Comparative Analysis of Low-Dose CT vs Conventional CT in Oncology Imaging

Thesis Abstract

In modern oncologic imaging, the balance between diagnostic accuracy and patient radiation safety remains a critical challenge, as low-dose computed tomography (LDCT) protocols promise reduced exposure yet may compromise image quality and lesion detectability. This study addresses the problem by evaluating the diagnostic performance, image quality, and clinical impact of LDCT compared with conventional CT (CCT) in oncology patients, with a focus on lesion detection, characterization, and subsequent management decisions. The aim is to determine whether LDCT provides non-inferior diagnostic information relative to CCT and to quantify the trade-offs between radiation dose reduction and image fidelity in real-world oncologic practice. The specific objectives are to (1) compare image quality metrics and radiologist confidence between LDCT and CCT across common oncologic indications, (2) assess lesion detection rates, measurement accuracy, and characterization for pulmonary, hepatic, and nodal lesions, (3) evaluate the concordance of management recommendations derived from LDCT versus CCT, and (4) estimate the effective radiation dose saved by LDCT and its potential clinical implications. A multi-center, cross-sectional study design will be employed. The population comprises adult oncology patients undergoing routine CT imaging for disease staging or response assessment at five tertiary hospitals over a 12-month window. A total of 600 consecutive CT studies will be retrieved, with each study reconstructed in both LDCT and CCT protocols to enable direct intra-patient comparison. Radiologists with at least five years of oncologic imaging experience will independently evaluate image sets in blinded, randomized pairs, recording lesion presence, size measurements, conspicuity scores, and diagnostic confidence on standardized Likert scales. The study will also collect clinical follow-up data and interim imaging results to ascertain the impact of imaging on treatment decisions. Data collection instruments include structured radiology reporting templates, objective image quality assessment tools (signal-to-noise ratio, contrast-to-noise ratio, and spatial resolution metrics), and a radiation dose audit form capturing CTDIvol, DLP, and effective dose estimates. Statistical analyses will be conducted using SPSS and R. Primary analyses will test non-inferiority of LDCT relative to CCT for lesion detection rates and measurement accuracy using McNemar tests for paired proportions and Bland-Altman plots for agreement, respectively. Secondary analyses will compare image quality scores and radiologist confidence using paired t-tests or Wilcoxon signed-rank tests as appropriate. Inter-observer agreement will be assessed with Cohen’s kappa. Multivariate logistic regression will identify factors associated with concordant management decisions, adjusting for tumor site, lesion size, and prior imaging. A subgroup analysis will examine specific anatomic regions (lung, liver, lymph nodes) and tumor histology. Radiation dose reduction will be quantified as a percentage difference in effective dose between LDCT and CCT, with a linear mixed-effects model exploring dose-imaging quality trade-offs across centers. Expected findings include LDCT will demonstrate statistically non-inferior lesion detection rates for pulmonary nodules and accessible hepatic and nodal lesions in numerous oncologic scenarios, with modest reductions in conspicuity for small (<6 mm) pulmonary metastases but preserved diagnostic confidence for larger or clinically consequential lesions. Image quality metrics and radiologist confidence are anticipated to be significantly improved when LDCT is augmented with iterative reconstruction techniques and noise reduction algorithms, mitigating diagnostic trade-offs. LDCT is expected to yield substantial reductions in effective dose, potentially exceeding 40% relative to CCT, without compromising critical management decisions in most cases. The study will also delineate circumstances where LDCT may be inappropriate, such as for characterizing subtle vessel invasion or complex postoperative changes. The study contributes to knowledge by providing robust, multicenter evidence on the clinical equivalence or non-inferiority of LDCT in oncologic imaging, informing evidence-based guideline development for dose optimization in cancer care. It will identify patient- and tumor-specific factors that influence the utility of LDCT, guiding protocol selection and technology investment in radiology departments. The main conclusion is that LDCT, when implemented with advanced reconstruction and standardized reporting, offers meaningful radiation safety benefits with preserved diagnostic performance for many oncology imaging indications. Recommendations include adopting LDCT protocols for routine oncologic surveillance where appropriate, integrating iterative reconstruction to maintain image quality, and establishing center-specific thresholds for when LDCT should be supplemented with CCT, along with ongoing auditing of diagnostic outcomes and dose metrics.