Quantification Of Infarction Research Articles

Detection, Isolation and Quantification of Myocardial Infarct with Four Different Histological Staining Techniques.

The precise quantification of myocardial infarction is crucial for evaluating therapeutic strategies. We developed a robust, color-based semi-automatic algorithm capable of infarct region detection, isolation and quantification with four different histological staining techniques, and of the isolation and quantification of diffuse fibrosis in the heart. Our method is developed based on the color difference in the infarct and non-infarct regions after histological staining. Mouse cardiac tissues stained with Masson's trichrome (MTS), hematoxylin and eosin (H&E), 2,3,5-Triphenyltetrazolium chloride and picrosirius red were included to demonstrate the performance of our method. We demonstrate that our algorithm can effectively identify and produce a clear visualization of infarct tissue in the four staining techniques. Notably, the infarct region on an H&E-stained tissue section can be clearly visualized after processing. The MATLAB-based program we developed holds promise for infarct quantification. Additionally, our program can isolate and quantify diffuse fibrotic elements from an MTS-stained cardiac section, which suggests the algorithm's potential for evaluating pathological cardiac fibrosis in diseased cardiac tissues. We demonstrate that this color-based algorithm is capable of accurately identifying, isolating and quantifying cardiac infarct regions with different staining techniques, as well as diffuse and patchy fibrosis in MTS-stained cardiac tissues.

Detection, Isolation and Quantification of Myocardial Infarct with Four Different Histological Staining Techniques.

Precise quantification of myocardial infarction is crucial for evaluating the therapeutic strategies. We developed a robust, color-based semi-automatic algorithm capable of infarct region detection, isolation and quantification with four different histological staining techniques, and the isolation and quantification of diffuse fibrosis in the heart. Our method is developed based on the color difference in the infarct and non-infarct regions after histological staining. Mouse cardiac tissues stained with Masson's trichrome (MTS), hematoxylin and eosin (H&E), 2,3,5-Triphenyltetrazolium chloride and picrosirius red were included to demonstrate the performance of our method. We demonstrate that our algorithm can effectively identify and produce a clear visualization of infarct tissue for the four staining techniques. Notably, the infarct region on a H&E-stained tissue section can be clearly visualized after processing. The MATLAB-based program we developed holds promise in the infarct quantification. Additionally, our program can isolate and quantify the diffuse fibrotic elements from an MTS-stained cardiac section, which suggested the algorithm's potential for evaluating pathological cardiac fibrosis in diseased cardiac tissues. In conclusion, we demonstrate that this color-based algorithm is capable of accurately identifying, isolating and quantifying cardiac infarct regions with different staining techniques, as well as the diffuse and patchy fibrosis in MTS-stained cardiac tissues.

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue

BackgroundInfarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to in vivo stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections. MethodsThree rat ischemic stroke cohorts were used in this study (Total n = 91 rats; Cohort 1 n = 21, Cohort 2 n = 40, Cohort 3 n = 30). For each, brains were serially-sliced, stained with TTC and scanned on both anterior and posterior sides. Ground truth annotation and infarct morphometric analysis (e.g., brain-Vbrain, infarct-Vinfarct, and non-infarct-Vnon-infarct volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development (n = 3 training cases with 36 slices [18 anterior and posterior faces], n = 18 testing cases with 218 slices [109 anterior and posterior faces]), as well as infarct morphometrics automation. The infarct quantification pipeline and pre-trained model were packaged as a standalone software and applied to Cohort 2, an internal validation dataset. Finally, software and model trainability were tested as a use-case with Cohort 3, a dataset from a separate institute. ResultsBoth high segmentation and statistically significant quantification performance (correlation between manual and software) were observed across all datasets. Segmentation performance: Cohort 1 brain accuracy = 0.95/f1-score = 0.90, infarct accuracy = 0.96/f1-score = 0.89; Cohort 2 brain accuracy = 0.97/f1-score = 0.90, infarct accuracy = 0.97/f1-score = 0.80; Cohort 3 brain accuracy = 0.96/f1-score = 0.92, infarct accuracy = 0.95/f1-score = 0.82. Infarct quantification (cohort average): Vbrain (ρ = 0.87, p < 0.001), Vinfarct (0.92, p < 0.001), Vnon-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarct:non-infact ratio (ρ = 0.92, p < 0.001). ConclusionTectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.

MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images.

Myocardial infarction (MI) occurs when an artery supplying blood to the heart is abruptly occluded. The "gold standard" method for imaging MI is cardiovascular magnetic resonance imaging (MRI) with intravenously administered gadolinium-based contrast (with damaged areas apparent as late gadolinium enhancement [LGE]). However, no "gold standard" fully automated method for the quantification of MI exists. In this work, we propose an end-to-end fully automatic system (MyI-Net) for the detection and quantification of MI in MRI images. It has the potential to reduce uncertainty due to technical variability across labs and the inherent problems of data and labels. Our system consists of four processing stages designed to maintain the flow of information across scales. First, features from raw MRI images are generated using feature extractors built on ResNet and MoblieNet architectures. This is followed by atrous spatial pyramid pooling (ASPP) to produce spatial information at different scales to preserve more image context. High-level features from ASPP and initial low-level features are concatenated at the third stage and then passed to the fourth stage where spatial information is recovered via up-sampling to produce final image segmentation output into: (i) background, (ii) heart muscle, (iii) blood and (iv) LGE areas. Our experiments show that the model named MI-ResNet50-AC provides the best global accuracy (97.38%), mean accuracy (86.01%), weighted intersection over union (IoU) of 96.47%, and bfscore of 64.46% for the global segmentation. However, in detecting only LGE tissue, a smaller model, MI-ResNet18-AC, exhibited higher accuracy (74.41%) than MI-ResNet50-AC (64.29%). New models were compared with state-of-the-art models and manual quantification. Our models demonstrated favorable performance in global segmentation and LGE detection relative to the state-of-the-art, including a four-fold better performance in matching LGE pixels to contours produced by clinicians.

Effects of Image Size on Deep Learning

In this work, the best size for late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) images in the training dataset was determined to optimize deep learning training outcomes. Non-extra pixel and extra pixel interpolation algorithms were used to determine the new size of the LGE-MRI images. A novel strategy was introduced to handle interpolation masks and remove extra class labels in interpolated ground truth (GT) segmentation masks. The expectation maximization, weighted intensity, a priori information (EWA) algorithm was used for the quantification of myocardial infarction (MI) in automatically segmented LGE-MRI images. Arbitrary threshold, comparison of the sums, and sums of differences are methods used to estimate the relationship between semi-automatic or manual and fully automated quantification of myocardial infarction (MI) results. The relationship between semi-automatic and fully automated quantification of MI results was found to be closer in the case of bigger LGE MRI images (55.5% closer to manual results) than in the case of smaller LGE MRI images (22.2% closer to manual results).

Abstract WP213: The Effect Of Nicotine Withdrawal On Stroke Outcome In Female Rats

Significance: Smoking-derived nicotine (N) is known to synergistically magnify the risk and severity of cerebral ischemia in females. Most importantly, smoking is the one preventable risk factor and giving up smoking reduces the risk for cerebral ischemia. However, how long the harmful effects of N on the brain persist after women stop smoking is unknown. In a laboratory study using an animal model of cerebral ischemia, we demonstrated that N alters brain energy metabolism and thus exacerbates ischemic brain damage. Therefore, the current study aims to investigate how long after N withdrawal (NW) N toxicity on brain energy metabolism persists and its impact on stroke outcomes in female rats. Methods: Female Sprague-Dawley rats (n=8/group) were randomly exposed to either saline or N (4.5 mg/kg) for 16-21 days after which point, they were withdrawn from N exposure and able to recover for 0, 15, or 30 days. These rats were then randomly assigned to either have their cortical tissue collected for global metabolomic (Metabolon Inc) and Western blot analysis or undergo a sham surgery or transient middle-cerebral artery occlusion (tMCAO; 90 min). Post-stroke cognition was tested with contextual fear conditioning at month following tMCAO, subsequently the brains were collected for infarct quantification. Results: Analysis of the metabolomics data revealed an increase in carbohydrate metabolites in the 30-day NW group when compared to the N-exposed group, suggesting persistence of N toxicity in the brain. Furthermore, fear conditioning data revealed a significantly lower freezing time in all NW groups when compared to the saline group implying that spatial memory deficits persist even after 30 days of NW. Lastly, the observed infarct volume was 26%(p&lt;0.05), 25%(p&lt;0.05), and 16%(p&lt;0.05) higher in the 0, 15, and 30 day NW groups respectively, when compared to the saline group. Conclusion: Even after 30 days of NW, N-induced global metabolomic changes in the brain persist and may be responsible for increased ischemic brain damage as well as cognitive deficits in female rats.

