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Emerging Trends in Early Lung Cancer Detection via LDCT: A Critical Review

by Gagan Thakral, Umesh Kumar, Sapna Gambhir
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 5
Year of Publication: 2025
Authors: Gagan Thakral, Umesh Kumar, Sapna Gambhir
10.5120/ijca2025924882

Gagan Thakral, Umesh Kumar, Sapna Gambhir . Emerging Trends in Early Lung Cancer Detection via LDCT: A Critical Review. International Journal of Computer Applications. 187, 5 ( May 2025), 49-61. DOI=10.5120/ijca2025924882

@article{ 10.5120/ijca2025924882,
author = { Gagan Thakral, Umesh Kumar, Sapna Gambhir },
title = { Emerging Trends in Early Lung Cancer Detection via LDCT: A Critical Review },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 5 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 49-61 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number5/emerging-trends-in-early-lung-cancer-detection-via-ldct-a-critical-review/ },
doi = { 10.5120/ijca2025924882 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-05-29T00:02:58.441697+05:30
%A Gagan Thakral
%A Umesh Kumar
%A Sapna Gambhir
%T Emerging Trends in Early Lung Cancer Detection via LDCT: A Critical Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 5
%P 49-61
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Lung cancer remains one of the leading sources of cancer-related mortality throughout the world. The early detection of lung cancer plays a very crucial role in improving a patient’s survival rate. Low-Dose Computed Tomography (LDCT) has emerged as a powerful tool for early lung cancer screening. LDCT scan uses reduced x-ray dose as compared to normal CT scan. LDCT maintains a balance between reduced radiation exposure and high sensitivity. This systematic review follows the PRISMA framework to explore the latest advancements in LDCT-based lung cancer detection. This systematic review also includes artificial intelligence-driven detection support and integration of LDCT scan with multi-modal biomarkers. The review discusses the impact of large-scale screening programs and highlights key challenges such as false positives. The review also provides publicly available datasets. The manuscript provides a systematic review in tabular form with complete details like results, shortcomings, and future scope of the selected papers. The authors also discussed over diagnosis, accessibility, and examined potential solutions to enhance screening efficacy. Additionally, we analyze emerging trends in AI-powered image analysis and the role of deep learning in improving detection accuracy. The study also provides insights about the explain ability in lung cancer detection. LDCT scan has suggestively improved early detection rates and efficiency of the system. Further research is required to improve screening procedures and address its limitations. This systematic review provides understandings of the current state of LDCT for lung cancer detection and future directions for advancing early diagnosis.

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Index Terms

Computer Science
Information Sciences

Keywords

Lung Cancer Artificial Intelligence early detection LDCT scan screening

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