Breathing Variability Research Articles

Breathing variability during running in athletes: The role of sex, exercise intensity and breathing reserve

Highly trained aerobic athletes progressively use most of their breathing reserve with increased exercise intensity during whole-body exercise. Additionally, females typically present proportionally smaller lungs than males. Therefore, sex, exercise intensity, and breathing reserve use likely influence the volume and time in which respiratory parameters vary between consecutive breaths during whole-body exercise. However, breath-by-breath variability has been scarcely investigated during exercise. Accordingly, we sought to investigate breath-by-breath pulmonary ventilation (V̇E), tidal volume (VT), and respiratory frequency (fR) variability during a maximal treadmill incremental exercise test in 17 females and 18 males highly trained professional endurance runners. The breath-by-breath variability was analyzed by root mean square of successive differences (RMSSD) within 1-minute windows. Females had lower absolute and percent predicted forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) than males, as well as lower height-adjusted absolute FVC than males. V̇E and VT reserve use were similar between the sexes at peak exercise. While RMSSDV̇E and RMSSDfR did not change over exercise (P > 0.05), RMSSDVT progressively decreased (P < 0.001). RMSSDVT was negatively correlated with VT reserve use only in males. Females showed lower RMSSDV̇E than males during the entire exercise test (P < 0.001). At iso-V̇E reserve use, between-sex differences in RMSSDV̇E persisted (P = 0.003). Our findings indicate that exercise intensity decreases VT variability in professional runners, which is linked to VT reserve use in males but not females. Additionally, the female sex lowers V̇E variability regardless of exercise intensity and V̇E reserve use.

Robust Control of Exo-Abs, a Wearable Platform for Ubiquitous Respiratory Assistance

Abstract Existing noninvasive breathing assist options compatible with out-of-hospital settings are limited and not appropriate to enable essential everyday activities, thereby deteriorating the quality of life. In our prior work, we developed the Exo-Abs, a novel wearable robotic platform for ubiquitous assistance of respiratory functions in patients with respiratory deficiency. This paper concerns the development of a model-based closed-loop control algorithm for the Exo-Abs to automate its breathing assistance. To facilitate model-based development of closed-loop control algorithms, we developed a control-oriented mathematical model of the Exo-Abs. Then, we developed a robust absolutely stabilizing gain-scheduled proportional-integral control algorithm for automating the breathing assistance with the Exo-Abs, by (i) solving a linear matrix inequality formulation of the Lyapunov stability condition against sector-bounded uncertainty and interindividual variability in the mechanics of the abdomen and the lungs and (ii) augmenting it with a heuristic yet effective gain scheduling algorithm. Using in silico evaluation based on realistic and plausible virtual patients, we demonstrated the efficacy and robustness of the automated breathing assistance of the Exo-Abs under a wide range of variability in spontaneous breathing and Exo-Abs efficiency: the absolutely stabilizing gain-scheduled proportional-integral control resulted in small exhalation trajectory tracking error (&amp;lt;30 ml) with smooth actuation, which was superior to (i) its proportional-integral control counterpart in tracking efficacy and to (ii) its proportional-integral-derivative control counterpart in chattering.

Cycle-frequency content EEG analysis improves the assessment of respiratory-related cortical activity

Objective. Time-frequency (T-F) analysis of electroencephalographic (EEG) is a common technique to characterise spectral changes in neural activity. This study explores the limitations of utilizing conventional spectral techniques in examining cyclic event-related cortical activities due to challenges, including high inter-trial variability.Approach. Introducing the cycle-frequency (C-F) analysis, we aim to enhance the evaluation of cycle-locked respiratory events. For synthetic EEG that mimicked cycle-locked pre-motor activity, C-F had more accurate frequency and time localization compared to conventional T-F analysis, even for a significantly reduced number of trials and a variability of breathing rhythm.Main results. Preliminary validations using real EEG data during both unloaded breathing and loaded breathing (that evokes pre-motor activity) suggest potential benefits of using the C-F method, particularly in normalizing time units to cyclic activity phases and refining baseline placement and duration.Significance. The proposed approach could provide new insights for the study of rhythmic neural activities, complementing T-F analysis.

