Metabolically active volumes automatic delineation methodologies in PET imaging: review and perspectives

International audiencePET imaging is now considered a gold standard tool in clinical oncology, especially for diagnosis purposes. More recent applications such as therapy follow up or tumor targeting in radiotherapy require a fast, accurate and robust metabolically active tumor volumes on emission images, which cannot be obtained through manual contouring. This clinical need has sprung a large number of methodological developments regarding automatic methods to defined tumor volumes on PET images. This paper reviews most of the methodologies that have been recently proposed and discusses their framework and methodological and/or clinical validation. Perspectives regarding the future work to be done are also suggested

A Study of Inclusive Double-Pomeron-Exchange in p pbar -> p X pbar at root s = 630 GeV

We report measurements of the inclusive reaction, p pbar -> p X pbar, in events where either or both the beam-like final-state baryons were detected in Roman-pot spectrometers and the central system was detected in the UA2 calorimeter. A Double-Pomeron-Exchange (DPE) analysis of these data and single diffractive data from the same experiment demonstrates that, for central masses of a few GeV, the extracted Pomeron-Pomeron total cross section exhibits an enhancement which exceeds factorization expectations by an order-of-magnitude. This may be a signature for glueball production. The enhancement is shown to be independent of uncertainties connected with possible non-universality of the Pomeron flux factor. Based on our analysis, we present DPE cross section predictions, for unit (1 mb) Pomeron-Pomeron total cross section, at the Tevatron, LHC and the 920 GeV fixed-target experiment, HERA-B.Comment: 52 pages, 27 Encapsulated Postscript figures, 3 Tables, LaTex, Revised version as it will appear in European Physics Journal

The age of reason for FDG PET image-derived indices.

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Cross Section Measurements of Hard Diffraction at the SPS-Collider

The UA8 experiment previously reported the observation of jets in diffractive events containing leading protons (``hard diffraction''), which was interpreted as evidence for the partonic structure of an exchanged Reggeon, believed to be the Pomeron . In the present Letter, we report the final UA8 hard-diffractive (jet) cross section results and their interpretation. After corrections, the fraction of single diffractive events with mass from 118 to 189 GeV that have two scattered partons, each with Et_jet > 8 GeV, is in the range 0.002 to 0.003 (depending on x_p). We determine the product, fK, of the fraction by which the Pomeron's momentum sum rule is violated and the normalization constant of the Pomeron-Flux-Factor of the proton. For a pure gluonic- or a pure qqbar-Pomeron , respectively: fK = 0.30 +- 0.05 +- 0.09) and (0.56 +- 0.09 +- 0.17) GeV^-2.Comment: 20 pages, 5 Encapsulated Postscript figures, LaTex, Final Version, Physics Letters B (in Pess 1998

Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.: 18F-FDG PET and CT tumor delineation in NSCLC

International audienceUNLABELLED: The objectives of this study were to investigate the relationship between CT- and (18)F-FDG PET-based tumor volumes in non-small cell lung cancer (NSCLC) and the impact of tumor size and uptake heterogeneity on various approaches to delineating uptake on PET images. METHODS: Twenty-five NSCLC cancer patients with (18)F-FDG PET/CT were considered. Seventeen underwent surgical resection of their tumor, and the maximum diameter was measured. Two observers manually delineated the tumors on the CT images and the tumor uptake on the corresponding PET images, using a fixed threshold at 50% of the maximum (T(50)), an adaptive threshold methodology, and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Maximum diameters of the delineated volumes were compared with the histopathology reference when available. The volumes of the tumors were compared, and correlations between the anatomic volume and PET uptake heterogeneity and the differences between delineations were investigated. RESULTS: All maximum diameters measured on PET and CT images significantly correlated with the histopathology reference (r > 0.89, P < 0.0001). Significant differences were observed among the approaches: CT delineation resulted in large overestimation (+32% ± 37%), whereas all delineations on PET images resulted in underestimation (from -15% ± 17% for T(50) to -4% ± 8% for FLAB) except manual delineation (+8% ± 17%). Overall, CT volumes were significantly larger than PET volumes (55 ± 74 cm(3) for CT vs. from 18 ± 25 to 47 ± 76 cm(3) for PET). A significant correlation was found between anatomic tumor size and heterogeneity (larger lesions were more heterogeneous). Finally, the more heterogeneous the tumor uptake, the larger was the underestimation of PET volumes by threshold-based techniques. CONCLUSION: Volumes based on CT images were larger than those based on PET images. Tumor size and tracer uptake heterogeneity have an impact on threshold-based methods, which should not be used for the delineation of cases of large heterogeneous NSCLC, as these methods tend to largely underestimate the spatial extent of the functional tumor in such cases. For an accurate delineation of PET volumes in NSCLC, advanced image segmentation algorithms able to deal with tracer uptake heterogeneity should be preferred

