Zero-Extra-Dose PET Delayed Imaging with Data-Driven Attenuation Correction Estimation

Role of dual-time point 18F-FDG PET/CT imaging in the primary diagnosis and staging of hilar cholangiocarcinoma

PURPOSE

The aim of this study was to evaluate the role of dual-time point ¹⁸F-FDG PET/CT imaging in the primary diagnosis and staging of hilar cholangiocarcinoma (HCCA).

METHODS

Dual-time point FDG PET/CT findings, including early phase whole-body scanning and abdominal delayed phased performed 1 and 2 h after radiotracer injection, respectively, were retrospective reviewed in 69 patients conformed HCCA by histology. PET/CT was evaluated based on visual interpretation and the semiquantitative index of SUVmax and tumor-to-normal liver tissue ratio (TNR) for both early and delayed images.

RESULTS

For all 69 HCCA patients, the mean SUVmax of the lesion and TNR in delayed phase was significantly higher than that in early phase (6.1 ± 4.7, 2.2 ± 1.7, vs 5.1 ± 3.4, 1.6 ± 1.1; P < 0.001). The sensitivity and accuracy value of detection primary lesions was 69.6% and 70% in early phase vs 76.8% and 76.8% in delay phase, respectively. There was a significant correlation between lesion SUVmax and Ki67 index in both dual-time imaging (r = 0.462, P < 0.001 in early phase vs r = 0.47, P < 0.001 in delay phase). The sensitivity, specificity and accuracy value of metastatic lymph nodes prediction was 50%, 67.3% and 71% in early phase vs 62.5%, 73.3% and 76.8% in delayed phase, respectively. The sensitivity, specificity and accuracy of FDG PET/CT in detecting distant metastasis in our study was 75%, 100% and 97.1%. There was no difference of predicting distant metastasis between early phase and delayed phase.

CONCLUSION

Delayed phase in dual-time point ¹⁸F-FDG PET/CT scan provides additional usefulness for detection primary tumor and lymph nodes metastases in HCCA, but there was no added benefit of delayed PET/CT imaging in detection of distant metastases in this study. SUVmax in early and delayed phase could be used to assess tumor aggressiveness in pre-treatment HCCA.

Reconstruction of positron emission tomography images using adaptive sliced remeshing strategy

Purpose: The reconstruction of positron emission tomography images is a computationally intensive task which benefits from the use of increasingly complex physical models. Aiming to reduce the computational burden by means of a reduced system matrix, we present a list mode reconstruction approach based on maximum likelihood-expectation maximization and a sliced mesh support. Approach: The reconstruction strategy uses a fully 3D projection along series of 2D meshes arranged in the axial plane of the scanner. These series of meshes describe the continuous volumetric activity using a piece-wise linear function interpolated from the mesh elements. The mesh support is automatically adapted to the underlying structure of the activity by means of a remeshing process. This process finds a high-quality compact mesh representation constrained to a controlled interpolation error. Results: The method is tested using a Monte Carlo simulation of a Hoffman brain phantom and a National Electrical Manufacturers Association image quality phantom acquisition, using different sets of statistics. The reconstructions are compared against a voxelized reconstruction under different conditions, achieving similar or superior results. The number of parameters needed to reconstruct the image in voxel and mesh support is also compared, and the mesh reconstruction permits to reduce the number of nodes used to represent a complex image. Conclusions: The proposed reconstruction strategy reduces the number of parameters needed to describe the activity distribution by more than one order of magnitude for similar voxel size and with similar accuracy than state-of-the-art methods.