BLM は、EPSRC 思い立ったの受信者であり、東フィンランド大学にブリストル大学実験心理学学校の旅行補助金を受け取った。MJK はエリザベス ・ ブラックウェル所、Wellcome の信頼の国際戦略的支援ファンドに資金を供給 [ISSF2: 105612/Z/14/Z]。KTJ と OHJG は、UEF 脳の戦略的な資金東フィンランド大学から、オ フィンランド フィンランドのアカデミーによって賄われています。仕事は、ダンヒル医療信頼 [許可番号 R385/1114] によって支えられました。

動物の手続きがコミュニティ評議会指令 86/609/EEC の指針に従って行われ、動物のケアおよび使用委員会クオピオ、フィンランド東フィンランド大学によって承認します。
 1 です。 動物モデル <ol><li>麻酔ラット MRI 実験操作の持続期間のためフェイス マスクを通して N 2/O 2 フロー (70%/30%) におけるイソフルランと 300 から 400 グラムの重量を量る。換気フードを麻酔します。1.5 2.4% とイソフルラン レベルを維持します。
	<ol><li>胴体の下に空気圧枕を介して呼吸から MRI の中に麻酔のモニター深度。反射をピンチに反応の欠如は外科麻酔のため十分な深さの印として取られます。磁石に接続使用イソフルラン スカベン ジャーの穴します</li>。
	</ol></li> <li>実行永久中大脳動脈閉塞 (MCAO) 焦点の虚血性脳卒中を誘発します。MCAO の腔内のスレッド モデルを使用し、ロンガ ら によって与えられた方法に従って操作を実行 22. <ol><li>遮蔽のスレッドのままに (シリコン PTFE 強化 monofil フィラメント、直径 0.22 mm) MRI 実験の期間のための場所で</li>。
	</ol></li> <li>動脈血血液ガスと pH 血液アナライザーを使用して分析します。
	<ol><li>MRI の間に胴体と直腸の温度監視システムを使用して直腸の温度の下に置かれた空気圧枕と呼吸数モニター。胴体の下にパッドを加熱水を使用して 37 ° C に近いコア温度を維持します</li>。
		<li>MCAO 後すぐにセキュリティで保護された磁石の中心にクレードルにラットを産んだラット ヘッド ホルダーを使用しています。穴磁石にラットを転送する前に生理食塩水 2 mL を腹腔内注入します</li>。
	</ol></li></ol> 2。MRI <ol><li>、9.4T を使用して取得 MRI データ (12 cm 勾配挿入) すると 31 cm の水平方向磁石インターフェース、積極的に分離されたリニア ボリューム送信機と直交受信コイル ペア装備コンソール/</li>。
	<li>最大 5 h 投稿 MCAO の各ラットをスキャンします。(60, 120, 180 240 分ポスト MCAO) 時間間隔でサンプリング congruently 12 を取得 (0.5 mm スライス ギャップ、スライス厚 1 mm、ビューのフィールドを = = 2.56 × 2.56 cm) 拡散テンソル (2.2.1) カー ・ パーセル-Meiboom ギル T 2 (微量のコロナのスライス2.2.2) と高速ローアングル ショット T 1 (2.2.3)。。
	<ol><li>拡散テンソル画像のトレースを取得 (D av = 1/3 トレース [D]) 各軸に沿って 3 つのバイポーラ グラデーション (拡散勾配の期間 = 5 ミリ秒、拡散時間 = 15 ms) と 3 つの b 値 (0, 400, 1400 s/mm-2 s)、ここで、Δ = 15 ms &#8706; = 5 ms 時間 (TE) をエコー = 36 ms 繰り返し時間 (TR) = 4000 ms と集録時間 = 7.36 分</li>
		<li>T 2 定量化のための 12 のエコー ・ カー-パーセル-Meiboom-ギル T 2 シーケンスを取得、ここでエコー間隔 = 10 ms、TR 2000 ms と捕捉時間を = = 4.20 分</li>
		<li>を取得、高速低角度ショット (フラッシュ) T 1, 5407.58 ms まで、TR を反転から最初のフラッシュのシーケンス (T 10) までの時間ですが 10 逆転の 600 ミリ秒単位での 7.58 ms = 5.5 ミリ秒、反転パルス間の時間 (T リラックス) 10 s および集録時間を = = 8.20 分</li>
	</ol></li></ol> 3。画像処理 <ol><li>relaxometry の計算と ADC マップ: qT 2 qT 1 ブリストル大学 web サイト [DOI:10.5523/bris.1bjytiabmtwqx2kodgbzkwso0k] に用意されている Matlab 関数を使用して、ADC マップを計算入力は MRI のデータの場所へのファイル パス。
	<ol><li>T の 2 データは、ハミングの再構成画像の (または畳み込み、同等の結果が以下の効率的な計算によって画像のドメイン) の前に k 空間でのフィルタ リングを適用します。QT 2 マップ各時系列の対数を解くことによって計算、ボクセル賢明な線形最小二乗によって基礎 (T 2 崩壊する bi 指数フィットを行うこともできますが、ボクセル ワイズ F テスト テストはそのボクセルを明らかに追加のパラメーターが適切でないイメージ) 内</li>。
		<li>T の 1 データには、ハミング k 空間像の再構成する前にフィルタ リングが適用されます。T 1 参照 23 に示す方法によるとフィッティングを実行します。(強度画像の使用) が原因不明な記号の問題に対処する最も低い強度ポイント可能性があります除外、または同様の結果に合う過程で推定します</li>。
		<li>拡散強調データ、ハミング (これはセグメント化された k 空間軌道のためより簡単な) イメージのドメインの畳み込みによるフィルタ リングが適用されます。 13 法による ADC マップに適合します</li>。
	</ol></li> <li>虚血組織の識別 <ol><li>病変識別のため明確な対照を提供するように逆数 D av 画像 (1/D av) 虚血性の組織を識別します。興味 (VOI) の虚血のボリュームを生成するには、値 1 つ中央絶対偏差中央値上全体脳 1/D av 流通のボクセルとして虚血組織を定義します。非虚血性の半球の相同領域を識別するために、垂直軸を虚血性のボイを反映します。脳脊髄液を含むボクセルを含むを避けるために非虚血性のヴォイスを手動で調整します</li>。