Electrical Impedance Tomography, Artificial Intelligence, and Variable Ventilation: Transforming Respiratory Monitoring and Treatment in Critical Care.

Electrical Impedance Tomography (EIT), combined with variable ventilation strategies and Artificial Intelligence (AI), is poised to revolutionize critical care by transitioning from reactive to predictive approaches. This integration aims to enhance patient outcomes through personalized interventions and real-time monitoring. this narrative review explores the principles and applications of EIT, variable ventilation, and AI in critical care. EIT impedance sensing creates dynamic images of internal physiology, aiding the management of conditions like Acute Respiratory Distress Syndrome (ARDS). Variable ventilation mimics natural breathing variability to improve lung function and minimize ventilator-induced lung injury. AI enhances EIT through advanced image reconstruction techniques, neural networks, and digital twin technology, offering more accurate diagnostics and tailored therapeutic interventions. the confluence of EIT, variable ventilation, and AI represents a significant advancement in critical care, enabling a predictive, personalized approach. EIT provides real-time insights into lung function, guiding precise ventilation adjustments and therapeutic interventions. AI integration enhances EIT diagnostic capabilities, facilitating the development of personalized treatment plans. This synergy fosters interdisciplinary collaborations and sets the stage for innovative research, ultimately improving patient outcomes and advancing the future of critical care.

Relación entre meditación, regulación emocional y expresión vocal

Introduction: The voice is an indicator of emotional states, influenced by factors such as vagal tone, breathing and heart rate variability. This study explores these factors and their relationship with emotional regulation and meditative practice as a self-regulation technique. Purpose: To investigate the difference in vocal characteristics and heart rate variability in experienced (EM) and novice (NM) meditators before and after a meditation practice and in non-meditators - control group (CG), before and after a control test. Methods: 3 x 2 quasi-factorial study. Three groups were evaluated (experienced meditators EM; novice meditators NM; and control group CG, non-meditators) at two points in the experimental manipulation - before and after a meditation session for meditators, and before and after a word search task for the control group. The fundamental frequency, jitter, shimmer, harmonic-to-noise ratio and the first (F1), second (F2) and third (F3) formants of the vowel [a]; heart rate variation (SDNN, RMSSD, LF/HF, SD1 and SD2); anxiety state and vocal self-perception, were investigated, before and after the intervention. Results: The EM group achieved optimal vocal tract relaxation. The NM and CG groups showed changes in F1. Long-term meditative practice was associated with a large difference in F3, SDNN and SD2 in heart rate variation. Conclusion: The results suggest that meditation practice influences vocal expression and emotional reaction, and that experience in meditation practice favors this relationship.

Respiratory and chest wall mechanics in very preterm infants.

Data on static compliance of the chest wall (Ccw) in preterm infants are scarce. We characterized the static compliance of the lung (CL) and Ccw to determine their relative contribution to static compliance of the respiratory system (Crs) in very preterm infants at 36 wk postmenstrual age (PMA). We also aimed to investigate how these compliances were influenced by the presence of bronchopulmonary dysplasia (BPD) and impacted breathing variables. Airway opening pressure, esophageal pressure, and tidal volume (VT) were measured simultaneously during a short apnea evoked by the Hering-Breuer reflex. We computed tidal breathing variables, airway resistance (R), and dynamic lung compliance (CL,dyn), inspiratory capacity (IC), and Crs, CL, and Ccw. Functional residual capacity was assessed by the multiple breath washout technique (FRCmbw). Breathing variables, compliances, and lung volumes were adjusted for body weight. Twenty-three preterm infants born at 27.2 ± 2.0 wk gestational age (GA) were studied at 36.6 ± 0.6 wk PMA. Median and interquartile range (IQR) Crs/kg is 0.69 (0.6), CL/kg 0.95 (1.0), and Ccw/kg 3.0 (2.4). Infants with BPD (n = 11) had lower Crs/kg (P = 0.013), CL/kg (P = 0.019), and Ccw/kg (P = 0.027) compared with infants without BPD. Ccw/CL ratio was equal between groups. FRCmbw/kg (P = 0.044) and IC/kg (P = 0.005) were decreased in infants with BPD. Infants with BPD have reduced static compliance of the respiratory system, the lungs, and chest wall. Decreased Crs, CL, and Ccw in infants with BPD explain the lower FRC and IC seen in these infants.NEW & NOTEWORTHY Data on chest wall compliance in very preterm infants in the postsurfactant era are scarce. To our knowledge, we are the first group to report data on static respiratory system compliance (Crs), lung compliance (CL), and chest wall compliance (Ccw) in preterm infants with and without bronchopulmonary dysplasia (BPD) in the postsurfactant era.

