positron emission tomography
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2022 ◽  
Inés Califano ◽  
Fabian Pitoia ◽  
Roxana Chirico ◽  
Alejandra de Salazar ◽  
Maria Bastianello

Abstract Purpose 18F-DOPA Positron Emission Tomography/Computed Tomography (18F-DOPA PET/CT) is a sensitive functional imaging method (65-75%) for detecting disease localization in medullary thyroid cancer (MTC). We aimed: i) to assess the clinical usefulness of 18F-DOPA PET/CT in patients with MTC and elevated calcitonin (Ctn) and CEA levels and, ii) to evaluate changes in disease management secondary to the findings encountered with this methodology. Methods thirty-six patients with MTC and Ctn levels ≥150 pg/ml were prospectively included. Neck ultrasound, chest contrast-enhanced CT, liver magnetic resonance imaging/ abdominal 3-phase contrast-enhanced CT and bone scintigraphy were carried out up to 6 months before the 18F DOPA PET/CT. Results 77.7% were female and 27% had hereditary MTC. Median Ctn level was 1450 pg/ml [150-56620], median CEA level 413 ng/ml [2.9-7436]. Median Ctn DT was 37.5 months [5.7-240]; median CEA DT was 31.8 [4.9-180]. 18F-DOPA PET/CT was positive in 33 patients (91.6%); in 18 (56%) uptake was observed in lymph nodes in the neck or mediastinum, in 7 cases (22%) distant metastases were diagnosed, and in 8 additional patients (24%) both locoregional and distant sites of disease were found. Ctn and CEA levels were higher in patients with ≥ 3 foci of distant metastases. In 14 patients (38.8%), findings on 18F-DOPA PET/CT led to changes in management; surgery for locoregional lymph nodes was the most frequent procedure in 8 patients (22%). Conclusion 18F-DOPA PET/CT was useful for the detection of recurrent disease in MTC and provided helpful information for patient management.

2022 ◽  
Vol 15 ◽  
Artur Agaronyan ◽  
Raeyan Syed ◽  
Ryan Kim ◽  
Chao-Hsiung Hsu ◽  
Scott A. Love ◽  

The olive baboon (Papio anubis) is phylogenetically proximal to humans. Investigation into the baboon brain has shed light on the function and organization of the human brain, as well as on the mechanistic insights of neurological disorders such as Alzheimer’s and Parkinson’s. Non-invasive brain imaging, including positron emission tomography (PET) and magnetic resonance imaging (MRI), are the primary outcome measures frequently used in baboon studies. PET functional imaging has long been used to study cerebral metabolic processes, though it lacks clear and reliable anatomical information. In contrast, MRI provides a clear definition of soft tissue with high resolution and contrast to distinguish brain pathology and anatomy, but lacks specific markers of neuroreceptors and/or neurometabolites. There is a need to create a brain atlas that combines the anatomical and functional/neurochemical data independently available from MRI and PET. For this purpose, a three-dimensional atlas of the olive baboon brain was developed to enable multimodal imaging analysis. The atlas was created on a population-representative template encompassing 89 baboon brains. The atlas defines 24 brain regions, including the thalamus, cerebral cortex, putamen, corpus callosum, and insula. The atlas was evaluated with four MRI images and 20 PET images employing the radiotracers for [11C]benzamide, [11C]metergoline, [18F]FAHA, and [11C]rolipram, with and without structural aids like [18F]flurodeoxyglycose images. The atlas-based analysis pipeline includes automated segmentation, registration, quantification of region volume, the volume of distribution, and standardized uptake value. Results showed that, in comparison to PET analysis utilizing the “gold standard” manual quantification by neuroscientists, the performance of the atlas-based analysis was at >80 and >70% agreement for MRI and PET, respectively. The atlas can serve as a foundation for further refinement, and incorporation into a high-throughput workflow of baboon PET and MRI data. The new atlas is freely available on the Figshare online repository (https://doi.org/10.6084/m9.figshare.16663339), and the template images are available from neuroImaging tools & resources collaboratory (NITRC) (https://www.nitrc.org/projects/haiko89/).

