SAB & PARTNERS

Name and Current Position

Professor Neal K. Bangerter; Chair of Electrical and Computer Engineering, Boise State University, USA; Visiting Professor, Department of Bioengineering, Imperial College London, UK.

Expertise Summary

Prof. Bangerter is recognized internationally for his seminal work in magnetic resonance imaging (MRI) and artificial intelligence (AI), with a strong focus on musculoskeletal imaging applications. His focus has been on the development of advanced MRI techniques for the imaging of joints, ultra-high field MRI, and the development of novel quantitative MRI pulse sequences for cartilage imaging. He has contributed to large-scale data-driven health research, including the UK Biobank neuroimaging initiative. His research spans both methodological innovation and translational applications in quantitative musculoskeletal imaging, neuroimaging, and broader healthcare applications.

Education & Training

• B.A. Physics (Honors, Phi Beta Kappa), University of California, Berkeley, USA (1995)
• M.S. Electrical Engineering, Stanford University, USA (2001)
• Ph.D. Electrical Engineering, Stanford University, USA (2004)

Key Academic Appointments

• Associate Professor of Electrical & Computer Engineering, Brigham Young University, USA (2008 – 2018)
• Visiting Scholar, University of Oxford, UK (2013 – 2014)
• Adjunct Associate Professor of Radiology, University of Utah, USA (2008 – present)
• Associate Professor of Magnetic Resonance Physics, Department of Bioengineering, Imperial College London, UK (2018 – 2023)
• Visiting Professor of Magnetic Resonance Physics, Department of Bioengineering,
• Professor and Department Chair, Electrical & Computer Engineering, Boise State University, USA (2023 – present)

Scientific Leadership & Honors

• David C. Evans Chair in Electrical & Computer Engineering, Brigham Young University (2012 – 2015)
• Founder and Director, BYU Medical Imaging Research Laboratory
• Instrumental contributor to the UK Biobank Neuroimaging Project
• Outstanding Faculty Teaching Awards, Brigham Young University (2013–2015)

Role within Chondrometrics

Prof. Bangerter provides strategic expertise in MRI methodology, quantitative imaging, and the application of AI to musculoskeletal clinical research applications. His experience in ultra-high field MRI, pulse sequence development, and large-scale imaging data analysis supports the advancement of Chondrometric’s high-precision imaging biomarkers and analytical methodologies.

Selected Publications or Output

• Eckstein F, Bangerter N, Wirth W: Magnetic Resonance Imaging (MRI) transverse relaxation time (T2) for non-invasive assessment of cartilage composition -from method development to automated processing of large clinical cohorts. Paracelsus Proceedings of Experimental Medicine 2026 Jan 15 https://ppexmed.com/articles/000642.html
• Lally PJ et al.. Steady-state free precession for T2* relaxometry: All echoes in every readout with k-space aliasing. Magn Reson Med. 2025 Oct;94(4):1563-1576. https://pubmed.ncbi.nlm.nih.gov/40457600/
• Huang J, et al. Data- and physics-driven deep learning based reconstruction for fast MRI: Fundamentals and methodologies. IEEE Rev Biomed Eng. 2025;18:152-171. https://pubmed.ncbi.nlm.nih.gov/39437302/
• Bangerter NK et al. Quantitative techniques for musculoskeletal MRI at 7 Tesla. Quant Imaging Med Surg. 2016 Dec;6(6):715-730. https://pubmed.ncbi.nlm.nih.gov/28090448/
• Miller KL et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci. 2016 Nov;19(11):1523-1536. https://pubmed.ncbi.nlm.nih.gov/27643430/

Other

• Key roles in industry, including McKinsey & Company, Microsoft
• Vice President of product management at Reactrix.
• Co-founder of a data visualization company
• Contribution to the development of AI strategies in healthcare through consulting and executive education.

Name and Current Position
Ass. Prof. Rupsa Bhattacharjee, PhD; Department of Medical Science & Technology (DMST) at IIT Madras, Chennai, India

Expertise Summary

Prof. Bhattacharjee is a Biomedical Engineer with ample experience in MRI acquisition and post-processing and the used of computational methods. A recent focus has been the application of machine- and deep-learning technology to model development for synthetic imaging, grading, image assessment and analysis, anomaly detection, and segmentation. She has specialized in musculoskeletal MRI and osteoarthritis research, exploring the technical feasibility of utilizing new-generation MRI scanners at different field strengths.

