脳CTおよびMR画像における超急性期脳梗塞の診断支援に関する研究

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Title 脳CTおよびMR画像における超急性期脳梗塞の診断支援に_{関する研究( 本文(Fulltext) )} Author(s) 長島, 宏幸 Report No.(Doctoral Degree) 博士(再生医科学) 乙第1466号 Issue Date 2013-03-19 Type 博士論文 Version publisher URL http://hdl.handle.net/20.500.12099/48081 ※この資料の著作権は、各資料の著者・学協会・出版社等に帰属します。

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CT ࠾ࡼࡧ MR ⏬ീ࡟࠾ࡅࡿ

㉸ᛴᛶᮇ⬻᱾ሰࡢデ᩿ᨭ᥼࡟㛵ࡍࡿ◊✲

Studies on diagnostic support for hyperacute ischemic stroke

in brain CT and MR images

ᒱ㜧኱Ꮫ኱Ꮫ㝔 ་Ꮫ⣔◊✲⛉ ෌⏕་⛉Ꮫᑓᨷ

෌⏕ᕤᏛㅮᗙ ▱⬟࢖࣓࣮ࢪ᝟ሗศ㔝

Department of Intelligent Image Information,

Division of Regeneration and Advanced Medical Sciences,

Graduate School of Medicine,

Gifu University

ᖹᡂ

25 ᖺ㸦2013 ᖺ㸧3 ᭶

March, 2013

㛗ᓥ ᏹᖾ

Hiroyuki Nagashima

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⬻

_{CT ࠾ࡼࡧ MR ⏬ീ࡟࠾ࡅࡿ}

㉸ᛴᛶᮇ⬻᱾ሰࡢデ᩿ᨭ᥼࡟㛵ࡍࡿ◊✲

㛗ᓥ ᏹᖾ

ᒱ㜧኱Ꮫ኱Ꮫ㝔 ་Ꮫ⣔◊✲⛉ ෌⏕་⛉Ꮫᑓᨷ

෌⏕ᕤᏛㅮᗙ ▱⬟࢖࣓࣮ࢪ᝟ሗศ㔝

ࠛ

501-1194 ᒱ㜧┴ᒱ㜧ᕷᰗᡞ 1-1

TEL㸸027-235-9488㸪FAX㸸027-235-2501

E-mail㸸[email protected]

ᣦᑟᩍᐁ㸸 ⸨⏣ᘅᚿ ᩍᤵ

せ᪨ ᮏ◊✲ࡢ┠ⓗࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰࢆ⏬ീデ᩿ࡍࡿ་ᖌࢆᨭ᥼ࡍࡿࡓࡵ㸪⬻ CT ⏬ീ࡟࠾ࡅࡿ⏬ീ⾲♧᮲௳ࡢ᭱㐺໬ࢆᅗࡿࡇ࡜㸪⬻ CT ⏬ീୖࡢ㠀ᖖ࡟ῐ࠸⏬ീ ᡤぢࢆ⮬ື᳨ฟࡍࡿࢩࢫࢸ࣒ࢆᵓ⠏ࡍࡿࡇ࡜㸪ࡑࡋ࡚㸪⬻MR ⏬ീࡢ᭱㐺࡞⾲♧ ᮲௳ࢆ⮬ືㄪ⠇ࡍࡿࢩࢫࢸ࣒ࢆᵓ⠏ࡍࡿࡇ࡜࡛࠶ࡿ㸬ᮏㄽᩥࡣ9 ❶࡛ᵓᡂࡉࢀ࡚ ࠸ࡿ㸬➨1 ❶࡛ࡣᮏ◊✲ࡢ⫼ᬒ࡜ᴫせࢆ㏙࡭ࡿ㸬➨ 2 ❶࡛ࡣ⬻ CT ⏬ീୖࡢ㉸ᛴ ᛶᮇ⬻᱾ሰᕢࢆ㆑ูࡍࡿࡓࡵࡢ᭱㐺࡞࢘࢕ࣥࢻ࢘᮲௳࡟ࡘ࠸࡚㏙࡭ࡿ㸬➨3 ❶࠿ ࡽ➨5 ❶࡛ࡣ⬻ CT ⏬ീୖࡢ␲ࢃࡋ࠸㉸ᛴᛶᮇ⬻᱾ሰᕢࢆ⮬ື᳨ฟࡍࡿࡓࡵࡢᑐ ഃᛶᕪศᢏ⾡ࢆ⏝࠸ࡓࢥࣥࣆ࣮ࣗࢱᨭ᥼デ᩿ࢩࢫࢸ࣒࡟ࡘ࠸࡚㏙࡭ࡿ㸬➨6 ❶࠿ ࡽ➨8 ❶࡛ࡣ㉸ᛴᛶᮇ⬻᱾ሰࡢ⏬ീデ᩿ࡸ἞⒪㐺ᛂࡢỴᐃࡢ㝿࡟᭷ຠ฼⏝ࡉࢀ࡚ ࠸ࡿᣑᩓᙉㄪ⏬ീ࠾ࡼࡧぢ࠿ࡅࡢᣑᩓಀᩘ⏬ീ࡟࠾ࡅࡿ᭱㐺࡞⾲♧᮲௳⮬ືㄪ⠇ ࢩࢫࢸ࣒࡟ࡘ࠸࡚㏙࡭ࡿ㸬᭱ᚋ࡟㸪➨9 ❶࡛ࡣᮏ◊✲ࡢࡲ࡜ࡵࢆ㏙࡭ࡿ㸬

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Studies on diagnostic support for hyperacute ischemic stroke

in brain CT and MR images

Hiroyuki Nagashima

Department of Intelligent Image Information,

Division of Regeneration and Advanced Medical Sciences,

Graduate School of Medicine,

Gifu University

1-1 Yanagido, Gifu-shi, Gifu 501-1194, Japan

TEL: 027-235-9488, FAX: 027-235-2501

E-mail: [email protected]

Thesis adviser: Professor Hiroshi Fujita

Abstract

The purposes of this thesis are to attempt the optimization of image display conditions in brain computed tomography (CT) images, to develop an computerized scheme for detecting automatically the subtle image findings of hyperacute ischemic stroke (AIS) on brain CT images, and to develop a computerized scheme for adjusting automatically the proper display conditions in brain magnetic resonance images for support the radiologists and neurosurgeons who perform the diagnostic imaging of AIS. This paper consists of nine chapters. Chapter 1 describes the background and overview of this study. Chapter 2 describes the proper window widths for recognising the local lesions of AIS on brain CT images. Chapters 3-5 describe a computer-aided diagnostic scheme using the contralateral subtraction technique which detects automatically the suspected lesions in diagnostic brain CT imaging for AIS. Chapters 6-8 describe a computerized scheme for automated adjustment of proper display conditions in diffusion-weighted magnetic resonance images and apparent diffusion coefficient maps effectively used for diagnostic imaging and treatment decisions of AIS. Finally, chapter 9 summarizes all of these studies.

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┠ ḟ

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1 ❶ ⥴ ㄽ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 1

1.1 ࡣࡌࡵ࡟㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 1 1.2 ⬻ CT ⏬ീ࡟࠾ࡅࡿ⏬ീ⾲♧᮲௳ࡢ᭱㐺໬㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 2 1.3 ⬻ CT ⏬ീ࡟࠾ࡅࡿࢥࣥࣆ࣮ࣗࢱᨭ᥼᳨ฟ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 3 1.4 ⬻ MR ⏬ീ࡟࠾ࡅࡿ⾲♧᮲௳ࡢ⮬ືㄪ⠇㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 4 1.5 ᮏ◊✲ࡢ┠ⓗ࡜ᵓᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 4 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 6

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2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ

࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃

13

2.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 13 2.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 13 2.2.1 ࢹ࢕ࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸ࡓᐇ㦂㺃㺃㺃㺃㺃㺃㺃 14 2.2.1.1 ࢹ࢕ࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࡢసᡂ㺃㺃㺃㺃㺃 14 2.2.1.2 ⏬ീホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 16 2.2.1.2.1 ⏬ീࣀ࢖ࢬࡢ ᐃ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 16 2.2.1.2.2 ROC ゎᯒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 16 2.2.2 ⮫ᗋ⏬ീࢆ⏝࠸ࡓᐇ㦂㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 16 2.2.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 16 2.2.2.2 ROC ゎᯒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 17 2.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 19 2.3.1 ࢹ࢕ࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸ࡓᐇ㦂㺃㺃㺃㺃㺃㺃㺃 19 2.3.2 ⮫ᗋ⏬ീࢆ⏝࠸ࡓᐇ㦂㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 20 2.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 21 2.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 23 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 24

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3 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ᳨ฟࡢࡓࡵࡢ

ࢥࣥࣆ࣮ࣗࢱᨭ᥼デ᩿ࢩࢫࢸ࣒㸦

1㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 25

3.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 25 3.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 25 3.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫࡢホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 25 3.2.2 ᑐഃᛶᕪศ⏬ീࡢసᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 27 3.2.3 ⬻᱾ሰࡢೃ⿵㝜ᙳࡢ⮬ືᢳฟ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 27 3.2.4 ᢳฟࡋࡓ⬻᱾ሰೃ⿵㝜ᙳࡢ≉ᚩ㔞ศᯒ㺃㺃㺃㺃㺃㺃㺃㺃㺃 27 3.2.5 ࢩࢫࢸ࣒ࡢ≉ᛶホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 31 3.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 31 3.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 33 3.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 37 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 37

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4 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ᳨ฟࡢࡓࡵࡢ

ࢥࣥࣆ࣮ࣗࢱᨭ᥼デ᩿ࢩࢫࢸ࣒㸦

2㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 39

4.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 39 4.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 39 4.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫࡢホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 39 4.2.2 ᥦ᱌ᡭἲࡢᴫせ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 40 4.2.3 ᑐഃᛶᕪศ⏬ീࡢసᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 40 4.2.4 ⬻᱾ሰೃ⿵㝜ᙳࡢᣠ࠸ୖࡆฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 43 4.2.5 ➨ 1 ẁ㝵࡟࠾ࡅࡿ≉ᚩᢳฟฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 44 4.2.6 ➨ 1 ẁ㝵࡟࠾ࡅࡿഇ㝧ᛶೃ⿵ࡢ㝖ཤ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 44 4.2.7 ➨ 2 ẁ㝵࡟࠾ࡅࡿ≉ᚩᢳฟฎ⌮࡜ ㉸ᛴᛶᮇ⬻᱾ሰࡢ᳨ฟ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 44 4.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 45 4.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 49 4.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 52 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 53

(8)

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5 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ᳨ฟࡢࡓࡵࡢ

ࢥࣥࣆ࣮ࣗࢱᨭ᥼デ᩿ࢩࢫࢸ࣒㸦

3㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 55

5.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 55 5.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 55 5.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 55 5.2.2 ᥦ᱌ᡭἲࡢᴫせ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 57 5.2.3 ᑐഃᛶయ✚ᕪศࢹ࣮ࢱࡢసᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 57 5.2.4 ㉸ᛴᛶᮇ⬻᱾ሰೃ⿵ࡢᣠ࠸ୖࡆฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 58 5.2.5 ≉ᚩᢳฟฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 59 5.2.6 ㉸ᛴᛶᮇ⬻᱾ሰ㝜ᙳࡢ᳨ฟฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 60 5.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 62 5.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 64 5.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 66 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 66

➨

6 ❶ ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓ⬻ MR ⏬ീ࡟࠾ࡅࡿ

⾲♧᮲௳⮬ືㄪ⠇ࢩࢫࢸ࣒㸦

1㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 67

6.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 67 6.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 68 6.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 68 6.2.2 ᥦ᱌ᡭἲࡢᴫせ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 68 6.2.3 ⬻ᐇ㉁㒊ࡢᢳฟฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 69 6.2.4 どᗋ఩⨨Ỵᐃᡭἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 71 6.2.5 どᗋ㑅ᢥᡭἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 72 6.2.6 DWI ࡢ⾲♧᮲௳ࡢㄪ⠇㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 73 6.2.7 ࢩࢫࢸ࣒ࡢ≉ᛶホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 73 6.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 75 6.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 77 6.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 80 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 80

(9)

( vi )

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7 ❶ ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓ⬻ MR ⏬ീ࡟࠾ࡅࡿ

⾲♧᮲௳⮬ືㄪ⠇ࢩࢫࢸ࣒㸦

2㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 83

7.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 83 7.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 84 7.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 84 7.2.2 ᥦ᱌ᡭἲࡢᴫせ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 85 7.2.3 ⬻ᐇ㉁㒊ࡢᢳฟฎ⌮㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 85 7.2.4 ⃰ᗘࣄࢫࢺࢢ࣒ࣛゎᯒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 86 7.2.5 DWI ࡢ⾲♧᮲௳ࡢㄪ⠇㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 86 7.2.6 ࢩࢫࢸ࣒ࡢ≉ᛶホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 86 7.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 89 7.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 91 7.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 93 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 93

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8 ❶ ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓ⬻ MR ⏬ീ࡟࠾ࡅࡿ

⾲♧᮲௳⮬ືㄪ⠇ࢩࢫࢸ࣒㸦

3㸧㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 97

8.1 ⥴ゝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 97 8.2 ᪉ἲ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 97 8.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 97 8.2.2 3 ḟඖ⏬ീࡢసᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 98 8.2.3 ⬻ᐇ㉁㒊ࡢᢳฟ࡜ ADC map ࡢసᡂ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 98 8.2.4 ⃰ᗘࣄࢫࢺࢢ࣒ࣛゎᯒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 99 8.2.5 DWI ࠾ࡼࡧ ADC map ࡢ⾲♧᮲௳ࡢㄪ⠇㺃㺃㺃㺃㺃㺃㺃㺃 100 8.2.6 ࢩࢫࢸ࣒ࡢ≉ᛶホ౯㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 100 8.3 ⤖ᯝ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 102 8.4 ⪃ᐹ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 105 8.5 ⤖ㄒ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 106 ཧ⪃ᩥ⊩㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 106

(10)

➨

9 ❶ ⤖ ㄽ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 107

ㅰ㎡㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 111

ᮏㄽᩥ࡛⏝࠸ࡓㄽᩥ࠾ࡼࡧⓎ⾲ࣜࢫࢺ㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃㺃 113

(11)

➨

_{1 ❶}

⥴ ㄽ

(12)

