Optimization-Based Conformal Path Planning for In Situ Bioprinting in Complex Skin Defect Repair

Academic Background

The skin, as the largest organ in the human body, plays a crucial role in protecting the body from external harm. However, the high prevalence of skin injuries such as burns and chronic ulcers worldwide has led to an increasing demand for effective treatments. Although traditional tissue engineering and three-dimensional (3D) bioprinting technologies have shown potential, they still face numerous challenges when dealing with diverse skin injuries, particularly the risks of contamination or tissue damage during the implantation of printed scaffolds. In situ bioprinting, as an emerging technology, directly deposits bioink at the injury site, avoiding the potential risks of the traditional “print-implant” two-step strategy and demonstrating superior therapeutic effects. However, maintaining printing fidelity during in situ bioprinting, especially in model layering and path planning, remains a critical challenge.

Source of the Paper

This paper was co-authored by Wenxiang Zhao, Chuxiong Hu, Yunan Wang, Shize Lin, Ze Wang, and Tao Xu, affiliated with the State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University, and the Center for Bio-Intelligent Manufacturing and Living Matter Bioprinting, Research Institute of Tsinghua University in Shenzhen. The paper was published in 2025 in the journal Bio-design and Manufacturing, titled Optimization-based conformal path planning for in situ bioprinting during complex skin defect repair.

Research Process

1. Optimization-Based Conformal Path Planning Algorithm

The core of the research is the proposal of an optimization-based conformal path planning algorithm for in situ bioprinting to repair complex skin injuries. The algorithm identifies optimal waypoints on a point cloud-approximated curved surface through constrained optimization, ensuring high similarity in shape and angle between the pre-designed planar path and the surface-mapped 3D path. The specific process is as follows:

• Parameter Definition: The study first defines the surface S, planar path P, and mapping relationship Rs. By stepwise searching points on the planar path P and mapping them onto the curved surface S, the algorithm ensures that the distance and angle of the path on the surface are consistent with those of the planar path.
• Conformal Mapping with Shape Preservation: By minimizing the deviation between the geodesic distance of path points and the preset step size stp, the study fits the point cloud region using a quadratic surface and iteratively optimizes it using the interior-point optimization algorithm.
• Conformal Mapping with Shape and Angle Preservation: To simultaneously optimize distance and angle, the study normalizes distance and angle errors, constructing a unified optimization model to ensure that the shape and angle of the path on the surface are highly consistent with those of the planar path.

2. Conformal Path Generation Strategy

To address coverage issues in wound repair, the study further improves the path generation strategy by proposing a method to directly generate conformal paths on the wound surface, eliminating the reliance on pre-designed planar paths. The specific steps are as follows:

• Single-Layer Path Generation: The study uses a Zigzag path pattern to directly generate conformal paths on the wound surface. By stepwise searching points on the surface, the algorithm ensures that the path maintains spatial distance and linear constraints with previous points.
• Multi-Layer Path Generation: To address volumetric injuries, the study combines a radial basis function (RBF) point cloud hole-filling algorithm to generate multi-layer conformal paths. By offsetting the initial path points layer by layer, the algorithm ensures that each layer’s path is highly consistent with the wound shape.

3. Point Cloud Model Design and Processing

The study designs four types of 3D models (ellipsoidal surface, mathematical surface, folded protrusion structure, and murine back wound model) and obtains point cloud data of the wound model through 3D scanning. To validate the effectiveness of the algorithm, the study conducts physical printing experiments on these models.

4. Materials and Printing Experiments

The study uses methacrylated gelatin (GelMA) and lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) to prepare bioink and conducts in situ printing experiments using a seven-axis bioprinting robot. During the printing process, the study ensures high fidelity of the printing path through tool center point (TCP) calibration and robot motion control algorithms.

Main Results

1. Selection and Analysis of Step Size Parameters

The study experimentally analyzes the impact of the step size parameter stp on path mapping error and computational complexity. The results show that as stp decreases, the mapping error gradually decreases, but the computational complexity increases exponentially. The study determines the optimal step size value through an empirical formula, ensuring a balance between computational speed and error.

2. Comparison Between Conformal Paths and Direct Projection Paths

The study compares the performance of conformal paths and direct projection paths on curved surfaces. The results show that conformal paths have significant advantages in maintaining path spacing and angles, especially in regions with significant curvature changes, where direct projection paths often exhibit uneven spacing and angle distortion.

3. Bioprinting Validation on Geometric Models

The study conducts actual printing experiments on geometric models to validate the high fidelity of conformal paths. The results show that the printing effect of conformal paths on complex surfaces is highly consistent with the pre-designed path, with a printing coverage rate close to 98%. In contrast, the coverage rate of direct projection paths is only 93.6%, with noticeable gap defects.

4. Bioprinting Validation on Skin Wound Models

The study conducts in situ bioprinting experiments with multi-layer conformal path planning on murine back wound models. The results show that the printed structure effectively covers the wound area, with an average deviation from healthy skin of 0.52-0.90 mm and a maximum deviation of 2.12 mm. This indicates that the conformal path planning algorithm has high feasibility in guiding in situ bioprinting for repairing complex skin injuries.

Conclusions and Significance

The study proposes an optimization-based conformal path planning algorithm that effectively addresses the path planning challenges of in situ bioprinting on complex surfaces. By balancing shape and angle preservation, the algorithm generates highly accurate printing paths, significantly improving printing precision and coverage. The study not only provides a systematic path planning method for the development of in situ bioprinting technology but also opens new avenues for customized treatment of volumetric injuries.

Research Highlights

1. Innovative Path Planning Algorithm: The proposed conformal path planning algorithm demonstrates significant advantages in maintaining path shape and angles, particularly excelling in handling complex surfaces.
2. Multi-Layer Path Generation Strategy: By combining the radial basis function point cloud hole-filling algorithm, the study achieves the generation of multi-layer conformal paths, providing an effective solution for repairing volumetric injuries.
3. High-Fidelity Printing Validation: The study validates the high fidelity of conformal paths through actual printing experiments, with a printing coverage rate close to 98%, significantly outperforming traditional direct projection paths.

Other Valuable Information

The study also explores the impact of step size parameters on path mapping error and computational complexity and determines the optimal step size value through an empirical formula, providing important references for future path planning on unknown surfaces.