Automated evaluation of masseter muscle volume: deep learning prognostic approach in oral cancer.

BACKGROUND: Sarcopenia has been identified as a potential negative prognostic factor in cancer patients. In this study, our objective was to investigate the relationship between the assessment method for sarcopenia using the masseter muscle volume measured on computed tomography (CT) images and the life expectancy of patients with oral cancer. We also developed a learning model using deep learning to automatically extract the masseter muscle volume and investigated its association with the life expectancy of oral cancer patients. METHODS: To develop the learning model for masseter muscle volume, we used manually extracted data from CT images of 277 patients. We established the association between manually extracted masseter muscle volume and the life expectancy of oral cancer patients. Additionally, we compared the correlation between the groups of manual and automatic extraction in the masseter muscle volume learning model. RESULTS: Our findings revealed a significant association between manually extracted masseter muscle volume on CT images and the life expectancy of patients with oral cancer. Notably, the manual and automatic extraction groups in the masseter muscle volume learning model showed a high correlation. Furthermore, the masseter muscle volume automatically extracted using the developed learning model exhibited a strong association with life expectancy. CONCLUSIONS: The sarcopenia assessment method is useful for predicting the life expectancy of patients with oral cancer. In the future, it is crucial to validate and analyze various factors within the oral surgery field, extending beyond cancer patients.

Machine Learning Analysis of Gaze Data for Enhanced Precision in Diagnosing Oral Mucosal Diseases.

The diagnosis of oral mucosal diseases is a significant challenge due to their diverse differential characteristics. Risk assessment of lesions by visual examination is a complex process due to the lack of definitive guidelines. This study aimed to improve this process by creating a diagnostic algorithm using gaze data acquired during oral mucosal disease examinations. A total of 78 dentists were included in this study. Tobii Pro Nano® (Tobii Technology) was used to acquire gaze data during clinical photographic visual examinations. Advanced analysis tools such as support vector machines and heatmaps were used to visualize the gazing tendencies of a group of skilled oral surgeons, focusing on the number of gazes per region and the gazing time ratios. The preliminary findings showed the possibility of visualizing gazing tendencies and identifying areas of importance for diagnosis. The classification of intraoral photographs based on gross features revealed the existence of an optimal examination method for each category and diagnostically significant areas. This novel approach to analyzing gaze data has the potential to refine diagnostic techniques and increase both accuracy and efficiency.

Compact Storage of Radioactive Cesium in Compressed Pellets of Zeolite Polymer Composite Fibers.

To facilitate the safe storage of radioactive Cs, a zeolite⁻poly(ethersulfone) composite fiber was fabricated to be a compact storage form of radioactive Cs, and an immobilization was investigated with respect to the effects of volume reduction and stability of the fiber's adsorbent matrix. Using compressed heat treatment at 100⁻800 °C for a zeolite polymer composite fiber (ZPCF) containing Cs, the fabrication changed its form from a fiber into a pellet, which decreased the matrix volume to be about one-sixth of its original volume. The Cs leakage behavior of the ZPCF matrix was examined in its compact pellet form for non-radioactive Cs and radioactive Cs when different fabrication conditions were carried out in the immobilization. The elution ratio of non-radioactive Cs from the matrix was minimal, at 0.05%, when the ZPCF was compressed with heat treatment at 300 °C. When using radioactive Cs for the compression at below 300 °C, the pellet form also had no elution of the pollutants from the matrix. When the compressed treatment was at 500 °C, the matrix exhibited elution of radioactive Cs to the outside, meaning that the plastic component was burning and decomposed in the pellet. A comparison of ZPCF and natural zeolite indicated that the compressed heating process for ZPCF was useful in a less-volume-immobilized form of the compact adsorbent for radioactive Cs storage.

Preparation of antibodies against a novel immunosuppressant, FTY720, and development of an enzyme immunoassay for FTY720.

FTY720 (1) is a novel immunosuppressant (immunomodulator), derived from ISP-I (2: myriocin and thermozymocidin). To clarify the pharmacokinetic properties of 1, antibodies against 1 were prepared and a competitive enzyme immunoassay (EIA) was developed. Two kinds of haptens, 3 and 4, for 1 were synthesized and coupled to ovalbumin (OVA). Rabbits were immunized with 3-OVA or 4-OVA, and corresponding antibodies were obtained. Both antibodies recognized the 2-amino-2-(2-phenylethyl)propane-1,3-diol moiety in 1. Using the anti-3-OVA antibody, a competitive EIA for 1 was developed and evaluated. The range of quantification by the EIA was 0.06-10 ng/mL. The application of the EIA has enabled us to measure the FTY720 concentration in serum after oral administration of 1 (1mg/kg) to rats.