		<li>QT 1 と qT 2 時間との関係を決定するために、各ラットのため MCAO をポストし時点、qT 1 と qT 2 マップ上に虚血性と非虚血性のヴォイスを読み込みます。平均緩和時間を抽出し、半球 (ΔT 1 ΔT 2) 次の同等化を使用しての qT 1 と qT 2 の割合の差を計算: < img alt =「方程式」src ="ファイル/ftp_upload/55277/55277eq1.jpg"/> 、T x は、選択されたパラメーターや qT 1 qT 2。<img alt="Equation"src="/files/ftp_upload/55277/55277eq2.jpg"/> 虚血性のボイの平均緩和時間を指しますと <img alt="Equation"src="/files/ftp_upload/55277/55277eq3.jpg"/> 非虚血性のボイで平均緩和時間。それぞれのラットは、独自のコントロールとして機能するように非虚血性のボイを使用する必要があります</li>。
		<li>昇格した qT 1 と qT 2 ボクセルを識別するために次の条件を使用して: qT 1 または qT 2 分布の中央値の緩和時間を超える緩和時間と虚血性ボイ内任意の画素、1 つの半分-幅半分の最大値 (HWMH) 以上で非虚血性のボイ。これらの基準緩和時間として分類される 95 th パーセン タイル以上である必要があることを意味 &#39; 高 &#39;。非虚血性のボイの中央のリラクゼーション時間使用する独自のコントロールとして機能する各ラット</li>。
		低下の拡散の領域内で緩和時間の変化の空間分布を画像に <li>を識別して昇格した qT 1 または qT 2 色コード ボクセルと同様、両方のボクセル上昇 qT 1 と qT 2呼ばれる &#39; qT 1 と qT 2 重複 &#39;.</li>
		QT 1 と qT 2 によると病変の大きさを決定する <li>計算パラメーター f (騎士 ら によって紹介されたよう 18) ラットおよび時点ごとに得られる MRI データから。f 1 と f 2 というt 高 qT 1 または qT 2 ボクセルの数 (それぞれ) 虚血性のボイのサイズに対する割合として。
		<ol><li>使用次方程式 f 1 と f 2 を計算する: <img alt="Equation"src="/files/ftp_upload/55277/55277eq4.jpg"/> 、<img alt="Equation"src="/files/ftp_upload/55277/55277eq5.jpg"/> とは、緩和時間 (qT 1 または qT 2)、<img alt="Equation"src="/files/ftp_upload/55277/55277eq6.jpg"/> の数を指します &#39; 高 &#39; 虚血性 VOI で緩和時間ボクセル<img alt="Equation"src="/files/ftp_upload/55277/55277eq7.jpg"/> の数は、&#39; 低 &#39; 緩和時間虚血性のボイのボクセルと <img alt="Equation"src="/files/ftp_upload/55277/55277eq8.jpg"/>、ボクセル内の合計数虚血性のボイ。セクション 3.2.3 中昇格した qT 1 と qT 2 ボクセルを識別するための基準のとおりです。&#39; 低 &#39; ボクセルが緩和時間より中央 qT 1 または 1 つの HWHM によって非虚血性のボイの qT 2 とボクセル。減算 <img alt="Equation"src="/files/ftp_upload/55277/55277eq7.jpg"/> 虚血または他の病態 17 による緩和時間の減少が可能になります</li> <li>の程度を決定する &#39; qT 1。 と qT 2 重複 &#39; 脳全体のボリュームの割合として昇格した qT 1 と qT 2 の重複の量を計算することによりここと呼ばれる &#39; V 重複 &#39;。次の式を使用します: <img alt="Equation"src="/files/ftp_upload/55277/55277eq9.jpg"/> 、<img alt="Equation"src="/files/ftp_upload/55277/55277eq10.jpg"/> 両方で虚血性の VOI 内ボクセルの数を指します&#39; 高 &#39; qT 1 と &#39; 高 &#39; qT 2 と <img alt="Equation"src="/files/ftp_upload/55277/55277eq11.jpg"/> 全体のラット脳における画素の総数を表します。QT 2 relaxometry 地図周り全脳ボイを手動で作成するラットの脳におけるボクセルの数を決定します</li>。
		</ol></li></ol></li></ol> 4。虚血性病変と Triphenyletrazolium 塩化 (TTC) の検証 <ol><li>, 茎頂切除直後に慎重に頭蓋骨からラットの脳を抽出します。ラットが斬首された時間から 10 分以内でこの手順を実行します</li>。
	<li>ストア脳を冷蔵 0.01 M リン酸緩衝生理食塩水 (PBS) シリアル 1 mm 厚さにコロナ スライスに脳をセクションにラット脳スライサー マトリックスを使用する前にします</li>。
	<li> 24 で推奨されている断面後、暗闇の中で 30 分間 37 ° C で TTC を含む 20 mL の PBS で各脳スライスを孵化させなさい。TTC 濃度が 1% は受け入れられるが、改良されたコントラストの 0.5% を使用します。
	<ol><li>暗いに保つために箔でセクションのコンテナーをカバーします</li>。
	</ol></li> <li>インキュベーション後、ピペットを使用して TTC ソリューションを削除し、PBS の 3 つの変更でスライスを洗うです</li>。
	<li>すぐに標準的な光学顕微鏡とデジタル カメラを使用してスライスを撮影します</li>。
</ol> 5。統計解析 <ol><li>統計解析が Matlab および統計ソフトウェアを使用して遂行します</li>。
	時間氏パラメーターの関係を決定する <ol><li>実行ピアソン <li>&#39; s ΔT 1 の関係を決定するためのプールされたラット データ相関 ΔT 2 f 1 f 2 とV重複 時間ポスト MCAO</li>。
		<li>重要な線形関係を示すパラメーター (p &#60; 0.05)、興味のパラメーターを定量化することで脳卒中発症時期を予測できるかどうかを決定する線形最小正方形回帰分析を行います。発症時間の推定値の精度を評価する根平均二乗誤差 (RMSE) を使用します</li>。
	</ol></li> <li>病巣の大きさの定量化 <ol><li>、異なる qMRI のパラメーターに従って病変サイズを比較する一方向の行為関連性とフィッシャー &#39; s 最下位違い事後のボクセルの数の平均値に虚血性のボイと高 qT 1 と qT 2 ボクセルの数の平均値。違いが p で重要考慮される &#60; 0.05。Mauchly あたり球形仮定が満たされない場合 &#39; s 真球度テスト、正しい自由度および温室ガイサー推計によると意義値</li>。
	</ol>
	</li>
</ol>