Deformable vector fields warping for modelling of irregular breathing.

Purpose&#xD;4D computed tomography (4DCT) is the clinical standard to image organ motion in radiotherapy, although it is limited in imaging breathing variability. We propose a method to transfer breathing motion across longitudinal imaging datasets to include intra-patient variability and verify its performance in lung cancer patients. &#xD;Methods &#xD;Five repeated control 4DCTs for 6 non-small cell lung cancer patients were combined into multi-breath datasets (m4DCT) by merging stages of deformable image registration to isolate respiratory motion. The displacement of the centre of mass of the primary tumour and its volume changes were evaluated to quantify intra-patient differences. Internal target volumes defined on the m4DCT were compared with those conventionally drawn on the 4DCT.&#xD;Results &#xD;Motion analysis suggests no discontinuity at the junction between successive breaths, confirming the method's ability to merge repeated imaging into a continuum. Motion (variability) is primarily in superior-inferior direction and goes from 14.4 mm (8.7 mm) down to 0.1 mm (0.6 mm), respectively for tumours located in the lower lobes or most apical ones. On average, up to 65% and 74% of the tumour volume was subject to expansion or contraction in the inhalation and exhalation phases. These variations lead to an enlargement of the ITV up to 8% of its volume in our dataset.&#xD;Conclusion &#xD;4DCT can be extended to model variable breathing motion by adding synthetic phases from multiple time-resolved images. The inclusion of this improved knowledge of patients' breathing allows better definition of treatment volumes and their margins for radiation therapy.&#xD.

Sex Differences In The Phenotype Of Sleep-Disordered Breathing In C57BL/6J Mice

Sex differences in sleep-disordered breathing (SDB) are widely recognized. SDB is more prevalent in men, but women appear to exhibit more symptoms at lower levels of SDB severity, including insomnia symptoms. Mechanisms underlying sex differences in SDB are unknown. In this study, we compared the sleep architecture and breathing patterns during sleep between male and female mice and examined the effects of ovariectomy on SDB. We hypothesized that female and male mice differed in sleep and SDB, which are related to differences in carbon dioxide (CO2) chemosensitivity between sexes. Adult male (n=9) and female (n=10) C57BL/6J mice underwent full-polysomnography inside a whole-body plethysmography chamber. Arousals from sleep and apneas were manually scored. Breathing variability was assessed with Poincaré plots of minute ventilation. Hypercapnic ventilatory response (HCVR) was assessed during wakefulness and NREM sleep by acute administration of 8% CO2. In female mice, we performed bilateral ovariectomy and repeated sleep studies after 14 days. We found that arousal index was 55% increased in females compared to males, but sleep fragmentation was mainly attributed to spontaneous arousals in both groups. Surprisingly, apnea severity was significantly increased in female mice compared to males (32.4±6.7 vs 11.8±4.5, P=0.001). Breathing instability was also increased in females. HCVR was positively correlated with apnea index (r=0.55, P=0.05) and was significantly augmented in females compared to males. Ovariectomy did not affect sleep fragmentation, but attenuated CO2 sensitivity and improved breathing stability during sleep. Our results have suggested different SDB phenotypes between male and female C57BL/6J mice. SDB in female mice is associated with a hyperarousal state and increased HCVR compared to males. An exacerbated CO2 responsiveness related to ovarian hormones in females is an important determinant of differences in SDB severity and respiratory patterns between male and female sex. American Heart Association Postdoctoral Fellowship Award 828142 (to L.J.K.), NHLBI grant 2R01 HL133100-05, NIH R01 HL128970, and R01 HL13892 (to V.Y.P.), 1K23HL155730 and American Academy of Sleep Medicine Foundation 238-BS-20 (to L.V.P.). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Continuous and bilevel positive airway pressure may improve radiotherapy delivery in patients with intra-thoracic tumors