➨1 ❶ ⥴ㄽ

➨

1 ❶ ⥴ ㄽ

1.1 ࡣࡌࡵ࡟ ࢃࡀᅜ࡟࠾ࡅࡿ⬻⾑⟶⑌ᝈࡢṚஸ⪅ᩘࡣ㸪ᝏᛶ᪂⏕≀㸪ᚰ⑌ᝈ㸪⫵⅖࡟ḟ࠸࡛ Ṛᅉࡢ➨ 4 ఩࡛࠶ࡿ [1]㸬ࡲࡓ㸪⬻⾑⟶⑌ᝈࡢᖹᆒᅾ㝔᪥ᩘࡣ㸪⢭⚄࠾ࡼࡧ⾜ື ࡢ㞀ᐖࢆྵࡴ⑌ᝈࢆ㝖ࡅࡤ㸪ࡍ࡭࡚ࡢ⑌ᝈࡢ୰࡛᭱ࡶ㛗ࡃ㸪せ௓ㆤᛶ⑌ᝈࡢ㤳఩ ࢆ༨ࡵ࡚࠸ࡿ [2]㸬ࡇࡢࡼ࠺࡞≧ἣࡢ୰࡛㸪⬻⾑⟶⑌ᝈࡢデ᩿࠾ࡼࡧ἞⒪ࡣ㸪⏕ ࿨ணᚋࡢࡳ࡞ࡽࡎ㸪᪥ᖖ⏕άࡸ♫఍⏕ά࡬ࡢ᚟ᖐࡢࡓࡵࡢᶵ⬟ᨵၿ࡬ࡢᐤ୚ࡶồ ࡵࡽࢀ࡚࠸ࡿ㸬 ⬻⾑⟶⑌ᝈࡣ㸪⬻᱾ሰ㸪⬻ෆฟ⾑㸪ࢡࣔ⭷ୗฟ⾑࡟኱ูࡉࢀࡿࡀ㸪60㹼70 %ࡣ ⬻᱾ሰࡀ༨ࡵࡿ [3]㸬⬻᱾ሰ࡜ࡣ㸪⏕ά⩦័⑓࡟ࡼࡿື⬦◳໬ࡸᚰ⮚ෆࡢ⾑ᰦࡀ ཎᅉ࡛⬻ື⬦ࡀ⊃✽ࡲࡓࡣ㛢ሰࢆ㉳ࡇࡋ㸪⬻⣽⬊ࡀ㞀ᐖࡉࢀࡿ⑌ᝈ࡛࠶ࡿ㸬἞⒪ ἲ࡜ࡋ࡚ࡣ㸪⾑ᰦ⁐ゎ⒪ἲ㸪ᢠจᅛ⒪ἲ㸪ᢠ⾑ᑠᯈ἞⒪ࡀ᪋⾜ࡉࢀ㸪⬻⹫⾑ᚋࡢ ⤒㐣᫬㛫࡟ࡼࡗ࡚ྛ἞⒪ἲࡀ㑅ᢥࡉࢀࡿ㸬2005 ᖺ 10 ᭶࡟ㄆྍࡉࢀ㸪⬻᱾ሰࡢ㉸ ᛴᛶᮇࢆᑐ㇟࡟ᐇ᪋ࡉࢀࡿ⤌⧊ᆺࣉࣛࢫ࣑ࣀࢤࣥάᛶ໬ᅉᏊ㸦࢔ࣝࢸࣉ࣮ࣛࢮ㸧 ࢆ⏝࠸ࡓ⾑ᰦ⁐ゎ⒪ἲࡣ㸪ᚋ㑇⑕ࡢ࡞࠸๻ⓗ࡞⑕≧ᨵၿࢆࡶࡓࡽࡍ୍᪉㸪἞⒪㛤 ጞ᫬㛫ࡀ⤒㐣ࡍࡿ࡯࡝㸪ᩆ῭ྍ⬟࡞⬻ᐇ㉁㒊࡟୙ྍ㏫ⓗ࡞ኚ໬ࢆ᮶ࡓࡍࡓࡵ㸪἞ ⒪ࡢ᭷ຠᛶࡀపࡃ࡞ࡾ㸪᱾ሰᛶฟ⾑࡞࡝ࡢ㔜኱࡞ྜే⑕ࢆᣍࡃྍ⬟ᛶࡶ࠶ࡿ࡜ሗ ࿌ࡉࢀ࡚࠸ࡿ [4]㸬ࡑࡢࡓࡵ㸪⏕࿨ணᚋࡸ᪥ᖖ࣭♫఍⏕άࢆ⪃៖ࡍࡿ࡜㸪᪩ᮇ࡟ ⬻᱾ሰ࡛࠶ࡿࡇ࡜ࢆデ᩿ࡋ㸪ᩆ῭ྍ⬟࡞⬻ᐇ㉁㒊ࡢ᭷↓ࢆุ᩿ࡋ࡚㸪἞⒪ࢆ㛤ጞ ࡍࡿࡇ࡜ࡀᚲせ࡜࡞ࡿ㸬᪥ᮏ⬻༞୰Ꮫ఍ࡀసᡂࡋࡓ࢔ࣝࢸࣉ࣮ࣛࢮࢆ⏝࠸ࡓ⾑ᰦ ⁐ゎ⒪ἲ࡟㛵ࡍࡿᣦ㔪࡟ࡣ㸪⏬ീデ᩿ࡣ᭱ప㝈࡛῭ࡲࡏ㸪἞⒪㛤ጞ᫬㛫ࢆ㐜ࡽࡏ ࡚ࡣ࡞ࡽ࡞࠸ࡇ࡜ࡀ⧞ࡾ㏉ࡋグࡉࢀ࡚࠸ࡿ [5]㸬 ⬻᱾ሰࡢ㉸ᛴᛶᮇ࡟࠾ࡅࡿ⏬ീデ᩿࡟ࡣ㸪༢⣧ computed tomography㸦CT㸧᳨ ᰝࡸmagnetic resonance imaging㸦MRI㸧᳨ᰝࡀᐇ᪋ࡉࢀࡿ㸬༢⣧ CT ᳨ᰝࡣ㸪ྛ᪋

タ࡟࠾ࡅࡿ⿦⨨ࡢᬑཬ࡜✌ാయไ㸪᳨ᰝ᫬㛫ࡀ▷࠸࡞࡝ࡢ≉㛗ࢆ᭷ࡍࡿࡇ࡜࠿ࡽ㸪㉸ᛴᛶᮇ⬻᱾ሰࡢ⏬ീデ᩿࡜ࡋ࡚➨୍࡟㑅ᢥࡉࢀࡿ㸬༢⣧ CT ᳨ᰝࡣ㸪ࡇࢀࡲ࡛ ⬻ෆฟ⾑ࡸ⬻⭘⒆࡞࡝ࡢ㝖እデ᩿ࡀ୺య࡛࠶ࡗࡓࡀ㸪CT ⿦⨨ࡢⓎᒎ࡟ࡼࡾపࢥ ࣥࢺࣛࢫࢺ᳨ฟ⬟ࡀྥୖࡋࡓࡓࡵ㸪⬻⹫⾑ࡢึᮇẁ㝵࡛⓶㧊ቃ⏺ࡢᾘኻ㸪ࣞࣥࢬ ᰾࣭ᓥ⓶㉁ࡢ୙᫂░໬㸪⬻⁁ࡢᾘኻ࣭⊃ᑠ໬ࡢࡼ࠺࡞᪩ᮇ⹫⾑ኚ໬ࢆᥥฟ࡛ࡁࡿ ࡼ࠺࡟࡞ࡗࡓ㸬ࡑࡢࡓࡵ㸪CT ⏬ീ࡛᪩ᮇ⹫⾑ኚ໬ࢆ☜ㄆࡋ㸪ࡑࡢ⠊ᅖࡀ୰኱⬻ ື⬦ᨭ㓄ࡢ⬻ᐇ㉁㒊඲యࡢ 1/3 ௨ୗ࡛࠶ࡾ㸪ୟࡘ⬻ෆฟ⾑ࡢᏑᅾࡀ㝖እࡉࢀ㸪ྛ

(13)

➨1 ❶ ⥴ㄽ 2 -✀⚄⤒ᚩೃࡢ㐺ᛂᇶ‽ࡸ㝖እᇶ‽ࢆ‶ࡓࡋࡓⓎ⑕ᚋ3 ᫬㛫௨ෆࡢ⬻᱾ሰ࡛ࡣ㸪࢔ ࣝࢸࣉ࣮ࣛࢮࢆ⏝࠸ࡓ⾑ᰦ⁐ゎ⒪ἲࡀᐇ᪋ࡉࢀࡿ [5]㸬࡞࠾㸪ୖグ἞⒪ᣦ㔪࡛ࡣ㸪⾑ᰦ⁐ゎ⒪ἲࡢ㐺ᛂỴᐃ࡟㛵ࡍࡿከ᪋タ⮫ᗋ◊✲ࡢ⤖ᯝ࡟࠾࠸࡚㸪CT ⏬ീࢆ⏝ ࠸ࡿࡇ࡜ࡢ⛉Ꮫⓗ᰿ᣐࡀᚓࡽࢀ࡚࠸ࡿࡇ࡜࠿ࡽ㸪⾑ᰦ⁐ゎ⒪ἲࡢ㐺ᛂࢆุ᩿ࡍࡿ ࡓࡵࡢ⏬ീデ᩿࡟ࡣ CT ᳨ᰝࢆ᪋⾜ࡋホ౯ࡍࡿࡇ࡜ࡀ᥎ዡࡉࢀ࡚࠸ࡿ㸬ࡋ࠿ࡋ㸪 CT ⏬ീୖࡢ᪩ᮇ⹫⾑ኚ໬ࡣ㸪⬻ᐇ㉁㒊࡟ప྾཰ᇦ࡜ࡋ࡚ฟ⌧ࡍࡿ㠀ᖖ࡟ῐ࠸㝜 ᙳ࡛࠶ࡿࡓࡵどぬⓗ࡟㆑ูࡋ࡟ࡃࡃ㸪CT ⏬ീࢆៅ㔜࡟ㄞᙳࡋ࡞࠸࡜ぢⴠ࡜ࡉࢀ ࡿࡇ࡜ࡀ࠶ࡾ㸪ࡉࡽ࡟㸪ほᐹ⪅㛫࡛ㄆ㆑࡟ᕪࡀ⏕ࡌࡿ࡜ሗ࿌ࡉࢀ࡚࠸ࡿ [6]㹼[10]㸬 ୍᪉㸪MRI ᳨ᰝ࡛ࡣ㸪ྛ✀⏬ീࡀ᧜ീࡉࢀࡿ୰࡛㸪⤌⧊ෆࡢỈศᏊࡢᣑᩓ⌧㇟ ࢆ⏬ീ໬ࡍࡿᣑᩓᙉㄪ⏬ീ㸦diffusion-weighted image㸸DWI㸧ࡣ㸪㉸ᛴᛶᮇࡢ⹫⾑㡿ᇦࢆ㧗ಙྕ࡜ࡋ࡚᫂░࡟ᥥฟ࡛ࡁࡿ [11]㹼[15]㸬DWI ࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰ࡛࡞ ࡃ࡚ࡶ㧗ಙྕ࡟࡞ࡿࡇ࡜ࡀ࠶ࡾ㸦T2 shine through ⌧㇟㸧㸪ࡇࡢ⌧㇟ࡢᙳ㡪ࢆ㝖እ㸪 ࡘࡲࡾ㸪ᣑᩓࡢ⛬ᗘࢆᐃ㔞ⓗ࡟ホ౯ࡍࡿࡓࡵ㸪DWI ࡜㸪DWI ࡜ྠ᫬࡟᧜ീࡉࢀ ࡿ⏬ീ㸦b0 ⏬ീ㸧ࡢಙྕᙉᗘ࠿ࡽ㸪ぢ࠿ࡅࡢᣑᩓಀᩘ㸦apparent diffusion coefficient㸸 ADC㸧map ࡀసᡂࡉࢀࡿ [16]㹼[19]㸬ADC map ࡣ DWI ࡜࡜ࡶ࡟㸪Ꮡᅾデ᩿࠾ࡼ ࡧⓎ⑕࠿ࡽࡢ᫬ᮇุ᩿࡟฼⏝ࡉࢀ㸪⹫⾑㡿ᇦ࡟࠾ࡅࡿ἞⒪ᚋࡢྍ㏫ᛶࢆண ࡛ࡁ ࡿ࡜࠸࠺ሗ࿌ࡶ࠶ࡿ [20][21]㸬ࡇࢀࡽࡢ⏬ീୖࡢ⹫⾑㡿ᇦ࡟࠾ࡅࡿಙྕᙉᗘࡢ⛬ ᗘ࠾ࡼࡧ⠊ᅖࡢ☜ᐃࡣ㸪⾑ᰦ⁐ゎ⒪ἲ࡞࡝ࡢ἞⒪ἲࡢ㐺ᛂࢆỴᐃࡍࡿୖ࡛ࡶ㔜せ ࡞᝟ሗ࡜࡞ࡿ [22]㹼[27]㸬ࡋ࠿ࡋ㸪MRI ᳨ᰝࡣ㸪CT ᳨ᰝ࡟ẚ࡭᳨࡚ᰝ᫬㛫ࡀ㛗ࡃ㸪 ࡲࡓ㸪MR ⏬ീࢆ⏝࠸ࡓ⾑ᰦ⁐ゎ⒪ἲࡢ㐺ᛂᇶ‽࡟㛵ࡍࡿከ᪋タ⮫ᗋ◊✲ࡣᏑᅾ ࡏࡎ㸪DWI ࡢ⾑ᰦ⁐ゎ⒪ἲ࡟࠾ࡅࡿព⩏ࡣ᫂ࡽ࠿࡜࡞ࡗ࡚࠸࡞࠸㸬⌧ᅾ㸪ࣛࣥࢲ ࣒໬ẚ㍑ヨ㦂࡞࡝ࡢ㉁ࡢ㧗࠸⮫ᗋ◊✲ࡀᐇ᪋ࡉࢀ࡚࠸ࡿ [28]㹼[30]㸬 1.2 ⬻ CT ⏬ീ࡟࠾ࡅࡿ⏬ീ⾲♧᮲௳ࡢ᭱㐺໬ ㉸ᛴᛶᮇ⬻᱾ሰ࡟࠾ࡅࡿ CT ᳨ᰝ࡟࠾࠸࡚㸪࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨ࡢⓏሙ࡟ ࡼࡾ㸪ⷧ࠸ࢫࣛ࢖ࢫീࢆຍ⟬ࡍࡿࢫࢱࢵࢡࢫ࢟ࣕࣥࡀ฼⏝࡛ࡁ㸪ࡉࡽ࡟㸪⏬ീ෌ ᵓᡂ࡟฼⏝ࡉࢀࡿᢞᙳᩘࡢቑຍ࡜᳨ฟჾࡢᨵၿࡶຍࢃࡗ࡚㸪⬻⹫⾑ࡢึᮇẁ㝵࡛ ᪩ᮇ⹫⾑ኚ໬ࢆᥥฟ࡛ࡁࡿࡼ࠺࡟࡞ࡗࡓ㸬ࡋ࠿ࡋ㸪CT ⏬ീୖࡢ᪩ᮇ⹫⾑ኚ໬ࡣ㸪㠀ᖖ࡟ῐ࠸ప྾཰ᇦࢆ࿊ࡍࡿࡓࡵどぬⓗ࡟㆑ูࡋ࡟ࡃࡃ㸪୙㐺ษ࡞᧜ᙳ᮲௳ୗ࡛ ᧜ᙳࡉࢀࡓሙྜ࡟ࡣぢⴠ࡜ࡉࢀࡿࡇ࡜ࡀ࠶ࡿ㸬ࡲࡓ㸪ྛ᪋タ࡛᧜ᙳࡉࢀ㸪the european cooperative acute stroke study㸦ECASS㸧࡟Ⓩ㘓ࡉࢀࡓ 620 ⑕౛ࡢ⬻ CT ⏬