<ol>
	<li>Siesj&#246;, B. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+ischemic+brain+damage.">Mechanisms of ischemic brain damage.</a> Crit. Care Med. 16, 954-963 (1988).</li><li>Astrup, J., Siesj&#246;, B. K., Symon, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thresholds+in+cerebral+ischemia:+the+ischemic+penumbra.">Thresholds in cerebral ischemia: the ischemic penumbra.</a> Stroke. 12, 723-725 (1981).</li><li>Hacke, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Association+of+outcome+with+early+stroke+treatment:+pooled+analysis+of+ATLANTIS,+ECASS,+and+NINDS+rt-PA+stroke+trials.">Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials.</a> Lancet. 363, 768-774 (2004).</li><li>Rudd, A. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stroke+thrombolysis+in+England,+Wales+and+Northern+Ireland:+how+much+do+we+do+and+how+much+do+we+need?.">Stroke thrombolysis in England, Wales and Northern Ireland: how much do we do and how much do we need?.</a> J Neurol Neurosurg Psychiatry. 82, 14-19 (2011).</li><li>George, M. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Paul+Coverdell+National+Acute+Stroke+Registry+Surveillance+-+four+states,+2005-2007.">Paul Coverdell National Acute Stroke Registry Surveillance - four states, 2005-2007.</a> MMWR Surveill Summ. 58, 1-23 (2009).</li><li>Kauppinen, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiparametric+magnetic+resonance+imaging+of+acute+experimental+brain+ischemia.">Multiparametric magnetic resonance imaging of acute experimental brain ischemia.</a> Prog NMR Spectr. 80, 12-25 (2014).</li><li>Moseley, M. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Early+detection+of+regional+cerebral+ischemia+in+cats:+comparison+of+diffusion+and+T2-weighted+MRI+and+spectroscopy.">Early detection of regional cerebral ischemia in cats: comparison of diffusion and T2-weighted MRI and spectroscopy.</a> Magn Reson Med. 14, 330-346 (1990).</li><li>Kettunen, M. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interrelations+of+T(1)+and+diffusion+of+water+in+acute+cerebral+ischemia+of+the+rat.">Interrelations of T(1) and diffusion of water in acute cerebral ischemia of the rat.</a> Magn Reson Med. 44, 833-839 (2000).</li><li>Wintermark, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acute+stroke+imaging+research+roadmap.">Acute stroke imaging research roadmap.</a> Stroke. 39, 1621-1628 (2008).</li><li>Knight, R. A., Dereski, M. O., Helpern, J. A., Ordidge, R. J., Chopp, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Magnetic+resonance+imaging+assessment+of+evolving+focal+cerebral+ischemia.+Comparison+with+histopathology+in+rats.">Magnetic resonance imaging assessment of evolving focal cerebral ischemia. Comparison with histopathology in rats.</a> Stroke. 25, 1252-1261 (1994).</li><li>Madai, V. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DWI+intensity+values+predict+FLAIR+lesions+in+acute+ischemic+stroke.">DWI intensity values predict FLAIR lesions in acute ischemic stroke.</a> PLoS One. 9, e92295 (2014).</li><li>Siemonsen, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+T2+values+predict+time+from+symptom+onset+in+acute+stroke+patients.">Quantitative T2 values predict time from symptom onset in acute stroke patients.</a> Stroke. 40, 1612-1616 (2009).</li><li>Jokivarsi, K. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Estimation+of+the+onset+time+of+cerebral+ischemia+using+T1+and+T2+MRI+in+rats.">Estimation of the onset time of cerebral ischemia using T1 and T2 MRI in rats.</a> Stroke. 41, 2335-2340 (2010).</li><li>Rogers, H. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Timing+the+ischemic+stroke+by+1H-MRI:+Improved+accuracy+using+absolute+relaxation+times+over+signal+intensities.">Timing the ischemic stroke by 1H-MRI: Improved accuracy using absolute relaxation times over signal intensities.</a> NeuroReport. 25, 1180-1185 (2014).</li><li>McGarry, B. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stroke+onset+time+estimation+from+multispectral+quantitative+magnetic+resonance+imaging+in+a+rat+model+of+focal+permanent+cerebral+ischemia.">Stroke onset time estimation from multispectral quantitative magnetic resonance imaging in a rat model of focal permanent cerebral ischemia.</a> Int J Stroke. , (2016).</li><li>Calamante, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Early+changes+in+water+diffusion,+perfusion,+T1,+and+T2+during+focal+cerebral+ischemia+in+the+rat+studied+at+8.5+T.">Early changes in water diffusion, perfusion, T1, and T2 during focal cerebral ischemia in the rat studied at 8.5 T.</a> Magn Reson Med. 41, 479-485 (1999).</li><li>Gr&#246;hn, O. H. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Graded+reduction+of+cerebral+blood+flow+in+rat+as+detected+by+the+nuclear+magnetic+resonance+relaxation+time+T2:+A+theoretical+and+experimental+approach.">Graded reduction of cerebral blood flow in rat as detected by the nuclear magnetic resonance relaxation time T2: A theoretical and experimental approach.</a> J Cereb Blood Flow Metab. 20, 316-326 (2000).</li><li>Knight, M. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+spatiotemporal+theory+for+MRI+T2+relaxation+time+and+apparent+diffusion+coefficient+in+the+brain+during+acute+ischemia:+Application+and+validation+in+a+rat+acute+stroke+model.">A spatiotemporal theory for MRI T2 relaxation time and apparent diffusion coefficient in the brain during acute ischemia: Application and validation in a rat acute stroke model.</a> J Cereb Blood Flow Metab. 36, 1232-1243 (2016).</li><li>Thomalla, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DWI-FLAIR+mismatch+for+the+identification+of+patients+with+acute+ischaemic+stroke+within+4·5+h+of+symptom+onset+(PRE-FLAIR):+a+multicentre+observational+study.">DWI-FLAIR mismatch for the identification of patients with acute ischaemic stroke within 4·5 h of symptom onset (PRE-FLAIR): a multicentre observational study.</a> Lancet Neurol. 10, 978-986 (2011).</li><li>Petkova, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MR+imaging+helps+predict+time+from+symptom+onset+in+patients+with+acute+stroke:+implications+for+patients+with+unknown+onset+time.">MR imaging helps predict time from symptom onset in patients with acute stroke: implications for patients with unknown onset time.</a> Radiology. 257, 782-792 (2010).</li><li>Hoehn-Berlage, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evolution+of+regional+changes+in+apparent+diffusion+coefficient+during+focal+ischemia+of+rat+brain:+the+relationship+of+quantitative+diffusion+NMR+imaging+to+reduction+in+cerebral+blood+flow+and+metabolic+disturbances.">Evolution of regional changes in apparent diffusion coefficient during focal ischemia of rat brain: the relationship of quantitative diffusion NMR imaging to reduction in cerebral blood flow and metabolic disturbances.</a> J. Cereb. Blood Flow Metab. 15, 1002-1011 (1995).</li><li>Longa, E. Z., Weinstein, P. R., Carlson, S., Cummins, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reversible+middle+cerebral+artery+occlusion+without+craniectomy+in+rats.">Reversible middle cerebral artery occlusion without craniectomy in rats.</a> Stroke. 20, 84-91 (1989).</li><li>Nekolla, S., Gneiting, T., Syha, J., Deichmann, R., Haase, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=T1+maps+by+K-space+reduced+snapshot-FLASH+MRI.">T1 maps by K-space reduced snapshot-FLASH MRI.</a> J Comput Assist Tomogr. 16, 327-332 (1992).</li><li>Joshi, C. N., Jain, S. K., Murthy, P. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+optimized+triphenyltetrazolium+chloride+method+for+identification+of+cerebral+infarcts.">An optimized triphenyltetrazolium chloride method for identification of cerebral infarcts.</a> Brain Res Brain Res Protoc. 13, 11-17 (2004).</li><li>McGarry, B. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determining+stroke+onset+time+using+quantitative+MRI:+High+accuracy,+sensitivity+and+specificity+obtained+from+magnetic+resonance+relaxation+times.">Determining stroke onset time using quantitative MRI: High accuracy, sensitivity and specificity obtained from magnetic resonance relaxation times.</a> Cerebrovasc Dis Extra 6. 6, 60-65 (2016).</li><li>Fiehler, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Severe+ADC+decreases+do+not+predict+irreversible+tissue+damage+in+humans.">Severe ADC decreases do not predict irreversible tissue damage in humans.</a> Stroke. 33, 79-86 (2002).</li><li>Lestro Henriques, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intralesional+Patterns+of+MRI+ADC+Maps+Predict+Outcome+in+Experimental+Stroke.">Intralesional Patterns of MRI ADC Maps Predict Outcome in Experimental Stroke.</a> Cerebrovasc Dis. 39, 293-301 (2015).</li><li>Kettunen, M. I., Gr&#246;hn, O. H. J., Silvennoinen, M. J., Penttonen, M., Kauppinen, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+assessment+of+the+balance+between+oxygen+delivery+and+consumption+in+the+rat+brain+after+transient+ischemia+with+T2-BOLD+magnetic+resonance+imaging.">Quantitative assessment of the balance between oxygen delivery and consumption in the rat brain after transient ischemia with T2-BOLD magnetic resonance imaging.</a> J Ceber Blood Flow Metab. 22 (3), 262-270 (2002).</li></ol>

