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Carole Lartizien

Publications and source records attributed to Carole Lartizien.

6 recordsLinked to original sources

Correction methods for random coincidences in fully 3D whole-body PET: impact on data and image quality.

UNLABELLED: With the advantages of the increased sensitivity of fully 3-dimensional (3D) PET for whole-body imaging come the challenges of more complicated quantitative corrections and, in particular, an increase in the number of random coincidences. The most common method of correcting for random coincidences is the real-time subtraction of a delayed coincidence channel, which does not add bias but increases noise. An alternative approach is the postacquisition subtraction of a low-noise random coincidence estimate, which can be obtained either from a smoothed delayed coincidence sinogram or from a calibration scan or directly estimated. Each method makes different trade-offs between noise amplification, bias, and data-processing requirements. These trade-offs are dependent on activity injected, the local imaging environment (e.g., near the bladder), and the reconstruction algorithm. METHODS: Using fully 3D whole-body simulations and phantom studies, we investigate how the gains in noise equivalent count (NEC) rates from using a noiseless random coincidence estimation method are translated to improvements in image signal-to-noise ratio (SNR). The image SNR, however, depends on the image reconstruction method and the local imaging environment. RESULTS: We show that for fully 3D whole-body imaging using a particular set of scanners and clinical protocols, a low-noise estimate of random coincidences improves sinogram and image SNRs by approximately 15% compared with online subtraction of delayed coincidences. CONCLUSION: A 15% improvement in image SNR arises from a 32% increase in the NEC rate. Thus, scan duration can be reduced by 25% while still maintaining a constant total acquired NEC.

Algorithms↗

Volumetric model and human observer comparisons of tumor detection for whole-body positron emission tomography.

RATIONALE AND OBJECTIVES: The performances of model and human observers were compared for detecting and localizing tumors in whole-body positron emission tomography imaging. Volumetric implementations of model observers were used instead of standard planar implementations to reproduce the common practice of using volumetric image displays to assess whole-body positron emission tomography images. MATERIALS AND METHODS: Observer studies with simulated data were used to compare three different acquisition protocols for an average patient size. Multiple realizations of simulated whole-body data with multiple added 1-cm diameter spherical lesions (targets) per image volume for efficiency were used. The location and contrast ratio of the targets were chosen randomly within ranges determined by initial calibration studies. Human observer studies were performed using a volumetric image display routinely used in clinical practice, and human observer detection performance was quantified using an alternate free-response operating characteristic analysis. The human detection performances were compared with the performances of volumetric implementations of the non-prewhitening matched filter and the channelized hotelling observer and also to the target contrast measured in the reconstructed image. RESULTS: Human observer detectability was generally well described as a linear function of these three figures of merit for the detection task considered. The best correlations (r = 0.96, rho = 0.98) were achieved with the channelized hotelling observer and non-prewhitening matched filter model observers. CONCLUSION: The use of volumetric model observers provides a means for quantitative comparisons of different protocols and also provides a useful tool for the optimization of key parameters in whole-body positron emission tomography imaging.

Humans↗

A lesion detection observer study comparing 2-dimensional versus fully 3-dimensional whole-body PET imaging protocols.

UNLABELLED: We compared the impact of 2-dimensional (2D) and fully 3-dimensional (3D) acquisition modes on the performance of human observers in detecting and localizing tumors in whole-body (18)F-FDG images. METHODS: We selected protocols based on noise equivalent count (NEC) rates derived from a series of 2D and fully 3D whole-body patient and phantom acquisitions on a dual-mode PET scanner. The fully 3D peak NEC value for a standard 70-kg patient was achieved for an injected dose of approximately 444 MBq (12 mCi) assuming a 90-min delay before acquisition, whereas the 2D peak value was never reached. The protocols were therefore set to those corresponding to a 444-MBq injected dose in fully 3D and 2D and a 740-MBq (20 mCi) injected dose in 2D that was considered as the maximum allowable dose. We used a non-Monte Carlo simulator to generate multiple realizations of whole-body PET data based on the geometry of the mathematic cardiac torso phantom (MCAT) with accurate noise properties. Two-dimensional and fully 3D acquisition times were set to 5 min per bed position. Spherical 1-cm-diameter lesions (targets) with random locations and contrasts were distributed in different organs. The simulated 2D datasets were reconstructed using attenuation-weighted ordered-subsets expectation maximization ((AW)OSEM) and the fully 3D datasets were reconstructed with FORE+(AW)OSEM (FORE = Fourier rebinning). Five human observers located and ranked the targets using a volumetric display of the whole-body PET data to replicate the clinical practice. An alternate free-response operating characteristic (AFROC) analysis of the human observer reports was performed for each protocol and each organ separately. RESULTS: The 2D protocol corresponding to 740-MBq injected dose allowed the overall best detection performance. It was followed by the fully 3D acquisition at the peak fully 3D NEC rate from a 444-MBq injected dose. A 2D acquisition corresponding to a 444-MBq injected dose was ranked last. Differences in detection performance were organ specific. CONCLUSION: This study showed that, for this patient size and scanner type, the fully 3D acquisition mode allowed better or equivalent detection performance than the 2D mode for an injected dose corresponding to the peak fully 3D NEC rate. The 2D acquisition protocol combined with a higher injected dose resulted in the highest detectabilities.

Algorithms↗

Synthesis and in vivo imaging properties of [11C]befloxatone: a novel highly potent positron emission tomography ligand for mono-amine oxidase-A.

