Imaging, biomarker and invasive assessment of diffuse left ventricular myocardial fibrosis in atrial fibrillation.

BACKGROUND: Using cardiovascular magnetic resonance imaging (CMR), it is possible to detect diffuse fibrosis of the left ventricle (LV) in patients with atrial fibrillation (AF), which may be independently associated with recurrence of AF after ablation. By conducting CMR, clinical, electrophysiology and biomarker assessment we planned to investigate LV myocardial fibrosis in patients undergoing AF ablation. METHODS: LV fibrosis was assessed by T1 mapping in 31 patients undergoing percutaneous ablation for AF. Galectin-3, coronary sinus type I collagen C terminal telopeptide (ICTP), and type III procollagen N terminal peptide were measured with ELISA. Comparison was made between groups above and below the median for LV extracellular volume fraction (ECV), followed by regression analysis. RESULTS: On linear regression analysis LV ECV had significant associations with invasive left atrial pressure (Beta 0.49, P = 0.008) and coronary sinus ICTP (Beta 0.75, P < 0.001), which remained significant on multivariable regression. CONCLUSION: LV fibrosis in patients with AF is associated with left atrial pressure and invasively measured levels of ICTP turnover biomarker.

A comprehensive multi-index cardiac magnetic resonance-guided assessment of atrial fibrillation substrate prior to ablation: Prediction of long-term outcomes.

INTRODUCTION: Multiple cardiac magnetic resonance (CMR)-derived indices of atrial fibrillation (AF) substrate have been shown in isolation to predict long-term outcome following catheter ablation. Left atrial (LA) fibrosis, LA volume, LA ejection fraction (EF), left ventricular ejection fraction (LVEF), LA shape (sphericity) and pulmonary vein anatomy have all been shown to correlate with late AF recurrence. This study aimed to validate and assess the relative contribution of multiple indices in a long-term single-center study. METHODS AND RESULTS: Eighty-nine patients (53% paroxysmal AF, 73% male) underwent comprehensive CMR study before first-time AF ablation (median follow-up 726 days [IQR: 418-1010 days]). The 3D late gadolinium-enhanced acquisition (1.5T, 1.3 × 1.3 × 2 mm) was quantified for fibrosis; LA volume and sphericity were assessed on manual segmentation at atrial diastole; LAEF and LVEF were quantified on multislice cine imaging. AF recurred in 43 patients (48%) overall (31 at 1 year). In the recurrence group, LA fibrosis was higher (42% vs 29%; hazard ratio [HR]: 1.032; P = .002), left atrial ejection fraction (LAEF) lower (25% vs 34%; HR: 0.063; P = .016) and LVEF lower (57% vs 63%; HR: 0.011; P = .008). LA volume (135 vs 124 mL) and sphericity (0.819 vs 0.822) were similar. Multivariate Cox regression analysis was adjusted for age and sex (Model 1), additionally AF type (Model 2) and combined (Model 3). In Models 1 and 2, LA fibrosis, LAEF, and LVEF were independently associated with outcome, but only LA fibrosis was independent in Model 3 (HR: 1.021; P = .022). CONCLUSIONS: LAEF, LVEF, and LA fibrosis differed significantly in the AF recurrence cohort. However, on combined multivariate analysis only LA fibrosis remained independently associated with outcome.

The value of ablation parameter indices for predicting mature atrial scar formation in humans: An in vivo assessment using cardiac magnetic resonance imaging.

