scholarly journals Effect of data conserving respiratory motion compensation on left ventricular functional parameters assessed in gated myocardial perfusion SPECT

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Matti J Kortelainen ◽  
Tuomas M Koivumäki ◽  
Marko J Vauhkonen ◽  
Mikko A Hakulinen
Keyword(s):  
Image Quality ◽  
Myocardial Perfusion ◽  
Ejection Fraction ◽  
Phase Analysis ◽  
Motion Compensation ◽  
Respiratory Motion ◽  
Wall Motion ◽  
Left Ventricular ◽  
Functional Parameters ◽  
Lv Volumes

Abstract Background Respiratory motion compromises image quality in myocardial perfusion (MP) single-photon emission computed tomography (SPECT) imaging and may affect analysis of left ventricular (LV) functional parameters, including phase analysis-quantified mechanical dyssynchrony parameters. In this paper, we investigate the performance of two algorithms, respiratory blur modeling (RBM) and joint motion-compensated (JMC) ordered-subsets expectation maximization (OSEM), and the effects of motion compensation on cardiac-gated MP-SPECT studies. Methods Image acquisitions were carried out with a dual-detector SPECT/CT system in list-mode format. A cardiac phantom was imaged as stationary and under respiratory motion. The images were reconstructed with OSEM, RBM-OSEM, and JMC-OSEM algorithms, and compared in terms of mean squared error (MSE). Subsequently, MP-SPECT data of 19 patients were binned into dual-gated (respiratory and cardiac gating) projection images. The images of the patients were analyzed with Quantitative Gated SPECT (QGS) 2012 program (Cedars-Sinai Medical Center, USA). The parameters of interest were LV volumes, ejection fraction, wall motion, wall thickening, phase analysis, and perfusion parameters. Results In phantom experiment, compared to the stationary OSEM reconstruction, the MSE values for OSEM, RBM-OSEM, and JMC-OSEM were 8.5406·10−5,2.7190·10−5, and 2.0795·10−5, respectively. In the analysis of LV function, use of JMC had a small but statistically significant (p < 0.05) effect on several parameters: it increased LV volumes and standard deviation of phase angle histogram, and it decreased ejection fraction, global wall motion, and lateral, septal, and apical perfusion. Conclusions Compared to standard OSEM algorithm, RBM-OSEM and JMC-OSEM both improve image quality under motion. Motion compensation has a minor effect on LV functional parameters.

Respiratory motion reduction with a dual gating approach in myocardial perfusion SPECT: Effect on left ventricular functional parameters

2017 ◽  
Vol 25 (5) ◽  
pp. 1633-1641 ◽  
Author(s):  
Matti J. Kortelainen ◽  
Tuomas M. Koivumäki ◽  
Marko J. Vauhkonen ◽  
Marja K. Hedman ◽  
Satu T. J. Kärkkäinen ◽  
...  
Keyword(s):  
Myocardial Perfusion ◽  
Respiratory Motion ◽  
Myocardial Perfusion Spect ◽  
Left Ventricular ◽  
Functional Parameters ◽  
Perfusion Spect ◽  
Dual Gating

scholarly journals 154 Can we improve the accuracy and reproducibility of left ventricular ejection fraction from 2D echocardiography using artificial intelligence? A validation against cardiac magnetic resonance

2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
A Popoff ◽  
H Langet ◽  
P Piro ◽  
C Ropert ◽  
P Allain ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Image Quality ◽  
Ejection Fraction ◽  
Cardiac Function ◽  
Objective Assessment ◽  
Left Ventricular ◽  
Lv Volumes