著者が明らかに何もありません。

The current protocol for estimation of stroke onset time in rats uses quantitative diffusion and relaxation time MRI data rather than signal intensities of respective weighted MR contrast images19. Recent evidence points to inferior performance of image intensities in estimating stroke onset time 14,25. In the &#39;diffusion-positive&#39; stroke lesion our MRI protocol provides stroke onset times from qT1 and qT2 MRI data with an accuracy of half an hour or so. It is a general trend that qT2 data outperforms that of qT1. The best accuracy for onset time determination is obtained from the volume of overlapping elevated qT1 and qT2 (Voverlap).
The images in Figure 1 demonstrate that while the reduced diffusion coefficient appears rather uniform, regions with abnormal qT1 and qT2 are heterogeneously scattered within the ischemic lesion. This finding is in accordance with previous observations and is likely due to different sensitivities of these qMRI parameters to pathophysiological changes caused by ischemia 6. This suggests qMRI parameters may be informative of tissue status and supports notions that DWI over-estimates ischemic damage 26. Indeed, recent preclinical evidence points toward the heterogeneity of ischemic damage within diffusion defined lesions 27. Thus, the combination of diffusion, qT1 and qT2 potentially provides information on stroke onset time and tissue status, both of which are clinically useful for treatment decisions regarding patients with unknown onset.
Voverlap and f2 gave the most accurate estimates of stroke onset time. The benefit of quantifying relaxation times is that unlike signal intensities they are insensitive to inherent variations caused by technical factors such as magnetic field inhomogeneities and proton density 6, including the expected magnetic field variation within the ischemic lesion 18. Reduced uncertainty associated with onset time estimates of qT1 and f1 are likely due to the aforementioned bi-phasic response of qT1 to ischemia, which contributes to the shallow slope of the time-dependent qT1 change 8,15,16. The MRI data shown (Figure 2) are in accordance with previous works 13,14, in that the time courses of relaxation time differences between the ischemic and contralateral non-ischemic brain are adequately described by linear functions. It is, however, important to note that the underpinning hydrodynamic changes due to ischemia are not linear 1,18.
The current MRI protocol for stroke time&#160;is demonstrated in rats subjected to permanent ischemia using the Longa et al. procedure 22. In our experience, the Longa et al. procedure fails to induce MCAO in 10-20% of rats, however, as ADC is used to verify presence of ischemia, the experiments can be terminated prematurely. Failure to induce MCAO is often due to imperfect occluder thread. A further factor resulting in experimental failures is that MCAO is a severe procedure causing death of up to 20% of rats during a prolonged MRI session.
The stroke onset timing protocol applies only to permanent ischemia. In rat focal ischemia with reperfusion, the relationship between Dav and qT1 or qT2 will dissociate as Dav&#160;recovers, but may not for qT1 and qT2&#160;depending on duration of ischemia prior to reperfusion 8,28. Additionally, the evolution of ischemic damage is likely to be more variable in stroke patients due to individual differences in factors affecting microcirculation such as age and co-morbidities (e.g., diabetes, hypertension, heart disease). These factors will inevitably influence the time dependence of f1, f2 and Voverlap in human strokes and thus requires investigation in clinical settings.
To conclude, qMRI parameters provide estimates of stroke onset time. Voverlap and f2 provide the most accurate estimates and may also be informative of tissue status. qMRI could therefore be clinically beneficial in terms of aiding treatment decisions for patients with unknown onset time. An issue to be considered here is that the gray-to-white-matter ratio in rat brain is much higher than in humans, and hydrodynamics in these brain tissue types may vary 18. Nevertheless, further investigation into the time dependence of f2, Voverlap and qT2 in hyper acute stroke patients is warranted.

