Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM

The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC‐ISMRM) held a workshop entitled “Steps on the path to clinical translation” in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round‐table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community.


INTRODUCTION
Quantitative MR (qMR) imaging and spectroscopic biomarkers can probe a multitude of biophysical properties in patients with a wide range of disease. They offer great potential for advancing our understanding of pathology as well as improving diagnosis, prognosis, and prediction of response to therapy. Too often, this potential has not translated into widespread clinical adoption, with a low number of qMR imaging or spectroscopic methods used in clinical decision making. 1,2 On 7th September 2022, the British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM) held a workshop entitled "Steps on the path to clinical translation" in Cardiff (UK). The aim was to highlight to the BIC-ISMRM community the difficulties in translating qMR imaging and spectroscopic biomarkers, developed in academia, into clinical application and to discuss some possible solutions to improve successful translation.

Problems
In the morning session, we focused on problems associated with the clinical translation of qMR imaging biomarkers. Speakers presented the perspectives of a radiologist (Shonit Punwani -University College London), a radiographer (Rebecca Mills -University of Oxford), and two clinical physicists (Maria Yanez Lopez -Swansea Bay University Health Board and Matthew Grech-Sollars -University College London and University College London Hospitals NHS Foundation Trust).
A. Radiologist's perspective: Shonit Punwani (S.P.) opened the workshop by expressing his opinion that the clinical community is aware of more sensitive imaging biomarkers being developed but that there is not an established pathway to move imaging biomarkers into the clinic. He suggested that we need to link up the translational pathway by providing supportive infrastructure for the essential translational work that takes place in between the initial development of a novel qMR imaging biomarker and the final clinical application. The infrastructure developed by the National Cancer Imaging Translational Accelerator 3 is such an example. He also suggested that there should be suitable academic recognition for clinical translation such as high impact journals publishing more reproducibility studies and more research grant funding focussed on clinical translation. S.P. described his personal experience of taking multi-parametric MRI for prostate cancer from a single centre implementation to a clinically relevant tool, 4 a process that took over 10 y. SP highlighted the need for strong technical and biological validation and multi-centre evaluation, explaining how not all steps along the pathway need to be performed by one group of researchers. To progress along the radiological research pathway a research group or community needs to: 1. establish that there is an unmet clinical need, 2. find the resources to support the necessary studies to provide an evidence base, 3. understand the regulations involved in the anticipated change in clinical practice,  5 for clinical myocardial T1-mapping as an example of the steps required and challenges in moving a research idea to clinical product. In over 10 y of development, ShMOLLI has amassed a large published clinical evidence base, which supports its use for clinical applications. 6,7 Industry partner support is vital for clinical translation of MR methods borne out of research development.
Radiographers are at the coalface of data acquisition and perform initial quality assurance on the data. Therefore, the need for quick, easy to interpret inline analysis and quality testing is important. physicists support many aspects of qMR biomarker translation including sequence installation, protocol setup, image acquisition and reconstruction, image analysis and reporting. They concluded that good communication across all disciplines and stakeholders is key to a successful outcome and that clinical physicists play a central role in this.

Solutions
In the afternoon session, we focused on solutions. Speakers discussed the perspectives of a vendor (Fabrizio Fasano -Siemens Healthineers), an Imaging Contract/Clinical Research Organization (CRO) (John Waterton -Bioxydyn Ltd), an open science initiative (Michael Thrippleton -ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)), and a metrologist (Matt Hall, National Physical Laboratory). To conclude, insights from imaging networks and the use of consensus papers to improve the standardization and harmonization of qMR imaging were provided (Penny Hubbard Cristinacce, National Cancer Imaging Translational Accelerator (NCITA)).

A.
Vendor's perspective: The session opened with Fabrizio Fasano (F.F.), quoting Zoellner and Porter in stating that 'Translational research is a bidirectional process that involves multidisciplinary integration among basic, clinical, practice, population, and policy-based research. The goal of translational research is to speed up scientific discovery into patient and community benefit'. 9 F.F. described the research agreements that assist provide researchers' access to pulse sequences beyond the standard imaging protocols: a. academia-led, locally tested protocols that use Consumer-to-Producer (C2P) software prototyping b. industry-led protocols that use Work-in-Progress (WIP) software packages which are documented and can be distributed to other researchers and scanners c. WIPs that undergo regulatory assessment are CE marked and released as product.
Each of these steps can contribute to different extents to the quality of the result, with the intent of delivering to the market a reliable product. Reliability is an essential aspect of the "prototype-to-market process". In fact, it minimizes the time spent on later product revisions. Every small modification in hardware or software components translates into a new CE marking process, which is a costly effort, both in time and resources (both technical and legal). The necessity to consider the intellectual property aspects of an implementation, as it moves through initial research and validation, was also discussed.

Conclusions Survey questions
What will and will not work in a clinical workflow?
• For diagnostic imaging biomarkers, identify if the biomarker provides a definitive answer or has to be used as a guide alongside other assessments/biomarkers.

