| 1. |
- Nordlund, David, et al.
(författare)
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Multi-vendor, multicentre comparison of contrast-enhanced SSFP and T2-STIR CMR for determining myocardium at risk in ST-elevation myocardial infarction
- 2016
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Ingår i: European Heart Journal-Cardiovascular Imaging. - : Oxford University Press (OUP). - 2047-2412 .- 2047-2404. ; 17:7, s. 744-753
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: Myocardial salvage, determined by cardiac magnetic resonance imaging (CMR), is used as end point in cardioprotection trials. To calculate myocardial salvage, infarct size is related to myocardium at risk (MaR), which can be assessed by T2-short tau inversion recovery (T2-STIR) and contrast-enhanced steady-state free precession magnetic resonance imaging (CE-SSFP). We aimed to determine how T2-STIR and CE-SSFP perform in determining MaR when applied in multicentre, multi-vendor settings.METHODS AND RESULTS: A total of 215 patients from 17 centres were included after percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction. CMR was performed within 1-8 days. These patients participated in the MITOCARE or CHILL-MI cardioprotection trials. Additionally, 8 patients from a previous study, imaged 1 day post-CMR, were included. Late gadolinium enhancement, T2-STIR, and CE-SSFP images were acquired on 1.5T MR scanners (Philips, Siemens, or GE). In 65% of the patients, T2-STIR was of diagnostic quality compared with 97% for CE-SSFP. In diagnostic quality images, there was no difference in MaR by T2-STIR and CE-SSFP (bias: 0.02 ± 6%, P = 0.96, r(2) = 0.71, P < 0.001), or between treatment and control arms. No change in size or quality of MaR nor ability to identify culprit artery was seen over the first week after the acute event (P = 0.44).CONCLUSION: In diagnostic quality images, T2-STIR and CE-SSFP provide similar estimates of MaR, were constant over the first week, and were not affected by treatment. CE-SSFP had a higher degree of diagnostic quality images compared with T2 imaging for sequences from two out of three vendors. Therefore, CE-SSFP is currently more suitable for implementation in multicentre, multi-vendor clinical trials.
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| 2. |
- Bhat, Misha, et al.
(författare)
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Fetal iGRASP cine CMR assisting in prenatal diagnosis of complicated cardiac malformation with impact on delivery planning
- 2019
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 39:4, s. 231-235
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Tidskriftsartikel (refereegranskat)abstract
- Limited visualisation of the fetal heart and vessels by fetal ultrasound due to suboptimal fetal position, patient habitus and skeletal calcification may lead to missed diagnosis, overdiagnosis and parental uncertainty. Counseling and delivery planning may in those cases also be tentative. The recent fetal cardiac magnetic resonance (CMR) reconstruction method utilising tiny golden angle iGRASP (iterative Golden-angle RAdial Sparse Parallel MRI) allows for cine imaging of the fetal heart for use in clinical practice. This case describes an unbalanced common atrioventricular canal where limited ultrasound image quality and visibility of the aortic arch precluded confirming or ruling out presence of a ventricular septal defect. Need of prostaglandins or neonatal intervention was thus uncertain. Cardiovascular magnetic resonance imaging confirmed ultrasound findings and added value by ruling out a significant ventricular septal defect and diagnosing arch hypoplasia. This confirmed the need of patient relocation for delivery at a paediatric cardiothoracic surgery centre and prostaglandins could be initiated before the standard postnatal ultrasound. The applied CMR method can thus improve diagnosis of complicated fetal cardiac malformation and has direct clinical impact. This article is protected by copyright. All rights reserved.
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| 3. |
- Bidhult, Sebastian, et al.