脳組織は、ATP 合成と限られたエネルギー資源の酸化的リン酸化の依存度が高いため虚血に対して特に脆弱です。脳水プールの再分配、興奮神経伝達物質放出と最終的に破壊的なプロセス1の開始につながる細胞内および細胞外スペースの微妙な時間依存イオン変化の ischemia の結果します。虚血、組織の損傷は、特定の時間枠の2内血流をリストアできない場合初期コアを超えて します。脳卒中発症の時間は、現在の薬物療法の虚血性脳卒中、血栓溶解薬3で再開通を含む臨床判断の重要な基準の 1 つです。その結果、多くの患者は、自動的に、証人や症状4、5の意識の欠如 ('ウェイク アップ ストローク')、睡眠中に起こる脳卒中により、未知の症状発症時期による血栓溶解療法の対象外です。このような患者は、血栓溶解療法のものと思われるので、脳卒中発症の時間を決定する手順そのためです。
MRI プローブ水in vivo。ダイナミクスを急性虚血性エネルギー障害6深刻な摂動.特に、水の分子の並進 (熱) によって支配される水の拡散はエネルギー障害7による虚血の早期の瞬間に減少します。これは順番神経細胞8の無酸素脱分極の結果します。拡散 MRI (飲酒運転) 脳卒中急性期9のゴールド スタンダードの診断イメージ投射様相となっています。飲酒運転信号が虚血虚血組織識別することを許可するのに応答して急速に増加、虚血性脳卒中10の最初の数時間の間に任意の時間依存性を表示されません。同様に、見かけの拡散係数 (ADC) などの水の拡散の定量的な対策または拡散テンソル (Dav) のトレース、虚血性の組織で急速に減少、動物脳卒中脳卒中発症からの時間との関係を示す10患者11をモデル化します。
定量的な MRI (qMRI) 緩和パラメーター、qT1qT2 qT1ρ、回転運動と水の水素原子の交換によって支配され、虚血性脳実質次のように複雑な経時変化を表示エネルギー障害6。このような経時変化は、脳卒中発症患者12と虚血13,14,15の動物モデルで推定するに有効になります。ラット焦点ストローク、qT1ρ虚血発症後ほぼ瞬時に増加、少なくとも 6 時間13,14線形続行されます。qT1緩和時間はまた 2 つの時定数で記述することができます脳虚血組織における時間依存的増加: 初期の速い段階の後、持続時間8,16遅いフェーズ。この相性増加のため qT1ストロークのタイミングでの使用は、qT1ρ MRI 15のそれよりも複雑かもしれません。qT2緩和時間も変化を示す bi, ラット焦点のストロークでというが初期を短縮されて 1 時間以内時間13と直線的に増加が続きます。初期の短縮を含む 2 つの並列実行要因によって説明される: (i) の蓄積はいわゆる結果脱酸素化ヘモグロビン '否定的な血液酸素化レベル依存効果' と (ii) は、細胞外の水へのシフト、細胞内スペース17,18。QT2の時間依存の増加は細胞毒性の原因および/または分子病態浮腫とそれに続く分解細胞内の高分子構造18。QT1ρと qT2データの両方は、前臨床モデル14ストローク発症時間の正確な見積もりを提供します。qT2 12と T2-加重信号強度19,20は、臨床の現場で脳卒中発症時間推定のため悪用されています。
量的緩和時間の大脳半球機能差に加え虚血領域内の上昇の緩和時間の分布も脳卒中発症時間14の代理として役立つかもしれない。ストローク、高架 qT1ρqT2 qT と地域のモデルラット1緩和時間は当初普及には虚血性病変が定義されているよりも小さいが時間14,15、増加 21。したがって虚血性病変のサイズに対する割合として上昇の緩和時間の分布の定量化は推定14,15と脳卒中発症時間もできます。ここでは、qMRI パラメーターを使用してストロークのラットモデルにおける脳卒中発症時刻を確認するプロトコルについて述べる。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td></td>
			<td>Magnetic Field Strength</td>
			<td>Operation Frequency</td>
		</tr>
		<tr>
			<td>MRI scanner</td>
			<td>Agilent, Santa Clara, CA, USA</td>
			<td>9.4T</td>
			<td>400.13 MHz</td>
		</tr>
		<tr>
			<td>Linear volume transmit RF-coil</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td>-</td>
			<td>400.13MHz</td>
		</tr>
		<tr>
			<td>Actively decoupled receive coil</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td>-</td>
			<td>400.13MHz</td>
		</tr>
		<tr>
			<td>Rat head holder</td>
			<td>RAPID Biomedical, Rimpar, Germany</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>i-Stat handheld blood-gas analyzer</td>
			<td>i-Stat Co, East Windsor, NJ, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Pneumatic pillow breathing rate monitor</td>
			<td>SA Instruments Inc, Stony Brook, NY, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Rodent rectal temperarure moniring device</td>
			<td>SA Instruments Inc, Stony Brook, NY, USA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Name</td>
			<td>Company</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Chemicals</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane: Attane Vet 1000mg/g</td>
			<td>Piramal Healthcare UK Ltd, Northumberland, UK</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2,3,5-Triphenyltetrazolium cholide=TTC</td>
			<td>Sigma-Aldrich, Gillinham, Dorset, UK</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

a magnetic resonance imaging protocol for stroke onset time estimation in permanent cerebral ischemia

