Evaluation of a novel PET tracer [18F]-Florbetazine for Alzheimer's disease diagnosis and ß-amyloid deposition quantification.

[18F]-Florbetazine ([18F]-92) is a selective PET tracer for ß-amyloid (Aß) depositions with a novel diaryl-azine scaffold to reduce lipophilicity and to achieve higher gray-to-white matter contrast. We aimed to assess its diagnostic value in Alzheimer's disease (AD) and pharmacokinetics characteristics in human subjects. METHODS: Six healthy controls (HCs) and nine AD patients underwent dynamic PET examination with [18F]-Florbetazine and a structural MRI scan. The time-activity-curves (TACs) for volumes of interest (VOIs) in cerebral cortex, cerebellar cortex and cerebral white matter was depicted and their standardized uptake value ratios (SUVRs) with cerebellar cortex as reference were compared between HCs and AD patients. The cerebral gray-to-white matter SUV ratio (GWR) was also calculated. RESULTS: In HCs, radioactivities in the cerebral cortex VOIs were homogeneously low and at the same level as in cerebellar cortex, while in AD patients, cortical VOIs expected to contain Aß exhibited high radioactivity. Cerebral cortex SUVRs remain relatively low in HCs while keep increasing along with time in AD patients. After 15 min, the cerebral cortex SUVRs became significant higher in AD patients compared to HCs with 100 % discrimination accuracy. In AD patients, GWR remained over 1.3 for all time intervals and visual inspection showed lower uptake in cerebral white matter compared to cerebral cortex. CONCLUSION: [18F]-Florbetazine PET showed high uptake on Aß plaques and high gray-to-white contrast in AD patients that are favorable in visual read. [18F]-Florbetazine can be potentially used for detection and quantification of Aß depositions in the living human brain.

Risk management for viral clearance: A case study on adoption of platform validation approach and risk management of process changes.

Viral clearance (VC) studies are routinely required prior to entering clinical trials or for commercial launch of biopharmaceuticals. With increasing prior knowledge and experience, platform validation can be used to eliminate some VC studies and such strategy has been updated into industry guidelines, such as ICH Q5A (R2). In addition, process changes can happen during life-cycle management of a product. In these circumstances, high-risk process parameters need to be identified and corresponding control strategies need to be defined to ensure viral safety of the product. This work describes the design of a science-based risk management tool and how this tool is employed for platform validation and process change scenarios.

The impact of deep-inspiration breath-hold total-body PET/CT imaging on thoracic 18F-FDG avid lesions compared with free-breathing.

OBJECTIVES: To investigate PET/CT registration and quantification accuracy of thoracic lesions of a single 30-second deep-inspiration breath-hold (DIBH) technique with a total-body PET (TB-PET) scanner, and compared with free-breathing (FB) PET/CT. METHODS: 137 of the 145 prospectively enrolled patients finished a routine FB-300 s PET/CT exam and a 30-second DIBH TB-PET with chest to pelvis low dose CT. The total-body FB-300 s, FB-30 s, and DIBH-30 s PET images were reconstructed. Quantitative assessment (SUVmax and SUVmean of lung and other organs), PET/CT registration assessment and lesion analysis (SUVmax, SUVpeak, SUVmean and tumor-background ratio) were compared with Wilcoxon signed-rank tests. RESULTS: The SUVmax and SUVmean of the lung with DIBH-30 s were significantly lower than those with FB. The distances of the liver dome between PET and CT were significantly smaller with DIBH-30 s than with FB. 195 assessable lesions in 106 patients were included, and the detection sensitivity was 97.9 % and 99.0 % in FB-300 s, and DIBH-30 s, respectively. For both small co-identified lesions (n = 86) and larger co-identified lesions with a diameter ≥ 1 cm (n = 91), the lesion SUVs were significantly greater with DIBH-30 s than with FB-300 s. Regarding lesion location, the differences of the SUVs for the lesions in the lower thorax area (n = 97, p < 0.001) were significant between DIBH-30 s and FB-300 s, while these differences were not statistically significant in the upper thorax (n = 80, p > 0.05). The lesion tumor-to-surrounding-background ratio (TsBR) was significantly increased, both in the upper and lower thorax. CONCLUSION: The TB DIBH PET/CT technique is feasible in clinical practice. It reduces the background lung uptake and achieves better registration and lesion quantification, especially in the lower thorax.

