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Advances in technical radiotherapy have resulted in significant sparing of organs at risk (OARs), reducing radiation-related toxicities for patients with cancer of the head and neck (HNC). Accurate delineation of target volumes (TVs) and OARs is critical for maximising tumour control and minimising radiation toxicities. When performed manually, variability in TV and OAR delineation has been shown to have significant dosimetric impacts for patients on treatment. Auto-segmentation (AS) techniques have shown promise in reducing both inter-practitioner variability and the time taken in TV and OAR delineation in HNC. Ultimately, this may reduce treatment planning and clinical waiting times for patients. Adaptation of radiation treatment for biological or anatomical changes during therapy will also require rapid re-planning; indeed, the time taken for manual delineation currently prevents adaptive radiotherapy from being implemented optimally. We are therefore standing on the doorstep of a transformation of routine radiotherapy planning via the use of artificial intelligence. In this article, we outline the current state-of-the-art for AS for HNC radiotherapy in order to predict how this will rapidly change with the introduction of artificial intelligence. We specifically focus on delineation accuracy and time saving. We argue that, if such technologies are implemented correctly, AS should result in better standardisation of treatment for patients and significantly reduce the time taken to plan radiotherapy.

Study Objectives: Sleep problems are often undetected in adults with Down syndrome (DS). Our objective was to determine the prevalence of sleep disorders in adults with DS through self-reported and objective sleep measures. Methods: We performed a community-based cross-sectional study of 54 adults with DS not referred for sleep disorders. Two polysomnography (PSG) sleep studies were performed. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI); daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS) and the risk for the sleep apnea syndrome (OSA) was identified using the Berlin Questionnaire (BQ). Participants' sleep/wake pattern was assessed from sleep diaries and by wrist actigraphy. PSQI, ESS, and PSG measures were compared with 35 sex-, age-, and body mass index-matched patients in the control groups. Results: In PSG measures, adults with DS showed lower sleep efficiency (69 ± 17.7 versus 81.6 ± 11; P < .001), less rapid eye movement sleep (9.4 ± 5.8 versus 19.4 ± 5.1; P < .001), a higher prevalence of OSA (78% versus 14%; P < .001), and a higher apnea-hypopnea index (23.5 ± 24.5 versus 3.8 ± 10.5; P < .001) than patients in the control group. In the DS group, the questionnaires (mean PSQI 3.7 ± 2.9; mean ESS 6.3 ± 4.5 and mean BQ 1 ± 0) did not reflect the sleep disturbances detected on the PSG. Actigraphy data recorded daytime sleep that was not self-reported (118.2 ± 104.2 minutes). Conclusions: Adults with DS show severe sleep disruption and a high prevalence of OSA, undetected by self-reported sleep measures. Actigraphy, PSG, and validated simplified devices for screening OSA should be routinely recommended for this population because treatment of sleep disorders can contribute to healthy aging.

Background Based on associations between sleep spindles, cognition, and sleep-dependent memory processing, here we evaluated potential relationships between levels of CSF Aβ 42 , P-tau, and T-tau with sleep spindle density and other biophysical properties of sleep spindles in a sample of cognitively normal elderly individuals. Methods One-night in-lab nocturnal polysomnography (NPSG) and morning to early afternoon CSF collection were performed to measure CSF Aβ 42 , P-tau and T-tau. Seven days of actigraphy were collected to assess habitual total sleep time. Results Spindle density during NREM stage 2 (N2) sleep was negatively correlated with CSF Aβ 42 , P-tau and T-tau. From the three, CSF T-tau was the most significantly associated with spindle density, after adjusting for age, sex and ApoE4. Spindle duration, count and fast spindle density were also negatively correlated with T-tau levels. Sleep duration and other measures of sleep quality were not correlated with spindle characteristics and did not modify the associations between sleep spindle characteristics and the CSF biomarkers of AD. Conclusions Reduced spindles during N2 sleep may represent an early dysfunction related to tau, possibly reflecting axonal damage or altered neuronal tau secretion, rendering it a potentially novel biomarker for early neuronal dysfunction. Given their putative role in memory consolidation and neuroplasticity, sleep spindles may represent a mechanism by which tau impairs memory consolidation, as well as a possible target for therapeutic interventions in cognitive decline. Electronic supplementary material The online version of this article (10.1186/s13024-019-0309-5) contains supplementary material, which is available to authorized users.