Education & Training

• Bachelor (B.Tech) in Electronics & Instrumentation Engineering, DETS, University of Kalyani, India (2007-2011)
• Masters (M.E.) in Biomedical Engineering, SBSE, Jadavpur University, India (2011 – 2013)
• PhD. in Biomedical Engineering, CBME, Indian Institute of Technology (IIT) New Delhi, India (2016 – 2021)

Key Academic & Other Appointments

• MRI Clinical Application Specialist, Philips Health Systems, Gurugram, India (2013-2021)
• Associate Specialist, Radiology, University of California (UCSF), San Francisco, US (2021-2025)
• Assistant Professor at the DMST, IITM, Chennai, India (2025-)

Scientific Leadership & Honors

• Travel Stipend Awards to International Society for Magnetic Resonance in Medicine (ISMRM) Conferences (2018 & 2019)
• Best MRI Clinical Application Specialist: Silver Medal, Philipps (2019)
• Multiple “Summa and magna cum laude awards” at ISMRM (2019, 2023 & 2024)
• Junior Fellow Award at ISMRM (2024)
• Bruce Hasegawa Award at UCSF (2024)
• Invited speaker at the International Workshop of Osteoarthritis Imaging, Magdalene College, Cambridge, UK (2025)

Role within Chondrometrics

Rupsa Bhattacharjee contributes her profound expertise in MRI acquisition and parameter optimization, pulse sequence design, mathematical algorithm development, MRI reconstruction and post-processing, clinical correlation, computational bioscience, radiomics, and machine and deep learning technology. She further advises Chondrometrics on musculoskeletal imaging biomarkers, such as bone shape, muscle health, T1rho and T2 relaxation, and new contrast mechanisms.

Selected Publications or Output

• Bhattacharjee R, et al. Cartilage compositional T2 patterns in subjects at risk of polyarticular OA: Technical feasibility at 0.55 T, clinical and functional associations. NMR in Biomedicine 38:e70164 (2025)
• Bhattacharjee R, et al. The relationships between patellofemoral bone remodeling, cartilage composition, and vertical loading rate: PET/MRI in isolated patellofemoral osteoarthritis. Osteoarthritis Cartilage 32(12):1591-1600 (2024) https://pubmed.ncbi.nlm.nih.gov/39277026/
• Bhattacharjee R, et al. Effects of T1p characteristics of load-bearing hip cartilage on bilateral knee patellar cartilage subregions: Subjects with none to moderate radiographic hip osteoarthritis. J Magn Reson Imaging 60(1):186-202 (2023). https://pubmed.ncbi.nlm.nih.gov/37702305/  
• Bhattacharjee R, et al. Feasibility of translating 3.0T-trained deep-learning segmentation models out-of-the-box on low-field MRI 0.55T knee-MRI of healthy controls. [Arxiv] https://doi.org/10.48550/arXiv.2310.17152 (2023)
• Bhattacharjee R, et al. Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation. Neuroradiology. 64(9):1801-1818 (2022) https://pubmed.ncbi.nlm.nih.gov/35435463/

Other

• Trainee at ISMRM (2016-)
• Siemens Seed Grant for three pilot projects at UCSF (2022)
• ISMRM Study Group Memberships on various topics
• ISMRM Abstract Reviewer 2024 & 2025

Name and Current Position

Prof. Mikael Boesen, MD, PhD; Professor of Radiology at Copenhagen University; Head of Imaging Research and Senior Consultant, Musculoskeletal Imaging at Bispebjerg and Frederiksberg Hospital, and co-founder and Chief Scientific officer of the Radiological AI test center (RAIT.dk) in Copenhagen, Denmark

Expertise Summary

Prof. Boesen is an internationally recognized expert in musculoskeletal (MSK) radiology, with a focus on imaging of inflammatory and degenerative joint disease. His work has significantly contributed to advanced quantification of synovitis and bone marrow lesions using dynamic contrast-enhanced MRI (DCE-MRI) in the context of osteoarthritis and rheumatoid arthritis clinical trials. He is an expert in AI-driven diagnostics within multiple diagnostic areas through his work in RAIT.dk. Mikael Boesen has 20 years of experience in clinical trial design and imaging protocol standardization for international pharmaceutical and biotech companies.

Education & Training

• MD in Medicine, University of Copenhagen, Denmark (1999)
• PhD on MRI of articular tissues, following intraarticular treatment in arthritis. Parker Institute and Medical Faculty, Aalborg University, Denmark (2004-2008)
• Specialist Training: Senior Consultant in Musculoskeletal Radiology Rigshospitalet and Bispebjerghospital Copenhagen Denmark (2008-2013)

Key Academic Appointments

• Professor of Radiology, Copenhagen University, Denmark (2017–present)
• Associate Professor of Radiology, Copenhagen University, Denmark (2015–2017)
• Head of Imaging Research, Parker Institute, Denmark (2008-2017)