Comprehensive Phenotypic Characterization of Late Gadolinium Enhancement Predicts Sudden Cardiac Death in Coronary Artery Disease

BackgroundLate gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD). ObjectivesThe authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD). MethodsPatients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD. ResultsOf 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell’s C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell’s C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models. ConclusionsComprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD.

4D strain analysis in murine echocardiography facilitates quantification of myocardial infarction

Abstract Introduction and rationale Myocardial infarction (MI) can be surgically induced in mice. Accurate measurement of infarction size (IS) is regularly used as an experimental readout. Established methods for IS consist of macroscopic or histological staining of the left ventricle (LV). These methods do not allow for further molecular analysis and do not characterize the functional state of the LV. Echocardiographic analysis of the LV is often performed in MI studies, yet most studies rely on 2D-B-Mode or M-Mode imaging. Here, the extent of the infarction can easily be misjudged. Therefore, we wanted to develop a new strategy to reliably estimate IS in echocardiography. Methods and results Echocardiography was performed at baseline conditions and 7 days after MI induction using a Vevo 3100 sonography device with a MX550S transducer (slice thickness for 4D datasets: 150μm). For 4D strain analysis, a custom-made software tool was used to trace the endocardial surface of the LV. The method was checked for inter-observer reliability which was excellent for volumetry and estimation of systolic function (correlation of ejection fraction between observers: r=0.9414, p&amp;lt;0.0001). Surface area strain was computed and the area that displayed a surface area strain &amp;gt;−10% was considered infarcted. IS measured by 4D surface area strain was correlated with ejection fraction (r=−0.510, p=0.002) and IS estimated by triphenyl tetrazolium chloride staining (r=0.582, p=0.005). Conclusion 4D strain analysis based estimation of IS is a reliable method for functional and morphological characterization of infarcted hearts. Other than established IS measurements, it allows for additional molecular analyses within the same individuum and can be used to monitor growth or reduction of the akinetic area over time. It therefore emerges as a powerful tool for murine MI studies. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): DFG - GRK 2407 (360043781)

Infarct quantification with cardiovascular magnetic resonance using "standard deviation from remote" is unreliable: validation in multi-centre multi-vendor data

BackgroundThe objective of the study was to investigate variability and agreement of the commonly used image processing method “n-SD from remote” and in particular for quantifying myocardial infarction by late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR). LGE-CMR in tandem with the analysis method “n-SD from remote” represents the current reference standard for infarct quantification. This analytic method utilizes regions of interest (ROIs) and defines infarct as the tissue with a set number of standard deviations (SD) above the signal intensity of remote nulled myocardium. There is no consensus on what the set number of SD is supposed to be. Little is known about how size and location of ROIs and underlying signal properties in the LGE images affect results. Furthermore, the method is frequently used elsewhere in medical imaging often without careful validation. Therefore, the usage of the “n-SD” method warrants a thorough validation.MethodsData from 214 patients from two multi-center cardioprotection trials were included. Infarct size from different remote ROI positions, ROI size, and number of standard deviations (“n-SD”) were compared with reference core lab delineations.ResultsVariability in infarct size caused by varying ROI position, ROI size, and “n-SD” was 47%, 48%, and 40%, respectively. The agreement between the “n-SD from remote” method and the reference infarct size by core lab delineations was low. Optimal “n-SD” threshold computed on a slice-by-slice basis showed high variability, n = 5.3 ± 2.2.ConclusionThe “n-SD from remote” method is unreliable for infarct quantification due to high variability which depends on different placement and size of remote ROI, number “n-SD”, and image signal properties related to the CMR-scanner and sequence used. Therefore, the “n-SD from remote” method should not be used, instead methods validated against an independent standard are recommended.