INTRODUCTION: The VisiTag module (CARTO3) provides an objective assessment of radiofrequency (RF) ablation parameters. This study aimed to determine the predictive value and optimal VisiTag threshold settings for prediction of gaps in mature atrial scar, as assessed non-invasively using cardiac magnetic resonance (CMR) imaging. METHODS: Twenty-four subjects (11 paroxysmal atrial fibrillation) underwent first-time RF ablation with operators blinded to VisiTag data. Three-dimensional late gadolinium enhancement (LGE) CMR scans were performed at 3 months (1.3 × 1.3 × 4 mm3 ). A survey of UK operators defined the standard VisiTag settings ("Force," 8 g; "Time," 10 seconds; "Percentage Time," 50%; "Range," 3 mm; "Impedance" and "Temperature" "off"). Each ablation procedure was exported 27 times, varying single VisiTag parameters from default values. The presence of gaps in VisiTag markers (18 sectors) was assessed for each export and compared with gaps in CMR enhancement. RESULTS: At default settings, VisiTag gaps were specific (97.5%) but less sensitive (50.4%) for CMR gaps. Sensitivity improved at higher thresholds (89.2% at 20 g, 85.6% at 30 seconds, 88.5% impedance 10 Ω, 92.8% temperature 42°C), but with a lower positive predictive value (PPV) (42.3%, 42.7%, 41.1%, and 37.7%, respectively, vs 90.9% at baseline). "Force" thresholds demonstrated stable PPV from 2 to 8 g (P = 0.24), but a rapid fall at forces more than 10 g. The binomial logistic regression model explained 41.7% of gaps; χ 2 (4), 148; P < 0.0001, correctly classifying 82% of cases (specificity 94.9%, sensitivity 56.8%). CONCLUSION: Gaps in VisiTags predict gaps in CMR LGE enhancement with high specificity at default settings. Sensitivity may be improved using more stringent thresholds but at the potential cost of unnecessary ablation, particularly when a force more than 10 g is stipulated.

Pulmonary vein encirclement using an Ablation Index-guided point-by-point workflow: cardiovascular magnetic resonance assessment of left atrial scar formation.

AIMS: A point-by-point workflow for pulmonary vein isolation (PVI) targeting pre-defined Ablation Index values (a composite of contact force, time, and power) and minimizing interlesion distance may optimize the creation of contiguous ablation lesions whilst minimizing scar formation. We aimed to compare ablation scar formation in patients undergoing PVI using this workflow to patients undergoing a continuous catheter drag workflow. METHODS AND RESULTS: Post-ablation cardiovascular magnetic resonance imaging was performed in patients undergoing 1st-time PVI using a parameter-guided point-by-point workflow (n = 26). Total left atrial scar burden and the width and continuity of the pulmonary vein encirclement were determined on analysis of atrial late gadolinium enhancement sequences. Comparison was made with a cohort of patients (n = 20) undergoing PVI using continuous drag lesions. Mean post-ablation scar burden and scar width were significantly lower in the point-by-point group than in the control group (6.6 ± 6.8% vs. 9.6 ± 5.0%, P = 0.03 and 7.9 ± 3.6 mm vs. 10.7 ± 2.3 mm, P = 0.003). More complete bilateral pulmonary vein encirclements were seen in the point-by-point group (P = 0.038). All patients achieved acute PVI. CONCLUSION: Pulmonary vein isolation using a point-by-point workflow is feasible and results in a lower scar burden and scar width with more complete pulmonary vein encirclements than a conventional drag lesion approach.

Optimization of late gadolinium enhancement cardiovascular magnetic resonance imaging of post-ablation atrial scar: a cross-over study.

BACKGROUND: Cardiovascular magnetic resonance (CMR) imaging may be used to visualize post-ablation atrial scar (PAAS), and three-dimensional late gadolinium enhancement (3D LGE) is the most widely employed technique for imaging of chronic scar. Detection of PAAS provides a unique non-invasive insight into the effects of the ablation and may help guide further ablation procedures. However, there is evidence that PAAS is often not detected by CMR, implying a significant sensitivity problem, and imaging parameters vary between leading centres. Therefore, there is a need to establish the optimal imaging parameters to detect PAAS. METHODS: Forty subjects undergoing their first pulmonary vein isolation procedure for AF had detailed CMR assessment of atrial scar: one scan pre-ablation, and two scans post-ablation at 3 months (separated by 48 h). Each scan session included ECG- and respiratory-navigated 3D LGE acquisition at 10, 20 and 30 min post injection of a gadolinium-based contrast agent (GBCA). The first post-procedural scan was performed on a 1.5 T scanner with standard acquisition parameters, including double dose (0.2 mmol/kg) Gadovist and 4 mm slice thickness. Ten patients subsequently underwent identical scan as controls, and the other 30 underwent imaging with a reduced, single, dose GBCA (n = 10), half slice thickness (n = 10) or on a 3 T scanner (n = 10). Apparent signal-to-noise (aSNR), contrast-to-noise (aCNR) and imaging quality (Likert Scale, 3 independent observers) were assessed. PAAS location and area (%PAAS scar) were assessed following manual segmentation. Atrial shells with standardised %PAAS at each timepoint were then compared to ablation lesion locations to assess quality of scar delineation. RESULTS: A total of 271 3D acquisitions (out of maximum 280, 96.7%) were acquired. Likert scale of imaging quality had high interobserver and intraobserver intraclass correlation coefficients (0.89 and 0.96 respectively), and showed lower overall imaging quality on 3 T and at half-slice thickness. aCNR, and quality of scar delineation increased significantly with time. aCNR was higher with reduced, single, dose of GBCA (p = 0.005). CONCLUSION: 3D LGE CMR atrial scar imaging, as assessed qualitatively and quantitatively, improves with time from GBCA administration, with some indices continuing to improve from 20 to 30 min. Imaging should be performed at least 20 min post-GBCA injection, and a single dose of contrast should be considered. TRIAL REGISTRATION: Trial registry- United Kingdom National Research Ethics Service 08/H0802/68 - 30th September 2008.

