Time-course of effects of external beam radiation on [18F]FDG uptake in healthy tissue and bone marrow.

The utility of PET for monitoring responses to radiation therapy have been complicated by metabolically active processes in surrounding normal tissues. We examined the time-course of [18F]FDG uptake in normal tissues using small animal-dedicated PET during the 2 month period following external beam radiation. Four mice received 12 Gy of external beam radiation, in a single fraction to the left half of the body. Small animal [18F]FDG-PET scans were acquired for each mouse at 0 (pre-radiation), 1, 2, 3, 4, 5, 8, 12, 19, 24, and 38 days following irradiation. [18F]FDG activity in various tissues was compared between irradiated and non-irradiated body halves before, and at each time point after irradiation. Radiation had a significant impact on [18F]FDG uptake in previously healthy tissues, and time-course of effects differed in different types of tissues. For example, liver tissue demonstrated increased uptake, particularly over days 3-12, with the mean left to right uptake ratio increasing 52% over mean baseline values (p < 0.0001). In contrast, femoral bone marrow uptake demonstrated decreased uptake, particularly over days 2-8, with the mean left to right uptake ratio decreasing 26% below mean baseline values (p = 0.0005). Significant effects were also seen in lung and brain tissue. Radiation had diverse effects on [18F]FDG uptake in previously healthy tissues. These kinds of data may help lay groundwork for a systematically acquired database of the time-course of effects of radiation on healthy tissues, useful for animal models of cancer therapy imminently, as well as interspecies extrapolations pertinent to clinical application eventually

Gating, enhanced gating, and beyond: information utilization strategies for motion management, applied to preclinical PET

BACKGROUND: Respiratory gating and gate optimization strategies present solutions for overcoming image degradation caused by respiratory motion in PET and traditionally utilize hardware systems and/or employ complex processing algorithms. In this work, we aimed to advance recently emerging data-driven gating methods and introduce a new strategy for optimizing the four-dimensional data based on information contained in that data. These algorithms are combined to form an automated motion correction workflow. METHODS: Software-based gating methods were applied to a nonspecific population of 84 small-animal rat PET scans to create respiratory gated images. The gated PET images were then optimized using an algorithm we introduce as ‘gating+’ to reduce noise and optimize signal; the technique was also tested using simulations. Gating+ is based on a principle of only using gated information if and where it adds a net benefit, as evaluated in temporal frequency space. Motion-corrected images were assessed quantitatively and qualitatively. RESULTS: Of the small-animal PET scans, 71% exhibited quantifiable motion after software gating. The mean liver displacement was 3.25 mm for gated and 3.04 mm for gating+ images. The (relative) mean percent standard deviations measured in background ROIs were 1.53, 1.05, and 1.00 for the gated, gating+, and ungated values, respectively. Simulations confirmed that gating+ image voxels had a higher probability of being accurate relative to the corresponding ungated values under varying noise and motion scenarios. Additionally, we found motion mapping and phase decoupling models that readily extend from gating+ processing. CONCLUSIONS: Raw PET data contain information about motion that is not currently utilized. In our work, we showed that through automated processing of standard (ungated) PET acquisitions, (motion-) information-rich images can be constructed with minimal risk of noise introduction. Such methods have the potential for implementation with current PET technology in a robust and reproducible way

The Reading Palaeofire Database : an expanded global resource to document changes in fire regimes from sedimentary charcoal records

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b - Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345.Peer reviewe

Real-time data-driven motion correction in PET

Abstract PET imaging has been, and continues to be, an evolving diagnostic technology. In recent years, the modernizing digital landscape has opened new opportunities for data-driven innovation. One such facet has been data-driven motion correction (DDMC) in PET. As both research and industry propel this technology forward, we can recognize prospects and opportunities for further development. The concept of clinical practicality is supported by DDMC approaches—it is what sets them apart from traditional hardware-driven motion correction strategies that have largely not gained acceptance in routine diagnostic PET; the ease of use of DDMC may help propel acceptance of motion correction solutions in clinical practice. As we reflect on the present field, we should consider that DDMC can be made even more practical, and likely more impactful, if further developed to fit within a real-time acquisition framework. This vision for development is not new, but has been made more feasible with contemporary electronics, and has begun to be revisited in contemporary literature. The opportunities for development lie on a new forefront of innovation where medical physics integrates with engineering, data science, and modern computing capacities. Real-time DDMC is a systems integration challenge, and achieving it will require cooperation between hardware and software developers, and likely academia and industry. While challenges for development do exist, it is likely that we will see real-time DDMC come to fruition in the coming years. This effort may establish groundwork for developing similar innovations in the emerging digital innovation age

On transcending the impasse of respiratory motion correction applications in routine clinical imaging – a consideration of a fully automated data driven motion control framework

Positron emission tomography (PET) is increasingly used for the detection, characterization, and follow-up of tumors located in the thorax. However, patient respiratory motion presents a unique limitation that hinders the application of high-resolution PET technology for this type of imaging. Efforts to transcend this limitation have been underway for more than a decade, yet PET remains for practical considerations a modality vulnerable to motion-induced image degradation. Respiratory motion control is not employed in routine clinical operations. In this article, we take an opportunity to highlight some of the recent advancements in data-driven motion control strategies and how they may form an underpinning for what we are presenting as a fully automated data-driven motion control framework. This framework represents an alternative direction for future endeavors in motion control and can conceptually connect individual focused studies with a strategy for addressing big picture challenges and goals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2197-7364-1-8) contains supplementary material, which is available to authorized users