ീ࡟࠾࠸࡚㸪⏬ീ୙Ⰻ࡞⑕౛ࡀ20 %Ꮡᅾࡋࡓ࡜ሗ࿌ࡉࢀ࡚࠸ࡿ [31]㸬ࡋࡓࡀࡗ࡚㸪

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➨1 ❶ ⥴ㄽ

ࡢタᐃࡀᚲせ࡛࠶ࡿ㸬

ࡇࢀࡲ࡛㸪⬻ CT ⏬ീ࡟࠾ࡅࡿపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟ࡢྥୖࢆ┠ⓗ࡜ࡋࡓ㸪⥺

㉁࡟㛵ࢃࡿ⟶㟁ᅽࡸ㸪⏬ീࣀ࢖ࢬ࡟㛵ࢃࡿࢫ࢟ࣕࣥ᪉ᘧ㸪㹖⥺ฟຊ㸪ࢫࣛ࢖ࢫཌ㸪 ࠾ࡼࡧ⏬ീ෌ᵓᡂ㛵ᩘ࡞࡝ࡢ᧜ᙳࣃ࣓࣮ࣛࢱࡢ᭱㐺໬࡟㛵ࡍࡿ◊✲ࡣ㸪ᩘከࡃሗ ࿌ࡉࢀ࡚࠸ࡿ [32]㹼[38]㸬ࡲࡓ㸪middle cerebral artery embolism local fibrinolytic intervention trial japan㸦MELT Japan㸧࡛ࡣ㸪⬻ CT ᳨ᰝ࡟࠾ࡅࡿ᧜ᙳ᮲௳࡜⏬ീ⾲ ♧᮲௳ࡢᶆ‽໬ࢆ⾜࠸㸪ࡉࡽ࡟㸪ㄞᙳカ⦎ࣉࣟࢢ࣒ࣛࢆ⏝ពࡋ࡚㸪᪩ᮇ⹫⾑ኚ໬ ࡟ᑐࡍࡿ᳨ฟ⬟ࡢྥୖࢆᅗࡗ࡚࠸ࡿ [39]㸬MELT Japan ࡢሗ࿌ࡢ୰࡛㸪⏬ീ⾲♧ ᮲௳࡛࠶ࡿ࢘࢕ࣥࢻ࢘ᖜ㸦window width㸸WW㸧ࡢタᐃࡣ㸪80 hounsfield units㸦HU㸧 ௨ୗ࡜ࡍࡿࡇ࡜ࡀ᥎ዡࡉࢀ࡚࠸ࡿ㸬୍᪉㸪⮫ᗋ⏬ീ࡟࠾ࡅࡿ୺ほⓗホ౯࡟ࡼࡾ㸪 WW ࢆ⊃ࡃࡋ࡚ほᐹࡍࡿࡇ࡜ࡀ᭷ຠ࡛࠶ࡿ࡜࠸࠺ሗ࿌ࡀࡉࢀ࡚࠸ࡿ [40][41]㸬 ᮏ◊✲࡛ࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡟㸪᧜ᙳ⥺㔞ࢆኚ໬ࡉࡏࡓࢹࢪࢱࣝࣇ࢓ࣥ ࢺ࣒⏬ീࢆసᡂࡋ㸪WW ࡢኚ໬ࡀపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟࡟୚࠼ࡿᙳ㡪࡟ࡘ࠸࡚ᐃ 㔞ⓗ࡟ホ౯ࡋࡓ㸬ࡉࡽ࡟㸪࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨࡛᧜ᙳࡉࢀࡓ㸪㉸ᛴᛶᮇ⬻᱾ ሰ⑕౛ࡀྵࡲࢀࡿCT ⏬ീࢆ⏝࠸ࡓほᐹ⪅ᐇ㦂ࢆᐇ᪋ࡋ࡚㸪WW ࡢ㐪࠸࡟࠾ࡅࡿ ㄞᙳ⢭ᗘ࡟ࡘ࠸᳨࡚ウࡋࡓ㸬 1.3 ⬻ CT ⏬ീ࡟࠾ࡅࡿࢥࣥࣆ࣮ࣗࢱᨭ᥼᳨ฟ ㏆ᖺ㸪་⏝⏬ീ㡿ᇦ࡟࠾࠸࡚ࢹ࢕ࢪࢱࣝ⏬ീᢏ⾡ࡢⓎ㐩࡟ࡼࡾ㸪࡯ࡰ඲࡚ࡢ⏬ ീࡢࢹ࢕ࢪࢱࣝ໬ࡀྍ⬟࡟࡞ࡗࡓ㸬ࡑࡢ୰࡛㸪ࢹ࢕ࢪࢱࣝ⏬ീࡢᥦ౪࡟࠾࠸࡚㸪デ᩿᝟ሗࢆ࡛ࡁࡿࡔࡅ㆑ูࡋࡸࡍࡃࡍࡿࡇ࡜㸪࠶ࡿ࠸ࡣ᪂ࡓ࡞デ᩿᝟ሗࢆ⏬ീ࡟ ௜ຍࡍࡿࡇ࡜ࡀ㔜せ࡞ㄢ㢟࡜࡞ࡗ࡚ࡁࡓ㸬ࡑࡢࡓࡵ㸪ࢹ࢕ࢪࢱࣝ⏬ീࢆ⏝࠸ࡓ⏬ ീデ᩿࡟࠾࠸࡚㸪㧗ᗘ࡞⏬ീฎ⌮ᢏ⾡ࡢ㛤Ⓨ [42][43]ࡀᚲせ࡛࠶ࡾ㸪ࡉࡽ࡟㸪⏬ ീࢹ࣮ࢱࡢゎᯒ⤖ᯝࢆ➨2 ࡢពぢ࡜ࡋ࡚་ᖌࡀ⏬ീデ᩿࡬✚ᴟⓗ࡟฼⏝ࡍࡿࢥࣥ ࣆ࣮ࣗࢱᨭ᥼デ᩿㸦computer-aided diagnosis㸸CAD㸧[44]㹼[47]ࢩࢫࢸ࣒ࡣ㸪ࢹ࢕ ࢪࢱࣝ⏬ീࡢ≉ᚩࢆ᭱኱㝈࡟฼⏝ࡋࡓᢏ⾡࡜ࡋ࡚㛤Ⓨࡀᮇᚅࡉࢀ࡚࠸ࡿ㸬CAD ࢩ ࢫࢸ࣒ࡢ୍⯡ⓗᙺ๭ࡣ㸪୺࡟⑓ᕢ㒊ࡢぢⴠ࡜ࡋࡢῶᑡ㸪デ᩿⤖ᯝࡢࡤࡽࡘࡁࡢῶ ᑡ㸪་ᖌࡢ㈇ᢸ㍍ῶ࡛࠶ࡿ㸬CAD ࢩࢫࢸ࣒ࡢ㛤Ⓨ࡟㛵ࡍࡿ◊✲ࡣ㸪⬚㒊༢⣧⏬ീ㸪 ஙᡣ⏬ീ㸪CT ࢥࣟࣀࢢࣛࣇ࢕࡞࡝ᵝࠎ࡞ࣔࢲࣜࢸ࢕ࡸᑐ㇟㒊఩࣭⑌⑓࡟ᑐࡋ᪋ ⾜ࡉࢀ࡚ࡁ࡚࠾ࡾ [48]㹼[58]㸪௒ᚋࡣ㸪᭦࡞ࡿ◊✲ࡢⓎᒎ࡜㸪ᐇ⏝ⓗ࡞ CAD ࢩࢫ ࢸ࣒ࡢ㛤Ⓨࡀ⾜ࢃࢀ࡚࠸ࡃࡶࡢ࡜ᛮࢃࢀࡿ㸬 ᮏ◊✲࡛ࡣ㸪᪩ᮇデ᩿ࡀᝈ⪅ࡢ⏕Ṛ࠾ࡼࡧணᚋ࡟ᙳ㡪ࢆཬࡰࡍ⬻᱾ሰࢆᑐ㇟࡟㸪 ⑓ᕢࡢ㆑ูࡀᅔ㞴࡛་ᖌࡢ⇍⦎ᗘ࡟ᕥྑࡉࢀࡿ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾

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➨1 ❶ ⥴ㄽ 4 -ሰࡢ⏬ീデ᩿࡟╔┠ࡋ㸪⹫⾑㡿ᇦࢆ⮬ື᳨ฟࡍࡿCAD ࢩࢫࢸ࣒ࡢ㛤Ⓨࢆヨࡳࡓ㸬 ▷᫬㛫࡛ᐜ᫆࡟᳨ᰝྍ⬟࡞ CT ᳨ᰝ࡟࡚㸪㠀ᖖ࡟ῐ࠸㉸ᛴᛶᮇ⬻᱾ሰࡢ⏬ീᡤぢ ࢆぢⴠ࡜ࡍࡇ࡜࡞ࡃࢥࣥࣆ࣮ࣗࢱ᳨ฟࡍࡿࡇ࡜ࡣ㸪⾑ᰦ⁐ゎ⒪ἲࡢ㐺ᛂࢆ㎿㏿ୟ ࡘⓗ☜࡟Ỵᐃ࡛ࡁ㸪㔜⠜࡞ฟ⾑ᛶྜే⑕ࡢ㜵Ṇ࡟ࡶࡘ࡞ࡀࡿ㸬 1.4 ⬻ MR ⏬ീ࡟࠾ࡅࡿ⾲♧᮲௳ࡢ⮬ືㄪ⠇ ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡟᧜ീࡉࢀࡿ DWI ࡣ㸪⹫⾑㡿ᇦࢆ㧗ಙྕ࡟ᥥฟ࡛ࡁ㸪 ⏬ീデ᩿࡟࠾࠸࡚୰ᚰⓗ࡞ᙺ๭ࢆᡂࡋ࡚࠸ࡿ㸬ࡲࡓ㸪ᣑᩓࡢ⛬ᗘࢆᐃ㔞⾲♧ࡋࡓ ADC map ࡣ㸪DWI ࡜࡜ࡶ࡟㸪Ꮡᅾデ᩿࠾ࡼࡧⓎ⑕࠿ࡽࡢ᫬ᮇุ᩿࡟฼⏝ࡉࢀ࡚ ࠸ࡿ㸬ࡉࡽ࡟㸪DWI ࠾ࡼࡧ ADC map ࡟࠾ࡅࡿ⹫⾑㡿ᇦࡢಙྕᙉᗘࡢ⛬ᗘ࠾ࡼࡧ ⠊ᅖࡢ☜ᐃࡣ㸪⾑ᰦ⁐ゎ⒪ἲ࡞࡝ࡢ἞⒪ἲࡢ㐺ᛂࢆỴᐃࡍࡿୖ࡛ࡶ㔜せ࡞᝟ሗ࡜

࡞ࡿ㸬ࡋ࠿ࡋ㸪⹫⾑㡿ᇦࡢ⛬ᗘࡸ⠊ᅖࡣ㸪⾲♧⏬ീࡢ⏬⣲್ࡢᖜ࡟ᑐᛂࡍࡿWW

ࡸ㸪WW ࡢ୰㛫್࡛࠶ࡿ࢘࢕ࣥࢻ࢘ࣞ࣋ࣝ㸦window level㸸WL㸧ࡢㄪ⠇࡟ࡼࡾ኱ ࡁࡃኚ໬ࡍࡿ [59]㸬ࡑࡢࡓࡵ㸪୙㐺ษ࡞⾲♧᮲௳࡛⏬ീデ᩿ࢆᐇ᪋ࡍࡿ࡜㸪㉸ᛴ ᛶᮇ⬻᱾ሰࡢᏑᅾデ᩿ࡸ⠊ᅖุᐃࡢ⢭ᗘపୗ࡟ࡘ࡞ࡀࡿྍ⬟ᛶࡀ࠶ࡿ [60]㹼[62]㸬

ཌ ⏕ ປ ാ ┬ ◊ ✲ ⌜ Acute Stroke Imaging Standardization Group-Japan 㸦ASIST-Japan㸧ࡣ㸪ᇶᗏ᰾ࣞ࣋ࣝࡢỈᖹ᩿ b0 ⏬ീࡢどᗋࡢ఩⨨࡟෇ᙧࡢ㛵ᚰ㡿 ᇦ㸦region of interest㸸ROI㸧ࢆ┠ど࡟࡚ᡭື࡛タᐃࡋ㸪ᖹᆒ⏬⣲್ࢆィ ࡋ࡚㸪 ࡑࡢ್ࢆDWI ⾲♧ࡢ WW ࡟㸪WW ࡢ୰㛫್ࢆ WL ࡟タᐃࡍࡿࡇ࡜࡛㸪DWI ࡢ⾲ ♧᮲௳ࢆᶆ‽໬ࡍࡿ᪉ἲࢆ⪃᱌ࡋࡓ [63]㹼[66]㸬ࡇࡢ᪉ἲࡣ㸪᪋タ㛫࠾ࡼࡧᢸᙜ ⪅㛫࡟࠾ࡅࡿ DWI ࡢ⾲♧᮲௳ࡢኚືࢆపῶ࡛ࡁࡿ࡜ሗ࿌ࡉࢀ࡚࠾ࡾ㸪⏬ീデ᩿ ࡢ⢭ᗘྥୖ࡜⾑ᰦ⁐ゎ⒪ἲࡢṇ☜࡞㐺ᛂỴᐃ࡟࠾࠸࡚㸪᭷⏝࡞᪉ἲ࡛࠶ࡿ࡜⪃࠼ ࡿ㸬ࡋ࠿ࡋ㸪ASIST-Japan ࡢᥦ᱌᪉ἲࡣ㸪ࣔࢽࢱୖࡢ⏬ീࢆほᐹࡍࡿ་ᖌࡢᡭື ࡟ࡼࡿROIタᐃࡀᚲせ࡜࡞ࡿࡓࡵ㸪෌⌧ᛶ࡟ຎࡾ㸪సᴗ᫬㛫࡜ປຊࢆᚲせ࡜ࡍࡿ㸬 ᮏ◊✲࡛ࡣ㸪ASIST-Japan ࡟ࡼࡾ⪃᱌ࡉࢀࡓ DWI ࡢ⾲♧᮲௳ࢆỴᐃࡍࡿ᪉ἲࡢ ᐇ⏝໬ࢆ┠ⓗ࡟㸪b0 ⏬ീࡢᕥྑ୧ഃࡢどᗋ఩⨨ࢆ⮬ືỴᐃࡋ㸪ṇᖖ࡞どᗋഃࢆ⮬ ື㑅ᢥࡍࡿᡭἲࢆ㛤Ⓨࡋࡓ㸬ࡑࡋ࡚㸪㑅ᢥࡉࢀࡓどᗋ఩⨨ࡢಙྕᙉᗘࢆ฼⏝ࡋ࡚㸪 DWI ࡢ⾲♧᮲௳ࢆ⮬ືㄪ⠇ࡍࡿࢩࢫࢸ࣒ࢆ㛤Ⓨࡋࡓ㸬 1.5 ᮏ◊✲ࡢ┠ⓗ࡜ᵓᡂ ᮏ◊✲ࡢ┠ⓗࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰࢆ⏬ീデ᩿ࡍࡿᨺᑕ⥺⛉་ࡸ⬻⚄⤒እ⛉་ࢆ ᨭ᥼ࡍࡿࡓࡵ㸪⬻CT ⏬ീ࡟࠾ࡅࡿ᭱㐺࡞⏬ീ⾲♧᮲௳㸦WW㸧ࢆỴᐃࡍࡿࡇ࡜㸪