Abstract Funding Acknowledgements Philips BACKGROUND Accurate and reproducible echocardiographic measurements are paramount for objective assessment and follow-up of the cardiac function. However, manual contouring – e.g., for determining left ventricular (LV) volumes and ejection fraction (EF) – is limited by image quality and operator experience. Meanwhile, despite the wider availability of (semi-)automated tools, strong multimodal validation is still lacking for their widespread and safe use in the clinical routine. PURPOSE To evaluate the accuracy and reproducibility of an Artificial Intelligence (AI)-based semi-automated tool to compute LV volumes and EF, in comparison with manual contouring, using cardiac magnetic resonance (cMR) as reference. METHODS Manual and AI measurements from echocardiography were compared to measurements from cMR in a retrospective two-centre study. One hundred fourteen patients in sinus rhythm were included; among those, 85 had abnormal LV function (56 dilated and 29 hypertrophic). Three successive cardiac cycles were available for apical 4- and 2-chamber views. Two senior (A1 and B1) and one junior (A2) cardiologists contoured the ED and ES endocardial borders in the cardiac cycle of their choice, while blinded to quantitative outcomes. For AI analysis, a deep convolutional neural networks model was used to segment the LV cavity on the frames selected by the three observers. This model was trained using ED and ES manual contouring from senior cardiologist A1 on an independent single-centre dataset that consisted of 700 apical 4- and 2-chamber views. The same biplane Simpson’s method was used to compute all LV volumes and EF. RESULTS Despite challenging image quality (poor: 6%; fair: 33%; high: 61%, as rated by observers), the majority of the AI segmentations were deemed acceptable (75% in total; 80% for images of high quality). Overall, inter-observer agreement was better by AI than by manual contouring (ICC = 0.99 vs. 0.89, 1.00 vs. 0.95 and 0.95 vs. 0.89 for LVED, LVES and LVEF respectively, all p &lt; 0.001). For LVED and LVES, agreement vs. cMR was higher by AI (80.95 ± 39.09; -46.42 ± 38.29) than by manual contouring for junior observer A2 (-81.47 ± 43; -51.88 ± 40.43), although still lower than by manual contouring for the best senior observer (-54.71 ± 31.44; -32.75 ± 32.80), see upper part in figure below. LVEF bias was reduced near to zero by AI, with slightly higher variability than by manual contouring ([-0.91; -0.05] ± [8.47; 10.17] vs. [-0.19; 5.44] ± [7.75; 8.79]), see lower part in figure below. CONCLUSION The AI model generalized well to different sites, observers and image quality. Compared to manual contouring, LV volumes and EF by AI showed comparable or improved accuracy and higher reproducibility. These findings demonstrate the value of AI-based tools, with potential for full automation, for objective assessment and follow-up of the cardiac function. Abstract 154 Figure.

scholarly journals Feasibility and accuracy of the automated software for dynamic quantification of left ventricular and atrial volumes and function in a large unselected population

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
G Italiano ◽  
G Tamborini ◽  
V Mantegazza ◽  
V Volpato ◽  
L Fusini ◽  
...  
Keyword(s):  
Machine Learning ◽  
Atrial Fibrillation ◽  
Image Quality ◽  
Normal Subjects ◽  
Left Ventricular ◽  
Systolic Volume ◽  
Unselected Population ◽  
Lv Volumes ◽  
Time Required ◽  
2D Images

Abstract Funding Acknowledgements Type of funding sources: None. Objective. Preliminary studies showed the accuracy of machine learning based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes. We aimed to evaluate the feasibility and accuracy of machine learning based automated dynamic quantification of LV and LA volumes in an unselected population. Methods. We enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV and LA volumes were obtained from 2D images; 3D images were analysed using Dynamic Heart Model (DHM) software (Philips) resulting in LV and LA volume-time curves. A subgroup of 140 patients underwent also cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded and results were compared between 2DTTE, DHM and CMR. Results. The use of DHM was feasible in 522/600 cases (87%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n = 38) or minor (n = 149) borders corrections were needed. The overall time required for DHM datasets was approximately 40 seconds, resulting in physiologically appearing LV and LA volume–time curves in all cases. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173 ± 64 vs 142 ± 58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55%±12 vs 56%±14; LA volume 89 ± 36 vs 89 ± 38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r = 0.70 and r = 0.82, p &lt; 0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r= 0.82, p &lt; 0.001) and LA volumes. Conclusions. The DHM software is feasible, accurate and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation. Table 1 DHM quality Adjustment Feasibility Good Suboptimal Minor Major Total of patients (n, %) 522/600 (87%) 327/522 (62%) 195/522 (28%) 149/522 (29%) 38/522 (6%) Normal subjects (n, %) 39/40 (97%) 23/39 (57%) 16/39 (40%) 9/39 (21%) 1/39 (3%) Atrial Fibrillation (n, %) 59/73 (81%)* 28/59 (47%) 31/59 (53%) 15/59 (25%) 6/59 (10%) Valvular disease (n, %) 271/312 (87%) 120/271 (%) 151/271 (%) 65/271 (24%) 16/271 (6%) Coronary artery disease (n, %) 47/58 (81%)* 26/47 (46%) 21/47 (37%) 16/47 (34%) 5/47 (11%) Miscellaneous (n, %) 24/25 (96%) 18/24 (75%) 6/24 (25%) 5/24 (21%) 3/24 (12%) Feasibility of DHM, image quality and need to adjustments in global population and in each subgroup. Abstract Figure 1

Abstract 4840: Tako-Tsubo Cardiomyopathy without Apical Ballooning - Results of the German Tako-Tsubo Registry

