Presentation is loading. Please wait.

Presentation is loading. Please wait.

Cerebral Blood Flow by Means of Xenon-enhanced Computed Tomography: From Trans-axial to Surface Quantitative Images Shigeru Sase 1, Homaro Yamamoto 2,

Similar presentations


Presentation on theme: "Cerebral Blood Flow by Means of Xenon-enhanced Computed Tomography: From Trans-axial to Surface Quantitative Images Shigeru Sase 1, Homaro Yamamoto 2,"— Presentation transcript:

1 Cerebral Blood Flow by Means of Xenon-enhanced Computed Tomography: From Trans-axial to Surface Quantitative Images Shigeru Sase 1, Homaro Yamamoto 2, and Yutaka Sawa 2 1 Anzai Medical Co., Ltd., Tokyo, Japan 2 Sawa Hospital, Osaka, Japan

2 [Purpose] To create brain surface images by stacking thin tomographic images obtained by xenon-enhanced computed tomography (Xe-CT). To demonstrate usefulness of layer-by- layer spherical analysis of blood flow and lambda for patients with dementia.

3 ④ Radiopaque substance due to large atomic weight. What is Xenon ? ③ Soluble in blood and brain tissue. ② Goes through blood-brain barrier. ① Xe is an inert gas and not metabolized in human body. Ideal substance as blood-flow tracer using CT. 54 131.3

4 Blood flow measurement using Xe gas Workstation for Image Processing Xe gas Inhalator CT System Requirements

5 Blood flow measurement using Xe gas Inhale 30% Xe for 4 min. Then, inhale air for 4 min. Measurement of respiratory Xe concentration, which is used as a surrogate of arterial Xe. Meanwhile, CT scanning at 1-min intervals.

6 Blood flow measurement using Xe gas 01 2345678 [min] Saturation speed (Ka) and saturation concentration(Aa) of Xe in arterial blood. Time course of Xe concentration [C(t)]in brain tissue Blood flow ( f ) and lambda (λ) can be calculated pixel by pixel using Ka, Aa and C(t). Ka Aa Ka (Fick’s Law) Arterial Xe Conc.

7 Blood Flow and Lambda Images obtained by Xe-CT 24-y.o. Healthy Man Blood Flow ImageLambda Image [mL/100 g tissue/min] Xe Solubility in Tissue Xe Solubility in Blood Xe Solubility Coefficient =

8 Lambda Image Fat 5% Fat 30% 62-y.o. Woman 63-y.o. Woman Fat 90% 15-y.o. Man Fatty Liver Lambda Fat-rich Tissue Water-rich Tissue High Low White Matter Gray Matter 1.5 ー 0.8 ー

9 [Methods] CT: Aquilion ONE (Toshiba, Japan): Area- detector CT capable of volume scan of the brain. Xe gas inhalator: AZ-725 (Anzai Medical, Japan). Subjects: Patients with dementia, Age- matched healthy controls. Creation of brain surface images, and layer- by-layer analyses (layer thickness: 5mm)

10 Installed CT Scanner The coverage of Detector: 160mm ( 320-row * 896ch ) Slice Thickness: 0.5mm ( The thinnest in the industry ) The coverage of Detector: 160mm ( 320-row * 896ch ) Slice Thickness: 0.5mm ( The thinnest in the industry ) Toshiba Medical Systems corporation

11 Functional maps of human cerebral cortex Cortices of frontal, parietal, occipital and temporal lobes Frontal Lobe Parietal Lobe Occipital Lobe Temporal Lobe

12 [Results]

13 Surface images of blood flow and lambda for healthy volunteer

14 36.133.8 34.531.838.1 RT LATLT LATSUPANTPOST CT Blood Flow Brain Surface 0.520.51 0.480.500.53 Lambda 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) CT Healthy Volunteer (77-y.o. Woman) mL/100g/min

15 Comparison of Xe-CT and SPECT

16 RT LATLT LATSUPANTPOST Brain Surface 34.636.2 27.335.732.1 33.032.8 29.734.832.7 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) CT Blood Flow Blood Flow Patient (78-y.o. Woman) mL/100g/min

17 RT LATLT LATSUPANTPOST Brain Surface 34.636.2 27.335.732.1 33.032.8 29.734.832.7 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) IMP SPECT (3D-SSP) CT Blood Flow Blood Flow Blood Flow Patient (78-y.o. Woman) mL/100g/min

18 RT LATLT LATSUPANTPOST Brain Surface 34.636.2 27.335.732.1 33.032.8 29.734.832.7 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) IMP SPECT (3D-SSP) CT Blood Flow Blood Flow Reduction Regions Patient (78-y.o. Woman) mL/100g/min

19 Comparison of AD patient and healthy volunteer

20 RT LATLT LATSUPANTPOST Brain Surface 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) CT Blood Flow Blood Flow AD Patient (83-y.o. Woman) 25.525.1 25.226.821.6 22.225.1 25.925.121.6 mL/100g/min