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➨1 ❶ ⥴ㄽ

࡞ࡽࡧ࡟ CT ⏬ീୖࡢ⹫⾑㡿ᇦࢆ⮬ື᳨ฟࡍࡿࢩࢫࢸ࣒ࢆ㛤Ⓨࡍࡿࡇ࡜࡛࠶ࡿ㸬

ࡲࡓ㸪DWI ࠾ࡼࡧ ADC map ࡟࠾ࡅࡿ᭱㐺࡞⏬ീ⾲♧᮲௳ࢆ⮬ືỴᐃࡍࡿࢩࢫࢸ

࣒ࢆ㛤Ⓨࡍࡿࡇ࡜ࡶᮏ◊✲ࡢ┠ⓗ࡛࠶ࡿ㸬ᮏㄽᩥࡣ9 ❶࡛ᵓᡂࡉࢀ࡚࠸ࡿ㸬௨ୗ ࡟ࡑࡢᴫせࢆ♧ࡍ㸬 ➨2 ❶࡛ࡣ㸪ࠕ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ WW ࡢ᳨ウࠖ ࡟ࡘ࠸࡚㏙࡭ࡿ㸬ࡇࡇ࡛ࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰࢆࢩ࣑࣮ࣗࣞࢩࣙࣥࡋࡓࢹࢪࢱࣝࣇ ࢓ࣥࢺ࣒⏬ീ㸪࠾ࡼࡧ࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨ࢆ⏝࠸࡚ᐇ㝿࡟᧜ᙳࡉࢀࡓ㉸ᛴᛶ ᮇ⬻᱾ሰ⑕౛30 ౛࡜ṇᖖ⑕౛ 30 ౛ࡢ CT ⏬ീࡢ WW ࢆኚ໬ࡉࡏ࡚ᐇ᪋ࡋࡓほᐹ ⪅ᐇ㦂ࡢ⤖ᯝࢆ♧ࡍ㸬 ➨3 ❶㸪➨ 4 ❶㸪࠾ࡼࡧ➨ 5 ❶࡛ࡣ㸪ࠕ⬻CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ᳨ฟ ࡢࡓࡵࡢࢥࣥࣆ࣮ࣗࢱᨭ᥼デ᩿ࢩࢫࢸ࣒ࠖࡢࢸ࣮࣐ࡢୗ㸪➨3 ❶࡛ࡣ㸪ᮏ◊✲ࡢ ୺ࡓࡿ⏬ീฎ⌮࡛࠶ࡿ㸪ேయࡢᕥྑᑐ⛠ᛶࢆ฼⏝ࡋࡓᑐഃᛶᕪศᢏ⾡࡟ࡘ࠸࡚㏙ ࡭ࡿ㸬ࡉࡽ࡟㸪⏬ീᡤぢࡢ᭱ࡶ㢧ⴭ࡞1 ࢫࣛ࢖ࢫീࢆ฼⏝ࡋࡓ⹫⾑㡿ᇦࡢ⮬ື᳨ ฟᡭἲ࡟ࡘ࠸࡚ࡶ㏙࡭ࡿ㸬➨4 ❶࡛ࡣ㸪➨ 3 ❶࡛฼⏝ࡋࡓᑐഃᛶᕪศᢏ⾡ࢆᑟධ ࡋ㸪ࢩࢫࢸ࣒ࡢ᭦࡞ࡿᛶ⬟ྥୖࢆᅗࡿࡓࡵ㸪ୖ࣭ୗഃࡢࢫࣛ࢖ࢫീࢆ฼⏝ࡋࡓ≉ ᚩ㔞ゎᯒ࡟ࡼࡾഇ㝧ᛶೃ⿵ࢆ㝖ཤࡉࡏࡿᡭἲ࡟ࡘ࠸࡚㏙࡭ࡿ㸬➨5 ❶࡛ࡣ㸪➨ 3 ❶࠾ࡼࡧ➨4 ❶࡛ㄢ㢟࡜࡞ࡗࡓ㸪ഇ㝧ᛶೃ⿵ࡢཎᅉ࡜࡞ࡿ᧜ᙳయ఩ࡢഴࡁ࡟ࡼࡿ ᕥྑᑐ⛠ᛶࡢၥ㢟ࢆゎỴࡍࡿࡓࡵ㸪➼᪉ᛶࡢCT య✚ࢹ࣮ࢱࢆ฼⏝ࡋࡓ୕ḟඖⓗ ࡞ᅇ㌿⿵ṇ࢔ࣝࢦࣜࢬ࣒ࢆຍ࠼ࡓ㸪ᑐഃᛶᕪศᢏ⾡࡟ࡼࡿ㉸ᛴᛶᮇ⬻᱾ሰࡢ⮬ື ᳨ฟᡭἲ࡟ࡘ࠸࡚㏙࡭ࡿ㸬 ➨6 ❶㸪➨ 7 ❶㸪࠾ࡼࡧ➨ 8 ❶࡛ࡣ㸪ࠕ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓ⬻ MR ⏬ ീ࡟࠾ࡅࡿ⾲♧᮲௳⮬ືㄪ⠇ࢩࢫࢸ࣒ࠖࡢࢸ࣮࣐ࡢୗ㸪➨6 ❶࡛ࡣ㸪ASIST-Japan ࡟ࡼࡾ⪃᱌ࡉࢀࡓb0 ⏬ീୖࡢどᗋࡢಙྕᙉᗘࢆ฼⏝ࡍࡿ DWI ࡢ⾲♧᮲௳ㄪ⠇ᡭ ἲࡢ⮬ື໬ࢩࢫࢸ࣒࡟ࡘ࠸࡚㏙࡭ࡿ㸬➨ 7 ❶࡛ࡣ㸪➨ 6 ❶࡛ㄢ㢟࡜࡞ࡗࡓ㸪 ASIST-Japan ࡢ⪃᱌᪉ἲ࠾ࡼࡧᮏ⮬ື໬ࢩࢫࢸ࣒ࡢၥ㢟Ⅼࢆᨵၿࡍࡿࡓࡵ㸪どᗋ ఩⨨ࡢಙྕᙉᗘࢆ฼⏝ࡏࡎ࡟DWI ࡢ⾲♧᮲௳ࢆ⮬ືㄪ⠇ࡍࡿᡭἲ࡜ࡋ࡚㸪b0 ⏬ ീࡢ⬻ᐇ㉁㒊࡟࠾ࡅࡿ⃰ᗘࣄࢫࢺࢢ࣒ࣛࢆ฼⏝ࡋࡓ⮬ືㄪ⠇ࢩࢫࢸ࣒࡟ࡘ࠸࡚㏙ ࡭ࡿ㸬➨ 8 ❶࡛ࡣ㸪b0 ⏬ീࢆ౑⏝ࡍࡿࡇ࡜࡞ࡃ㸪┤᥋㸪DWI ࢆ㐺ṇ⾲♧ࡍࡿࡓ ࡵࡢ⮬ືㄪ⠇ᡭἲ࡟ࡘ࠸࡚㏙࡭ࡿ㸬ࡉࡽ࡟㸪㉸ᛴᛶᮇ⬻᱾ሰ࡟ᑐࡍࡿ⏬ീデ᩿ࡸ

἞⒪㐺ᛂࡢỴᐃ࡟࠾࠸࡚DWI ࡜࡜ࡶ࡟᭷ຠ฼⏝ࡉࢀ࡚࠸ࡿ㸪ADC map ࡟࠾ࡅࡿ

⾲♧᮲௳ࡢ⮬ືㄪ⠇ᡭἲ࡟ࡘ࠸࡚ࡶ㏙࡭ࡿ㸬

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➨1 ❶ ⥴ㄽ 6 -ཧ ཧ⪃ᩥ⊩ [1] ཌ⏕ປാ┬኱⮧ᐁᡣ⤫ィ᝟ሗ㒊㸸ᖹᡂ 23 ᖺேཱྀືែ⤫ィ᭶ሗᖺィ㸦ᴫᩘ㸧ࡢ ᴫἣ㸪http://www.mhlw.go.jp/toukei/saikin/hw/jinkou/geppo/nengai11/index.html [2] ཌ⏕ປാ┬኱⮧ᐁᡣ⤫ィ᝟ሗ㒊㸸ᝈ⪅ㄪᰝࡢᴫἣ㸸㏥㝔ᝈ⪅ࡢᖹᆒᅾ㝔᪥ᩘ ➼㸸2008㸪http://www.mhlw.go.jp/toukei/saikin/hw/kanja/08/index.html [3] ཌ⏕ປാ┬኱⮧ᐁᡣ⤫ィ᝟ሗ㒊㸸ᚰ⑌ᝈ㸫⬻⾑⟶⑌ᝈṚஸ⤫ィࡢᴫἣ㸸2004㸪 http://www.mhlw.go.jp/toukei/saikin/hw/jinkou/tokusyu/sinno05/index.html [4] ᖹ㔝↷அ㸪͆ᛴᛶᮇ⬻᱾ሰࡢ⏬ീデ᩿෌ධ㛛㸸ึᮇ⹫⾑⑓ኚࡢ⠊ᅖุᐃࡢ⌧≧ ࡜ㄢ㢟㸪͇⏬ീデ᩿㸪vol.25㸪no.12㸪pp.1471-1480㸪2005㸬 [5] ᪥ᮏ⬻༞୰Ꮫ఍་⒪ྥୖ࣭♫఍ಖ㝤ጤဨ఍ rt-PA㸦࢔ࣝࢸࣉ࣮ࣛࢮ㸧㟼ὀ⒪ἲ ᣦ㔪㒊఍㸪͆rt-PA㸦࢔ࣝࢸࣉ࣮ࣛࢮ㸧㟼ὀ⒪ἲ㐺ṇ἞⒪ᣦ㔪㸪͇⬻༞୰㸪vol.27㸪 no.2㸪pp.327-354㸪2005㸬

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[7] ᡂ෠༤❶㸪͆⬻᱾ሰࡢ early CT sign㸸⬻᱾ሰ㉸ᛴᛶᮇ㸸Brain attack ᫬௦ࡢデ᩿ ࡜἞⒪㸪͇་ṑ⸆ฟ∧㸪ᮾி㸪pp.25-31㸪2001㸬 [8] ᶫᮏὒ୍㑻㸪͆X ⥺ CT㸸⬻༞୰ࢆ㜵ࡄ㸫⑓デ㐃ᦠࡢ᭱๓⥺㸪͇༡ᒣᇽ㸪ᮾி㸪 pp.81-104㸪2001㸬 [9] ๓⏣ṇᖾ㸪͆ᛴᛶᮇ⬻᱾ሰࡢ⏬ീデ᩿෌ධ㛛㸸㢌㒊 CT ࡢ⮫ᗋⓗព⩏࡜ㄢ㢟㸸⾑ᰦ⁐ゎ⒪ἲࢆ⾜࠺࡟࠶ࡓࡾ㸪͇⏬ീデ᩿㸪vol.25㸪no.12㸪pp.1454-1462㸪2005㸬 [10] Ᏻ㝙➼ᛮ㸪ᗈ⏿ ඃ㸪ෆᒣ㞝௓㸪➉ෆ㟹἞㸪⸨ᮧ┤Ꮚ㸪͆Emergency Radiology㸸 ᩆᛴ⏬ീデ᩿㸦IVR ࢆྵࡴ㸧࡟࠾࠸࡚ᨺᑕ⥺⛉་ࡢ▱ࡗ࡚࠾ࡃ࡭ࡁ࣏࢖ࣥࢺ㸸 ⬻⾑⟶㞀ᐖࡢ἞⒪㑅ᢥ࡟࠾ࡅࡿ⏬ീデ᩿ࡢ⌧≧㸪͇᪥⋊་ሗ㸪vol.51㸪no.1㸪 pp.20-29㸪2006㸬 [11] ஭⏣ṇ༤㸪኱す㈗ᘯ㸪㇏⏣ᆂᏊ㸪⚟⏣ᅜᙪ㸪Ỉෆᐉኵ㸪͆ᣑᩓᙉㄪ⏬ീ㸸⮫ ᗋ⿦⨨࡟࠾ࡅࡿ⌧≧࡜ᑗ᮶㸪͇INNERVISION㸪vol.15㸪no.9㸪pp.63-66㸪2000㸬 [12] ⏣୰ᛅⶶ㸪͆Diffusion MRI 㧗ಙྕࡢព࿡ࡍࡿࡶࡢ㸸⬻᱾ሰ㉸ᛴᛶᮇ㸸Brain

attack ᫬௦ࡢデ᩿࡜἞⒪㸪͇་ṑ⸆ฟ∧㸪ᮾி㸪pp.32-37㸪2001㸬

[13] Saur D, kucinski T, Grzyska U, Eckert B, Eggers C, Niesen W, Schoder V, Zeumer H, Weiller C, Röther J, “Sensitivity and interrater agreement of CT and diffusion-weighted MR imaging in hyperacute stroke,” AJNR Am J Neuroradiol,

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➨1 ❶ ⥴ㄽ

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[15] ⾲฼▱ᖾ㸪ᫍ㔝㈗ᚿ㸪୸ᒣ႐ோ㸪すᮧ೺ྖ㸪͆᪩ᮇ⬻᱾ሰデ᩿࡟࠾ࡅࡿDiffusion MRI ࡢᙺ๭㸪͇᪥ᨺᢏᏛㄅ㸪vol.62㸪no.10㸪pp.1422-1427㸪2006㸬

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➨1 ❶ ⥴ㄽ

8

-[24] ⯚ᮌ೺ྐ㸪ⶶᮏせ஧㸪ᚋ⸨ṇ᠇㸪ᢲᮏ ๛㸪ᅵ஭኱㍜㸪ྜྷ⏣࿴㐨㸪㬆ᾏ ἞㸪 ỿ ṇᶞ㸪ᒣᙧ ᑓ͆Apparent diffusion coefficient ࢆ⏝࠸ࡓᛴᛶᮇ⬻⹫⾑㡿ᇦ ࡢྍ㏫ᛶホ౯㸪͇⬻༞୰ࡢእ⛉㸪vol.33㸪no.1㸪pp.30-34㸪2005㸬

