Clinical analysis of the “small plateau” sign on the flow-volume curve followed by deep learning automated recognition

Background Small plateau (SP) on the flow-volume curve was found in parts of patients with suspected asthma or upper airway abnormalities, but it lacks clear scientific proof. Therefore, we aimed to characterize its clinical features. Methods We involved patients by reviewing the bronchoprovocation test (BPT) and bronchodilator test (BDT) completed between October 2017 and October 2020 to assess the characteristics of the sign. Patients who underwent laryngoscopy were assigned to perform spirometry to analyze the relationship of the sign and upper airway abnormalities. SP-Network was developed to recognition of the sign using flow-volume curves. Results Of 13,661 BPTs and 8,168 BDTs completed, we labeled 2,123 (15.5%) and 219 (2.7%) patients with the sign, respectively. Among them, there were 1,782 (83.9%) with the negative-BPT and 194 (88.6%) with the negative-BDT. Patients with SP sign had higher median FVC and FEV1% predicted (both P < .0001). Of 48 patients (16 with and 32 without the sign) who performed laryngoscopy and spirometry, the rate of laryngoscopy-diagnosis upper airway abnormalities in patients with the sign (63%) was higher than those without the sign (31%) (P = 0.038). SP-Network achieved an accuracy of 95.2% in the task of automatic recognition of the sign. Conclusions SP sign is featured on the flow-volume curve and recognized by the SP-Network model. Patients with the sign are less likely to have airway hyperresponsiveness, automatic visualizing of this sign is helpful for primary care centers where BPT cannot available.

Regulation and Intervention of Intracranial Pressure

Intracranial pressure is the total amount of pressure exerted by the brain, blood and cerebrocinal fluid in the rigid cranial space. Compliance is an indicator of the brain's tolerance for increased ICP, when compliance is exceeded, there will be a dramatic increase in the pressure/volume curve so that ICP will increase rapidly. In the injured brain, cerebral blood flow (CBF) is regulated to supply sufficient oxygen and substrates to the brain. Certain physiological factors such as hypercarbia, acidosis and hypoxemia cause vasodilation which causes an increase in CBF, seizure activity and fever will increase the level of brain metabolism and CBF. Cerebral edema is the most common cause of non-traumatic brain injury such as central nervous system infections, metabolic and systemic encephalopathy. Vasogenic brain edema occurs due to injury to the blood-brain barrier and increased capillary permeability in the area around the injury, or to inflammation, especially in CNS infections. Medical management of elevated intracranial pressure includes sedation, cerebrospinal fluid drainage, and osmotherapy with either mannitol or hypertonic salts.

Insights into diastolic function analyses using cardiac magnetic resonance imaging: impact of trabeculae and papillary muscles

Background This cardiovascular magnetic resonance (CMR) study investigates the impact of trabeculae and papillary muscles (TPM) on diastolic function parameters by differentiation of the time-volume curve. Differentiation causes additional problems, which is overcome by standardization. Methods Cine steady-state free-precession imaging at 1.5 T was performed in 40 healthy volunteers stratified for age (age range 7–78y). LV time-volume curves were assessed by software-assisted delineation of endocardial contours from short axis slices applying two different methods: (1) inclusion of TPM into the myocardium and (2) inclusion of TPM into the LV cavity blood volume. Diastolic function was assessed from the differentiated time-volume curves defining the early and atrial peaks, their filling rates, filling volumes, and further dedicated diastolic measures, respectively. Results Only inclusion of TPM into the myocardium allowed precise assessment of early and atrial peak filling rates (EPFR, APFR) with clear distinction of EPFR and APFR expressed by the minimum between the early and atrial peak (EAmin) (100% vs. 36% for EAmin < 0.8). Prediction of peak filling rate ratios (PFRR) and filling volume ratios (FVR) by age was superior with inclusion of TPM into the myocardium compared to inclusion into the blood pool (r2 = 0.85 vs. r2 = 0.56 and r2 = 0.89 vs. r2 = 0.66). Standardization problems were overcome by the introduction of a third phase (mid-diastole, apart from diastole and systole) and fitting of the early and atrial peaks in the differentiated time-volume curve. Conclusions Only LV volumetry with inclusion of TPM into the myocardium allows precise determination of diastolic measures and prevents methodological artifacts.

Exploring the 175-year history of spirometry and the vital lessons it can teach us today

175 years have elapsed since John Hutchinson introduced the world to his version of an apparatus that had been in development for nearly two centuries, the spirometer. Though he was not the first to build a device that sought to measure breathing and quantify the impact of disease and occupation on lung function, Hutchison coined the terms spirometer and vital capacity that are still in use today, securing his place in medical history. As Hutchinson envisioned, spirometry would become crucial to our growing knowledge of respiratory pathophysiology, from Tiffeneau and Pinelli's work on forced expiratory volumes, to Fry and Hyatt's description of the flow–volume curve. In the 20th century, standardization of spirometry further broadened its reach and prognostic potential. Today, spirometry is recognized as essential to respiratory disease diagnosis, management and research. However, controversy exists in some of its applications, uptake in primary care remains sub-optimal and there are concerns related to the way in which race is factored into interpretation. Moving forward, these failings must be addressed, and innovations like Internet-enabled portable spirometers may present novel opportunities. We must also consider the physiologic and practical limitations inherent to spirometry and further investigate complementary technologies such as respiratory oscillometry and other emerging technologies that assess lung function. Through an exploration of the storied history of spirometry, we can better contextualize its current landscape and appreciate the trends that have repeatedly arisen over time. This may help to improve our current use of spirometry and may allow us to anticipate the obstacles confronting emerging pulmonary function technologies.