Scientific Leadership & Honors

• Board Member, Clinical Academic Group (CAG) in Osteoarthritis (ROAD.dk), CAG-Shift, CAG Aging and CAG MUSKOS
• SAB Member: “Radiobotics”, “Teal Medical”, “Sanos Clinics A/S”.
• Project Lead: Clinical Imaging Consortium (CLIC), supported by the Innovation Fund Denmark, and X-AID supported by Eurostar
• Chairman, Clinical and SAB, Image Analysis Group (IAG), London, UK (2010–)
• Co–founder, Chairman & CSO, Radiological AI Test Centre (RAIT.dk), (2021–)

Role within Chondrometrics

Prof. Boesen provides strategic guidance on the integration of imaging biomarkers and AI solutions for MSK research, supporting the company’s mission to advance the validation and clinical application of quantitative imaging in osteoarthritis.

Selected Publications or Output

• Boesen M, et al. Knee pain and inflammation in the infrapatellar fat pad estimated by conventional and dynamic contrast-enhanced magnetic resonance imaging in obese patients with osteoarthritis: a cross-sectional study, Osteoarthritis Cartilage 2014 Jul;22(7):933-40 https://pubmed.ncbi.nlm.nih.gov/24821663/
• Boesen M, et al. The impact of a significant weight loss on inflammation assessed on DCE-MRI and static MRI in knee osteoarthritis: a prospective cohort study Osteoarthritis Cartilage, 2020 Jun;28(6):766-773. https://pubmed.ncbi.nlm.nih.gov/32165240/
• Boesen M, et al. Use of DCE-MRI in arthritis in the appendicular skeleton: a narrative review Skeletal Radiology 2025 Nov;54(11):2457-2479. https://pubmed.ncbi.nlm.nih.gov/40495074/

Other

• Total No. of publications: 220; Total No. of citations: 6300+; H-Index: 44 (Google Scholar); Google Scholar Link: Mikael Boesen Profile
• PhD supervision and co-supervision: 27; post-doctoral supervision: 6
• Lead investigator of Eurostar X-AID (2019), the Danish Government-funded SmartChest/AIKOA signature project (2020), Innovation foundation Denmark projects CLIC-project.org (2022) and CLIC-BAIT (2026)
• Partner at the European IHI Probe project (2026)

Name and Current Position

Prof. Rainer Burgkart, MD; former Director of Research and Education, Clinic for Orthopaedics and Sportorthopaedics & Associate Professor, TUM, Munich, Germany.

Expertise Summary

Prof. Burgkart is an orthopaedic surgeon and internationally recognized researcher at the TUM Munich, with more than three decades of experience at the intersection of orthopaedic surgery, musculoskeletal biomechanics, and quantitative imaging. His research spans MRI- and CT-based assessment of cartilage, computer-assisted surgery, robotics, biofunctional implant surfaces, tissue engineering, and AI-based image analysis. He has made seminal contributions to the development of advanced simulation and training systems in medicine. His interdisciplinary work bridges basic science, clinical application, and medical technology, with strong links to biology, engineering, informatics.

Education & Training

• Study of Medicine at the University of Essen, Münster and University Clinic Dortmund. International clinical rotations in New Zealand and Switzerland (1982–1988)
• Doctoral thesis (Dr. med., M.D.) at the University of Münster (1989)
• Resident in Orthopaedic Surgery and Traumatology, KRdI, TUM, Munich (1989–1991 & 1992–1997)
• Research Fellowship, Orthopaedic Clinic, Duke University, Durham, NC, USA (1991–1992 & 1998-1999)
• Habilitation (TUM Munich) on 3D surgical simulation and navigation techniques (2007)

Key Academic Appointments

• Senior Attending Physician, Clinic for Orthopaedics and Sportorthopaedics, KRdI, TUM (1997-2025)
• Director of Research and Education at the above institution (2000-2025)
• Associate Professor at the above institution (2007-)

Scientific Leadership & Honors

• Göran Selvik Award, European Orthopaedic Research Society (EORS), for advanced 3D volumetry methods in MRI-based cartilage assessment in osteoarthritis (1999)
• Winner, Ideenwettbewerb, German Federal Ministry of Education and Research (BMBF), for „VR Training Simulator for Orthopaedics“ (2000)
• ISPO Academic Challenge Award for the innovative product idea „Activated phantom limbs for the representation of body movements“ (2003)
• Karl-Heinz-Höhne Prize MedVis-Award for „Innovative Visualizing of Implant Planning in Orthopedics“ (2010)
• EU Robotics Technology Transfer Award  (2nd place), for „SIMone: Robotic Birth Training Simulator“ (2011)
• Founding Member, „Network for Regenerative Medicine“ (2005)
• Founding Member, „Network for Muskuloskelettal Biomechanics“ (2006)
• Board Member, DFG-Excellence-Initiative, TUM International Graduate School of Science and Engineering (IGSSE) (2006 – 2023)
• Board Member, Deutscher DIN Normenausschuss DIN NA 027-02-15 AA „Endoprothetik und Osteosynthese“ (2007 – 2025)