In-depth phenotypic characterisation of myocardial fibrosis by cardiovascular magnetic resonance predicts sudden cardiac death in coronary heart disease: a long-term prospective outcome study

Abstract Background Prospective studies harnessing late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) afford the potential to non-invasively characterise the phenotypic substrate for sudden cardiac death (SCD) and simultaneously interrogate its mechanistic drivers. Purpose To assess the utility of infarct characterisation by CMR, including scar microstructure analysis, to predict SCD in prospectively investigated patients with coronary heart disease (CHD). Methods Patients with stable CHD were prospectively recruited into a registry between August 2009 and January 2016. The primary outcome for this study was SCD or aborted SCD. Patients with a secondary prevention implantable cardioverter defibrillator (ICD) indication were excluded. All patients had CMR with LGE imaging. Infarct quantification (core scar and peri-infarct zone [PIZ]) was performed by an independent level 3 CMR reader. Outcome events were adjudicated by a panel of cardiologists blinded to the CMR data. To investigate fibrosis microstructure, bespoke computational image processing algorithms were applied to the LGE images in order to extract specific morphological and texture related features. Results Of 437 patients (mean age 64, mean left ventricular ejection fraction [LVEF] 47%, 91% with LGE) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. Patients with higher PIZ mass had an increased risk of the primary outcome (10-year risk 0.7%, 24.0% and 37.8% for patients with PIZ mass &amp;lt;5.66g, 5.66–12.28g and ≥12.29g respectively, P&amp;lt;0.001; figure 1a). On univariable analysis, an increase in PIZ mass and core infarct mass was associated with an increased risk of the primary outcome (per gram: HR 1.12, 95% CI 1.09–1.15, P&amp;lt;0.001 and HR 1.05, 95% CI 1.04–1.06, P&amp;lt;0.001 respectively). PIZ mass and core infarct mass remained independently associated with the primary outcome after adjustment for baseline predictors (per gram: HR 1.10, 95% CI 1.06–1.14, P&amp;lt;0.001 and HR 1.04, 95% CI 1.02–1.06, P&amp;lt;0.001 respectively) and together provided incremental value compared to conventional variables in predicting the endpoint (Harrell's C-statistic 0.76 to 0.82, figure 1b-c). Bespoke analysis of imaging data identified several shape-based scar metrics that associated with the primary outcome (figure 2). These included core infarct transmurality, radiality and interface length (the latter defining the core scar-PIZ boundary length), and the number of PIZ islets. Conclusions In this large prospective study of patients with stable CHD, both PIZ mass and core infarct mass independently predicted long-term SCD risk after adjusting for conventional predictors including LVEF. Reassuringly, minimal or absent LGE portended a comparatively low risk of SCD. Analysis of the scar microstructure identified several shape-based features that associated with SCD. These results highlight a potential avenue towards a more personalised approach to ICD implantation decisions. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Lung and Heart Institute, Imperial College London

Behavioral and histopathological consequences of transient ischemic stroke in the Flinders Sensitive Line rat, a genetic animal model of depression

