Methodological Steps Research Articles

Consensus and contestation: Reflections on the development of an indicator framework for a just transition to a circular economy

We explore an attempt to derive a set of indicators reflecting a just transition to a circular economy (CE) at a supply chain level. Here we build upon the theoretical work presented in Purvis and Genovese (2023) with an account of an empirical exercise following the standard methodological steps outlined for the creation of a measurement dashboard. A literature review of existing CE indicators for supply chains was therefore followed by a Delphi approach which sought to understand and incorporate the expertise of CE scholars and practitioners. The 3 round Delphi incorporated a survey, and an individual, and group Analytical Hierarchy Process, as a standard technique to derive consensus from experts in terms of suitable indicator categories. Yet contestations observed during the consensus building exercises cast doubt on the suitability of our nominally consensus-driven approach, as well as the use of indicators themselves for our critical purposes. We describe the dilemmas precipitated by this failure of consensus, with reference to the inherent challenges to indicator frameworks and a series of questions for better research design. The paper also reflects on the fundamental contradictions related to the use of indicators for inducing transformational dynamics, and problematises the desire for consensus, thereby paving the way for further research avenues.

Co-developing a theory of change for a personalised multimodal cancer prehabilitation programme in South Wales

BackgroundEvidence suggests that prehabilitation interventions, which optimise physical and mental health prior to treatment, can improve outcomes for surgical cancer patients and save costs to the health system through faster recovery and fewer complications. However, robust, theory-based evaluations of these programmes are needed. Using a theory of change (ToC) approach can guide evaluation plans by describing how and why a programme is expected to work. Theories of Change have not been developed for cancer prehabilitation programmes in the literature to date. This paper aims to provide an overview of the methodological steps we used to retrospectively construct a ToC for Prehab2Rehab (P2R), a cancer prehabilitation programme being implemented by the Cardiff and Vale University Health Board.MethodsWe used an iterative, participatory approach to develop the ToC. Following a literature review and document analysis, we facilitated a workshop with fourteen stakeholders from across the programme using a ‘backwards mapping’ approach. After the workshop, stakeholders had three additional opportunities to refine and validate a final working version of the ToC.ResultsOur process resulted in the effective and timely development of a ToC. The ToC captures how P2R’s interventions or activities are expected to bring about short, medium and long-term outcomes that, collectively, should result in the overarching desired impacts of the programme, which were improved patient flow and reduced costs to the health system. The process of developing a ToC also enabled us to have a better understanding of the programme and build rapport with key stakeholders.ConclusionsThe ToC has guided the design of an evaluation that covers the complexity of P2R and will generate lessons for policy and clinical practice on supporting surgical cancer patients in Wales and beyond. We recommend that evaluators apply a ToC development process at the outset of evaluations to bring together stakeholders and enhance the utilisation of the findings. This paper details a pragmatic, efficient and replicable process that evaluators could adopt to develop a ToC. Theory-informed evaluations may provide better evidence to develop and refine cancer prehabilitation interventions and other complex public health interventions.

Methodological steps forward in toxicological in vitro screening of mineral wools in primary rat alveolar macrophages and normal rat mesothelial NRM2 cells.

