs CT | MRI had highest sensitivity in detecting liver metastasis | |||||||
SPECT | 99mTc-MAA SPECT/CT | Could detect liver metastasis | ||||||
Pancreas | PET | FDG-PET | Could predict RtT | |||||
FDG-PET (CT) vs CA-19-9 | FDG-PET was univariate preoperative predictor of OS | FDG-PET was superior in predicting pathologic treatment response | ||||||
FDG-PET/CT was superior in diagnosis | ||||||||
FDG-PET/CT | Independent prognostic factor of PFS and OS | |||||||
Could predict prognosis | ||||||||
Independent prognostic values for OS | ||||||||
FDG-PET/CT and ceCT | Equal potential in Diagnosing | FDG-PET/CT was superior in metastasis detection | ||||||
ceCT was superior at nodal staging | FDG-PET/CT was superior | |||||||
F-FDG PET/CT was superior | F-FDG PET/CT was superior in predicting LN metastasis | |||||||
FDG-PET/CT was superior | ||||||||
FDG-PET/CT and FDG-PET/MR | Equal diagnostic performance | |||||||
18F-FDG PET/MR was superior in TNM staging | 18F-FDG PET/MR was superior in liver metastasis | |||||||
FDG-PET/CT vs EUS | EUS was superior in detection of locoregional and isolated locoregional recurrences | |||||||
68Ga-FAPI PET/CT vs ceCT | 68Ga-FAPI PET/CT was superior | |||||||
FAPI PET/(CT) vs 18F-FDG PET/CT | Equivalent detection ability | Al18F-NOTA-FAPI-04 PET/CT was superior in TNM staging | ||||||
68Ga-FAPI PET was superior in diagnosis | ||||||||
Ga-FAPI PET/CT superior | Ga-FAPI PET/CT was superior | Ga-FAPI PET/CT superior | ||||||
FDG-PET/CT vs CA19-9 | Both potent predictors for determining the lymph node status | |||||||
Esophagus | SPECT | C-Met targeted fluorescence molecular endoscopy | It did not improve endoscopy | |||||
99mTc-3PRGD2 SPEC vs [18F] FDG PET/CT | SPECT was superior | SPECT was superior | FDG-PET/CT was superior | |||||
99mTc-3PRGD2 SPEC vs CT | SPECT was superior | |||||||
PET | 18F-FDG PET/CT | Showed prognostic ability | ||||||
Could identify interval metastasis | ||||||||
Could predict prognosis | Could predict recurrence | |||||||
Could predict recurrence | ||||||||
Could predict prognosis | ||||||||
68Ga-FAPI-04 PET/CT | Could predict lymph node metastasis | |||||||
[68Ga] Pentixafor-PET/CT vs (FDG)-PET/CT | [68Ga] Pentixafor-PET/CT can be complementary to (FDG)-PET/CT | [68Ga] Pentixafor-PET/CT can be complementary to (FDG)-PET/CT | ||||||
MRI | CT vs MRI vs EUS | MRI had better diagnostic performance for tumor staging | ||||||
DW-MRI | Could predict pathologic complete response | |||||||
DCE-MRI | Could predict response to treatment | |||||||
FDG-PET/CT vs DWI-MRI | DWI-MRI was independent prognostic factor | DWI-MRI was superior in predicting lymph node metastasis | ||||||
Stomach | PET | FAPI PET/CT vs FDG PET/CT | FAPI PET/CT is more effective than FDG PET/CT |
TNM: Tumor-node-metastasis; PFS: Progression-free survival; FDG: Fluorodeoxyglucose; PET: Positron emission tomography; CT: Computed tomography; DWI-MRI: Diffusion-weighted imaging magnetic resonance imaging; DCE: Dynamic contrast-enhanced; EUS: Endoscopic ultrasound; HCC: Hepatocellular carcinoma; SPECT: Single photon emission computed tomography; TACE: Transarterial chemoembolization; CCRT: Concurrent chemoradiotherapy; OS: Overall survival.
LIVER NEOPLASMS
Liver cancer is one of the current global health challenges not only because of its growing incidence but also because of its prognoses[55,56]. The five-year survival of liver cancer is about 21 percent. Therefore, liver cancer is one of the most lethal GI neoplasms[57].
