Landscape of Innovative Methods for Early Diagnosis of Gastric Cancer: A Systematic Review.
Alexandra OrășeanuMihaela Cristina BriscOctavian Adrian MaghiarHoria PopaCiprian Mihai BriscSabina Florina ȘoleaTeodor Andrei MaghiarCiprian BriscPublished in: Diagnostics (Basel, Switzerland) (2023)
From a global perspective, gastric cancer (GC) persists as a significant healthcare issue. In the Western world, the majority of cases are discovered at late stages, when the treatment is generally unsuccessful. There are no organized screening programs outside of Asia (Japan and Republic of Korea). Traditional diagnosis techniques (such as upper endoscopy), conventional tumor markers (CEA, CA19-9, and CA72-4), radiographic imaging, and CT scanning all have drawbacks. The gold standard for the earliest detection of cancer and related premalignant lesions is still endoscopy with a proper biopsy follow-up. Since there are currently no clinically approved biomarkers for the early diagnosis of GC, the identification of non-invasive biomarkers is expected to help improve the prognosis and survival rate of these patients. The search for new screening biomarkers is currently underway. These include genetic biomarkers, such as circulating tumor cells, microRNAs, and exosomes, as well as metabolic biomarkers obtained from biofluids. Meanwhile, cutting-edge high-resolution endoscopic technologies are demonstrating promising outcomes in the visual diagnosis of mucosal lesions with the aid of linked color imaging and machine learning models. Following the PRISMA guidelines, this study examined the articles in databases such as PubMed, resulting in 167 included articles. This review discusses the currently available and emerging methods for diagnosing GC early on, as well as new developments in the endoscopic detection of early lesions of the stomach.
Keyphrases
- high resolution
- circulating tumor cells
- healthcare
- machine learning
- ultrasound guided
- end stage renal disease
- ejection fraction
- randomized controlled trial
- chronic kidney disease
- public health
- gene expression
- mesenchymal stem cells
- mass spectrometry
- gas chromatography
- big data
- artificial intelligence
- squamous cell carcinoma
- papillary thyroid
- photodynamic therapy
- clinical practice
- skeletal muscle
- deep learning
- peritoneal dialysis
- type diabetes
- patient reported
- adipose tissue
- combination therapy
- bone marrow
- label free
- small bowel
- contrast enhanced
- copy number
- health information
- social media
- tandem mass spectrometry
- ulcerative colitis