Beyond the Scan: The Evolving Role of Computed Tomography in Early Cancer Detection: From Early Lesion Detection to Precision Oncologic Imaging
Abstract: Background: Early cancer detection remains an important objective of modern oncology because the stage at diagnosis strongly influences treatment options and prognosis. Computed tomography (CT) has developed from a primarily anatomical imaging technique into a sophisticated platform capable of high-resolution structural assessment, quantitative tissue characterization, and increasingly automated image analysis. Its role is particularly important in lung, colorectal, pancreatic, and other abdominal malignancies. Objective: To review the current role of CT in early cancer detection and examine emerging developments that may improve lesion detection, characterization, and clinical decision-making. Methods: A narrative review of recent and established peer-reviewed literature was undertaken, with emphasis on low-dose CT screening, contrast-enhanced CT, spectral and multi-energy CT, photon-counting detector CT, radiomics, and artificial intelligence-assisted cancer detection. Recent diagnostic studies, systematic reviews, meta-analyses, and clinical guidance documents were considered. Results: Low-dose CT has demonstrated a mortality benefit in high-risk lung-cancer screening populations; in the National Lung Screening Trial, low-dose CT reduced lung-cancer mortality by 20% compared with chest radiography [1]. Contemporary lung-screening recommendations continue to incorporate risk-based selection and structured management of CT-detected nodules [2,3]. In colorectal cancer, CT has useful diagnostic and staging performance, although sensitivity varies according to depth of tumor invasion and clinical question [4,5]. Emerging technologies are extending CT's capabilities: spectral CT can provide iodine maps and virtual monochromatic images that may improve lesion characterization and treatment assessment [6], and photon-counting CT offers higher spatial resolution and intrinsic spectral information with potential oncologic benefits [7,8]. Artificial intelligence and radiomics may identify subtle imaging patterns before overt morphological abnormalities become apparent; recent pancreatic-cancer studies have demonstrated promising pre-diagnostic performance using quantitative CT features and deep-learning systems [9-11]. Conclusion: CT remains central to contemporary cancer imaging, but its future role extends beyond conventional anatomical visualization. The integration of low-dose techniques, spectral imaging, photon-counting technology, radiomics, and artificial intelligence may enable earlier and more precise detection of malignancy. However, prospective validation, standardized protocols, and clinical integration are required before emerging technologies can be routinely relied upon for cancer screening or diagnosis.
Keywords: Computed tomography; cancer detection; early diagnosis; oncologic imaging; low-dose CT; spectral CT; photon-counting CT; radiomics; artificial intelligence
How to Cite?: Misba Hassan, "Beyond the Scan: The Evolving Role of Computed Tomography in Early Cancer Detection: From Early Lesion Detection to Precision Oncologic Imaging", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 1710-1715, https://www.ijsr.net/getabstract.php?paperid=SR26926085407, DOI: https://dx.doi.org/10.21275/SR26926085407