Bedside Monitoring Research Articles

Application of Drainage Position Ventilation and Real- Time Bedside Monitoring in Mechanical Ventilation of Patients Infected with nCov-19

Application of Drainage Position Ventilation and Real- Time Bedside Monitoring in Mechanical Ventilation of Patients Infected with nCov-19

Coronavirus Disease 2019 Calls for Predictive Analytics Monitoring-A New Kind of Illness Scoring System.

Coronavirus disease 2019 can lead to sudden and severe respiratory failure that mandates endotracheal intubation, a procedure much more safely performed under elective rather than emergency conditions. Early warning of rising risk of this event could benefit both patients and healthcare providers by reducing the high risk of emergency intubation. Current illness severity scoring systems, which usually update only when clinicians measure vital signs or laboratory values, are poorly suited for early detection of this kind of rapid clinical deterioration. We propose that continuous predictive analytics monitoring, a new approach to bedside management, is more useful. The principles of this new practice anchor in analysis of continuous bedside monitoring data, training models on diagnosis-specific paths of deterioration using clinician-identified events, and continuous display of trends in risks rather than alerts when arbitrary thresholds are exceeded.

Monitoring Microcirculation: Utility and Barriers - A Point-of-View Review.

Microcirculation is a particular organ of the cardiovascular system. The goal of this narrative review is a critical reappraisal of the present knowledge of microcirculation monitoring, mainly focused on the videomicroscopic evaluation of sublingual microcirculation in critically ill patients. We discuss the technological developments in handheld videomicroscopy, which have resulted in adequate tools for the bedside monitoring of microcirculation. By means of these techniques, a large body of evidence has been acquired about the role of microcirculation in the pathophysiological mechanisms of shock, especially septic shock. We review the characteristics of sublingual microcirculation in septic shock, which mainly consist in a decrease in the perfused vascular density secondary to a reduction in the proportion of perfused vessels along with a high heterogeneity in perfusion. Even in patients with high cardiac output, red blood cell velocity is decreased. Thus, hyperdynamic flow is absent in the septic microcirculation. We also discuss the dissociation between microcirculation and systemic hemodynamics, particularly after shock resuscitation, and the different behavior among microvascular beds. In addition, we briefly comment the effects of some treatments on microcirculation. Despite the fact that sublingual microcirculation arises as a valuable goal for the resuscitation in critically ill patients, significant barriers remain present for its clinical application. Most of them are related to difficulties in video acquisition and analysis. We comprehensively analyzed these shortcomings. Unfortunately, a simpler approach, such as the central venous minus arterial PCO2 difference, is a misleading surrogate for sublingual microcirculation. As conclusion, the monitoring of sublingual microcirculation is an appealing method for monitoring critically ill patients. Nevertheless, the lack of controlled studies showing benefits in terms of outcome, as well as technical limitations for its clinical implementation, render this technique mainly as a research tool.

Abstract 14846: Artificial Intelligence and Clinical Stability After the Norwood Operation

Background: Postoperative management of the neonate following the Norwood operation is among the most complex and challenging in pediatric critical care. Artificial intelligence is poised to assist in management of this complex population. Methods: We developed a convolutional neural network (CNN) model trained on electrocardiogram (ECG) waveforms collected from 45 neonates after the Norwood procedure. Waveforms from the first two postoperative days (critical) and the day prior to transfer out of the ICU (stable) were used for training. The model was validated on 10 post-Norwood neonates. Models were compared to traditional machine learning algorithms on non-waveform data, heart rate variability, and then combined in a final model to optimize performance. Retrospective clinical observation scoring was completed for comparison. Results: The CNN model on 3-lead ECG yielded an area under the curve of the receiver operating characteristic (AUC-ROC) of 0.97 ( 0.02). The final model combining predictions from the CNN, random forest on vital signs, and logistic regression on pH, lactic acid, and base deficit values achieved 0.98 ( 0.02). Retrospective clinical observations agreed with the final model 78% of the time. Conclusions: Application of this novel combined machine learning model can accurately detect changes in clinical status as patients progress from critically ill to stable following the Norwood procedure, yielding impressive clinical insights from the ECG beyond what is currently possible. This work provides the basis for the development of a novel bedside monitoring tool and suggests new ways artificial intelligence may influence clinical care beyond predicting deterioration events.

Abstract 300: Detection of Hemodynamic Status Using a Novel Analytic Based Solely on a Single Ecg Waveform

Introduction: Delayed identification of hemodynamic deterioration remains a persistent issue for in-hospital patient care. Unfortunately, no continuously measured non-invasive method of detecting hemodynamic deterioration currently exists. Clinicians rely on vital signs associated with tachycardia and hypotension to identify hemodynamically unstable patients. However, the collection of non-invasive vital signs remains labor-intensive, inconsistent, and error-prone in practice. In contrast, the Analytic for Hemodynamic Instability (AHI) depends only on the continuous ECG signal from a typical bedside monitor. Hypothesis: Continuous real-time hemodynamic status obtained from the analysis of existing ECG monitor data can accurately detect the combination of hypotension and tachycardia without the need for continuous direct measurement of blood pressure. Methods: 28,348 5-minute windows of the analytic output were analyzed from 222 consecutive adult patients receiving continuous ECG and arterial line monitoring at an academic medical center. AHI outputs were compared to vital sign indication of tachycardia and hypotension in the same window. Results: The observed sensitivity and specificity of AHI compared to vital signs measurement were 95.6% and 84.9%, respectively, with an area under the curve (AUC) of 0.90 and an accuracy of 85.6%. The false-negative rate was 4.4%. The false-positive rate was 15.1%. Conclusions: The AHI derived hemodynamic status correlated well with vital sign derived hemodynamic status for both invasive and non-invasive methods. In patients who had their blood pressure monitored non-invasively, AHI provided continuous hemodynamic monitoring in patients who usually have vitals measured only every few hours. Footnote: The Analytic for Hemodynamic Instability is currently pending US FDA review and is not yet for sale in the US.

Assessment of Cerebral Blood Flow and Oxygen Extraction in Pediatric Sickle Cell Disease with Non-Invasive Diffuse Optical Spectroscopies

Introduction: Cerebral infarcts and associated cognitive impairments are a devastating consequence of sickle cell disease (SCD). While the underlying mechanisms are poorly understood, infarctions are thought to arise from anemia-induced microvascular perfusion abnormalities and subsequent reduced cerebrovascular reserve that is insufficient to meet tissue metabolic demands. Thus, quantification of abnormalities in microvascular cerebral blood flow (CBF) and oxygen extraction (OEF) may be useful in identifying infarct risk and monitoring therapeutic efficacy. Unfortunately, current modalities that quantify microvascular hemodynamics (e.g., PET, MRI) are prohibitively expensive, have limited availability, and require anesthesia in children <6y, making them inappropriate as routine monitoring tools. Transcranial Doppler ultrasound (TCD) is currently the standard screening tool for overt stroke risk in pediatric SCD, but it only measures blood flow velocity in the large arteries, which is a poor surrogate for microvascular perfusion in sickle cell disease. Diffuse optical spectroscopies (specifically near-infrared frequency-domain spectroscopy, FDNIRS, and diffuse correlation spectroscopy, DCS) offer a low-cost, non-invasive alternative for bedside monitoring of tissue-level OEF and CBF. We previously demonstrated that FDNIRS/DCS are sensitive to elevations in resting-state OEF and CBF in children with sickle cell disease compared to healthy controls (Lee, Neurophotonics 2019), consistent with previous studies using MRI and PET. In this feasibility study, we demonstrate these optical techniques are sensitive to altered cerebral hemodynamics in sickle patients who are 1) undergoing chronic transfusion, and 2) experiencing vaso-occlusive pain episodes (VOE). Methods: To date, we have recruited 6 pediatric patients with sickle cell disease undergoing chronic transfusion (5 females and 1 male, 6 - 14 y, mean ± std hemoglobin change pre- to post-transfusion = 1 ± 0.8 g/dL) and 4 patients admitted to the Emergency department for VOE (2 females and 2 males, 8 - 18 y, mean±std hemoglobin on admission = 8.9 ± 1.6 g/dL). For the transfusion cohort, FDNIRS/DCS measurements were made immediately prior to the start of transfusion and again immediately upon completion. For the VOE cohort, FDNIRS/DCS measurements were made upon hospital admission. For all FDNIRS/DCS assessments, a custom sensor was manually held over right and left forehead to assess oxygen extraction fraction (OEF, %) and an index of microvascular cerebral blood flow (CBFi, cm2/s) (Lee, Neurophotonics 2019). Hemispheric results were averaged to yield a mean of each measured parameter. Total measurement time was less than 15 minutes. Results: In the cohort undergoing chronic transfusion, one patient data was excluded due to poor DCS signal quality. Of the remaining 5 patients, OEF and CBFi decreased after transfusion by a median of -6.4% and -30.0%, respectively (Fig 1A, B). The FDNIRS-measured OEF decrease is comparable to previous results with MRI (Guilliams, Blood 2017) that quantified both cortical OEF and CBF response to transfusion in a similarly aged cohort. However, the DCS-measured CBFi decrease is more prominent than previously reported (30% vs. 9%). The enhanced sensitivity of DCS to CBF in sickle cell disease was reported in our recent study and is likely attributed to the confounding influences of hematocrit on the DCS-measured CBFi (Sathialingam, Biomed Opt Exp 2020). In the cohort measured during VOE, one patient data was excluded due to poor FDNIRS data quality. Of the remaining 3 subjects, OEF was elevated compared to healthy controls and was on the upper range of values measured in a cohort of otherwise subjects with sickle cell disease who were without clinical complications and were measured as part of a separate study (Fig. 1C). Conclusion: These data demonstrate how FDNIRS/DCS may be used as a simple, low-cost tool for bedside assessment of cerebral hemodynamics in non-sedated sickle children that could be used to track brain health over time, particularly during periods thought to be prone to hemodynamic instability like transfusion or VOEs. Although ~20% of data was discarded in this dataset due to improper sensor positioning leading to poor signal quality, we have recently implemented real-time quality control feedback to ensure our data passes quality criteria. Disclosures Lam: Sanguina, Inc: Current equity holder in private company.

Influence of current injection scheme on electrical impedance tomography for monitoring of the respiratory function of obese subjects

Electrical impedance tomography (EIT) has been proposed as a noninvasive radiation-free functional imaging modality for bedside monitoring of lung ventilation. Due to the intrinsic low sensitivity of measured boundary voltages with respect to internal conductivity changes, EIT image reconstructions are more challenging for the regions that are located deeper from the attached surface electrodes. Considering the worldwide prevalence of obesity, it is highly desirable for an EIT system to produce high-quality images from obese as well as lean subjects. In EIT, the internal current density distribution and the sensitivity of a boundary voltage to a change of internal conductivity vary with respect to the current injection scheme. We quantified the range of measured boundary voltages subject to a chosen current injection scheme and investigated the influence of various obesity levels on the number of distinguishable boundary voltages given a fixed amount of system noise. We found that the 0-skip current injection scheme, where neighboring electrode pairs are used for current injections, could be most favorable to improve spatial resolution but produces the smallest number of distinguishable boundary voltages. To obtain an enough number of distinguishable boundary voltages from an obese subject, the gap between current injection electrodes should be increased depending on the circumference of a chosen imaging plane. We suggested a guideline for current injection schemes in EIT to produce images with better quality from obese as well as lean subjects.

Hardware challenges with an anticoagulation strategy guided by detection of atrial fibrillation by an implantable loop recorder

Abstract Background A “pill-in-the-pocket” anticoagulation strategy, guided by ECG data from an implantable loop recorder (ILR), has been advocated as a clinical strategy. However, a fundamental requirement is the ability to reliably obtain daily ECG data from patients. Objective To determine the reliability of daily ECG data transfer from ILRs. Methods We evaluated patients implanted with an ILR in whom we sought to withhold oral anticoagulation (OAC) unless atrial fibrillation (AF) was detected. The ILR transmits data nightly to a bedside monitor. Once received, the data are sent to a central server. Over the course of a month, we tracked for each patient whether ECG data were received by the server. Results The study included 170 AF patients with an ILR where we planned to withhold OAC unless AF was documented. Daily ECG data were automatically transmitted and retrievable in only 36 (21%) patients. Two (1%) pts had not a single day of connectivity, 6 (4%) pts were connected <7 days, and 16 (9%) pts were connected <14 days. Wireless connectivity was lost for >48 hours in 89 (52%) patients (Figure). Most patients experienced multiple reasons for data transmission failure within the month. Conclusions To determine whether an ILR guided OAC strategy is feasible, reliable daily transmission of ECG data is a fundamental prerequisite. Current technology facilitated daily ECG data transfer in only 1/5 of patients. In the remaining, there was either extended loss of connectivity or no connectivity at all. A “pill-in-the-pocket” anticoagulation approach is currently difficult given existing hardware limitations. Funding Acknowledgement Type of funding source: None

Precision Medicine in Neonates: Future Perspectives for the Lung.

Bronchopulmonary dysplasia (BPD) is the most common complication of pre-term birth with long lasting sequelae. Since its first description more than 50 years ago, many large randomized controlled trials have been conducted, aiming to improve evidence-based knowledge on the optimal strategies to prevent and treat BPD. However, most of these intervention studies have been performed on a population level without regard for the variation in clinical and biological diversity (e.g., gestational age, ethnicity, gender, or disease progression) between patients that is driven by the complex interaction of genetic pre-disposition and environmental exposures. Nevertheless, clinicians provide daily care such as lung protective interventions on an individual basis every day despite the fact that research supporting individualized or precision medicine for monitoring or treating pre-term lungs is immature. This narrative review summarizes four potential developments in pulmonary research that might facilitate the process of individualizing lung protective interventions to prevent development of BPD. Electrical impedance tomography and electromyography of the diaphragm are bedside monitoring tools to assess regional changes in lung volume and ventilation and spontaneous breathing effort, respectively. These non-invasive tools allow a more individualized optimization of invasive and non-invasive respiratory support. Investigation of the genomic variation in caffeine metabolism in pre-term infants can be used to optimize and individualize caffeine dosing regimens. Finally, volatile organic compound analysis in exhaled breath might accurately predict BPD at an early stage of the disease, enabling clinicians to initiate preventive strategies for BPD on an individual basis. Before these suggested diagnostic or monitoring tools can be implemented in daily practice and improve individualized patient care, future research should address and overcome their technical difficulties, perform extensive external validation and show their additional value in preventing BPD.

Portable, consumer-grade pulse oximeters are accurate for home and medical use: Implications for use in the COVID-19 pandemic and other resource-limited environments.

ObjectiveTo determine the correlation between 3 lightweight portable pulse oximeter devices compared to a standard wall mount pulse oximetry device.MethodsWe performed a single‐center, prospective, observational study of 4 pulse oximetry devices, 3 of which are commercially available to the public. A convenience sample of 200 emergency department (ED) patients with chief complaints of cardiopulmonary origin or a peripheral capillary oxygen saturation ≤ 94 percent were enrolled. Analysis of variance was performed to compare SpO2s and test characteristics of the 3 devices compared to control.ResultsAlthough differences in measured SpO2s were observed (P < 0.001) across groups, the differences were small (mean differences ranged from 1.00% to 1.87%). The correlation between test devices and the control were high (r range 0.70–0.79). Although the test characteristics were not perfect, the devices did have good sensitivity using a cutoff value of 94% (sensitivity ranging from 90% to 92%), which improved with lower SpO2 cutoff values to 92% (sensitivity ranging from 96% to 97%).ConclusionThe 3 commercially available devices were accurate enough to be clinically useful when compared to a hospital bedside monitor pulse oximeter. Consumer‐grade portable pulse oximeters may be useful if overwhelming numbers of patients require oxygen saturation monitoring, such as during the COVID‐19 pandemic.

A Retrospective Analysis of Children and Adolescents With Diabetic Ketoacidosis in the Intensive Care Unıt: Is It Significant that the Blood Ketone Level Becomes Negative in Diabetic Ketoacidosis?

Introduction: Diabetic ketoacidosis (DKA) is the most common cause of acute morbidity and mortality in children and adolescents with type 1 diabetes mellitus (T1DM). Because DKA management is associated with complications, endocrine communities have published guidelines and attempted to set standards for DKA diagnosis and management worldwide. In this study, for the patients followed up in the intensive care unit who have been treated according to DKA protocols, clinical and laboratory characteristics, differences between new and old diagnosed patients, and results of treatment were evaluated.Methods: The records of 67 patients hospitalized in the pediatric intensive care unit for the past two years were reviewed retrospectively. Patients were grouped as newly diagnosed and old diagnosed diabetics.Results: The mean age of the patients was 8.66 ± 5.0 years (3 months to 17.9 years) and 39 (58.2%) were male. Forty-five patients (67.1%) presented with mild DKA and 22 (33.9%) with severe DKA. Fourteen (63.6%) of the severe DKA cases were newly diagnosed with T1DM. Six patients had hyponatremia (corrected serum Na level <135 mmol/L) and five had hypernatremia (serum Na level >145 mmol/L). Only one of the hyponatremic patients had severe acidosis, while four of the hypernatremic patients had severe acidosis. At the 14th hour, blood glucose levels were below 200 mg/dl, blood ketones became negative in 5.8 hours, and at 9.1 hours, blood pH and/or HCO3 levels were normalized, recovery criteria were completed, and subcutaneous (SC) insulin injection was started. Of the patients, 38 (56.7) were newly diagnosed with T1DM. The mean age of newly diagnosed T1DM patients was smaller (7.40 ± 4.96) than those with old diagnosis, respiratory rates (RRs) were higher and pCO2 levels were lower on admission. Blood glucose, blood ketone negativity, acidosis, and Glasgow coma score (GCS) scores of the newly diagnosed T1DM patients improved later than the previous diagnoses. Only one patient under two years of age with a pH of 6.89 was given HCO3. None of the patients had symptomatic brain edema and death.Conclusions: As a result, DKA is an acute and serious complication of diabetes, whose results are promising when managed only with minimal individual changes according to guidelines. Bicarbonate administration is not needed except in patients with very severe acidosis. Bedside blood ketone monitoring seems to be important because it allows for early enteral feeding.

A noninvasive flexible conformal sensor for accurate real-time monitoring of local cerebral edema based on electromagnetic induction.

Cerebral edema (CE) is a non-specific pathological swelling of the brain secondary to any type of neurological injury. The real-time monitoring of focal CE mostly found in early stage is of great significance to reduce mortality and disability. Magnetic Induction Phase Shift (MIPS) is expected to achieve non-invasive continuous monitoring of CE. However, most existing MIPS sensors are made of hard materials which makes it difficult to accurately retrieve CE information. In this article, we designed a conformal two-coil structure and a single-coil structure, and studied their sensitivity map using finite element method (FEM). After that, the conformal MIPS sensor that is preferable for local CE monitoring was fabricated by flexible printed circuit (FPC). Next, physical experiments were conducted to investigate its performance on different levels of simulated CE solution volume, measurement distance, and bending. Subsequently, 14 rabbits were chosen to establish CE model and another three rabbits were selected as controls. The 24-hour MIPS real-time monitoring experiments was carried out to verify that the feasibility. Results showed a gentler attenuation trend of the conformal two-coil structure, compared with the single-coil structure. In addition, the novel flexible conformal MIPS sensor has a characteristic of being robust to bending according to the physical experiments. The results of animal experiments showed that the sensor can be used for CE monitoring. It can be concluded that this flexible conformal MIPS sensor is desirable for local focusing measurement of CE and subsequent multidimensional information extraction for predicting model. Also, it enables a much more comfortable environment for long-time bedside monitoring.

Creating 12-lead electrocardiogram waveforms using a three-lead bedside monitor to ensure appropriate monitoring.

How do you place the three electrodes to create waveforms for leads I, II, III, aVR, aVL, aVF, and V1-V6?

Excess cerebral oxygen delivery follows return of spontaneous circulation in near-term asphyxiated lambs

Hypoxic-ischaemia renders the neonatal brain susceptible to early secondary injury from oxidative stress and impaired autoregulation. We aimed to describe cerebral oxygen kinetics and haemodynamics immediately following return of spontaneous circulation (ROSC) and evaluate non-invasive parameters to facilitate bedside monitoring. Near-term sheep fetuses [139 ± 2 (SD) days gestation, n = 16] were instrumented to measure carotid artery (CA) flow, pressure, right brachial arterial and jugular venous saturation (SaO2 and SvO2, respectively). Cerebral oxygenation (crSO2) was measured using near-infrared spectroscopy (NIRS). Following induction of severe asphyxia, lambs received cardiopulmonary resuscitation using 100% oxygen until ROSC, with oxygen subsequently weaned according to saturation nomograms as per current guidelines. We found that oxygen consumption did not rise following ROSC, but oxygen delivery was markedly elevated until 15 min after ROSC. CrSO2 and heart rate each correlated with oxygen delivery. SaO2 remained > 90% and was less useful for identifying trends in oxygen delivery. CrSO2 correlated inversely with cerebral fractional oxygen extraction. In conclusion, ROSC from perinatal asphyxia is characterised by excess oxygen delivery that is driven by rapid increases in cerebrovascular pressure, flow, and oxygen saturation, and may be monitored non-invasively. Further work to describe and limit injury mediated by oxygen toxicity following ROSC is warranted.

Toward Monocyte HLA-DR Bedside Monitoring: A Proof-of-Concept Study.

Decreased expression of human leukocyte antigen-DR on monocytes (mHLA-DR) is recognized as the most appropriate marker for the monitoring of immune alterations in septic patients and critically ill subjects. Its measurement has been established for years by flow cytometry, but remains under-used due to pre-analytical constraints. The objectives of the present work were to develop a rapid and robust one-step protocol. A novel, simplified protocol has been developed to measure mHLA-DR in whole blood using flow cytometry. It is a one-step procedure that includes red cell lysis, antibodies, and fixative reagents. It has been compared to the standardized routine protocol in two consecutive cohorts of septic shock patients (n = 37). Finally, the protocol was applied to a few subjects in point-of-care settings, by collecting capillary blood from fingerpricks. Strong correlation was observed between the one-step method and routine protocol in 24 patients. After testing several stabilizing agents, the procedure was further optimized by adding a low-dose formaldehyde to the stain and lyse solution. This improved method was tested in a second cohort of 13 patients, and again strongly correlated to the routine protocol. Finally, the fingerprick and venous puncture samples were shown to provide similar results. The present work demonstrates the feasibility of a bedside protocol for flow cytometry measurement of mHLA-DR in critically ill subjects. This helps overcome pre-analytical constraints previously identified, which have limited wider use of this biomarker in intensive care units. In addition, preliminary results from fingerprick samples are promising.

Temporal Differential Expression of Physiomarkers Predicts Sepsis in Critically Ill Adults.

Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes. Our primary objective was to develop artificial intelligence capable of predicting sepsis earlier using a minimal set of streaming physiological data in real time. A total of 29,552 adult patients were admitted to the intensive care unit across five regional hospitals in Memphis, Tenn, over 18 months from January 2017 to July 2018. From these, 5,958 patients were selected after filtering for continuous (minute-by-minute) physiological data availability. A total of 617 (10.4%) patients were identified as sepsis cases, using the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria. Physiomarkers, a set of signal processing features, were derived from five physiological data streams including heart rate, respiratory rate, and blood pressure (systolic, diastolic, and mean), captured every minute from the bedside monitors. A support vector machine classifier was used for classification. The model accurately predicted sepsis up to a mean and 95% confidence interval of 17.4 ± 0.22 h before sepsis onset, with an average test accuracy of 83.0% (average sensitivity, specificity, and area under the receiver operating characteristics curve of 0.757, 0.902, and 0.781, respectively). This study demonstrates that salient physiomarkers derived from continuous bedside monitoring are temporally and differentially expressed in septic patients. Using this information, minimalistic artificial intelligence models can be developed to predict sepsis earlier in critically ill patients.

