Obesity and extent of emphysema depicted at CT.

AIM: To investigate the underlying relationship between obesity and the extent of emphysema depicted at CT. METHODS AND MATERIALS: A dataset of 477 CT examinations was retrospectively collected from a study of chronic obstructive pulmonary disease (COPD). The low attenuation areas (LAAs; ≤950 HU) of the lungs were identified. The extent of emphysema (denoted as %LAA) was defined as the percentage of LAA divided by the lung volume. The association between log-transformed %LAA and body mass index (BMI) adjusted for age, sex, the forced expiratory volume in one second as percent predicted value (FEV1% predicted), and smoking history (pack years) was assessed using multiple linear regression analysis. RESULTS: After adjusting for age, gender, smoking history, and FEV1% predicted, BMI was negatively associated with severe emphysema in patients with COPD. Specifically, one unit increase in BMI is associated with a 0.93-fold change (95% CI: 0.91-0.96, p<0.001) in %LAA; the estimated %LAA for males was 1.75 (95% CI: 1.36-2.26, p<0.001) times that of females; per 10% increase in FEV1% predicated is associated with a 0.72-fold change (95% CI: 0.69-0.76, p<0.001) in %LAA. CONCLUSION: Increasing obesity is negatively associated with severity of emphysema independent of gender, age, and smoking history.

Time-frequency analysis of temporomandibular joint (TMJ) clicking sounds using radially Gaussian Kernels.

Temporomandibular joint (TMJ) sounds and motion were recorded during two clinically-derived movements--simple jaw opening and jaw protrusion followed by opening--from ten patients. A new time-frequency method--radially Gaussian kernel distribution--was applied to classify the TMJ clicking sounds into six groups, type I to type VI, based on the time-frequency patterns of energy distribution. The number of clicks and percentage of each type were examined. Relations between the two movements were examined by the prevalence of each type. A detailed classification of TMJ clicking sounds is provided by time-frequency patterns and may provide a better understanding of temporomandibular disorders.

Quantitative description of temporomandibular joint sounds: defining clicking, popping, egg shell crackling and footsteps on gravel.

This study presents a quantitative description of temporomandibular joint (TMJ) sounds provided by a rule-based classification system based on sound classification by three dentists, who listened to and classified the sound recordings as no sound, click, coarse crepitus and fine crepitus. The sounds were recorded with microphones in the ear canal from 126 subjects during vertical opening, digitized at 15 000 Hz, and replayed using a computer sound card and speakers. The dentists' classification of a test set resulted in intra- and inter-tester j values ranging from 0.71 to 0.81 and 0.61-0.73, respectively. Pooled j values for the dentists and the dentists plus the rules were 0.67 and 0.58, respectively, which were not significantly different in terms of the sound features on which the rules were based (P = 0.13). Linear discriminant analysis showed the four TMJ sound types were significantly different (P < 0.001). The performance of the rules was equivalent to the dentists and marginally better than the linear discriminant functions (P = 0.08), establishing the validity of the quantitative descriptions they provide. The recording and rebroadcast methodology produced sounds very similar to those observed in the clinic and could be used to train clinicians in classifying TMJ sounds.

The association between research diagnostic criteria for temporomandibular disorder findings and biting force and endurance in patients with temporomandibular disorders.

OBJECTIVE: This study was designed to evaluate the association between examination findings based on Research Diagnostic Criteria for Temporomandibular Disorders and performances on bite force and endurance tasks. METHODS: Subjects were 126 patients with temporomandibular disorder and 34 pain-free controls. A subset of patients with temporomandibular disorder (n = 56) also were evaluated following a brief conservative 4-week treatment intervention. RESULTS: A multivariate analysis of variance indicated that female patients (P <.001) but not males (P =.17) had lower bite forces than age- and gender-matched controls. Dental examination findings were significantly but modestly predictive of bite task performance (R2 = 0.175), with higher joint pain and smaller maximum unassisted jaw opening associated with lower bite force. The brief treatment interventions resulted in both self-reported and clinically determined improvements. Clinical and self-reported improvement significantly predicted pre-post treatment changes in biting force among female subjects (R2 = 0.237). Specifically, reduction in joint palpation pain and self-reported pain (McGill Pain Questionnaire short form) were the primary predictors of increases in bite force. The improvement in biting force was modest (mean = 7 lb), and the force levels of female patients remained lower than those of control subjects. Treatment did not significantly increase endurance time. DISCUSSION: The brief conservative treatments used resulted in improvements in pain and jaw opening, and 81.8% of patients reported moderate to major improvement. The modest association of the bite task with Research Diagnostic Criteria for Temporomandibular Disorders examination findings and treatment improvement in this heterogeneous sample suggests that the bite and endurance tasks have limited diagnostic utility and sensitivity to treatment effects.

The influence of mandibular movements on joint sounds in patients with temporomandibular disorders.

STATEMENT OF PROBLEM: There are discrepancies among researchers concerning the reliability and use of temporomandibular joint sounds. PURPOSE: This study examined the reliability of mandibular movements and sounds and determined the correlation between movements and sounds. MATERIAL AND METHODS: The mandibular movements of 35 subjects diagnosed with temporomandibular disorders were recorded with 2 CCD cameras, and sounds were recorded bilaterally with Panasonic electret condenser microphones in the ear canal. Subjects performed 3 movements, each repeated 5 times. RESULTS: Reliability of maximum movements across the 5 trials was good to excellent, with Intraclass Correlation Coefficients (ICC) between 0.76 and 0.91 for all movements except protrusion. Temporomandibular sound event counts were reliable for most movements, including vertical opening, protrusion, and right and left laterotrusion (ICCs between 0.41 and 0.81). Most subjects produced sound events either in 100% or in none of the trials. Reliability for sound events was better during protrusion (ICCs between 0.56 and 0.81) than vertical opening (ICCs 0.41 to 0.64). Subjects with sound events during vertical opening (followed by closing) were significantly more likely to have sound events during protrusion (followed immediately by vertical opening and closing) (P <.01). CONCLUSION: Temporomandibular sound events are generally reliable and warrant study regarding their use in classifying and diagnosing patients with temporomandibular disorders. Condylar translation, which occurs during both vertical opening and protrusion, appears to have a strong influence on the production of temporomandibular sound events.

A data dependent computer algorithm for the detection of muscle activity onset and offset from EMG recordings.

This paper describes modifications to an algorithm presented by Marple-Horvat and Gilbey (1992) for identifying bursts of muscle activity in electromyographical (EMG) recordings. Our efforts to apply their algorithm to spontaneously moving infants and toddlers resulted in limited success. The modified algorithm makes several parameters dependent on the data being analyzed; these changes enabled it to analyze a variety of EMG recordings more effectively. The original algorithm had a success rate (correctly identified bursts) of 62.9% and combined error rate (number of insertions and deletions) of 73.0% when applied to an independent test data set. The modified algorithm displayed a success rate of 85.4% and combined error rate of 23.6%.