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௓㸪ᒣୖ ᏹ㸪ᒸ⏣ 㟹㸪㛗㇂ᕝὈᘯ㸪ⱉᑿ୐⮧㸪ዟ⏣ ⪽㸪ᓠᯇ୍ኵ㸪㇏⏣ ୍๎㸪͆ASPECTS-DWI ࡟࠾ࡅࡿ㡿ᇦู᪩ᮇ⹫⾑ኚ໬࡜ rt-PA 㟼ὀ⒪ἲᚋࡢ⬻ ᱾ሰᝈ⪅ࡢ㌿ᖐ㸪⬻༞୰㸪vol.31㸪no.5㸪pp.366-373㸪2009㸬

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[32] ∦⏣࿴ᘅ㸪͆Neuro-imaging Update㸦⏬ീデ᩿ࡢศ㔝㸧㸸᪂ࡋ࠸ CT ᧜ീἲ㸸⬻ ⾑⟶㞀ᐖ࡬ࡢᛂ⏝㸪͇⬻༞୰㸪vol.26㸪no.4㸪pp.552-556㸪2004㸬

[33] ዟᮧ⨾࿴㸪͆పࢥࣥࢺࣛࢫࢺศゎ⬟ࡢホ౯᪉ἲ㸪͇࢔࣮ࣝࢸ࢕㸪vol.27㸪pp.42-47㸪 2005㸬

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➨1 ❶ ⥴ㄽ [34] ᑠᕝṇே㸪͆ᛴᛶᮇ⬻᱾ሰࡢ༢⣧ CT ࡟ࡘ࠸࡚㸫పࢥࣥࢺࣛࢫࢺศゎ⬟㸫㸪͇ ᪥ᨺᢏᏛㄅ㸪vol.62㸪no.10㸪pp.1377-1379㸪2006㸬 [35] ๓⏣ṇᖾ㸪͆ᛴᛶᮇ⬻᱾ሰ⏬ീデ᩿ࡢᶆ‽໬ࡢ⌧≧㸸༢⣧CT ࡢព⩏࡜ᶆ‽໬ ࡢ⌧≧㸪͇INNERVISION㸪vol.24㸪no.1㸪pp.11-14㸪2009㸬 [36] ⸨ᮧ୍㑻㸪͆᫂᪥࠿ࡽ౑࠼ࡿ㢌㒊 CT㸸㢌㒊༢⣧ CT ࡣࣀࣥ࣊ࣜ࢝ࣝ࠿࣊ࣜ࢝ ࣝ࠿㸽㸪͇࢔࣮ࣝࢸ࢕㸪vol.44㸪pp.25-33㸪2009㸬 [37] 㡲Ọ┾୍㸪㛗ᓥᏹᖾ㸪ᑠᯘ ㄔ㸪୰㔜ᐩኵ㸪ᑠᒇᰤ୍㸪᰿ᓊ ᚭ㸪ⓑ▼᫂ஂ㸪 ᕝᓥᗣᘯ㸪ཎᕝဴ⨾㸪͆16 ิ࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨࡟࠾ࡅࡿ⮬సࢹࢪࢱࣝࣇ ࢓ࣥࢺ࣒ࢆ⏝࠸ࡓ㉸పࢥࣥࢺࣛࢫࢺศゎ⬟ࡢホ౯㸸ᛴᛶᮇ⬻᱾ሰࡢCT ⏬ീᡤ ぢࡢ᳨ฟࢆ┠ⓗ࡜ࡋࡓ᧜ᙳ᮲௳ࡢ㐺ṇ໬࡟㛵ࡍࡿᇶ♏ⓗ᳨ウ㸪͇⩌㤿┴❧┴Ẹ ೺ᗣ⛉Ꮫ኱Ꮫ⣖せ㸪vol.4㸪pp.39-45㸪2009㸬 [38] ὾ཱྀ┤Ꮚ㸪ᑠᑎ⚽୍㸪͆ᛴᛶᮇ⬻᱾ሰデ᩿࡟ᑐࡍࡿ࣊ࣜ࢝ࣝࢫ࢟ࣕࣥࡢ㐺⏝ ࡟㛵ࡍࡿ᳨ウ㸪͇᪥ᨺᢏᏛㄅ㸪vol.66㸪no.6㸪pp.632-640㸪2010㸬 [39] ᑠᕝ ᙲ㸪͆ཌ⏕ປാ⛉Ꮫ◊✲㈝⿵ຓ㔠ࠕ㉸ᛴᛶᮇ⬻᱾ሰ࡟ᑐࡍࡿᒁᡤ⥺⁐ ゎἲࡢຠᯝ࡟㛵ࡍࡿ⮫ᗋ◊✲ࠖ㸪͇ᖹᡂ14 ᖺᗘ⥲ᣓ◊✲ሗ࿌᭩㸪2003. [40] ᖹ㔝↷அ㸪͆⬻༞୰ᑓ㛛་ࡢࡓࡵࡢ⬻⾑⟶㞀ᐖࡢ⏬ീデ᩿㸸ᛴᛶᮇ⬻᱾ሰࡢ 㢌㒊༢⣧CT࣭ᣑᩓᙉㄪ⏬ീ㸪͇ศᏊ⬻⾑⟶⑓㸪vol.7㸪no.1㸪pp.78-85㸪2008㸬 [41] ⣽▮㈗ு㸪బࠎᮌ┿⌮㸪͆㉸ᛴᛶᮇ⬻᱾ሰࡢCT㸸ᩆᛴ࡛ᙺ❧ࡘ㢌㒊 CT࣭MRI㸪͇ ༡Ụᇽ㸪ᮾி㸪pp.22-26㸪2010㸬

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[50] ୰ᕝ₶ဢ㸪ΎỈ᫛ఙ㸪ᑠ⏿⚽ᩥ㸪͆ከ᫬┦ࡢ3 ḟඖ࣐ࣝࢳࢫࣛ࢖ࢫ CT ീ࠿ࡽ ࡢ⫢⭘⒗ࡢ⮬ືᢳฟᡭἲࡢ㛤Ⓨ㸪͇㟁Ꮚ᝟ሗ㏻ಙᏛ఍ㄽᩥㄅ㸪vol.J87-D-ϩ㸪no.1㸪 pp.260-270㸪2004㸬 [51] ୖཎ⌮ᏹ㸪㈈⏣ఙ௓㸪ஂಖ ‶㸪Ἑ⏣ెᶞ㸪ோᮌ Ⓩ㸪す㇂ ᘯ㸪➲ᕝ㐨୕㸪 ᳃ᒣ⣖அ㸪࣐͆ࣝࢳࢫࣛ࢖ࢫ CT ⏬ീࢆ⏝࠸ࡓ㦵⢒㧼⑕デ᩿ᨭ᥼࢔ࣝࢦࣜࢬ࣒ ࡢᵓ⠏㸪͇㟁Ꮚ᝟ሗ㏻ಙᏛ఍ᢏ⾡◊✲ሗ࿌㸪vol.105㸪no.221㸪pp.59-62㸪2005㸬 [52] ோᮌ Ⓩ㸪͆࿧྾ჾ࣭ᚠ⎔ჾࡢCAD㸪͇Med Imag Tech㸪vol.24㸪no.3㸪pp.161-166㸪

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ᙪ㸪ຍ⸨༤ᇶ㸪ᒾ㛫 ஽㸪ᫍ ༤᫛㸪⸨⏣ᗈᚿ㸪͆⬻MR ⏬ീ࡟࠾ࡅࡿࣛࢡࢼ

᱾ሰࡢ᳨ฟἲ㸪͇㟁Ꮚ᝟ሗ㏻ಙᏛ఍ㄽᩥㄅ㸪vol.J90-D㸪no.7㸪pp.1820-1829㸪2007㸬 [57] ᑠ⏿⚽ᩥ㸪͆ከḟඖ་⏝⏬ീࡢ▱ⓗデ᩿ᨭ᥼ࢩࢫࢸ࣒㸪͇Med Imag Tech㸪vol.26㸪

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[61] Chowdhury D, Wardlaw JM, Dennis MS, “Are multiple acute small subcortical infarctions caused by embolic mechanisms?,” J Neurol Neurosurg Psychiatry, vol.75, no.10, pp.1416-1420, 2004. [62] ᖹ㔝↷அ㸪͆㉸ᛴᛶᮇ⬻᱾ሰ⏬ീデ᩿ࡢᶆ‽໬ࡢ⌧≧㸸MRI㸦DWI㸪MRA㸪 T2*WI㸧ࡢព⩏࡜ᶆ‽໬ࡢ⌧≧㸪͇INNERVISION㸪vol.24㸪no.1㸪pp.15-19㸪2009㸬 [63] బࠎᮌ┿⌮㸪⸨ཎಇᮁ㸪͆㢌㒊㡿ᇦ࡛ࡢᣑᩓᙉㄪ⏬ീࡢ⮫ᗋ㸪͇᪥⋊་ሗ㸪vol.50㸪 no.4㸪pp.621-628㸪2005㸬 [64] బࠎᮌ┿⌮㸪͆ᛴᛶᮇ⬻᱾ሰࡢ CT㸪MRI㸸ᶆ‽໬ࡢព⩏㸪͇⬻༞୰㸪vol.27㸪 no.4㸪pp.564-567㸪2005㸬 [65] బࠎᮌ┿⌮㸪͆⬻༞୰ᑓ㛛་ࡢࡓࡵࡢ⬻⾑⟶㞀ᐖࡢ⏬ീデ᩿㸸ᅜෆ࡟࠾ࡅࡿ ᣑᩓᙉㄪ⏬ീ㸪℺ὶᙉㄪ⏬ീࡢᶆ‽໬ࡢືྥ㸪͇ศᏊ⬻⾑⟶⑓㸪vol.6㸪no.1㸪 pp.73-77㸪2007㸬

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-➨

➨

2 ❶

⬻

CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ

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➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ 13

-➨

➨

2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ

࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ

2.1 ⥴ゝ ㉸ᛴᛶᮇ⬻᱾ሰ࡟࠾ࡅࡿ CT ᳨ᰝࡣ㸪⿦⨨ࡢᬑཬ࡜✌ാయไ㸪᳨ᰝ᫬㛫ࡀ▷࠸ ࡞࡝ࡢ≉㛗ࢆᣢࡕ㸪ከ᪋タ⮫ᗋ◊✲࡟ࡼࡿ⾑ᰦ⁐ゎ⒪ἲࡢ CT ⏬ീࢆ⏝࠸ࡓ㐺ᛂ Ỵᐃࡢ⛉Ꮫⓗ᰿ᣐࡀᚓࡽࢀ࡚࠸ࡿࡇ࡜࠿ࡽ㸪⏬ീデ᩿࡜ࡋ࡚➨୍࡟㑅ᢥࡉࢀࡿ㸬 ࡋ࠿ࡋ㸪㉸ᛴᛶᮇࡢ CT ⏬ീᡤぢ࡛࠶ࡿ᪩ᮇ⹫⾑ኚ໬ࡣ㸪⬻ᐇ㉁࡟㠀ᖖ࡟ῐ࠸ప ྾཰ᇦ࡜ࡋ࡚ฟ⌧ࡍࡿࡓࡵ㸪どぬⓗ࡟㆑ูࡋ࡟ࡃࡃ㸪ほᐹ⪅㛫࡛㆑ู࡟ᕪࡀ⏕ࡌ ࡿ࡜ሗ࿌ࡉࢀ࡚࠸ࡿ㸬 MELT Japan ࡛ࡣ㸪⬻ CT ᳨ᰝࡢ⏬ീ⾲♧᮲௳࡛࠶ࡿ WW ࡢタᐃࢆ 80 HU ௨ୗ ࡟ࡍࡿࡼ࠺᥎ዡࡋ࡚࠸ࡿ㸬Lev ࡽࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰ⑕౛ࡀྵࡲࢀࡓ 30 ౛ࡢ CT ⏬ീࡢWW ࢆ 8 HU ࡟ึᮇタᐃࡋ㸪⚄⤒ᨺᑕ⥺⛉་ 2 ྡࡀ WW ࢆ 1㹼30 HU ࡲ࡛ ኚ໬ࡉࡏ࡞ࡀࡽほᐹࡋࡓ⤖ᯝ㸪WW ࢆ 80 HU ࡟タᐃࡋࡓ⾲♧᮲௳࡟ẚ࡭࡚㸪ㄞᙳ ⢭ᗘࡀྥୖࡋࡓ࡜ሗ࿌ࡋ࡚࠸ࡿ [1]㸬ࡋ࠿ࡋ㸪ࡇࡢሗ࿌ࡣ㸪ࢩࣥࢢࣝࢫࣛ࢖ࢫ CT ⿦⨨࡛᧜ᙳࡉࢀࡓ⏬ീࢆ฼⏝ࡋࡓ⤖ᯝ࡛࠶ࡾ㸪ࡲࡓ㸪඲⑕౛࡟ᑐࡋ࡚ྠ୍ࡢ᧜ᙳ ᮲௳࡛᧜ᙳࡉࢀ࡚࠸ࡿࡓࡵ㸪WW ࡢኚ໬ࡀ⏬ീࣀ࢖ࢬࡢ␗࡞ࡿ CT ⏬ീࡢಙྕ᳨ ฟ⬟࡟ཬࡰࡍᙳ㡪࡟ࡘ࠸࡚ࡢ᳨ウࡣ࡞ࡉࢀ࡚࠸࡞࠸㸬ࡉࡽ࡟㸪ほᐹ⪅ᐇ㦂࡟฼⏝ ࡋࡓ⑕౛ᩘࡸほᐹ⪅ᩘࡀᑡ࡞࠸ࡓࡵ㸪⤫ィⓗ࡞ಙ㢗ᛶ࡟␲ၥࡀṧࡿ㸬ࡇࢀࡲ࡛㸪㉸ᛴᛶᮇ⬻᱾ሰࡢ CT ⏬ീ࡟࠾ࡅࡿ⾲♧᮲௳ࡢ᭱㐺໬࡟㛵ࡍࡿ◊✲ሗ࿌ࡣ㸪Lev ࡽࡢሗ࿌௨እ࡟Ꮡᅾࡏࡎ㸪⏬ീࣀ࢖ࢬࡀኚ໬ࡋࡓCT ⏬ീ࡟࠾ࡅࡿ WW ࡀཬࡰࡍ ಙྕ᳨ฟ⬟ࡢᙳ㡪࡟㛵ࡍࡿᇶ♏ⓗ࡞◊✲ሗ࿌ࡣࡉࢀ࡚࠸࡞࠸㸬 ᮏ◊✲࡛ࡣ㸪⟶㟁ὶ᫬㛫✚㸦mAs ್㸧ࢆኚ໬ࡉࡏ࡚᧜ᙳࡋࡓỈࣇ࢓ࣥࢺ࣒⏬ീ ࢆ⏝࠸࡚㸪㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟ࢆホ౯ࡍࡿࡓࡵࡢ ࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆసᡂࡋ㸪WW ࡀపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟࡟ཬࡰࡍᙳ㡪࡟ ࡘ࠸࡚ࢩ࣑࣮ࣗࣞࢩࣙࣥᐇ㦂ࢆ⾜ࡗࡓ㸬ࡲࡓ㸪࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨࡛᧜ᙳࡉ ࢀࡓ㸪㉸ᛴᛶᮇ⬻᱾ሰ⑕౛ࡀྵࡲࢀࡿ60 ౛ࡢ CT ⏬ീࢆ⏝࠸࡚㸪10 ྡࡢほᐹ⪅