2022 ◽  
Vol 12 (1) ◽  
Simon Klingler ◽  
Jason P. Holland

AbstractClinical production of 89Zr-radiolabeled antibodies (89Zr-mAbs) for positron emission tomography imaging relies on the pre-conjugation of desferrioxamine B (DFO) to the purified protein, followed by isolation and characterization of the functionalized intermediate, and then manual radiosynthesis. Although highly successful, this route exposes radiochemists to a potentially large radiation dose and entails several technological and economic hurdles that limit access of 89Zr-mAbs to just a specialist few Nuclear Medicine facilities worldwide. Here, we introduce a fully automated synthesis box that can produce individual doses of 89Zr-mAbs formulated in sterile solution in < 25 min starting from [89Zr(C2O4)4]4– (89Zr-oxalate), our good laboratory practice-compliant photoactivatable desferrioxamine-based chelate (DFO-PEG3-ArN3), and clinical-grade antibodies without the need for pre-purification of protein. The automated steps include neutralization of the 89Zr-oxalate stock, chelate radiolabeling, and light-induced protein conjugation, followed by 89Zr-mAb purification, formulation, and sterile filtration. As proof-of-principle, 89ZrDFO-PEG3-azepin-trastuzumab was synthesized directly from Herceptin in < 25 min with an overall decay-corrected radiochemical yield of 20.1 ± 2.4% (n = 3), a radiochemical purity > 99%, and chemical purity > 99%. The synthesis unit can also produce 89Zr-mAbs via the conventional radiolabeling routes from pre-functionalized DFO-mAbs that are currently used in the clinic. This automated method will improve access to state-of-the-art 89Zr-mAbs at the many Nuclear Medicine and research institutions that require automated devices for radiotracer production.

2022 ◽  
Rikuto Yoshimizu ◽  
Junsuke Nakase ◽  
Takafumi Mochizuki ◽  
Yasushi Takata ◽  
Kengo Shimozaki ◽  

Abstract Background: This study investigated the whole-body skeletal muscle activity pattern of hang power clean (HPC), a major weight training exercise, using positron emission tomography (PET). Methods: Twelve college weightlifting athletes performed three sets of HPC 20 times with a barbell set to 40 kg both before and after an intravenous injection of 37 MBq 18F-fluorodeoxyglucose (FDG). PET-computed tomography images were obtained 50 min after FDG injection. Regions of interest were defined within 71 muscles. The standardized uptake value was calculated to examine the FDG uptake of muscle tissue per unit volume, and FDG accumulation was compared to the control group. The Mann–Whitney U-test was used to evaluate the differences in the mean SUV between groups. The difference between SUVs of the right and left muscles was evaluated by a paired t-test. A P-value <0.05 was considered statistically significant.Results: FDG accumulation within the vastus lateralis, vastus intermedius, and vastus medialis was higher than that of the rectus femoris. FDG accumulation within the triceps surae muscle was significantly higher only in the soleus. In the trunk and hip muscles, FDG accumulation of only the erector spinae was significantly increased. In all skeletal muscles, there was no difference between SUVs of the right and left muscles.Conclusions: The monoarticular muscles in the lower limbs were active in HPC. In contrast, deep muscles in the trunk and hip were not active during HPC. HPC is not suitable for core training and needs to be supplemented with other training.

2022 ◽  
Vol 14 (1) ◽  
Ziyu Liu ◽  
Travis S. Johnson ◽  
Wei Shao ◽  
Min Zhang ◽  
Jie Zhang ◽  

Abstract Background To help clinicians provide timely treatment and delay disease progression, it is crucial to identify dementia patients during the mild cognitive impairment (MCI) stage and stratify these MCI patients into early and late MCI stages before they progress to Alzheimer’s disease (AD). In the process of diagnosing MCI and AD in living patients, brain scans are collected using neuroimaging technologies such as computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET). These brain scans measure the volume and molecular activity within the brain resulting in a very promising avenue to diagnose patients early in a minimally invasive manner. Methods We have developed an optimal transport based transfer learning model to discriminate between early and late MCI. Combing this transfer learning model with bootstrap aggregation strategy, we overcome the overfitting problem and improve model stability and prediction accuracy. Results With the transfer learning methods that we have developed, we outperform the current state of the art MCI stage classification frameworks and show that it is crucial to leverage Alzheimer’s disease and normal control subjects to accurately predict early and late stage cognitive impairment. Conclusions Our method is the current state of the art based on benchmark comparisons. This method is a necessary technological stepping stone to widespread clinical usage of MRI-based early detection of AD.

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