期刊
CLINICAL CANCER RESEARCH
卷 19, 期 13, 页码 3591-3599出版社
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-12-1307
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资金
- UCLH/UCL
- Department of Health's NIHR Biomedical Research Centre
- Cancer Research UK [16463] Funding Source: researchfish
Purpose: We prospectively examined the role of tumor textural heterogeneity on positron emission tomography/computed tomography (PET/CT) in predicting survival compared with other clinical and imaging parameters in patients with non-small cell lung cancer (NSCLC). Experimental Design: The feasibility study consisted of 56 assessed consecutive patients with NSCLC (32 males, 24 females; mean age 67 +/- 9.7 years) who underwent combined fluorodeoxyglucose (FDG) PET/CT. The validation study population consisted of 66 prospectively recruited consecutive consenting patients with NSCLC (37 males, 29 females; mean age, 67.5 +/- 7.8 years) who successfully underwent combined FDG PET/CT-dynamic contrast-enhanced (DCE) CT. Images were used to derive tumoral PET/CT textural heterogeneity, DCE CT permeability, and FDG uptake (SUVmax). The mean follow-up periods were 22.6 +/- 13.3 months and 28.5 +/- 13.2 months for the feasibility and validation studies, respectively. Optimum threshold was determined for clinical stage and each of the above biomarkers (where available) from the feasibility study population. Kaplan-Meier analysis was used to assess the ability of the biomarkers to predict survival in the validation study. Cox regression determined survival factor independence. Results: Univariate analysis revealed that tumor CT-derived heterogeneity (P < 0.001), PET-derived heterogeneity (P = 0.003), CT-derived permeability (P = 0.002), and stage (P < 0.001) were all significant survival predictors. The thresholds used in this study were derived from a previously conducted feasibility study. Tumor SUVmax did not predict survival. Using multivariable analysis, tumor CT textural heterogeneity (P = 0.021), stage (P = 0.001), and permeability (P < 0.001) were independent survival predictors. These predictors were independent of patient treatment. Conclusions: Tumor stage and CT-derived textural heterogeneity were the best predictors of survival in NSCLC. The use of CT-derived textural heterogeneity should assist the management of many patients with NSCLC. Clin Cancer Res; 19(13); 3591-9.(c) 2013 AACR.
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