Figure 1 - uploaded by Jules Laurent Nelissen
Content may be subject to copyright.
Distribution of major causes of death in 2011 calculated by the World Health Organization. Cardiovascular diseases are responsible for 31% of all deaths globally 5 .
Contexts in source publication
Context 1
... disease is one of the leading causes of death in the western world. Each year, 17.3 million people die from cardiovascular diseases, accounting for 31 % of all deaths globally (Figure 1) [1][2] . Cardiovascular disease is caused by disorders of the heart and blood vessels, and includes diseases such as coronary heart disease, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease, hypertension and heart failure 3 . ...
Context 2
... TU/e, Eindhoven, The Netherlands) was used ( Upon the detection of a trigger, from the SAII monitoring system (Small Animal Instruments Inc., New York, USA), the logic device sends a trigger to the scanner, possibly delayed by an initial delay time, which can be followed by n triggers each separated by a repeat time and the possibility to use a blanking time (Figure 10 A&C). The logic device enabled a reduction of the acquisition of the ECG triggered 3D UTE sequence by sending multiple triggers to the scanner after detection of a single ECG R-wave. ...
Context 3
... logic device enabled a reduction of the acquisition of the ECG triggered 3D UTE sequence by sending multiple triggers to the scanner after detection of a single ECG R-wave. The logic device was connected to the SAII small animal monitoring system, control computer, and the AVANCE III hardware unit of the Bruker MR scanner as depicted in Figure 11 and was tested with an oscilloscope and SAII before connecting and testing with the scanner AVANCE III hardware unit and 3D UTE sequence. ...
Context 4
... mice were intubated and the lungs were ventilated with a MidiVent mechanical ventilator (Harvard Apparatus, Massachusetts, USA). A left anterolateral thoracotomy was performed by incision of the chest to gain access to the thoratic organs, a tissue retractor was placed to keep the chest open, the lungs were deflated and the left descending coronary artery of the heart was permanently occluded by tightly lacing a fine suture (6-0, silk), as is depicted in Figure 12. Immediately after ligation of the left descending coronary artery, a part of apical side of the LV changed color from bright red to pale red indicating successful ligation. ...
Context 5
... (opioid analgesia, 0.1 mg.kg) was given pre operative for analgesia, as well at the end of the day of surgery and one day later. The first experiment (Figure 13 I) was designed to test if it was possible to detect myocardial fibrosis with the 3D UTE, and for further optimalization of the sequence. 19 C57BL/6 were included, 12 with a permanent occlusion of a coronary artery and 7 healthy littermates who served as controls. ...
Context 6
... the second experiment ( Figure 13 II) the 3D UTE sequence was applied in vivo. 8 C57BL/6 mice with a permanent occlusion and 5 healthy controls were included. ...
Context 7
... correct for timing and gradient errors, calibrated k-space trajectories and a calibrated gradient timing were used. To further reduce the acquisition time to approximately 20 minutes per dataset the acquisition matrix was undersampled by a factor 2. To improve contrast between the blood and the myocardium a 3 mm thick saturation slice was used, planned in SA orientation just above the LV base ( Figure 14). Excitation of the saturation slice was done with a 1.5ms Gauss RF pulse with a flip 90 o angle and followed by a spoiler gradient. ...
Context 8
... all slides were dehydrated and mounted with Entellan (Merck). A Zeiss Axio Observer Z-1 bright field microscope equipped with an Axiocam MrC5 was used to digitalize the microscope images ( Figure 15). To compare the volume of collagen rich areas as quantified from the 3D Δ UTE MR images with histology, 1.6x/2.5x ...
Context 9
... volumes were normalized to total heart volume. Histological images were analyzed with Matlab using a custom-built color detection algorithm based on the hue-saturation-value (HSV) and red-green-blue (RGB) color spaces ( Figure 16) to quantify whole heart volume and infarct volume. Total heart volume was determined using a HSV based threshold and the collagen-rich volume was calculated using a RGB threshold for red in the apical region of the heart where normally the infarct, and thus formation of collagen, was expected. ...
Context 10
... Figure 17 the results are shown of the phantom containing alginate and water with 0.1 mM Prohance scanned with a conventional FLASH 3D sequence (A) and the 3D UTE sequence (B, C, D), note that the k-space trajectory was pre-measured in the phantom in these experiments. In a cross section of the 3D FLASH dataset (A) the water appears bright where the alginate gives no signal due to its short transversal relaxation rate. ...