The reproducibility of late gadolinium enhancement cardiovascular magnetic resonance imaging of post-ablation atrial scar: a cross-over study.

BACKGROUND: Cardiovascular magnetic resonance (CMR) imaging has been used to visualise post-ablation atrial scar (PAAS), generally employing a three-dimensional (3D) late gadolinium enhancement (LGE) technique. However the reproducibility of PAAS imaging has not been determined. This cross-over study is the first to investigate the reproducibility of the technique, crucial for both future research design and clinical implementation. METHODS: Forty subjects undergoing first time ablation for atrial fibrillation (AF) had detailed CMR assessment of PAAS. Following baseline pre-ablation scan, two scans (separated by 48 h) were performed at three months post-ablation. Each scan session included 3D LGE acquisition at 10, 20 and 30 min post administration of gadolinium-based contrast agent (GBCA). Subjects were allocated at second scan post-ablation to identical imaging parameters ('Repro', n = 10), 3 T scanner ('3 T', n = 10), half-slice thickness ('Half-slice', n = 10) or half GBCA dose ('Half-gad', n = 10). PAAS was compared to baseline scar and then reproducibility was assessed for two measures of thresholded scar (% left atrial (LA) occupied by PAAS (%LA PAAS) and Pulmonary Vein Encirclement (PVE)), and then four measures of non-thresholded scar (point-by-point assessment of PAAS, four normalisation methods). Thresholded measures of PAAS were evaluated against procedural outcome (AF recurrence). RESULTS: A total of 271 3D acquisitions (out of maximum 280, 96.7%) were acquired. At 20 and 30 min, inter-scan reproducibility was good to excellent (coefficient of variation at 20 min and 30 min: %LA PAAS 0.41 and 0.20; PVE 0.13 and 0.04 respectively for 'Repro' group). Changes in imaging parameters, especially reduced GBCA dose, reduced inter-scan reproducibility, but for most measures remained good to excellent (ICC for %LA PAAS 0.454-0.825, PVE 0.618-0.809 at 30 min). For non-thresholded scar, highest reproducibility was observed using blood pool z-score normalisation technique: inter-scan ICC 0.759 (absolute agreement, 'Repro' group). There was no significant relationship between indices of PAAS and AF recurrence. CONCLUSION: PAAS imaging is a reproducible finding. Imaging should be performed at least 20 min post-GBCA injection, and a blood pool z-score should be considered for normalisation of signal intensities. The clinical implications of these findings remain to be established in the absence of a simple correlation with arrhythmia outcome. TRIAL REGISTRATION: United Kingdom National Research Ethics Service 08/H0802/68 - 30th September 2008.

Intra-cardiac and peripheral levels of biochemical markers of fibrosis in patients undergoing catheter ablation for atrial fibrillation.