Role within Chondrometrics

Prof. Burgkart contributes his deep expertise in musculoskeletal biomechanics, quantitative MRI-based articular tissue imaging, and computer-assisted orthopaedic surgery. Drawing on his long-standing expertiese in OA imaging biomarkers, AI-based image analysis, and implant science, he supports the company’s mission to develop and validate high-precision imaging endpoints for clinical research applications.

Selected Publications or Output

• Guilak F et al. Viscoelastic properties of the cell nucleus. Biochem Biophys Res Commun. 2000 Mar 24;269(3):781-6.  https://pubmed.ncbi.nlm.nih.gov/10720492/
• Burgkart R., et al.: Feasibility of T and Z scores from magnetic resonance imaging data for quantification of cartilage loss in osteoarthritis. Arthritis Rheum. 2003 Oct;48(10):2829-35. https://pubmed.ncbi.nlm.nih.gov/14558088/
•  Rossetti L, et al.: The microstructure and micromechanics of the tendon-bone insertion Nat Mater 2017 Jun;16(6):664-670. https://pubmed.ncbi.nlm.nih.gov/28250445/
• Theruvath AJ, et al.: Tracking stem cell implants in cartilage defects of minipigs by using ferumoxytol-enhanced MRI. Radiology 2019 Jul;292(1):129-137 https://pubmed.ncbi.nlm.nih.gov/31063081/

Other

• 26 granted patents on multimodal training simulators for medicine, x-ray imaging and computer-assisted implant positioning devices
• Supervision of 91 dissertations and 95 Master-/Bachelor-/Semester theses
• 254 ISI-cited publications,  6,047 total citations in peer-reviewed journals, h-index: 42

Name and Current Position

Professor Akshay S. Chaudhari, Ph.D: Associate, Radiology and Biomedical Data Science; Group Leader, Machine Intelligence in Medical Imaging Laboratory; Interim Division Chief, Integrative Biomedical Imaging Informatics at Stanford (Radiology); Co-Director Stanford Radiology Artificial Intelligence Development & Evaluation Laboratory: Associate Director Stanford Center for Artificial Intelligence in Medicine & Imaging, Stanford University School of Medicine, Standford, USA

Expertise Summary

Prof. Chaudhari is an internationally recognized expert in artificial intelligence (AI) and medical imaging, with a focus in musculoskeletal applications and particularly osteoarthritis. His work spans accelerated and quantitative MRI, image reconstruction, automated tissue segmentation, relaxometry, opportunistic CT analysis, and data-efficient machine learning. He combines methodological innovation with clinical translation, and has contributed extensively to AI-enabled imaging biomarkers for musculoskeletal research. More recently he has expancded his work to oncology applications and to the use of large language models in medical (radiology) practice.

Education & Training

• B.S. in Bioengineering Science (cum laude Honors), University of California, San Diego, USA (2012)
• M.S. in Bioengineering, Stanford University, USA (2014)
• Ph.D. in Bioengineering, Stanford University, USA (2017)

Key Academic Appointments

• Research Scientist / Postdoctoral Scholar,Radiology, Stanford Univ., USA (2017 – 2019)
• Assistant Professor of Radiology and Biomedical Data Science, Stanford Univ., USA (2020 – 2024)
• Interim Division Chief, Integrative Biomedical Imaging Informatics at Stanford (IBIIS), Department of Radiology, Stanford Univ., USA (2025 – present)
• Associate Professor of Biomedical Data Science (joint), Stanford University, USA (2026 – present)

Scientific Leadership & Honors

• Best Young Investigator Award /Abstract –International Workshop on Osteoarthritis Imaging (IWOAI) (2015, 2017, 2018 and 2019)
• Multiple „Summa Cum Laude Awards” at ISMRM Conferences (2017-2024
• W. S. Moore Best Young Investigator Award, ISMRM (2019)
• Best Paper Finalist – Medical Imaging with Deep Learning Conference (2021)
• Best Paper Award, Medical Imaging with Deep Learning Conference (2022)
• Hearst Health Prize for Data Science (2023)
• Amazon Research Award (2023)
• Microsoft-OpenAI Accelerate Foundation Models Academic Research Award (2023)
• American Roentgen Ray Society Silver Medal (2024)
• Junior Fellow Award, ISMRM (2025)
• Most Cited Researcher in 2023 – Magnetic Resonance in Medicine Journal (2025)

Role within Chondrometrics

Prof. Chaudhari provides strategic expertise in quantitative MRI, AI-driven image analysis, and musculoskeletal imaging biomarkers. His experience in rapid knee MRI, cartilage morphometry and relaxometry, automated segmentation, and translational imaging research. He supports Chondrometrics in advancing precise, scalable biomarkers and analytical methods for osteoarthritis clinical trials and related clinical research applications.