Patients with depression have an increased risk for stroke, higher mortality rates following stroke and worse functional outcomes among survivors. Preclinical studies may help to better understand the underlying mechanisms linking these two diseases, but only a few animal studies have investigated the effects of prestroke depression. The present study investigates whether Flinders Sensitive Line (FSL) rats, a genetic depression model, respond differently to focal ischemic stroke compared to control strains (Flinders Resistant Line [FRL] and Sprague-Dawley [SD]). Male adult FSL, FRL and SD rats received a unilateral injection of either vehicle or Endothelin-1 (ET-1) adjacent to the middle cerebral artery (MCA). Motor function was assessed at 48 h followed by euthanasia and infarct volume measurement using 2,3,5-triphenyltetrazolium chloride (TTC) staining and image analysis. In a separate cohort behavior was assessed using standard tests for motor function, locomotor activity, cognition, anxiety- and depression-like behavior beginning at 10 days post-injection followed by infarct quantification. We found that ET-1-induced MCA occlusion produced significant infarcts in all three strains. Stroke animals had slightly impaired motor function, but there was no clear interaction effects between strain and stroke surgery on behavioral outcomes. We conclude that FSL rats show no increased susceptibility to brain damage or behavioral deficits following ET-1-induced focal ischemic stroke compared to controls.

A total closed chest sheep model of cardiogenic shock by percutaneous intracoronary ethanol injection

To develop a reproducible and stable closed chest model of ischemic cardiogenic shock in sheep, with high survival rate and potential insight into human pathology. We established a protocol for multi-step myocardial alcoholisation of the left anterior descending coronary artery by percutaneous ethanol injection. A thorough hemodynamic assessment was obtained by invasive and non-invasive monitoring devices. Repeated blood samples were obtained to determine haemoglobin and alcohol concentration, electrolytes, blood gas parameters and cardiac troponin I. After sacrifice, tissue was excised for quantification of infarction and histology. Cardiogenic shock was characterized by a significant decrease in mean arterial pressure (− 33%), cardiac output (− 29%), dP/dtmax (− 28%), carotid blood flow (− 22%), left ventricular fractional shortening (− 28%), and left ventricle end-systolic pressure–volume relationship (− 51%). Lactate and cardiac troponin I levels increased from 1.4 ± 0.2 to 4.9 ± 0.7 mmol/L (p = 0.001) and from 0.05 ± 0.02 to 14.74 ± 2.59 µg/L (p = 0.001), respectively. All haemodynamic changes were stable over a three-hour period with a 71% survival rate. The necrotic volume (n = 5) represented 24.0 ± 1.9% of total ventricular mass. No sham exhibited any variation under general anaesthesia. We described and characterized, for the first time, a stable, reproducible sheep model of cardiogenic shock obtained by percutaneous intracoronary ethanol administration.

Evolution of left ventricular function among subjects with ST-elevation myocardial infarction after percutaneous coronary intervention

BackgroundAtrioventricular plane displacement (AVPD) reflects longitudinal left ventricular (LV) systolic function, and wall thickening (WT) regional radial LV function. The temporal evolution of these measures after STEMI with CMR has not been evaluated. We aimed to investigate how AVPD and WT are affected globally and regionally from the sub-acute to the chronic phase after ST-elevation myocardial infarction (STEMI).MethodsHealthy volunteers without cardiovascular disease and medication (controls, n = 20) and patients from the CHILL-MI study (NCT01379261) prospectively underwent magnetic resonance imaging (MRI) 2–6 days and 6 months after STEMI (n = 77). CHILL-MI randomized STEMI-patients to cooling therapy initiated before reperfusion or standard of care. AVPD was measured at six points in three long axis cine images and wall thickening in short axis cine images. Infarction was quantified using late gadolinium enhancement (LGE) and used to define infarct and remote segments.ResultsThere were no difference in AVPD either at acute or chronic phase (p = 0.90 and p = 0.40) or WT (p = 0.85 and p = 0.99) between patients randomized to cooling therapy and standard of care. Therefore, the results are presented for the pooled cohort. Global AVPD was decreased in both the sub-acute (12 ± 2 mm, p < 0.001) and the chronic phase (13 ± 2 mm, p < 0.001) compared to controls (15 ± 2 mm) with a partial recovery of AVPD (p < 0.001) in the chronic phase. Patients with left anterior descending (LAD) and right coronary artery (RCA) infarcts had decreased AVPD in the chronic phase in both infarcted and remote segments. Mean WT was decreased in patients with LAD infarction both in the sub-acute and the chronic phase in both infarcted and remote segments. The decrease in WT in patients with RCA and left circumflex (LCx) infarcts was more affected in the infarcted segments, especially in the chronic phase.ConclusionAVPD was a global rather than regional marker of cardiac function in this STEMI study and this may explain the prognostic importance of local measurements of mitral annular plane systolic excursion (MAPSE). The decrease in WT in remote myocardium even in the chronic phase needs to be taken into consideration when combining functional measurements with infarct quantification for diagnosis of post-ischemic stunning and hibernation.