Befloxatone (1, (5R)-5-(methoxymethyl)-3-[4-[(3R)-4,4,4-trifluoro-3-hydroxybutoxy]phenyl]-2-oxazolidinone) is an oxazolidinone derivative belonging to a new generation of reversible and selective mono-amine oxidase-A (MAO-A) inhibitors. In vitro and ex vivo studies have demonstrated that befloxatone is a potent, reversible and competitive MAO-A inhibitor with potential antidepressant properties. Befloxatone (1) was labelled with carbon-11 (t(12): 20.4 min) using [(11)C]phosgene as reagent. Typically, starting from a 1.2 Ci (44.4 GBq) cyclotron-produced [(11)C]CH(4) batch, 150-300 mCi (5.55-11.10 GBq) of [(11)C]befloxatone ([(11)C]-1) with a radiochemical- and chemical purity of more than 99% were routinely obtained within 20 min of radiosynthesis (including HPLC purification) with specific radioactivities of 500-2000 mCi/micromol (18.5-74.0 GBq/micromol). The results obtained in vivo with carbon-11-labelled befloxatone not only confirm the biochemical and pharmacological profile of befloxatone found in rodent and in human tissues but also point out [(11)C]befloxatone as an excellent tool for the assessment of MAO-A binding sites using positron emission tomography, a high-resolution, sensitive, non-invasive and quantitative imaging technique.

Animals↗

Evaluating image reconstruction methods for tumor detection in 3-dimensional whole-body PET oncology imaging.

UNLABELLED: We compare 3 image reconstruction algorithms for use in 3-dimensional (3D) whole-body PET oncology imaging. We have previously shown that combining Fourier rebinning (FORE) with 2-dimensional (2D) statistical image reconstruction via the ordered-subsets expectation-maximization (OSEM) and attenuation-weighted OSEM (AWOSEM) algorithms demonstrates improvements in image signal-to-noise ratios compared with the commonly used analytic 3D reprojection (3DRP) or FORE+FBP (2D filtered backprojection) reconstruction methods. To assess the impact of these reconstruction methods on detecting and localizing small lesions, we performed a human observer study comparing the different reconstruction methods. The observer study used the same volumetric visualization software tool that is used in clinical practice, instead of a planar viewing mode as is generally used with the standard receiver operating characteristic (ROC) methodology. This change in the human evaluation strategy disallowed the use of a ROC analysis, so instead we compared the fraction of actual targets found and reported (fraction-found) and also investigated the use of an alternative free-response operating characteristic (AFROC) analysis. METHODS: We used a non-Monte Carlo technique to generate 50 statistically accurate realizations of 3D whole-body PET data based on an extended mathematic cardiac torso (MCAT) phantom and with noise levels typical of clinical scans performed on a PET scanner. To each realization, we added 7 randomly located 1-cm-diameter lesions (targets) whose contrasts were varied to sample the range of detectability. These targets were inserted in 3 organs of interest: lungs, liver, and soft tissues. The images were reconstructed with 3 reconstruction strategies (FORE+OSEM, FORE+AWOSEM, and FORE+FBP). Five human observers reported (localized and rated) 7 targets within each volume image. An observer's performance accuracy with each algorithm was measured, as a function of the lesion contrast and organ type, by the fraction of those targets reported and by the area below the AFROC curve. This AFROC curve plots the fraction of reported targets at each rating threshold against the fraction of cases with (> or =1) similarly rated false reports. RESULTS: Images reconstructed with FORE+AWOSEM yielded the best overall target detection as compared with FORE+FBP and FORE+OSEM, although these differences in detectability were region specific. The FORE+FBP and FORE+AWOSEM algorithms had similar performances for liver targets. The FORE+OSEM algorithm performed significantly worse at target detection, especially in the liver. We speculate that this is the result of using an incorrect statistical model for OSEM and that the incorporation of attenuation weighting in AWOSEM largely compensates for this model inaccuracy. These results were consistent for both the fraction of actual targets found and the AFROC analysis. CONCLUSION: We demonstrated the efficacy of performing observer detection studies using the same visualization tools as those used in clinical PET oncology imaging. These studies demonstrated that the FORE+AWOSEM algorithm led to the best overall detection and localization performance for 1-cm-diameter targets compared with the FORE+OSEM and FORE+FBP algorithms.

Algorithms↗

Optimization of injected dose based on noise equivalent count rates for 2- and 3-dimensional whole-body PET.

UNLABELLED: The noise equivalent count (NEC) rate index is used to derive guidelines on the optimal injected dose to the patient for 2-dimensional (2D) and 3-dimensional (3D) whole-body PET acquisitions. METHODS: We performed 2D and 3D whole-body acquisitions of an anthropomorphic phantom modeling the conditions for (18)F-FDG PET of the torso and measured the NEC rates for different activity levels for several organs of interest. The correlations between count rates measured from the phantom and those from a series of whole-body patient scans were then analyzed. This analysis allowed validation of our approach and estimation of the injected dose that maximizes NEC rate as a function of patient morphology for both acquisition modes. RESULTS: Variations of the phantom and patient prompt and random coincidence rates as a function of single-photon rates correlated well. On the basis of these correlations, we demonstrated that the patient NEC rate can be predicted for a given single-photon rate. Finally, we determined that patient single-photon rates correlated with the mean dose per weight at acquisition start when normalized by the body mass index. This correlation allows modifying the injected dose as a function of patient body mass index to reach the peak NEC rate in 3D mode. Conversely, we found that the peak NEC rates were never reached in 2D mode within an acceptable range of injected dose. CONCLUSION: The injected dose was adapted to patient morphology for 2D and 3D whole-body acquisitions using the NEC rate as a figure of merit of the statistical quality of the sinogram data. This study is a first step toward a more comprehensive comparison of the image quality obtained using both acquisition modes.

Fluorodeoxyglucose F18↗