Selected Publications or Output

• Chaudhari AS et al. Five-minute knee MRI for simultaneous morphometry and T2 relaxometry of cartilage and meniscus and for semiquantitative radiological assessment using double-echo in steady-state at 3T. J Magn Reson Imaging. 2018 May;47(5):1328-1341. https://pubmed.ncbi.nlm.nih.gov/29090500/
• Chaudhari AS et al. Rapid knee MRI acquisition and analysis techniques for imaging  osteoarthritis. J Magn Reson Imaging 2020 Nov;52(5):1321-1339. https://pubmed.ncbi.nlm.nih.gov/31755191/
• Wirth W, et al. Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data from the osteoarthritis initiative healthy reference cohort. MAGMA. 2021 Jun;34(3):337-354. https://pubmed.ncbi.nlm.nih.gov/33025284/
• Wang YJ, Chaudhari AS. AI-driven smart patient retrieval for precision oncology. Nat Rev Cancer. 2026 Mar 26. https://pubmed.ncbi.nlm.nih.gov/41888294/
• Blankemeier L, et al. Merlin: a computed tomography vision-language foundation model and dataset. Nature. 2026 Mar 4. https://pubmed.ncbi.nlm.nih.gov/41781626/

Other

• Visiting Scholar, Institute of Biomedizinische Technik, ETH Zurich, Switzerland (2015)
• Consulting Deep Learning Scientist, Subtle Medical, Menlo Park, California, USA (2018 – 2022)
• Scientific Advisory Board Member, Brain Key, Palo Alto, California, USA (2018 – present)
• Co-Founder, Cognita, Menlo Park, California, USA (2024 – present)

Name and Current Position

Jamie E. Collins, PhD; Associate Professor of Orthopedic Surgery at Harvard Medical School, Boston USA, Biostatistician and Associate Director, Orthopedic and Arthritis Center for Outcomes Research, Brigham and Women’s Hospital, Boston USA

Expertise Summary

Dr. Jamie E. Collins is an internationally recognized biostatistician specializing in osteoarthritis (OA) clinical trials, imaging biomarkers, and longitudinal disease modeling. Her work focuses on the development and validation of structural and biochemical biomarkers of OA progression, statistical methods for correlated and high-dimensional imaging data, and design and analysis of randomized controlled trials. She has played a central role in advancing MRI-based endpoints and prognostic enrichment strategies to support disease-modifying OA drug development.

Education & Training

• BA Mathematics/Statistics, Boston University, Boston, USA (2005)
• MA Mathematics/Statistics, Boston University, Boston, USA (2005)
• PhD Biostatistics, Boston University School of Public Health, Boston, USA (2014)

Key Academic Appointments

• Associate Director, Orthopedic and Arthritis Center for Outcomes Research (OrACORe), Brigham and Women’s Hospital, Boston, USA (2023–present)
• Associate Professor of Orthopedic Surgery, Harvard Medical School, Boston, USA (2022–present)
• Assistant Professor of Orthopedic Surgery, Harvard Medical School, Boston, USA (2014–2022)

Scientific Leadership & Honors

• Director, Statistical Consulting Unit, Department of Orthopedic Surgery, Brigham and Women’s Hospital, Boston, USA
• Director, Data Management and Analysis Core, Brigham Coordinating Center (BRICC), Arthritis Foundation OA Clinical Trials Network, USA
• Osteoarthritis Research Society International (OARSI) Rising Star Clinical Research Award (2021)

Role within Chondrometrics

At Chondrometrics, Dr. Collins provides strategic guidance on statistical methodology for MRI-based endpoints, trial design, enrichment strategies, and regulatory alignment of structural imaging biomarkers in osteoarthritis. She supports the company’s mission to advance quantitative imaging solutions that enhance the efficiency and interpretability of disease-modifying OA clinical trials.