CT Imaging of Acute Ischemic Stroke [Formula: see text

Although acute ischemic stroke remains one of the most common causes of death and disability worldwide, it is a potentially treatable condition if appropriately managed in a timely manner. The goals of acute stroke imaging include establishing a diagnosis as fast as possible with (1) accurate infarct quantification, (2) intracranial and cervical vasculature assessment, and (3) brain perfusion analysis for detection of infarct core and potentially salvageable penumbra allowing optimal patient selection for appropriate therapy. Given the extensive number of images generated from acute stroke imaging studies and as "time is brain," this article aims to highlight a logical approach for the radiologist in acute stroke computed tomography imaging in order to accurately interpret and communicate results in a timely manner.

Segmentation and quantification of infarction without contrast agents via spatiotemporal generative adversarial learning.

Accurate and simultaneous segmentation and full quantification (all indices are required in a clinical assessment) of the myocardial infarction (MI) area are crucial for early diagnosis and surgical planning. Current clinical methods remain subject to potential high-risk, nonreproducibility and time-consumption issues. In this study, a deep spatiotemporal adversarial network (DSTGAN) is proposed as a contrast-free, stable and automatic clinical tool to simultaneously segment and quantify MIs directly from the cine MR image. The DSTGAN is implemented using a conditional generative model, which conditions the distributions of the objective cine MR image to directly optimize the generalized error of the mapping between the input and the output. The method consists of the following: (1) A multi-level and multi-scale spatiotemporal variation encoder learns a coarse to fine hierarchical feature to effectively encode the MI-specific morphological and kinematic abnormality structures, which vary for different spatial locations and time periods. (2) The top-down and cross-task generators learn the shared representations between segmentation and quantification to use the commonalities and differences between the two related tasks and enhance the generator preference. (3) Three inter-/intra-tasks to label the relatedness discriminators are iteratively imposed on the encoder and generator to detect and correct the inconsistencies in the label relatedness between and within tasks via adversarial learning. Our proposed method yields a pixel classification accuracy of 96.98%, and the mean absolute error of the MI centroid is 0.96mm from 165 clinical subjects. These results indicate the potential of our proposed method in aiding standardized MI assessments.

Clinical evaluation of two dark blood methods of late gadolinium quantification of ischemic scar.

Late gadolinium enhancement (LGE) imaging was validated for diagnosis and quantification of myocardial infarction (MI). Despite good contrast between scar and normal myocardium, contrast between blood pool and myocardial scar can be limited. Dark blood LGE sequences attempt to overcome this issue. To evaluate T1 rho (T1 ρ)-prepared dark blood sequence and compare to blood nulled (BN) phase sensitive inversion recovery (PSIR) and standard myocardium nulled (MN) PSIR for detection and quantification of scar. Prospective. Thirty patients with prior MI. Patients underwent identical 1.5 T MRI protocols. Following routine LGE imaging, a slice with scar, remote myocardium, and blood pool was selected. PSIR LGE was repeated with inversion time set to MN, to BN, and T1 ρ FIDDLE (flow-independent dark-blood delayed enhancement) in random order. Three observers. Qualitative assessment of confidence scores in scar detection and degree of transmurality. Quantitative assessment of myocardial scar mass (grams), and contrast-to-noise ratio (CNR) measurements between scar, blood pool, and myocardium. Repeated-measures analysis of variance (ANOVA) with Bonferroni correction, coefficient of variation, and the Cohen κ statistic. CNRscar-blood was significantly increased for both BN (27.1 ± 10.4) and T1 ρ (30.2 ± 15.1) compared with MN (15.3 ± 8.4 P < 0.001 for both sequences). There was no significant difference in CNRscar-myo between BN (55.9 ± 17.3) and MN (51.1 ± 17.8 P = 0.512); both had significantly higher CNRscar-myo compared with the T1 ρ (42.6 ± 16.9 P = 0.007 and P = 0.014, respectively). No significant difference in scar size between LGE methods: MN (2.28 ± 1.58 g) BN (2.16 ± 1.57 g) and T1 ρ (2.29 ± 2.5 g). Confidence scores were significantly higher for BN (3.87 ± 0.346) compared with MN (3.1 ± 0.76 P < 0.001) and T1 ρ (3.20 ± 0.71 P < 0.001). PSIR with inversion time (TI) set for blood nulling and the T1 ρ LGE sequence demonstrated significantly higher scar to blood CNR compared with routine MN. PSIR with TI set for blood nulling demonstrated significantly higher reader confidence scores compared with routine MN and T1 ρ LGE, suggesting routine adoption of a BN PSIR approach might be appropriate for LGE imaging. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:146-152.