࡟ࡼࡿreceiver operating characteristic㸦ROC㸧ᐇ㦂ࢆ᪋⾜ࡋ㸪WW ࡢ㐪࠸࡟࠾ࡅࡿ ㄞᙳ⢭ᗘ࡬ࡢᙳ㡪࡟ࡘ࠸᳨࡚ウࡋࡓ㸬

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➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ 2.2.1 ࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸ࡓᐇ㦂 ㉸ᛴᛶᮇ⬻᱾ሰࢆᑐ㇟࡜ࡋࡓ CT ᳨ᰝ࡟࠾ࡅࡿ᧜ᙳࣃ࣓࣮ࣛࢱࡢ᭱㐺໬࡟㛵ࡍ ࡿ◊✲ࡣ㸪୺࡟CT ್ࡢᕪࡀ᭱ᑠ 5 HU ࡢಙྕࢆ⏝࠸ࡓᛶ⬟ホ౯ࣇ࢓ࣥࢺ࣒ࢆ⏝࠸ ᳨࡚ウࡉࢀ࡚࠸ࡿ [2][3]㸬ࡋ࠿ࡋ㸪㉸ᛴᛶᮇ⬻᱾ሰࢆక࠺⬻ᐇ㉁㒊ࡢ CT ್ࡣ㸪 ྵỈ㔞ࡢ1 %ࡢኚ໬࡟࠾࠸࡚ 2.6 HU పୗࡋ [4]㸪ࡲࡓ㸪Ⓨ⑕ࡋ࡚࠿ࡽ㛫ࡶ࡞࠸⹫ ⾑㡿ᇦ࡟࠾ࡅࡿ࿘㎶⤌⧊࡜ࡢCT ್ࡢᕪ㸦CT ್ᕪ㸧ࡣ㸪1㹼3 HU ⛬ᗘ࡛࠶ࡿ࡜ሗ ࿌ࡉࢀ࡚࠸ࡿ [2]㸬ࡋࡓࡀࡗ࡚㸪㉸ᛴᛶᮇ⬻᱾ሰࢆࢩ࣑࣮ࣗࣞࢩࣙࣥࡋࡓపࢥࣥ ࢺࣛࢫࢺ᳨ฟ⬟ࡢホ౯ࢆ⾜࠺ሙྜ㸪᪤Ꮡࡢᛶ⬟ホ౯ࣇ࢓ࣥࢺ࣒࡛ࡣ㐺ᛂእ࡜࡞ࡿ㸬 ཎࡽ [5]ࡣ㸪࿘㎶㒊࡜ࡢ CT ್ᕪࡀ 2 HU ࡜࡞ࡿᅛᙧࣇ࢓ࣥࢺ࣒ࢆసᡂࡋ㸪పࢥࣥ ࢺࣛࢫࢺศゎ⬟ࡢホ౯ࢆ⾜ࡗ࡚࠾ࡾ㸪ᴟࡵ࡚᭷⏝࡞◊✲࡛࠶ࡿ࡜⪃࠼ࡿ㸬ࡋ࠿ࡋ㸪 ྛ᪋タ࡛⡆౽࡟฼⏝࡛ࡁࡿࡶࡢ࡛ࡣ࡞ࡃ㸪ỗ⏝ᛶ࡟㛵ࡋ࡚ஈࡋ࠸ࡶࡢ࡜᥎ ࡍࡿ㸬 ᮏ◊✲࡛ࡣ㸪᪤ᏑࡢỈࣇ࢓ࣥࢺ࣒ࢆ᧜ᙳࡋࡓCT ⏬ീ࡜⏬ീฎ⌮ᢏ⾡ࢆ⏝࠸࡚స ᡂࡋࡓಙྕ⏬ീ࠿ࡽࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆసᡂࡋ㸪WW ࡀపࢥࣥࢺࣛࢫࢺ᳨ ฟ⬟࡟ཬࡰࡍᙳ㡪࡟ࡘ࠸᳨࡚ウࡋࡓ㸬 2.2.1.1 ࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࡢసᡂ

ᮏ◊✲࡛ࡣ㸪4 data acquisition system㸦DAS㸧ࡢ࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨㸦Light Speed Plus㸸GE ᶓἙ࣓ࢹ࢕࢝ࣝࢩࢫࢸ࣒♫〇㸧ࢆ౑⏝ࡋࡓ㸬ࡲࡎ㸪᪤Ꮡࡢி㒔⛉ Ꮫ♫〇ࡢᛶ⬟ホ౯ࣇ࢓ࣥࢺ࣒㸦JIS Z4923 200 mmȭ㸧ࢆᑓ⏝ᨭᣢྎ࡟㓄⨨ࡋ㸪ࣇ

࢓ࣥࢺ࣒୰ᚰࢆ CT ࢞ࣥࢺࣜෆ୰ᚰ࡟タᐃࡋ࡚⏬ീࣀ࢖ࢬホ౯⏝ࡢࢫ࢟ࣕࣥ఩⨨

ࢆ᧜ᙳࡋ㸪ࣀ࢖ࢬ⏬ീࢆ཰㞟ࡋࡓ㸬᧜ᙳ᮲௳ࡣ㸪ࢫ࣮࢟ࣕࣥࣔࢻ㸸ࢥࣥ࣋ࣥࢩࣙ ࢼࣝ㸪⟶㟁ᅽ㸸120 kV㸪෌ᵓᡂࢫࣛ࢖ࢫཌ㸸10 mm㸦2.5 mm4 DAS㸧㸪෌ᵓᡂ㛵 ᩘ㸸STANDARD㸪FOV㸸200 mm ୍ᐃ࡟࡚㸪mAs ್㸦⾲♧ CTDIW㸧ࢆ200㸦37.55

mGy㸧㸪400㸦75.11 mGy㸧㸪600㸦112.66 mGy㸧㸪800 mAs㸦150.21 mGy㸧࡜ኚ໬ࡉ ࡏࡓ㸬࡞࠾㸪⟶㟁ὶࡣ㸪200 mA ࡟ᅛᐃࡋࡓ㸬ࡲࡓ㸪ྛ mAs ್࡟࠾࠸࡚㸪30 ⏬ീ ࢆ཰㞟ࡋࡓ㸬ḟ࡟㸪Microsoft ♫〇ࡢࣉࣟࢢ࣑ࣛࣥࢢࢯࣇࢺ㸦Visual C++ 6.0㸧ࢆ⏝ ࠸࡚㸪512512 ࣐ࢺࣜࢡࢫෆࡢ⏬⣲್ࢆ 0 ࡟ࡋ㸪ࡑࡢ୰࡟㝧ᛶീ࡜࡞ࡿಙྕ㝜ᙳ ࢆ1 ಶ㓄⨨ࡉࡏࡓ⏬ീࢆసᡂࡋࡓ㸬࡞࠾㸪ಙྕ㝜ᙳࡢ┤ᚄࡣ㸪2.2.2 ࡛฼⏝ࡋࡓ㉸ ᛴᛶᮇ⬻᱾ሰ⑕౛࡟࠾ࡅࡿ⹫⾑㡿ᇦࡢ᭱ᑠᚄࡀ⣙10 mm ࡛࠶ࡗࡓࡇ࡜㸪ࡲࡓ㸪஦ ๓ᐇ㦂࡟࠾࠸࡚ಙྕᚄࡢ␗࡞ࡿࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸ࡓどぬⓗホ౯ࢆᐇ ᪋ࡋࡓ⤖ᯝ㸪ಙྕᚄࡀ30 mm ௨ୖ࡛ࡣಙྕ᳨ฟ⬟ࡀ୍ᐃ࡜࡞ࡗࡓࡇ࡜࠿ࡽ㸪10㸪 15㸪20㸪25㸪30 mm ࡜ኚ໬ࡉࡏ㸪ಙྕࢥࣥࢺࣛࢫࢺࡣ㸪1㸪2㸪3 ࡜ኚ໬ࡉࡏࡓ㸬 ࡑࡋ࡚㸪ィ15 ✀㢮ࡢಙྕࡀ㓄⨨ࡉࢀࡓ⏬ീࢆ 2 ࢭࢵࢺ㸪ィ 30 ⏬ീࢆ⏝ពࡋࡓ㸬 ࡞࠾㸪ಙྕࡢ఩⨨ࡣ㸪஘ᩘࢆ⏝࠸࡚Ỵᐃࡉࡏࡓ㸬᭱ᚋ࡟㸪᧜ᙳࡋࡓࣀ࢖ࢬ⏬ീ࡜

(27)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ 15 -ᅗ2.1 200 mAs ࡛᧜ᙳࡉࢀࡓಙྕࢥࣥࢺࣛࢫࢺࡀ 3 ࡢࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ㸬 ࡞࠾㸪⏬ീ࡟࠾ࡅࡿಙྕࡢ┤ᚄࡣ30 mm ࡛࠶ࡿ㸬 ᅗ2.2 ྛ mAs ್࡛᧜ᙳࡉࢀࡓಙྕࢥࣥࢺࣛࢫࢺࡀ 2 ࡢࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ㸬 a ࠾ࡼࡧ b ࡣ㸪ࡑࢀࡒࢀ 200 mAs ࠾ࡼࡧ 800 mAs ࡛ࡢ⏬ീ࡛࠶ࡿ㸬࡞࠾㸪ྛ⏬ീ ࡟࠾ࡅࡿಙྕࡢ┤ᚄࡣ30 mm ࡛࠶ࡿ㸬

(28)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ ಙྕ⏬ീࡢῶ⟬ฎ⌮࡟ࡼࡾࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒30 ⏬ീࢆసᡂࡋࡓ㸬ᅗ 2.1 ࡟㸪200 mAs ࡛᧜ᙳࡉࢀࡓಙྕࢥࣥࢺࣛࢫࢺࡀ 3 ࡢࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ㸪ᅗ 2.2 ࡟㸪 ྛmAs ್࡛᧜ᙳࡉࢀࡓಙྕࢥࣥࢺࣛࢫࢺࡀ 2 ࡢࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ♧ࡍ㸬 2.2.1.2 ⏬ീホ౯ 2.2.1.2.1 ⏬ീࣀ࢖ࢬࡢ ᐃ mAs ್ࡢ␗࡞ࡿ 4 ᮲௳ࡢྛࣀ࢖ࢬ⏬ീ 30 ⏬ീ࠿ࡽ 5 ⏬ീࢆ㑅ᢥࡋ㸪⏬ീࡢ୰ ኸ㒊࠾ࡼࡧ࿘㎶㒊4 ࣧᡤ࡟┤ᚄ 40 mm ࡢ෇ᙧ ROI ࢆタᐃࡋ࡚ ROI ෆࡢ⏬⣲ࡢᶆ ‽೫ᕪ㸦standard deviation㸸SD㸧ࢆồࡵ㸪mAs ್ࡈ࡜࡛ຍ⟬ᖹᆒࡋࡓ㸬 2.2.1.2.2 ROC ゎᯒ ほᐹ⪅ᐇ㦂ࡣ㸪ࡲࡎ㸪ほᐹ⪅࡟ᑐࡋ㸪࠶ࡽ࠿ࡌࡵホ౯ᇶ‽ࡀ୍ᐃ࡜࡞ࡿࡼ࠺࡟ ࢺ࣮ࣞࢽࣥࢢࢆ⾜ࡗࡓ㸬ྛmAs ್࡟࠾ࡅࡿࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ 30 ⏬ീ࡜ࣀ

࢖ࢬ⏬ീ30 ⏬ീ㸪ィ 60 ⏬ീࢆ㧗⢭⣽ 21.3 ᆺ liquid crystal display㸦LCD㸧ࣔࢽࢱ 㸦MS 35i2 3M monochrome㸸TOTOKU ♫〇㸧࡟ࣛࣥࢲ࣒࡟⾲♧ࡋ㸪WW ࢆ 20㸪40㸪 60㸪80 HU ࡟タᐃࡋࡓ㝿ࡢ㐃⥆☜ಙᗘἲࢆ⏝࠸ࡓほᐹ⪅ᐇ㦂ࢆᬯᐊୗ࡛ᐇ᪋ࡋࡓ㸬 ࡞࠾㸪ほᐹ⪅࡟ࡣ㸪᧜ᙳ᮲௳࡟㛵ࡍࡿ᝟ሗࡣᥦ♧ࡋ࡚࠸࡞࠸㸬ࡲࡓ㸪⾲♧ࡍࡿྛ ᮲௳ࡢ㡰␒ࡶほᐹ⪅ࡈ࡜࡟ࣛࣥࢲ࣒࡟ࡋࡓ㸬⏬ീほᐹ࡟࠾ࡅࡿ᫬㛫ⓗ㛫㝸ࡣ㸪ྛ ᮲௳㛫࡛3 ᪥௨ୖ✵ࡃࡼ࠺タᐃࡋࡓ㸬どぬホ౯ࡋࡓほᐹ⪅ࡣ㸪16 ᖺ࠾ࡼࡧ 42 ᖺ ࡢ⮫ᗋ⤒㦂ࢆᣢࡘ2 ྡࡢデ⒪ᨺᑕ⥺ᢏᖌ࡜㸪ᮏ᪋タ࡟ᅾ⡠ࡍࡿ 5 ྡࡢᏛ㒊⏕ࡢィ 7 ྡ࡛࠶ࡿ㸬Ꮫ⏕ࡀどぬホ౯ࢆ⾜ࡗࡓ⌮⏤ࡣ㸪஦๓࡟ほᐹ⪅ᐇ㦂ࢆᐇ᪋ࡋࡓ⤖ᯝ㸪デ⒪ᨺᑕ⥺ᢏᖌ࡜Ꮫ⏕㛫ࡢホ౯⤖ᯝ࡟᭷ព࡞ᕪࡀㄆࡵࡽࢀࡎ㸪ᮏほᐹ⪅ᐇ㦂࡟ࡣ ㄞᙳ⬟ຊࡢ᭷↓ࢆᚲせࡋ࡞࠸࡜⪃࠼ࡓࡓࡵ࡛࠶ࡿ [6]㸬᭱ᚋ࡟㸪ᚓࡽࢀࡓほᐹ⪅ 7 ྡࡢ☜ಙᗘ⤖ᯝࢆROC ゎᯒࢯࣇࢺ ROCKIT㸦ࢩ࢝ࢦ኱Ꮫ〇㸧࡟ධຊࡋ㸪ィ 16 ᮲

