| 1. |
- Berggren, Klas, et al.
(författare)
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Super-Resolution Cine Image Enhancement for Fetal Cardiac Magnetic Resonance Imaging
- 2022
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Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley. - 1522-2586 .- 1053-1807. ; 56:1, s. 223-231
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundFetal cardiac magnetic resonance imaging (MRI) improves the diagnosis of congenital heart defects, but is sensitive to fetal motion due to long image acquisition time. This may be overcome with faster image acquisition with low resolution, followed by image enhancement to provide clinically useful images.PurposeTo combine phase-encoding undersampling with super-resolution neural networks to achieve high-resolution fetal cine cardiac MR images with short acquisition time.Study TypeProspective.SubjectsTwenty-eight fetuses (gestational week 36 [interquartile range 33–38 weeks]).Field Strength/Sequence1.5 T, balanced steady-state free precession (bSSFP) cine sequence.AssessmentImages were acquired using fully sampled Doppler ultrasound-gated clinical bSSFP cine as reference, with equivalent cine sequences with decreased phase-encoding resolution (25%, 33%, and 50% of clinical standard). Two super-resolution methods based on convolutional neural networks were proposed and evaluated (phasrGAN and phasrresnet). Data were partitioned into training (36 cine slices), validation (3 cine slices), and test sets (67 cine slices) without overlap. Conventional reconstruction methods using bicubic interpolation and k-space zeropadding were used for comparison. Three blinded observers scored image quality between 1 and 10.Statistical TestsImage scores are reported as median [interquartile range] and were compared using Mann–Whitney's nonparametric test with P < 0.05 showing statistically significant differences.ResultsBoth proposed methods showed no significant difference in image quality compared to clinical images (8 [7–8.5]) down to 33% (phasrGAN 8 [6.5–8]; phasrresnet 8 [7–8], all P ≥ 0.19) phase-encoding resolution, i.e., up to three times faster image acquisition, whereas bicubic interpolation and k-space zeropadding showed significantly lower quality for 33% phase-encoding resolution (both 7 [6–8]).Data ConclusionSuper-resolution enhancement can be used for fetal cine cardiac MRI to reduce image acquisition time while maintaining image quality. This may lead to an improved success rate for fetal cine MR imaging, as the impact of fetal motion is lessened by shortened acquisitions.Level of Evidence1Technical EfficacyStage 2
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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. |
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| 8. |
- 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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| 9. |
- 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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| 10. |
- 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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