2025· 150th anniversary of the Metre Convention — From Units to the Universe· 0 citations
TL;DR
The Health Laboratory of the Spanish National Metrology Institute is addressing a challenge by leading three research projects based on the calibration of medical equipment, specifically focusing on diagnostic imaging equipment such as ultrasound and computed tomography (CT) scanners, electrocardiographs (ECG), and blood pressure monitors to ensure measurement traceability.
Abstract
The lack of uniformity among working standards for medical equipment calibration poses a significant challenge in achieving comparable measurements across Spanish hospitals. Furthermore, although beyond our scope, each Spanish Autonomous Community utilizes medical record systems that may not be interoperable between different levels of care, impeding patient care and healthcare system efficiency. While resolving this issue is complex, it is crucial to acknowledge it and collaborate to establish a unified document management system and standardize calibration and verification procedures.While progress is made towards this goal, the Health Laboratory of the Spanish National Metrology Institute (CEM) is addressing a challenge by leading three research projects based on the calibration of medical equipment, specifically focusing on diagnostic imaging equipment such as ultrasound and computed tomography (CT) scanners, electrocardiographs (ECG), and blood pressure monitors to ensure measurement traceability. The main innovation of diagnostic imaging has been based on the design and manufacture of a standard for the verification of ultrasound and CT scanners, called Phantometer, designed to verify the dimensional measurements of ultrasound machines, expandable to diagnostic imaging equipment such as CT, and provide metrological traceability to the International System of Units (SI) in the quantity of length.This new healthcare approach intends for the Phantometer to have several significant advantages over other similar phantoms due to the material it uses, the number of removable reference spheres it possesses, and its versatility in placement for verifying ultrasound and CT scanners.Another main challenge of this laboratory is to ensure that the results of electrocardiographs are traceable both to the volt (for signal amplitude) and to the second (for time measurement), ensuring precision in detecting the heart's electrical activity. To this end, reference standards that can quantify and evaluate the quality of measurement in these increasingly technologically evolved devices are being studied. As a future goal, CEM will focus on obtaining reliable databases for Machine Learning (ML) training, which will allow the creation of more realistic models that can be related to real medical quantities. Therefore, one of the current challenges in the field of electrocardiography is the evaluation of the quality and decision uncertainty of simplified devices such as fitness wearables for the early detection of cardiac abnormalities and diseases. The main challenge for blood pressure monitors is based on ensuring the accuracy and quality of measurement with different equipment. It is intended to include the study of the integration of new technologies in different blood pressure monitors that will help improve the accuracy of these devices through the implementation of advanced algorithms to process signals and reduce errors, and position detection, finding the optimal position of the cuff to prevent measurement errors. All these challenges are fundamental to achieving two strategic objectives: first, the unification of calibration procedures with reliable measurements traceable to the International System of Units (SI), and second, addressing the integrating ML in quality assessment of medical equipment and uncertainty analysis in diagnostic devices. This approach simultaneously ensures metrological consistency and technological advancement in medical diagnostics.
The work is about how medical devices are ultimate goal for realization of SI units with owing traceability from different Si units
It is combination of multiple parameters, that single technical group or technical area can supply fulfill the accuracy requirements,
Since the ultimate goal of metrology is to improve quality of life, the medical metrology can be seen with ultimate goal to improve the quality of human health. It is quite evident that in coming years the extent of medical metrology will expend exponential.
Medical devices, essential tools in modern healthcare, rely on accurate measurements to ensure patient safety and effective treatment. To achieve this, these devices must be calibrated and verified against SI units, tracing their accuracy back to fundamental standards.
As healthcare advances, the demand for accurate medical device measurements will continue to grow. This poster will explore the specific challenges associated with metrology in intensive care units. We will delve into the complexity of tracing these devices to SI units and the multifaceted expertise required for their accurate evaluation.
