Anomaly detection of retention loss in fixed partial dentures using resonance frequency analysis and machine learning: An in vitro study.

PURPOSE: This study aimed to determine the usefulness of machine learning techniques, specifically supervised and unsupervised learning, for assessing the cementation condition between a fixed partial denture (FPD) and its abutment using a resonance frequency analysis (RFA) system. METHODS: An in vitro mandibular model was used with a single crown and three-unit bridge made of a high-gold alloy. Two cementation conditions for the single crown and its abutment were set: cemented and uncemented. Four cementation conditions were set for the bridge and abutments: both crowns were firmly cemented, only the premolar crown was cemented, only the molar crown was cemented, and both crowns were uncemented. For RFA under cementation conditions, 16 impulsive forces were directly applied to the buccal side of the tested tooth at a frequency of 4 Hz using a Periotest device. Frequency responses were measured using a 3D accelerometer mounted on the occlusal surface of the tested tooth. Both supervised and unsupervised learning methods were used to analyze the datasets. RESULTS: Using supervised learning, the fully cemented condition had the highest feature importance scores at approximately 3000 Hz; the partially cemented condition had the highest scores between 1000 and 2000 Hz; and the highest scores for the uncemented condition were observed between 0 and 500 Hz. Using unsupervised learning, the uncemented and partially cemented conditions exhibited the highest anomaly scores. CONCLUSIONS: Machine learning combined with RFA exhibits good potential to assess the cementation condition of an FPD and hence facilitate the early diagnosis of FPD retention loss.

Resonance frequency analysis for evaluation of the connecting condition between fixed prostheses and their abutment teeth: An in vitro and finite element analysis study.

STATEMENT OF PROBLEM: Loss of retention is a clinical complication for fixed partial dentures (FPDs). However, a method sensitive enough to measure the early retention loss of FPDs is lacking. PURPOSE: The purpose of this in vitro and finite element analysis (FEA) study was to determine whether resonance frequency analysis (RFA) with a newly developed system can detect lack of FPD retention caused by cement loss. MATERIALS AND METHODS: Two evaluation methods were used: RFA of an in vitro model of a 3-unit FPD from the second premolar to the second molar and FEA by using a simplified model. The in vitro model was used to evaluate 4 connecting conditions: both crowns cemented, only the premolar crown cemented, only the molar crown cemented, and both crowns uncemented. Tapping stimulation (16 impulsive forces, 4 Hz) was directly applied to the buccal side of the second molar or the second premolar, and an attached 3D accelerometer sensor was used to record the resonance frequency (RF) of the tapped tooth. The amplitude, frequency, Q-value, and total area under the curve (AUC) of the RF values in the buccolingual direction were compared between connecting conditions. The FEA was done by using a simplified model of a 3-unit FPD with similar connecting conditions as the in vitro model study, and the RF amplitude and frequency of each tooth were calculated. Statistical evaluation included 1-way analysis of variance and the Tukey HSD test to compare the differences among each connecting condition under each parameter for measurement sites on the molar and the premolar, respectively (α=.05). RESULTS: For both the molar and premolar measurements in both the in vitro and FEA models, when the measurement site was on the uncemented tooth, the amplitude of RF-1 increased, the Q-value of RF-2 decreased, and the area under the curve increased (P<.05). CONCLUSIONS: The same 3 trends found between the measurement sites of the in vitro study and FEA indicated that RFA may be useful for detecting an FPD with loosening caused by cement loss, even partial cement loss.

Evaluation of implant screw loosening by resonance frequency analysis with triaxial piezoelectric pick-up: in vitro model and in vivo animal study.

OBJECTIVE: The aim of this study was to evaluate implant screw loosening using resonance frequency (RF) analysis with triaxial piezoelectric pick-up in vitro and in vivo. METHODS: For the in vitro experiment, a titanium implant was inserted into a mandibular model. The abutment screws were tightened to 10 N torque and loosened from 0 to 90° for RF measurement using 13 different screw conditions. In the in vivo experiment, three titanium implants were installed in each tibia of a New Zealand white rabbit, and the RF values were recorded after 8 weeks. For the RF analyses, a small 3D accelerometer was mounted rigidly onto the implant abutment, and impulsive vibration was directly applied to the abutment to vibrate the implant in a direction perpendicular to the tibia and implant (x-axis). The y-axis was defined as parallel to the tibia. The RF values of the x- and y-axis directions (RF-X and RF-Y) were used for evaluation. RESULTS: The RF values significantly decreased according to the degree of screw loosening (p < 0.05, ANOVA). In the in vitro model, RF-Y with x- and y-axis vibrations (RF-Yx and RF-Yy) significantly differed from the initial value at 10 and 15°, respectively (p < 0.05, Dunnett's test). In the in vivo experiment, the RF-Yy significantly differed from the initial value between 5 and 20° (p < 0.05). CONCLUSION: The results suggest that RF analysis with triaxial piezoelectric pick-up can be used to detect implant screw loosening. CLINICAL RELEVANCE: RF analysis with the triaxial piezoelectric pick-up can be used to detect screw loosening after mounting the superstructure.

Modeling infection of spring onion by Puccinia allii in response to temperature and leaf wetness.

The influence of temperature and leaf wetness duration on infection of spring onion (Japanese bunching onion) leaves by Puccinia allii was examined in controlled-environment experiments. Leaves of potted spring onion plants (Allium fistulosum cv. Yoshikura) were inoculated with urediniospores and exposed to 6.5, 10, 15, 22, or 27 h of wetness at 5, 10, 15, 20, or 25 degrees C. The lesion that developed increased in density with increasing wetness duration. Relative infection was modeled as a function of both temperature and wetness duration using the modified version of Weibull's cumulative distribution function (R(2) = 0.9369). Infection occurred between 6.5 and 27 h of leaf wetness duration at 10, 15, 20, and 25 degrees C and between 10 and 27 h at 5 degrees C, and increased rapidly between 6.5 and 15 h of wetness at 10, 15, and 20 degrees C. At 25 degrees C, few uredinia developed regardless of the wetness duration. Parameter H, one of eight parameters used in the equation and which controls the asymmetry in the response curve, varied markedly according to the temperature, so that the model could be improved by representing H as a function of wetness duration (R(2) = 0.9501).