Evaluation of a respiratory motion-corrected image reconstruction algorithm in 2-[18F]FDG and [68Ga]Ga-DOTA-NOC PET/CT: impacts on image quality and tumor quantification.

Background: Respiratory motions may cause artifacts on positron emission tomography (PET) images that degrade image quality and quantification accuracy. This study aimed to evaluate the effect of a respiratory motion-corrected image reconstruction (MCIR) algorithm on image quality and tumor quantification compared with nongated/nonmotion-corrected reconstruction. Methods: We used a phantom consisting of 5 motion spheres immersed in a chamber driven by a motor. The spheres and the background chamber were filled with 18F solution at a sphere-to-background ratio of 5:1. We enrolled 42 and 16 patients undergoing 2-deoxy-2-[18F]fluoro-D-glucose {2-[18F]FDG} and 68Ga-labeled [1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid]-1-Nal3-octreotide {[68Ga]Ga-DOTA-NOC} PET/computed tomography (CT) from whom 74 and 30 lesions were segmented, respectively. Three reconstructions were performed: data-driven gating-based motion correction (DDGMC), external vital signal module-based motion correction (VSMMC), and noncorrection reconstruction. The standardized uptake values (SUVs) and the volume of the spheres and the lesions were measured and compared among the 3 reconstruction groups. The image noise in the liver was measured, and the visual image quality of motion artifacts was scored by radiologists in the patient study. Results: In the phantom study, the spheres' SUVs increased by 26-36%, and the volumes decreased by 35-38% in DDGMC and VSMMC compared with the noncorrection group. In the 2-[18F]FDG PET patient study, the lesions' SUVs had a median increase of 10.87-12.65% while the volumes had a median decrease of 14.88-15.18% in DDGMC and VSMMC compared with those of noncorrection. In the [68Ga]Ga-DOTA-NOC PET patient study, the lesions' SUVs increased by 14.23-15.45%, and the volumes decreased by 19.11-20.94% in DDGMC and VSMMC. The image noise in the liver was equal between the DDGMC, VSMMC, and noncorrection groups. Radiologists found improved image quality in more than 45% of the cases in DDGMC and VSMMC compared with the noncorrection group. There was no statistically significant difference in SUVs, volumes, or visual image quality scores between DDGMC and VSMMC. Conclusions: MCIR improves tumor quantification accuracy and visual image quality by reducing respiratory motion artifacts without compromised image noise performance or elongated acquisition time in 2-[18F]FDG and [68Ga]Ga-DOTA-NOC PET/CT tumor imaging. The performance of DDG-driven MCIR is as good as that of the external device-driven solution.

Small lesion depiction and quantification accuracy of oncological 18F-FDG PET/CT with small voxel and Bayesian penalized likelihood reconstruction.

BACKGROUND: To investigate the influence of small voxel Bayesian penalized likelihood (SVB) reconstruction on small lesion detection compared to ordered subset expectation maximization (OSEM) reconstruction using a clinical trials network (CTN) chest phantom and the patients with 18F-FDG-avid small lung tumors, and determine the optimal penalty factor for the lesion depiction and quantification. METHODS: The CTN phantom was filled with 18F solution with a sphere-to-background ratio of 3.81:1. Twenty-four patients with 18F-FDG-avid lung lesions (diameter < 2 cm) were enrolled. Six groups of PET images were reconstructed: routine voxel OSEM (RVOSEM), small voxel OSEM (SVOSEM), and SVB reconstructions with four penalty factors: 0.6, 0.8, 0.9, and 1.0 (SVB0.6, SVB0.8, SVB0.9, and SVB1.0). The routine and small voxel sizes are 4 × 4 × 4 and 2 × 2 × 2 mm3. The recovery coefficient (RC) was calculated by dividing the measured activity by the injected activity of the hot spheres in the phantom study. The SUVmax, target-to-liver ratio (TLR), contrast-to-noise ratio (CNR), the volume of the lesions, and the image noise of the liver were measured and calculated in the patient study. Visual image quality of the patient image was scored by two radiologists using a 5-point scale. RESULTS: In the phantom study, SVB0.6, SVB0.8, and SVB0.9 achieved higher RCs than SVOSEM. The RC was higher in SVOSEM than RVOSEM and SVB1.0. In the patient study, the SUVmax, TLR, and visual image quality scores of SVB0.6 to SVB0.9 were higher than those of RVOSEM, while the image noise of SVB0.8 to SVB1.0 was equivalent to or lower than that of RVOSEM. All SVB groups had higher CNRs than RVOSEM, but there was no difference between RVOSEM and SVOSEM. The lesion volumes derived from SVB0.6 to SVB0.9 were accurate, but over-estimated by RVOSEM, SVOSEM, and SVB1.0, using the CT measurement as the standard reference. CONCLUSIONS: The SVB reconstruction improved lesion contrast, TLR, CNR, and volumetric quantification accuracy for small lesions compared to RVOSEM reconstruction without image noise degradation or the need of longer emission time. A penalty factor of 0.8-0.9 was optimal for SVB reconstruction for the small tumor detection with 18F-FDG PET/CT.

