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Computed tomography (CT) remains a cornerstone in oncological imaging due to its high-resolution anatomical visualization and widespread availability where This retrospective study evaluated the diagnostic accuracy of contrast-enhanced CT scans in detecting various cancerous lesions, comparing its performance with magnetic resonance imaging (MRI) and positron emission tomography (PET) in a cohort of 110 patients aged 20 to 80 years while CT demonstrated an overall accuracy of 77.3%, with sensitivity and specificity values of 89.5% and 15.8%, respectively as well as The highest accuracy was observed in breast cancer detection (86.4%), followed by lung (83.3%) and liver cancers (78.6%) furthermore Despite CT’s advantages, its limited specificity and relatively high false positive rates necessitate complementary modalities to reduce diagnostic uncertainty. MRI and PET showed superior specificity and overall detection rates, with PET/CT combination especially enhancing staging accuracy by integrating functional and anatomical data. So, finally these findings underscore the importance of modality selection tailored to cancer type and clinical context, advocating for integrated imaging strategies to optimize diagnostic workflows in oncologic practice.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-15
DOI
https://doi.org/10.5281/zenodo.16883645
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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Zenodo (CERN European Organization for Nuclear Research)
Radiomics and Machine Learning in Medical Imaging
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Abstract

Computed tomography (CT) remains a cornerstone in oncological imaging due to its high-resolution anatomical visualization and widespread availability where This retrospective study evaluated the diagnostic accuracy of contrast-enhanced CT scans in detecting various cancerous lesions, comparing its performance with magnetic resonance imaging (MRI) and positron emission tomography (PET) in a cohort of 110 patients aged 20 to 80 years while CT demonstrated an overall accuracy of 77.3%, with sensitivity and specificity values of 89.5% and 15.8%, respectively as well as The highest accuracy was observed in breast cancer detection (86.4%), followed by lung (83.3%) and liver cancers (78.6%) furthermore Despite CT’s advantages, its limited specificity and relatively high false positive rates necessitate complementary modalities to reduce diagnostic uncertainty. MRI and PET showed superior specificity and overall detection rates, with PET/CT combination especially enhancing staging accuracy by integrating functional and anatomical data. So, finally these findings underscore the importance of modality selection tailored to cancer type and clinical context, advocating for integrated imaging strategies to optimize diagnostic workflows in oncologic practice.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 40%
Radiomics and Machine Learning in Medical Imaging
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