As a case study we present Infusion Pump, and Syringe Pump, a widely utilized device essential to primary healthcare, specifically for giving patients medication, blood, nutrition, and hydration. Therefore, it is essential that the infusion devices produce the most accurate and precise volume and flow possible, particularly when dealing with neonatology (the care of newborns) or cancer treatment. Appropriate calibration technique along with measurement uncertainty evaluation, is essential for maintaining the traceability of these devices. In this study, flow rate measurement with associated uncertainty was carried out with syringe pump and linear peristaltic infusion pump using the gravimetric-based method (primary method for the calibration of infusion devices).
In this case study two different infusion devices (Syringe Pump and Infusion Pump) are calibrated using the gravimetric method (GM). The measurement uncertainty of two infusion devices are compared and it is observed that the syringe pump offers relatively lower uncertainty in the proposed range with respect to linear peristaltic infusion pump.
Infusion devices (Syringe Pump and Infusion Pump) were evaluated at three flow rates (10 mL/hr, 20 mL/hr, and 50 mL/hr) using the Gravimetric Method (GM). Measured flow rates and their associated expanded uncertainties (U, k=2) were determined.
Analysis revealed that the Infusion Pump may not be suitable for low flow rates (10 mL/hr) as the uncertainty values were comparable to the maximum permissible error of the infusion pumps. This limited the ability to confidently assess conformity.
However, incorporating occlusion pressure into the evaluation could potentially favor the Infusion Pump over the Syringe Pump. This case study exemplifies how multiple parameters (e.g., flow rate, occlusion pressure) significantly influence the selection and performance assessment of medical devices.
We will present other case studies in this poster, showcasing medical devices and their essential reliance on traceability to multiple SI units.
V. V. Agrawal, Vishesh, S. Yadav et al.· 150th anniversary of the Met...· 0 citations
Point of care testing (POCT) systems act as the building blocks for efficient healthcare through timely diagnostic capability – which qualitatively fits patient care sites but still shows the metrological instabilities exposing the issues related to global calibration deviation and internal device variation. Such scenarios require solutions that enhance diagnostic reliability and equitable access to a standard healthcare practice globally.
This poster demonstrates the current effort to implement artificial intelligence (AI) to address metrological issues that are met with POCT systems. AI technology has the greatest opportunity in predictive analytics applied to diagnostic devices and real-time quality control, thereby increasing accuracy and decreasing variability. The devices will automatically adjust with the help of calibration algorithms which would be AI driven. One important area of development is that the POCT systems across different manufacturers must be standardized, and AI can bridge the compatibility issues across different brands of POCT. Structural AI can translate diagnostics’ outputs, or unify them, for better system integration and provide global referentiality of the results. Recent developments presented the possibility of point-of-care testing portable areas of AI innovations that possess self-calibrating and error identification capability to minimize actual reliance on the user and human error in testing concurrently enhancing the accuracy of the test. In the future, it will be promoted to create an international metrological reference system for artificial-intelligence-supported diagnostics, as well as to define the requirements for them and create legal norms for validation. Such approaches concentrating on data safety with the help of blockchain and other similar tools, expand the reliability of such innovations.
The integration of AI in operating POCT systems exhibits possibilities, higher accuracy of diagnosis, better patient results and affordability for worldwide use. This approach demonstrates the importance of digital transformation-AI in developing metrology for healthcare improvements.
G. Omondi· 150th anniversary of the Met...· 0 citations
The rapid expansion of diagnostic radiology services across Namibia’s public and private sectors necessitates a robust, standardized framework for quality control (QC), which is part of a comprehensive quality assurance program to ensure patient safety and diagnostic accuracy. While ionizing radiation is a powerful diagnostic tool, its use carries inherent risks of stochastic and deterministic effects, making the meticulous management of radiation dose a critical public health concern. The current radiological landscape in Namibia is characterized by varying practices and a lack of unified QC protocols, which lead to significant inconsistencies in radiation dose delivery and suboptimal image quality. This paper proposes a comprehensive, pragmatic framework for QC designed to harmonize national practices. The methodology includes routine equipment performance testing focusing on kilovoltage peak (kVp) accuracy, kVp reproducibility, timer reproducibility, half-value layer, and tube output reproducibility. This framework is specifically tailored to address the unique logistical and resource challenges within Namibia’s healthcare system, such as the geographical dispersion of facilities and limited specialized personnel. By implementing this standardized approach, Namibia can enhance patient protection through optimized radiation doses and significantly improve the reliability and clinical value of radiological examinations. Furthermore, the framework facilitates the transition from reactive maintenance to proactive quality assurance. This initiative represents a vital step toward strengthening the Namibian healthcare infrastructure, ensuring that diagnostic services align with international standards of radiation safety as set by the International Atomic Energy Agency. Ultimately, this framework fosters a sustainable culture of excellence in medical imaging for the benefit of all Namibian patients.