௳࡟࠾ࡅࡿྛࠎࡢᖹᆒROC ᭤⥺࡜ᖹᆒ ROC ᭤⥺ୗ㠃✚㸦area under the curve㸸 AUC㸧ࢆồࡵࡓ㸬࡞࠾㸪ほᐹ⪅ࡢ◊✲ཧຍ࡟࠾࠸࡚㸪⮫ᗋ⤒㦂ࡸホ౯⤖ᯝ࡞࡝ࡢ ಶே᝟ሗࢆබ㛤ࡍࡿ᪨ࢆㄝ᫂ࡋࡓୖ࡛㸪ࡍ࡭࡚ࡢほᐹ⪅࠿ࡽᢎㅙ᭩ࢆᚓ࡚࠸ࡿ㸬 2.2.2 ⮫ᗋ⏬ീࢆ⏝࠸ࡓᐇ㦂

2.2.2.1 ⏬ീࢹ࣮ࢱ࣮࣋ࢫ

ᮏᐇ㦂࡟౑⏝ࡋࡓ⏬ീࢹ࣮ࢱ࣮࣋ࢫࡣ㸪2006 ᖺ 4 ᭶࠿ࡽ 2007 ᖺ 9 ᭶ࡲ࡛࡟୰ ኸ⩌㤿⬻⚄⤒እ⛉⑓㝔࡛16 DAS ࡢ࣐ࣝࢳࢫࣛ࢖ࢫ CT ⿦⨨㸦LightSpeed 16㸸GE

ᶓἙ࣓ࢹ࢕࢝ࣝࢩࢫࢸ࣒♫〇㸧ࢆ⏝࠸࡚᧜ᙳࡉࢀࡓ㸪㉸ᛴᛶᮇ⬻᱾ሰ⑕౛30 ౛㸦⏨

(29)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ

17

-ᅗ2.3 WW ࢆ 80 ࠾ࡼࡧ 20 HU ࡟タᐃࡋࡓ㝿ࡢ㉸ᛴᛶᮇ⬻᱾ሰ⑕౛㸬a ࠾ࡼࡧ c ࡣWW ࡀ 80 HU ࡢ⏬ീ㸪b ࠾ࡼࡧ d ࡣ WW ࡀ 20 HU ࡢ⏬ീ࡛࠶ࡿ㸬

CT ⏬ീ࡛ᵓ⠏ࡉࢀ࡚࠸ࡿ㸬࡞࠾㸪30 ౛ࡢ㉸ᛴᛶᮇ⬻᱾ሰ⑕౛࡟࠾ࡅࡿ㈐௵⾑⟶ ࡣ㸪ࡍ࡭࡚୰኱⬻ື⬦㸦middle cerebral artery㸸MCA㸧࡛࠶ࡾ㸪MCA 㡿ᇦ඲య࡟

᱾ሰ⠊ᅖࡀᗈࡀࡗࡓ⑕౛ࡀ8 ౛㸪MCA 㡿ᇦࡢ୍㒊࡟㝈ᒁࡋࡓ⑕౛ࡀ 22 ౛㸦⓶㧊

ቃ⏺ࡢᾘኻ8 ౛㸪ࣞࣥࢬ᰾࣭ᓥ⓶㉁ࡢ୙᫂░໬ 14 ౛㸧Ꮡᅾࡍࡿ㸬CT ⏬ീୖ࡟࠾

ࡅࡿ᪩ᮇ⹫⾑ኚ໬ࡢ᭷↓ࡢุᐃ㸪࠾ࡼࡧ⏬ീᡤぢࡀ㉸ᛴᛶᮇ⬻᱾ሰ࡛࠶ࡿࡢ࠿ྰ ࠿ࡢุᐃࡣ㸪2 ྡࡢ⬻⚄⤒እ⛉་ࡀ MRI ᳨ᰝ࡛᧜ീࡉࢀࡓ DWI ࡜ ADC map ࢆ☜ ㄆࡋ࡞ࡀࡽࢥࣥࢭࣥࢧࢫࡢࡶ࡜࡟Ỵᐃࡉࢀࡓ㸬᧜ᙳ᮲௳ࡣ㸪ࢫ࣮࢟ࣕࣥࣔࢻ㸸ࢥ ࣥ࣋ࣥࢩࣙࢼࣝ㸪⟶㟁ᅽ㸸120 kV㸪⟶㟁ὶ㸸200 mA㸪ᅇ㌿᫬㛫㸸2.0 sec/rot㸦400 mAs㸧㸪 ෌ᵓᡂࢫࣛ࢖ࢫཌ㸸5 mm㸦2.5 mm8 DAS㸧㸪෌ᵓᡂ㛵ᩘ㸸STANDARD ࡛࠶ࡿ㸬 ࡞࠾㸪ᮏ◊✲࡟࠾ࡅࡿ⏬ീࢹ࣮ࢱ࣮࣋ࢫࡢ฼⏝࡟㝿ࡋ㸪ᮏ᪋タࡢ೔⌮ጤဨ఍ࡢᑂ ᰝࢆཷࡅ㸪ᢎㄆࢆྲྀᚓࡋ࡚࠸ࡿ㸬ࡲࡓ㸪ᮏ⏬ീࢹ࣮ࢱ࣮࣋ࢫࡣ㸪᪋タ࠿ࡽ CT ⏬ ീࡀᥦ౪ࡉࢀࡿ๓࡟ᝈ⪅᝟ሗࢹ࣮ࢱࡀ๐㝖ࡉࢀ㸪ಶேࡀ≉ᐃ࡛ࡁ࡞࠸ࡼ࠺༏ྡ໬ ࡉࢀ࡚࠸ࡿ㸬 2.2.2.2 ROC ゎᯒ ᐇ㦂᪉ἲࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰ⑕౛30 ౛࡜ṇᖖ⑕౛ 30 ౛㸪ィ 60 ౛ࡢ CT ⏬ീࢆ ୖグ࡜ྠ୍ࡢ㧗⢭⣽LCD ࣔࢽࢱ࡟ࣛࣥࢲ࣒࡟⾲♧ࡋ㸪WW ࢆ 80 ࠾ࡼࡧ 20 HU ࡜

(30)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ

ᅗ2.4 200 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീ࡟࠾ࡅࡿྛ WW ࡛ࡢᖹᆒ ROC ᭤⥺

(31)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ 19 -ᅗ2.6 ྛ mAs ್࠾ࡼࡧྛ WW ࡟࠾ࡅࡿᖹᆒ AUC ⊂❧࡟タᐃࡋ࡚㸪㐃⥆☜ಙᗘἲࢆ⏝࠸ࡓほᐹ⪅ᐇ㦂ࢆᬯᐊୗ࡛ᐇ᪋ࡋࡓ㸬ࡑࡢᚋ㸪 ྠ୍⑕౛ࡢCT ⏬ീࢆྠ୍ࣔࢽࢱୖ࡟୪࡭࡚㓄⨨ࡋ㸪୍᪉ࡢ⏬ീࡢ WW ࢆ 80 HU ࡟㸪௚᪉ࡢ⏬ീࡢWW ࢆ 20 HU ࡟タᐃࡋ࡚㸪୧⏬ീࢆ฼⏝ࡋࡓほᐹ⪅ᐇ㦂ࢆᐇ ᪋ࡋࡓ㸬࡞࠾㸪ほᐹ⪅ᐇ㦂ࡢ᪋⾜๓࡟ࡣ㸪ᮏ◊✲ෆᐜ㸪ほᐹ᪉ἲ㸪࠾ࡼࡧホ౯ᇶ ‽࡟ࡘ࠸࡚ㄝ᫂ࡋ㸪༑ศ࡞ࢺ࣮ࣞࢽࣥࢢࢆᐇ᪋ࡋࡓ㸬ࡲࡓ㸪ほᐹ⪅࡟ࡣ㸪⏬ീほ ᐹࡢ㝿࡟WL ࢆኚ໬ࡉࡏ࡚ほᐹࡍࡿࡼ࠺౫㢗ࡋࡓ㸬≉࡟㸪WW ࡀ 20 HU ࡟タᐃࡉ ࢀࡓ⏬ീࡣ㸪⮫ᗋ࡟࠾࠸࡚ぢ័ࢀ࡚࠸࡞࠸ࡓࡵ㸪WL ࢆ㐺ᐅኚ໬ࡉࡏ࡚ほᐹࡍࡿ ࡇ࡜ࡸ㸪㝞ᪧᛶ⬻᱾ሰᡤぢࢆ↓どࡋ࡚ほᐹࡍࡿࡇ࡜➼ࢆヲ⣽࡟ㄝ᫂ࡋࡓ㸬ᝈ⪅ࡢ ⮫ᗋ⑕≧ࡸ᪤ Ṕ࡞࡝ࡢ᝟ሗࡣᥦ♧ࡋ࡚࠸࡞࠸㸬どぬホ౯ࡋࡓほᐹ⪅ࡣ㸪3㹼26 ᖺ㸦ᖹᆒ 13.4s8.9㸧ࡢ⮫ᗋ⤒㦂ࢆᣢࡘ 10 ྡࡢデ⒪ᨺᑕ⥺ᢏᖌ࡛࠶ࡿ㸬ᚓࡽࢀࡓ ☜ಙᗘ⤖ᯝ࠿ࡽᖹᆒROC ᭤⥺࡜ᖹᆒ AUC ࢆồࡵࡓ㸬࡞࠾㸪2.2.1.2.2 ࡜ྠᵝ㸪ほ ᐹ⪅ࡢ◊✲ཧຍ࡟࠾ࡅࡿᢎㅙ᭩ࡣ㸪ࡍ࡭࡚ࡢほᐹ⪅࠿ࡽྲྀᚓࡋ࡚࠸ࡿ㸬ᅗ2.3 ࡟㸪 WW ࢆ 80 ࠾ࡼࡧ 20 HU ࡟タᐃࡋࡓ㝿ࡢ㉸ᛴᛶᮇ⬻᱾ሰ⑕౛ࢆ♧ࡍ㸬 2.3 ⤖ᯝ 2.3.1 ࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸ࡓᐇ㦂 ᮏ◊✲࡟࠾࠸࡚ࣀ࢖ࢬ⏬ീ࠿ࡽSD ࢆồࡵࡓ⤖ᯝ㸪mAs ್ࡢቑຍ࡟కࡗ࡚ SD

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➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ ᅗ2.7 ⮫ᗋ⏬ീ࡟࠾ࡅࡿほᐹ⪅ 10 ྡࡢᖹᆒ ROC ᭤⥺ ࡣపῶࡋࡓ㸬࡞࠾㸪200㸪400㸪600㸪800 mAs ࡟࠾ࡅࡿ SD ࡣ㸪ࡑࢀࡒࢀ㸪s3.4㸪 s2.4㸪s2.0㸪s1.7 ࡜࡞ࡗࡓ㸬 ᅗ2.4 ࠾ࡼࡧᅗ 2.5 ࡟㸪ࡑࢀࡒࢀ 200 ࠾ࡼࡧ 800 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീ࡟࠾ࡅ ࡿྛWW ࡛ࡢᖹᆒ ROC ᭤⥺ࢆ♧ࡍ㸬200 mAs ࡟࠾࠸࡚㸪WW ࢆ⊃ࡵࡿࡇ࡜࡟ࡼ ࡾ㸪ಙྕ᳨ฟ⬟ࡢྥୖࡀㄆࡵࡽࢀࡓࡀ㸪800 mAs ࡛ࡣ㸪WW ࡢኚ໬࡟ࡼࡿಙྕ᳨ ฟ⬟ࡢᕪࡀㄆࡵࡽࢀ࡞࠸⤖ᯝ࡜࡞ࡗࡓ㸬 ᅗ2.6 ࡟㸪mAs ್࡜ WW ࢆኚ໬ࡉࡏࡓ 16 ᮲௳࡟࠾ࡅࡿᖹᆒ AUC ࢆ♧ࡍ㸬⤖ᯝ ࡼࡾ㸪AUC ࡣ㸪mAs ್ࡢቑຍ㸪WW ࡢ⊃ᑠ໬࡟ࡼࡾୖ᪼ࡋࡓ㸬ࡲࡓ㸪WW ࢆ 20 HU ࡟タᐃࡍࡿࡇ࡜࡛㸪௚ࡢ WW ࡟ẚ࡭࡚㸪AUC ࡣᴟࡵ࡚㧗್࡜࡞ࡗࡓ㸬800 mAs ࡟࠾ࡅࡿྛWW ࡛ࡢᖹᆒ AUC 㛫ࡢ⤫ィⓗ᭷ពᕪ᳨ᐃ㸦୧ഃ࣌࢔࣮ࢻ t ᳨ᐃ㸧ࢆ ⾜ࡗࡓ⤖ᯝ㸪ࡍ࡭࡚ࡢWW 㛫࡟࠾࠸࡚㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୖ࡜࡞ࡾ㸪᭷ព ᕪࡣㄆࡵࡽࢀ࡞࠿ࡗࡓ㸬ࡋ࠿ࡋ㸪200㸪400㸪600 mAs ࡟࠾࠸࡚㸪ୖグ࡜ྠᵝ㸪ྛ WW ࡛ࡢᖹᆒ AUC 㛫ࡢ᭷ពᕪ᳨ᐃࢆ⾜ࡗࡓ⤖ᯝ㸪WW ࢆ 20 HU ࡜ 80 HU ࡟タᐃ ࡋࡓ㝿ࡢᖹᆒAUC 㛫࡛ࡣ㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୗ࡜࡞ࡾ㸪᭷ពᕪࡣㄆࡵࡽࢀ ࡓ㸦p= .0144㸪.0320㸪.0172㸧㸬 2.3.2 ⮫ᗋ⏬ീࢆ⏝࠸ࡓᐇ㦂 10 ྡࡢほᐹ⪅ࡢᖹᆒ ROC ᭤⥺ࢆᅗ 2.7 ࡟♧ࡍ㸬WW ࢆ 80 HU ࡟タᐃࡋࡓ㝿ࡢ