Is an imaging biomarker useful if it does not give a yes/no answer to aid diagnosis?
• Standardized language is important to facilitate clinical adoption.
2. How can we standardize the language we use to aid clinical translation? Should effort be made to develop a consensus paper to standardize terminology to aid clinical translation?
• Understand the practicalities of the workflow, in terms of analysis time and processing power, as they can determine usability.
3. Quantitative MR parameter maps often need to be created away from the scanner console. What is the maximum amount of time after acquisition, if an imaging biomarker is to be integrated into the clinical workflow?
How big of an improvement justifies a change in clinical practice?
• Identify and consult with clinical practice policy makers. • Well-characterized references and to query precision of our measurements.

How do we incentivize transparency and reproducibility?
How do we standardize data acquisition and analysis more effectively?
• Consider the role of both bespoke and commercial phantoms and whether they are attractive to vendors for manufacture.
1. It is known that vendors will find a method less attractive if a method requires a phantom, so when should we use a phantom? Should we use phantoms to standardize data acquisition for every sequence?
• Parameter standardization between vendors is difficult. 2. Do you agree with a goal-orientated approach to quality?
• More transparency and consensus papers are needed.
3. Should we standardize, harmonize or optimize pulse sequences in multi-centre studies?
How do we share data, code, and good practice more effectively?
• Individual institutions and grant-awarding bodies must promote good sharing practices and facilitate code and data sharing between researchers.
1. At what point should we be sharing code? At what point should we be sharing data?
• Good practice is well served through networks, but contributions to shared code need to be acknowledged suitably.
2. How do we balance the need for the subject's privacy against the value of sharing data? i.e., how much can we anonymise without losing valuable information and how do we get consent for making data public?
• Consent tracking is necessary for data sharing and robust anonymization processes required to allow personal data to be removed without losing necessary detail to perform the data analysis.
3. Techniques generally require buy-in from scanner manufacturers to become part of their product in order to change clinical practice. How do we balance the need for researchers to protect the IP to allow this to happen, against the value of sharing code and data publicly?

Conclusions Survey questions
How can we improve quality management of qMR imaging biomarkers?
• Define quality, as quality means different things to different people e.g. vendors, researchers.

Does a Quality Management System (QMS) exist in your place of work?
• The "Quality Management System" should scale with the problem.

Do you use it?
• In-house expertise and assistance within institutions needed to show researchers what to do and how to do it.

How do we incentivize the use of a QMS?
How can we engage with end users to support clinical translation?
• Understand the challenges and bottlenecks.

1.
As an early career researcher, what is the best way to contact clinicians?
• Provide good documentation and continuation.

2.
How do we integrate our MR development with PACs systems?
• Involve end users sooner.

3.
How do we find out if a patient group can tolerate the imaging method?
Note: Survey questions were derived from those suggested by each of the seven roundtable discussion groups.
image contrast is not arbitrary and therefore has physical meaning. This allows variability to be quantified and scanners to be compared and calibrated. Metrics such as length, temperature, concentration, dosage, mass, time, and energy are all traceable to international definitions of SI units, and he suggested that this could be the case for qMR parameters. Using phantoms with traceable materials and structures, the principles of metrology can be used to allow scanners to be benchmarked in an application-specific way. For instance, for T 1 , T 2 , apparent diffusion coefficient, and iron and fat content. M.H. stated that, alongside optimized and consensus-built acquisition methods and open-source and community recommended analysis, a metrological approach to quantification can help us address the challenges of personalized medicine, patient stratification, large and long-term studies, and the integration of artificial intelligence approaches in qMRI. 16

CONCLUSIONS AND NEXT STEPS
Following the talks, participants were allocated into small groups to discuss one of seven questions related to the translation of MR imaging biomarkers, such as 'How do we standardize data acquisition and analysis more effectively?' and 'How can we improve quality management of qMR imaging biomarkers?' (Table 1). Participants were asked to provide three main conclusions and three further questions arising from these group-facilitated discussions and presented these at the subsequent panel discussion. Themes of transparency, standardization of language, acquisition, and analysis, and the need for institutional support of code/data sharing and quality management, ran throughout the conclusions.
The questions produced from these discussions were used to form a survey aimed to capture the opinions and knowledge of the wider MR community (open from 9th September to 17th October 2022). The survey was circulated to the workshop participants and subsequently on the following mailing lists: British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM), MRI-PHYSICS and to gain a clinical perspective, the British Society of Neuroradiologists (BSNR). We received 101 responses with the completion rate varying from 27.7% to 100%. Responses were received from imaging scientists (research (42.6%) and clinical (11.9%)), clinicians (6.9%), others (5%), and 33.7% chose not to disclose. The survey results will be summarized in a future publication and will form the basis of ongoing consensus building. We plan to expand our discussions to include other relevant voices such as, other clinical and preclinical imaging and non-imaging societies, manufacturers of ancillary equipment, National Health Service's National Institute for Health and Care Excellence (NHS NICE), the Medicines and Healthcare products Regulatory Agency (MHRA), the US Food and Drugs Administration (FDA), European Medicines Agency (EMA), and Patient-Public Involvement groups. We also intend to obtain a wider international perspective at ISMRM 2023 by surveying attendees and through the new ISMRM Standardized Measures and Benchmarks committee.

AFFILIATIONS
1 Quantitative Biomedical Imaging Laboratory, Division of Cancer