(författare)
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A new vessel segmentation algorithm for robust blood flow quantification from two-dimensional phase-contrast magnetic resonance images
- 2019
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961 .- 1475-097X. ; 39:5, s. 327-338
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Tidskriftsartikel (refereegranskat)abstract
- Blood flow measurements in the ascending aorta and pulmonary artery from phase-contrast magnetic resonance images require accurate time-resolved vessel segmentation over the cardiac cycle. Current semi-automatic segmentation methods often involve time consuming manual correction, relying on user experience for accurate results. The purpose of this study was to develop a semi-automatic vessel segmentation algorithm with shape constraints based on manual vessel delineations for robust segmentation of the ascending aorta and pulmonary artery, to evaluate the proposed method in healthy volunteers and patients with heart failure and congenital heart disease, to validate the method in a pulsatile flow phantom experiment, and to make the method freely available for research purposes. Algorithm shape constraints were extracted from manual reference delineations of the ascending aorta (n=20) and pulmonary artery (n=20) and were included into a semi-automatic segmentation method only requiring manual delineation in one image. Bias and variability (bias±SD) for flow volume of the proposed algorithm versus manual reference delineations were 0·0±1·9ml in the ascending aorta (n=151; 7 healthy volunteers; 144 heart failure patients) and -1·7±2·9 ml in the pulmonary artery (n=40; 25 healthy volunteers; 15 patients with atrial septal defect). Inter-observer bias and variability were lower (p=0·008) for the proposed semi-automatic method (-0·1±0·9ml) compared to manual reference delineations (1·5±5·1ml). Phantom validation showed good agreement between the proposed method and timer-and-beaker flow volumes (0·4±2·7ml). In conclusion, the proposed semi-automatic vessel segmentation algorithm can be used for efficient analysis of flow and shunt volumes in the aorta and pulmonary artery. This article is protected by copyright. All rights reserved.
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| 4. |
- Bidhult, Sebastian, et al.
(författare)
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Independent validation of metric optimized gating for fetal cardiovascular phase-contrast flow imaging
- 2019
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 81:1, s. 495-503
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To validate metric optimized gating phase-contrast MR (MOG PC-MR) flow measurements for a range of fetal flow velocities in phantom experiments. 2) To investigate intra- and interobserver variability for fetal flow measurements at an imaging center other than the original site.METHODS: MOG PC-MR was compared to timer/beaker measurements in a pulsatile flow phantom using a heart rate (∼145 bpm), nozzle diameter (∼6 mm), and flow range (∼130-700 mL/min) similar to fetal imaging. Fifteen healthy fetuses were included for intra- and interobserver variability in the fetal descending aorta and umbilical vein.RESULTS: Phantom MOG PC-MR flow bias and variability was 2% ± 23%. Accuracy of MOG PC-MR was degraded for flow profiles with low velocity-to-noise ratio. Intra- and interobserver coefficients of variation were 6% and 19%, respectively, for fetal descending aorta; and 10% and 17%, respectively, for the umbilical vein.CONCLUSION: Phantom validation showed good agreement between MOG and conventionally gated PC-MR, except for cases with low velocity-to-noise ratio, which resulted in MOG misgating and underestimated peak velocities and warranted optimization of sequence parameters to individual fetal vessels. Inter- and intraobserver variability for fetal MOG PC-MR imaging were comparable to previously reported values.
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| 5. |
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| 6. |
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| 7. |
- Bidhult, Sebastian, et al.
(författare)
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Validation of T1 and T2 algorithms for quantitative MRI : Performance by a vendor-independent software
- 2016
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Ingår i: BMC Medical Imaging. - : Springer Science and Business Media LLC. - 1471-2342. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Determination of the relaxation time constants T1 and T2 with quantitative magnetic resonance imaging is increasingly used for both research and clinical practice. Recently, groups have been formed within the Society of Cardiovascular Magnetic Resonance to address issues with relaxometry. However, so far they have avoided specific recommendations on methodology due to lack of consensus and current evolving research. Standardised widely available software may simplify this process. The purpose of the current study was to develop and validate vendor-independent T1 and T2 mapping modules and implement those in the versatile and widespread software Segment, freely available for research and FDA approved for clinical applications. Results: The T1 and T2 mapping modules were developed and validated in phantoms at 1.5T and 3T with reference standard values calculated from reference pulse sequences using the Nelder-Mead Simplex optimisation method. The proposed modules support current commonly available MRI pulse sequences and both 2- and 3-parameter curve fitting. Images acquired in patients using three major vendors showed vendor-independence. Bias and variability showed high agreement with T1 and T2 reference standards for T1 (range 214-1752ms) and T2 (range 45-338ms), respectively. Conclusions: The developed and validated T1 and T2 mapping and quantification modules generated relaxation maps from current commonly used MRI sequences and multiple signal models. Patient applications showed usability for three major vendors.
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| 8. |
- Cheimariotis, Grigorios Aris, et al.