AIMS: Measurement of circulating biomarkers of fibrosis may have a role in selecting patients and treatment strategy for catheter ablation. Pro-collagen type III N-terminal pro-peptide (PIIINP), C-telopeptide of type I collagen (ICTP), fibroblast growth factor 23 (FGF-23), and galectin 3 (gal-3) have all been suggested as possible biomarkers for this indication, but studies assessing whether peripheral levels reflect intra-cardiac levels are scarce. METHODS AND RESULTS: We studied 93 patients undergoing ablation for paroxysmal atrial fibrillation (AF) (n = 63) or non-paroxysmal AF (n = 30). Femoral venous, left and right atrial, and coronary sinus blood were analysed using ELISA to determine biomarker levels. Levels were compared with control patients (n = 36) and baseline characteristics, including left atrial voltage mapping data. C-telopeptide of type I collagen levels were higher in AF than in non-AF patients (P = 0.007). Peripheral ICTP levels were higher than all intra-cardiac levels (P < 0.001). Peripheral gal-3 levels were higher than left atrial levels (P = 0.001). Peripheral levels of FGF-23 and PIIINP were not significantly different from intra-cardiac levels. CS levels of ICTP were higher than right and left atrial levels (P < 0.001). gal-3 was higher in women vs. men (P ≤ 0.001) and with higher body mass index (P ≤ 0.001). ICTP levels increased with reducing ejection fraction (P ≤ 0.012). CONCLUSIONS: Atrial fibrillation patients have higher levels of circulating ICTP than matched non-AF controls. In AF ablation patients, intra-cardiac sampling of FGF-23 or PIIINP gives no further information over peripheral sampling. For gal-3 and ICTP, intra-cardiac sampling may be necessary to assess their association with intra-cardiac processes. None of the biomarkers is related to fibrosis assessed by left atrial voltage.

Biophysical Modeling Predicts Ventricular Tachycardia Inducibility and Circuit Morphology: A Combined Clinical Validation and Computer Modeling Approach.

INTRODUCTION: Computational modeling of cardiac arrhythmogenesis and arrhythmia maintenance has made a significant contribution to the understanding of the underlying mechanisms of arrhythmia. We hypothesized that a cardiac model using personalized electro-anatomical parameters could define the underlying ventricular tachycardia (VT) substrate and predict reentrant VT circuits. We used a combined modeling and clinical approach in order to validate the concept. METHODS AND RESULTS: Non-contact electroanatomic mapping studies were performed in 7 patients (5 ischemics, 2 non-ischemics). Three ischemic cardiomyopathy patients underwent a clinical VT stimulation study. Anatomical information was obtained from cardiac magnetic resonance imaging (CMR) including high-resolution scar imaging. A simplified biophysical mono-domain action potential model personalized with the patients' anatomical and electrical information was used to perform in silico VT stimulation studies for comparison. The personalized in silico VT stimulations were able to predict VT inducibility as well as the macroscopic characteristics of the VT circuits in patients who had clinical VT stimulation studies. The patients with positive clinical VT stimulation studies had wider distribution of action potential duration restitution curve (APD-RC) slopes and APDs than the patient with a negative VT stimulation study. The exit points of reentrant VT circuits encompassed a higher percentage of the maximum APD-RC slope compared to the scar and non-scar areas, 32%, 4%, and 0.2%, respectively. CONCLUSIONS: VT stimulation studies can be simulated in silico using a personalized biophysical cardiac model. Myocardial spatial heterogeneity of APD restitution properties and conductivity may help predict the location of crucial entry/exit points of reentrant VT circuits.

A randomized prospective mechanistic cardiac magnetic resonance study correlating catheter stability, late gadolinium enhancement and 3 year clinical outcomes in robotically assisted vs. standard catheter ablation.