The most common type of liver cancer is hepatocellular carcinoma (HCC), which accounts for approximately 90 percent of liver cancer cases[58]. HCC is the second most fatal tumor, with a 20.3 percent five-year survival rate, according to the surveillance, epidemiology, and results program of the National Cancer Institute (Figure 2, Table 1).
PET imaging using FDG
FDG-PET has a 50%-55% sensitivity for diagnosing and characterizing HCC[59-61]. A study found that 18F-FDG PET-CT has 59% accuracy, 60% specificity, and 76.5% sensitivity in identifying primary HCC and its metastases[62].
The prognostic use of FDG-PET in HCC appears to be connected to particular gene expressions. HCC cells with high expression of vinexin beta, vascular cell adhesion molecule-1, and the natural killer cell inhibitory receptor, appear to have more aggressive biological properties. A substantial association was found between the grade of FDG uptake and the pathological grade. In an experiment by Lee and colleagues on surgical samples from ten patients with HCC showed that tumors with significantly higher 18F-FDG uptake activity were more biologically malignant compared to tumors with lower 18F-FDG uptake. The presence of FDG within a diagnosed HCC might be regarded as an imaging indicator of biological aggressiveness[63].
Furthermore, in a meta-analysis, researchers indicated that an elevated tumor maximal Standardized Uptake Value (SUVmax), as well as a high ratio of lesion SUVmax to average liver SUVmax was associated with a poor outcome in HCC cases. Furthermore, the uptake of FDG in the primary lesions can differentiate the extra-hepatic HCC from intrahepatic disease with a higher uptake in extra-hepatic tumors[64].
Choline, a phosphatidyl cellular membrane component, is upregulated in tumor cells, and radiolabeled choline PET-CT detects well to moderately differentiated HCC more accurately than FDG-PET-CT. FDG-PET-CT is however superior for poorly differentiated and advanced-stage HCC. Combining choline PET-CT and FDG-PET-CT improves the detection of HCC. A systematic review and meta-analysis found that the pooled detection rate per patient and lesion-based of HCC with dual tracer PET-CT was 91% and 89%[65].
Tumor cells accumulate acetate, a precursor for fatty acid production, as a tumor activity marker. In a study by Ho et al[66] dual-tracer PET with FDG-11C-acetate showed 87.3% sensitivity in biopsy-confirmed HCC patients, while FDG had a sensitivity of 47.3%. According to a large cohort study, combining FDG PET-CT with C-11-acetate PET-CT improved sensitivity for identifying primary HCC, yet there was no improvement in detecting metastatic lesions. Additionally, they noted that FDG-PET has a 64.4% sensitivity for detecting primary HCC, whereas 11C-acetate PET has 84.4% sensitivity. A study indicates that dual-tracer PET-CT was much more percise at determining tumor-node-metastasis staging than contrast CT in liver transplantation (LT) and partial-hepatectomy patients. It also accurately assessed tumor burden regarding the size as well as the number of HCC lesions. LT individuals who have 11C-acetate-avid HCC lesions may have more prolonged survival after LT. In advanced-stage patients, 11C-acetate PET-CT might provide valuable information in addition to 18F-FDG because it is related to tumor differentiation in advanced-stages lesions; whereas 18F-FDG uptake was prevalent in those advanced-stage patients. Treatment strategies might be more personalized based on dual radiotracer PET-CT measurements of tumor metabolism features[67].
Fibroblast activation protein (FAP), a serine protease in fibroblast membranes, is excessively expressed in most of the epithelial carcinomas, such as HCC[68]. 68 Ga-FAP inhibitor (FAPI), a fibroblast activating protein inhibitor, helps diagnose various types of cancers[69], with 18F-FAPI-PET-CT being more sensitive in identifying HCC lesions[70-73]. However, 18F-FAPI benefits from a longer half-life which is equal to 68 Ga-FAPI in identifying malignant tumors[74]. A prospective study found that 18F-FAPI-PET-CT was better in detection of primary tumors and lymph node metastases in HCC compared to 18F-FDG-PET-CT[75].
