Z. Jason Qian

Objective Transfeminine patients (transwomen/feminine nonbinary folks assigned male at birth) can undergo chondrolaryngoplasty (“tracheal shave”) to feminize their neck appearance. While isolated cases of vocal complications have been reported following the procedure, aggregated outcomes have not been quantitatively studied. We present acoustic and stroboscopic data to describe a patient cohort with vocal complications after chondrolaryngoplasty and discuss reparative surgical technique. Methods Subjective and objective data, including videostroboscopy, were collected from patients with voice complaints after chondrolaryngoplasty. Dislocated anterior commissures were reconstructed with feminization laryngoplasty. Postoperative voice data were recorded and statistically compared to preoperative data using paired t ‐tests. Results On consecutive chart review, of the 94 transfeminine women with prior outside history of chondrolaryngoplasty, 27 (29%) reported chronic postoperative hoarseness, deepened pitch, or loss of upper register. On endoscopy, short, lax vocal folds with persistent anterior glottic gap and phase asymmetry were commonly noted; anterior commissure dislocation was confirmed in‐office by using needle localization through absent thyroid cartilage. After open resuspension of the anterior commissure with feminization laryngoplasty, post‐repair modal‐speaking, minimum, and maximum fundamental frequencies (F0) increased on average by 7, 8, and 5 semitones, respectively ( p < 0.01), when compared to pre‐repair values. On average, perioperative maximum phonation time did not change significantly ( p = 0.15). Average self‐assessment of vocal femininity increased by 48% ( p < 0.01). Conclusion Anterior commissure dislocation should be suspected with signs of vocal impairment after chondrolaryngoplasty. Following proper diagnosis, resuspension of the anterior commissure via feminization laryngoplasty approach can be an effective reparative technique. Level of Evidence This work represents a 2011 OCEBM Level 4 evidence as a case series Laryngoscope , 133:2301–2307, 2023

Objectives The objective of this study is to determine whether machine learning may be used for objective assessment of aesthetic outcomes of auricular reconstructive surgery. Methods Images of normal and reconstructed auricles were obtained from internet image search engines. Convolutional neural networks were constructed to identify auricles in 2D images in an auto‐segmentation task and to evaluate whether an ear was normal versus reconstructed in a binary classification task. Images were then assigned a percent score for “normal” ear appearance based on confidence of the classification. Results Images of 1115 ears (600 normal and 515 reconstructed) were obtained. The auto‐segmentation task identified auricles with 95.30% accuracy compared to manually segmented auricles. The binary classification task achieved 89.22% accuracy in identifying reconstructed ears. When the confidence of the classification was used to assign percent scores to “normal” appearance, the reconstructed ears were classified to a range of 2% (least like normal ears) to 98% (most like normal ears). Conclusion Image‐based analysis using machine learning can offer objective assessment without the bias of the patient or the surgeon. This methodology could be adapted to be used by surgeons to assess quality of operative outcome in clinical and research settings. Level of Evidence 4 Laryngoscope , 133:2413–2416, 2023