MRI は、脳水の低下の拡散係数による急性期脳梗塞を検出する特異的かつ高感度イメージング ツールを提供します。虚血性脳卒中のモデルラット、(低拡散による線引き) 虚血性病変と非虚血性対側半球の定量的 T1と T2 MRI 緩和時間 (qT1および qT2) の違いを増やす脳卒中発症からの時間。MRI 緩和時間差の時間依存性は線形関数で記述されるヒューリスティックと脳卒中発症時の簡単な見積もりを提供します。さらに、異常 qT1と qT2虚血病変内のボリュームはストロークのタイミングの相補的な方法を提供するとともに直線的に増加します。(半) 自動化されたコンピューター ルーチンに基づいて定量化された拡散係数は虚血ラットにおける急性期脳梗塞組織を記述する発表します。このルーチンは、大脳半球機能差 qT1 qT2緩和時間と場所異常 qT1と病変内 qT2ボクセルのボリュームを決定します。QT1発症時間の見積もりに関連付けられた不確実性、qT2 MRI データがストロークの最初の 5 時間の ± 47 分 ± 25 分から変わる。最も正確な発症時間の見積もりを異常 qT1と qT2病変ボリュームの重複の量を定量化することで得られる、' V は、重複を ' と呼ばれることができます (± 25 分) または qT2大脳半球機能差を定量化することで緩和時間のみ (± 28 分)。全体的にみて、qT2派生パラメーターは qT1からのそれらを上回る。現在の MRI プロトコルは、一過性脳虚血に適用できない可能性があります恒久的な虚血モデルの超急性期でテストします。

ラットの血液ガスの通り: その2 95.8 ± 3.2%、P、CO2 51.6 ± 2.9 mmHg、pH 7.30 ± 0.04。
典型的な DavqT2 MCAO は図 1 aの最初 3 のパネルに示すように 4 時間ポイント記事で代表的なラットの中央のスライスから qT1画像。図 1の他のパネルで画像を示す赤と昇格した qT1qT2 Vが重なる地域と虚血病変領域の自動検出の虚血性病変が緑色で表示されます。2 h のポスト-MCAO、虚血性病変で高 qT1地域だった高 qT2よりも大きく (p &#60; 0.01)、時間 (図 1) が収束します。Davで虚血性病変高 qT1の地域よりも大きかった (p &#60; 0.05) と qT2 (p &#60; 0.05) 最初の 2 時間で。
QMRI パラメーターの時間の依存関係は、図 2のとおりです。すべての qMRI パラメーターが時間ポスト MCAO の有意な予測因子 (ΔT1: R2 = 0.71、ΔT2: R2 = 0.75、f1: R2 = 0.53、f2: R2 = 0.82 V重複: R2 = 0.87)。脳卒中発症が ± ΔT1ΔT2± f1f2±34 分 ± 25 V重複分に 47 分 28 分 ± 37 分頃各パラメーターの RMSE を基に、不確実性の時間の見積もりに関連付けられます。したがって、脳卒中発症からの時間の最も正確な推定値を与えた Vオーバー ラップします。
MCAO は主に灰白質 (図 1 d) で不可逆的な虚血性損傷を確認後、約 6 時間のサンプルを脳 TTC 染色します。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55277/55277fig1.jpg"> 
図 1: 例ラットにおける虚血性脳卒中による qMRI のパラメーターの変更。(な) 例 qMRI 画像虚血 4 時間以上です。最初の 4 つの列表示 Davマップ、qT2マップ、qT1マップと T2強調像それぞれ。残りの列は、Davを自動的にセグメント化された病変の様々 な表現とマップを表示します。自動的に検出された Dav病変が赤い [5] 列に表示されます。6 D 列にav病変は高 qT2緑ボクセルと赤で表示されます。列 7 Dav病変は緑色で示されている高 qT1ボクセルと赤で表示されます。列 8 Dav病変が昇格した qT1と qT2が (V重複) 緑ボクセルと赤で表示されます。(b) は、時間記事、MCAO の関数として Dav病変だけでなく、時間 0 で非病変 qT2配布 qT2の分布を示しています。(c) 凡例を示しています対応する qT1分布、隣接するパネル (b) と (c) に係る。(d) は、動物は 6 h ポスト MCAO で犠牲になった後に TTC 染色脳スライスを示しています。<a href="http://ecsource.jove.com/files/ftp_upload/55277/55277fig1large.jpg" target="_blank">この図の拡大版を表示するのにはここをクリックしてください</a>。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55277/55277fig2.jpg"> 
図 2: 虚血のタイミングに関連する時間のポスト MCAO と qMRI のパラメーター間の関係。f1f2、(c) V のオーバー ラップ、(d)、(b) ΔT1 , (e)、(、) を示しています ΔT2。各パラメーター (赤実線) に最適、RMSE バー (黒実線) が表示されます。点線は、MCAO を受ける indivudual 5 ラットのそれぞれを表しています。<a href="http://ecsource.jove.com/files/ftp_upload/55277/55277fig2large.jpg" target="_blank">この図の拡大版を表示するのにはここをクリックしてください</a>。

Watch this Scientific Journal Video about A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia at JoVE.com

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

磁気共鳴イメージング (qMRI) パラメーターを利用したストロークのラットモデルにおける脳卒中発症時間推定のためのプロトコルを説明します。手順は、脳卒中急性期病変と定量的 T1と T2 (qT1および qT2) 緩和時間ストロークのタイミングのための描写のための拡散強調 MRI を悪用します。

恒久的な脳虚血における脳卒中発症時間推定のための磁気共鳴イメージ投射プロトコル

MRI provides a sensitive and specific imaging tool to detect acute ischemic stroke by means of a reduced diffusion coefficient of brain water. In a rat ...

a-magnetic-resonance-imaging-protocol-for-stroke-onset-time

Research

JoVE Journal

Neuroscience

14.0K ビュー.  University of Bristol. 磁気共鳴イメージング (qMRI) パラメーターを利用したストロークのラットモデルにおける脳卒中発症時間推定のためのプロトコルを説明します。手順は、脳卒中急性期病変と定量的 T1と T2 (qT1および qT2) 緩和時間ストロークのタイミングのための描写のための拡散強調 MRI を悪用します。

ビデオ: A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

Magnetic Resonance Spectroscopy of live Drosophila melanogaster using Magic Angle Spinning