Ga-68 LNC1007 is a radiotracer, created by chemically combining two ligands that target FAP and tripeptide arginine-glycine-aspartic, two key targets in cancer cell growth. A study comparing 68Ga-LNC1007 with 18F-FDG-PET-CT discovered that 68Ga-LNC1007 identified all of the HCC cases (55 primary tumors) and was superior to 2-18F-FDG for diagnosing HCC[76].
PANCREATIC NEOPLASMS
By 2025, PC is expected to become the third most common cause of cancer-related deaths, potentially overtaking breast cancer[77]. Typically, the initial phase of PC lacks noticeable symptoms which justifies the significant number of cases diagnosed at advanced stages (80%)[78,79]. Similar to other cancers, the management of PC depends on early diagnosis, suggesting the curable one-third of PC, if diagnosed at early stages[80]. Imaging techniques are necessary for PC's early detection, staging, treatment, and surgical resection procedures[81].
PET imaging using PET-CT
A meta-analysis which comprised 3567 patients with PC indicated that PET-CT for PC has 89% sensitivity, 70% specificity, and 84% diagnostic accuracy[82]. Nonetheless, PET-CT provides detailed data in volume, size, and stage[83]. The combined use with CA19-9 enhanced the indicators to 96.25%, 63.64%, and 92.31%. The SUVmax combined with CA19-9 level had a 0.94 area under the curve (AUC), substantially greater than either alone[84]. Additionally, the integrated use of PET-CT and CT exhibited even better accuracy (90.0%) and sensitivity (97.6%) than either scan alone. The investigators found that the combination of PET-CT and CT enhances the identification of recurrence. The PET-CT scan was particularly beneficial in identifying recurrences in regions that had been missed by the CT scan[85].
Moreover, PET-CT has been demonstrated to predict PC prognosis[86,87]. Low SUVmax is associated with a PC survival rate at each stage. It has been discovered that PET-CT metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were independent predictive variables of overall survival (OS) in locally progressed PC patients who received Stereotactic Body Radiation Therapy. In another study, MTV independently provided valuable information on prognosis of locally advanced PC targeted with radiation and chemotherapy. Characteristics shown via volume-based PET-CT approach may assist in identifying patients who benefit from radiation therapy[88].
Additionally, MTV and TLG can improve prediction models of prognosis of patients who are candidate for surgical management. In a study of 89 individuals with PC who experienced surgical therapy, of whom 57 treated with neoadjuvant chemotherapy, the MTV and TLG were shown to have significant potential in predicting relapse-free survival (RFS) and OS, regardless of treatment[89]. In another study, MTV and TLG predicted RFS and OS better than baseline tumor size, SUVmax, and serum CA19-9[90]. The results of a comparison study between PET-CT images obtained three months prior to and three months post-radioembolization of hepatic metastases originated from PC indicated that differences in the SUVmax and TLG could serve as predictors of progression-free survival (PFS), OS, and the time to intrahepatic progression subsequent to hepatic metastases[91].
PET imaging using other PET tracers
Quinoline-based FAPIs have shown promising outcomes in both pre/clinical molecular imaging investigations[92,93]. The first published report of clinical research employing FAPI-PET to examine PC was released in 2018[94]. Alongside the findings of this study, pancreatic neoplasms exhibited increased 68Ga-FAPI (FAPI-02) PET-CT uptake, while its rate in normal tissues, unlike 18F-FDG, was low[95]. This low background activity enhances the image contrast and accuracy. Likewise, other observational case studies showed the superiority of 68Ga-FAPI-PET-CT to 18F-FDG-PET-CT in detecting pancreatic-related metastasis[96,97].
Using multiplex immunohistochemistry, a retrospective investigation was conducted to analyze the images of 215 treatment-naïve pancreatic ductal adenocarcinomas (PDACs). The results showed that patients with FAP-dominant and fibroblast-rich stroma had a worse prognosis compared to those with collagen-rich stroma[98]. Shi et al[99] found that there was a strong correlation between high FAP expression levels and poor outcomes in 134 individuals with PDAC. Hence, parameters obtained from FAPI-PET-CT could be potentially in correlation with the clinical prognosis of PC. Nevertheless, this necessitates additional investigations.
