Antoine Martineau

18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

Intratumoral uptake heterogeneity in 18F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown to be 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 pretreatment 18F-FDG PET images (breast, cervix, esophageal, head and neck, and lung cancer tumors) was assembled. Four robust and reproducible textural feature–derived parameters were considered. The issues associated with the calculation of textural features 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 textural features was assessed through multivariate Cox analysis in the esophageal and non–small cell lung cancer (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 textural features varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and calculation methods 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 non–small cell lung cancer, but in the esophageal tumors, volume and heterogeneity had less complementary value because of smaller overall volumes. Conclusion: Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10 cm3, although the complementary information increases substantially with larger volumes.

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

The goal of this study was to determine the best predictive factor among image-derived parameters extracted from sequential 18F-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 ΔSUVmax (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 18F-FDG PET for early prediction of response to neoadjuvant chemotherapy.

Estrogen receptor-positive/human epidermal growth factor receptor 2-negative breast tumors: Early prediction of chemosensitivity with (18) F-fluorodeoxyglucose positron emission tomography/computed tomography during neoadjuvant chemotherapy.

The objective of this prospective study was to evaluate the ability of 18F‐fluorodeoxyglucose (18F‐FDG) positron emission tomography/computed tomography (PET/CT) to predict chemosensitivity in patients with estrogen receptor (ER)‐positive/human epidermal growth factor receptor 2 (HER2)‐negative breast cancer.

Early Metabolic Response to Neoadjuvant Treatment: FDG PET/CT Criteria according to Breast Cancer Subtype

PURPOSE To investigate parameters based on fluorine 18 fluorodeoxyglucose (FDG) positron emission tomographic (PET) imaging that are best correlated with pathologic complete response (PCR) in human epidermal growth factor receptor type 2 (HER2)-positive cancer and triple-negative breast cancer (TNBC) and with partial or complete response in ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS This study was approved by institutional review board with waivers of informed written consent and included consecutive patients treated by neoadjuvant chemotherapy. Five PET examination-derived parameters were tested: standard uptake value (SUV) maximum (SUV(max)), peak (SUV(peak)), and mean (SUV(mean)), metabolically active tumor volume, and total lesion glycolysis (TLG). Absolute values at baseline PET, at PET imaging after two cycles of chemotherapy, and variation (ie, change) were measured. Correlations with pathologic response (Wilcoxon rank-sum test) and predictive power assessed (area under the curve [AUC] on the basis of receiver operating characteristic analysis) were examined. RESULTS Included were 169 consecutive patients (mean age, 50 years). PCR was more frequent in HER2-positive tumors (16 of 33 patients [48.5%]) and TNBCs (20 of 54 patients [37%]) than in ER positive/HER2-negative tumors (four of 82 [4.9%]) (P < .001). Among patients with ER-positive/HER2-negative cancers, 33 patients had partial response. In TNBC, best association with PCR was obtained with change in SUV(max) (AUC, 0.86) or change in TLG (AUC, 0.88). In HER2-positive phenotype, absolute SUV(max) (or SUV(peak)) values at PET imaging after two cycles of chemotherapy (AUC for each cycle, 0.93) were better correlated with PCR than change in SUV(max) (AUC, 0.78; P = .11) or change in TLG (AUC, 0.62; P = .005). Regarding ER-positive/HER2-negative cancers, change in SUV(max) or change in TLG (AUC, 0.75) were parameters best correlated with partial or complete response. Baseline SUV(max) was higher in lymph nodes than in primary tumor in 31 patients. Findings were similar considering the site with highest FDG uptake. CONCLUSION Quantitative indexes of tumor glucose use that are best correlated with pathologic response vary by phenotype: change in SUV(max) or TLG are most adequate for TNBCs and ER-positive/ HER2-negative cancers and absolute SUV(max) after two cycles of chemotherapy for HER2-positive breast cancers.

Correlation between tumour characteristics, SUV measurements, metabolic tumour volume, TLG and textural features assessed with 18F-FDG PET in a large cohort of oestrogen receptor-positive breast cancer patients

PurposeThe study was designed to evaluate 1) the relationship between PET image textural features (TFs) and SUVs, metabolic tumour volume (MTV), total lesion glycolysis (TLG) and tumour characteristics in a large prospective and homogenous cohort of oestrogen receptor-positive (ER+) breast cancer (BC) patients, and 2) the capability of those parameters to predict response to neoadjuvant chemotherapy (NAC).Methods171 consecutive patients with large or locally advanced ER+ BC without distant metastases underwent an 18F-FDG PET examination before NAC. The primary tumour was delineated with an adaptive threshold segmentation method. Parameters of volume, intensity and texture (entropy, homogeneity, contrast and energy) were measured and compared with tumour characteristics determined on pre-treatment breast biopsy (Wilcoxon rank-sum test). The correlation between PET-derived parameters was determined using Spearman’s coefficient. The relationship between PET features and pathological findings was determined using the Wilcoxon rank-sum test.ResultsSpearman’s coefficients between SUVmax and TFs were 0.43, 0.24, -0.43 and -0.15 respectively for entropy, homogeneity, energy and contrast; they were higher between MTV and TFs: 0.99, 0.86, -0.99 and -0.87. All TFs showed a significant association with the histological type (IDC vs. ILC; 0.02 < P < 0.03) but didn’t with immunohistochemical characteristics. SUVmax and TLG predicted the pathological response (P = 0.0021 and P = 0.02 respectively); TFs didn’t (P: 0.27, 0.19, 0.94, 0.19 respectively for entropy, homogeneity, energy and contrast).ConclusionsThe correlation of TFs was poor with SUV parameters and high with MTV. TFs showed a significant association with the histological type. Finally, while SUVmax and TLG were able to predict response to NAC, TFs failed.

Effect of variation in relaxation parameter value on LOR-RAMLA reconstruction of 18F-FDG PET studies.

PurposeWe tested the impact of different values of the relaxation parameter lambda (λ) on contrast and noise in line-of-response row-action maximum likelihood algorithm (LOR-RAMLA) in 18F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) imaging. MethodsPhantom studies were performed on a Gemini XL PET/CT scanner. The NEMA/IEC (National Electrical Manufacturers Association/International Electro technical Commission) torso phantom was used and acquisition data were reconstructed with λ values ranging from 0.025 to 0.1. Quality of the reconstructed images was evaluated by contrast recovery coefficients and background variability values according to the NEMA NU 2-2001 procedures. ResultsContrast recovery coefficients and background variability increased significantly when λ increased. The best noise-versus-resolution trade-off was obtained with λ in the 0.04–0.06 range. For LOR-RAMLA reconstruction, the manufacturer allows a possible λ choice from 0.025 to 0.1. We would not advise too small (0.025) or too large (0.1) λ values which result in too smooth or too noisy images. ConclusionWe determined optimal λ values in LOR-RAMLA on a Gemini XL PET/CT scanner. Caution is needed when using λ values out of that range.