Quantitative ultrasound scatteromics for characterization of reconstructed neopharyngeal tissue: Assessment of postoperative speech outcome after total laryngopharyngectomy.
Authors
Affiliations (7)
Affiliations (7)
- Department of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan.
- Department of Otorhinolaryngology Head and Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; Voice Center, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan; Graduate Institute of Management, Chang Gung University, Taoyuan, Taiwan.
- School of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Plastic and Reconstructive Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.
- School of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan; Department of Biomedical Sciences and Engineering, Tzu Chi University, Hualien, Taiwan; Department of Biomedical Engineering, Chung Yuan Christian University, Taoyuan, Taiwan.
- Department of Otorhinolaryngology Head and Neck Surgery, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; Voice Center, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan. Electronic address: [email protected].
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan; Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan. Electronic address: [email protected].
Abstract
Restoring speech after total laryngopharyngectomy (TLP) with flap reconstruction remains challenging. This study evaluated the feasibility of ultrasound scatteromics for assessing postoperative speech recovery by characterizing reconstructed flap tissues. Twenty-six patients were classified into phonation and whisper groups. Quantitative ultrasound (QUS) imaging based on the Nakagami parameter (m), homodyned K distribution parameters (α and k), and entropy (H) was performed from three anatomical views. For each parametric image, 13 first-order statistical features were extracted and selected to construct scatteromics features, which were used to train machine learning classifiers with repeated five-fold stratified cross-validation. Model performance and probabilistic reliability were evaluated using the area under the receiver operating characteristic curve (AUROC), calibration analysis, and the Brier score, and a simplified scatteromics model using four core parameters (m, α, k, and H) was assessed for comparison. Scatteromics derived from the reconstructed neopharynx view yielded consistently high discriminative performance across classifiers, with AUROC values ranging from 0.90 to 0.99. The simplified scatteromics approach demonstrated comparably strong classification performance, whereas individual QUS envelope statistics parameters showed limited discriminative ability (AUROC < 0.70). Probabilistic evaluation indicated that the full scatteromics framework yielded more stable probability estimation under limited sample size. Scatteromics may serve as a physically interpretable approach for characterizing reconstructed flap tissue and exploring speech recovery after TLP.