DefinePK

Abstract

Background: Integrated positron emission tomography with computed tomography (PET-CT) has emerged as a pivotal imaging modality in the realm of personalized oncology. By combining metabolic and anatomical information, it enables more accurate tumor characterization, precise staging, early treatment response evaluation, and relapse detection. PET-CT is particularly effective in guiding therapeutic decisions across various cancer types, thereby supporting its role as a cornerstone in precision medicine.
Objective: To evaluate the real-world impact of PET-CT fusion imaging on cancer staging, treatment planning, metabolic response assessment, and progression-free survival (PFS) across five major tumor types.
Methods: This retrospective cohort study was conducted at a tertiary care cancer center in Sindh, Pakistan, from January 2020 to December 2023. A total of 152 patients with histologically confirmed malignancies—non-small cell lung cancer (n=41), lymphoma (n=38), colorectal cancer (n=29), breast cancer (n=22), and head and neck squamous cell carcinoma (n=22)—were included. All underwent baseline and follow-up ^18F-FDG PET-CT scans. Data on demographic profiles, tumor stage, PET parameters (SUVmax, MTV, TLG), and treatment modifications were recorded. Staging alterations, metabolic response (CMR, PMR, SMD, PMD), and correlation with 2-year PFS were statistically analyzed.
Results: Staging was modified by PET-CT in 34% of patients, with 28% upstaged and 11% downstaged. Treatment plans were altered in 35% of cases, including 14 surgical cancellations and 18 radiotherapy plan revisions. Complete metabolic response (CMR) was observed in 30% of patients and was significantly associated with 88% 2-year PFS, compared to 16% in those with progressive metabolic disease (p<0.001). PET-CT demonstrated high recurrence detection accuracy (sensitivity 91%, specificity 84%).
Conclusion: PET-CT significantly influences staging, guides personalized treatment planning, and serves as a prognostic marker in oncology. Its integration with radiomics, artificial intelligence, and novel radiotracers is poised to enhance its diagnostic power and clinical utility in the evolving landscape of precision oncology.