Periodic Reporting for period 1 - ROCHESTER (Quantification of Free and Bound Water Concentrations in Human Cortical Bone Employing Hybrid Hard-tissue MRI: Towards Comprehensive Osteoporosis Assessment)
Okres sprawozdawczy: 2021-05-01 do 2023-04-30
1. Literature review on the cortical bone water:
• Extensive studies were carried out to understand role of MRI to detect cortical bone water in the assessment of cortical bone quality.
2. Novel methodologies to acquire cortical bone MRI:
• UTE sequences at 7T preclinical MRI (Bruker) were implemented and acquired:
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3. Verification of the novel imaging method:
• Quantification was carried out to show if the new imaging method enables constructive signal for the measurement:
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• Analysis of the new images were developed using new generation of deep learning techniques. Results are planned in two different categories:
i. T2-map (Variable TEs); Finding notion of the three proton pools,
ii. T1-map (Variable FAs); Finding notion of porosity-related signal changes / Relaxometry.
• Two different estimation schemes must are finalized for accurate parameter mapping
i. Mutual estimation of the three proton pool from 7T data (ways to consider minerals with MRI),
ii. QSM / phase quantification and mineralization data from uCT (uCT data to be acquired).
4. Clinical biomarker achieved:
• Multi sample acquisition and related data analysis to be carried out.
• main scientific and/or technological achievements:
• Results for data acquisition shows UTE-MRI is capable to move to the extent of all the proton pools ex-vivo,
• Progressive results on deep-learning analysis establishes a new line to estimate different cortical pool protons with enough accuracy for further studies,
• main innovation outputs (if applicable):
• Pushing the imaging technology to the level of mineral detection and quantification using MRI is novel and innovative, especially when targeting patient imaging in-vivo (to be completed in my next grants),
• Employing novel deep-learning techniques based on physics information and knowledge is innovative in this field.
• contribution to the state of the art
• Deep learning based analysis for cortical bone water quantification with simultaneous multi-compartmental imaging, detection and estimation.
• scientific and/or technological quality of the results
• Results show how the scientific concepts are neatly marched with the technological capabilities of the MRI machines used; meaning scientific predictions of the MR acquisitions for compartmental study and quantification are to be properly predicted by the actual imaging data and AI-based analysis.
• Attending a prestigious Horizon-EU grant has positive influence on my career. This grant made me the opportunity to extend academic and innovation relationships with great scientists of the field and UK/EU organizations. Next step is to fund a proposal to extend this work as advised above (preceded by pre-application support fund).
- Does the work carried out enhance innovation capacity, create new market opportunities, strengthen competitiveness and growth of companies, address issues related to climate change or the environment, address industrial and/or societal needs at regional level or bring other important benefits for society?
• Work carried out in this project is an initial phase of accurate human bone quality assessment and management systems, superior to what DXA offers to the healthcare in different ways: non-ionizing modality with excellent coverage to biological information embedded within the (human) cortical bone.
- Give information on the relevant innovation activities carried out (prototypes, testing activities, standards, clinical trials) and/or new products, services, reference materials, processes or methods (to be) launched to the market, if any.
• Finalized algorithms extracted from this work is the animal study phase of the laboratory-phase prototype of the system mentioned in the previous bullet.
- Does the work carried out contribute towards European policy objectives and strategies and/or have an impact on policy making?
• Techniques and methods proposed in this research project leads to new diagnostic medical devices with better efficacy and lower harm to the human body.
- Please identify potential users of the project results. Has there been suitable communication with interested parties?
• Bone epidemiologists, MSK Radiologists, (MR)Imaging Scientists, AI experts.