Kaino N. Haipinge, Vera Uushona, Sylvanus A. Onjefu et al.· Advances in Radiotherapy &a...· 0 citations
Health metrology plays a crucial role in modern medicine. This discipline faces significant challenges that demand innovative solutions to ensure precise and reliable medical measurements. Health metrology thus positions itself as a fundamental pillar to address future challenges in healthcare, guaranteeing reliable measurements traceable to the International System of Units.
A cutting-edge technology on the rise today is Artificial Intelligence (AI), which plays a key role in the healthcare field, enabling more advanced analysis and automation of measurements. Machine Learning (ML) and AI algorithms help us identify subtle patterns, improving early disease detection, with the consequent savings for the healthcare system that this implies.
The Spanish National Metrology Institute (CEM) has recently established a Health Laboratory with the purpose of strengthening the metrological infrastructure in the healthcare sector. This laboratory seeks to promote research and development of innovative measurement technologies to address emerging challenges in health metrology. Among its current objetives are:
• Exploring the application of Artificial Intelligence and Machine Learning in healthcare, specifically in diagnostic imaging.
• Actively participating in European projects and networks related to health metrology.
• Contributing and supporting projects in the EMP Health Call 2025, in the specific line dedicated to the health sector.
The challenge that CEM aims to address is the evaluation of the quality of AI systems based on the analysis of medical image data from ultrasound and CT scans. Similarly, it intends to study the implementation of AI for analyzing the minimum radiation dose limit that would allow achieving results similar to those obtained with higher dose values and provide quality diagnostic images.
This challenge would ensure that doses remain below established legal limits with available AI tools. It will allow identifying response patterns to different radiation doses, predicting the efficacy of lower doses based on individual patient characteristics, and optimizing dosing regimens to maximize efficacy while minimizing side effects.
This objective would lead to the reduction of adverse effects and toxicity, optimization of resources and cost reduction in the healthcare system, as well as personalization of treatments based on individual patient characteristics.
This new approach to Health metrology that is presented in the coming years will provide the integration of artificial intelligence in terms of specific regulation in metrology and, above all, data protection.
This challenge arises from the need for synergy between Machine Learning (ML), Artificial Intelligence (AI), and Personalized and Precision Medicine in the healthcare field. This technological convergence will allow a more precise, personalized, and effective approach to disease diagnosis and treatment.
Ángela Esteban Temprano, Laura Delgado San Martín, Teresa Fernández Vicente et al.· 150th anniversary of the Met...· 0 citations
Clinical testing using human-derived samples, such as blood and urine, has made remarkable progress due to advacements in measurement technologies and standards, playing a crucial role in supporting human health and well-being.
In response to emerging trends and evolving healthcare demands, there are several challenges in this field that need to be addressed. Key cahllenges include, 1) ensuring the reliability of measurements for the implementation of telemedicine and centralized testing, which has seen explosive demand since the COVID-19 pandemic; 2) improving the quality of medical data for the successful integration of AI technologies; and 3) enabling early diagnosis and disesase prevention in response to the global aging trend.
To address these challenges, the Korea Research Institute of Standards and Science (KRISS) is conducting innovative research and development efforts.
Firstly, as part of standardizing micro-sampling blood collection methods that maximize the advantages of remote blood sampling (home sampling) and easy delivery for the establishment of telemedicine and remote testing systems, KRISS is developing certified reference materials for dried blood spots, the most widely used micro-sampling platform. It is also conducted fundamental research on traceability and bias factors to improve the measurement reliability of this sampling method.