AIMS: To prospectively compare cardiac magnetic resonance late gadolinium enhancement (LGE) findings created by standard vs. robotically assisted catheter ablation lesions and correlate these with clinical outcomes. METHODS AND RESULTS: Forty paroxysmal atrial fibrillation patients (mean age 54 ± 13.8 years) undergoing first left atrial ablation were randomized to either robotic-assisted navigation (Hansen Sensei(®) X) or standard navigation. Pre-procedural, acute (24 h post-procedure) and late (beyond 3 months) scans were performed with LGE and T2W imaging sequences and percentage circumferential enhancement around the pulmonary vein (PV) antra were quantified. Baseline pre-procedural enhancements were similar in both groups. On acute imaging, mean % encirclements by LGE and T2W signal were 72% and 80% in the robotic group vs. 60% (P = 0.002) and 76%(P = 0.45) for standard ablation. On late imaging, the T2W signal resolved to baseline in both groups. Late gadolinium enhancement remained the predominant signal with 56% encirclement in the robotic group vs. 45% in the standard group (P = 0.04). At 6 months follow-up, arrhythmia-free patients had an almost similar mean LGE encirclement (robotic 64%, standard 60%, P = 0.45) but in recurrences, LGE was higher in the robotic group (43% vs. 30%, P = 0.001). At mean 3 years follow-up, 1.3 procedures were performed in the robotic group compared with 1.9 (P < 0.001) in the standard to achieve a success rate of 80% vs. 75%. CONCLUSION: Robotically assisted ablation results in greater LGE around the PV antrum. Effective lesions created through improved catheter stability and contact force during initial treatment may have a role in reducing subsequent re-do procedures.

Cardiac magnetic resonance and electroanatomical mapping of acute and chronic atrial ablation injury: a histological validation study.

AIMS: To provide a comprehensive histopathological validation of cardiac magnetic resonance (CMR) and endocardial voltage mapping of acute and chronic atrial ablation injury. METHODS AND RESULTS: 16 pigs underwent pre-ablation T2-weighted (T2W) and late gadolinium enhancement (LGE) CMR and high-density voltage mapping of the right atrium (RA) and both were repeated after intercaval linear radiofrequency ablation. Eight pigs were sacrificed following the procedure for pathological examination. A further eight pigs were recovered for 8 weeks, before chronic CMR, repeat RA voltage mapping and pathological examination. Signal intensity (SI) thresholds from 0 to 15 SD above a reference SI were used to segment the RA in CMR images and segmentations compared with real lesion volumes. The SI thresholds that best approximated histological volumes were 2.3 SD for LGE post-ablation, 14.5 SD for T2W post-ablation and 3.3 SD for LGE chronically. T2-weighted chronically always underestimated lesion volume. Acute histology showed transmural injury with coagulative necrosis. Chronic histology showed transmural fibrous scar. The mean voltage at the centre of the ablation line was 3.3 mV pre-ablation, 0.6 mV immediately post-ablation, and 0.3 mV chronically. CONCLUSION: This study presents the first histopathological validation of CMR and endocardial voltage mapping to define acute and chronic atrial ablation injury, including SI thresholds that best match histological lesion volumes. An understanding of these thresholds may allow a more informed assessment of the underlying atrial substrate immediately after ablation and before repeat catheter ablation for atrial arrhythmias.

Quantitative magnetic resonance imaging analysis of the relationship between contact force and left atrial scar formation after catheter ablation of atrial fibrillation.

BACKGROUND: Catheter contact force (CF) is an important determinant of radiofrequency (RF) lesion quality during pulmonary vein isolation (PVI). Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows good visualization of ablation lesions. OBJECTIVE: This study describes a new technique to examine the relationship between CF during RF delivery and LGE signal intensity (SI) following PVI. METHODS: Six patients underwent PVI for paroxysmal AF using a CF-sensing catheter and following preprocedural MRI. During ablation, CF-time integral (FTI) and position was documented for each RF application. All patients underwent repeat LGE MRI 3 months later. The LGE SIs were projected onto a MRI-derived 3-dimensional left atrial (LA) shell and a CF map was generated on the same shell. The entire LA surface was divided into 5 mm(2) segments. Force and LGE maps were fused and compared for each 5 mm(2) zone. An effective lesion was defined when MRI-defined scar occupied >90% of a 5 mm(2) analysis zone. RESULTS: Acute PVI was achieved in 100%. Two hundred sixty-eight RF lesions were tagged on the LA shells and given a lesion-specific FTI. Increasing FTI correlated with increased LGE SI, which was greater when the FTI was > 1,200 gs. Below an FTI of 1,200 gs, an increment in the FTI resulted in only a small increment in scar, whereas above 1,200 gs an increment in the FTI resulted in a large change of scar. CONCLUSION: There is a correlation between FTI and LGE SI in MRI following AF ablation. Real-time FTI maps are feasible and may prevent inadequate lesion formation.

Linking green supply chain management practices and environmental performance in the manufacturing industry: a hybrid SEM-ANN approach.

