Exploring scenarios for implementing fast quantitative MRI
Purpose: MRI waitlists and discomfort from long scanning sessions are significant problems in clinical radiology. Novel multiparametric quantitative MRI techniques (qMRI) for radiological imaging enable acquisition of full-brain data within minutes to address these problems. While technical and clin...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | European Journal of Radiology Open |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352047725000255 |
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| author | Susan V. van Hees Martin B. Schilder Alexandra Keyser Alessandro Sbrizzi Jordi P.D. Kleinloog Wouter P.C. Boon |
| author_facet | Susan V. van Hees Martin B. Schilder Alexandra Keyser Alessandro Sbrizzi Jordi P.D. Kleinloog Wouter P.C. Boon |
| author_sort | Susan V. van Hees |
| collection | DOAJ |
| description | Purpose: MRI waitlists and discomfort from long scanning sessions are significant problems in clinical radiology. Novel multiparametric quantitative MRI techniques (qMRI) for radiological imaging enable acquisition of full-brain data within minutes to address these problems. While technical and clinical work is advancing, there has been limited research on implementing fast qMRI. This paper aims to identify implementation factors and scenarios within a healthcare setting facing rising demand, staff shortages, and limited capacity of MRI systems. Methods: The paper reports on data collected using qualitative methods: 1) Interviews and guided discussions, 2) co-creation workshop. Both steps involved key representatives with various backgrounds and expertise, such as radiologists, lab technicians, insurers, and patients. Results: Workshop participants visualised current and future workflows, which helped articulate implementation factors for qMRI. Supply and demand in MRI will change with increased accessibility and shortened timeslots. Three implementation scenarios came forward: 1) stable deployment, 2) extension to conducting more complex diagnostic exams, and 3) (more) preventive screening. Discussion and conclusions: This paper demonstrates challenges, solutions, and opportunities for successfully implementing fast qMRI in the clinic, and five lessons for adoption in the clinic: 1) importance of balancing perfectionism with confidence when it comes to clinicians’ expectations, 2) good use of Artificial Intelligence, 3) considering a learning curve associated with implementation, 4) regarding competing technologies, and 5) including patients’ experiences. Future research should investigate salient issues regarding future of AI in radiology and for moving imaging practices out of the clinic. |
| format | Article |
| id | doaj-art-7e6fc9af8fa548c2aff9f51228051ac8 |
| institution | OA Journals |
| issn | 2352-0477 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | European Journal of Radiology Open |
| spelling | doaj-art-7e6fc9af8fa548c2aff9f51228051ac82025-08-20T02:28:16ZengElsevierEuropean Journal of Radiology Open2352-04772025-06-011410065810.1016/j.ejro.2025.100658Exploring scenarios for implementing fast quantitative MRISusan V. van Hees0Martin B. Schilder1Alexandra Keyser2Alessandro Sbrizzi3Jordi P.D. Kleinloog4Wouter P.C. Boon5Copernicus Institute of Sustainable Development, Innovation Studies Section, Utrecht University, the Netherlands; Correspondence to: Princetonlaan 8a, P.O. Box 80115, Utrecht 3584 CB, the Netherlands.Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the NetherlandsCopernicus Institute of Sustainable Development, Innovation Studies Section, Utrecht University, the NetherlandsComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the NetherlandsComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the NetherlandsCopernicus Institute of Sustainable Development, Innovation Studies Section, Utrecht University, the NetherlandsPurpose: MRI waitlists and discomfort from long scanning sessions are significant problems in clinical radiology. Novel multiparametric quantitative MRI techniques (qMRI) for radiological imaging enable acquisition of full-brain data within minutes to address these problems. While technical and clinical work is advancing, there has been limited research on implementing fast qMRI. This paper aims to identify implementation factors and scenarios within a healthcare setting facing rising demand, staff shortages, and limited capacity of MRI systems. Methods: The paper reports on data collected using qualitative methods: 1) Interviews and guided discussions, 2) co-creation workshop. Both steps involved key representatives with various backgrounds and expertise, such as radiologists, lab technicians, insurers, and patients. Results: Workshop participants visualised current and future workflows, which helped articulate implementation factors for qMRI. Supply and demand in MRI will change with increased accessibility and shortened timeslots. Three implementation scenarios came forward: 1) stable deployment, 2) extension to conducting more complex diagnostic exams, and 3) (more) preventive screening. Discussion and conclusions: This paper demonstrates challenges, solutions, and opportunities for successfully implementing fast qMRI in the clinic, and five lessons for adoption in the clinic: 1) importance of balancing perfectionism with confidence when it comes to clinicians’ expectations, 2) good use of Artificial Intelligence, 3) considering a learning curve associated with implementation, 4) regarding competing technologies, and 5) including patients’ experiences. Future research should investigate salient issues regarding future of AI in radiology and for moving imaging practices out of the clinic.http://www.sciencedirect.com/science/article/pii/S2352047725000255ImplementationFast quantitative MRIRelaxometryWorkflowsQualitative research |
| spellingShingle | Susan V. van Hees Martin B. Schilder Alexandra Keyser Alessandro Sbrizzi Jordi P.D. Kleinloog Wouter P.C. Boon Exploring scenarios for implementing fast quantitative MRI European Journal of Radiology Open Implementation Fast quantitative MRI Relaxometry Workflows Qualitative research |
| title | Exploring scenarios for implementing fast quantitative MRI |
| title_full | Exploring scenarios for implementing fast quantitative MRI |
| title_fullStr | Exploring scenarios for implementing fast quantitative MRI |
| title_full_unstemmed | Exploring scenarios for implementing fast quantitative MRI |
| title_short | Exploring scenarios for implementing fast quantitative MRI |
| title_sort | exploring scenarios for implementing fast quantitative mri |
| topic | Implementation Fast quantitative MRI Relaxometry Workflows Qualitative research |
| url | http://www.sciencedirect.com/science/article/pii/S2352047725000255 |
| work_keys_str_mv | AT susanvvanhees exploringscenariosforimplementingfastquantitativemri AT martinbschilder exploringscenariosforimplementingfastquantitativemri AT alexandrakeyser exploringscenariosforimplementingfastquantitativemri AT alessandrosbrizzi exploringscenariosforimplementingfastquantitativemri AT jordipdkleinloog exploringscenariosforimplementingfastquantitativemri AT wouterpcboon exploringscenariosforimplementingfastquantitativemri |