Man-made vitreous fibers (MMVF) comprise diverse materials for thermal and acoustic insulation, including stone wool. Depending on dimension, durability, and dose, MMVF might induce adverse health effects. Therefore, early predictive in vitro (geno)toxicity screening of new MMVF is highly desired to ensure safety for exposed workers and consumers. Here, we investigated, as a starting point, critical in vitro screening determinants and pitfalls using primary rat alveolar macrophages (AM) and normal rat mesothelial cells (NRM2). A stone wool fiber (RIF56008) served as an exemplary MMVF (fibrous vs. ground to estimate impact of fiber shape) and long amosite (asbestos) as insoluble fiber reference. Materials were comprehensively characterized, and in vivo-relevant in vitro concentrations defined, based on different approaches (low to supposed overload: 0.5, 5 and 50µg/cm2). After 4-48h of incubation, certain readouts were analyzed and material uptake was investigated by light and fluorescence-coupled darkfield microscopy. DNA-strand break induction was not morphology-dependent and nearly absent in both cell types. However, NRM2 demonstrated material-, morphology- and concentration-dependent membrane damage, CINC-1 release, reduction in cell count, and induction of binucleated cells (asbestos > RIF56008 > RIF56008 ground). In contrast to NRM2, asbestos was nearly inactive in AM, with CINC-1 release solely induced by RIF56008. In conclusion, to define an MMVF-adapted, predictive in vitro (geno)toxicity screening tool, references, endpoints, and concentrations should be carefully chosen, based on in vivo relevance, and sensitivity and specificity of the chosen cell model. Next, further endpoints should be evaluated, ideally with validation by in vivo data regarding their predictivity.

Applying Topic Modeling to Literary Analysis: A Review

Abstract This article examines the integration of topic modeling within literary studies, highlighting its potential to transform conventional literary analysis through computational techniques. It reviews the theoretical underpinnings underlying topic modeling, including prominent algorithms like Latent Dirichlet Allocation, Non-negative Matrix Factorization, and Neural Topic Models, and discuss their utility in dissecting large textual corpora to uncover latent thematic and stylistic patterns. The article subsequently addresses the specific methodological steps for effective implementation, spanning text preprocessing model tuning and result interpretation. We further illustrate the diverse applications of topic modeling in literary studies through thematic analysis, comparative studies, and the extraction of cultural and historical insights. Challenges such as model accuracy, technical limitations, and ethical considerations are critically assessed. The review concludes by envisioning prospective future directions that foresee enhanced integration of topic modeling into literary criticism, facilitated by technological and interdisciplinary advancements.

The Effectiveness of eHealth Interventions in Promoting the Health Literacy of Informal Caregivers: A Systematic Literature Review Protocol

Background: Digital Information and Communication Technologies (ICTs) offer significant opportunities to enhance public health, particularly through their strategic use in promoting health literacy. Objectives: This systematic review protocol aims to outline the methodological steps necessary to conduct a systematic review of the effectiveness of digital interventions in improving health literacy among informal caregivers. Methods: This review will include studies involving adult informal caregivers (≥18 years) undergoing a digital health intervention promoting health literacy. Intervention, effectiveness or efficacy, RCT, quasi-experimental, and observational studies will be eligible. This review will follow the methodology for Cochrane Systematic Review and Meta-Analysis. The search strategy will identify studies published in the databases SCOPUS and Web of Science, as well as CINAHL (via EBSCO) and PubMed and gray literature sources. Two in-dependent reviewers will screen the studies, extract data, and critically appraise the selected studies. It is planned that the risk of bias will be assessed using the RoB2, Newcastle-Ottawa Scale (NOS), and the ROBINS-I (Risk Of Bias In Non-randomized Studies of Interventions). From the included studies, data will be extracted on the identification of the study, the aim of the study, characteristics of the population, study method and intervention and control conditions, study variables, and significant results. Conclusions: It is anticipated that the results of the study will guide healthcare professionals and managers in incorporating digital technologies into health literacy programs for informal caregivers. Whenever possible, a statistical meta-analysis will be performed to combine study results. The PROSPERO registration number is CRD42024589465.