BackgroundMinimizing tumor motion in radiotherapy for intra-thoracic tumors reduces side-effects by limiting radiation exposure to healthy tissue. Continuous or Bilevel Positive Airway Pressure (CPAP/BiPAP) could achieve this, since it could increase lung inflation and decrease tidal volume variability. We aim to identify the better CPAP/BiPAP setting for minimizing tumor motion. MethodsIn 10 patients (5 with lung cancer, 5 with other intra-thoracic tumors), CPAP/BiPAP was tested with the following settings for 10 min each: CPAP 5, 10 and 15 cmH2O and BiPAP 14/10 cmH2O with a lower (7 breaths/min) and higher back-up respiratory rate (BURR initially 1 breath/min above the spontaneous breathing frequency, with the option to adjust if the patient continued to initiate breaths). Electrical impedance tomography was used to analyse end-expiratory lung impedance (EELI) as an estimate of end-expiratory lung volume and tidal impedance variation (TIV) as an estimate of tidal volume. ResultsNine out of ten patients tolerated all settings; one patient could not sustain CPAP-15. A significant difference in EELI was observed between settings (χ2 22.960, p < 0.001), with most increase during CPAP-15 (median (IQR) 1.03 (1.00 – 1.06), normalized to the EELI during spontaneous breathing). No significant differences in TIV and breathing variability were found between settings. ConclusionsThis study shows that the application of different settings of CPAP/BiPAP in patients with intra-thoracic tumors is feasible and tolerable. BiPAP with a higher BURR may offer the greatest potential for mitigating tumor motion among the applied settings, although further research investigating tumor motion should be conducted.

Respiratory entrainment related reverse triggering in mechanically ventilated children

BackgroundThe underlying pathophysiological pathways how reverse triggering is being caused are not fully understood. Respiratory entrainment may be one of these mechanisms, but both terms are used interchangeably. We sought to characterize reverse triggering and the relationship with respiratory entrainment among mechanically ventilated children with and without acute lung injury.MethodsWe performed a secondary phyiology analysis of two previously published data sets of invasively mechanically ventilated children < 18 years with and without lung injury mechanically ventilated in a continuous or intermittent mandatory ventilation mode. Ventilator waveforms, electrical activity of the diaphragm measured with surface electromyography and oesophageal tracings were analyzed for entrained and non-entrained reverse triggered breaths.ResultsIn total 102 measurements (3110 min) from 67 patients (median age 4.9 [1.8 ; 19,1] months) were analyzed. Entrained RT was identified in 12 (12%) and non-entrained RT in 39 (38%) recordings. Breathing variability for entrained RT breaths was lower compared to non-entrained RT breaths. We did not observe breath stacking during entrained RT. Double triggering often occurred during non-entrained RT and led to an increased tidal volume. Patients with respiratory entrainment related RT had a shorter duration of MV and length of PICU stay.ConclusionsReverse triggering is not one entity but a clinical spectrum with different mechanisms and consequences.Trial registrationNot applicable.

High-Flow and Low-Flow Oxygen Delivery by Nasal Cannula Evaluated in Infant and Adult Airway Replicas.

