Factors Influencing Hypertrophic Scarring after Thyroidectomy

Predicting the severity of postoperative scars using artificial intelligence based on images and clinical data

Evaluation of scar severity is crucial for determining proper treatment modalities; however, there is no gold standard for assessing scars. This study aimed to develop and evaluate an artificial intelligence model using images and clinical data to predict the severity of postoperative scars. Deep neural network models were trained and validated using images and clinical data from 1283 patients (main dataset: 1043; external dataset: 240) with post-thyroidectomy scars. Additionally, the performance of the model was tested against 16 dermatologists. In the internal test set, the area under the receiver operating characteristic curve (ROC-AUC) of the image-based model was 0.931 (95% confidence interval 0.910‒0.949), which increased to 0.938 (0.916‒0.955) when combined with clinical data. In the external test set, the ROC-AUC of the image-based and combined prediction models were 0.896 (0.874‒0.916) and 0.912 (0.892‒0.932), respectively. In addition, the performance of the tested algorithm with images from the internal test set was comparable with that of 16 dermatologists. This study revealed that a deep neural network model derived from image and clinical data could predict the severity of postoperative scars. The proposed model may be utilized in clinical practice for scar management, especially for determining severity and treatment initiation.

Photobiomodulation therapy with an 830-nm light-emitting diode for the prevention of thyroidectomy scars: a randomized, double-blind, sham device-controlled clinical trial

This randomized, double-blind, and sham device-controlled trial aimed to evaluate the efficacy and safety of home-based photobiomodulation therapy using an 830-nm light-emitting diode (LED)-based device for the prevention of and pain relief from thyroidectomy scars. Participants were randomized to receive photobiomodulation therapy using an LED device or a sham device without an LED from 1 week postoperatively for 4 weeks. Scars were assessed using satisfaction scores, the numeric rating scale (NRS) score for pain, Global Assessment Scale (GAS), and Vancouver Scar Scale (VSS) scores. The scars were also assessed using a three-dimensional (3D) skin imaging device to detect color, height, pigmentation, and vascularity. Assessments were performed at the 1-, 3-, and 6-month follow-ups. Forty-three patients completed this trial with 21 patients in the treatment group and 22 patients in the control group. The treatment group showed significantly higher patient satisfaction and GAS scores and lower NRS and VSS scores than the control group at 6 months. Improvements in color variation, height, pigmentation, and vascularity at 6 months were greater in the treatment group than in the control group, although the differences were not significant. In conclusion, early application of 830-nm LED-based photobiomodulation treatment significantly prevents hypertrophic scar formation and reduces postoperative pain without noticeable adverse effects.