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PurposeThe purpose of this study was to investigate the use of a probabilistic quad-tree graph (hidden Markov tree, HMT) to provide fast computation, robustness and an interpretational framework for multimodality image processing and to evaluate this framework for single gross tumor target (GTV) delineation from both positron emission tomography (PET) and computed tomography (CT) images.MethodsWe exploited joint statistical dependencies between hidden states to handle the data stack using multi-observation, multi-resolution of HMT and Bayesian inference. This framework was applied to segmentation of lung tumors in PET/CT datasets taking into consideration simultaneously the CT and the PET image information. PET and CT images were considered using either the original voxels intensities, or after wavelet/contourlet enhancement. The Dice similarity coefficient (DSC), sensitivity (SE), positive predictive value (PPV) were used to assess the performance of the proposed approach on one simulated and 15 clinical PET/CT datasets of non-small cell lung cancer (NSCLC) cases. The surrogate of truth was a statistical consensus (obtained with the Simultaneous Truth and Performance Level Estimation algorithm) of three manual delineations performed by experts on fused PET/CT images. The proposed framework was applied to PET-only, CT-only and PET/CT datasets, and were compared to standard and improved fuzzy c-means (FCM) multimodal implementations.ResultsA high agreement with the consensus of manual delineations was observed when using both PET and CT images. Contourlet-based HMT led to the best results with a DSC of 0.92 0.11 compared to 0.89 +/- 0.13 and 0.90 +/- 0.12 for Intensity-based HMT and Wavelet-based HMT, respectively. Considering PET or CT only in the HMT led to much lower accuracy. Standard and improved FCM led to comparatively lower accuracy than HMT, even when considering multimodal implementations.ConclusionsWe evaluated the accuracy of the proposed HMT-based framework for PET/CT image segmentation. The proposed method reached good accuracy, especially with pre-processing in the contourlet domain.

Purpose: 4D positron emission tomography and computed tomography (PET/CT) can be used to reduce motion artifacts by correlating the raw PET data with the respiratory cycle. The accuracy of each PET phase is dependent on the reproducibility and consistency of the breathing cycle during acquisition. The objective of this study is to evaluate the impact of breathing amplitude and phase irregularities on the quantitative accuracy of 4D PET standardized uptake value (SUV) measurements. In addition, the magnitude of quantitative errors due to respiratory motion and partial volume error are compared.Methods: Phantom studies were performed using spheres filled with F-18 ranging from 9 to 47 mm in diameter with background activity. Motion was simulated using patient breathing data. The authors compared the accuracy of SUVs derived from gated PET (4 bins and 8 bins, phase-based) for ideal, average, and highly irregular breathing patterns.Results: Under ideal conditions, gated PET produced SUVs that were within (-5.4 +/- 5.3)% of the static phantom measurements averaged across all sphere sizes. With breathing irregularities, the quantitative accuracy of gated PET decreased. Gated PET SUVs (best of 4 bins) were (-9.6 +/- 13.0)% of the actual value for an average breather and decreased to (-17.1 +/- 10.8)% for a highly irregular breather. Without gating, the differences in the SUV from actual value were (-28.5 +/- 18.2)%, (-25.9 +/- 14.4)%, and (-27.9 +/- 18.2)% for the ideal, average, and highly irregular breather, respectively.Conclusions: Breathing irregularities reduce the quantitative accuracy of gated PET/CT. Current gated PET techniques may underestimate the actual lesion SUV due to phase assignment errors. Evaluation of respiratory trace is necessary to assess accuracy of data binning and its effect on 4D PET SUVs. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4766876]

Purpose: 4D positron emission tomography and computed tomography (PET/CT) can be used to reduce motion artifacts by correlating the raw PET data with the respiratory cycle. The accuracy of each PET phase is dependent on the reproducibility and consistency of the breathing cycle during acquisition. The objective of this study is to evaluate the impact of breathing amplitude and phase irregularities on the quantitative accuracy of 4D PET standardized uptake value (SUV) measurements. In addition, the magnitude of quantitative errors due to respiratory motion and partial volume error are compared. Methods: Phantom studies were performed using spheres filled with F-18 ranging from 9 to 47 mm in diameter with background activity. Motion was simulated using patient breathing data. The authors compared the accuracy of SUVs derived from gated PET (4 bins and 8 bins, phase-based) for ideal, average, and highly irregular breathing patterns. Results: Under ideal conditions, gated PET produced SUVs that were within (-5.4 +/- 5.3)% of the static phantom measurements averaged across all sphere sizes. With breathing irregularities, the quantitative accuracy of gated PET decreased. Gated PET SUVs (best of 4 bins) were (-9.6 +/- 13.0)% of the actual value for an average breather and decreased to (-17.1 +/- 10.8)% for a highly irregular breather. Without gating, the differences in the SUV from actual value were (-28.5 +/- 18.2)%, (-25.9 +/- 14.4)%, and (-27.9 +/- 18.2)% for the ideal, average, and highly irregular breather, respectively. Conclusions: Breathing irregularities reduce the quantitative accuracy of gated PET/CT. Current gated PET techniques may underestimate the actual lesion SUV due to phase assignment errors. Evaluation of respiratory trace is necessary to assess accuracy of data binning and its effect on 4D PET SUVs. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4766876]

Purpose: 4D positron emission tomography and computed tomography (PET/CT) can be used to reduce motion artifacts by correlating the raw PET data with the respiratory cycle. The accuracy of each PET phase is dependent on the reproducibility and consistency of the breathing cycle during acquisition. The objective of this study is to evaluate the impact of breathing amplitude and phase irregularities on the quantitative accuracy of 4D PET standardized uptake value (SUV) measurements. In addition, the magnitude of quantitative errors due to respiratory motion and partial volume error are compared. Methods: Phantom studies were performed using spheres filled with F-18 ranging from 9 to 47 mm in diameter with background activity. Motion was simulated using patient breathing data. The authors compared the accuracy of SUVs derived from gated PET (4 bins and 8 bins, phase-based) for ideal, average, and highly irregular breathing patterns. Results: Under ideal conditions, gated PET produced SUVs that were within (-5.4 +/- 5.3)% of the static phantom measurements averaged across all sphere sizes. With breathing irregularities, the quantitative accuracy of gated PET decreased. Gated PET SUVs (best of 4 bins) were (-9.6 +/- 13.0)% of the actual value for an average breather and decreased to (-17.1 +/- 10.8)% for a highly irregular breather. Without gating, the differences in the SUV from actual value were (-28.5 +/- 18.2)%, (-25.9 +/- 14.4)%, and (-27.9 +/- 18.2)% for the ideal, average, and highly irregular breather, respectively. Conclusions: Breathing irregularities reduce the quantitative accuracy of gated PET/CT. Current gated PET techniques may underestimate the actual lesion SUV due to phase assignment errors. Evaluation of respiratory trace is necessary to assess accuracy of data binning and its effect on 4D PET SUVs. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4766876]