PurposeTo evaluate if a three‐component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue.Materials and MethodsTen healthy volunteers were examined at 3T, with T 2‐weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono‐, bi‐, and triexponential fit parameters (D 1, D 2, D 3, f fast2, f fast3, and f interm) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( normalRadj2) and the Shapiro‐Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared.ResultsFitting the diffusion signal was feasible for all models. The three‐component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in normalRadj2 of the ROI containing high diffusion signals (ROIrest), which was 0.42 ± 0.14, 0.61 ± 0.11, 0.77 ± 0.09, and 0.81 ± 0.08 for DTI, one‐, two‐, and three‐component models, respectively, and in visual comparison of the fitted and measured S0. None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the f fast component of the two and three‐component models were significantly different (P < 0.001).ConclusionTriexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information. Level of Evidence: 2 Technical Efficacy: Stage 1J. MAGN. RESON. IMAGING 2017;46:228–239

BackgroundSocietal challenges that call for a new type of engineer suggest the need for the implementation of interdisciplinary engineering education (IEE). The aim of IEE is to train engineering students to bring together expertise from different disciplines in a single context. This review synthesizes IEE research with a focus on characterizing vision, teaching practices, and support.PurposeWe aim to show how IEE is conceptualized, implemented, and facilitated in higher engineering education at the levels of curricula and courses. This aim leads to two research questions:What aspects of vision, teaching, and support have emerged as topics of interest in empirical studies of IEE?What points of attention regarding vision, teaching, and support can be identified in empirical studies of IEE as supporting or challenging IEE?Scope/MethodNinety‐nine studies published between 2005 and 2016 were included in a qualitative analysis across studies. The procedure included formulation of research questions, searching and screening of studies according to inclusion/exclusion criteria, description of study characteristics, appraisal, and synthesis of results.ConclusionsChallenges exist for identifying clear learning goals and assessments for interdisciplinary education in engineering (vision). Most pedagogy for interdisciplinary learning is designed to promote collaborative teamwork requiring organization and team management. Our review suggests that developing interdisciplinary skills, knowledge, and values needs sound pedagogy and teaming experiences that provide students with authentic ways of engaging in interdisciplinary practice (teaching). Furthermore, there is a limited understanding of what resources hinder the development of engineering programs designed to support interdisciplinarity (support).

In science policy, it is generally acknowledged that science-based problem-solving requires interdisciplinary research. For example, policy makers invest in funding programs such as Horizon 2020 that aim to stimulate interdisciplinary research. Yet the epistemological processes that lead to effective interdisciplinary research are poorly understood. This article aims at an epistemology for interdisciplinary research (IDR), in particular, IDR for solving ‘real-world’ problems. Focus is on the question why researchers experience cognitive and epistemic difficulties in conducting IDR. Based on a study of educational literature it is concluded that higher-education is missing clear ideas on the epistemology of IDR, and as a consequence, on how to teach it. It is conjectured that the lack of philosophical interest in the epistemology of IDR is due to a philosophical paradigm of science (called a physics paradigm of science ), which prevents recognizing severe epistemological challenges of IDR, both in the philosophy of science as well as in science education and research. The proposed alternative philosophical paradigm (called an engineering paradigm of science ) entails alternative philosophical presuppositions regarding aspects such as the aim of science, the character of knowledge, the epistemic and pragmatic criteria for accepting knowledge, and the role of technological instruments. This alternative philosophical paradigm assume the production of knowledge for epistemic functions as the aim of science, and interprets ‘knowledge’ (such as theories, models, laws, and concepts) as epistemic tools that must allow for conducting epistemic tasks by epistemic agents, rather than interpreting knowledge as representations that objectively represent aspects of the world independent of the way in which it was constructed. The engineering paradigm of science involves that knowledge is indelibly shaped by how it is constructed. Additionally, the way in which scientific disciplines (or fields) construct knowledge is guided by the specificities of the discipline, which can be analyzed in terms of disciplinary perspectives . This implies that knowledge and the epistemic uses of knowledge cannot be understood without at least some understanding of how the knowledge is constructed. Accordingly, scientific researchers need so-called metacognitive scaffolds to assist in analyzing and reconstructing how ‘knowledge’ is constructed and how different disciplines do this differently. In an engineering paradigm of science, these metacognitive scaffolds can also be interpreted as epistemic tools, but in this case as tools that guide, enable and constrain analyzing and articulating how knowledge is produced (i.e., explaining epistemological aspects of doing research). In interdisciplinary research, metacognit...

In decision making concerning the diagnosis and treatment of patients, doctors have a responsibility to do this to the best of their abilities. Yet we argue that the current paradigm for best medical practice - evidence-based medicine (EBM) - does not always support this responsibility. EBM was developed to promote a more scientific approach to the practice of medicine. This includes the use of randomized controlled trials in the testing of new treatments and prophylactics and rule-based reasoning in clinical decision making. But critics of EBM claim that such a scientific approach does not always work in the clinic. In this article, we build on this critique and argue that rule-based reasoning and the use of general guidelines as promoted by EBM does not accommodate the complex reasoning of doctors in clinical decision making. Instead, we propose that a new medical epistemology is needed that accounts for complex reasoning styles in medical practice and at the same time maintains the quality usually associated with 'scientific'. The medical epistemology we propose conforms to the epistemological responsibility of doctors, which involves a specific professional attitude and epistemological skills. Instead of deferring part of the professional responsibility to strict clinical guidelines, as EBM allows for, our alternative epistemology holds doctors accountable for epistemic considerations in clinical decision making towards the diagnosis and treatment plan of individual patients. One of the key intellectual challenges of doctors is the ability to bring together heterogeneous pieces of information to construct a coherent 'picture' of a specific patient. In the proposed epistemology, we consider this 'picture' as an epistemological tool that may then be employed in the diagnosis and treatment of a specific patient.