Selected Publications or Output

• Collins JE et al. Approaches to optimize analyses of multidimensional ordinal MRI data in osteoarthritis research: a perspective. Osteoarthritis and Cartilage Open. 2024 Jun 1;6(2):100465. https://pubmed.ncbi.nlm.nih.gov/38601258/
• Katz JN, Collins JE, et al. A randomized trial of physical therapy for meniscal tear and knee pain. New England Journal of Medicine. 2025 Oct 30;393(17):1694-703. https://pubmed.ncbi.nlm.nih.gov/41160820/
• Collins JE et al. Five-year structural changes in patients with meniscal tear and osteoarthritis: Data from an RCT of arthroscopic partial meniscectomy vs. physical therapy. Arthritis Rheumatol. 2022 Aug;74(8):1333-1342. https://pubmed.ncbi.nlm.nih.gov/35245416/
• Collins JE, et al. Magnetic Resonance Imaging biomarkers of knee osteoarthritis progression. ACR Open Rheumatol. 7(9): e70085 (2025) https://pubmed.ncbi.nlm.nih.gov/40977252/
• Eckstein F, Stamm T, Collins JE. Which endpoints should be applied in interventional trials? -: From single uni-dimensional assessment tailored to a drug’s mechanism of action to multi-component measures and multi-domain composites. Osteoarthr Imaging. 5(1):100256 (2025) https://pubmed.ncbi.nlm.nih.gov/40160440/

Other

• H-Index = 44

Name and Current Position

Priv. Doz. Jana Eder, PhD; Principal Investigator at Medical University Vienna, Austria.

Expertise Summary

Dr. Jana Eder is an Artifcial Intelligence (AI) scientist working at the interface of artificial intelligence and clinical research. Her work focuses on learning from limited labeled and heterogeneous medical data, including quantitative imaging. She develops robust and clinically relevant AI methods for research studies and clinical trials.

Education & Training

• PhD, Paracelsus Medical University (2018)
• Privat Dozent, Paracelsus Medical University (2023)

Key Academic Appointments

• Marie Curie Fellow, Early-Stage Researcher (2025-2018)
• Visiting PhD / Postdoctoral Researcher, ETH Zurich, Switzerland (2017/2018)
• Data Scientist, Chondrometrics GmbH, Freilassing, Germany (2018-2019)
• Senior Data Scientist, Siemens Research, Vienna, Austria (2022)
• Senior Key Expert for AI, Siemens Research, Vienna, Austria (2022-2025)
• Principal Investigator, AI Research, Medical University Vienna, Austria (2025-)

Scientific Leadership & Honors

• Best Paper Award – 7th IEEE International Conference on Fog and Edge Computing, IEEE Computing Society (2023)
• Paracelsus Science Award (2018/ 2019)
• Young Scientist Scholarship for a Research stay at ETH Zurich (2018)
• Member of the Year Award, Marie Curie Alumni Association Austria (2017)
• DAdorW Future Price, German Academy of Osteological and Rheumatological Sciences (2016)
• Marie Curie Doctoral Fellowship (2015)
• DAAD Promos Scholarship for a Research Semester Abroad, DAAD German Academic Exchange Service (2014)
• GIZ Scholarship for a Semester Abroad, German Federal Ministry of Education and Research and German Society for International Collaborations (2012)

Role within Chondrometrics

Dr. Jana Eder provides strategic leadership in artificial intelligence for healthcare, focusing on data-efficient learning from limited and heterogeneous datasets. She advances methods such as weak supervision and multi-source learning. She works on their rigorous clinical validation, to enable robust, clinically meaningful endpoints for research and clinical trials.

Selected Publications or Output

• Wirth, W., Eder, J. et al. Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model. Skeletal Radiol 2025 Mar;54(3):571-584. https://pubmed.ncbi.nlm.nih.gov/39230576/
• Eder, J., et al. Method and system for operating a technical device with a model based on artificial intelligence. U.S. Patent Application US20240272632A1. European Patent Application EP4414795A1 –
• Kemnitz, J. et al. Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteo-arthritic knee pain. Magn Reson Mater Phy (MAGMA) 2020 Aug;33(4):483-493. https://pubmed.ncbi.nlm.nih.gov/31872357/

Other

• Scientific Advisor, Women in AI, Austria (since 2018)
• Co-Author of the Handbook of Data Science and AI

Name and Current Position

Assoc. Prof. Tazio Maleitzke, Orthopaedic Surgeon, Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre (Denmark)

Expertise Summary

Prof. Maleitzke is clinician scientist and translational researcher in orthopaedic surgery. His work focuses on inflammation control in joint injuries. Specifically, he investigated the role of glucocorticoid-altering enzymes, Calca-derived peptides, subsets from the stromal vascular fraction, and placenta-derived cell therapies in cartilage pathology and repair. He has been the lead of clinical and preclinical trials, testing advanced therapies for joint restoration, including cell-based and cell-free treatments, genicular arterial embolization, and evidence-based platelet-rich plasma (PRP) therapies. He is a co-investigator in the ILOBONE (DFG -funded) and PROTO (EU-funded) clinical trials. With a focus on translational research, he aims to design trials that have a notable impact for patients, and to test innovative and sometimes unconventional therapies to drive clinical progress