Feasibility study of a single breath-hold, 3D mDIXON pulse sequence for late gadolinium enhancement imaging of ischemic scar.

Late gadolinium enhancement (LGE) imaging is well validated for the diagnosis and quantification of myocardial infarction (MI). 2D LGE imaging involves multiple breath-holds for acquisition of short-axis slices to cover the left ventricle (LV). 3D LGE methods cover the LV in a single breath-hold; however, breath-hold duration is typically long with images susceptible to motion artifacts. To assess a single breath-hold 3D mDIXON LGE pulse sequence for image quality and quantitation of MI. Prospective. Ninety- two patients with prior MI. 1.5T cardiac MRI protocol using both conventional 2D phase sensitive inversion recovery and 3D mDIXON LGE imaging 10 minutes following contrast administration in random order to avoid bias. Data were analyzed qualitatively for image quality (three observers). Quantitative assessment of myocardial scar mass (full-width half-maximum), scar transmurality, and contrast-to-noise ratio measurements were performed. Time for 2D and 3D LGE imaging was recorded. Paired Student's t-test, Wilcoxon rank test, Cohen κ statistic, Pearson correlation, linear regression, and Bland-Altman analysis. Image quality scores were comparable between 3D and 2D LGE (1.4 ± 0.6 vs. 1.3 ± 0.5; P = 0.162). 3D LGE was associated with greater scar tissue mass (3D: 18.9 ± 17.5 g vs. 2D: 17.8 ± 16.2 g P = 0.03), although this difference was less pronounced when scar tissue was expressed as %LV mass (3D: 13.4 ± 9.9% vs. 2D: 12.7 ± 9.5% P = 0.07). For 3D vs. 2D scar mass there was a strong and significant positive correlation; Bland-Altman analysis showed mean mass bias of 1.1 g (95% confidence interval [CI]: -5.7 to 7.9). Segmental level agreement of scar transmurality between 3D and 2D LGE at the clinical viability threshold of 50% transmurality was excellent (κ = 0.870). 3D image acquisition (15.6 ± 1.4 sec) was just 5% of time required for 2D images (311.6 ± 43.2 sec) P < 0.0001. Single breath-hold 3D mDIXON LGE imaging allows quantitative assessment of MI mass and transmurality, with comparable image quality, in vastly shorter overall acquisition time compared with standard 2D LGE imaging. 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1437-1445.

Empirical Mode Decomposition and Monogenic Signal-Based Approach for Quantification of Myocardial Infarction From MR Images.