This research determines the influence of green supply chain management practices (GSCM) on environmental performance. It also investigates the moderating role of supply chain environmental cooperation on GSCM practices and environmental performance relationships. A total of 370 employees of several Bangladeshi manufacturing companies were conveniently chosen as respondents. To verify the data validity and reliability and to test the hypotheses, we used SmartPLS. Finally, we employed an artificial neural network (ANN) to examine the relationship. Green design and green manufacturing have significant positive impacts on environmental performance, while green procurement and green distribution do not. Moreover, environmental cooperation moderates the relationships of green design and green distribution with environmental performance. The moderating effect of supply chain environmental cooperation in the relationship between GSCM practices and environmental performance in the manufacturing industry adds knowledge to the existing literature by incorporating a hybrid model combining PLS-SEM and ANN. Our study adds to the current body of knowledge by delving into the literature on GSCM from the perspective of Bangladesh's industrial sector. This study fills a knowledge gap by shedding light on the interactions of GSCM and environmental performance. Indeed, this study represents a step forward from classic linear regression-based models to an ANN-based nonlinear model. It also demonstrates new contributions to the literature on green supply chain management and environmental performance.

Evaluation of current algorithms for segmentation of scar tissue from late gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge.

BACKGROUND: Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop. METHODS: The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King's College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study. RESULTS: Some algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72. CONCLUSIONS: The study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

Evaluating the impact of Trichoderma biofertilizer and planting dates on mustard yield performance using the InfoCrop growth model.

A crop simulation model is adopted to calculate the potential yield in a certain location. The data sets generated in each scenario (2021-2022) were used to evaluate the InfoCrop model. A field experiment using a randomized complete block design was conducted at the Agronomy Department's research field, Hajee Mohammad Danesh Science and Technology University. The following two factors: 1) factor A: sowing dates (Planting date 1: PD1 = 5th November and Planting date 2: PD2 = 15th November 2021) and 2) factor B: Trichoderma biofertilizers (T1 = control, T2 = 50% chemical fertilizer + 2,000 kg ha-1 Trichoderma biofertlizer, T3 = fully chemical fertilizer; and T4 = fully 3,000 kg ha-1 Trichoderma biofertilizer). Three BARI (Bangladesh Agricultural Research Institute) released varieties (V1 = BARI Sarisa-14, V2 = BARI Sarisa-16, and V3 = BARI Sarisa-17) used for the completion of the experiment. The Trichoderma biofertilizer and planting dates had a significant influence on yield and yield attributes of mustard. Results showed that plant height, leaf width, leaves per plant, pods per plant, harvest index, maturity date, and yield were significantly affected by Trichoderma biofertilizer treatments, two different conditions, and varieties. The regression analysis indicated a significant linear relationship between two different growing conditions especially for harvest index PD2>PD1 (0.88>0.83), grain yield (0.94>0.90), flowering date (0.95>0.91) and maturity date (0.95>0.90). It was found that the model significantly overestimated all the parameters with an acceptable error range (<15%) while growth and yield characteristics including flowering and maturity dates and yield were simulated and results were compared to observed data. BARI Sarisa 16 had the highest simulated yield of 2.5 t ha-1 and showed a high yielding variety among the used varieties in the experiment. As a result, it can be concluded that if the InfoCrop growth model is carefully calibrated, it will be an excellent tool for evaluating and identifying the best yielding variety.

Novel Workflow for Conversion of Catheter-Based Electroanatomic Mapping to DICOM Imaging for Noninvasive Radioablation of Ventricular Tachycardia.