Additionally, in collaboration with the National Health Insurance Service of Korea, KRISS is developing national reference standards based on the big data originated from huge Korea National Healthcare System. The projects have improved the quality of accumulated medical database, an outstanding national resource of Korea by assessment of measurement traceability and uncertainty for integration with AI data validation. This effort is paving the way for improving national healthcare and public well-being through data qualification.
Lastly, in response to the global aging trend and the growing emphasis on preventive healthcare, KRISS is developing standards for precision medicine. These standards aim to assess environmental hazard exposure and enable early disease detection. The reference materials for the purposes take roles in qualification to evaluate the bio-exposure toxicity and efficacy of diverse environmental factors. These materials will also play a crucial role in quality control for laboratories, ensuring consistent and reliable results that contributes to national policies and healthcare programs through the establishment of a national measurement system.
The strength of organic metrology lies in its straightforward apporach to both measurands and measurement procedures, even in complex biological applications. It ensures completely established measurement traceability to the International System of Units (SI) and utilizes matrix-matched reference materials, which are essential for building a global measurement network and ensuring reliability across the world. Over the past decades, significant progress has been made in developing measurement system and standardization based on organic metrology, driven by the efforts of the Organic Analysis Working Group (CCQM-OAWG) and the Joint Committee for Traceability of Laboratory Medicine (JCTLM). In the coming century, this strong foundation is expected to play a key role in realizing telemedicine, AI-powered healthcare, and precision medicine for the 'sustainable’ health and well-being of humanity.
Ji-Seon Jeong, Ha-Jeong Kwon, Kihwan Choi et al.· 150th anniversary of the Met...· 0 citations
Ensuring precise and reliable measurements in nuclear medicine is a cornerstone of patient safety and effective treatment. Radionuclide dose calibrators, or activimeters, are critical instruments for determining the activity of radiopharmaceuticals used in diagnostic and therapeutic procedures. However, traditional calibration and intercomparison methods face significant challenges, including the short half-life of radiopharmaceuticals, variations in sample geometry, and susceptibility to environmental influences. These limitations impede the accuracy and reliability of measurements, with direct implications for healthcare outcomes.
This project addresses these challenges by leveraging Metrology 4.0 technologies—artificial intelligence (AI), Internet of Things (IoT), and blockchain—to redefine the calibration and intercomparison of dose calibrators. A significant breakthrough has been achieved with AI-driven computational vision techniques, which automate the analysis of measurement data, eliminate human error, and enhance precision and repeatability. Blockchain technology complements these advancements by providing secure, immutable records of measurement data, ensuring traceability and enabling robust auditing processes.
Recent laboratory validations have demonstrated substantial improvements in measurement accuracy and operational efficiency when compared to traditional methods. These findings underscore the transformative potential of integrating advanced technologies into metrology practices, especially in high-stakes applications like nuclear medicine. By fostering global standardization in radionuclide activity measurements, this work directly contributes to international metrological efforts and enhances the safety and efficacy of nuclear medicine.
Looking ahead, this project aims to refine AI algorithms for broader applicability, extend experimental validations to encompass a diverse range of radionuclides, and explore real-time monitoring capabilities through next-generation sensors. Furthermore, it highlights emerging metrological needs, such as the development of standardized digital protocols and collaborative data-sharing frameworks, which are essential for scaling these innovations globally.
This initiative exemplifies how Metrology 4.0 can address contemporary measurement challenges, promote technological innovation, and ultimately improve global metrology systems. It represents a paradigm shift in how precision, security, and interoperability are achieved in complex measurement environments.
Keywords: Metrology 4.0, Nuclear Medicine, Dose Calibrators, Artificial Intelligence, Blockchain, IoT, Digital Transformation
Monaliza de Oliveira Almeida, Wilson de Souza Melo Jr, Carlos Henrique Simões de Sousa et al.· 150th anniversary of the Met...· 0 citations
