This study aimed to compare combined audio‐visual coaching with audio coaching alone and assess their respective impact on the reproducibility of external breathing motion and, one step further, on the internal lung tumor motion itself, through successive sessions. Thirteen patients with NSCLC were enrolled in this study. The tumor motion was assessed by three to four successive 4D CT sessions, while the breathing signal was measured from magnetic sensors positioned on the epigastric region. For all sessions, the breathing was regularized with either audio coaching alone (AC, normaln=5) or combined with a real‐time visual feedback (A/VC, normaln=8) when tolerated by the patients. Peak‐to‐peak amplitude, period and signal shape of both breathing and tumor motions were first measured. Then, the correlation between the respiratory signal and internal tumor motion over time was evaluated, as well as the residual tumor motion for a gated strategy. Although breathing and tumor motions were comparable between AC and AV/C groups, A/VC approach achieved better reproducibility through sessions than AC alone (mean tumor motion of 7.2 mm±1 vs. 8.6 mm±1.8 mm, and mean breathing motion of 14.9 mm±1.2 mm vs. 13.3 mm±3.7 mm, respectively). High internal/external correlation reproducibility was achieved in the superior‐inferior tumor motion direction for all patients. For the anterior‐posterior tumor motion direction, better correlation reproducibility has been observed when visual feedback has been used. For a displacement‐based gating approach, A/VC might also be recommended, since it led to smaller residual tumor motion within clinically relevant duty cycles. This study suggests that combining real‐time visual feedback with audio coaching might improve the reproducibility of key characteristics of the breathing pattern, and might thus be considered in the implementation of lung tumor radiotherapy.PACS number: 87

Mandible movement recording and its dedicated signal processing for sleep/wake recognition improve sleep disorder index accuracy by assessing the total sleep time. Such a feature is welcome in home screening methods.

No abstract

SUMMARYThe mandible movement (MM) signal provides information on mandible activity. It can be read visually to assess sleep-wake state and respiratory events. This study aimed to assess (1) the training of independent scorers to recognize the signal specificities; (2) intrascorer reproducibility and (3) interscorer variability. MM was collected in the mid-sagittal plane of the face of 40 patients. The typical MM was extracted and classified into seven distinct pattern classes: active wakefulness (AW), quiet wakefulness or quiet sleep (QW/S), sleep snoring (SS), sleep obstructive events (OAH), sleep mixed apnea (MA), respiratory related arousal (RERA) and sleep central events (CAH). Four scorers were trained; their diagnostic capacities were assessed on two reading sessions. The intra-and interscorer agreements were assessed using Cohen's j. Intrascorer reproducibility for the two sessions ranged from 0.68 [95% confidence interval (CI): 0.59-0.77] to 0.88 (95% CI: 0.82-0.94), while the between-scorer agreement amounted to 0.68 (95% CI: 0.65-0.71) and 0.74 (95% CI: 0.72-0.77), respectively. The overall accuracy of the scorers was 75.2% (range: 72.4-80.7%). CAH MMs were the most difficult to discern (overall accuracy 65.6%). For the two sessions, the recognition rate of abnormal respiratory events (OAH, CAH, MA and RERA) was excellent: the interscorer mean agreement was 90.7% (Cohen's j: 0.83; 95% CI: 0.79-0.88). The discrimination of OAH, CAH, MA characteristics was good, with an interscorer agreement of 80.8% (Cohen's j: 0.65; 95% CI: 0.62-0.68). Visual analysis of isolated MMs can successfully diagnose sleep-wake state, normal and abnormal respiration and recognize the presence of respiratory effort. IN TROD UCTI ONMouth opening is a common observation during sleep in patients suffering from sleep-disordered breathing (SDB) (Miyamoto et al., 1999). The conjunction of sleep (and sleep stage) and neuro-anatomical factors of the upper respiratory airway will contribute in varying proportions to the occurrence of the obstructive event. Many factors influence the upper airway (UA) resistance and the occurrence of SDB. Inability to prevent UA obstruction during sleep is a feature of obstructive sleep apnea patients, inducing a cyclical phenomenon with persistent breathing effort. In the complex mechanisms leading to UA obstruction, the inferior jaw position (and linked structures including pharyngeal dilator muscles) is both influenced by and participates in pharyngeal patency. Mandible lowering during sleep is thought to be related to UA patency, as it is associated with both reduced cross-sectional area of the lumen and increased collapsibility of the UA (secondary to an inferior-posterior movement of the mandible) (Isono et al., 2004;Kuna and Remmers, 1985), and may contribute to sleep-related breathing abnormalities.The hypothetical mechanism explaining the mandible behaviour during sleep is postulated as follows.In normal conditions, the central respiratory drive commands the phasic inspiratory contraction of the...

Given the importance of the detection and classification of sleep apneas and hypopneas (SAHs) in the diagnosis and the characterization of the SAH syndrome, there is a need for a reliable non-invasive technique measuring respiratory effort. This paper proposes a new method for the scoring of SAHs based on the recording of the midsagittal jaw motion (mouth opening) and on a dedicated automatic analysis of this signal. Continuous wavelet transform is used to quantize respiratory effort from the jaw motion, to detect salient mandibular movements related to SAHs and to delineate events which are likely to contain the respiratory events. The classification of the delimited events is performed using multi-layer perceptrons which were trained and tested on sleep data from 34 recordings. Compared with SAHs scored manually by an expert, the sensitivity and specificity of the detection were 86.1% and 87.4% respectively. Moreover, the overall classification agreement in the recognition of obstructive, central and mixed respiratory events between the manual and automatic scorings was 73.1%. The midsagittal jaw motion signal is hence a reliable marker of respiratory effort and allows an accurate detection and classification of SAHs.