Quantification of myocardial infarction on late Gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) images into heterogeneous infarct periphery (or gray zone) and infarct core plays an important role in cardiac diagnosis, especially in identifying patients at high risk of cardiovascular mortality. However, quantification task is challenging due to noise corrupted in cardiac MR images, the contrast variation, and limited resolution of images. In this study, we propose a novel approach for automatic myocardial infarction quantification, termed DEMPOT, which consists of three key parts: Decomposition of image into intrinsic modes, monogenic phase performing on combined dominant modes, and multilevel Otsu thresholding on the phase. In particular, inspired by the Hilbert-Huang transform, we perform the multidimensional ensemble empirical mode decomposition and 2-D generalization of the Hilbert transform known as the Riesz transform on the MR image to obtain the monogenic phase that is robust to noise and contrast variation. Then, a two-stage algorithm using multilevel Otsu thresholding is accomplished on the monogenic phase to automatically quantify the myocardium into healthy, gray zone, and infarct core regions. Experiments on LGE-CMR images with myocardial infarction from 82 patients show the superior performance of the proposed approach in terms of reproducibility, robustness, and effectiveness.

4D cardiac imaging at clinical 3.0 T provides accurate assessment of murine myocardial function and viability

ObjectivesWe validate a 4D strategy tailored for 3T clinical systems to simultaneously quantify function and infarct size in wild type mice after ischemia/reperfusion, with improved spatial and temporal resolution by comparison to previous published protocols using clinical field MRI systems. MethodsC57BL/6J mice underwent 60min ischemia/reperfusion (n=14) or were controls without surgery (n=6). Twenty-four hours after surgery mice were imaged with gadolinium injection and sacrificed for post-mortem MRI and histology with serum also taken for Troponin I levels. The double ECG- and respiratory-triggered 3D FLASH (Fast Low Angle Shot) gradient echo (GRE) cine sequence had an acquired isotropic resolution of 344μm, TR/TE of 7.8/2.9ms and acquisition time 25–35min. The conventional 2D FLASH cine sequence had the same in-plane resolution of 344μm, 1mm slice thickness and TR/TE 11/5.4ms for an acquisition time of 20–25min plus 5min for planning. Left ventricle (LV) and right ventricle (RV) volumes were measured and functional parameters compared 2D to 3D, left to right and for inter and intra observer reproducibility. MRI infarct volume was compared to histology. ResultsFor the function evaluation, the 3D cine outperformed 2D cine for spatial and temporal resolution. Protocol time for the two methods was equivalent (25–35min). Flow artifacts were reduced (p=0.008) and epi/endo-cardial delineation showed good intra and interobserver reproducibility. Paired t-test comparing ejection volume left to right showed no significant difference for 3D (p=0.37), nor 2D (p=0.30) and correlation slopes of left to right EV were 1.17 (R2=0.75) for 2D and 1.05 (R2=0.50) for 3D.Quantifiable ‘late gadolinium enhancement’ infarct volume was seen only with the 3D cine and correlated to histology (R2=0.89). Left ejection fraction and MRI-measured infarct volume correlated (R2>0.3). ConclusionsThe 4D strategy, with contrast injection, was validated in mice for function and infarct quantification from a single scan with minimal slice planning.

YO-05 - Long-term contribution of Nrf2 to behavioral recovery following focal cerebral ischemia-reperfusion injury

Ischemic stroke is a leading cause of death and adult disability worldwide. The redox sensitive transcription factor Nrf2 is a key target for protection in rodent stroke models. We investigated protection afforded by 5 mg/kg dietary sulforaphane in C57BL6/J WT and Nrf2-/- adult male mice subjected to 60min middle cerebral artery occlusion and 72 h or 21 days reperfusion. Behavioural outcomes were measured and brains were sectioned for high throughput imaging and infarct quantification. SFN pretreatment improved functional rotating rod and grip strength performance, significantly reduced cresyl violet infarct volumes and upregulated HO-1 and PPARγ expression in cerebrovascular endothelium. We subsequently conducted the first long-term (>14 day) follow up studies of stroke in Nrf2-deficient and in wild-type mice subjected to long-term pretreatment with SFN (5 mg/kg/day). Basal and inducible contributions of Nrf2 to alternative activation of resident microglia and recruited macrophages, long-term cytokine expression (IL-1β, IL-6, IL-10), post-infarct neurogenesis and angiogenesis and functional recovery were investigated. Our findings highlight the translational potential of Nrf2 inducers in stroke research and establish that dietary levels of sulforaphane afford protection in rodent models of focal cerebral ischaemia.