Evaluation of Data-Driven Respiration Gating in Continuous Bed Motion in Lung Lesions.

Respiration gating is used in PET to prevent image quality degradation due to respiratory effects. In this study, we evaluated a type of data-driven respiration gating for continuous bed motion, OncoFreeze AI, which was implemented to improve image quality and the accuracy of semiquantitative uptake values affected by respiratory motion. Methods: 18F-FDG PET/CT was performed on 32 patients with lung lesions. Two types of respiration-gated images (OncoFreeze AI with data-driven respiration gating, device-based amplitude-based OncoFreeze with elastic motion compensation) and ungated images (static) were reconstructed. For each image, we calculated SUV and metabolic tumor volume (MTV). The improvement rate (IR) from respiration gating and the contrast-to-noise ratio (CNR), which indicates the improvement in image noise, were also calculated for these indices. IR was also calculated for the upper and lower lobes of the lung. As OncoFreeze AI assumes the presence of respiratory motion, we examined quantitative accuracy in regions where respiratory motion was not present using a 68Ge cylinder phantom with known quantitative accuracy. Results: OncoFreeze and OncoFreeze AI showed similar values, with a significant increase in SUV and decrease in MTV compared with static reconstruction. OncoFreeze and OncoFreeze AI also showed similar values for IR and CNR. OncoFreeze AI increased SUVmax by an average of 18% and decreased MTV by an average of 25% compared with static reconstruction. From the IR results, both OncoFreeze and OncoFreeze AI showed a greater IR from static reconstruction in the lower lobe than in the upper lobe. OncoFreeze and OncoFreeze AI increased CNR by 17.9% and 18.0%, respectively, compared with static reconstruction. The quantitative accuracy of the 68Ge phantom, assuming a region of no respiratory motion, was almost equal for the static reconstruction and OncoFreeze AI. Conclusion: OncoFreeze AI improved the influence of respiratory motion in the assessment of lung lesion uptake to a level comparable to that of the previously launched OncoFreeze. OncoFreeze AI provides more accurate imaging with significantly larger SUVs and smaller MTVs than static reconstruction.

Cancer-associated fibroblast-dependent and -independent invasion of gastric cancer cells.

PURPOSE: Cancer cells are known to exhibit a cancer-associated fibroblast (CAF)-dependent invasive mode in the presence of CAFs. The purpose of this study was to investigate whether intrinsic factors of gastric cancer cells influence the CAF-dependent invasive mode of cancer cells. METHODS: We observed dynamic movement of CAFs, and cancer cells, by time-lapse imaging of 2-D and 3-D collagen invasion models, and evaluated invasion modes of gastric cancer cell lines (MKN-7, MKN-45, and HSC44PE). We further examined whether modification of invasive capacity of CAFs can alter invasive mode of MKN-7, and HSC44PE cells. RESULTS: When MKN-7 and MKN-45 cells were co-cultured with CAFs, CAFs first invade collagen matrix followed by cancer cells (CAF-dependent invasion), whereas HSC44PE cells invaded collagen matrix independent of CAFs' invasion. Overexpression or suppression of podoplanin in CAFs, respectively, increased or decreased the invasive capacity of CAFs, and significantly increased or decreased the number of invading MKN-7 cells, respectively. CAFs overexpressing a podoplanin mutant, lacking the cytoplasmic domain, had significantly reduced invasive capacity, compared to CAFs overexpressing wild-type podoplanin, and it also reduced the number of invading MKN-7 cells significantly. When HSC44PE cells, and CAFs were co-cultured, changes in the podoplanin expression in CAFs similarly altered the invasive capacity of CAFs, but it did not affect the number of invading HSC44PE cells. CONCLUSIONS: These results indicate that in presence of CAFs, gastric cancer cells exhibit both CAF-dependent and -independent modes of invasion, the determinants of which may depend on the intrinsic properties of the gastric cancer cells.

Achievements of true whole-body imaging using a faster acquisition of the lower extremities in variable-speed continuous bed motion.

Variable-speed continuous bed motion 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT), a reliable imaging technique, allows setting the bed motion speed for arbitrary sections of the body. The purpose of this study was to evaluate the relationship between the PET image quality and the bed speed following shortening of the scanning time for the lower extremities to achieve whole-body acquisition optimization of the examination time. Four sets of images were created by editing four-phase dynamic whole-body PET/CT images acquired at a bed speed of 6 and 14 mm/s in the trunk and lower extremities, respectively. The signal-to-noise ratio (SNR) was calculated using regions of interest in the liver, gluteus muscles, thigh, and lower legs, and the relationship between the bed speed and the SNR was assessed. The number of patients with findings in the lower extremities among 967 cases was evaluated. Based on this relationship between the SNR and bed motion speed, it is reasonable to increase the speed of the lower extremities by up to three times that of the trunk. The findings from whole-body FDG-PET imaging revealed that the number of patients with detected lesions in the lower extremities was 6.6% (64/967), bone metastases were found in 2.6%, soft lesions in 1.8%, and inflammation in 2.3%. Images of the lower extremities, which have a better SNR than the trunk, can be acquired at a faster bed speed using the variable-speed continuous bed motion PET.