Many efforts have been made to standardize the interpretation of 18 f-fDG pet/ct in multiple myeloma (MM) with qualitative visual analysis or with quantitative metabolic parameters using various methods for lesion segmentation of PET images. The aim of this study was to propose a quantitative method for bone and bone marrow evaluation of 18 F-FDG PET/CT considering the extent and intensity of bone 18 F-FDG uptake: Intensity of Bone Involvement (IBI). Whole body 18 F-FDG PET/CT of 59 consecutive MM patients were evaluated. Compact bone tissue was segmented in PET images using a global threshold for HU of the registered CT image. A whole skeleton mask was created and the percentage of its volume with 18 F-FDG uptake above hepatic uptake was calculated (Percentage of Bone Involvement -PBI). IBI was defined by multiplying PBI by mean SUV above hepatic uptake. IBI was compared with visual analysis performed by two experienced nuclear medicine physicians. IBI calculation was feasible in all images (range:0.00-1.35). Visual analysis categorized PET exams into three groups (negative/ mild, moderate and marked bone involvement), that had different ranges of IBI (multi comparison analysis, p < 0.0001). There was an inverse correlation between the patients' hemoglobin values and IBI (r = −0.248;p = 0.02). IBI score is an objective measure of bone and bone marrow involvement in MM, allowing the categorization of patients in different degrees of aggressiveness of the bone disease. The next step is to validate IBI in a larger group of patients, before and after treatment and in a multicentre setting.Lytic bone lesions are reported in approximately 80% of myeloma multiple (MM) patients 1,2 . Early and precise evaluation of bone involvement is crucial for staging and correct disease management.Hybrid image of positron emission tomography with 18 F-fluordeoxyglucose and computed tomography ( 18 F-FDG PET/CT) is one of the main methods for the evaluation of MM patients. It allows whole-body images, intra and extramedullary lesion detection, distinction between active lesions and scar or necrotic tissue and has been more sensitive than MRI in treatment assessment 3-5 .Many efforts have been attempted to standardize the interpretation of 18 F-FDG PET/CT in MM, using qualitative visual analysis or quantitative metabolic parameters, such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) 6-9 . However, none of these methods have been extensively used in clinical practice or research projects, probably because of the complexity of the visual quantification 6,7 or due to the lack of standardization of MTV and TLG calculations 8-10 . Also, MTV and TLG only consider areas visually defined as lesions and ignore diffuse uptake of the bone marrow.

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BackgroundInformation and communication technology solutions have the potential to support active and healthy aging and improve monitoring and treatment outcomes. To make such solutions acceptable, all stakeholders must be involved in the requirements elicitation process. Due to the COVID-19 situation, alternative approaches to commonly used face-to-face methods must often be used. One aim of the current article is to share a unique experience from the Pharaon project where due to the COVID-19 outbreak alternative elicitation methods were used. In addition, an overview of common functional, quality, and emotional goals identified by six pilot sites is presented to complement the knowledge about the needs of older adults.MethodsOriginally planned face-to-face co-creation seminars were impossible to carry out, and all pilot sites chose alternative requirements elicitation methods that were most suitable in their situation. The elicited requirements were presented in the form of goal models. In one summary goal model, we provide an overview of common functional, quality, and emotional goals.ResultsDifferent elicitation methods were combined based on the digital literacy of the target group and their access to digital tools. Methods applied without digital technologies were phone interviews, reviews of literature and previous projects, while by means of digital technologies online interviews, online questionnaires, and (semi-)virtual co-creation seminars were conducted. The combination of the methods allowed to involve all planned stakeholders. Virtual and semi-virtual co-creation seminars created collaborative environment comparable to face-to-face situations, while online participation helped to save the time of the participants. The most prevalent functional goals elicited were “Monitor health,” “Receive advice,” “Receive information.” “Easy to use/comfortable,” “personalized/tailored,” “automatic/smart” were identified as most prevalent quality goals. Most frequently occurring emotional goals were “involved,” “empowered,” and “informed.”ConclusionThere are alternative methods to face-to-face co-creation seminars, which effectively involve older adults and other stakeholders in the requirements elicitation process. Despite the used elicitation method, the requirements can be easily transformed into goal models to present the results in a uniform way. The common requirements across different pilots provided a strong foundation for representing detailed requirements and input for further software development processes.

F-FDG PET/CT quantification of whole-body tumor burden in lymphoma is not routinely performed because of the lack of fast methods. Although the semiautomatic method is fast, it is not fast enough to quantify tumor burden in daily clinical practice. Our purpose was to evaluate the performance of convolutional neural network (CNN) software in localizing neoplastic lesions in whole-body 18 F-FDG PET/CT images of pediatric lymphoma patients. Methods: The retrospective image dataset, derived from the data pool of the International Atomic Energy Agency (coordinated research project E12017), included 102 baseline staging 18 F-FDG PET/CT studies of pediatric lymphoma patients (mean age, 11 y). The images were quantified to determine the whole-body tumor burden (whole-body metabolic tumor volume [wbMTV] and whole-body total lesion glycolysis [wbTLG]) using semiautomatic software and CNN-based software. Both were displayed as semiautomatic wbMTV and wbTLG and as CNN wbMTV and wbTLG. The intraclass correlation coefficient (ICC) was applied to evaluate concordance between the CNN-based software and the semiautomatic software. Results: Twenty-six patients were excluded from the analysis because the software was unable to perform calculations for them. In the remaining 76 patients, CNN and semiautomatic wbMTV tumor burden metrics correlated strongly (ICC, 0.993; 95% CI, 0.989 2 0.996; P , 0.0001), as did CNN and semiautomatic wbTLG (ICC, 0.999; 95% CI, 0.998-0.999; P , 0.0001). However, the time spent calculating these metrics was significantly (,0.0001) less by CNN (mean, 19 s; range, 11-50 s) than by the semiautomatic method (mean, 21.6 min; range, 3.2-62.1 min), especially in patients with advanced disease. Conclusion: Determining whole-body tumor burden in pediatric lymphoma patients using CNN is fast and feasible in clinical practice.

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Lack of integration, staff burden or time constraints as barriers to the implementation of an early palliative care intervention