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➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ 21 -ᖹᆒAUC ࡣ 0.616s0.154 ࡜࡞ࡾ㸪WW ࢆ 20 HU ࡟タᐃࡋࡓ㝿ࡢᖹᆒ AUC ࡣ 0.677 s0.058 ࡜࡞ࡗࡓ㸬୧ WW ࡟࠾ࡅࡿᖹᆒ AUC 㛫࡟࠾࠸࡚㸪⤫ィⓗ᭷ពᕪ᳨ᐃ㸦୧ ഃ࣌࢔࣮ࢻt ᳨ᐃ㸧ࢆ⾜ࡗࡓ⤖ᯝ㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୖ࡜࡞ࡾ㸪᭷ពᕪࡣㄆ ࡵࡽࢀ࡞࠿ࡗࡓ㸦p= .3352㸧㸬ࡋ࠿ࡋ㸪୧ WW ࡟࠾ࡅࡿ AUC 㛫࡟࠾࠸࡚㸪ᶆ‽೫ ᕪࡢᕪࢆ᳨ᐃࡋࡓ⤖ᯝ㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୗ࡜࡞ࡾ㸪᭷ពᕪࡣㄆࡵࡽࢀࡓ 㸦p= .0251㸧㸬 WW ࡢ␗࡞ࡿ୧⏬ീࢆ฼⏝ࡋࡓ㝿ࡢᖹᆒ AUC ࡣ 0.720s0.127 ࡜࡞ࡗࡓ㸬WW ࢆ20 HU ࡟タᐃࡋࡓ㝿ࡢᖹᆒ AUC ࡜㸪WW ࡢ␗࡞ࡿ୧⏬ീࢆ฼⏝ࡋࡓ㝿ࡢᖹᆒ AUC 㛫࡟࠾࠸࡚㸪᭷ពᕪ᳨ᐃࢆ⾜ࡗࡓ⤖ᯝ㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୖ࡜࡞ࡾ㸪 ᭷ពᕪࡣㄆࡵࡽࢀ࡞࠿ࡗࡓ㸦p= .3124㸧㸬ࡋ࠿ࡋ㸪WW ࢆ 80 HU ࡟タᐃࡋࡓ㝿ࡢᖹ ᆒAUC ࡜ࡢ㛫࡟࠾࠸࡚ࡣ㸪᭷ព☜⋡ p ್ࡀ 0.05 ௨ୗ࡜࡞ࡾ㸪᭷ពᕪࡣㄆࡵࡽࢀ ࡓ㸦p= .0206㸧㸬 2.4 ⪃ᐹ ㉸ᛴᛶᮇ⬻᱾ሰࡢ CT ⏬ീᡤぢ࡛࠶ࡿ᪩ᮇ⹫⾑ኚ໬ࡣ㸪㠀ᖖ࡟ῐ࠸ప྾཰ᇦࢆ ࿊ࡍࡿࡓࡵ㸪ㄞᙳ࡟ᅔ㞴ࢆせࡍࡿࡀ㸪CT ᳨ᰝࡢ᧜ᙳ᮲௳ࡸ⏬ീ⾲♧᮲௳ࢆ㐺ษ ࡟タᐃࡍࡿࡇ࡜࡟ࡼࡾᨵၿࡉࢀ࠺ࡿ࡜ሗ࿌ࡉࢀ࡚࠸ࡿ [7]㸬ࡇࢀࡲ࡛㸪⬻ CT ⏬ീ ࡟࠾ࡅࡿపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟࡟㛵ࡍࡿ᧜ᙳࣃ࣓࣮ࣛࢱࡢ᳨ウࡣᩘከࡃᐇ᪋ࡉࢀ ࡚࠸ࡿ㸬ࡋ࠿ࡋ㸪⏬ീ⾲♧᮲௳ࡢ᳨ウሗ࿌ࡣᴟࡵ࡚ᑡ࡞ࡃ㸪⏬ീࣀ࢖ࢬࡀ␗࡞ࡿ CT ⏬ീ࡟࠾ࡅࡿ WW ࡢㄪ⠇ࡀཬࡰࡍపࢥࣥࢺࣛࢫࢺ᳨ฟ⬟ࡢᙳ㡪࡟ࡘ࠸࡚ࡢ᳨ ウࡣࡉࢀ࡚࠸࡞࠸㸬ࢃࢀࢃࢀࡣ㸪ᇶ♏ⓗᐇ㦂࡜ࡋ࡚㸪㉸ᛴᛶᮇ⬻᱾ሰࡢ᪩ᮇ⹫⾑ ኚ໬ࢆࢩ࣑࣮ࣗࣞࢩࣙࣥࡋࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆసᡂࡋ㸪Ỉࣇ࢓ࣥࢺ࣒⏬ ീࡶే⏝ࡋ࡚ほᐹ⪅ᐇ㦂ࢆᐇ᪋ࡋࡓ㸬 ᮏ◊✲࡛⏝࠸ࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࡣ㸪Ỉࣇ࢓ࣥࢺ࣒⏬ീ࡜పࢥࣥࢺࣛࢫ ࢺࡢಙྕࢆྵࢇࡔ⏬ീ࡜ࡢῶ⟬ฎ⌮࡟ࡼࡾసᡂࡉࢀ࡚࠸ࡿ㸬ࡑࡢࡓࡵ㸪ಙྕࡢ㎶ ⦕᝟ሗࡀ㸪ᐇ㝿࡟᧜ᙳࡉࢀࡓCT ⏬ീୖࡢಙྕ࡜␗࡞ࡿࡇ࡜ࡀᠱᛕࡉࢀࡿ㸬ᕷᕝ ࡽࡣ㸪CT ⏬ീࡢ✵㛫࿘Ἴᩘ≉ᛶࡢᙳ㡪ࢆຍ࿡ࡋࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࡢస ᡂ᪉ἲࢆᥦ᱌ࡋ࡚࠸ࡿ [8]㸬ࢃࢀࢃࢀࡣ㸪సᡂࡋࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࡢಙ ྕࢥࣥࢺࣛࢫࢺࡀ1㹼3 ࡜ᴟࡵ࡚ᑠࡉࡃ㸪㎶⦕᝟ሗࡢᕪ␗ࡀ㸪ほᐹ⪅ᐇ㦂ࢆᐇ᪋ࡋ ࡓ㝿ࡢホ౯⤖ᯝ࡟ᙳ㡪ࢆཬࡰࡍ⛬ᗘ࡛ࡣ࡞࠸࡜⪃࠼㸪༢⣧࡞ῶ⟬ฎ⌮࡟ࡼࡾࢹࢪ ࢱࣝࣇ࢓ࣥࢺ࣒⏬ീࢆసᡂࡋࡓ㸬 ᮏ◊✲࡛ࡣ㸪ࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ࡜Ỉࣇ࢓ࣥࢺ࣒⏬ീࢆ⏝࠸࡚ほᐹ⪅ᐇ㦂 ࢆᐇ᪋ࡋࡓ㸬ࡑࡢ⤖ᯝ㸪7 ྡࡢほᐹ⪅࡟࠾ࡅࡿᖹᆒ AUC ࡣ㸪mAs ್ࡢቑຍ࡜ WW

(34)

➨2 ❶ ⬻ CT ⏬ീ࡟࠾ࡅࡿ㉸ᛴᛶᮇ⬻᱾ሰ㆑ูࡢࡓࡵࡢ࢘࢕ࣥࢻ࢘ᖜࡢ᳨ウ ࡢ⊃ᑠ໬࡟ࡼࡾୖ᪼ࡋࡓ㸬ࡲࡓ㸪200㸪400㸪600 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീ࡟ᑐࡋ㸪 WW ࢆ 20 ࠾ࡼࡧ 80 HU ࡟タᐃࡋࡓ㝿ࡢᖹᆒ AUC 㛫࡟࠾࠸࡚㸪⤫ィⓗ᭷ពᕪ᳨ᐃ ࢆ⾜ࡗࡓ⤖ᯝ㸪᭷ពᕪࡀㄆࡵࡽࢀࡓ㸬ࡋ࠿ࡋ㸪800 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീ࡛ࡣ㸪 X ⥺㔞Ꮚࣀ࢖ࢬࡢᙳ㡪ࡀపῶࡉࢀ࡚࠸ࡿࡓࡵ㸪WW ࢆኚ໬ࡉࡏ࡚ࡶಙྕ᳨ฟ⬟࡟ ᕪࡀ⏕ࡌ࡞࠿ࡗࡓ㸬 ᅗ2.4 ࡟࠾ࡅࡿ 200 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീࢆ⏝࠸ࡓྛ WW ࡛ࡢᖹᆒ ROC ᭤⥺ ࡢᙧ≧࠿ࡽ㸪ಙྕࡀᏑᅾࡍࡿࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ࡟࠾ࡅࡿほᐹ⪅ࡢ☜ಙᗘࡢ ኚືࡀ㸪ࣀ࢖ࢬ⏬ീ࡟࠾ࡅࡿ☜ಙᗘࡢኚື࡟ẚ࡭࡚኱ࡁ࠸ࡇ࡜ࡀ᥎ ࡉࢀࡿ㸬ᮏ ◊✲࡛฼⏝ࡋࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ30 ⏬ീ࡟ࡣ㸪ಙྕࢥࣥࢺࣛࢫࢺࡀ 1 ࡢ┤ ᚄࡀ␗࡞ࡿ㝜ᙳࡀ10 ⏬ീྵࡲࢀ࡚࠾ࡾ㸪ほᐹࡍࡿ㝿࡟ࡇࢀࡽࡢಙྕ㝜ᙳࡀぢⴠ࡜ ࡉࢀࡓࡓࡵ࡜⪃࠼ࡿ㸬ࡋ࠿ࡋ㸪200 mAs ࡛᧜ᙳࡉࢀࡓ⏬ീ࡟࠾࠸࡚㸪WW ࢆ⊃ࡃ ࡍࡿࡇ࡜࡟ࡼࡾᖹᆒAUC ࡀୖ᪼ࡋ࡚࠸ࡿࡇ࡜࠿ࡽ㸪WW ࡢ⊃ᑠ໬ࡣ㸪ಙྕ㝜ᙳ ࡢ᳨ฟឤᗘࡢྥୖࡀᅗࢀࡿࡶࡢ࡜⪃࠼ࡿ㸬㏆ᖺ㸪⏬㉁࡜⿕ࡤࡃ⥺㔞ࡢ᭱㐺໬ࢆᅗࡿࡇ࡜ࡀྍ⬟࡞ CT ⏝⮬ື㟢ฟᶵᵓࢆά ⏝ࡋࡓ᧜ᙳࡀᐇ᪋ࡉࢀ࡚࠸ࡿ㸬ࡇࡢᶵ⬟ࡣ㸪⏬ീࣀ࢖ࢬࡢホ౯ᣦᶆ࡛࠶ࡿ SD ࢆ ฼⏝ࡋ㸪ฟຊ⥺㔞ࢆไᚚࡍࡿࡇ࡜࡛⏬㉁ࢆᶆ‽໬ࡍࡿࡶࡢ࡛࠶ࡿ㸬ᮏ◊✲࡟࠾࠸ ࡚㸪᧜ᙳࡉࢀࡓỈࣇ࢓ࣥࢺ࣒⏬ീ࠿ࡽSD ࢆồࡵࡓ⤖ᯝ㸪ୖグࡢ ROC ゎᯒ⤖ᯝ࡛ ᭷ពᕪࡀㄆࡵࡽࢀࡓ600 mAs㸦112.66 mGy㸧࡛ࡣs2.0 ࡜࡞ࡗࡓ㸬ࡼࡗ࡚㸪ྛ᪋タ ࡛ᡤ᭷ࡍࡿ┤ᚄ200 mm ࡢỈࣇ࢓ࣥࢺ࣒⏬ീୖࡢ SD ࡀs2.0 ࢆୖᅇࡿሙྜ࡟ࡣ㸪どぬⓗ࡞ࣀ࢖ࢬࡢᙳ㡪ࢆపῶࡉࡏࡿࡓࡵ࡟WW ࢆᗈࡆࡿࡢ࡛ࡣ࡞ࡃ㸪WW ࢆ 20 HU ࡟タᐃࡋ㸪⏬ീࢥࣥࢺࣛࢫࢺࢆୖ᪼ࡉࡏ࡚ほᐹࡍࡿࡇ࡜ࡀ㸪ಙྕ᳨ฟ⬟ࡢᶆ ‽໬࡟ࡘ࡞ࡀࡿࡶࡢ࡜⪃࠼ࡿ㸬ࡓࡔࡋ㸪SD ࡣ㸪✵㛫࿘Ἴᩘ≉ᛶ࡟౫Ꮡࡉࢀ㸪⿦ ⨨ࡈ࡜࡛ಙྕ᳨ฟ⬟ࡀ␗࡞ࡿࡶࡢ࡜᥎ ࡉࢀࡿࡇ࡜࠿ࡽ㸪᪋タࡈ࡜ࡢ᳨ウࡀᚲせ ࡛࠶ࡿ㸬ࡲࡓ㸪ୖグࡢ᳨ウࡣ㸪ᆒ୍࡞≀㉁࡛ᵓᡂࡉࢀࡓࢹࢪࢱࣝࣇ࢓ࣥࢺ࣒⏬ീ ࢆ⏝࠸ࡓᐇ㦂⤖ᯝ࡟ᇶ࡙ࡃࡶࡢ࡛࠶ࡾ㸪ᐇ㝿ࡢ⮫ᗋ⏬ീ࡟┤᥋཯ᫎࡉࡏࡿࡇ࡜ࡣ ࡛ࡁ࡞࠸㸬ࡋ࠿ࡋ㸪ୖグࡢ⤖ᯝࡼࡾ㸪WW ࢆ 20 HU ࡟タᐃࡍࡿࡇ࡜࡛㸪పࢥࣥࢺ ࣛࢫࢺ᳨ฟ⬟ࡢྥୖࡀᅗࢀࡿࡇ࡜ࡣ☜ドࡉࢀ࡚࠾ࡾ㸪ᕥྑᑐ⛠ᛶࡢ≉ᚩࢆ฼⏝ࡋ ࡚ẚ㍑ㄞᙳࡉࢀࡿ⮫ᗋ⏬ീ࡟࠾࠸࡚ࡣ㸪ᙉㄪࡉࢀࡓ᪩ᮇ⹫⾑ኚ໬ࡀᐜ᫆࡟㆑ูྍ ⬟࡜࡞ࡿࡶࡢ࡜⪃࠼ࡿ㸬 MELT Japan ࡣ㸪㉸ᛴᛶᮇ⬻᱾ሰࡢ CT ⏬ീࢆほᐹࡍࡿ㝿㸪WW ࢆ 80 HU ௨ୗ ࡟タᐃࡍࡿࡼ࠺᥎ዡࡋ࡚࠸ࡿ㸬ࡲࡓ㸪ࢃࢀࢃࢀࡣ㸪ྛ᪋タ࡟࠾ࡅࡿ㢌㒊 CT ᳨ᰝ ࡢ࣮ࣝࢳࣥ᧜ᙳ᮲௳ࢆㄪᰝࡋ࡚࠾ࡾ [9]㸪ࡑࡢሗ࿌ࢆᇶ࡟ྛ᪋タࡢ mAs ್ࢆᖹᆒ ࡍࡿ࡜⣙350 mAs ࡛࠶ࡗࡓ㸬ࡑࡇ࡛㸪ᮏ◊✲࡛ᚓࡽࢀࡓᅗ 2.6 ࡢ⤖ᯝࢆ฼⏝ࡋ࡚㸪 ࡇࢀࡽࡢྛ᮲௳ୗ࡛᧜ᙳ࠾ࡼࡧ⏬ീほᐹࡉࢀࡓሙྜࢆࢩ࣑࣮ࣗࣞࢩࣙࣥࡍࡿ࡜㸪