Education & Training

• Research Scholarship, ANZAC Research Institute, University of Sydney, Australia (2012-2013)
• Medical Degree, Charité – Universitätsmedizin Berlin, Germany (2016)
• Doctoral thesis, Charité – Universitätsmedizin Berlin, Germany & University of Sydney, Australia (2013-2017)
• Residency in Orthopaedic Surgery and Board Certification, Charité – Universitätsmedizin Berlin, Germany (2016-2023)
• Habilitation: Charité – Universitätsmedizin Berlin, Germany (2024)

Key Academic Appointments

• BIH Junior Clinician Scientist Fellow, Charité – Universitätsmedizin Berlin, Germany (2018 – 2020)
• BIH Clinician Scientist Fellow, Charité – Universitätsmedizin Berlin, Germany (2021 – 2023)
• Head of Trauma Orthopaedic Research Copenhagen Hvidovre (TORCH), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Denmark (2024-)
• Clinical Associate Professor, Department of Clinical Medicine, University of Copenhagen, Denmark (2024-)
• Permanent Visiting Associate Professor (10%), Julius Wolff Institute, Charité – Universitätsmedizin Berlin, Germany (2024-)
• Chief Medical Officer (CMO), Hazel Therapeutics, Danish Technical University, Copenhagen, Denmark (2024-)

Scientific Leadership & Honors

• 1st Prize Oral Presentation Award, Scientific Young Forum, Berlin Surgical Society (2020)
• EFORT Free Paper Award Trauma – SILVER (2021)
• ESCEO-IOF Young Investigator Award (2023)
• EFORT Best Poster, Basic Science Poster Walk & EFORT Jacques Duparc Award (2023)
• NIS Generali Award, German Society for Trauma Surgery (2023)
• Ferdinand Sauerbruch Award, Berlin Surgical Society (2023);
• Travel Fellowship, Guildal Foundation, Denmark (2025)

Role within Chondrometrics

Assoc. Prof. Maleitzke contributes a highly valued clinical perspective to his wealth of scientific expertise. As a clinician-scientist he operates at the interface where many of the key questions in musculoskeletal research arise: in patients, not in datasets. His core focus spans a broad range of musculoskeletal research areas, including joint health, inflammation, osteoarthritis, cell-based therapies, cartilage repair, etc., all of which matter to Chondrometrics. As a co-investigator in PROTO Horizon he interacts in two clinical trials with researchers active in the company.

Selected Publications or Output

• Maleitzke T, et al. Comment on “Surgical restabilization reduces the progression of post-traumatic osteoarthritis initiated by ACL rupture in mice” by Lin et al. (2024), and recommendations for non-invasive knee joint injury models. Osteoarthritis Cartilage;3 3(5):658-659 (2025). https://pubmed.ncbi.nlm.nih.gov/39947509/
• Fleckenstein FN, et al. Genicular Artery Embolization for the Treatment of Symptomatic Knee Osteoarthritis. Radiology. 316(1):e243648 (2025) https://pubmed.ncbi.nlm.nih.gov/40693933/
• Maleitzke T, et al. Transgenic disruption of endogenous glucocorticoid signaling in osteoblasts does not alter long-term K/BxN serum transfer-induced arthritis. Arthritis Res Ther. 4;25(1):140 (2024) https://pubmed.ncbi.nlm.nih.gov/37542341/
• Maleitzke T, et al. Standardized protocol and outcome measurements for the collagen antibody-induced arthritis mouse model. STAR Protoc.;3(4):101718 (2022) https://pubmed.ncbi.nlm.nih.gov/36152302/
• Eckstein F, et al. The design of a sample rapid magnetic resonance imaging (MRI) acquisition protocol supporting assessment of multiple articular tissues and pathologies in knee osteoarthritis. Osteoarthr Cartil Open23;6(3):100505 (2024). https://pubmed.ncbi.nlm.nih.gov/39183946/