The Role of Total-Body PET in Drug Development and Evaluation: Status and Outlook.

Total-body PET, an emerging technique, enables high-quality simultaneous total-body dynamic PET acquisition and accurate kinetic analysis. It has the potential to facilitate the study of multiple tracers while minimizing radiation dose and improving tracer-specific imaging. This advancement holds promise for enhancing the development and clinical evaluation of drugs, particularly radiopharmaceuticals. Multiple clinical trials are using a total-body PET scanner to explore existing and innovative radiopharmaceuticals. However, challenges persist, along with the opportunities, with regard to the use of total-body PET in drug development and evaluation. Specifically, considerations relate to the role of total-body PET in clinical pharmacologic evaluations and its integration into the theranostic paradigm. In this review, state-of-the-art total-body PET and its potential roles in pharmaceutical research are explored.

Low 18F-fluorodeoxyglucose dose positron emission tomography assisted by a deep-learning image-denoising technique in patients with lymphoma.

Background: Patients with lymphoma receive multiple positron emission tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic response. With PET imaging, a reduced level of injected fluorine-18 fluorodeoxyglucose ([18F]FDG) activity can be administered while maintaining the image quality. In this study, we investigated the efficacy of applying a deep learning (DL) denoising-technique on image quality and the quantification of metabolic parameters and Deauville score (DS) of a low [18F]FDG dose PET in patients with lymphoma. Methods: This study retrospectively enrolled 62 patients who underwent [18F]FDG PET scans. The low-dose (LD) data were simulated by taking a 50% duration of routine-dose (RD) PET list-mode data in the reconstruction, and a U-Net-based denoising neural network was applied to improve the images of LD PET. The visual image quality score (1 = undiagnostic, 5 = excellent) and DS were assessed in all patients by nuclear radiologists. The maximum, mean, and standard deviation (SD) of the standardized uptake value (SUV) in the liver and mediastinum were measured. In addition, lesions in some patients were segmented using a fixed threshold of 2.5, and their SUV, metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) were measured. The correlation coefficient and limits of agreement between the RD and LD group were analyzed. Results: The visual image quality of the LD group was improved compared with the RD group. The DS was similar between the RD and LD group, and the negative (DS 1-3) and positive (DS 4-5) results remained unchanged. The correlation coefficients of SUV in the liver, mediastinum, and lesions were all >0.85. The mean differences of SUVmax and SUVmean between the RD and LD groups, respectively, were 0.22 [95% confidence interval (CI): -0.19 to 0.64] and 0.02 (95% CI: -0.17 to 0.20) in the liver, 0.13 (95% CI: -0.17 to 0.42) and 0.02 (95% CI: -0.12 to 0.16) in the mediastinum, and -0.75 (95% CI: -3.42 to 1.91), and -0.13 (95% CI: -0.57 to 0.31) in lesions. The mean differences in MTV and TLG were 0.85 (95% CI: -2.27 to 3.98) and 4.06 (95% CI: -20.53 to 28.64) between the RD and LD groups. Conclusions: The DL denoising technique enables accurate tumor assessment and quantification with LD [18F]FDG PET imaging in patients with lymphoma.

All-trans retinoic acid acts as a dual-purpose inhibitor of SARS-CoV-2 infection and inflammation.

Coronavirus disease 2019 (COVID-19) was an epidemic that effected human health caused by SARS-CoV-2 infection. All-trans retinoic acid (ATRA) has anti-inflammatory capability. In this article, we evaluated the effectiveness and revealed the molecular mechanism of ATRA for treating SARS-CoV-2 using deep learning, in vitro studies, multi-scale molecular modeling, and network pharmacology. The DeepDTA model suggested that ATRA would be effective against COVID-19. In vitro studies confirmed the antiviral activity of ATRA. Subsequently, multi-scale molecular modeling indicated that ATRA could binding to angiotensin converting enzyme 2 (ACE2), 3C-like protease (3CLpro), RNA dependent RNA polymerase (RdRp), helicase, and 3'-to-5' exonuclease by non-covalent interactions. Additionally, network pharmacology suggested that ATRA alleviated inflammatory response by regulating the IL-17 signaling pathway and binding with TNF, PTGS2, and MAPK1 directly. In summary, our findings provide the first evidence that ATRA suppresses the entry and replication of SARS-CoV-2, and regulates inflammatory response of host cells.