Impact of total variation regularized expectation maximization reconstruction on the image quality of 68Ga-PSMA PET: a phantom and patient study.

OBJECTIVES: To investigate the impact of total variation regularized expectation maximization (TVREM) reconstruction on the image quality of 68Ga-PSMA-11 PET/CT using phantom and patient data. METHODS: Images of a phantom with small hot sphere inserts and 20 prostate cancer patients were acquired with a digital PET/CT using list-mode and reconstructed with ordered subset expectation maximization (OSEM) and TVREM with seven penalisation factors between 0.01 and 0.42 for 2 and 3 minutes-per-bed (m/b) acquisition. The contrast recovery (CR) and background variability (BV) of the phantom, image noise of the liver, and SUVmax of the lesions were measured. Qualitative image quality was scored by two radiologists using a 5-point scale (1-poor, 5-excellent). RESULTS: The performance of CR, BV, and image noise, and the gain of SUVmax was higher for TVREM 2 m/b groups with the penalization of 0.07 to 0.28 compared to OSEM 3 m/b group (all p < 0.05). The image noise of OSEM 3 m/b group was equivalent to TVREM 2 and 3 m/b groups with a penalization of 0.14 and 0.07, while lesions' SUVmax increased 15 and 20%. The highest qualitative score was attained at the penalization of 0.21 (3.30 ± 0.66) for TVREM 2 m/b groups and the penalization 0.14 (3.80 ± 0.41) for 3 m/b group that equal to or greater than OSEM 3 m/b group (2.90 ± 0.45, p = 0.2 and p < 0.001). CONCLUSIONS: TVREM improves lesion contrast and reduces image noise, which allows shorter acquisition with preserved image quality for PSMA PET/CT. ADVANCES IN KNOWLEDGE: TVREM reconstruction with optimized penalization factors can generate higher quality PSMA-PET images for prostate cancer diagnosis.

A preliminary study of imaging paclitaxel-induced tumor apoptosis with (99)Tc(m)-His10-Annexin V.

BACKGROUND: In tumors the process of apoptosis occurs over an interval of time after chemotherapy. It is important to determine the best time for detecting apoptosis by in vivo imaging. In this study, we evaluated the dynamics and feasibility of imaging non-small cell lung cancer (NSCLC) apoptosis induced by paclitaxel treatment using a (99)Tc(m)-labeled Annexin V recombinant with ten consecutive histidines (His10-Annexin V) in a mouse model. METHODS: (99)Tc(m)-His10-Annexin V was prepared by one step direct labeling; radio-chemical purity (RCP) and radio-stability was tested. The binding of (99)Tc(m)-His10-Annexin V to apoptotic cells was validated in vitro using camptothecin-induced Jurkat cells. In vivo bio-distribution was determined in mice by dissection. The human H460 NSCLC tumor cell line (H460) tumor-bearing mice were treated with intravenous paclitaxel 24, 48 and 72 hours later. (99)Tc(m)-His10-Annexin V was injected intravenously, and planar images were acquired at 2, 4 and 6 hours post-injection on a dual-head gamma camera fitted with a pinhole collimator. Tumor-to-normal tissue ratios (T/NT) were calculated by ROI analysis and they reflected specific binding of (99)Tc(m)-His10-Annexin V. Mice were sacrificed after imaging. Caspase-3, as the apoptosis detector, was determined by flow cytometry, and DNA fragmentation was analyzed by the terminal deoxynucleotidytransferase mediated dUTP nick-end labeling (TUNEL) assay. Nonspecific accumulation of protein was estimated using bovine serum albumin (BSA). The imaging data were correlated with TUNEL-positive nuclei and caspase-3 activity. RESULTS: (99)Tc(m)-His10-Annexin V had a RCP > 98% and high stability 2 hours after radio-labeling, and it could bind to apoptotic cells with high affinity. Bio-distribution of (99)Tc(m)-His10-Annexin V showed predominant uptake in kidney, relatively low uptake in myocardium, liver and gastrointestinal tract, and rapid clearance from blood and kidney was observed. The T/NT was significantly increased after paclitaxel treatment, whereas it was low in untreated tumors (T/NT = 1.43 ± 0.18). The %ID/g activity in Group 2 (24 hours), Group 3 (48 hours) and Group 4 (72 hours) after treatment was 2.55 ± 0.73, 3.35 ± 1.10, and 3.4 ± 0.96, respectively. Whereas in the non-treated group, Group 1, %ID/g was 1.10 ± 0.18. The radiotracer uptake was positively correlated to the apoptotic index (r = 0.852, P < 0.01), as well as caspase-3 activity (r = 0.816, P < 0.01). CONCLUSION: This study addresses the dynamics and feasibility of imaging non-small cell lung tumor apoptosis using (99)Tc(m)- His10-Annexin V.