Antibody-mediated PET scan
Although the majority of studies using antibody mediated PET in PC s are at animal experiments, they have reported promising outcomes. For instance, Chen et al[100] recruited 89Zr-labeled Anti-Trop-2 antibody (AF650) to evaluate Trop-2 as an immunoPET target in three PC cell lines (BxPC-3, MIA PaCa-2, and AsPC-1). The use of 89Zr-DFO-AF650 showed a remarkable capacity to differentiate primary tumors in the orthotopic BxPC-3 cancer model. It suggests a strong association observed between PET imaging and great sensitivity and bio-distribution. They concluded that this method clearly demonstrates the significant promise of Trop-2-based method of non-invasive imaging in detecting PC and tracking the treatment response.
COLORECTAL NEOPLASMS
In 2020, CRC was attributed to around 150000 new cases and over 53000 fatalities[101]. Non-metastatic CRC has a good prognosis, having an approximate 5-year survival rate of around 90[101]. Regrettably, the five-year survival rate for metastatic CRC stands at a mere 14%. The main treatment options for CRC are surgical removal of the primary tumor and metastasis, systemic chemotherapy, and neoadjuvant chemoradiation[102,103].
PET imaging using FDG
Despite the limitations of FDG-PET in inflammation, infection, and some non-neoplastic conditions[104], FDG-PET-CT is invaluable due to its capacity to evaluate the abnormal metabolic activity that occurs before any visible changes in structure, as well as its capability of detecting tiny malignant tumors within structures with normal morphology[105].
Several studies have tried to improve clinical management strategies of CRC by employing imaging prognostic parameters including depth of presence of malignant lymph nodes, tumor spread, extramural vascular invasion (EMVI), and tumor deposits[106]. In this direction, Lv et al[107] designed and validated a machine learning model of predicting the prognosis of primary CRC by 18F-FDG-PET-CT radiomic and clinical-biological features. They concluded that radiomics signature, including four clinical and four PET-CT characteristics, resulted in the most efficient prognostic prediction model (C-index 0.780, 95%CI: 0.634-0.877). In addition, they reported radiomics features to be associated with tumor metabolic markers, such as SUVmax and SUVmean. This integrated model of bio-clinic and radiology depicts the potentials of 18F-FDG- PET-CT findings along other features in predicting CRC prognosis.
PET imaging using other PET tracers
Studying primary and recurrent GI malignancies, Pang et al[108] found that 68Ga-FAPI-PET-CT with a detection rate of 100% is superior in detecting primary tumors than 18F-FDG-PET-CT with a detection rate of 53%. Furthermore, the 68Ga-FAPI PET/CT scan revealed enhanced tumor delineation and increased contrast between the tumor and its surrounding background. The study revealed the significant absorption of primary CRC lesions in 18F-FDG-PET-CT and 68Ga-FAPI-PET-CT scans. The SUVmax of 68Ga-FAPI in the primary lesions was greater than that of 18F-FDG (15.9 vs 7.9). The superiority of 68Ga-FAPI-PET-CT over 18F-FDG-PET-CT was evident in the visualization and image quality of peritoneal metastases in CRC. Additionally, the average SUVmax value was significantly greater[109].
In 2022, Kömek et al[110] evaluated the patients with CRC and showed that [68 Ga]Ga-DOTA-FAPI-04 PET/CT had a sensitivity of 90% in detecting nodal involvement and a sensitivity of 100% in peritoneal seeding, while these values for 18F-FDG-PET-CT were 80% and 55%. These findings shed light on the promising efficacy of [68 Ga] Ga-DOTA-FAPI-04 PET-CT in evaluating patients with CRC, regarding the primary and secondary lesions.
Prashanth et al[111] examined 29 patients with CRC by 68Ga-FAPI-PET-CT and reported the sensitivity of FAPI in the detection of recurrence was 100%, which was higher than that of FDG-conventional imaging (88%). In another study on 68Ga-FAPI-PET-CT, moderate 68Ga-FAPI absorption in primary CRC tumors was seen (SUVmax, 8.6). In metastatic lesions, however, the SUVmax and SUVmean were 7.95 and 3.96, respectively. Simultaneously, the activity levels of the background and normal tissues were extremely low. Consequently, the tumor-to-background ratio (TBR) exceeded 3, resulting in a significant contrast between normal and tumor tissue. Therefore, the study reported that FAPI-PET-CT has promising potential for detecting metastatic CRC, particularly in cases with lymph node and liver metastasis[112].