PURPOSE: A recent clinical trial has demonstrated that noninvasive radioablation (NIRA) has the potential to reduce recurrent ventricular tachycardia (VT) that is refractory to drugs and standard catheter ablation. Electroanatomic mapping (EAM) that would be useful for planning is obtained during catheter ablation, but incompatibility between EAM and DICOM formats required for radiation planning has impeded the use of existing catheter-based mapping to guide NIRA and is an important hurdle for its wider adoption. In this paper we define a process to facilitate the fusion of catheter-based EAM with DICOM imaging for radiation planning. METHOD AND MATERIALS: The raw data export of the CARTO3 EAM system (version 6.0.45.171, ".mesh" file) was processed with a MATLAB script to generate 3-dimensional (3D) visual took kit files containing X, Y, Z coordinates obtained during mapping and corresponding impedance, voltage, and other point-based information. The image could then be visualized with standard image processing software (3D Slicer) and the target outlined on the image surface. This structure was in turn converted to a DICOM image and fused with patient thoracic imaging using anatomic landmarks. Robustness of the workflow was assessed through implementation with a second magnetic resonance imaging based VT ablation planning system, ADAS-VT. RESULTS: This process facilitated the fusion of EAM and DICOM imaging to inform selection of NIRA targets. The workflow was found to be robust and compatible with a second VT ablation planning system. CONCLUSIONS: The conversion of catheter-based EAM to a DICOM compatible format permits the fusion of images for radiation planning and provides an avenue for the wider application of NIRA. Further improvements in the compatibility of these imaging formats would be expected to improve quality and reproducibility of image fusion.

Hyperparameter optimisation and validation of registration algorithms for measuring regional ventricular deformation using retrospective gated computed tomography images.

Recent dose reduction techniques have made retrospective computed tomography (CT) scans more applicable and extracting myocardial function from cardiac computed tomography (CCT) images feasible. However, hyperparameters of generic image intensity-based registration techniques, which are used for tracking motion, have not been systematically optimised for this modality. There is limited work on their validation for measuring regional strains from retrospective gated CCT images and open-source software for motion analysis is not widely available. We calculated strain using our open-source platform by applying an image registration warping field to a triangulated mesh of the left ventricular endocardium. We optimised hyperparameters of two registration methods to track the wall motion. Both methods required a single semi-automated segmentation of the left ventricle cavity at end-diastolic phase. The motion was characterised by the circumferential and longitudinal strains, as well as local area change throughout the cardiac cycle from a dataset of 24 patients. The derived motion was validated against manually annotated anatomical landmarks and the calculation of strains were verified using idealised problems. Optimising hyperparameters of registration methods allowed tracking of anatomical measurements with a mean error of 6.63% across frames, landmarks, and patients, comparable to an intra-observer error of 7.98%. Both registration methods differentiated between normal and dyssynchronous contraction patterns based on circumferential strain ([Formula: see text], [Formula: see text]). To test whether a typical 10 temporal frames sampling of retrospective gated CCT datasets affects measuring cardiac mechanics, we compared motion tracking results from 10 and 20 frames datasets and found a maximum error of [Formula: see text]. Our findings show that intensity-based registration techniques with optimal hyperparameters are able to accurately measure regional strains from CCT in a very short amount of time. Furthermore, sufficient sensitivity can be achieved to identify heart failure patients and left ventricle mechanics can be quantified with 10 reconstructed temporal frames. Our open-source platform will support increased use of CCT for quantifying cardiac mechanics.

Standardised computed tomographic assessment of left atrial morphology and tissue thickness in humans.

AIMS: Left atrial (LA) remodelling is a common feature of many cardiovascular pathologies and is a sensitive marker of adverse cardiovascular outcomes. The aim of this study was to establish normal ranges for LA parameters derived from coronary computed tomographic angiography (CCTA) imaging using a standardised image processing pipeline to establish normal ranges in a previously described cohort. METHODS: CCTA imaging from 193 subjects recruited to the Budapest GLOBAL twin study was analysed. Indexed LA cavity volume (LACVi), LA surface area (LASAi), wall thickness and LA tissue volume (LATVi) were calculated. Wall thickness maps were combined into an atlas. Indexed LA parameters were compared with clinical variables to identify early markers of pathological remodelling. RESULTS: LACVi is similar between sexes (31 ml/m2 v 30 ml/m2) and increased in hypertension (33 ml/m2 v 29 ml/m2, p = 0.009). LASAi is greater in females than males (47.8 ml/m2 v 45.8 ml/m2 male, p = 0.031). Median LAWT was 1.45 mm. LAWT was lowest at the inferior portion of the posterior LA wall (1.14 mm) and greatest in the septum (median = 2.0 mm) (p < 0.001). Conditions known to predispose to the development of AF were not associated with differences in tissue thickness. CONCLUSIONS: The reported LACVi, LASAi, LATVi and tissue thickness derived from CCTA may serve as reference values for this age group and clinical characteristics for future studies. Increased LASAi in females in the absence of differences in LACVi or LATVi may indicate differential LA shape changes between the sexes. AF predisposing conditions, other than sex, were not associated with detectable changes in LAWT.Clinical trial registration:http://www.ClinicalTrials.gov/NCT01738828.