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

Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET.

International audienceAccurate volume of interest (VOI) estimation in PET is crucial in different oncology applications such as response to therapy evaluation and radiotherapy treatment planning. The objective of our study was to evaluate the performance of the proposed algorithm for automatic lesion volume delineation; namely the fuzzy hidden Markov chains (FHMC), with that of current state of the art in clinical practice threshold based techniques. As the classical hidden Markov chain (HMC) algorithm, FHMC takes into account noise, voxel intensity and spatial correlation, in order to classify a voxel as background or functional VOI. However the novelty of the fuzzy model consists of the inclusion of an estimation of imprecision, which should subsequently lead to a better modelling of the 'fuzzy' nature of the object of interest boundaries in emission tomography data. The performance of the algorithms has been assessed on both simulated and acquired datasets of the IEC phantom, covering a large range of spherical lesion sizes (from 10 to 37 mm), contrast ratios (4:1 and 8:1) and image noise levels. Both lesion activity recovery and VOI determination tasks were assessed in reconstructed images using two different voxel sizes (8 mm3 and 64 mm3). In order to account for both the functional volume location and its size, the concept of % classification errors was introduced in the evaluation of volume segmentation using the simulated datasets. Results reveal that FHMC performs substantially better than the threshold based methodology for functional volume determination or activity concentration recovery considering a contrast ratio of 4:1 and lesion sizes of <28 mm. Furthermore differences between classification and volume estimation errors evaluated were smaller for the segmented volumes provided by the FHMC algorithm. Finally, the performance of the automatic algorithms was less susceptible to image noise levels in comparison to the threshold based techniques. The analysis of both simulated and acquired datasets led to similar results and conclusions as far as the performance of segmentation algorithms under evaluation is concerned

Measurement of the branching ratio of the decay Ξ0→Σ+μ−νˉμ\Xi^{0}\rightarrow \Sigma^{+} \mu^{-} \bar{\nu}_{\mu}

From the 2002 data taking with a neutral kaon beam extracted from the CERN-SPS, the NA48/1 experiment observed 97 $\Xi^{0}\rightarrow \Sigma^{+} \mu^{-} \bar{\nu}_{\mu}$ candidates with a background contamination of $30.8 \pm 4.2$ events. From this sample, the BR($\Xi^{0}\rightarrow \Sigma^{+} \mu^{-} \bar{\nu}_{\mu}$) is measured to be $(2.17 \pm 0.32_{\mathrm{stat}}\pm 0.17_{\mathrm{syst}})\times10^{-6}$

Recent NA48/2 and NA62 results

The NA48/2 Collaboration at CERN has accumulated and analysed unprecedented statistics of rare kaon decays in the $K_{e4}$ modes: $K_{e4}(+-)$ ($K^\pm \to \pi^+ \pi^- e^\pm \nu$) and $K_{e4}(00)$ ($K^\pm \to \pi^0 \pi^0 e^\pm \nu$) with nearly one percent background contamination. It leads to the improved measurement of branching fractions and detailed form factor studies. New final results from the analysis of 381 $K^\pm \to \pi^\pm \gamma \gamma$ rare decay candidates collected by the NA48/2 and NA62 experiments at CERN are presented. The results include a decay rate measurement and fits to Chiral Perturbation Theory (ChPT) description.Comment: Prepared for the Proceedings of "Moriond QCD and High Energy Interactions. March 22-29 2014." conferenc