Background: In this study, we proposed a deep learning technique that can simultaneously detect suspicious positions of benign vocal cord tumors in laparoscopic images and classify the types of tumors into cysts, granulomas, leukoplakia, nodules and polyps. This technique is useful for simplified home-based self-prescreening purposes to detect the generation of tumors around the vocal cord early in the benign stage. Results: We implemented four convolutional neural network (CNN) models (two Mask R-CNNs, Yolo V4, and a single-shot detector) that were trained, validated and tested using 2183 laryngoscopic images. The experimental results demonstrated that among the four applied models, Yolo V4 showed the highest F1-score for all tumor types (0.7664, cyst; 0.9875, granuloma; 0.8214, leukoplakia; 0.8119, nodule; and 0.8271, polyp). The model with the lowest false-negative rate was different for each tumor type (Yolo V4 for cysts/granulomas and Mask R-CNN for leukoplakia/nodules/polyps). In addition, the embedded-operated Yolo V4 model showed an approximately equivalent F1-score (0.8529) to that of the computer-operated Yolo-4 model (0.8683). Conclusions: Based on these results, we conclude that the proposed deep-learning-based home screening techniques have the potential to aid in the early detection of tumors around the vocal cord and can improve the long-term survival of patients with vocal cord tumors.

Pericardial metastasis from HPV‐positive oropharyngeal squamous cell carcinoma (OPSCC) without local recurrence is extremely rare. We report about a 69‐year‐old man exhibiting pericardial metastasis on positron emission tomography/computed tomography (PET/CT). There are currently no reports on the use of PET/CT in patients with pericardial metastasis from p16‐positive OPSCCs.

Background and Objectives: This study reports an association between nasolacrimal duct obstruction (NLDO) and perinasal uptake on radioactive iodine (RAI) whole-body scan. Materials and Methods: This is a retrospective study of 37 patients from May to November 2017 who underwent thyroidectomy and I-131 ablation for papillary thyroid cancer (PTC) and had a follow-up I-123 diagnostic WBS and dacryoscintigraphy. Ophthalmic examinations assessed punctal stenosis, NLDO, tear film break-up time, Schirmer’s test, punctate keratopathy, tear meniscus height, epiphora, and ocular dryness. Perinasal and nasal uptake on whole-body scans (WBSs) were assessed as negative (no uptake) or positive (focal uptake). The associations between perinasal uptake on WBS, dacryoscintigraphy findings, and ophthalmic assessments were assessed. Results: Nasal uptake on I-131 post-ablation WBS were observed in 60 eyes (81%); perinasal uptake was observed in 8 eyes (11%). Nasal uptake on I-123 post-ablation WBS were observed in all eyes; perinasal uptake was observed in 15 eyes (20%). Perinasal and nasal uptake on I-131 post-ablation WBS were significantly associated with delayed excretion on dacryoscintigraphy (p < 0.001 and p = 0.03, respectively). Perinasal uptake on I-123 WBS was associated with both abnormal dacryoscintigraphy findings and ocular dryness (p < 0.001 and p = 0.02, respectively). Conclusions: Perinasal uptake on I-131 post-ablation and I-123 diagnostic WBS was significantly associated with delayed excretion on dacryoscintigraphy, suggesting NLDO.