Late Gadolinium Enhancement Cardiovascular Magnetic Resonance Assessment of Substrate for Ventricular Tachycardia With Hemodynamic Compromise.

Background: The majority of data regarding tissue substrate for post myocardial infarction (MI) VT has been collected during hemodynamically tolerated VT, which may be distinct from the substrate responsible for VT with hemodynamic compromise (VT-HC). This study aimed to characterize tissue at diastolic locations of VT-HC in a porcine model. Methods: Late Gadolinium Enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging was performed in eight pigs with healed antero-septal infarcts. Seven pigs underwent electrophysiology study with venous arterial-extra corporeal membrane oxygenation (VA-ECMO) support. Tissue thickness, scar and heterogeneous tissue (HT) transmurality were calculated at the location of the diastolic electrograms of mapped VT-HC. Results: Diastolic locations had median scar transmurality of 33.1% and a median HT transmurality 7.6%. Diastolic activation was found within areas of non-transmural scar in 80.1% of cases. Tissue activated during the diastolic component of VT circuits was thinner than healthy tissue (median thickness: 5.5 mm vs. 8.2 mm healthy tissue, p < 0.0001) and closer to HT (median distance diastolic tissue: 2.8 mm vs. 11.4 mm healthy tissue, p < 0.0001). Non-scarred regions with diastolic activation were closer to steep gradients in thickness than non-scarred locations with normal EGMs (diastolic locations distance = 1.19 mm vs. 9.67 mm for non-diastolic locations, p < 0.0001). Sites activated late in diastole were closest to steep gradients in tissue thickness. Conclusions: Non-transmural scar, mildly decreased tissue thickness, and steep gradients in tissue thickness represent the structural characteristics of the diastolic component of reentrant circuits in VT-HC in this porcine model and could form the basis for imaging criteria to define ablation targets in future trials.

A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

Segmentation of medical images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first step for ablation treatment of atrial fibrillation. However, direct segmentation of LGE-MRIs is challenging due to the varying intensities caused by contrast agents. Since most clinical studies have relied on manual, labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning approaches. To address this, we organized the 2018 Left Atrium Segmentation Challenge using 154 3D LGE-MRIs, currently the world's largest atrial LGE-MRI dataset, and associated labels of the left atrium segmented by three medical experts, ultimately attracting the participation of 27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis, offering an overall picture of the major design choices of convolutional neural networks (CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show that the top method achieved a Dice score of 93.2% and a mean surface to surface distance of 0.7 mm, significantly outperforming prior state-of-the-art. Particularly, our analysis demonstrated that double sequentially used CNNs, in which a first CNN is used for automatic region-of-interest localization and a subsequent CNN is used for refined regional segmentation, achieved superior results than traditional methods and machine learning approaches containing single CNNs. This large-scale benchmarking study makes a significant step towards much-improved segmentation methods for atrial LGE-MRIs, and will serve as an important benchmark for evaluating and comparing the future works in the field. Furthermore, the findings from this study can potentially be extended to other imaging datasets and modalities, having an impact on the wider medical imaging community.

CemrgApp: An interactive medical imaging application with image processing, computer vision, and machine learning toolkits for cardiovascular research.

Personalised medicine is based on the principle that each body is unique and will respond to therapies differently. In cardiology, characterising patient specific cardiovascular properties would help in personalising care. One promising approach for characterising these properties relies on performing computational analysis of multimodal imaging data. An interactive cardiac imaging environment, which can seamlessly render, manipulate, derive calculations, and otherwise prototype research activities, is therefore sought-after. We developed the Cardiac Electro-Mechanics Research Group Application (CemrgApp) as a platform with custom image processing and computer vision toolkits for applying statistical, machine learning and simulation approaches to study physiology, pathology, diagnosis and treatment of the cardiovascular system. CemrgApp provides an integrated environment, where cardiac data visualisation and workflow prototyping are presented through a common graphical user interface.