An Image Fusion Algorithm for Sustainable Development Goals Satellite-1 Night-Time Light Images Based on Optimized Image Stretching and Dual-Domain Fusion

The Glimmer Imager of Urbanization (GIU) on SDGSAT-1 provides high-resolution and global-coverage images of night-time lights (NLs) with 10 m panchromatic (PAN) and 40 m multispectral (MS) imagery. High-resolution 10 m MS NL images after ideal fusion can be used to better study subtle manifestations of human activities. Most existing remote sensing image-fusion methods are based on the fusion of daytime optical remote sensing images, which do not apply to lossless compressed images of the GIU. To address this limitation, we propose a novel approach for 10 m NL data fusion, namely, a GIU NL image fusion model based on PAN-optimized OIS (OIS) and DDF (DDF) fusion for SDGSAT-1 high-resolution products. The OIS of PAN refers to the optimized stretching method that integrates linear and gamma stretching while DDF indicates a fusion process that separately merges the dark and light regions of NL images using different fusion methods, then stitches them together. In this study, fusion experiments were conducted in four study areas—Beijing, Shanghai, Moscow, and New York—and the proposed method was compared to traditional methods using visual evaluation and five quantitative evaluation metrics. The results demonstrate that the proposed method achieves superior visual quality and outperforms conventional methods across all quantitative metrics. Additionally, the ablation study confirmed the necessity of the methodological steps employed in this study.

Avaliação da acústica em shopping centers de Maceió

Shopping centers are increasingly becoming popular as a leisure option in urban centers, as they offer security and provide protection against high urban temperatures. However, these spaces have become places of agglomeration, which results in very noisy environments due to the intense flow of people. Thus, this work aims to evaluate the acoustic environment of the three largest shopping centers in the city of Maceio, Brazil. The methodological steps of this study included the selection of shopping centers, sound measurements, the identification of noise sources in the spaces, and the analysis and discussion of the results, made through the collection of sound pressure levels and speech intelligibility levels. The results indicated that, in some of the scenarios studied, the sound levels were above what is allowed by the standards and may be harmful to hearing health in case of prolonged permanence. It was concluded that the lack of adequate acoustic materials in projects can contribute to high sound pressure levels and noise exposure.

Using AI in the informal currency market: evidence from Cuba

ABSTRACT This article explains the various steps of a novel methodology designed to analyse the informal currency market and calculate a parallel exchange rate (ER). We utilize artificial intelligence algorithms for Natural Language Processing to extract data from social network groups and classified websites. The methodology has been implemented since 2021 amidst Cuba’s complex financial and political landscape. Given that the official exchange rate remains fixed and overvalued, the calculated ER has become vital for assessing the real-time effects of regulatory changes, economic shocks, and policies. We conduct a statistical and econometric analysis using vector autoregressive models and spillover indexes to validate the economic and financial consistency of the informal market’s time series.

Evaluation criteria for a systemic approach to flood risk management: stakeholders’ perspectives

Flood risk management authorities rely on structural engineering measures centralised at the spatial and governance levels. These are mainly evaluated based on damage reduction without considering social, economic and environmental criteria. The research proposes an evaluative and procedural methodology to support the choice of spatially distributed measures. After illustrating the research project and the applied methodology, the paper focuses on the first methodological step, which involves identifying multi-scalar and multidisciplinary evaluative criteria through a systematic literature review and interviews. The paper concludes by presenting the criteria, reflecting on the topic and the subsequent developments of the research.

Cost-benefit analysis: just a step in the HIA process

Abstract The economic analysis within Health Impact Assessments (HIA) is a critical component in informing public policy decisions by assessing the financial implications of health outcomes associated with the different intervention options. Health metrics play a role defining the cost-effectiveness and societal value associated with the interventions. These metrics, quantifying the health impacts, include quality-adjusted life years (QALYs), years of life lost (YLLs) or disability-adjusted life years (DALYs). On another level, such metrics need to be translated into cost-effectiveness and societal value in which other methods play a role, such as the value of statistical life (VSL) or the value of a life year (VOLY). While VSL quantifies the value individuals place on reducing mortality risk, VOLY evaluates the value attributed to extending life expectancy. On another hand, uncertainties related to economic valuation pose challenges to the accuracy and reliability of cost estimates within HIA. These come from several factors, including data quality, methodological differences across studies, and subjective judgments involved in valuing health states. In fact, estimating the economic value of a prevented death involves multifaceted considerations and important assumptions. Additionally, assigning monetary values to non-fatal health outcomes, such as disability or reduced quality of life, involves subjective assessments and value judgments. By selecting appropriate metrics, considering diverse data sources, and addressing methodological steps and uncertainties, HIA practitioners can improve the utility of economic assessments, facilitating evidence-based decision-making in public health policy and resource allocation. This work was supported by National Funds through FCT - Fundação para a Ciência e a Tecnologia,I.P., within CINTESIS, R&D Unit (reference UIDP/4255/2020).

