Movement Quality After Intra-articular Injections — Comprehensive Real-World Evaluation Using Markerless Motion Analysis in Knee Osteoarthritis
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Baku · TOTBİD, Türkiye · 2026

10 · Injection Therapy

Movement Quality After Intra-articular Injections

Comprehensive Real-World Evaluation Using Markerless Motion Analysis in Knee Osteoarthritis

A real-world case series of 122 patients with knee osteoarthritis assessed with MAI Motion after iPAAG, PRP, hyaluronic acid or PRP+HA injections. C.R.A.F.T. movement-quality scores rose in every group, from baselines of 4.1–7.4 to peaks of 6.7–8.9, with the clearest gains in the first 4–6 months.

Presentation Details

Presented, and open to scrutiny.

Each presentation connects surgical decision-making, markerless movement measurement and quantitative imaging — bringing MSK Doctors Research to an international clinical and scientific audience.

Event

Turkic-Speaking Countries Orthopaedics & Traumatology International Congress (TOTBİD & Azerbaijan Orthopaedic Society), Baku Marriott Hotel Boulevard, 3–6 September 2026 · Abstract SB-040

Format

Oral presentation

Authors

Selin Demirel Mısırlı (presenting) · Feza Korkusuz — Hacettepe University, Faculty of Medicine, Department of Sports Medicine, Ankara, Türkiye; Paul Lee · Tanvi Verma — MSK Doctors, MSK House, Silk Willoughby, Sleaford, UK

Dr Selin Demirel Mısırlı portrait

Presenting author

Dr Selin Demirel Mısırlı

Hacettepe University, Department of Sports Medicine, Ankara, Türkiye

Themes

Knee osteoarthritisIntra-articular injectionsC.R.A.F.T. frameworkReal-world evidence

Scientific Focus

Knee osteoarthritis brings progressive pain, reduced mobility and impaired movement quality, and intra-articular treatments such as platelet-rich plasma (PRP), hyaluronic acid (HA), 2.5% polyacrylamide hydrogel (iPAAG) and combinations are increasingly used to improve joint function.

Yet the question clinicians struggle to answer in routine practice is not whether the patient feels less pain but whether they actually move better. This study asked that question with MAI Motion, an AI-based markerless system that turns standard video into three-dimensional movement data and scores movement quality from 0 to 10 on the C.R.A.F.T. framework: control, repetition, asymmetry, flow and rotational dynamics (twist).

Patients receiving iPAAG (n=9), PRP (n=11), HA (n=59) or PRP+HA (n=43) were assessed during routine outpatient visits at variable intervals from before injection to more than 24 months afterwards. Because baseline data were limited, the analysis was descriptive, summarising absolute values and longitudinal change.

Results

Follow-up2.5% iPAAG (n=9)PRP (n=11)HA (n=59)PRP+HA (n=43)
Before injection4.17.46.5 ± 1.26.5 ± 1.4
0–15 days6.2 ± 2.06.5 ± 1.5
15 days – 6 weeks8.36.2 ± 1.08.1 ± 0.5
6 weeks – 3 months5.16.5 ± 0.3
3–12 months7.3 ± 1.77.0 ± 0.87.1 ± 0.6
12–24 months8.46.9
> 24 months6.9 ± 1.77.5

Table 1. Overall C.R.A.F.T. scores (0–10) across treatment groups and follow-up time points. Values are mean ± SD or single observations; assessments were performed at variable intervals from pre-injection to more than 24 months. Dashes mark time points with no available measurement.

A · 2.5% iPAAG hydrogel

C.R.A.F.T. overall scores over time for patients treated with 2.5% iPAAG hydrogel

B · PRP

C.R.A.F.T. overall scores over time for patients treated with intra-articular PRP

C · HA

C.R.A.F.T. overall scores over time for patients treated with intra-articular hyaluronic acid

D · PRP + HA

C.R.A.F.T. overall scores over time for patients treated with intra-articular PRP plus hyaluronic acid
Figure 1. Longitudinal changes in overall C.R.A.F.T. scores following intra-articular injections in knee osteoarthritis: (A) 2.5% iPAAG hydrogel, (B) PRP, (C) HA and (D) PRP+HA. Each point is one measurement at a variable follow-up interval from pre-injection to more than 24 months; lines join repeated measurements of the same patient.

Why It Matters

C.R.A.F.T. scores increased over time in every treatment group. Baselines ranged from 4.1 to 7.4 and peak values reached 6.7 to 8.9, an improvement of roughly 30–75%, with the most pronounced gains inside the first 4–6 months.

Individual trajectories rose progressively, with some variability at later time points, and despite heterogeneous follow-up the longitudinal plots showed consistent positive trends.

The authors are careful about what this does and does not show: it is a real-world observation, not evidence of causation, of superiority between treatments, or of a generalisable effect size, because follow-up timing was uneven, baseline measurement was limited and the analysis is descriptive.

What it does show is that movement quality can be tracked in routine clinics, so treatment can be monitored by how a patient moves as well as by how they feel.

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The Human Algorithm

Designing Knee Surgery through Robotics, Motion and Biology

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