Other

• Scholar of the Klaus Murmann Fellowship Programme at the Foundation of German Business (SDW) co-funded by the German Ministry of Education (2010-2016)
• Fellow of the Emeralds Career Programme for strategy talents by the Boston Consulting Group (2016-2019))
• Research Steering Committee Member, Initiator & Organizer Tour of the Big 4, MUSKOS Graduate Program, University of Copenhagen, Copenhagen, Denmark (2023-)
• 72. Lindau Nobel Laureate Meeting, Council for the Laureate Meeting (2023)
• Department of Clinical Medicine (IKM) Board Member, Clinical Associate Professor Representative, IKM Career Day 2026 Organization Committee, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark (2024-)
• Junior Chair, Copenhagen Academic Group (CAG) Research in Osteoarthritis in Denmark (ROAD) and Organizer of CAG ROAD Symposium 2026, Copenhagen, Denmark (2024-)
• Danish Orthopedic Academy (DOA) Representative for Copenhagen University Hospital Hvidovre, Copenhagen, Denmark (2024-)
• Spin-out of Hazel Therapeutics from the Danish Technical University, a company that develops a disease-modifying OA drug (DMOAD) based on locally injected RNA medicine, to target inflammation and cartilage pathology (2025)

Name and Current Position

Prof. Tom Turmezei; Consultant Musculoskeletal Radiologist, Norfolk and Norwich University Hospitals, Norwich & Honorary Professor, University of East Anglia, Norwich, UK.

Expertise Summary

Prof. Turmezei is a practicing clinical radiologist in Norwich, UK, and an internationally recognized expert in musculoskeletal radiology and quantitative imaging, with a focus on osteoarthritis (OA) imaging, weight-bearing CT, and quantitative 3-D analysis. His work has significantly contributed to imaging biomarkers in osteoarthritis, particularly in the development and validation of advanced quantitative joint assessment techniques. 

Education & Training

• BMBCh (Medicine), University of Oxford, UK (2002)
• MA in Natural Sciences (Psychology), University of Cambridge, UK (2003)
• Specialist Training in Radiology, UK (2006–2011)
• Fellow of the Royal College of Radiologists, UK (2009)
• MPhil (Medical Sciences), University of Cambridge, UK (2013)
• Clinical Musculoskeletal Radiology Fellowship, Royal National Orthopaedic Hospital, Stanmore, UK (2016–2017)
• PhD (Engineering), University of Cambridge, UK (2017)

Key Academic Appointments

• Wellcome Trust Clinical PhD Fellowship, Cambridge University Engineering Department, UK (2012–2016)
• Visiting Researcher, University of Cambridge, UK (2016– )
• Honorary Associate Professor, University of East Anglia, Norwich, UK (2017–2021)
• Honorary Professor, University of East Anglia, Norwich, UK (2022– )

Scientific Leadership & Honors

• Young Investigator Awards, International Workshop on OA Imaging (2016 & 2019)
• Roentgen Professorship, Royal College of Radiologists, UK (2020)
• Computed Tomography in Osteoarthritis (OCTA): Research Founder and Executive Committee Chair (2020–2025)
• Academic Committee Member Royal College of Radiologists, UK (2020–2023)
• Member (2020–2023) and Vice Chair (2023) for the National Institute for Health and Care Research UK Imaging Workforce Working Group.
• Board Member, International Weight Bearing Computed Tomography Soc. (2021– )
• NHS England National Clinical Impact Award (N2) (2024)
• Organiser of the 19^th International Workshop on OA Imaging, Cambridge, UK (2025)
• Board Member of the International Society of OA Imaging (2025– )

Role within Chondrometrics

Prof. Turmezei provides strategic guidance on MSK imaging biomarkers, quantitative analysis, clinical imaging evaluation and clinical applications, supporting the company’s mission to advance high-precision imaging endpoints in osteoarthritis clinical research.

Selected Publications or Output

• MacKay JW at al. Three-Dimensional Surface-Based Analysis of Cartilage MRI Data in Knee Osteoarthritis: Validation and Initial Clinical Application. J Magn Reson Imaging. 2020 Oct;52(4):1139-1151.https://pubmed.ncbi.nlm.nih.gov/32447815/
• Turmezei TD et al.. Quantitative Three-dimensional Assessment of Knee Joint Space Width from Weight-bearing CT. Radiology. 2021 Jun;299(3):649-659. https://pubmed.ncbi.nlm.nih.gov/33847516/
• Pers YM et al. ADIPOA2 consortium. Effect of intra-articular adipose-derived mesenchymal stromal cell versus placebo injection on pain and function in patients with knee osteoarthritis: the ADIPOA2 phase 2b randomised clinical trial. Ann Rheum Dis. 2025 Dec;84(12):2103-2114. https://pubmed.ncbi.nlm.nih.gov/40885690/

Other

• Collaborator and advisor to UK cultural institutions such as the Fitzwilliam Museum, Cambridge, and Hunterian Museum, London, on clinical imaging applications and analysis of artefacts since 2014.
• Imaging Editor for Gray’s Anatomy, Elsevier, 42^nd (2020) and 43^rd editions (2025)
• Co-founder and Director of KNEE3D Ltd (2024– ), a UK startup providing advanced research imaging analysis services from CT imaging.