| Project/Area Number |
14571311
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Cerebral neurosurgery
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| Research Institution | Osaka University |
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Principal Investigator |
NAKAJIMA Yoshikazu Osaka University, School of Medicine, Assistant Professor, 医学系研究科, 助手 (80314334)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHIMINE Toshiki Osaka University, School of Medicine, Professor, 医学系研究科, 教授 (00201046)
KATO Amami Osaka University, School of Medicine, Associate Professor, 医学系研究科, 助教授 (00233776)
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| Project Period (FY) |
2002 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2003: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2002: ¥2,100,000 (Direct Cost: ¥2,100,000)
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| Keywords | image analysis / DICOM format / diital subtraction angiography (DSA) / a video signal / mean transit time / cerebral blood flow / endovascular surery / apoplexy / 医用画像 / 脳血管撮影検査 / DSA / 脳卒中 / モニタリング / クモ膜下出血 |
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| Research Abstract |
We have previously reported the utility of a perfusion imaging (PI) method that displays color-coded images of global and local cerebral perfusion based on digital subtraction angiography (DSA) image data. The system computes the mean transit time of bolus-injected contrast media, and displays the flow velocity value in a blood vessel as a color-coded picture (cerebral perfusion image). The previous system processed digitized data converted from an analog signal on videotape. The aim of this study was to evaluate the clinical utility of a new system that can directly analyze digitized data from serial DSA images in a DICOM format on a portable personal computer (PC). We applied this system to assess changes in cerebral perfusion in the treatment of acute apoplexy as well as in animal experiments. This system was able to visualize cerebral perfusion using 20 DSA images (512 x 512-pixels) in less than 1 second. Information regarding changes in flow velocity of the cerebral vessels and global perfusion status could be provided in semi-real time. Moreover, as compared to out previous system, the new system can detect smaller differences in signal density in the high-density range. This is important for clinical use because the signal density of cerebral vessels on DSA is around this high range. The system described here can provide indispensable information for objectively evaluating DSA image data in semi-real time. It could be especially beneficial for intra-operative monitoring of cerebral perfusion during endovascular surgery.
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