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Understanding the internal functioning of natural systems often requires interdisciplinary approaches and competences that allow encompassing and disentangling different and strictly intertwined physical and biological processes. Hydrology and ecophysiology are examples of complementary and highly interconnected disciplines that share water as a common analysis element when investigating the functioning of vegetated ecosystems. In this discussion paper, we call for more frequent and active dialogue and collaboration between (field) hydrologists and ecophysiologists to study natural processes at the boundary between the two disciplines. We report some examples of the specific approaches of hydrologists and ecophysiologists to analyse water movement in the soil-vegetation-atmosphere continuum at increasing spatial scales, highlighting how the same mechanisms can be seen from different, but largely complementary, points of view. We argue that these different perspectives can and should be merged in order to overcome possibly fragmented vision of complex processes and provide a more holistic comprehension of ecohydrological mechanisms in forest ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: To determine whether artificial intelligence (AI) processed PET/CT images of reduced by one-third of 18-F-FDG activity compared to the standard injected dose, were non-inferior to native scans and if so to assess the potential impact of commercialization., Materials and Methods: SubtlePET™ AI was introduced in a PET/CT center in Italy. Eligible patients referred for 18F-FDG PET/CT were prospectively enrolled. Administered 18F-FDG was reduced to two-thirds of standard dose. Patients underwent one low-dose CT and two sequential PET scans; "PET-processed" with reduced dose and standard acquisition time, and "PET-native" with an elapsed time to simulate standard acquisition time and dose. PET-processed images were reconstructed using SubtlePET™. PET-native images were defined as the standard of reference. The datasets were anonymized and independently evaluated in random order by four blinded readers. The evaluation included subjective image quality (IQ) assessment, lesion detectability, and assessment of business benefits., Results: From February to April 2020, 61 patients were prospectively enrolled. Subjective IQ was not significantly different between datasets (4.62±0.23, p=0.237) for all scanner models, with "almost perfect" inter-reader agreement. There was no significant difference between datasets in lesions' detectability, target lesion mean SUV max value, and liver mean SUV mean value (182.75/181.75 [SD:0.71], 9.8/11.4 [SD:1.13], 2.1/1.9 [SD:0.14] respectively). No false-positive lesions were reported in PET-processed examinations. Agreed SubtlePET™ price per examination was 15-20% of FDG savings., Conclusion: This is the first real-world study to demonstrate the non-inferiority of AI processed 18F-FDG PET/CT examinations obtained with 66% standard dose and a methodology to define the AI solution price.

Background: Integrated PET/CT is widely used in the preoperative staging and prognostic assessment of non-small-cell lung cancer (NSCLC) patients. The aims of this study were to evaluate the prognostic significance of SUVmax of primary tumor in patients undergoing surgical treatment and, in order to minimize technical interferences, to verify whether SUVmax standardized by SUVmax liver or SUVmax blood pool provided additional prognostic information., Patients and Methods: A retrospective study of 413 consecutive NSCLC patients undergoing potentially curative surgical resection after PET/CT obtained in the same PET center over a 6-year period. The SUVmax was calculated drawing region of interest around the primitive tumor, the liver, and the aortic arch in PET images. The same procedure was performed for 2 adjacent planes and the average of these measures was considered., Results: Nine patients were considered 30-day postoperative deaths and were excluded from the analysis. At the end of the study, 312 (77.2%) of the 404 patients were alive (median follow-up, 26 months) and 92 had died (median survival, 17 months). At multivariate analysis tumor-node-metastasis stage, primary tumor grading and primary tumor SUVmax (T-SUVmax) were found to be independent prognostic factors, while T-SUVmax/SUVmax blood pool ratio, and T-SUVmax/SUVmax liver ratio were not., Conclusions: T-SUVmax is an independent predictor for survival in NSCLC patients undergoing surgery and might be helpful in guiding adjuvant treatment strategies. SUVmax of primary tumor normalized by SUV blood pool or SUV liver does not provide additional prognostic information., (Copyright © 2013 Elsevier Inc. All rights reserved.)