Imaging Techniques and Biochemical Biomarkers: New Insights into Diagnosis of Pancreatic Cancer.

IF 1.8 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Biochemistry and Biophysics Pub Date : 2024-07-19 DOI:10.1007/s12013-024-01437-z
Seyed Hamed Jafari, Zahra Sadat Lajevardi, Mohammad Masoud Zamani Fard, Ameneh Jafari, Soroush Naghavi, Fatemeh Ravaei, Seyed Pouya Taghavi, Kimia Mosadeghi, Fatemeh Zarepour, Maryam Mahjoubin-Tehran, Neda Rahimian, Hamed Mirzaei
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Abstract

Pancreatic cancer (PaC) incidence is increasing, but our current screening and diagnostic strategies are not very effective. However, screening could be helpful in the case of PaC, as recent evidence shows that the disease progresses gradually. Unfortunately, there is no ideal screening method or program for detecting PaC in its early stages. Conventional imaging techniques, such as abdominal ultrasound, CT, MRI, and EUS, have not been successful in detecting early-stage PaC. On the other hand, biomarkers may be a more effective screening tool for PaC and have greater potential for further evaluation compared to imaging. Recent studies on biomarkers and artificial intelligence (AI)-enhanced imaging have shown promising results in the early diagnosis of PaC. In addition to proteins, non-coding RNAs are also being studied as potential biomarkers for PaC. This review consolidates the current literature on PaC screening modalities to provide an organized framework for future studies. While conventional imaging techniques have not been effective in detecting early-stage PaC, biomarkers and AI-enhanced imaging are promising avenues of research. Further studies on the use of biomarkers, particularly non-coding RNAs, in combination with imaging modalities may improve the accuracy of PaC screening and lead to earlier detection of this deadly disease.

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成像技术和生化生物标志物:胰腺癌诊断的新视角。
胰腺癌(Pancreatic cancer,PaC)的发病率正在上升,但我们目前的筛查和诊断策略并不十分有效。然而,最近的证据显示,胰腺癌会逐渐发展,因此筛查对胰腺癌有帮助。遗憾的是,目前还没有理想的筛查方法或方案来早期发现肺癌。传统的成像技术,如腹部超声波、CT、核磁共振成像和 EUS 等,在检测早期 PaC 方面并不成功。另一方面,与成像技术相比,生物标志物可能是一种更有效的 PaC 筛查工具,并具有更大的进一步评估潜力。最近关于生物标志物和人工智能(AI)增强成像的研究显示,在早期诊断帕金森病方面取得了可喜的成果。除蛋白质外,非编码 RNA 也正在作为 PaC 的潜在生物标记物进行研究。本综述整合了目前有关 PaC 筛查模式的文献,为今后的研究提供了一个有条理的框架。虽然传统成像技术在检测早期 PaC 方面效果不佳,但生物标记物和人工智能增强成像是很有前景的研究途径。进一步研究生物标志物(尤其是非编码 RNA)与成像模式的结合使用,可能会提高帕金森病筛查的准确性,从而更早地发现这种致命疾病。
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来源期刊
Cell Biochemistry and Biophysics
Cell Biochemistry and Biophysics 生物-生化与分子生物学
CiteScore
4.40
自引率
0.00%
发文量
72
审稿时长
7.5 months
期刊介绍: Cell Biochemistry and Biophysics (CBB) aims to publish papers on the nature of the biochemical and biophysical mechanisms underlying the structure, control and function of cellular systems The reports should be within the framework of modern biochemistry and chemistry, biophysics and cell physiology, physics and engineering, molecular and structural biology. The relationship between molecular structure and function under investigation is emphasized. Examples of subject areas that CBB publishes are: · biochemical and biophysical aspects of cell structure and function; · interactions of cells and their molecular/macromolecular constituents; · innovative developments in genetic and biomolecular engineering; · computer-based analysis of tissues, cells, cell networks, organelles, and molecular/macromolecular assemblies; · photometric, spectroscopic, microscopic, mechanical, and electrical methodologies/techniques in analytical cytology, cytometry and innovative instrument design For articles that focus on computational aspects, authors should be clear about which docking and molecular dynamics algorithms or software packages are being used as well as details on the system parameterization, simulations conditions etc. In addition, docking calculations (virtual screening, QSAR, etc.) should be validated either by experimental studies or one or more reliable theoretical cross-validation methods.
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