The nasal cannula is widely regarded as a safe and effective means of administering low- and high-flow oxygen to patients irrespective of their age. However, variability in delivered oxygen concentration (FDO2 FDO2 ) via nasal cannula has the potential to pose health risks. The present study aimed to evaluate predictive equations for FDO2 over a large parameter space, including variation in breathing, oxygen flow, and upper-airway geometry representative of both young children and adults. Realistic nasal airway geometries were previously collected from medical scans of adults, infants, and neonates. Nasal airway replicas based on these geometries were used to measure the FDO2 for low-flow oxygen delivery during simulated spontaneous breathing. The present study extends previously published data sets to include higher oxygen flows. The extended data sets included nasal cannula oxygen flows that ranged from 6 to 65 L/min for the adult replicas, and from 0.5 to 6 L/min for the infant replicas. For both age groups, FDO2 was measured over a range of breathing frequencies, inspiratory to expiratory time ratios, and tidal volumes. Measured FDO2 values were compared with values predicted by using a previously derived flow-weighted equation. For both age groups, FDO2 was observed to increase nonlinearly with the ratio between oxygen flow supplied to the nasal cannula and the average inhalation flow. The previously derived flow-weighted equation over-predicted FDO2 at higher oxygen flows. A new empirical equation, therefore, was proposed to predict FDO2 for either age group as a function of nasal cannula flow, tidal volume, and inspiratory time. Predicted FDO2 values matched measured values, with average relative errors of 2.4% for infants and 4.3% for adults. A new predictive equation for FDO2 was obtained that accurately matched measured data in both adult and infant airway replicas for low- and high-flow regimens.

Effects of breathing variables on modelled particle lung deposition at physical activity for children and adults

AbstractThe respiratory tract deposited fraction (DF) is the link between exposure and health effects of airborne particles. Here, we investigate how breathing pattern alterations at increasing physical activity affect DF in different regions of the respiratory tract and compare DF between adults and children (5 and 10 years old). We performed a literature review on the alteration of tidal volume with minute ventilation at increasing physical activity and used the results to model the size resolved (0.001–10 µm) DF, primarily using the deposition models from NCRP and Yeh and Schum (1980), but also MPPD. We found a shift in the deposited size distribution with increasing physical activity—DF of ultrafine particles increased in the alveolar region and decreased in the other regions, while DF of coarser particles decreased in the alveolar region and increased in the extra-thoracic region. Children had a 10–20% higher DF of ultrafine particles in the alveolar region compared to adults. We also present parametrizations of the daily average size resolved (0.005–5 µm) DF, accounting for varying physical activity throughout the day and oral/nasal breathing. These can be applied to any size distribution to estimate deposited doses. We found that deposited mass and number doses were more than twice as high for 5-year-olds compared to adults when normalized for body weight, primarily caused by their higher weight normalized minute ventilation. This demonstrates the importance of studying children’s exposure to air pollution and not only rely on data from adults.

Application of cardiorespiratory training with biofeedback in a patient with comorbidity

Biofeedback is increasingly used in practice due to diversity, the possibility of visualization of corrective functions, and the availability of objective indicators for assessing the dynamics of the training process. Biofeedback training helps to teach patients to skills that alleviate their condition, support active functioning, thereby increasing the quality of life. One of the simple methods of biofeedback is cardiorespiratory training, during which the patient learns the skill of diaphragmatic relaxation breathing, which is effective in rehabilitation for various pathologies, especially in pediatric practice. This type of biofeedback is based on the control of breathing and heart rate variability (HRV). HRV reflects the body’s ability to quickly recover from exposure to mental and physical stress factors. HRV is a unique marker of a person’s cardiovascular and psychophysiological health. This clinical example demonstrates a case of respiratory correction in a patient with comorbidities (multiple sclerosis, essential arterial hypertension, and panic disorder). The training was chosen as the most optimal for improving the patient’s quality of life, in respect that the leading complaint was panic attacks. One of the main goals of rehabilitation for this child is to teach the skills of diaphragmatic relaxation breathing, which allowed the patient learning to cope with future panic attacks, reduce anxiety and thereby improve his well-being. The article describes in detail the course of the training, recommended exercises for daily use, and presents the positive trend in the recorded indicators and the patient’s condition by the end of the course. Cardiorespiratory training is an effective and understandable method of rehabilitation that can be actively used in practice for an objective assessment of the classes performed and for psycho-emotional correction in children and adolescents with various pathologies.

Exploring the role of the Kölliker-Fuse nucleus in breathing variability by mathematical modelling.

