Sebastien Hapdey

Management of respiratory motion in PET/computed tomography: the state of the art.

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.

Searching for Alternatives to Full Kinetic Analysis in 18F-FDG PET: An Extension of the Simplified Kinetic Analysis Method

The most accurate way to estimate the glucose metabolic rate (or its influx constant) from 18F-FDG PET is to perform a full kinetic analysis (or its simplified Patlak version), requiring dynamic imaging and the knowledge of arterial activity as a function of time. To avoid invasive arterial blood sampling, a simplified kinetic analysis (SKA) has been proposed, based on blood curves measured from a control group. Here, we extend the SKA by allowing for a greater variety of arterial input function (A(t)) curves among patients than in the original SKA and by accounting for unmetabolized 18F-FDG in the tumor. Methods: Ten A(t)s measured in patients were analyzed using a principal-component analysis to derive 2 principal components describing most of the variability of the A(t). The mean distribution volume of 18F-FDG in tumors for these patients was used to estimate the corresponding quantity in other patients. In subsequent patient studies, the A(t) was described as a linear combination of the 2 principal components, for which the 2 scaling factors were obtained from an early and a late venous sample drawn for the patient. The original and extended SKA (ESKA) were assessed using fifty-seven 18F-FDG PET scans with various tumor types and locations and using different injection and acquisition protocols, with the Ki derived from Patlak analysis as a reference. Results: ESKA improved the accuracy or precision of the input function (area under the blood curve) for all protocols examined. The mean errors (±SD) in Ki estimates were −12% ± 33% for SKA and −7% ± 22% for ESKA for a 20-s injection protocol with a 55-min postinjection PET scan, 20% ± 42% for SKA and 1% ± 29% for ESKA (P < 0.05) for a 120-s injection protocol with a 55-min postinjection PET scan, and −37% ± 19% for SKA and −4% ± 6% for ESKA (P < 0.05) for a 20-s injection protocol with a 120-min postinjection PET scan. Changes in Ki between the 2 PET scans in the same patients also tended to be estimated more accurately and more precisely with ESKA than with SKA. Conclusion: ESKA, compared with SKA, significantly improved the accuracy and precision of Ki estimates in 18F-FDG PET. ESKA is more robust than SKA with respect to various injection and acquisition protocols.

Baseline Total Metabolic Tumor Volume measured with fixed or different adaptive thresholding methods equally predicts outcome in Peripheral T cell lymphoma.

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 18F-FDG PET/CT with adaptive thresholding methods with TMTV measured with a fixed 41% SUVmax 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% SUVmax 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 SUVmax. The TMTV values obtained with each adaptive method were compared with those obtained with the 41% SUVmax method. Their respective prognostic impacts on outcome prediction were compared using receiver-operating-characteristic (ROC) curve analysis and Kaplan–Meier survival curves. Results: The median value of TMTV41%, TMTVDa, TMTVNs, TMTVFit, and TMTVBl were, respectively, 231 cm3 (range, 5–3,824), 175 cm3 (range, 8–3,510), 198 cm3 (range, 3–3,934), 175 cm3 (range, 8–3,512), and 333 cm3 (range, 3–5,113). The intraclass correlation coefficients were excellent, from 0.972 to 0.988, for TMTVDa, TMTVFit, and TMTVNs, and less good for TMTVBl (0.856). The mean differences obtained from the Bland–Altman plots were 48.5, 47.2, 19.5, and −253.3 cm3, 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% SUVmax, 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.

The influence of tumor oxygenation on (18)F-FDG (fluorine-18 deoxyglucose) uptake: a mouse study using positron emission tomography (PET).

BackgroundThis study investigated whether changing a tumors oxygenation would alter tumor metabolism, and thus uptake of 18F-FDG (fluorine-18 deoxyglucose), a marker for glucose metabolism using positron emission tomography (PET).ResultsTumor-bearing mice (squamous cell carcinoma) maintained at 37°C were studied while breathing either normal air or carbogen (95% O2, 5% CO2), known to significantly oxygenate tumors. Tumor activity was measured within an automatically determined volume of interest (VOI). Activity was corrected for the arterial input function as estimated from image and blood-derived data. Tumor FDG uptake was initially evaluated for tumor-bearing animals breathing only air (2 animals) or only carbogen (2 animals). Subsequently, 5 animals were studied using two sequential 18F-FDG injections administered to the same tumor-bearing mouse, 60 min apart; the first injection on one gas (air or carbogen) and the second on the other gas. When examining the entire tumor VOI, there was no significant difference of 18F-FDG uptake between mice breathing either air or carbogen (i.e. air/carbogen ratio near unity). However, when only the highest 18F-FDG uptake regions of the tumor were considered (small VOIs), there was a modest (21%), but significant increase in the air/carbogen ratio suggesting that in these potentially most hypoxic regions of the tumor, 18F-FDG uptake and hence glucose metabolism, may be reduced by increasing tumor oxygenation.ConclusionTumor 18F-FDG uptake may be reduced by increases in tumor oxygenation and thus may provide a means to further enhance 18F-FDG functional imaging.