Failure to rescue: A quality indicator for postoperative care.

Postoperative complications occur despite optimal perioperative care and are an important driver of mortality after surgery. Failure to rescue, defined as death in a patient who has experienced serious complications, has emerged as a quality metric that provides a mechanistic pathway to explain disparities in mortality rates among hospitals that have similar perioperative complication rates. The risk of failure to rescue is higher after invasive surgical procedures and varies according to the type of postoperative complication. Multiple patient factors have been associated with failure to rescue. However, failure to rescue is more strongly correlated with hospital factors. In addition, microsystem factors, such as institutional safety culture, teamwork, and other attitudes and behaviors may interact with the hospital resources to effectively prevent patient deterioration. Early recognition through bedside and remote monitoring is the first step toward prevention of failure to rescue followed by rapid response initiatives and timely escalation of care.

Deep learning model for ultrafast quantification of blood flow in diffuse correlation spectroscopy.

Diffuse correlation spectroscopy (DCS) is increasingly used in the optical imaging field to assess blood flow in humans due to its non-invasive, real-time characteristics and its ability to provide label-free, bedside monitoring of blood flow changes. Previous DCS studies have utilized a traditional curve fitting of the analytical or Monte Carlo models to extract the blood flow changes, which are computationally demanding and less accurate when the signal to noise ratio decreases. Here, we present a deep learning model that eliminates this bottleneck by solving the inverse problem more than 2300% faster, with equivalent or improved accuracy compared to the nonlinear fitting with an analytical method. The proposed deep learning inverse model will enable real-time and accurate tissue blood flow quantification with the DCS technique.

Use of 2.1 MHz MRI scanner for brain imaging and its preliminary results in stroke

Cerebral stroke greatly contributes to death and disability rates in China and the whole world. Effective non-invasive imaging device for bedside monitoring of stroke is critically needed in clinically. This study developed a lightweight (350 kg) and low-footprint magnetic resonance imaging (MRI) system for brain imaging. Static magnetic field was built using an H-typed permanent magnet, which has 50.9 mT magnetic field strength (corresponding to 2.167 MHz proton Larmor frequency). Biplanar gradient coils were designed using the target field method based on dipole equivalent. Radio-frequency coils were optimized by particle swarm optimization. The 2 MHz MRI system was deployed in the Department of Neurology of hospital to test its performance in stroke imaging detection. Gradient recall echo and fast spin echo sequences were utilized to acquire T1- and T2-weighted MR images, respectively. Brain images of a healthy volunteer, a patient with hemorrhagic stroke, a patient of ischemic stroke, and a patient with ischemic stroke and images from 17-day long-term monitoring of hemorrhagic stroke were obtained with a 1.5 mm * 2.0 mm spatial resolution in plane, and a 10 mm thickness.

Optical coherence tomography for fast bedside imaging, assessment and monitoring of autoimmune inflammatory skin diseases?

Optical coherence tomography (OCT) is a non-invasive, high-resolution imaging technique with a growing impact in dermatology. The principle of OCT is comparable to that of sonography, except that it uses infrared laser light instead of ultrasound waves. It has been clinically demonstrated that OCT is suitable for discriminating between different types of non-melanoma skin cancer at an early stage of disease. Optical coherence tomography generates two- or three-dimensional images of up to 2mm penetration depth, a field of view of 6mm × 6mm, and an acquisition time of seconds. The resolution capability of OCT is more than 3 to 100 times higher than that of ultrasound imaging. It is of particular interest that the additional information on vasculature provided by OCT angiography enables the assessment and monitoring of inflammatory skin diseases. The use of OCT to locate exact blister levels was demonstrated for diagnosing autoimmune bullous diseases. It is anticipated that detection of subclinical lesions could indicate a relapse of the disease. In the future, this could enable intervention and early treatment. Furthermore, the development of high-speed OCT could allow fast scanning and bedside imaging of large body sites.