Semi-automated left ventricular endocardial detection versus hand-tracing in the measurement of left ventricular volumes and ejection fraction in daily clinical practice

Background The common method of assessing left ventricle (LV) volumes and ejection fraction (EF) is hand-tracing Biplane Simpson method. Alternatively, ultrasound vendors offer different semi-automated LV endocardial border detection software with anatomical intelligence to assess LV volumes and EF. By using speckle-tracking technique, this software tracks the LV endocardium throughout the cardiac cycle and computes the LV volumes in every image frame using the disk summation method from which a volume-curve is generated, and the EF is calculated using the maximum and minimum volumes obtained. Data on the performance of this method in comparison with the hand-tracing Biplane Simpson method in daily clinical practice is scarce. Purpose To determine the accuracy of LV volumes and EF using semi-automated LV endocardial detection tracing, and to compare the reproducibility of this method with the hand-tracing Biplane Simpson method, among operators with varying level of experience in echocardiography. Methods This was a single center retrospective observational study, conducted in year 2020. 127 patients, aged &gt;18 years, who underwent clinically indicated transthoracic echocardiography were recruited. The echocardiographic images were analyzed independently in a blinded fashion by 3 operators – a sonographer, a fellow-in-training and a cardiologist specialized in echocardiography. The LV volumes and EF were first measured using hand-tracing Biplane Simpson method, then repeated using semi-automated tracing at a different time and the operator were blinded to the initial hand-tracing measurements. Results The mean age of patients was 50±16 years, 35.4% were male, mean body surface area was 1.62±0.18m2, 92.1% were in sinus rhythm, and 61.4% had good acoustic window. Table 1 shows the LV end-diastolic volume (EDV), end-systolic volume (ESV) and EF, measured using different method, by the 3 operators. There were excellent correlation and agreement between semi-automated tracing measurements and hand-tracing measurements of LV EDV (r=0.985, LOA [mean ± 1.96 SD] 16.9 ml, ICC 0.991), ESV (r=0.990, LOA 12.7 ml, ICC 0.994) and EF (r=0.962, LOA 7.43%, ICC 0.967) by experienced cardiologist. The limit of agreement (LOA) between cardiologist and sonographer for semi-automated tracing measurement of LV EDV, ESV and EF were 29.13 ml, 19.74 ml and 9.25% respectively, which was comparable with that of hand-tracing measurement. The agreement between cardiologist and fellow-in-training for semi-automated tracing measurement of LV volumes and EF was slightly better than hand-tracing method, with a LOA of 25.60 ml, 17.48 ml and 7.08%, for EDV, ESV and EF respectively (Table 2). Conclusion In daily clinical practice, measurement of LV volumes and EF using semi-automated LV endocardial tracing method is accurate and demonstrates comparable reproducibility with hand-tracing Biplane Simpson method among operators with different level of experience in echocardiography. FUNDunding Acknowledgement Type of funding sources: None.

Automated non-invasive pressure-volume loop analysis of cardiac aging in a large cohort of healthy community dwellers

Background/Introduction Pressure-volume loops (PVloops) provide a wealth of information on cardiac function that is not readily available from cardiac imaging alone. Methods To estimate left ventricular (LV) PVloops non-invasively have been available, but have so far not been used to interrogate ventricular function in large patient cohorts, due to the complexity of estimating PVloops. A new method was recently validated that construct PVloops non-invasively from cine cardiac magnetic resonance (CMR), based on the time-varying elastance model [1]. At the same time, we have validated a framework for automated, quality controlled analysis of cine CMR in large cohorts of patients/subjects [2]. Combining these two methods could automated PVloop estimation, enabling analysis of ventricular pressure-volume relationships in large study populations. Purpose Evaluate if CMR-based non-invasive PVloops can be used to interrogate the impact of cardiac ageing on LV function occurring in a large population of healthy community dwellers. Methods Non-invasive PVloops were calculated from a full cardiac cycle LV volume curve and brachial blood pressure data using a recently validated method based on the time-varying elastance model [1], in 7,650 healthy community dwellers from the UKBiobank population study. The LV volume curve was automatically obtained using our state-of-the-art, quality controlled deep learning (DL) based cine CMR analysis framework [2]. External Work, pressure-volume-area (PVA), end-systolic pressure (Pes), ventricular elastance (Ees, an estimate of contractility) and arterial elastance (Ea) and energy per ejected volume (EEV: PVA/ stroke volume) were calculated from the PVloops. We performed univariate regression between PVloop parameters and age. We also calculated the additional impact of cardiovascular risk-factors in a multivariate analysis. Results See results in table 1. With age, LV volumes fall (p&lt;0.001) in healthy subjects, while systolic blood pressure and Pes increases (both p&lt;0.001). As a result of the higher afterload, PVA (p=0.894) and EW (p=0.499) do not significantly change with age despite a lower SV. Arterial elastance (Ea) increased, and so did contractility, as measured by Ees (p&lt;0.001). Due to all these changes, EEV increased with age (p&lt;0.001). In multivariate analysis, cardiovascular risk factors hypercholesterolemia and hypertension negatively impacted Pes, PVA, Ees and EEV. Diabetes and smoking habits did not. Conclusion Non-invasive CMR-based PVloop analyses capture the impact of known changes occurring during cardiac ageing on cardiac work, contractility and energetic expenditure. Obtaining PVloops automatically using our AI analysis system in this large cohort of healthy subjects allows to formulate reference for assessment of cardiac disease. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The authors acknowledge financial support (support) the National Institute for Health Research (NIHR) Cardiovascular MedTech Co-operative (previously existing as the Cardiovascular Healthcare Technology Co-operative 2012 - 2017) award to the Guy's and St Thomas' NHS Foundation Trust, in partnership with King's College London and the NIHR comprehensive Biomedical Research Centre of the Guy's & St Thomas' NHS Foundation Trust. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health Univariate regression analysis Example of estimated PV loop