High-Resolution Magic Angle Spinning (HRMAS) proton magnetic resonance spectroscopy (1H-MRS) is a novel non-destructive technique that improves spectral line-widths and allows high-resolution spectra to be obtained from extracts, intact cells, cell cultures, and more importantly intact tissue to investigate relationships between metabolites and cellular processes. In vivo HRMAS 1H-MRS studies have yet to be reported in the live fruit fly Drosophila melanogaster. Drosophila, as a simpler genetic organism, allows the multiple biological functions and various evolutionarily conserved signaling pathways to be examined at the whole organism level and it is a useful model for investigating genetics and physiology. To this end, we developed and implemented an in vivo HRMAS 1H-MRS method to investigate live Drosophila at 14.1 T. Here, we outline an HRMAS 1H-MRS protocol for the molecular characterization of Drosophila with a conventional MR spectrometer equipped with an HRMAS probe. This technique is a novel, in vivo, non-destructive Drosophila metabolite measurement approach, which enables the identification of disease biomarkers and thus may contribute to novel therapeutic development.

Magnetic Resonance Spectroscopy of live Drosophila melanogaster using Magic Angle Spinning

This technique enables the use of high-resolution magic angle spinning proton MR spectroscopy (HRMAS 1H-MRS) for molecular characterization of live Drosophila melanogaster with a conventional 14.1 tesla spectrometer equipped with an HRMAS probe.

ライブの磁気共鳴分光法キイロショウジョウバエマジックアングルスピニングを使用して

High-Resolution Magic Angle Spinning (HRMAS) proton magnetic resonance spectroscopy (1H-MRS) is a novel non-destructive technique that improves spectral ...

神経科学

Multiple-mouse Neuroanatomical Magnetic Resonance Imaging

The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and evaluating mouse models of human disease. MRI is an excellent modality for investigating genetically altered animals. It is capable of whole brain coverage, can be used in vivo, and provides multiple contrast mechanisms for investigating different aspects of neuranatomy and physiology. The advent of high-field scanners along with the ability to scan multiple mice simultaneously allows for rapid phenotyping of novel mutations.
Effective mouse MRI studies require attention to many aspects of experiment design. In this article, we will describe general methods to acquire quality images for mouse phenotyping using a system that images mice concurrently in shielded transmit/receive radio frequency (RF) coils in a common magnet (Bock et al., 2003). We focus particularly on anatomical phenotyping, an important and accessible application that has shown a high potential for impact in many mouse models at our imaging centre. Before we can provide the detailed steps to acquire such images, there are important practical considerations for both in vivo brain imaging (Dazai et al., 2004) and ex vivo brain imaging (Spring et al., 2007) that should be noted. These are discussed below.

Magnetic resonance imaging (MRI) has become an increasingly popular tool for examining the phenotype of genetically altered mice. This article illustrates the methods necessary to achieve high-throughput phenotyping of genetically altered mice using multiple-mouse MRI.

複数のマウスの神経解剖学的磁気共鳴イメージング

The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and ...

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4.
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.

This article describes techniques to perform high-resolution functional magnetic resonance imaging with 1.2 mm sampling in human midbrain and subcortical structures using a 3T scanner. Use of these techniques to resolve topographic maps of visual stimulation in the human superior colliculus (SC) is given as an example.

人間の中脳の高解像度機能的磁気共鳴画像法

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon ...

The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33. To help improve this understanding, proton magnetic resonance spectroscopy (1H-MRS) can be used as it allows the in vivo quantification of brain metabolites such as &#947;-aminobutyric acid (GABA) and glutamate in a region-specific manner 41. In fact, a recent study demonstrated that 1H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31. Methodological factors to consider and possible modifications to the protocol are also discussed.

This article aims to describe a basic protocol for combining transcranial direct current stimulation (tDCS) with proton magnetic resonance spectroscopy (1H-MRS) measurements to investigate the effects of bilateral stimulation on primary motor cortex metabolism.

一次運動野代謝に及ぼすバイ半球経頭蓋電気刺激効果の測定のためのツールと​​しての磁気共鳴分光法の利用

Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of ...

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has been heavily studied. While many imaging studies treat the hippocampus as a single unitary neuroanatomical structure, it is, in fact, composed of several subfields that have a complex three-dimensional geometry. As such, it is known that these subfields perform specialized functions and are differentially affected through the course of different disease states. Magnetic resonance (MR) imaging can be used as a powerful tool to interrogate the morphology of the hippocampus and its subfields. Many groups use advanced imaging software and hardware (&#62;3T) to image the subfields; however this type of technology may not be readily available in most research and clinical imaging centers. To address this need, this manuscript provides a detailed step-by-step protocol for segmenting the full anterior-posterior length of the hippocampus and its subfields: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus (DG), strata radiatum/lacunosum/moleculare (SR/SL/SM), and subiculum. This protocol has been applied to five subjects (3F, 2M; age 29-57, avg. 37). Protocol reliability is assessed by resegmenting either the right or left hippocampus of each subject and computing the overlap using the Dice&#39;s kappa metric. Mean Dice&#39;s kappa (range) across the five subjects are: whole hippocampus, 0.91 (0.90-0.92); CA1, 0.78 (0.77-0.79); CA2/CA3, 0.64 (0.56-0.73); CA4/dentate gyrus, 0.83 (0.81-0.85); strata radiatum/lacunosum/moleculare, 0.71 (0.68-0.73); and subiculum 0.75 (0.72-0.78). The segmentation protocol presented here provides other laboratories with a reliable method to study the hippocampus and hippocampal subfields in vivo using commonly available MR tools.

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The goal of this manuscript is to study the hippocampus and hippocampal subfields using MRI. The manuscript describes a protocol for segmenting the hippocampus and five hippocampal substructures: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, strata radiatum/lacunosum/moleculare, and subiculum.

高解像度<em&gt;インビボ</em&gt; 3T磁気共鳴画像を用いたヒト海馬サブフィールドのためのマニュアルセグメンテーションプロトコル

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has ...