(författare)
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Automatic lung segmentation in functional SPECT images using active shape models trained on reference lung shapes from CT
- 2018
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Ingår i: Annals of Nuclear Medicine. - : Springer Science and Business Media LLC. - 0914-7187 .- 1864-6433. ; 32:2, s. 94-104
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and compare automatic and manual SPECT lung segmentations with reference computed tomography (CT) volumes. Methods: A total of 77 subjects (69 patients with obstructive lung disease, and 8 subjects without apparent perfusion of ventilation loss) performed low-dose CT followed by ventilation/perfusion (V/P) SPECT examination in a hybrid gamma camera system. In the training phase, lung shapes from the 57 anatomical low-dose CT images were used to construct two active shape models (right lung and left lung) which were then used for image segmentation. The algorithm was validated in 20 patients, comparing its results to reference delineation of corresponding CT images, and by comparing automatic segmentation to manual delineations in SPECT images. Results: The Dice coefficient between automatic SPECT delineations and manual SPECT delineations were 0.83 ± 0.04% for the right and 0.82 ± 0.05% for the left lung. There was statistically significant difference between reference volumes from CT and automatic delineations for the right (R = 0.53, p = 0.02) and left lung (R = 0.69, p < 0.001) in SPECT. There were similar observations when comparing reference volumes from CT and manual delineations in SPECT images, left lung (bias was − 10 ± 491, R = 0.60, p = 0.005) right lung (bias 36 ± 524 ml, R = 0.62, p = 0.004). Conclusion: Automated segmentation on SPECT images are on par with manual segmentation on SPECT images. Relative large volumetric differences between manual delineations of functional SPECT images and anatomical CT images confirms that lung segmentation of functional SPECT images is a challenging task. The current algorithm is a first step towards automatic quantification of wide range of measurements.
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| 9. |
- Edlund, Jonathan, et al.
(författare)
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Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images
- 2022
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input.
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| 10. |
- Engblom, Henrik, et al.
(författare)
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A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance : Experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data
- 2016
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Ingår i: Journal of Cardiovascular Magnetic Resonance. - : Springer Science and Business Media LLC. - 1097-6647 .- 1532-429X. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) using magnitude inversion recovery (IR) or phase sensitive inversion recovery (PSIR) has become clinical standard for assessment of myocardial infarction (MI). However, there is no clinical standard for quantification of MI even though multiple methods have been proposed. Simple thresholds have yielded varying results and advanced algorithms have only been validated in single center studies. Therefore, the aim of this study was to develop an automatic algorithm for MI quantification in IR and PSIR LGE images and to validate the new algorithm experimentally and compare it to expert delineations in multi-center, multi-vendor patient data. Methods: The new automatic algorithm, EWA (Expectation Maximization, weighted intensity, a priori information), was implemented using an intensity threshold by Expectation Maximization (EM) and a weighted summation to account for partial volume effects. The EWA algorithm was validated in-vivo against triphenyltetrazolium-chloride (TTC) staining (n = 7 pigs with paired IR and PSIR images) and against ex-vivo high resolution T1-weighted images (n = 23 IR and n = 13 PSIR images). The EWA algorithm was also compared to expert delineation in 124 patients from multi-center, multi-vendor clinical trials 2-6 days following first time ST-elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI) (n = 124 IR and n = 49 PSIR images). Results: Infarct size by the EWA algorithm in vivo in pigs showed a bias to ex-vivo TTC of -1 ± 4%LVM (R = 0.84) in IR and -2 ± 3%LVM (R = 0.92) in PSIR images and a bias to ex-vivo T1-weighted images of 0 ± 4%LVM (R = 0.94) in IR and 0 ± 5%LVM (R = 0.79) in PSIR images. In multi-center patient studies, infarct size by the EWA algorithm showed a bias to expert delineation of -2 ± 6 %LVM (R = 0.81) in IR images (n = 124) and 0 ± 5%LVM (R = 0.89) in PSIR images (n = 49). Conclusions: The EWA algorithm was validated experimentally and in patient data with a low bias in both IR and PSIR LGE images. Thus, the use of EM and a weighted intensity as in the EWA algorithm, may serve as a clinical standard for the quantification of myocardial infarction in LGE CMR images. Clinical trial registration: CHILL-MI: NCT01379261. MITOCARE: NCT01374321.
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