In this paper we present an initial roadmap for the ethical development and eventual implementation of artificial amniotic sac and placenta technology in clinical practice. We consider four elements of attention: (1) framing and societal dialogue; (2) value sensitive design, (3) research ethics and (4) ethical and legal research resulting in the development of an adequate moral and legal framework. Attention to all elements is a necessary requirement for ethically responsible development of this technology. The first element concerns the importance of framing and societal dialogue. This should involve all relevant stakeholders as well as the general public. We also identify the need to consider carefully the use of terminology and how this influences the understanding of the technology. Second, we elaborate on value sensitive design: the technology should be designed based upon the principles and values that emerge in the first step: societal dialogue. Third, research ethics deserves attention: for proceeding with first-in-human research with the technology, the process of recruiting and counseling eventual study participants and assuring their informed consent deserves careful attention. Fourth, ethical and legal research should concern the status of the subject in the AAPT. An eventual robust moral and legal framework for developing and implementing the technology in a research setting should combine all previous elements. With this roadmap, we emphasize the importance of stakeholder engagement throughout the process of developing and implementing the technology; this will contribute to ethically and responsibly innovating health care.

In recent years there has been growing attention to the epistemology of clinical decision‐making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision‐making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision‐making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision‐making in diagnosis and treatment of PH, we have shown that clinical decision‐making is highly social and mediated by technologies. The epistemology of clinical decision‐making needs to take social and technological mediation into account.

Purpose: Clarification of interdisciplinary expertise as the ability to deal with the cognitive and epistemological challenges of multi-and interdisciplinary problem-solving-such as in developing and implementing medical technology for diagnoses and treatment of patients in collaborations between clinicians, technicians and engineers-, and of the higher-order cognitive skills needed as part of this expertise. Method: Clarify the epistemological difficulties of combining scientific knowledge, methodologies and technologies from different disciplines in problem-solving, by drawing on recent developments in the philosophy of science. Conclusion: We argue that interdisciplinary expertise involves the cognitive ability to connect, translate and establish links between disciplinary knowledge, as well as the metacognitive ability to understand and explain the role of the disciplinary perspective-consisting of, e.g., basic concepts, theories, models, methodologies, technologies, and specific ways of measuring, reasoning and modeling in a disciplinein how knowledge is used and produced.

PurposeTo compare diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and tri-exponential models of the diffusion magnetic resonance imaging (MRI) signal for the characterization of renal lesions in relationship to histopathological findings.MethodsSixteen patients planned to undergo nephrectomy for kidney tumour were scanned before surgery at 3 T magnetic resonance imaging (MRI), with T2-weighted imaging, DTI and diffusion weighted imaging (DWI) using ten b-values. DTI parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squared fitting of the DTI data and bi-, and tri-exponential fit parameters (Dbi, fstar,and Dtri, ffast,finterm) using a nonlinear fit of the multiple b-value DWI data. Average parameters were calculated for regions of interest, selecting the lesions and healthy kidney tissue. Tumour type and specificities were determined after surgery by histological examination. Mean parameter values of healthy tissue and solid lesions were compared using a Wilcoxon-signed ranked test and MANOVA.ResultsThirteen solid lesions (nine clear cell carcinomas, two papillary renal cell carcinoma, one haemangioma and one oncocytoma) and four cysts were included. The mean MD of solid lesions are significantly (p < 0.05) lower than healthy cortex and medulla, (1.94 ± 0.32*10− 3 mm2/s versus 2.16 ± 0.12*10− 3 mm2/s and 2.21 ± 0.14*10− 3 mm2/s, respectively) whereas ffast is significantly higher (7.30 ± 3.29% versus 4.14 ± 1.92% and 4.57 ± 1.74%) and finterm is significantly lower (18.7 ± 5.02% versus 28.8 ± 5.09% and 26.4 ± 6.65%). Diffusion coefficients were high (≥2.0*10− 3 mm2/s for MD, 1.90*10− 3 mm2/s for Dbi and 1.6*10− 3 mm2/s for Dtri) in cc-RCCs with cystic structures and/or haemorrhaging and low (≤1.80*10− 3 mm2/s for MD, 1.40*10− 3 mm2/s for Dbi and 1.05*10− 3 mm2/s for Dtri) in tumours with necrosis or sarcomatoid differentiation.ConclusionParameters derived from a two- or three-component fit of the diffusion signal are sensitive to histopathological features of kidney lesions.Electronic supplementary materialThe online version of this article (10.1186/s40644-018-0178-0) contains supplementary material, which is available to authorized users.