Cerebral blood flow measurement using intra-arterial bolus injection of 2H|2O monitored with magnetic resonance spectroscopy
Notice bibliographique
Résumé
This thesis reports the development of a MR-based, non-invasive cerebral blood flow (CBF) measurement method. The technique is a 3 step process: (1) Introduce a certain amount of tracer into the brain; (2) Monitor the kinetics of the tracer in the brain; (3) Fit a theoretical model to the monitored result to measure CBF. Measurements were performed on Sprague-Dawley rats pre-treated with Atropine$\\rm\\sp{TM},$ anaesthetized with Na-Pentobarbital. Animal preparation was a 3 step process: setting up mechanisms to monitor rat physiology; placement of the injection catheter; placement of the MR surface coil. Once prepared the animal was inserted into a Bruker Biospec 7/21 MR scanner for $\\sp2$H spectral acquisition. A series of 360 free induction decays (FID) were taken. The $\\sp2$H labeled water indicator was injected as an instantaneous bolus at the beginning of the 15$\\rm\\sp{th}$ FID. The serial data acquisition procedure was repeated to yield 5 sets of data per rat. The FID in the series was used to generate360 $\\sp2$H spectra. The peak heights of the spectra represent the relative amount of indicator in the brain at a particular time. The theoretical model fit to the washin and washout data was modified from the Stimulus-Response theorem. The model enabled measurement of the fast CBF (fCBF) and average CBF (aCBF) using the same indicator washin and washout curve. The validity of the CBF measurement method developed was tested, by examining its ability to track changes in CBF with changes in PaCO$\\sb2.$ Experiments were conducted in which PaCO$\\sb2$ levels were purposefully altered to hypocarbia and hypercarbia by adjusting ventilation rate and volume. The technique was able to track the anticipated changes in CBF with changes in PaCO$\\sb2.$ The reproducibility of the CBF measurement method developed was evaluated by repetitive CBF measurements on the same animal at the same PaCO$\\sb2$ level. The method was qualitatively reproducible. The CBF results obtained with the method developed were compared with values published in the literature using other techniques. The developed quantitative CBF method yielded an average CBF. 37% lower than the average of all values appearing in the literature (115 ml/100g/min). It is proposed that CBF underestimation is due to indicator not being freely diffusible and due to indicator recirculation. Two methods were employed to eliminate the CBF underestimation due to the indicator not being freely diffusible. The first was the extraction coefficient (E) method. E was the ratio of indicator extracted by the brain extravascular space to the total amount injected. The obtained E was related to PS to assess the degree of CBF underestimation. The second method employed deuterated alcohols as the indicators. Deuterated water and deuterated alcohol were simultaneously introduced into the brain. The more freely diffusible alcohol indicator resulted in a CBF that was larger. A convolution analysis was employed to account for CBF underestimation due to indicator recirculation. This technique utilized in input function obtained from the derivative of the washout curve and a point spread function from injecting an instantaneous bolus downstream of the brain while monitoring at the brain. This technique was successful in delineating and removing indicator recirculation from the CBF measurements. It was found that the diffusibility and recirculation corrected CBF values agree with a gold standard from the literature. (Abstract shortened by UMI.)
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».