Application of the sliding window method and Mask-RCNN method to nuclear recognition in oral cytology

Background: We aimed to develop an artificial intelligence (AI)-assisted oral cytology method, similar to cervical cytology. We focused on the detection of cell nuclei because the ratio of cell nuclei to cytoplasm increases with increasing cell malignancy. As an initial step in the development of AI-assisted cytology, we investigated two methods for the automatic detection of cell nuclei in blue-stained cells in cytopreparation images.Methods: We evaluated the usefulness of the sliding window method (SWM) and mask region-based convolutional neural network (Mask-RCNN) in identifying the cell nuclei in oral cytopreparation images. Thirty cases of liquid-based oral cytology were analyzed. First, we performed the SWM by dividing each image into 96 × 96 pixels. Overall, 591 images with or without blue-stained cell nuclei were prepared as the training data and 197 as the test data (total: 1,576 images). Next, we performed the Mask-RCNN by preparing 130 images of Class II and III lesions and creating mask images showing cell regions based on these images.Results: Using the SWM method, the highest detection rate for blue-stained cells in the evaluation group was 0.9314. For Mask-RCNN, 37 cell nuclei were identified, and 1 cell nucleus was identified as a non-nucleus after 40 epochs (error rate:0.027).Conclusions: Mask-RCNN is more accurate than SWM in identifying the cell nuclei. If the blue-stained cell nuclei can be correctly identified automatically, the entire cell morphology can be grasped faster, and the diagnostic performance of cytology can be improved

Cell Nucleus Detection in Oral Cytology Using Artificial Intelligence

We describe the detection of cell nuclei in oral cytology using artificial intelligence (AI). We focused on the detection of cell nuclei because the ratio of cell nuclei to cytoplasm increases with increasing cell malignancy. As an initial step in the development of AI-assisted cytology, we investigated two methods for the automatic detection of cell nuclei in blue-stained cells in cytopreparation images. We evaluated the usefulness of the sliding window method (SWM) and the mask region-based convolutional neural network (Mask-RCNN) method in identifying cell nuclei in oral cytopreparation images. Thirty cases of liquid-based oral cytology were analyzed. First, we performed the SWM by dividing each image into 96 × 96 pixels. Overall, 591 images with or without blue-stained cell nuclei were prepared as the training data and 197 as the test data (from among 1576 images in total). Next, we performed the Mask-RCNN method by preparing 130 images of Class II and III lesions and creating mask images showing cell regions based on these images. By the SWM method, the highest detection rate for blue-stained cells in the evaluation group was found to be 0.9314. For Mask-RCNN, 37 cell nuclei were identified, and 1 cell nucleus was identified as a non-nucleus after 40 epochs (error rate: 0.027). Mask-RCNN was shown to be more accurate than SWM in identifying the cell nuclei. If the bluestained cell nuclei can be correctly identified automatically, the entire cell morphology can be grasped faster, and the diagnostic performance of cytology can be improved

Long-term effect of photodynamic therapy on oral squamous cell carcinoma and epithelial dysplasia

Background: Oral squamous cell carcinoma (OSCC) treatment consists mainly of surgery, chemotherapy, and radiotherapy, alone or in combination. Epithelial dysplasia (ED) is also treated with surgery. However, these treatments can induce functional and/or aesthetic disturbances. Photodynamic therapy (PDT) can preserve organs. Although short-term studies have shown good progress, long-term evaluations have not yet been conducted. This study aimed to clarify the long-term effects of PDT on OSCC and ED. Methods: Patients who underwent PDT with the first (porfimer sodium) or second generation photosensitizers (talaporfin sodium) for early OSCC (T1 and T2) and ED were included in this study. The long-term prognosis was assessed.Results: Twenty-three patients were included. Complete response (CR) was observed in 19 patients (82.6%) and partial response (PR) in 4 patients (17.4%) 4 weeks after PDT. Regarding long-term progress, local region recurrence occurred in 11 of 19 CR cases (57.9%), and the term of recurrence was 27.4 ± 30.4 months. Surgical resection was performed in all local recurrence and PR cases, and 3 patients died of the underlying disease.Conclusions: PDT provides a good outcome in the short term, but its long-term effects are limited

Parotid Branches of the Auriculotemporal Nerve: An Anatomical Study With Implications for Frey Syndrome.

The auriculotemporal nerve is one of the many branches of the mandibular division of the trigeminal nerve. Of these, its superficial temporal branch has been most described. Although the parotid branches, secretomotor fibers to the parotid gland, are well known as the cause of Frey syndrome, there have been almost no descriptions of their anatomy. In this study, the authors dissected the parotid branches of the auriculotemporal nerve to elucidate their anatomy. A total of 10 sides from 7 adult and embalmed cadaver heads were used in this study. The specimens were derived from 3 males and 4 females, the age of cadavers at death ranged from 65 to 92 years old. Measurements included their diameter and the distance of their branching point from the main trunk of the auriculotemporal nerve from the middle of the tragus. Three of 10 sides had 2 parotid branches and 7 sides were found to have 1 parotid branch. The vertical distance between middle of the tragus to branching point of the parotid branch ranged from 1.79 to 16.17 mm. The horizontal distance between middle of the tragus to branching point of the parotid branch ranged from 3.03 to 12.62 mm. The diameter of the parotid branch ranged from 0.31 to 0.49 mm. An improved knowledge of the parotid branch of the auriculotemporal nerve might decrease injury to these structures with the potential for postoperative