Delineation of small mobile tumours with FDG-PET/CT in comparison to pathology in breast cancer patients

PURPOSE Various segmentation methods for 18F-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT) images were correlated with pathological volume in breast cancer patients as a model of small mobile tumours. METHODS Thirty women with T2-T3/M0 breast invasive ductal carcinoma (IDC) were included prospectively. A FDG-PET/CT was acquired 4 ± 3d before surgery in prone and supine positions, with/without respiratory gating. The segmentation methods were as follows: manual (Vm), relative (Vt%) and adaptive (Va) standard uptake value (SUV) threshold and semi-automatic on CT (Vct). Pathological volumes (Vpath) were measured for 26 lesions. RESULTS The mean (±SD) Vpath was 4.1 ± 2.9 mL, and the lesion displacements were 3.9 ± 2.8 mm (median value: 3 mm). The delineated VOIs did not vary with the acquisition position nor with respiration, regardless of the segmentation method. The Vm, Va, Vct and Vt% methods, except Vt30%, were correlated with Vpath (0.5<r<0.8). The Vt50% and Vm were the most accurate methods (mean±SD: 0.0 ± 1.6 mL and +0.6 ± 1.8 mL, respectively), followed by the Vct method. CONCLUSIONS When compared with pathology, small lesions (diameter <50mm) with limited respiratory displacement (i.e., breast or apical lung lesions) are best delineated on FDG-PET/CT using a 50% SUVmax threshold. The acquisition position and respiratory gating did not modify the delineated volumes.

Clinical respiratory motion correction software (reconstruct, register and averaged-RRA), for (18)F-FDG-PET-CT: phantom validation, practical implications and patient evaluation.

OBJECTIVE On fluorine-18 fludeoxyglucose (18F-FDG) positron emission tomography (PET) CT of pulmonary or hepatic lesions, standard uptake value (SUV) is often underestimated due to patient breathing. The aim of this study is to validate, on phantom and patient data, a motion correction algorithm [reconstruct, register and averaged (RRA)] implemented on a PET-CT system. METHODS Three phantoms containing five spheres filled with 18F-FDG and suspended in a water or Styrofoam®18F-FDG-filled tank to create different contrasts and attenuation environment were acquired on a Discovery GE710. The spheres were animated with a 2-cm longitudinal respiratory-based movement. Respiratory-gated (RRA) and ungated PET images were compared with static reference images (without movement). The optimal acquisition time, number of phases and the best phase within the respiratory cycle were investigated. The impact of irregular motion was also investigated. Quantification impact was computed on each sphere. Quantification improvement on 28 lung lesions was also investigated. RESULTS Phantoms: 4 min was required to obtain a stable quantification with the RRA method. The reference phase and the number of phases used for RRA did not affect the quantification which was similar on static acquisitions but different on ungated images. The results showed that the maximum standard uptake value (SUVmax) restoration is majored for the smallest spheres (≤2.1 ml). PATIENTS SUVmax on RRA and ungated acquisitions were statistically different to the SUVmax on whole-body images (p = 0.05) but not different from each other (mean SUVmax: 7.0 ± 7.8 vs 6.9 ± 7.8, p = 0.23 on RRA and ungated images, respectively). We observed a statistically significant correlation between SUV restoration and lesion displacement, with a real SUV quantitation improvement for lesion with movement >1.2 mm. CONCLUSION According to the results obtained using phantoms, RRA method is promising, showing a real impact on the lesion quantification on phantom data. With regard to the patient study, our results showed a trend towards an increase in the SUVs and a decrease in the volume between the ungated and RRA data. We also noticed a statistically significant correlation between the quantitative restoration obtained with RRA compared with ungated data and lesion displacement, indicating that the RRA approach should be reserved to patients with small lesions or nodes moving with a displacement larger than 1.2 cm. Advances in knowledge: This article investigates the performances of motion correction software recently introduced in PET. The conclusion revealed that such respiratory motion correction approach shows a real impact on the lesion quantification but must be reserved to the patient for whom lesion displacement was confirmed and high enough to clearly impact lesion evaluation.

Reproducibility of the adaptive thresholding calibration procedure for the delineation of 18F-FDG-PET-positive lesions.

ObjectiveThe aim of the study was to evaluate the robustness of the calibration procedure against the counting statistics and lesion volumes when using an adaptive thresholding method for the delineation of 2-[18F]fluoro-2-deoxyglucose (18F-FDG)-PET-positive tissue. Materials and methodsThree data sets obtained from physical and simulated images of a phantom containing hot spheres of known volume and contrast were used to study the robustness of the calibration procedure against the counting statistics and range of volumes and contrasts for a given PET model. The mathematical expression of the adaptive thresholding method used corresponds to a linear relationship between the optimal threshold value and the inverse of the local contrast. Robustness was evaluated by testing whether the slopes and intercepts of the linear expression found under two experimental conditions were significantly different (P<0.05). ResultsIt was found that the calibration step was not sensitive to the PET device for the studied PET model, nor to the counting statistics for a signal-to-noise ratio higher than 5.7. No statistical difference was found in the calibration step when using a wide range of volumes (0.2–200 ml) and contrasts (2.0–20.6) or more restricted ones (0.43–97.3 ml and 2.0–7.7, respectively). Therefore, a calibration procedure using limited experimental conditions can be applied to a wider range of volumes and contrasts. ConclusionThese results show that the manufacturer could propose simulated or experimental raw data corresponding to a given PET model with high counting statistics, allowing each clinical center to reconstruct calibration images according to the algorithm parameters used in the clinic.