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of structural MRI in vivo is ultimately limited by physiological noise, including pulsation, respiration and head movement. Although imaging hardware continues to improve, it is still difficult to resolve structures on the millimeter scale. For example, the primary visual sensory pathways synapse at the lateral geniculate nucleus (LGN), a visual relay and control nucleus in the thalamus that normally is organized into six interleaved monocular layers. Neuroimaging studies have not been able to reliably distinguish these layers due their small size that are less than 1 mm thick.
The resolving limit of structural MRI, in a postmortem brain was tested using multiple images averaged over a long duration (~24 h). The purpose was to test whether it was possible to resolve the individual layers of the LGN in the absence of physiological noise. A proton density (PD)1 weighted pulse sequence was used with varying resolution and other parameters to determine the minimum number of images necessary to be registered and averaged to reliably distinguish the LGN and other subcortical regions. The results were also compared to images acquired in living human brains. In vivo subjects were scanned in order to determine the additional effects of physiological noise on the minimum number of PD scans needed to differentiate subcortical structures, useful in clinical applications.

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

Here we present a protocol to determine the minimum number images that needed to be registered and averaged to resolve subcortical structures and test whether the individual layers of the LGN could be resolved in the absence of physiological noise.

ヒト皮質下の高分解能構造磁気共鳴イメージング<I&gt;インビボ</I&gt;と死後

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of ...

Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

The overall goal of this protocol is to accurately align magnetic resonance imaging (MRI) image volumes with histology sections via the creation of customized 3D-printed brain holders and slicer boxes.

組織学でMRIをマージするために、3D印刷技術を活用：脳セクショニングのためのプロトコルを

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume ...

Evaluation of Bioenergetic Function in Cerebral Vascular Endothelial Cells

The integrity of the blood-brain-barrier (BBB) is critical to prevent brain injury. Cerebral vascular endothelial (CVE) cells are one of the cell types that comprise the BBB; these cells have a very high-energy demand, which requires optimal mitochondrial function. In the case of disease or injury, the mitochondrial function in these cells can be altered, resulting in disease or&#160;the opening of the BBB. In this manuscript, we introduce a method to measure mitochondrial function in CVE cells by using whole, intact cells and a bioanalyzer. A mito-stress assay is used to challenge the cells that have been perturbed, either physically or chemically, and evaluate their bioenergetic function. Additionally, this method also provides a useful way to screen new therapeutics that have direct effects on mitochondrial function. We have optimized the cell density necessary to yield oxygen consumption rates that allow for the calculation of a variety of mitochondrial parameters, including ATP production, maximal respiration, and spare capacity. We also show the sensitivity of the assay by demonstrating that the introduction of the&#160;microRNA, miR-34a, leads to a pronounced and detectable decrease in mitochondrial activity. While the data shown in this paper is optimized for the bEnd.3 cell line, we have also optimized the protocol for primary CVE cells, further suggesting the utility in preclinical and clinical models.

Endothelial cell mitochondria are critical to maintain blood-brain-barrier integrity. We introduce a protocol to measure bioenergetic function in cerebral vascular endothelial cells.

脳血管内皮細胞での生体エネルギー機能の評価

The integrity of the blood-brain-barrier (BBB) is critical to prevent brain injury. Cerebral vascular endothelial (CVE) cells are one of the cell types ...

Online Transcranial Magnetic Stimulation Protocol for Measuring Cortical Physiology Associated with Response Inhibition

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) characterization of primary motor cortex (M1) excitability and inhibition. Motor response inhibition prevents unwanted actions and is abnormal in several neuropsychiatric conditions. TMS is a non-invasive technology that can quantify M1 excitability and inhibition using single- and paired-pulse protocols and can be precisely timed to study cortical physiology with high temporal resolution. We modified the original Slater-Hammel (S-H) stop signal task to create a &#34;racecar&#34; version with TMS pulses time-locked to intra-trial events. This task is self-paced, with each trial initiating after a button push to move the racecar towards the 800 ms target. GO trials require a finger-lift to stop the racecar just before this target. Interspersed randomly are STOP trials (25%) during which the dynamically adjusted stop signal prompts subjects to prevent finger-lift. For GO trials, TMS pulses were delivered at 650 ms after trial onset; whereas, for STOP trials, the TMS pulses occurred 150 ms after the stop signal. The timings of the TMS pulses were decided based on electroencephalography (EEG) studies showing event-related changes in these time ranges during stop signal tasks. This task was studied in 3 blocks at two study sites (n=38) and we recorded behavioral performance and event-related motor-evoked potentials (MEP). Regression modelling was used to analyze MEP amplitudes using age as a covariate with multiple independent variables (sex, study site, block, TMS pulse condition [single- vs. paired-pulse], trial condition [GO, successful STOP, failed STOP]). The analysis showed that TMS pulse condition (p&#60;0.0001) and its interaction with trial condition (p=0.009) were significant. Future applications for this online S-H/TMS paradigm include the addition of simultaneous EEG acquisition to measure TMS-evoked EEG potentials. A potential limitation is that in children, the TMS pulse sound could&#160;affect behavioral task performance.

We describe an experimental procedure to quantify excitability and inhibition of primary motor cortex during a motor response inhibition task by using Transcranial Magnetic Stimulation throughout the course of a Stop Signal Task.

反応抑制に関連する皮質の生理学を測定するためのオンラインの経頭蓋磁気刺激プロトコル

We describe the development of a reproducible, child-friendly motor response inhibition task suitable for online Transcranial Magnetic Stimulation (TMS) ...

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic resonance imaging (MRI) plays an important role in both confirming the diagnosis and evaluating the degree of compression. However, the anatomical detail provided by conventional MRI is not sufficient to accurately estimate neuronal damage and/or assess the possibility of neuronal recovery in chronic spinal cord compression patients. In contrast, diffusion tensor imaging (DTI) can provide quantitative results according to the detection of water molecule diffusion in tissues. In the present study, we develop a methodological framework to illustrate the application of DTI in chronic spinal cord compression disease. DTI fractional anisotropy (FA), apparent diffusion coefficients (ADCs), and eigenvector values are useful for visualizing microstructural pathological changes in the spinal cord. Decreased FA and increases in ADCs and eigenvector values were observed in chronic spinal cord compression patients compared to healthy controls. DTI could help surgeons understand spinal cord injury severity and provide important information regarding prognosis and neural functional recovery. In conclusion, this protocol provides a sensitive, detailed, and noninvasive tool to evaluate spinal cord compression.

Here, we present a protocol for the application of diffusion tensor imaging parameters to evaluate spinal cord compression.

慢性脊髄圧迫における拡散テンソル磁気共鳴画像

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic ...