Comparison Between 18F-FDG PET Image-Derived Indices for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer.

International audienceThe goal of this study was to determine the best predictive factor among image-derived parameters extracted from sequential F-FDG PET scans for early tumor response prediction after 2 cycles of neoadjuvant chemotherapy in breast cancer. METHODS: 51 breast cancer patients were included. Responder and nonresponder status was determined by histopathologic examination according to the tumor and node Sataloff scale. PET indices (maximum and mean standardized uptake value [SUV], metabolically active tumor volume, and total lesion glycolysis [TLG]), at baseline and their variation (Δ) after 2 cycles of neoadjuvant chemotherapy were extracted from the PET images. Their predictive value was investigated using Mann-Whitney U tests and receiver-operating-characteristic analysis. Subgroup analysis was also performed by considering estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, triple-negative, and HER2-positive tumors separately. The impact of partial-volume correction was also investigated using an iterative deconvolution algorithm. RESULTS: There were 24 pathologic nonresponders and 27 responders. None of the baseline PET parameters was correlated with response. After 2 neoadjuvant chemotherapy cycles, the reduction of each parameter was significantly associated with response, the best prediction of response being obtained with ΔTLG (96% sensitivity, 92% specificity, and 94% accuracy), which had a significantly higher area under the curve (0.91 vs. 0.82, P = 0.01) than did ΔSUV (63% sensitivity, 92% specificity, and 77% accuracy). Subgroup analysis confirmed a significantly higher accuracy for ΔTLG than ΔSUV for ER-positive/HER-negative but not for triple-negative and HER2-positive tumors. Partial-volume correction had no impact on the predictive value of any of the PET image-derived parameters despite significant changes in their absolute values. CONCLUSION: Our results suggest that the reduction after 2 neoadjuvant chemotherapy cycles of the metabolically active volume of primary tumor measurements such as ΔTLG predicts histopathologic tumor response with higher accuracy than does ΔSUV measurements, especially for ER-positive/HER2-negative breast cancer. These results should be confirmed in a larger group of patients as they may potentially increase the clinical value and efficiency of F-FDG PET for early prediction of response to neoadjuvant chemotherapy

Second primary cancer risk - the impact of applying different definitions of multiple primaries: results from a retrospective population-based cancer registry study

Background: There is evidence that cancer survivors are at increased risk of second primary cancers. Changes in the prevalence of risk factors and diagnostic techniques may have affected more recent risks.<p></p> Methods: We examined the incidence of second primary cancer among adults in the West of Scotland, UK, diagnosed with cancer between 2000 and 2004 (n = 57,393). We used National Cancer Institute Surveillance Epidemiology and End Results and International Agency for Research on Cancer definitions of multiple primary cancers and estimated indirectly standardised incidence ratios (SIR) with 95% confidence intervals (CI).<p></p> Results: There was a high incidence of cancer during the first 60 days following diagnosis (SIR = 2.36, 95% CI = 2.12 to 2.63). When this period was excluded the risk was not raised, but it was high for some patient groups; in particular women aged <50 years with breast cancer (SIR = 2.13, 95% CI = 1.58 to 2.78), patients with bladder (SIR = 1.41, 95% CI = 1.19 to 1.67) and head & neck (SIR = 1.93, 95% CI = 1.67 to 2.21) cancer. Head & neck cancer patients had increased risks of lung cancer (SIR = 3.75, 95% CI = 3.01 to 4.62), oesophageal (SIR = 4.62, 95% CI = 2.73 to 7.29) and other head & neck tumours (SIR = 6.10, 95% CI = 4.17 to 8.61). Patients with bladder cancer had raised risks of lung (SIR = 2.18, 95% CI = 1.62 to 2.88) and prostate (SIR = 2.41, 95% CI = 1.72 to 3.30) cancer.<p></p> Conclusions: Relative risks of second primary cancers may be smaller than previously reported. Premenopausal women with breast cancer and patients with malignant melanomas, bladder and head & neck cancers may benefit from increased surveillance and advice to avoid known risk factors

FDG PET uptake characterization through texture analysis: investigating the complementary nature of heterogeneity and functional tumor volume in a multi-cancer site patient cohort.: FDG-PET heterogeneity and volume

International audienceIntra-tumor uptake heterogeneity in 18F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural features (TF) analysis is a promising method for its quantification. An open issue associated with the use of TF for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown as a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types.METHODS:A single database of 555 pre-treatment 18F-FDG PET images (breast, cervix, esophageal, head & neck and lung cancer tumors) was assembled. Four robust and reproducible TF-derived parameters were considered. The issues associated with the calculation of TF using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves was investigated using Spearman rank coefficients, for different volume ranges. The complementary prognostic value of MATV and TF was assessed through multivariate Cox analysis in the esophageal and NSCLC cohorts.RESULTS:A large range of MATVs was included in the population considered (3-415 cm3, mean = 35, median = 19, SD=50). The correlation between MATV and TF varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and the calculation method both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P = 0.0053 and 0.0093 respectively) along with stage (P = 0.002) in NSCLC, but in the esophageal tumors, volume and heterogeneity had less complementary value due to smaller overall volumes.CONCLUSION:Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10cm3, although the complementary information increases substantially with larger volumes

Tomographie par émission de positonns au moyen du 18 fluorodésoxyglucose (TEP 18 FDG) dans la prise en charge thérapeutique des cancers thyroïdiens dofférenciés

RENNES1-BU Santé (352382103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

18F-FDG PET image-derived tumor characterization to improve prediction of response to neoadjuvant chemotherapy on locally advanced breast cancer

International audienceObjectives: Early prediction of no response to neoadjuvant chemotherapy (NAC) in breast cancer may help in identifying patients that would benefit from alternative therapeutic strategies. The objective of this study was to assess the potential predictive value of tumor characterization from 18F-FDG PET images including metabolically active tumor volume (MATV) and uptake heterogeneity characterization using texture analysis. Methods: 89 patients were included who underwent scans at baseline (PET1) and before the 3rd cycle of NAC (PET2). Pathological response was assessed after surgery using the Sataloff scale. Several image-derived parameters were extracted from delineated MATVs, including SUV max, peak and mean; total lesion glycolysis (TLG); local/regional textural features. The predictive value of these parameters at PET1 or PET2, and their evolution between PET1 and PET2 ({Delta}param, %) was assessed through receiver operating characteristic (ROC) area under the curve (AUC) analysis. Results: There were 45 responders and 44 nonresponders. There was no response differentiation using PET1 absolute values only for any of the parameters considered (AUCs <0.6). On the contrary, an AUC of 0.82, 0.81, 0.74, 0.73 and 0.67 was obtained for {Delta}TLG, {Delta}MATV, {Delta}SUVmax, {Delta}SUVpeak and {Delta}SUVmean respectively. Several uptake heterogeneity features, such as entropy and variance, could also predict pathological response with an AUC of 0.78 and 0.69 respectively. Conclusions: Significantly better prediction of response to NAC was achieved with {Delta}TLG (specificity 89%, sensitivity 73%) over SUVmax (specificity 58%, sensitivity 84%) (p=0.02). Although uptake heterogeneity characterization by itself did not perform better than standard image-derived indices, they may still provide complementary information that could help in improving prediction, which will be assessed in future studies