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Although an increased usage and development of 3D technologies is observed in healthcare over the last decades, full integration of these technologies remains challenging. The goal of this project is to qualitatively explore challenges, pearls, and pitfalls of AR/VR/3D printing applications usage in the medical field of a university medical center. Two rounds of face-to-face interviews were conducted using a semi-structured protocol. First an explorative round was held, interviewing medical specialists (8), PhD students (7), 3D technology specialists (5), and university teachers (3). In the second round, twenty employees in high executive functions of relevant departments were interviewed on seven statements that resulted from the first interviewing round. Data analysis was performed using direct content analyses. The first interviewing round resulted in challenges and opportunities in 3D technology usage that were grouped in 5 themes: aims of using AR/VR/3D printing (1), data acquisition (2), data management plans (3), software packages and segmentation tools (4), and output data and reaching end-user (5). The second interviewing round resulted in an overview of ideas and insights on centralization of knowledge, improving implementation of 3D technology in daily healthcare, reimbursement of 3D technologies, recommendations for further studies, and requirement of using certified software. An overview of challenges and opportunities of 3D technologies in healthcare was provided. Well-designed studies on clinical effectiveness, implementation and cost-effectiveness are warranted for further implementation into the clinical setting., (© 2023. The Author(s).)

Background: In a considerable subgroup of glioma patients treated with (chemo) radiation new lesions develop either representing tumor progression (TP) or treatment-related abnormalities (TRA). Quantitative diffusion imaging metrics such as the Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy (FA) have been reported as potential metrics to noninvasively differentiate between these two phenomena. Variability in performance scores of these metrics and absence of a critical overview of the literature contribute to the lack of clinical implementation. This meta-analysis therefore critically reviewed the literature and meta-analyzed the performance scores., Methods: Systematic searching was carried out in PubMed, EMBASE and The Cochrane Library. Using predefined criteria, papers were reviewed. Diagnostic accuracy values of suitable papers were meta-analyzed quantitatively., Results: Of 1252 identified papers, 10 ADC papers, totaling 414 patients, and 4 FA papers, with 154 patients were eligible for meta-analysis. Mean ADC values of the patients in the TP/TRA groups were 1.13 × 10 -3 mm 2 /s (95% CI 0.912 × 10 -3 -1.32 × 10 -3 mm 2 /s) and 1.38 × 10 -3 mm 2 /s (95% CI 1.33 × 10 -3 -1.45 × 10 -3 mm 2 /s, respectively. Mean FA values of TP/TRA was 0.19 (95% CI 0.189-0.194) and 0.14 (95% CI 0.137-0.143) respectively. A significant mean difference between ADC and FA values in TP versus TRA was observed (p = 0.005)., Conclusions: Quantitative ADC and FA values could be useful for distinguishing TP from TRA on a meta-level. Further studies using serial imaging of individual patients are warranted to determine the role of diffusion imaging in glioma patients., (© 2022. The Author(s).)

Background: Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status., Methods: After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics., Results: Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75-0.93), 0.81 (95%-CI 0.74-0.89), 0.84 (95%-CI 0.71-0.97) and 0.76 (95%-CI 0.61-0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies., Conclusions: Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival., (© 2022. The Author(s).)