The Kölliker-Fuse nucleus (KF), which is part of the parabrachial complex, participates in the generation of eupnoea under resting conditions and the control of active abdominal expiration when increased ventilation is required. Moreover, dysfunctions in KF neuronal activity are believed to play a role in the emergence of respiratory abnormalities seen in Rett syndrome (RTT), a progressive neurodevelopmental disorder associated with an irregular breathing pattern and frequent apnoeas. Relatively little is known, however, about the intrinsic dynamics of neurons within the KF and how their synaptic connections affect breathing pattern control and contribute to breathing irregularities. In this study, we use a reduced computational model to consider several dynamical regimes of KF activity paired with different input sources to determine which combinations are compatible with known experimental observations. We further build on these findings to identify possible interactions between the KF and other components of the respiratory neural circuitry. Specifically, we present two models that both simulate eupnoeic as well as RTT-like breathing phenotypes. Using nullcline analysis, we identify the types of inhibitory inputs to the KF leading to RTT-like respiratory patterns and suggest possible KF local circuit organizations. When the identified properties are present, the two models also exhibit quantal acceleration of late-expiratory activity, a hallmark of active expiration featuring forced exhalation, with increasing inhibition to KF, as reported experimentally. Hence, these models instantiate plausible hypotheses about possible KF dynamics and forms of local network interactions, thus providing a general framework as well as specific predictions for future experimental testing. KEY POINTS: The Kölliker-Fuse nucleus (KF), a part of the parabrachial complex, is involved in regulating normal breathing and controlling active abdominal expiration during increased ventilation. Dysfunction in KF neuronal activity is thought to contribute to respiratory abnormalities seen in Rett syndrome (RTT). This study utilizes computational modelling to explore different dynamical regimes of KF activity and their compatibility with experimental observations. By analysing different model configurations, the study identifies inhibitory inputs to the KF that lead to RTT-like respiratory patterns and proposes potential KF local circuit organizations. Two models are presented that simulate both normal breathing and RTT-like breathing patterns. These models provide testable hypotheses and specific predictions for future experimental investigations, offering a general framework for understanding KF dynamics and potential network interactions.

Sleep breathing patterns and neurocognitive function in a diverse Hispanic/Latino cohort

AbstractBackgroundSleep disorders are common in patients with Alzheimer’s Disease (AD). Obstructive sleep apnea (OSA), characterized by intermittent cessation of breathing and hypoxemia, has been associated with increased risk of AD and worse cognitive function. However, the interacting effects of neurocognitive function with sleep breathing patterns, independent of the apnea‐hypopnea index, (a measure of OSA severity) have not been carefully studied. We use a novel approach to analyzing home sleep apnea data to examine breathing patterns and their relationships with neurocognitive function.MethodThe Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a prospective multicenter study of diverse Latinos. Around 16,000 diverse Hispanic/Latinos were recruited from four major metropolitan cities. Participants used an ARES unirecorder device for a single night of unsupervised at home recording. We used python package “bycycle” to cannula data (sampled at 10Hz). Bycycle uses a time domain approach to parameterizing rhythmic time‐series data. We extracted breathing rate (breaths per minute), breathing variability (interquartile range of breathing rate) and time spent in inhalation phase (percent time). Participants ages ≥45 (unweighted n = 5,957) were tested in their preferred language using a brief battery including: B‐SEVLT (3‐trials sum) and Delayed Recall (memory), World Fluency (verbal fluency), and Digit Symbol Substitution (executive function). Covariates used in our models are described in Table 1. All presented estimates were weighted for appropriate generalization to the HCHS/SOL target population.ResultIn unadjusted models, all breathing measures were negatively associated with cognitive function, but only breathing rate remained significant after full covariate adjustment (Figure 1). We found significant interactions between breathing rate and sex, as well as age for verbal fluency models. Being female and older age were associated with steeper slopes of cognitive under‐performance for both breathing rate and breathing variability (Figure 2).ConclusionThese results suggest that breathing patterns outside apneas‐hypopneas may be as critical in understanding sleep related changes and cognitive function in an aging population. Given cessation of breathing during an apnea‐hypopnea event, breathing variability may add more precision to account for varying oxygen demands. Further studies should examine whether breathing instability is also associated with cognitive decline, impairment, and dementia.