Cross-cutting integration of equity and diversity lens in public health: a novel approach of JACARDI

Abstract Issue/Problem Health inequities persist across European countries, impacting the distribution, prevention, and management of non-communicable diseases. With increasing population diversity and improved understanding of the intersectional nature of drivers of health inequities, narrowing inequities calls for systematic integration of diversity perspectives into equity-driven policy and practice. Description of the problem The EU-co-funded Joint Action on CVDs and diabetes (JACARDI, 11/2023-10/2027) project with 76 partners from 21 countries and 142 national-level projects (later pilots), applies a structured approach for integrating equity and diversity perspectives within all project structures. This is achieved through design of a common methodological framework and terminology glossary for all thematic work packages (WPs) and their pilots, which are further supported through capacity building sessions and consultations. Results The “4Cs” framework (Critical reflection; Context and data; Co-design; and inclusive and accessible Communications) for integrating equity and diversity principles in JACARDI was developed based on results of focus group interviews with WP leaders (n = 24) and review of previous literature. This framework was applied as a lens to be applied in the planned activities by WPs and pilots, elaborated in an equity and diversity maturity matrix aligned with the XV methodological steps for pilot implementation. Additionally, equity and diversity indicators were integrated into harmonized context analysis questionnaires for national focal points of each partner country, as well as into the methodology for pilot assessment and reporting. Lessons Equity and diversity perspectives should be integrated into the core structures of project implementation, supported by practical tools, trainings and practical consultations to improve adherence and collaborative understanding across project partners. Key messages • Equity and diversity integration into core structures are essential for tackling health inequities and the NCD-related social gradient in Europe. • Encouraging critical reflection among JACARDI partners is pivotal for initiating a paradigm shift towards equity and diversity inclusion.

Pectus excavatum or Pectus chiaroscurum in paintings of St. Jerome (17th century)?

Considering the influence of artistic style is a key methodological step in the iconodiagnostic process in order to avoid some pitfalls. The two present artworks, depicting Saint Jerome, attributed respectively to the 17th-century Neapolitan school and to Valentin de Boulogne, French painter of the 17th century, highlight how the interplay of light and shadow can enhance and disguise a possible pectus excvatum.

Automated tree crown labeling with 3D radiative transfer modelling achieves human comparable performances for tree segmentation in semi-arid landscapes

Mapping tree crowns in arid or semi-arid areas, which cover around one-third of the Earth’s land surface, is a key methodology towards sustainable management of trees. Recent advances in deep learning have shown promising results for tree crown segmentation. However, a large amount of manually labeled data is still required. We here propose a novel method to delineate tree crowns from high resolution satellite imagery using deep learning trained with automatically generated labels from 3D radiative transfer modeling, intending to reduce human annotation significantly. The methodological steps consist of 1) simulating images with a 3D radiative transfer model, 2) image style transfer learning based on generative adversarial network (GAN) and 3) tree crown segmentation using U-net segmentation model. The delineation performances of the proposed method have been evaluated on a manually annotated dataset consisting of more than 40,000 tree crowns. Our approach, which relies solely on synthetic images, demonstrates high segmentation accuracy, with an F1 score exceeding 0.77 and an Intersection over Union (IoU) above 0.64. Particularly, it achieves impressive accuracy in extracting crown areas (r2 greater than 0.87) and crown densities (r2 greater than 0.72), comparable to that of a trained dataset with human annotations only. In this study, we demonstrated that the integration of a 3D radiative transfer model and GANs for automatically generating training labels can achieve performances comparable to human labeling, and can significantly reduce the time needed for manual labeling in remote sensing segmentation applications.