[Technetium-99m labeled synaptotagmin I C2A detection of paclitaxel-induced apoptosis in non-small cell lung cancer].

UNLABELLED: Objective To evaluate the efficacy of 99mTc-labeled C2A probe in detection of apoptosis of non-small cell lung cancer (NSCLC) cells after chemotherapy. METHODS: Imaging studies were performed in NSCLC H460-bearing mice. The mice were divided into 2 groups: the paclitaxel-treated group and control group. 99mTc-C2A was injected intravenously at 12, 24, 48 and 72 h after chemotherapy. Images were acquired at 3 h and 6 h after injection using a pinhole collimator. The regions of interest (ROI) were drawn in tumor area and contralateral nomal tissue, and the ratio of T/NT were caculated. The tumor sections were stained by HE and TUNEL (terminal deoxynucleotidyltransferase-mediated dUTP-nick-end labeling) staining to confirm the presence of apoptosis. Activated caspase-3 was also analyzed with flow cytometry. RESULTS: Little uptake of 99mTc-C2A was found in baseline images, but tumor uptake increased very much after chemotherapy, the T/NT ratio was 1.79 +/- 0.34, 2.23 +/- 0.33 and 2.78 +/- 0.34, respectively. The T/NT ratio of control was 1.48 +/- 0.23. Tumor uptake (% ID/g) of 99mTc-C2A in chemotherapy groups were 2.82 +/- 0.90, 3.13 +/- 0.48 and 3.52 +/- 1.18, respectively. Tumor uptake (% ID/g) in the control group was 1.21 +/- 0.51. It in paclitaxel-treatment groups were 2.82 +/- 0.90, 3.13 +/- 0.48 and 3.51 +/- 1.18, respectively, significantly higher than that in untreated mice. Furthermore, the uptake of 99mTc-C2A correlated well with apoptotic index (r = 0.56, P < 0.01), and activated caspase-3 (r = 0.59, P < 0.01). CONCLUSION: Our preliminary results demonstrated that 99mTc-C2A imaging in vivo for detection of cell death in solid tumors is feasible and well correlated with TUNEL staining and activated caspase-3. The C2A holds promise and warrants further development as a molecular probe to early predict cancer treatment efficacy.

[Application of technetium-99m labelled sandostatin Somatostatin receptor imaging in the detection of lung cancer].

OBJECTIVE: To evaluate the clinical value of (99)Tc(m)-sandostatin receptors imaging ((99)Tc(m)-sandostatin) in detection of lung tumors in comparison with fludeoxyglucose F18 dual head coincidence imaging ((18)F-FDG DHC). METHODS: Fifty-six consecutive patients (40 men, 16 women; mean age: 62 years, range 35 - 80 years) with pulmonary neoplasm were referred for evaluation. All underwent sandostatin scintigraphy using hybrid SPECT/CT. (18)F-FDG DHC imaging was also performed in 23 patients using the same camera. The tumor uptake of (99)Tc(m)-sandostatin and (18)F-FDG DHC were measured respectively and expressed as the ratio of T/Nr and T/Nm. Final clinical diagnosis was confirmed by histopathological study. RESULTS: Out of 56 cases, 46 were confirmed to be malignant and 10 benign. The sensitivity, specificity and accuracy of (99)Tc(m)-sandostatin in diagnosis of lung cancer were 95.7%, 90.0%, 94.6%, respectively. The positive predictive value (PPR) was 97.8%, and the negative predictive value (NPR) was 81.8%. In the 23 patients underwent both methods, the sensitivity, specificity and accuracy of (18)F-FDG DHC were 100%, 60.0%, 82.6%, respectively; the PPR was 76.5%, and the NPR 100%. Out of 13 patients with malignant neoplasms, 6 patients had regional lymph node metastasis, and all of 10 abnormal lymph nodules showed high uptake of FDG, while (99)Tc(m)-sandostatin imaging only 2 regional metastasized lymph nodes in one patient. T/N(r) and T/N(m) were 3.15 +/- 1.30, and 10.61 +/- 4.35 respectively. There was no relationship between sandostatin uptake and glucose metabolism. CONCLUSION: (99)Tc(m)-sandostatin scintigraphy is a promising noninvasive imaging technique for detection of the primary tumor of lung cancer but of limited value in the detection of lymph node metastasis.