Clinical Utility of Positron Emission Tomography Magnetic Resonance Imaging (PET-MRI) in Gastrointestinal Cancers

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

Targeting the Warburg effect: A revisited perspective from molecular mechanisms to traditional and innovative therapeutic strategies in cancer

Cancer reprogramming is an important facilitator of cancer development and survival, with tumor cells exhibiting a preference for aerobic glycolysis beyond oxidative phosphorylation, even under sufficient oxygen supply condition. This metabolic alteration, known as the Warburg effect, serves as a significant indicator of malignant tumor transformation. The Warburg effect primarily impacts cancer occurrence by influencing the aerobic glycolysis pathway in cancer cells. Key enzymes involved in this process include glucose transporters (GLUTs), HKs, PFKs, LDHs, and PKM2. Moreover, the expression of transcriptional regulatory factors and proteins, such as FOXM1, p53, NF-κB, HIF1α, and c-Myc, can also influence cancer progression. Furthermore, lncRNAs, miRNAs, and circular RNAs play a vital role in directly regulating the Warburg effect. Additionally, gene mutations, tumor microenvironment remodeling, and immune system interactions are closely associated with the Warburg effect. Notably, the development of drugs targeting the Warburg effect has exhibited promising potential in tumor treatment. This comprehensive review presents novel directions and approaches for the early diagnosis and treatment of cancer patients by conducting in-depth research and summarizing the bright prospects of targeting the Warburg effect in cancer.

Abdominal Positron Emission Tomography/Magnetic Resonance Imaging

Hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) is highly suited for abdominal pathologies. A precise co-registration of anatomic and metabolic data is possible thanks to the simultaneous acquisition, leading to accurate imaging. The literature shows that PET/MRI is at least as good as PET/CT and even superior for some indications, such as primary hepatic tumors, distant metastasis evaluation, and inflammatory bowel disease. PET/MRI allows whole-body staging in a single session, improving health care efficiency and patient comfort.

State-of-the-art imaging in oesophago-gastric cancer

Radiological investigations are essential in the management of oesophageal and gastro-oesophageal junction cancers. The current multimodal combination of CT, 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET/CT) and endoscopic ultrasound (EUS) has limitations, which hinders the prognostic and predictive information that can be used to guide optimum treatment decisions. Therefore, the development of improved imaging techniques is vital to improve patient management. This review describes the current evidence for state-of-the-art imaging techniques in oesophago-gastric cancer including high resolution MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, whole-body MRI, perfusion CT, novel PET tracers, and integrated PET/MRI. These novel imaging techniques may help clinicians improve the diagnosis, staging, treatment planning, and response assessment of oesophago-gastric cancer.

Multimodal Medical Image Fusion of Positron Emission Tomography and Magnetic Resonance Imaging Using Generative Adversarial Networks

Multimodal medical image fusion is a current technique applied in the applications related to medical field to combine images from the same modality or different modalities to improve the visual content of the image to perform further operations like image segmentation. Biomedical research and medical image analysis highly demand medical image fusion to perform higher level of medical analysis. Multimodal medical fusion assists medical practitioners to visualize the internal organs and tissues. Multimodal medical fusion of brain image helps to medical practitioners to simultaneously visualize hard portion like skull and soft portion like tissue. Brain tumor segmentation can be accurately performed by utilizing the image obtained after multimodal medical image fusion. The area of the tumor can be accurately located with the information obtained from both Positron Emission Tomography and Magnetic Resonance Image in a single fused image. This approach increases the accuracy in diagnosing the tumor and reduces the time consumed in diagnosing and locating the tumor. The functional information of the brain is available in the Positron Emission Tomography while the anatomy of the brain tissue is available in the Magnetic Resonance Image. Thus, the spatial characteristics and functional information can be obtained from a single image using a robust multimodal medical image fusion model. The proposed approach uses a generative adversarial network to fuse Positron Emission Tomography and Magnetic Resonance Image into a single image. The results obtained from the proposed approach can be used for further medical analysis to locate the tumor and plan for further surgical procedures. The performance of the GAN based model is evaluated using two metrics, namely, structural similarity index and mutual information. The proposed approach achieved a structural similarity index of 0.8551 and a mutual information of 2.8059.

Raman Microscopy: Progress in Research on Cancer Cell Sensing

In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.

Role of precision imaging in esophageal cancer

Esophageal cancer is a major cause of morbidity and mortality worldwide. Recent advancements in the management of esophageal cancer have allowed for earlier detection, improved ability to monitor progression, and superior treatment options. These innovations allow treatment teams to formulate more customized management plans and have led to an increase in patient survival rates. For example, in order for the most effective management plan to be constructed, accurate staging must be performed to determine tumor resectability. This article reviews the multimodality imaging approach involved in making a diagnosis, staging, evaluating treatment response and detecting recurrence in esophageal cancer.

