Preliminary Report of De Novo Adipogenesis Using Novel Bioabsorbable Implants and Image Evaluation Using A Porcine Model

Our bioabsorbable poly-L-lactic acid (PLLA) mesh implants containing collagen sponge is replaced with adipose tissue after implantation and is an innovative method for breast reconstruction. We investigated the formation of adipose tissue in a porcine model and evaluated the process via multimodal images in this preliminary study using an implant aggregate to generate the larger adipose tissue. The implant aggregate consists of PLLA mesh implants containing collagen sponge and a poly-glycolic acid woven bag covering them. We inserted the implant aggregates under the porcine mammary glands. Magnetic resonance imaging (MRI), ultrasonography (USG), and 3D surface imaging, and histological evaluations were performed to evaluate the formation of adipose tissue over time. The volume of the implant aggregate and the formed adipose tissue inside the implant aggregate could be evaluated over time via MRI. The space within the implant aggregate was not confirmed on USG due to the acoustic shadow of the PLLA threads. The change in volume was not confirmed precisely using 3D surface imaging. Histologically, the newly-formed adipose tissue was confirmed on the skin side. This implant aggregate has the ability to regenerate adipose tissue, and MRI is an appropriate method for the evaluation of the formation of adipose tissue.

Real-Time Multi-Modal Sensing and Feedback for Catheterization in Porcine Tissue

Objective: In this study, we introduce a multi-modal sensing and feedback framework aimed at assisting clinicians during endovascular surgeries and catheterization procedures. This framework utilizes state-of-the-art imaging and sensing sub-systems to produce a 3D visualization of an endovascular catheter and surrounding vasculature without the need for intra-operative X-rays. Methods: The catheterization experiments within this study are conducted inside a porcine limb undergoing motions. A hybrid position-force controller of a robotically-actuated ultrasound (US) transducer for uneven porcine tissue surfaces is introduced. The tissue, vasculature, and catheter are visualized by integrated real-time US images, 3D surface imaging, and Fiber Bragg Grating (FBG) sensors. Results: During externally-induced limb motions, the vasculature and catheter can be reliably reconstructed at mean accuracies of 1.9±0.3 mm and 0.82±0.21 mm, respectively. Conclusions: The conventional use of intra-operative X-ray imaging to visualize instruments and vasculature in the human body can be reduced by employing improved diagnostic technologies that do not operate via ionizing radiation or nephrotoxic contrast agents. Significance: The presented multi-modal framework enables the radiation-free and accurate reconstruction of significant tissues and instruments involved in catheterization procedures.

Prediction of the Ideal Implant Size Using 3-Dimensional Healthy Breast Volume in Unilateral Direct-to-Implant Breast Reconstruction

Background and objectives: There is no consensus regarding accurate methods for assessing the size of the implant required for achieving symmetry in direct-to-implant (DTI) breast reconstruction. The purpose of this study was to determine whether the ideal implant size could be estimated using 3D breast volume or mastectomy specimen weight, and to compare prediction performances between the two variables. Materials and Methods: Patients who underwent immediate DTI breast reconstruction from August 2017 to April 2020 were included in this study. Breast volumes were measured using 3D surface imaging preoperatively and at postoperative three months. Ideal implant size was calculated by correcting the used implant volume by the observed postoperative asymmetry in 3D surface imaging. Prediction models using mastectomy weight or 3D volume were made to predict the ideal implant volume. The prediction performance was compared between the models. Results: A total of 56 patients were included in the analysis. In correlation analysis, the volume of the implant used was significantly correlated with the mastectomy specimen weight (R2 = 0.810) and the healthy breast volume (R2 = 0.880). The mean ideal implant volume was 278 ± 123 cc. The prediction model was developed using the healthy breast volume: Implant volume (cc) = healthy breast volume × 0.78 + 26 cc (R2 = 0.900). The prediction model for the ideal implant size using the 3D volume showed better prediction performance than that of using the mastectomy specimen weight (R2 = 0.900 vs 0.759, p < 0.001). Conclusions: The 3D volume of the healthy breast is a more reliable predictor than mastectomy specimen weight to estimate the ideal implant size. The estimation formula obtained in this study may assist in the selection of the ideal implant size in unilateral DTI breast reconstruction.