Are Pretreatment ¹⁸F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy?

Abstract

There is evidence in some solid tumors that textural features of tumoral uptake in 18 F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non-small cell lung cancer (NSCLC). Methods: Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment 18 F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis. Results: Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P 5 0.004) and higher contrast (mean, 0.11 vs. 0.044; P 5 0.002) and busyness (mean, 0.76 vs. 0.37; P 5 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan-Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P 5 0.003; 12.6 vs. 25.8 mo, P 5 0.002; and 12.9 vs. 20.5 mo, P 5 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P 5 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P 5 0.015, and median not reached vs. 24 mo, P 5 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P 5 0.01, and median not reached vs. 24 mo, P 5 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters. Conclusion: In NSCLC, baseline 18 F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

“…This is well consistent with previous studies by texture analysis on MRI and CT scans, which reported that the COM-based texture parameter looks like most valuable parameter for tissue characterization [14,23]. COM-based texture parameter is a kind of second order texture feature which describes neighborhood gray-tone difference, and was generally interpreted to reflect the metabolic heterogeneity of entropy, energy, and contrast of tumor, so that these COM-based texture parameters have high association with tumor pathology stands to reason [17,24].…”

“…To date, there have been only a few studies investigating the PET texture analysis, and these studies have been localized to prediction of prognosis and evaluation for radiotherapy planning [15]. However, these studies have some ambiguous points about the relationship between textural features and histopathologic characteristics of tumors [17].…”

The precision of textural analysis in 18F-FDG-PET scans of oesophageal cancer

“…There are early reports that textural analysis, an additional tool quantifying intratumoural heterogeneity of 18 FDG-PET tracer uptake, may improve prediction of response and prognosis and it is hypothesised that image heterogeneity may be related to underlying biology and reflect the behaviour of malignant tumours [3][4][5][6][7].…”

Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma

“…Such characterization provides additional and complementary PET image derived quantitative indices with potential value as already demonstrated in predicting therapy response or as prognostic factors in several cancers including lung [16], sarcoma [17], oesophageal [18,19] and rectal cancer [20]. A variety of methodologies has been proposed in order to assess intra-tumour uptake heterogeneity, including visual assessment [21], SUV coefficient of variation (SUVcov) [20], area under the curve of the cumulative histogram (CHAUC) [22] and textural features (TF) analysis [18].…”