Objective: From patient and phantom studies, we aimed to highlight an original implementation process and share a two-years experience clinical feedback on xSPECT (xS), xSPECT Bone (xB) and Broadquant quantification (Siemens) for 99mTc-bone and 177Lu-NET (neuroendocrine tumors) imaging.Methods: Firstly, we checked the relevance of implemented protocols and Broadquant module on the basis of literature and with a homogeneous phantom study respectively. Then, we described xS and xB behaviours with reconstruction parameters (10i-0mm to 40i-20mm) and optimized the protocols through a blinded survey (7 physicians). Finally, the preferred 99mTc-bone reconstruction was assessed through an IEC NEMA phantom including liquid bone spheres. Conventional SNR, CNR, spatial resolution, Q.%error, and recovery curves; and innovative NPS, TTF and detectability score d' were performed (ImQuest software). We also sought to review the adoption of these tools in clinical routine and showed the potential of quantitative xB in the context of theranostics (Xofigo & REG;).Results: We showed the need of optimization of implemented reconstruction algorithms and pointed out a decay correction particularity with Broadquant. Preferred parameters were 1s-25i-8mm and 1s-25i-5mm for xS/xBbone and xS-NET imaging respectively. The phantom study highlighted the different image quality especially for the enhanced spatial resolution xB algorithm (1/TTF10%=2.1 mm) and showed F3D and xB shared the best performances in terms of image quality and quantification. xS was generally less efficient.Conclusions: Qualitative F3D still remains the clinical standard, xB and Broadquant offer challenging perspectives in theranostics. We introduced the potential of innovative metrics for image quality analysis and showed how CT tools should be adapted to fit nuclear medicine imaging.

Tomoscintigraphic reconstruction in nuclear medicine assumes that the distribution of the tracer is unchanged in the volume of interest throughout the duration of the acquisition. This condition is however not met in early-phase bone scintigraphy and early-phase pelvic SPECT may display helical artifacts due to the filling of the bladder. Those artifacts may hamper proper interpretation of surrounding bone areas. The aim of this study was to construct a 4D digital pelvic phantom to simulate different acquisition protocols and optimize the acquisition. A 4D digital pelvic phantom was generated with a dynamic component consisting in an expanding bladder with 2 ureters and a static part consisting in the 2 kidneys, bone structures, and soft tissues. Projection data were obtained using an attenuated Radon transform function. Four acquisitions protocols were tested: 32 projections of 16 seconds (32-16-1), 32 projections of 8 seconds (32-8-1), 2 consecutive SPECT of 32 projections of 4 seconds (32-4-2) and 2 consecutive SPECT of 16 projections of 8 seconds (16-8-2). The optimal protocol was then tested on one patient. The amplitude of the artifacts was reduced with the 32-8-1, 32-4-2, and 16-8-2 protocols. The 16-8-2 protocol had the highest signal to noise ratio among those 3 protocols. The bladder artifact was visually markedly reduced on the patient acquisition with a 16-8-2 protocol. Two successive early-phase bone SPECT, with a lower number of projection than the usual protocol reduce the impact of the helical artifacts around the bladder.

BACKGROUND:Ventilation/perfusion lung scan is subject to blur due to respiratory motion whether with planar acquisition or single photon emission computed tomography (SPECT). We propose a data-driven gating method for extracting different respiratory phases from lung scan list-mode or dynamic data.METHODS:The algorithm derives a surrogate respiratory signal from an automatically detected diaphragmatic region of interest. The time activity curve generated is then filtered using a Savitzky-Golay filter. We tested this method on an oscillating phantom in order to evaluate motion blur decrease and on one lung SPECT.RESULTS:Our algorithm reduced motion blur on phantom acquisition: mean full width at half maximum 8.1 pixels on non-gated acquisition versus 5.3 pixels on gated acquisition and 4.1 pixels on reference image. Automated detection of the diaphragmatic region and time-activity curves generation were successful on patient acquisition.CONCLUSIONS:This algorithm is compatible with a clinical use considering its runtime. Further studies will be needed in order to validate this method.

Few indexes are available for nuclear medicine image quality assessment, particularly for respiratory blur assessment. A variety of methods for the identification of blur parameters has been proposed in literature mostly for photographic pictures but these methods suffer from a high sensitivity to noise, making them unsuitable to evaluate nuclear medicine images. In this paper, we aim to calibrate and test a new blur index to assess image quality. Blur index calibration was evaluated by numerical simulation for various lesions size and intensity of uptake. Calibrated blur index was then tested on gamma-camera phantom acquisitions, PET phantom acquisitions and real-patient PET images and compared to human visual evaluation. For an optimal filter parameter of 9, non-weighted and weighted blur index led to an automated classification close to the human one in phantom experiments and identified each time the sharpest image in all the 40 datasets of 4 images. Weighted blur index was significantly correlated to human classification (rho=0.69 [0.45;0.84] P<.001) when used on patient PET acquisitions. The provided index allows to objectively characterize the respiratory blur in nuclear medicine acquisition, whether in planar or tomographic images and might be useful in respiratory gating applications.

Purpose To evaluate the prognostic value of 18F-fluorodeoxyglucose positron emission tomography (FDG PET) with quantitative analysis using metabolic parameters in metastatic differentiated thyroid cancer (DTC). Materials and Methods The FDG-PET scans of 37 patients with metastatic DTC were studied retrospectively. The number of FDG-avid lesions, the SUVmax, the SULpeak of the lesion with the highest FDG uptake, the overall metabolic tumor volume (MTV), and the total lesion glycolysis (TLG) were measured. Curves of progression-free survival (Kaplan-Meier) and Cox univariate and multivariate analyses determined the prognostic factors for survival. Results Progression-free survival was better in patients with less than 10 FDG-avid lesions (P = 0.0089), the SUVmax less than 10 (P = 0.0026), the SULpeak less than 5 (P = 0.0004), and the TLG less than 154 (P = 0.0110). Cox analyses showed that only the result of the PET scan was predictive of survival (age, TNM stage, histology, and the 131I whole body radioiodine scan were not associated with prognosis). In the univariate analysis, prognostic factors for progression-free survival and overall survival were the SUVmax (P = 0.004; P = 0.018), the SULpeak (P = 0.001; P = 0.017), and the TLG (P = 0.014; P = 0.012). The number of FDG-avid lesions was significantly associated with progression-free survival (P = 0.012), but not the MTV. In the multivariate analysis, the number of FDG-avid lesions and the SULpeak were independent prognostic factors. Conclusions FDG PET using metabolic parameters is a prognostic factor in metastatic DTC. It could improve the therapeutic management and follow-up of patients.