Optimal 16S rRNA gene amplicon sequencing analysis for oral microbiota to avoid the potential bias introduced by trimming length, primer, and database.

16S rRNA gene amplicon sequencing analysis is used to investigate bacterial communities; however, the estimated bacterial composition can differ from the original due to experimental and analytical biases. Therefore, this study determines the optimal conditions to minimize the potential biases in 16S rRNA gene amplicon sequencing analysis using different DNA samples, trimming lengths, primers, and databases. The results of the mock1 community with 250 and 300 bp paired-end (PE), comprising 15 bacteria from various environments, showed the highest similarity between the theoretical value and the data using the Greengenes2 and the V3 region at the genus level and V5-V6 at the species level. In the 300 bp PE sequencing analysis of the mock2 community, comprising six major oral bacteria, the data using the V3-V4, V4, and V5-V6 regions with the SILVA, Greengenes2, and the Human Oral Microbiome Database (HOMD) showed the highest similarity to the theoretical values at the genus level. At the species level, the data using the V3-V4 and V4 regions with Greengenes2 and the data using the V1-V2 with HOMD exhibited the highest alignment with the theoretical values. In the species analysis of the dental calculus samples with 300 bp PE, the Shannon index value was higher with the V1-V2 region and HOMD than with others. Our results suggest that the optimal conditions for oral microbiome analysis are the combinations of 300 bp PE and the V3-V4 or V4 region with the Greengenes2 and the V1-V2 with HOMD.IMPORTANCEThe 16S rRNA gene amplicon sequencing analysis is frequently used in oral microbiome research. However, this method can have biases that distort the experimental data, which depend on the methodological steps, including sequencing length, trimming length, selected amplification regions, and referenced databases. In this study, a combination of 300 bp PE and the primer targeting the V3-V4 or V4 regions with the Greengenes2 and the V1-V2 region with the HOMD was the most bias-minimizing condition for oral microbiota analysis. In addition, this is the first report of such analyses in modern Japanese dental calculus. The methods used in this study will aid in setting appropriate conditions for sequence analysis of microbiota obtained not only from the oral cavity but also from any environment.

A Culturally Sensitive Mobile App (DiaFriend) to Improve Self-Care in Patients With Type 2 Diabetes: Development Study.

Mobile apps designed with cultural sensitivity have demonstrated higher user acceptability and greater effectiveness in enhancing self-care skills. However, a significant gap exists in developing such apps for specific populations, such as Portuguese Americans living in southern Massachusetts, home to the second-largest Portuguese community in the United States. This group possesses unique cultural traditions, particularly in dietary practices, including a tendency toward high carbohydrate intake. Tailoring diabetes self-care apps to address these specific cultural requirements could substantially improve diabetes management within this population. The aim of this app development project was to develop a prototype diabetes management app for Portuguese Americans with type 2 diabetes mellitus using the design thinking methodology, incorporating user-centered design principles and cultural sensitivity. This paper describes the phase-2 results, focusing on app design and development. Phase 2 of this app development project adhered to the design thinking methodology delineated by the Hasso Plattner Institute of Design at Stanford University, focusing on 2 critical steps: ideation and prototyping. This phase started in March 2022 and continued until April 2024. The project was driven by a multidisciplinary team consisting of 2 nurse educators; an app development specialist; and 2 graduate research assistants from the university's Computer and Information Sciences Department, both well-versed in mobile app development. Data collected during phase 1, which will be published separately, informed the app design and development process. The prototype of the DiaFriend app (version 1) was designed and developed. The app comprises five features: (1) blood glucose monitoring, (2) weight tracking, (3) carbohydrate tracking, (4) exercise log, and (5) medication reminder. The carbohydrate tracking feature was explicitly tailored to correspond to Portuguese food culture. This paper presents the front-end interface flowchart, demonstrating how the user navigates through each screen. It also discusses the challenges faced during the backend development, such as data not being able to be stored and retrieved. The DiaFriend app (version 1) distinguishes itself from conventional diabetes self-care apps through its emphasis on cultural sensitivity. The development of this app underscores the importance of cultural considerations in health informatics. It establishes a foundation for future research in developing and evaluating culturally sensitive mobile health apps. The adaptation of such technologies has the potential to enhance self-care practices among Portuguese Americans with type 2 diabetes mellitus, with improved glycated hemoglobin levels as a potential outcome. The last step of the design thinking methodology, testing the app, will be conducted in phase 3 and the results will be published elsewhere.