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Anastasios Athanasiadis ◽  
Birke Schneider ◽  
Johannes Schwab ◽  
Uta Gottwald ◽  
Ellen Hoffmann ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Ejection Fraction ◽  
Wall Motion ◽  
Apical Ballooning ◽  
Left Ventricular ◽  
St Segment Elevation ◽  
T Wave ◽  
Wave Inversion ◽  
St Segment ◽  
Tako Tsubo Cardiomyopathy

Background : The German tako-tsubo cardiomyopathy (TTC) registry has been initiated to further evaluate this syndrome in a western population. We aimed to assess different patterns of left ventricular involvement in TTC. Methods : Inclusion criteria were: 1) acute chest symptoms, 2) reversible ECG changes (ST-segment elevation±T-wave inversion), 3) reversible left ventricular dysfunction with a wall motion abnormality not corresponding to a single coronary artery territory, 4) no significant coronary artery stenoses. Results : A total of 258 patients (pts) from 33 centers were included with a mean age of 68±12 years. Left ventriculography revealed the typical pattern of apical ballooning in 170 pts (66%) and an atypical mid-ventricular ballooning with normal wall motion of the apical and basal segments in 88 pts (34%). Mean age (68±11 vs 67±13 years) and gender distribution (150 women/20 men vs 80 women/8 men) were similar in both groups. Triggering events were present in 78% of the pts with apical ballooning (35% emotional, 34 physical and 9% combination) and in 75% of the pts with mid-ventricular ballooning (39% emotional, 25% physical and 11% combination). As assessed by left ventriculography, ejection fraction was significantly lower in pts with mid-ventricular ballooning (50±15% vs 45±13%, p=0.006). There was no difference in right ventricular involvement. Creatine kinase and troponin I were comparable in both groups. The ECG on admission showed ST-segment elevation in 87% of pts with apical ballooning and in 78% of pts with mid-ventricular ballooning. T-wave inversion was seen in 70% of the pts irrespective of the TTC variant. A Q-wave was significantly less present in pts with mid-ventricular ballooning (30% vs 16%, p=0.04). The QTc interval during the first 3 days was not different among both groups. Conclusion : A variant form with mid-ventricular ballooning was observed in one third of the pts with TTC. Left ventricular ejection fraction was significantly lower in these pts, although they revealed significantly less Q-waves on the admission ECG. All other parameters were similar and confirm the concept that apical and mid-ventricular ballooning represent two different manifestations of the same syndrome.

scholarly journals The agreement between 3D, standard 2D and triplane 2D speckle tracking: effects of image quality and 3D volume rate

2014 ◽  
Vol 1 (2) ◽  
pp. 71-83 ◽  
Author(s):  
Tudor Trache ◽  
Stephan Stöbe ◽  
Adrienn Tarr ◽  
Dietrich Pfeiffer ◽  
Andreas Hagendorff
Keyword(s):  
Image Quality ◽  
Speckle Tracking ◽  
Wall Motion ◽  
Left Ventricular ◽  
Motion Patterns ◽  
Volume Rate ◽  
2D Speckle Tracking ◽  
Wall Motion Abnormalities ◽  
3D Volume ◽  
2D And 3D

Comparison of 3D and 2D speckle tracking performed on standard 2D and triplane 2D datasets of normal and pathological left ventricular (LV) wall-motion patterns with a focus on the effect that 3D volume rate (3DVR), image quality and tracking artifacts have on the agreement between 2D and 3D speckle tracking. 37 patients with normal LV function and 18 patients with ischaemic wall-motion abnormalities underwent 2D and 3D echocardiography, followed by offline speckle tracking measurements. The values of 3D global, regional and segmental strain were compared with the standard 2D and triplane 2D strain values. Correlation analysis with the LV ejection fraction (LVEF) was also performed. The 3D and 2D global strain values correlated good in both normally and abnormally contracting hearts, though systematic differences between the two methods were observed. Of the 3D strain parameters, the area strain showed the best correlation with the LVEF. The numerical agreement of 3D and 2D analyses varied significantly with the volume rate and image quality of the 3D datasets. The highest correlation between 2D and 3D peak systolic strain values was found between 3D area and standard 2D longitudinal strain. Regional wall-motion abnormalities were similarly detected by 2D and 3D speckle tracking. 2DST of triplane datasets showed similar results to those of conventional 2D datasets. 2D and 3D speckle tracking similarly detect normal and pathological wall-motion patterns. Limited image quality has a significant impact on the agreement between 3D and 2D numerical strain values.

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