Dynamic contrast-enhanced imaging-MRI imaging
In 2022, Chen et al[113] explored the predictive and diagnostic potentials of dynamic contrast-enhanced imaging (DCE)-MRI in EMVI in 124 patients with rectal cancer. They reported the Ktrans and Ve values of EMVI-positive patients evaluated by DCE-MRI to be 1.08 ± 0.97 and 1.03 ± 0.93, while the values for conventional MRI were 0.68 ± 0.29 and 0.65 ± 0.31, respectively. These amounts were higher significantly in EMVI-negative patients (P < 0.05). In another study, Shen et al[114] applied DCE-MRI in 40 individuals with rectal cancer and 15 controls. The time-signal intensity curve of lesions presented in MRI exhibited an outflow pattern. In addition, a moderate association between Ktrans and iAUC, and pathological differentiation was highlighted (0.3 < r < 0.8, all P < 0.05), which provides new insights to preoperative diagnosis of rectal cancer.
ESOPHAGEAL NEOPLASMS
Although there have been advancements in therapeutic approaches and an increase in survival rates for esophageal cancer (EC) patients in the last twenty years, the prognosis of EC remains unfavorable, with an overall five-year survival rate of less than 20%[115,116] (Figure 3).
PET imaging using FDG
Tustumi et al[117] evaluated 113 patients with EC by 18F-FDG-PET-CT and demonstrated that TLG and MTV in the primary tumor and the SUVmax in the suspicious lymph nodes were correlated with survival after surgery (P ≤ 0.05). They concluded that pre-neoadjuvant 18F-FDG-PET-CT parameters can independently predict the prognosis (Figure 4).
PET imaging using other PET tracers
In a prospective analysis of 45 patients with locally advanced EC, the prognostic value of 68 Ga-FAPI was evaluated. Regarding the importance of T stage as a significant prognostic factor in patients with EC, groups with different T stages showed significantly different PET parameters; higher stages were associated with higher SUVmax-FAPI (P = 0.009) and GTVFAPI (P < 0.001). In addition, GTVFAPI values lower than 33.9 cm3 were correlated with better PFS. In this pilot study, Zhao et al[118] concluded that 68Ga-FAPI- PET-CT may predict the response to treatment and OS.
GASTRIC NEOPLASMS
The absolute number of cases of stomach cancer is expected to remain stable or perhaps rise in the future despite a lowering incidence, given the anticipated growth of the global population and the rise in average life expectancies in many countries. While there has been considerable progress in the clinical therapy of stomach cancer, most nations still have a 5-year survival rate of less than 30%, and reported death rates are in line with the disease's frequency. As a result, facilitating an early diagnosis are crucial.
PET imaging using FAPI
Pang et al[108] have recently demonstrated that FAPI-PET-CT is more effective than FDG-PET-CT in identifying primary and malignant lesions in a diverse group of patients, including GC. The significant detection rate observed for FAPI in primary gastric tumors with varying levels of differentiation, coupled with the recognized limitations of FDG in detecting certain subtypes of gastric carcinoma, like mucinous, poorly differentiated, and signet ring tumors[119], suggests the potential use of FAPI as a preferred radiotracer for assessing GC. The notably higher ratio of tumor uptake compared to background in primary GCs demonstrates the potential of FAPI-PET-CT for accurately identifying tumors for radiotherapy, as has been previously demonstrated in other tumor types[120] (Figure 5).
ImmunoPET and ImmunoSPECT
Radiotracers based on antibodies are used in the imaging procedures of immunoPET and immunoSPECT. In both preclinical and clinical trials, non-invasive imaging of GC has been accomplished using immunoPET and immunoSPECT. The following examines the application of immunoPET in GC that targets the antigens CDH17, PD-1, and MG7. For PET or SPECT imaging of stomach tumors, antibodies that were either newly developed or approved by the FDA and that targeted membrane antigens were radiolabeled with gallium-68 (68 Ga), technetium-99m (99m Tc), indium-111 (111 In), copper-64 (64 Cu), zirconium-89 (89 Zr), and bromine-76 (76 Br).