An experimental study on lung deposition of inhaled 2 μm particles in relation to lung characteristics and deposition models

BackgroundThe understanding of inhaled particle respiratory tract deposition is a key link to understand the health effects of particles or the efficiency for medical drug delivery via the lung. However, there are few experimental data on particle respiratory tract deposition, and the existing data deviates considerably when comparing results for particles > 1 μm.MethodsWe designed an experimental set-up to measure deposition in the respiratory tract for particles > 1 μm, more specifically 2.3 μm, with careful consideration to minimise foreseen errors. We measured the deposition in seventeen healthy adults (21–68 years). The measurements were performed at tidal breathing, during three consecutive 5-minute periods while logging breathing patterns. Pulmonary function tests were performed, including the new airspace dimension assessment (AiDA) method measuring distal lung airspace radius (rAiDA). The lung characteristics and breathing variables were used in statistical models to investigate to what extent they can explain individual variations in measured deposited particle fraction. The measured particle deposition was compared to values predicted with whole lung models. Model calculations were made for each subject using measured variables as input (e.g., breathing pattern and functional residual capacity).ResultsThe measured fractional deposition for 2.3 μm particles was 0.60 ± 0.14, which is significantly higher than predicted by any of the models tested, ranging from 0.37 ± 0.08 to 0.53 ± 0.09. The multiple-path particle dosimetry (MPPD) model most closely predicted the measured deposition when using the new PNNL lung model. The individual variability in measured particle deposition was best explained by breathing pattern and distal airspace radius (rAiDA) at half inflation from AiDA. All models underestimated inter-subject variability even though the individual breathing pattern and functional residual capacity for each participant was used in the model.ConclusionsWhole lung models need to be tuned and improved to predict the respiratory tract particle deposition of micron-sized particles, and to capture individual variations – a variation that is known to be higher for aged and diseased lungs. Further, the results support the hypothesis that the AiDA method measures dimensions in the peripheral lung and that rAiDA, as measured by the AiDA, can be used to better understand the individual variation in the dose to healthy and diseased lungs.

Comparative evaluation of a surface-based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms.

Four-dimensional computed tomography (4DCT), which relies on breathing-induced motion, requires realistic surrogate information of breathing variations to reconstruct the tumor trajectory and motion variability of normal tissues accurately. Therefore, the SimRT surface-guided respiratory monitoring system has been installed on a Siemens CT scanner. This work evaluated the temporal and spatial accuracy of SimRT versus our commonly used pressure sensor, AZ-733V. A dynamic thorax phantom was used to reproduce regular and irregular breathing patterns acquired by SimRT and Anzai. Various parameters of the recorded breathing patterns, including mean absolute deviations (MAD), Pearson correlations (PC), and tagging precision, were investigated and compared to ground-truth. Furthermore, 4DCT reconstructions were analyzed to assess the volume discrepancy, shape deformation and tumor trajectory. Compared to the ground-truth, SimRT more precisely reproduced the breathing patterns with a MAD range of 0.37±0.27 and 0.92±1.02mm versus Anzai with 1.75±1.54 and 5.85±3.61mm for regular and irregular breathing patterns, respectively. Additionally, SimRT provided a more robust PC of 0.994±0.009 and 0.936±0.062 for all investigated breathing patterns. Further, the peak and valley recognition were found to be more accurate and stable using SimRT. The comparison of tumor trajectories revealed discrepancies up to 7.2 and 2.3mm for Anzai and SimRT, respectively. Moreover, volume discrepancies up to 1.71±1.62% and 1.24±2.02% were found for both Anzai and SimRT, respectively. SimRT was validated across various breathing patterns and showed a more precise and stable breathing tracking, (i) independent of the amplitude and period, (ii) and without placing any physical devices on the patient's body. These findings resulted in a more accurate temporal and spatial accuracy, thus leading to a more realistic 4DCT reconstruction and breathing-adapted treatment planning.

Effectiveness of visual biofeedback-guided respiratory-correlated 4D-MRI for radiotherapy guidance on the MR-linac.

Respiratory-correlated 4D-MRI may provide motion characteristics for radiotherapy but is susceptible to irregular breathing. This study investigated the effectiveness of visual biofeedback (VBF) guidance for breathing regularization during 4D-MRI acquisitions on an MR-linac. A simultaneous multislice-accelerated 4D-MRI sequence was interleaved with a one-dimensional respiratory navigator (1D-RNAV) in 10 healthy volunteers on a 1.5T Unity MR-linac (Elekta AB, Stockholm, Sweden). Volunteer-specific breathing amplitudes and periods were derived from the 1D-RNAV signal obtained during unguided 4D-MRI acquisitions. These were used for the guidance waveform, while the 1D-RNAV positions were overlayed as VBF. VBF effectiveness was quantified by calculating the change in coefficient of variation ( ) for the breathing amplitude and period, the position SD of end-exhale, end-inhale and midposition locations, and the agreement between the 1D-RNAV signals and guidance waveforms. The 4D-MRI quality was assessed by quantifying amounts of missing data. VBF had an average latency of 520 ± 2 ms. VBF reduced median breathing variations by 18% to 35% (amplitude) and 29% to 57% (period). Median position SD reductions ranged from -3% to 35% (end-exhale), 29% to 38% (end-inhale), and 25% to 37% (midposition). Average differences between guidance waveforms and 1D-RNAV signals were 0.0 s (period) and +1.7 mm (amplitude). VBF also decreased the median amount of missing data by 11% and 29%. A VBF system was successfully implemented, and all volunteers were able to adapt to the guidance waveform. VBF during 4D-MRI acquisitions drastically reduced breathing variability but had limited effect on missing data in respiratory-correlated 4D-MRI.

Exploring beamline momentum acceptance for tracking respiratory variability in lung cancer proton therapy: a simulation study

Objective. Investigating the aspects of proton beam delivery to track organ motion with pencil beam scanning therapy. Considering current systems as a reference, specify requirements for next-generation units aiming at real-time image-guided treatments. Approach. Proton treatments for six non-small cell lung cancer (NSCLC) patients were simulated using repeated 4DCTs to model respiratory motion variability. Energy corrections required for this treatment site were evaluated for different approaches to tumour tracking, focusing on the potential for energy adjustment within beamline momentum acceptance (dp/p). A respiration-synchronised tracking, taking into account realistic machine delivery limits, was compared to ideal tracking scenarios, in which unconstrained energy corrections are possible. Rescanning and the use of multiple fields to mitigate residual interplay effects and dose degradation have also been investigated. Main results. Energy correction requirements increased with motion amplitudes, for all patients and tracking scenarios. Higher dose degradation was found for larger motion amplitudes, rescanning has beneficial effects and helped to improve dosimetry metrics for the investigated limited dp/p of 1.2% (realistic) and 2.4%. The median differences between ideal and respiratory-synchronised tracking show minimal discrepancies, 1% and 5% respectively for dose coverage (CTV V95) and homogeneity (D5-D95). Multiple-field planning improves D5-D95 up to 50% in the most extreme cases while it does not show a significant effect on V95. Significance. This work shows the potential of implementing tumour tracking in current proton therapy units and outlines design requirements for future developments. Energy regulation within momentum acceptance was investigated to tracking tumour motion with respiratory-synchronisation, achieving results in line with the performance of ideal tracking scenarios. ±5% Δp/p would allow to compensate for all range offsets in our NSCLC patient cohort, including breathing variability. However, the realistic momentum of 1.2% dp/p representative of existing medical units limitations, has been shown to preserve plan quality.

The Constrained Disorder Principle Accounts for the Variability That Characterizes Breathing: A Method for Treating Chronic Respiratory Diseases and Improving Mechanical Ventilation.

Variability characterizes breathing, cellular respiration, and the underlying quantum effects. Variability serves as a mechanism for coping with changing environments; however, this hypothesis does not explain why many of the variable phenomena of respiration manifest randomness. According to the constrained disorder principle (CDP), living organisms are defined by their inherent disorder bounded by variable boundaries. The present paper describes the mechanisms of breathing and cellular respiration, focusing on their inherent variability. It defines how the CDP accounts for the variability and randomness in breathing and respiration. It also provides a scheme for the potential role of respiration variability in the energy balance in biological systems. The paper describes the option of using CDP-based artificial intelligence platforms to augment the respiratory process's efficiency, correct malfunctions, and treat disorders associated with the respiratory system.