Automatic Detection and Tracking of Anatomical Landmarks in Transesophageal Echocardiography for Quantification of Left Ventricular Function.

OBJECTIVE: Evaluation of left ventricular (LV) function in critical care patients is useful for guidance of therapy and early detection of LV dysfunction, but the tools currently available are too time-consuming. To resolve this issue, we previously proposed a method for the continuous and automatic quantification of global LV function in critical care patients based on the detection and tracking of anatomical landmarks on transesophageal heart ultrasound. In the present study, our aim was to improve the performance of mitral annulus detection in transesophageal echocardiography (TEE). METHODS: We investigated several state-of-the-art networks for both the detection and tracking of the mitral annulus in TEE. We integrated the networks into a pipeline for automatic assessment of LV function through estimation of the mitral annular plane systolic excursion (MAPSE), called autoMAPSE. TEE recordings from a total of 245 patients were collected from St. Olav's University Hospital and used to train and test the respective networks. We evaluated the agreement between autoMAPSE estimates and manual references annotated by expert echocardiographers in 30 Echolab patients and 50 critical care patients. Furthermore, we proposed a prototype of autoMAPSE for clinical integration and tested it in critical care patients in the intensive care unit. RESULTS: Compared with manual references, we achieved a mean difference of 0.8 (95% limits of agreement: -2.9 to 4.7) mm in Echolab patients, with a feasibility of 85.7%. In critical care patients, we reached a mean difference of 0.6 (95% limits of agreement: -2.3 to 3.5) mm and a feasibility of 88.1%. The clinical prototype of autoMAPSE achieved real-time performance. CONCLUSION: Automatic quantification of LV function had high feasibility in clinical settings. The agreement with manual references was comparable to inter-observer variability of clinical experts.

Generating 3D images of material microstructures from a single 2D image: a denoising diffusion approach.

Three-dimensional (3D) images provide a comprehensive view of material microstructures, enabling numerical simulations unachievable with two-dimensional (2D) imaging alone. However, obtaining these 3D images can be costly and constrained by resolution limitations. We introduce a novel method capable of generating large-scale 3D images of material microstructures, such as metal or rock, from a single 2D image. Our approach circumvents the need for 3D image data while offering a cost-effective, high-resolution alternative to existing imaging techniques. Our method combines a denoising diffusion probabilistic model with a generative adversarial network framework. To compensate for the lack of 3D training data, we implement chain sampling, a technique that utilizes the 3D intermediate outputs obtained by reversing the diffusion process. During the training phase, these intermediate outputs are guided by a 2D discriminator. This technique facilitates our method's ability to gradually generate 3D images that accurately capture the geometric properties and statistical characteristics of the original 2D input. This study features a comparative analysis of the 3D images generated by our method, SliceGAN (the current state-of-the-art method), and actual 3D micro-CT images, spanning a diverse set of rock and metal types. The results shown an improvement of up to three times in the Frechet inception distance score, a typical metric for evaluating the performance of image generative models, and enhanced accuracy in derived properties compared to SliceGAN. The potential of our method to produce high-resolution and statistically representative 3D images paves the way for new applications in material characterization and analysis domains.

Correction: Teacher-student approach for lung tumor segmentation from mixed-supervised datasets.

[This corrects the article DOI: 10.1371/journal.pone.0266147.].

Real-time feedback on chest compression efficacy by hands-free carotid Doppler in a porcine model.

Aim: Current guidelines for cardiopulmonary resuscitation (CPR) recommend a one-size-fits-all approach in relation to the positioning of chest compressions. We recently developed RescueDoppler, a hands-free Doppler ultrasound device for continuous monitoring of carotid blood flow velocity during CPR. The aim of the present study is to investigate whether RescueDoppler via real-time hemodynamic feedback, could identify both optimal and suboptimal compression positions. Methods: In this model of animal cardiac arrest, we induced ventricular fibrillation in five domestic pigs. Manual chest compressions were performed for ten seconds at three different positions on the sternum in random order and repeated six times. We analysed Time Average Velocity (TAV) with chest compression position as a fixed effect and animal, position, and sequential time within animals as random effects. Furthermore, we compared TAV to invasive blood pressure from the contralateral carotid artery. Results: We were able to detect changes in TAV when altering positions. The positions with the highest (range 19 to 48 cm/s) and lowest (6-25 cm/s) TAV were identified in all animals, with corresponding peak pressure 50-81 mmHg, and 46-64 mmHg, respectively. Blood flow velocity was, on average, highest at the middle position (TAV 33 cm/s), but with significant variability between animals (SD 2.8) and positions within the same animal (SD 9.3). Conclusion: RescueDoppler detected TAV changes during CPR with alternating chest compression positions, identifying the position yielding maximal TAV. Future clinical studies should investigate if RescueDoppler can be used as a real-time hemodynamical feedback device to guide compression position.