Bentuk Kias Berunsur Tangan dan Aktivitas dengan Tangan pada Korpus Digital

The role of language as a communication tool is very important because it carries messages and provides information from the speaker or to the interlocutor. One of the uses of language to convey messages is by using hand activities. The research aims to analyze forms of figurative expressions involving the hand, specifically the use of figurative language and expressions that correlate with body parts, with the object being the Digital Corpus. The research approach used in this study is a qualitative approach through descriptive exposition. The methodological steps will be elaborated by the researcher through observation, analysis process, and description. Based on the analysis results, it can be concluded that, first: In the digital corpus CQPweb Lancaster University, a total of 91 figurative expressions involving the hand and hand activities were found. Second: In the process of forming figurative expressions involving the hand, only morphological processes of blending or composition in meaning formation were found. Third: The internal relation in figurative expressions involving the hand is formed by the arrangement or elements of two words that form a compound word. These compound words then indicate figurative meaning. This figurative meaning is produced from the combination of the meanings of the two combined words. Fourth: Several functions of figurative expressions involving the hand include: (1) creating poetic effects, (2) conveying implied meanings, (3) creating cultural identification, (4) creating expressive meanings, and (5) creating social and political critique.

Mental health of healthcare residents in the context of the COVID-19 Pandemic: a Scoping Review Protocol

The objective was to present the methodological steps for developing a scoping review aimed at mapping studies on the impacts of the COVID-19 pandemic on the mental health of health field residents. This is a scoping review protocol, developed in accordance with the guidelines of the Joanna Briggs Institute Manual and registered on the Open Science Framework (DOI: https://osf.io/vydtz/). For the literature search, the following databases will be used: PubMed via MEDLINE, Web of Science, SciVerse Scopus (Elsevier), Embase, PsycINFO, LILACS via BVS, ProQuest Dissertations & Theses Global, and Google Scholar. The selection process and the presentation of results will follow the PRISMA-ScR guidelines. B Based on the results found in the studies selected to compose the sample, we aim to evaluate the existing research on the impacts of COVID-19 on the mental health of residents in the health field, both within the academic environment and in the context of public policy discussions related to mental health. The goal is to develop a scoping review that enables the mapping of studies, the identification of gaps, and the proposal of new research on the subject.

EEG-based emotional valence and emotion regulation classification: a data-centric and explainable approach