DDcGAN: A Dual-discriminator Conditional Generative Adversarial Network for Multi-resolution Image Fusion

In this paper, we proposed a new end-to-end model, termed as dual-discriminator conditional generative adversarial network (DDcGAN), for fusing infrared and visible images of different resolutions. Our method establishes an adversarial game between a generator and two discriminators. The generator aims to generate a real-like fused image based on a specifically designed content loss to fool the two discriminators, while the two discriminators aim to distinguish the structure differences between the fused image and two source images, respectively, in addition to the content loss. Consequently, the fused image is forced to simultaneously keep the thermal radiation in the infrared image and the texture details in the visible image. Moreover, to fuse source images of different resolutions, e.g., a low-resolution infrared image and a high-resolution visible image, our DDcGAN constrains the downsampled fused image to have similar property with the infrared image. This can avoid causing thermal radiation information blurring or visible texture detail loss, which typically happens in traditional methods. In addition, we also apply our DDcGAN to fusing multi-modality medical images of different resolutions, e.g., a low-resolution positron emission tomography image and a high-resolution magnetic resonance image. The qualitative and quantitative experiments on publicly available datasets demonstrate the superiority of our DDcGAN over the state-of-the-art, in terms of both visual effect and quantitative metrics.

Bioconjugated gold nanoparticles as an efficient colorimetric sensor for cancer diagnostics

The chances of curing and reducing the adverse effect of cancer partly lie in early detection. Colorimetric sensor-based technique show promising results since the target is detected with high sensitivity but without the use of advanced/costly techniques through a simple visual color change. In most cases, gold nanoparticles (Au Nps) functionalized with biomolecules complementary to target analyte are used for colorimetric detection. The interaction of functionalized Au Nps with target analytes induce aggregation or dispersion where the color of the solution changes from red to blue or blue to red respectively, which can be visualized by the naked eyes. Such a facile technique has a high commercial viability and therefore, understanding its concept is essential. Here, some of the reported studies are discussed technically for better understanding about the invitro colorimetric detection of cancer.

Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm

Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.

Added Value of Including Entire Brain on Body Imaging With FDG PET/MRI

OBJECTIVE

FDG PET/MRI examination of the body is routinely performed from the skull base to the mid thigh. Many types of brain abnormalities potentially could be detected on PET/MRI if the head was included. The objective of this study was therefore to identify and characterize brain findings incidentally detected on PET/MRI of the body with the head included.

MATERIALS AND METHODS

We retrospectively identified 269 patients with FDG PET/MRI whole-body scans that included the head. PET/MR images of the brain were reviewed by a nuclear medicine physician and neuroradiologist, first individually and then concurrently. Both PET and MRI findings were identified, including abnormal FDG uptake, standardized uptake value, lesion size, and MRI signal characteristics. For each patient, relevant medical history and prior imaging were reviewed.

RESULTS

Of the 269 subjects, 173 were women and 96 were men (mean age, 57.4 years). Only the initial PET/MR image of each patient was reviewed. A total of 37 of the 269 patients (13.8%) had abnormal brain findings noted on the PET/MRI whole-body scan. Sixteen patients (5.9%) had vascular disease, nine patients (3.3%) had posttherapy changes, and two (0.7%) had benign cystic lesions in the brain. Twelve patients (4.5%) had serious nonvascular brain abnormalities, including cerebral metastasis in five patients and pituitary adenomas in two patients. Only nine subjects (3.3%) had a new neurologic or cognitive symptom suggestive of a brain abnormality.

CONCLUSION

Routine body imaging with FDG PET/MRI of the area from the skull base to the mid thigh may miss important brain abnormalities when the head is not included. The additional brain abnormalities identified on whole-body imaging may provide added clinical value to the management of oncology patients.

CT/MRI accuracy in detecting and determining preoperative stage of gastric adenocarcinoma in Albania

AIM OF THE STUDY

Gastric adenocarcinoma is among most frequent among cancers in Albania. Early detection and staging is helped by imaging methods, including CT and MRI. This study provides evidence on the CT and MRI accuracy in detecting and pre-operative staging of gastric adenocarcinoma in 62 patients in a diagnostic clinic in Albania. The correct staging of the gastric adenocarcinoma helps decide on the next treatment options.

MATERIAL AND METHODS

Sixty-two patients with gastric adenocarcinoma, confirmed with biopsy, underwent both CT and MRI examination at a clinic in Tirana during same week. Images were reviewed to determine the TNM classifications and staging using the current AJCC guidelines. Data on age, sex, cancer location and differentiation were also collected and analyzed. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value was estimated for both CT and MRI.

RESULTS AND CONCLUSIONS

CT has a higher accuracy than MRI (83% vs. 67%) for T1. Accuracy for T2 was the same (74%). Starting with T3 and upwards, MRI has a slightly more accurate ability to detect and stage the gastric adenocarcinoma (T3: 81 vs. 75; T4: 83 vs. 64). Both the CT and MRI abilities to accurately detect the N classification were the same. Regarding the M classification, the MRI has a slightly more accurate ability to detect metastases (M: 83 vs. 64). Clinicians might benefit from using CT whenever suspect gastric adenocarcinoma patients present first. Decision on surgery requires a MRI to rule out metastases.