Automatic assessment of left ventricular function for hemodynamic monitoring using artificial intelligence and transesophageal echocardiography.

We have developed a method to automatically assess LV function by measuring mitral annular plane systolic excursion (MAPSE) using artificial intelligence and transesophageal echocardiography (autoMAPSE). Our aim was to evaluate autoMAPSE as an automatic tool for rapid and quantitative assessment of LV function in critical care patients. In this retrospective study, we studied 40 critical care patients immediately after cardiac surgery. First, we recorded a set of echocardiographic data, consisting of three consecutive beats of midesophageal two- and four-chamber views. We then altered the patient's hemodynamics by positioning them in anti-Trendelenburg and repeated the recordings. We measured MAPSE manually and used autoMAPSE in all available heartbeats and in four LV walls. To assess the agreement with manual measurements, we used a modified Bland-Altman analysis. To assess the precision of each method, we calculated the least significant change (LSC). Finally, to assess trending ability, we calculated the concordance rates using a four-quadrant plot. We found that autoMAPSE measured MAPSE in almost every set of two- and four-chamber views (feasibility 95%). It took less than a second to measure and average MAPSE over three heartbeats. AutoMAPSE had a low bias (0.4 mm) and acceptable limits of agreement (- 3.7 to 4.5 mm). AutoMAPSE was more precise than manual measurements if it averaged more heartbeats. AutoMAPSE had acceptable trending ability (concordance rate 81%) during hemodynamic alterations. In conclusion, autoMAPSE is feasible as an automatic tool for rapid and quantitative assessment of LV function, indicating its potential for hemodynamic monitoring.

Segmental myocardial viability by echocardiography at rest.

BACKGROUND: Myocardial viability assessment adds value to the therapeutic decision-making of patients with ischemic heart disease. In this feasibility study, we investigated whether established echocardiographic measurements of post-systolic shortening (PSS), strain, strain rate and wall motion score (WMS) can discover viable myocardial segments. Our hypothesis is that non-viable myocardial segments are both akinetic and without PSS. METHODS: The study population consisted of 26 examinations strictly selected by visible dysfunction. We assessed WMS, strain by speckle tracking and strain rate by tissue Doppler. The segments (16*26 = 416) were categorized into either normokinetic/hypokinetic or akinetic/dyskinetic and whether there was PSS. The reference method was the presence of scar with segmental percentage volume scar fraction >50%, detected by late gadolinium-enhanced cardiovascular magnetic resonance. Agreement with echocardiography was evaluated by Kappa coefficient. RESULTS: WMS had Kappa coefficient 0.43 (sensitivity 99%, specificity 35%). Kappa coefficient of strain was 0.28 (sensitivity 98%, specificity 23%). By combining PSS in akinetic segments with WMS and strain, the Kappa coefficient was 0.06 and 0.08 respectively. CONCLUSION: Segmental viability was best shown by the presence of systolic function. Post-systolic shortening adds no value to the assessment of segmental myocardial viability.

Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings.

Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular complications. The standard of care for cardiac monitoring performed by trained cardiologists and anesthesiologists involves a manual and qualitative evaluation of ultrasound imaging, which is a time-demanding and resource-intensive process with intraobserver- and interobserver variability. In practice, such measures can only be performed a limited number of times during the intervention. To overcome these difficulties, this study presents a robust method for automatic and quantitative monitoring of cardiac function based on 3D transesophageal echocardiography (TEE) B-mode ultrasound recordings of the left ventricle (LV). Such an assessment obtains consistent measurements and can produce a near real-time evaluation of ultrasound imagery. Hence, the presented method is time-saving and results in increased accessibility. The mitral annular plane systolic excursion (MAPSE), characterizing global LV function, is estimated by landmark detection and cardiac view classification of two-dimensional images extracted along the long-axis of the ultrasound volume. MAPSE estimation directly from 3D TEE recordings is beneficial since it removes the need for manual acquisition of cardiac views, hence decreasing the need for interference by physicians. Two convolutional neural networks (CNNs) were trained and tested on acquired ultrasound data of 107 patients, and MAPSE estimates were compared to clinically obtained references in a blinded study including 31 patients. The proposed method for automatic MAPSE estimation had low bias and low variability in comparison to clinical reference measures. The method accomplished a mean difference for MAPSE estimates of (-0.16±1.06) mm. Thus, the results did not show significant systematic errors. The obtained bias and variance of the method were comparable to inter-observer variability of clinically obtained MAPSE measures on 2D TTE echocardiography. The novel pipeline proposed in this study has the potential to enhance cardiac monitoring in perioperative- and intensive care settings.

Continuous monitoring of cerebral blood flow during general anaesthesia in infants.

Background: General anaesthesia is associated with neurocognitive deficits in infants after noncardiac surgery. Disturbances in cerebral perfusion as a result of systemic hypotension and impaired autoregulation may be a potential cause. Our aim was to study cerebral blood flow (CBF) velocity continuously during general anaesthesia in infants undergoing noncardiac surgery and compare variations in CBF velocity with simultaneously measured near-infrared spectroscopy (NIRS), blood pressure, and heart rate. Methods: NeoDoppler, a recently developed ultrasound system, was used to monitor CBF velocity via the anterior fontanelle during induction and maintenance of general anaesthesia until the start of surgery, and during recovery. NIRS, blood pressure, and heart rate were monitored simultaneously and synchronised with the NeoDoppler measurements. Results: Thirty infants, with a median postmenstrual age at surgery of 37.6 weeks (range 28.6-60.0) were included. Compared with baseline, the trend curves showed a decrease in CBF velocity during induction and maintenance of anaesthesia and returned to baseline values during recovery. End-diastolic velocity decreased in all infants during anaesthesia, on average by 59%, whereas peak systolic- and time-averaged velocities decreased by 26% and 45%, respectively. In comparison, the reduction in mean arterial pressure was only 20%. NIRS values were high and remained stable. When adjusting for mean arterial pressure, the significant decrease in end-diastolic velocity persisted, whereas there was only a small reduction in peak systolic velocity. Conclusions: Continuous monitoring of CBF velocity using NeoDoppler during anaesthesia is feasible and may provide valuable information about cerebral perfusion contributing to a more targeted haemodynamic management in anaesthetised infants.

Hands-free continuous carotid Doppler ultrasound for detection of the pulse during cardiac arrest in a porcine model.

Background/Purpose: Pulse palpation is an unreliable method for diagnosing cardiac arrest. To address this limitation, continuous hemodynamic monitoring may be a viable solution. Therefore, we developed a novel, hands-free Doppler system, RescueDoppler, to detect the pulse continuously in the carotid artery. Methods: In twelve pigs, we evaluated RescueDopplers potential to measure blood flow velocity in three situations where pulse palpation of the carotid artery was insufficient: (1) systolic blood pressure below 60 mmHg, (2) ventricular fibrillation (VF) and (3) pulseless electrical activity (PEA). (1) Low blood pressure was induced using a Fogarty balloon catheter to occlude the inferior vena cava. (2) An implantable cardioverter-defibrillator induced VF. (3) Myocardial infarction after microembolization of the left coronary artery caused True-PEA. Invasive blood pressure was measured in the contralateral carotid artery. Time-averaged blood flow velocity (TAV) in the carotid artery was related to mean arterial pressure (MAP) in a linear mixed model. Results: RescueDoppler identified pulsatile blood flow in 41/41 events with systolic blood pressure below 60 mmHg, with lowest blood pressure of 19 mmHg. In addition the absence of spontaneous circulation was identified in 21/21 VF events and true PEA in 2/2 events. The intraclass correlation coefficient within animals for TAV and MAP was 0.94 (95% CI. 0.85-0.98). Conclusions: In a porcine model, RescueDoppler reliably identified pulsative blood flow with blood pressures below 60 mmHg. During VF and PEA, circulatory arrest was rapidly and accurately demonstrated. RescueDoppler could potentially replace unreliable pulse palpation during cardiac arrest and cardiopulmonary resuscitation.

Automated tissue Doppler imaging for identification of occluded coronary artery in patients with suspected non-ST-elevation myocardial infarction.

PURPOSE: Identification of regional dysfunction is important for early risk stratification in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). Strain echocardiography enables quantification of segmental myocardial deformation. However, the clinical use is hampered by time-consuming manual measurements. We aimed to evaluate whether an in-house developed software for automated analysis of segmental myocardial deformation based on tissue Doppler imaging (TDI) could predict coronary occlusion in patients with suspected NSTEMI. METHODS: Eighty-four patients with suspected NSTEMI were included in the analysis. Echocardiography was performed at admission. Strain, strain rate and post-systolic shortening index (PSI) were analyzed by the automated TDI-based tool and the ability to predict coronary occlusion was assessed. For comparison, strain measurements were performed both by manual TDI-based analyses and by semi-automatic speckle tracking echocardiography (STE). All patients underwent coronary angiography. RESULTS: Seventeen patients had an acute coronary occlusion. Global strain and PSI by STE were able to differentiate occluded from non-occluded culprit lesions (respectively - 15.0% vs. -17.1%, and 8.1% vs. 5.1%, both p-values < 0.05) and identify patients with an acute coronary occlusion (AUC 0.66 for both strain and PSI). Measurements of strain, strain rate and PSI based on TDI were not significantly different between occluded and non-occluded territories. CONCLUSION: Automated measurements of myocardial deformation based on TDI were not able to identify acute coronary occlusion in patients with suspected NSTEMI. However, this study confirms the potential of strain by STE for early risk stratification in patients with chest pain.

Teacher-student approach for lung tumor segmentation from mixed-supervised datasets.

PURPOSE: Cancer is among the leading causes of death in the developed world, and lung cancer is the most lethal type. Early detection is crucial for better prognosis, but can be resource intensive to achieve. Automating tasks such as lung tumor localization and segmentation in radiological images can free valuable time for radiologists and other clinical personnel. Convolutional neural networks may be suited for such tasks, but require substantial amounts of labeled data to train. Obtaining labeled data is a challenge, especially in the medical domain. METHODS: This paper investigates the use of a teacher-student design to utilize datasets with different types of supervision to train an automatic model performing pulmonary tumor segmentation on computed tomography images. The framework consists of two models: the student that performs end-to-end automatic tumor segmentation and the teacher that supplies the student additional pseudo-annotated data during training. RESULTS: Using only a small proportion of semantically labeled data and a large number of bounding box annotated data, we achieved competitive performance using a teacher-student design. Models trained on larger amounts of semantic annotations did not perform better than those trained on teacher-annotated data. Our model trained on a small number of semantically labeled data achieved a mean dice similarity coefficient of 71.0 on the MSD Lung dataset. CONCLUSIONS: Our results demonstrate the potential of utilizing teacher-student designs to reduce the annotation load, as less supervised annotation schemes may be performed, without any real degradation in segmentation accuracy.

Advances in Low-Density Flexible Polyurethane Foams by Optimized Incorporation of High Amount of Recycled Polyol.

An industrially manufactured recycled polyol, obtained by acidolysis process, was for the first time proved to be a possible replacement of the reference fossil-based polyol in a low-density formulation suitable for industrial production of flexible polyurethane foams. The influence of increasing recycled polyol amounts on the properties of the polyurethane foam has been studied, also performing foam emission tests to evaluate the environmental impact. Using 10 pbw recycled polyol in the standard formulation, significant differences of the physical properties were not observed, but increase of the recycled polyol amount to 30 pbw led to a dramatic decrease of the foam air flow and a very tight foam. To overcome this drawback, N,N'-bis[3-(dimethylamino)propyl]urea was selected as tertiary amine catalyst, enabling the preservation of foam properties even at high recycled polyol level (30 pbw). Foam emission data demonstrated that this optimized foam formulation also led to an important reduction of volatile organic compounds. The results open the way for further optimization studies in low-density flexible polyurethane foam formulations, to increase the reutilization of the polyurethane waste and reduce the amount of petroleum-based raw materials.

Feasibility and Reliability of Automatic Quantitative Analyses of Mitral Annular Plane Systolic Excursion by Handheld Ultrasound Devices: A Pilot Study.

OBJECTIVES: Handheld ultrasound devices (HUDs) have previously been limited to grayscale imaging without options for left ventricle (LV) quantification. We aimed to study the feasibility and reliability of automatic measurements of mitral annular plane systolic excursion (MAPSE) by HUDs. METHODS: An algorithm that automatically measured MAPSE from live grayscale recordings was implemented in a HUD. Twenty patients at a university hospital were examined by either a cardiologist or a sonographer. Standard echocardiography using a high-end scanner was performed. The apical 4-chamber view was recorded 4 times by both echocardiography and the HUD. MAPSE was measured by M-mode and color tissue Doppler (cTD) during echocardiography and automatically by the HUD. RESULTS: The automatic method underestimated mean MAPSE ± SD versus M-mode (9.6 ± 2.2 versus 10.9 ± 2.6 mm; difference, 1.2 ± 1.4 mm, P < .005). The difference between the automatic and cTD measurements was not significant (0.8 ± 1.8 mm; P = .073). The intraclass correlation coefficients (ICCs) between automatic and M-mode measurements was 0.85, and 0.81 for cTD measurements. There was good agreement between the methods, and the intra- and inter-rater ICCs were excellent for all methods (≥0.86). CONCLUSIONS: In this novel study evaluating automatic quantification of LV longitudinal function by HUD, we showed the high feasibility and reliability of the method. Compared to M-mode imaging, the automatic method underestimated MAPSE by 8% to 10%, but the difference with cTD imaging was nonsignificant. We conclude that this study's method for automatic quantitative assessment of LV function can be integrated in HUDs.

Recovery of Flexible Polyurethane Foam Waste for Efficient Reuse in Industrial Formulations.

Ester polyurethane (PU) foam waste was reacted at atmospheric pressure in an autoclave and using microwaves with diethylene glycol (DEG) at different PU/DEG ratios in the presence of diethanolamine as a catalyst to find the glycolysis conditions that allow for the improved recovery of the PU foam waste and enable the recycling of the whole glycolysis product in foam formulations suitable for industrial application. The recycled polyol was characterized by dynamic viscosity, hydroxyl number, water content, and density, while thermal stability was assessed using thermogravimetric analysis. In the PU foam formulation, 1% and 5% of the glycolyzed material was reused. The relationship between the reuse level of the recycled polyol and the physical properties of the foam was thoroughly investigated. It was observed that both hardness and air flow decreased with increasing recycled polyol content, particularly for the polyester type foam, while tensile strength and compression strength increased. Depending on the amount of recycled polyol and catalyst used, polyether-based foams could be obtained with a low air permeability, needed in special applications as sealed foams, or with higher air permeability desirable for comfort PU foams. The results open the way for further optimization studies of industrial polyurethane foam formulations using a glycolysis process without any separation stage.

No evidence of cardiac stunning or decoupling immediately after cardiopulmonary bypass for elective coronary surgery.

BACKGROUND: There is significant uncertainty regarding the timing of onset of cardiovascular stunning after cardiac surgery. Cardiovascular stunning is affecting both contractility (Ees) and arterial load. Arterial load may be represented by arterial elastance (Ea) and participates in ventriculo-arterial coupling through the Ea/Ees ratio, giving information on efficiency and performance. An alternative approach to ventriculo-arterial interaction is oscillatory power fraction (OPF). The aim of this study was to investigate the immediate beat-to-beat effects of on-pump coronary artery bypass graft (CABG) surgery on contractility, cardiac power parameters, arterial load and ventriculo-arterial coupling as well as classical haemodynamic parameters. METHODS: We included 41 patients scheduled for fast-track CABG surgery. Measurements were taken before and after cardiopulmonary bypass. A flow and pressure curve were recorded from transoesophageal pulsed wave Doppler and a radial artery catheter, respectively. This enabled the calculation of stroke work, total cardiac energy delivery, OPF and Ea/Ees ratio. Routine haemodynamic monitoring provided the classical haemodynamic parameters. RESULTS: Immediately after cardiopulmonary bypass there was no firm evidence for alterations in contractility, stroke work, stroke volume or arterial elastance. Ea/Ees ratio and OPF remained unchanged. CONCLUSIONS: There was no evidence for clinically relevant cardiac stunning or altered arterial load immediately after cardiopulmonary bypass for CABG surgery. The unchanged Ea/Ees ratio and OPF are indicating unchanged cardiac efficiency before and after cardiopulmonary bypass. This indicates that in elective CABG patients cardiovascular stunning is perhaps a phenomenon of inflammation and not immediate ischaemia-reperfusion injury or mechanical handling.

Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging.

PURPOSE: Accurate lung cancer diagnosis is crucial to select the best course of action for treating the patient. From a simple chest CT volume, it is necessary to identify whether the cancer has spread to nearby lymph nodes or not. It is equally important to know precisely where each malignant lymph node is with respect to the surrounding anatomical structures and the airways. In this paper, we introduce a new data-set containing annotations of fifteen different anatomical structures in the mediastinal area, including lymph nodes of varying sizes. We present a 2D pipeline for semantic segmentation and instance detection of anatomical structures and potentially malignant lymph nodes in the mediastinal area. METHODS: We propose a 2D pipeline combining the strengths of U-Net for pixel-wise segmentation using a loss function dealing with data imbalance and Mask R-CNN providing instance detection and improved pixel-wise segmentation within bounding boxes. A final stage performs pixel-wise labels refinement and 3D instance detection using a tracking approach along the slicing dimension. Detected instances are represented by a 3D pixel-wise mask, bounding volume, and centroid position. RESULTS: We validated our approach following a fivefold cross-validation over our new data-set of fifteen lung cancer patients. For the semantic segmentation task, we reach an average Dice score of 76% over all fifteen anatomical structures. For the lymph node instance detection task, we reach 75% recall for 9 false positives per patient, with an average centroid position estimation error of 3 mm in each dimension. CONCLUSION: Fusing 2D networks' results increases pixel-wise segmentation results while enabling good instance detection. Better leveraging of the 3D information and station mapping for the detected lymph nodes are the next steps.

Adaptive Spectral Envelope Estimation for Doppler Ultrasound.

Estimation of accurate maximum velocities and spectral envelope in ultrasound Doppler blood flow spectrograms are both essential for clinical diagnostic purposes. However, obtaining accurate maximum velocity is not straightforward due to intrinsic spectral broadening and variance in the power spectrum estimate. The method proposed in this paper for maximum velocity point detection has been developed by modifying an existing method-signal noise slope intersection, incorporating in it steps from an altered version of another method called geometric method. Adaptive noise estimation from the spectrogram ensures that a smooth spectral envelope is obtained postdetection of these maximum velocity points. The method has been tested on simulated Doppler signal with scatterers possessing a parabolic flow velocity profile constant in time, steady and pulsatile string phantom recordings, as well as in vivo recordings from uterine, umbilical, carotid, and subclavian arteries. The results from simulation experiments indicate a bias of less than 2.5% in maximum velocities when estimated for a range of peak velocities, Doppler angles, and SNR levels. Standard deviation in the envelope is low-less than 2% in the case of experiments done by varying the peak velocity and Doppler angle for steady phantom and simulated flow, and also less than 2% in the case of experiments done by varying SNR but keeping constant flow conditions for in vivo and simulated flow. Low variability in the envelope makes the prospect of using the envelope for automated blood flow measurements possible and is illustrated for the case of pulsatility index estimation in uterine and umbilical arteries.

Three-dimensional echocardiography in the evaluation of global and regional function in patients with recent myocardial infarction: a comparison with magnetic resonance imaging.

We aimed to compare three-dimensional (3D) and two-dimensional (2D) echocardiography in the evaluation of patients with recent myocardial infarction (MI), using late-enhancement magnetic resonance imaging (LE-MRI) as a reference method. Echocardiography and LE-MRI were performed approximately 1 month after first-time MI in 58 patients. Echocardiography was also performed on 35 healthy controls. Left ventricular (LV) ejection fraction by 3D echocardiography (3D-LVEF), 3D wall-motion score (WMS), 2D-WMS, 3D speckle tracking-based longitudinal, circumferential, transmural and area strain, and 2D speckle tracking-based longitudinal strain (LS) were measured. The global correlations to infarct size by LE-MRI were significantly higher (P < 0.03) for 3D-WMS and 2D-WMS compared with 3D-LVEF and the 4 different measurements of 3D strain, and 2D global longitudinal strain (GLS) was more closely correlated to LE-MRI than 3D GLS (P < 0.03). The segmental correlations to infarct size by LE-MRI were also significantly higher (P < 0.04) for 3D-WMS, 2D-WMS, and 2D LS compared with the other indices. Three-dimensional WMS showed a sensitivity of 76% and a specificity of 72% for identification of LV infarct size >12%, and a sensitivity of 73% and a specificity of 95% for identification of segments with transmural infarct extension. Three-dimensional WMS and 2D gray-scale echocardiography showed the strongest correlations to LE-MRI. The tested 3D strain method suffers from low temporal and spatial resolution in 3D acquisitions and added diagnostic value could not be proven.

Strain rate imaging combined with wall motion analysis gives incremental value in direct quantification of myocardial infarct size.

BACKGROUND: The study aimed to evaluate the diagnostic accuracy of a new method for direct echocardiographic quantification of the myocardial infarct size, using late enhancement magnetic resonance imaging (LE-MRI) as a reference method. METHODS AND RESULTS: Echocardiography and LE-MRI were performed on average 31 days after first-time myocardial infarction in 58 patients. Echocardiography was also performed on 35 healthy controls. Direct echocardiographic quantification of the infarct size was based on automated selection and quantification of areas with hypokinesia and akinesia from colour-coded strain rate data, with manual correction based on visual wall motion analysis. The left ventricular (LV) ejection fraction, speckle-tracking-based longitudinal global strain, wall motion score index (WMSI), longitudinal systolic motion and velocity, and the ratio of early mitral inflow velocity to mitral annular early diastolic velocity were also measured by echocardiography. The area under the receiver-operating characteristic curves for the identification of the infarct size >12% by LE-MRI was 0.84, using the new method for direct echocardiographic quantification of the infarct size. The new method showed significantly a higher correlation with the infarct size by LE-MRI both at the global (r = 0.81) and segmental (r = 0.59) level compared with other indices of LV function. CONCLUSION: Direct quantification of the percentage infarct size by strain rate imaging combined with wall motion analysis yields high diagnostic accuracy and better correlation to LE-MRI compared with other echocardiographic indices of global LV function. Echocardiography performed ~1 month after myocardial infarction showed ability to identify the patients with the infarct size >12%.

Comparison of a new methodology for the assessment of 3D myocardial strain from volumetric ultrasound with 2D speckle tracking.

An alternative approach to extract 3D myocardial strain based on elastic registration of the ultrasound images (3DSE) was developed by our lab. The aim of the present study was to test its clinical performance by comparing strain values obtained by 3DSE with the ones obtained with 2D speckle tracking (2DST). Standard 2D B-mode and volumetric datasets were acquired in 12 patients with coronary heart disease (CHD) and in 12 control subjects. Longitudinal (ε(LL)), circumferential (ε(CC)) and radial (ε(RR)) strain values were obtained from 2D datasets using commercially available 2DST software and from volumetric datasets using the 3DSE approach. 3DSE provided lower strain values than 2DST. With both approaches global ε(LL) and ε(CC) were significantly lower in patients with CHD than in controls. Global ε(LL) and ε(CC) correlated well between both methods (R = 0.83, R = 0.86, respectively), while segmental correlations were moderate [R = 0.63 (ε(LL)), R = 0.41 (ε(CC))]. The highest differences in ε(LL) values obtained by the two methods and the highest number of erroneous ε(LL) with 3DSE were observed in the basal LV segments. This study shows that in real-life datasets our 3DSE method provides global and regional ε(LL) and ε(CC) values that are comparable with the ones obtained from 2DST, even though they are not interchangeable with each other. As only a single acquisition is required, 3D methods may offer advantages over the current 2D techniques. However, the accuracy of the 3DSE can still be improved by solving the problems that appear with deformation estimation in the basal segments.