Context 11
... phantom experiments prove that the signal from the long T2 components can be effectively suppressed in the ΔUTE images. A selection of images with different undersampling factors is depicted in Figure 18 to show the effect on image quality. Noise, ringing and ghosting artefacts increase with higher undersampling factors, which becomes apparent in Figure 18 D and E. The image quality of images obtained with undersampling factors 1 and 2 are rather similar (Figure 18 A, B), whereas some more artefacts are observed in Figure 18 C with undersampling = 3. ...
Context 12
... selection of images with different undersampling factors is depicted in Figure 18 to show the effect on image quality. Noise, ringing and ghosting artefacts increase with higher undersampling factors, which becomes apparent in Figure 18 D and E. The image quality of images obtained with undersampling factors 1 and 2 are rather similar (Figure 18 A, B), whereas some more artefacts are observed in Figure 18 C with undersampling = 3. In Figure 19 3D UTE MR images are shown from the alginate sample with different gradient delays (0, 5, 10 and 50 µs). ...
Context 13
... selection of images with different undersampling factors is depicted in Figure 18 to show the effect on image quality. Noise, ringing and ghosting artefacts increase with higher undersampling factors, which becomes apparent in Figure 18 D and E. The image quality of images obtained with undersampling factors 1 and 2 are rather similar (Figure 18 A, B), whereas some more artefacts are observed in Figure 18 C with undersampling = 3. In Figure 19 3D UTE MR images are shown from the alginate sample with different gradient delays (0, 5, 10 and 50 µs). ...
Context 14
... selection of images with different undersampling factors is depicted in Figure 18 to show the effect on image quality. Noise, ringing and ghosting artefacts increase with higher undersampling factors, which becomes apparent in Figure 18 D and E. The image quality of images obtained with undersampling factors 1 and 2 are rather similar (Figure 18 A, B), whereas some more artefacts are observed in Figure 18 C with undersampling = 3. In Figure 19 3D UTE MR images are shown from the alginate sample with different gradient delays (0, 5, 10 and 50 µs). ...
Context 15
... ringing and ghosting artefacts increase with higher undersampling factors, which becomes apparent in Figure 18 D and E. The image quality of images obtained with undersampling factors 1 and 2 are rather similar (Figure 18 A, B), whereas some more artefacts are observed in Figure 18 C with undersampling = 3. In Figure 19 3D UTE MR images are shown from the alginate sample with different gradient delays (0, 5, 10 and 50 µs). The alginate appears darker for higher gradient delays, and in Figure 19 B, C and D a white rim is seen which becomes more prominent with higher gradient delay. ...
Context 16
... Figure 19 3D UTE MR images are shown from the alginate sample with different gradient delays (0, 5, 10 and 50 µs). The alginate appears darker for higher gradient delays, and in Figure 19 B, C and D a white rim is seen which becomes more prominent with higher gradient delay. For the image obtained with a gradient delay of 50 µs the alginate and water could not be distinguished (Figure 19 D) and multiple artefacts appear. ...
Context 17
... alginate appears darker for higher gradient delays, and in Figure 19 B, C and D a white rim is seen which becomes more prominent with higher gradient delay. For the image obtained with a gradient delay of 50 µs the alginate and water could not be distinguished (Figure 19 D) and multiple artefacts appear. The images with the shortest gradient delay results overall in the best image quality. ...
Context 18
... selection of images of a glass sphere filled with an aqueous solution of CuSO 4 obtained with different gradient delays is displayed in Figure 21. When we compare these images with the example image in the Bruker manual, the image with the correct gradient delay should be ideally homogeneous and artefact free. ...
Context 19
... we compare these images with the example image in the Bruker manual, the image with the correct gradient delay should be ideally homogeneous and artefact free. By visual evaluation of the various images it was found that the image with a gradient delay of 1 µs (Figure 21 A) seems to be the most homogeneous with the least ghosting artefacts. All other images (Figure 21 B,C,D) show a black or white inner rim inside the sphere-shaped phantom and more ghosting artefacts. ...
Context 20
... visual evaluation of the various images it was found that the image with a gradient delay of 1 µs (Figure 21 A) seems to be the most homogeneous with the least ghosting artefacts. All other images (Figure 21 B,C,D) show a black or white inner rim inside the sphere-shaped phantom and more ghosting artefacts. For the images with a gradient delay larger than 10 µs the center of the sphere appears dark. ...
