In 18 F-FDG PET, tumors are often characterized by their metabolically active volume and standardized uptake value (SUV). However, many approaches have been proposed to estimate tumor volume and SUV from 18 F-FDG PET images, none of them being widely agreed upon. We assessed the accuracy and robustness of 5 methods for tumor volume estimates and of 10 methods for SUV estimates in a large variety of configurations. Methods: PET acquisitions of an anthropomorphic phantom containing 17 spheres (volumes between 0.43 and 97 mL, sphere-to-surrounding-activity concentration ratios between 2 and 68) were used. Forty-one nonspheric tumors (volumes between 0.6 and 92 mL, SUV of 2, 4, and 8) were also simulated and inserted in a real patient 18 F-FDG PET scan. Four threshold-based methods (including one, T bgd , accounting for background activity) and a model-based method (Fit) described in the literature were used for tumor volume measurements. The mean SUV in the resulting volumes were calculated, without and with partial-volume effect (PVE) correction, as well as the maximum SUV (SUV max ). The parameters involved in the tumor segmentation and SUV estimation methods were optimized using 3 approaches, corresponding to getting the best of each method or testing each method in more realistic situations in which the parameters cannot be perfectly optimized. Results: In the phantom and simulated data, the T bgd and Fit methods yielded the most accurate volume estimates, with mean errors of 2% 6 11% and 28% 6 21% in the most realistic situations. Considering the simulated data, all SUV not corrected for PVE had a mean bias between 231% and 246%, much larger than the bias observed with SUV max (211% 6 23%) or with the PVE-corrected SUV based on T bgd and Fit (22% 6 10% and 3% 6 24%). Conclusion: The method used to estimate tumor volume and SUV greatly affects the reliability of the estimates. The T bgd and Fit methods yielded low errors in volume estimates in a broad range of situations. The PVE-corrected SUV based on T bgd and Fit were more accurate and reproducible than SUV max .

Combined PET/computed tomography (CT) is of value in cancer diagnosis, follow-up, and treatment planning. For cancers located in the thorax or abdomen, the patient’s breathing causes artifacts and errors in PET and CT images. Many different approaches for artifact avoidance or correction have been developed; most are based on gated acquisition and synchronization between the respiratory signal and PET acquisition. The respiratory signal is usually produced by an external sensor that tracks a physiological characteristic related to the patient’s breathing. Respiratory gating is a compensation technique in which time or amplitude binning is used to exclude the motion in reconstructed PET images. Although this technique is performed in routine clinical practice, it fails to adequately correct for respiratory motion because each gate can mix several tissue positions. Researchers have suggested either selecting PET events from gated acquisitions or performing several PET acquisitions (corresponding to a breath-hold CT position). However, the PET acquisition time must be increased if adequate counting statistics are to be obtained in the different gates after binning. Hence, other researchers have assessed correction techniques that take account of all the counting statistics (without increasing the acquisition duration) and integrate motion information before, during, or after the reconstruction process. Here, we provide an overview of how motion is managed to overcome respiratory motion in PET/CT images.

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The purpose of this study was to compare in a large series of peripheral T cell lymphoma, as a model of diffuse disease, the prognostic value of baseline total metabolic tumor volume (TMTV) measured on 18 F-FDG PET/CT with adaptive thresholding methods with TMTV measured with a fixed 41% SUV max threshold method. Methods: One hundred six patients with peripheral T cell lymphoma, staged with PET/CT, were enrolled from 5 Lymphoma Study Association centers. In this series, TMTV computed with the 41% SUV max threshold is a strong predictor of outcome. On a dedicated workstation, we measured the TMTV with 4 adaptive thresholding methods based on characteristic image parameters: Daisne (Da) modified, based on signal-to-background ratio; Nestle (Ns), based on tumor and background intensities; Fit, including a 3-dimensional geometric model based on spatial resolution (Fit); and Black (Bl), based on mean SUV max . The TMTV values obtained with each adaptive method were compared with those obtained with the 41% SUV max method. Their respective prognostic impacts on outcome prediction were compared using receiver-operatingcharacteristic (ROC) curve analysis and Kaplan-Meier survival curves. Results: The median value of TMTV 41% , TMTV Da , TMTV Ns , TMTV Fit , and TMTV Bl were, respectively, 231 cm 3 (range, 5-3,824), 175 cm 3 (range, 8-3,510), 198 cm 3 (range, 3-3,934), 175 cm 3 (range, 8-3,512), and 333 cm 3 (range, 3-5,113). The intraclass correlation coefficients were excellent, from 0.972 to 0.988, for TMTV Da , TMTV Fit , and TMTV Ns , and less good for TMTV Bl (0.856). The mean differences obtained from the Bland-Altman plots were 48.5, 47.2, 19.5, and 2253.3 cm 3 , respectively. Except for Black, there was no significant difference within the methods between the ROC curves (P . 0.4) for progression-free survival and overall survival. Survival curves with the ROC optimal cutoff for each method separated the same groups of low-risk (volume # cutoff) from high-risk patients (volume . cutoff), with similar 2-y progression-free survival (range, 66%-72% vs. 26%-29%; hazard ratio, 3.7-4.1) and 2-y overall survival (79%-83% vs. 50%-53%; hazard ratio, 3.0-3.5). Conclusion: The prognostic value of TMTV remained quite similar whatever the methods, adaptive or 41% SUV max , supporting its use as a strong prognosticator in lymphoma. However, for implementation of TMTV in clinical trials 1 single method easily applicable in a multicentric PET review must be selected and kept all along the trial. PET/ CT with 18 F-FDG has been recognized as the best imaging tool for staging and response assessment in FDG-avid lymphoma. The last International Conference on Malignant Lymphoma recommendations (1) encourage investigating the quantitative analysis of 18 F-FDG PET/CT at staging. In this regard, the measurement of the total metabolic tumor volume (TMTV), which gives an estimation of the total tumor burden, has gained special interest. Indeed, several series have shown that TMTV was predictive of outcome in different lymphoma subtypes: d...