Next-Generation Cartilage Repair: Clinical Use of Wharton’s Jelly MSCs and the Emerging Role of AI-Assisted Bioprinting

The treatment of articular cartilage defects remains a significant clinical challenge due to the tissue’s limited intrinsic repair capacity. This paper presents a review of clinical experiences with the use of Wharton’s jelly-derived mesenchymal stem cells (WJ-MSCs) as a novel therapeutic option for cartilage regeneration. WJ-MSCs offer key advantages, including high proliferative potential, strong immunomodulatory properties, and low immunogenicity, making them suitable for allogeneic applications. This review describes a single-step, dry-arthroscopic technique that was employed for the implantation of WJ-MSCs embedded in a scaffold directly into cartilage defects. Clinical follow-up, supported by MRI evaluation, demonstrated favorable outcomes with evidence of defect filling, improved cartilage surface quality, and sustained functional improvement in patients. These results suggest that WJ-MSC-based therapies, delivered through minimally invasive surgical techniques, represent a safe and effective strategy for cartilage repair, with the potential to become an important alternative to current standard treatments. Recent advances in artificial intelligence (AI) and multimodal bioprinting are opening new perspectives for standardizing regenerative therapies. Machine learning models can predict bioink performance, optimize scaffold design, and integrate real-time imaging feedback such as optical coherence tomography and photoacoustic imaging. These approaches allow closed-loop quality control and the creation of digital twins to ensure biomechanical fidelity of constructs. Incorporating AI-assisted bioprinting with Wharton’s jelly MSCs could accelerate the translation of laboratory findings into reproducible, patient-specific cartilage implants. This manuscript is structured as a translational review of WJ-MSC-based cartilage repair, with AI-assisted bioprinting presented as a prospective future manufacturing direction rather than current clinical practice.

Authors

Institutions

Publication Details

Journal
Bioengineering
Published
2026-08-27
DOI
https://doi.org/10.3390/bioengineering13090995
Primary Topic
Osteoarthritis Treatment and Mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Next-Generation Cartilage Repair: Clinical Use of Wharton’s Jelly MSCs and the Emerging Role of AI-Assisted Bioprinting

Wojciech Klon, Ewa Stodolak‐Zych, Bogusław Sadlik, Kamila Rawojć et al.
Bioengineering
Osteoarthritis Treatment and Mechanisms
article

Next-Generation Cartilage Repair: Clinical Use of Wharton’s Jelly MSCs and the Emerging Role of AI-Assisted Bioprinting

Wojciech Klon, Ewa Stodolak‐Zych, Bogusław Sadlik, Kamila Rawojć, Magdalena Matuszewska
article en

Abstract

The treatment of articular cartilage defects remains a significant clinical challenge due to the tissue’s limited intrinsic repair capacity. This paper presents a review of clinical experiences with the use of Wharton’s jelly-derived mesenchymal stem cells (WJ-MSCs) as a novel therapeutic option for cartilage regeneration. WJ-MSCs offer key advantages, including high proliferative potential, strong immunomodulatory properties, and low immunogenicity, making them suitable for allogeneic applications. This review describes a single-step, dry-arthroscopic technique that was employed for the implantation of WJ-MSCs embedded in a scaffold directly into cartilage defects. Clinical follow-up, supported by MRI evaluation, demonstrated favorable outcomes with evidence of defect filling, improved cartilage surface quality, and sustained functional improvement in patients. These results suggest that WJ-MSC-based therapies, delivered through minimally invasive surgical techniques, represent a safe and effective strategy for cartilage repair, with the potential to become an important alternative to current standard treatments. Recent advances in artificial intelligence (AI) and multimodal bioprinting are opening new perspectives for standardizing regenerative therapies. Machine learning models can predict bioink performance, optimize scaffold design, and integrate real-time imaging feedback such as optical coherence tomography and photoacoustic imaging. These approaches allow closed-loop quality control and the creation of digital twins to ensure biomechanical fidelity of constructs. Incorporating AI-assisted bioprinting with Wharton’s jelly MSCs could accelerate the translation of laboratory findings into reproducible, patient-specific cartilage implants. This manuscript is structured as a translational review of WJ-MSC-based cartilage repair, with AI-assisted bioprinting presented as a prospective future manufacturing direction rather than current clinical practice.

BioengineeringVol. 13(9)
Wroclaw University of Health and Sport Sciences (PL), Academy of Physiotherapy in Wrocław (PL), University of Bielsko-Biała (PL), AGH University of Krakow (PL)
Openalex Percentile: Top 10%
Osteoarthritis Treatment and Mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.