The expression of MG7, an antigen specific to GC, is strongly linked with the advancement of the disease[121]. More than 90% of GC patients have MG7, which may serve as a biomarker for the disease because it is overexpressed in GC tissues as compared to benign lesions or normal mucosa[121]. Afterwards, the NOTA-MG7 compound was utilized as a probe for in vivo imaging of BGC-823 stomach xenografts after being radiolabeled with the short-lived radioisotope gallium-68. Effective labeling at room temperature is made possible by using NOTA as a bifunctional chelator to radiolabel biomolecules with gallium-68. This is crucial for maintaining the immunoreactivity of the antibody. At 60 minutes following intravenous (tail vein) injection of 68 Ga-NOTA-MG7, the 68 Ga-labeled immunoconjugate showed a tumor absorption of 2.53 ± 0.28 percent ID/g. 68 Ga-NOTA-MG7 accumulated in the liver and kidneys in addition to the tumor, most likely as a result of the probe's metabolism in these organs. Antibodies have a delayed biodistribution profile and comparatively extended biological half-life when administered systemically. Because of this, they are frequently marked with radiometals that have longer half-lives, such zirconium-89 (half-life of 3.3 days). Given that gallium-68 has a short half-life of 67.7 minutes, tagging the antibody with a radioisotope with a longer half-life could result in a larger TBR. The high expression of MG7 in Helicobacter pylori-associated stomach illnesses, which may skew patient immunoPET data, is another restriction on the use of 68 Ga-NOTA-MG7[121].
CONCLUSION
The use of cutting-edge biological technology in precision medicine allows for precise diagnosis and therapy by considering a patient's living environment in addition to their clinical data, molecular imaging methods, and bioinformatics. The inconsistent biological properties across the human genome make it challenging to pinpoint the exact clinical and biological importance for each given patient.
In terms of care, we anticipate that reducing the pool of potential patients in accordance with dosage and scheduling guidelines and choosing concurrent medications based on the molecular targeted agents' mechanisms would result in efficient therapy tailored to each patient. FDG-PET-CT and other PET Tracers are becoming a crucial component of the first diagnosis in patients with GI malignancies. Additionally, there is growing interest in studying various radiotracers, especially those that assess hypoxia and other significant characteristics of the tumor micro-environment. These techniques require a forward-looking attitude and clear objectives, which will ultimately guarantee the efficient utilization of these promising tools for identifying GI cancer characteristics, assessing treatment effectiveness, and providing guidance for therapy and monitoring. By incorporating these sophisticated imaging and molecular technologies into the therapeutic process, medical professionals can customize treatment approaches for each patient, track the effectiveness of treatment, and make well-informed choices on ongoing care. This holistic strategy has significant potential for enhancing patient outcomes in the treatment of GI cancers.
Footnotes
Conflict-of-interest statement: The authors had no conflict of interests.
Provenance and peer review: Invited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Medical laboratory technology
Country of origin: United States
Peer-review report’s classification
Scientific Quality: Grade C
Novelty: Grade C
Creativity or Innovation: Grade D
Scientific Significance: Grade C
P-Reviewer: Tang Y S-Editor: Qu XL L-Editor: A P-Editor: Zhang L
Contributor Information
Mobina Fathi, Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran.
Hayder Jasim Taher, Department of Radiology, Hilla University College, Babylon 00964, Iraq.
Sabah Jassim Al-Rubiae, Department of Radiology, Hilla University College, Babylon 00964, Iraq.
Shirin Yaghoobpoor, Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran.
Ashkan Bahrami, Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran.
Reza Eshraghi, Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran.
Hossein Sadri, Faculty of Medicine, Kashan University of Medical Sciences, Kashan 1617768911, Iran.
Mahsa Asadi Anar, Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1983969411, Iran.
Ali Gholamrezanezhad, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States. gholamre@usc.edu.
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