Emotion classification using electroencephalographic (EEG) data is a challenging task in the field of Artificial Intelligence. While many researchers have focused on finding the best model or feature extraction technique to achieve optimal results, few have attempted to select the best methodological steps for working with the dataset. In this study, we applied two different theoretical approaches based on the noise of the dataset: curriculum learning and confident learning. Curriculum learning involves presenting training examples to the model in a specific order, starting with easier examples and gradually increasing in difficulty. This approach has been shown to improve model performance. Confident learning is a method for identifying and correcting label errors in datasets. By identifying and correcting these errors, confident learning can improve the performance of machine learning models trained on noisy datasets. We then applied the Integrated Gradient technique in order to assess the explainability of each model. Our aim was to explore the impact of different models and methods on emotion classification performance using EEG data. We collected and used an EEG dataset in which participants rated the emotional valence of positive and negative pictures while performing an emotion regulation (ER) task, comparing a control condition (Look) with two ER strategies: cognitive reappraisal and expressive suppression. We performed a multilabel classification to identify emotional neutrality or polarization of emotional valence (both positive and negative) rated by participants and the emotion regulation strategy adopted during the task. We compared the performance of models trained on three datasets selected based on label noise and evaluated their suitability for this task. Our results suggest different patterns based on the architecture used for feature importance, highlighting both advantages and criticisms.

Techno – economic and environmental design of a three – phase hybrid renewable energy system for UNVDA Ndop Cameroon using meta-heuristic and analytical approaches

A three – phase hybrid renewable energy system have been proposed in this study as an alternate current grid power supply for an agro – company in the North – West Region of Cameroon. In this study, an industrial load profile with an energy demand of 383.45 kWh/day, 72.79 kWp peak and a residential load with energy demand of 33.26 kWh/day, 2.7 kWp peak have been considered in solving the economic, technical and environmental aspects of the optimization problem. To achieve the best results, a two step methodology has been implored to design the system. The first method requires an analytical approach used to determine the required battery, inverter, diesel generator capacities and the number of three phase PV arrays (NF). The second methodology is a techno – economic and environmental analysis conducted for different number of NF using three meta-heuristic algorithms; ABC, GA and PSO. The obtained results from these methodologies showed that for different values of NF, the REF was in the range 62.9–99.8 % in the Photovoltaic hybrid system (PVHS). The lowest cost of energy was 0.1441 €/kWh at a final REF of 99.8 % compared to a standalone system with an energy cost of 0.1655 €/kWh. The PVHS consist of a 117 kW PV array, 30 kW inverter, 160 kW diesel generator operating at a load factor of 75 % and a battery bank capacity of 43.2 kWh. The Standalone option consist of a 126 kW PV array, 135 kW inverter and a battery bank capacity of 475.2 kWh. The large inverter capacity and battery bank in the standalone system accounts for the high energy cost compared to the PVHS. This study can be used to evaluate and validate the performance of hybrid renewable energy systems for agro – companies whose load profile lack time series data and require a three – phase supply for industrial applications.

Standardized maps – an emerging approach to leverage quantitative information in knee imaging

ObjectiveProperty maps, which capture spatial variations across the entire joint, are emerging as a powerful means for extracting and analyzing quantitative information from knee 3D imaging datasets, particularly from CT and MRI data. This perspective paper aims to discuss the processing pipelines used so far, as well as the results they have enabled with respect to osteoarthritis. DesignThe key methodological steps for obtaining property maps, including segmentation, property calculation, and standardization are presented and analysis methods are discussed. Representative studies are also examined to illustrate the state-of-the-art in this field. ResultsThree main processing pipelines have been used, with the segmentation, property calculation, and standardization steps occurring in different orders. Many methods have been successfully considered for ordering these steps, without any looking generally preferable to the others. Thanks to recent advances in segmentation and standardization techniques, routine processing of property maps appears conceivable in the near future. Maps have been analyzed for multiple purposes, including group comparisons, pattern recognition, and cross-property modelling. Mostly maps of cartilage thickness and composition, as well as maps of bone shape and mineral density have been reported. They revealed distinct patterns associated with osteoarthritis severity, achieved high diagnostic accuracy, and identified relationships among tissue properties. ConclusionsProperty maps represent a promising approach for leveraging the extensive information in imaging data. They are particularly interesting for standardizing complex spatial variations in tissue properties, enabling global analysis and modelling. Once challenging to obtain and interpret, current mapping methods are being improved to the point that property maps may well be in routine use in the near future.