Interactions of brain, blood, and CSF: a novel mathematical model of cerebral edema

Background Previous models of intracranial pressure (ICP) dynamics have not included flow of cerebral interstitial fluid (ISF) and changes in resistance to its flow when brain swelling occurs. We sought to develop a mathematical model that incorporates resistance to the bulk flow of cerebral ISF to better simulate the physiological changes that occur in pathologies in which brain swelling predominates and to assess the model’s ability to depict changes in cerebral physiology associated with cerebral edema. Methods We developed a lumped parameter model which includes a representation of cerebral ISF flow within brain tissue and its interactions with CSF flow and cerebral blood flow (CBF). The model is based on an electrical analog circuit with four intracranial compartments: the (1) subarachnoid space, (2) brain, (3) ventricles, (4) cerebral vasculature and the extracranial spinal thecal sac. We determined changes in pressure and volume within cerebral compartments at steady-state and simulated physiological perturbations including rapid injection of fluid into the intracranial space, hyperventilation, and hypoventilation. We simulated changes in resistance to flow or absorption of CSF and cerebral ISF to model hydrocephalus, cerebral edema, and to simulate disruption of the blood–brain barrier (BBB). Results The model accurately replicates well-accepted features of intracranial physiology including the exponential-like pressure–volume curve with rapid fluid injection, increased ICP pulse pressure with rising ICP, hydrocephalus resulting from increased resistance to CSF outflow, and changes associated with hyperventilation and hypoventilation. Importantly, modeling cerebral edema with increased resistance to cerebral ISF flow mimics key features of brain swelling including elevated ICP, increased brain volume, markedly reduced ventricular volume, and a contracted subarachnoid space. Similarly, a decreased resistance to flow of fluid across the BBB leads to an exponential-like rise in ICP and ventricular collapse. Conclusions The model accurately depicts the complex interactions that occur between pressure, volume, and resistances to flow in the different intracranial compartments under specific pathophysiological conditions. In modelling resistance to bulk flow of cerebral ISF, it may serve as a platform for improved modelling of cerebral edema and blood–brain barrier disruption that occur following brain injury.

Left Ventricular Diastolic Function Studied with Magnetic Resonance Imaging: A Systematic Review of Techniques and Relation to Established Measures of Diastolic Function

Purpose: In recent years, cardiac magnetic resonance (CMR) has been used to assess LV diastolic function. In this systematic review, studies were identified where CMR parameters had been evaluated in healthy and/or patient groups with proven diastolic dysfunction or known to develop heart failure with preserved ejection fraction. We aimed at describing the parameters most often used, thresholds where possible, and correlation to echocardiographic and invasive measurements. Methods and results: A systematic literature review was performed using the databases of PubMed, Embase, and Cochrane. In total, 3808 articles were screened, and 102 studies were included. Four main CMR techniques were identified: tagging; time/volume curves; mitral inflow quantification with velocity-encoded phase-contrast sequences; and feature tracking. Techniques were described and estimates were presented in tables. From published studies, peak change of torsion shear angle versus volume changes in early diastole (−dφ′/dV′) (from tagging analysis), early peak filling rate indexed to LV end-diastolic volume <2.1 s−1 (from LV time-volume curve analysis), enlarged LA maximal volume >52 mL/m2, lowered LA total (<40%), and lowered LA passive emptying fractions (<16%) seem to be reliable measures of LV diastolic dysfunction. Feature tracking, especially of the atrium, shows promise but is still a novel technique. Conclusion: CMR techniques of LV untwisting and early filling and LA measures of poor emptying are promising for the diagnosis of LV filling impairment, but further research in long-term follow-up studies is needed to assess the ability for the parameters to predict patient related outcomes.