21 RT LATLT LATSUPANTPOST Brain Surface 1 st Layer ( 0-5mm ) 2 nd Layer (5-10mm) CT Blood Flow Blood Flow 25.525.1 25.226.821.6 22.225.1 25.925.121.6 33.8 34.538.1 36.1 31.8 Healthy Volunteer (77-y.o. Woman) Blood Flow AD Patient (83-y.o. Woman) mL/100g/min

22 Effect of drug administration to AD patient

23 RT LATLT LATSUPANTPOST Brain Surface Before Galantamine CT Blood Flow Blood Flow AD Patient (77-y.o. Woman) After Galantamine (3 months) 22.724.3 20.922.724.0 24.926.1 25.724.426.2 (2 nd Layer) mL/100g/min

24 RT LATLT LATSUPANTPOST Brain Surface Before Galantamine CT Blood Flow Blood Flow AD Patient (77-y.o. Woman) After Galantamine (3 months) 22.724.3 20.922.724.0 24.926.1 25.724.426.2 (2 nd Layer) mL/100g/min

25 1 st Layer Superior View 1 st to 10 th layer images 2 nd Layer 10 th Layer 5 mm Superior View

26 (From Wikipedia) Cingulate Gyrus Thalamus Hypothalamus Parahippocampal Gyrus Hyppocampus Amygdala Mamillary Body Limbic System White Matter

27 Remove white areas in the figure. Side View 1 st Layer Superior View Images 2 nd Layer Schematic Diagram

28 Comparison of healthy volunteer and AD patient

29 Blood Flow Lambda 1 st Layer Healthy Volunteer (77-y.o. Woman)

30 1 st Layer Blood Flow Lambda 2 nd Layer Healthy Volunteer (77-y.o. Woman)

31 Blood Flow Lambda 3 rd Layer Healthy Volunteer (77-y.o. Woman)

32 Blood Flow Lambda 4 th Layer Healthy Volunteer (77-y.o. Woman)

33 Blood Flow Lambda 5 th Layer Healthy Volunteer (77-y.o. Woman)

34 Blood Flow Lambda 6 th Layer Healthy Volunteer (77-y.o. Woman)

35 Blood Flow Lambda 7 th Layer Healthy Volunteer (77-y.o. Woman)

36 Blood Flow Lambda 8 th Layer Healthy Volunteer (77-y.o. Woman)

37 Blood Flow Lambda 9 th Layer Healthy Volunteer (77-y.o. Woman)

38 Blood Flow Lambda 10 th Layer Healthy Volunteer (77-y.o. Woman)

39 Blood Flow Lambda 1 st Layer AD Patient (83-y.o. Woman)

40 Blood Flow Lambda 2 nd Layer AD Patient (83-y.o. Woman)

41 Blood Flow Lambda 3 rd Layer AD Patient (83-y.o. Woman)

42 Blood Flow Lambda 4 th Layer AD Patient (83-y.o. Woman)

43 Blood Flow Lambda 5 th Layer AD Patient (83-y.o. Woman)

44 Blood Flow Lambda 6 th Layer AD Patient (83-y.o. Woman)

45 Blood Flow Lambda 7 th Layer AD Patient (83-y.o. Woman)

46 Blood Flow Lambda 8 th Layer AD Patient (83-y.o. Woman)

47 Blood Flow Lambda 9 th Layer AD Patient (83-y.o. Woman)

48 Blood Flow Lambda 10 th Layer AD Patient (83-y.o. Woman)

49 Healthy Volunteer (77-y.o. Woman) AD Patient (83-y.o. Woman) Blood Flow Lambda Blood Flow Lambda

50 Healthy Volunteer (77-y.o. Woman) AD Patient (83-y.o. Woman) Blood Flow Lambda Blood Flow Lambda

51 Healthy Volunteer (77-y.o. Woman) AD Patient (83-y.o. Woman) Blood Flow Lambda Blood Flow Lambda

52 Healthy Volunteer (77-y.o. Woman) AD Patient (83-y.o. Woman) Blood Flow Lambda Blood Flow Lambda

53 AD Patient (77-y.o. Woman) AD Patient (83-y.o. Woman) Blood Flow Lambda Blood Flow Lambda

54 [Conclusions] Method of creating quantitative blood flow images for the brain surface was established. Layer-by-layer spherical analysis would provide useful information which could not be obtained from tomographic images. High lambda suggests accumulation of substances in which xenon is highly soluble.

55 [Future] When the function of head movement correction is much more accomplished, radiation exposure will be reduced by nearly half by decreasing the number of CT scans (from 9 to 5). Improvement of CT image processing by TOSHIBA could reduce mAs with little deterioration of the quality of CT images and also reduce the radiation exposure. Quantitative judgment of treatment effectiveness, specifying the form of dementia, and detecting the dementia in its early stage, by means of Xe-CT.

56 Thank you very much.


Download ppt "Cerebral Blood Flow by Means of Xenon-enhanced Computed Tomography: From Trans-axial to Surface Quantitative Images Shigeru Sase 1, Homaro Yamamoto 2,"

Similar presentations


Ads by Google