Dataset Information

Accurate Monitoring of Renal Injury State through in Vivo Magnetic Resonance Imaging with Ferric Coordination Polymer Nanodots.

ABSTRACT: It is highly challenging to detect the pathophysiology of the diseased kidneys and achieve precise diagnosis because there are few in vivo noninvasive imaging techniques to quantitatively assess kidney dysfunction. This longstanding challenge is normally attributed to the limited molecular contrast agents which can be addressed with renal clearable nanoprobes. In this report, we demonstrate the use of magnetic resonance imaging along with renal clearable ferric coordination polymer nanodots (Fe-CPNDs) for in vivo monitoring the kidney dysfunction effects following drug (daunomycin)-induced kidney injury. After intravenous injection of Fe-CPNDs, the change of the MR signal in the kidney can be precisely correlated with local pathological lesion which is demonstrated by renal anatomic details and biochemical examinations of urine and blood. This finding opens the door to the possibility of noninvasively assessing kidney dysfunction and local injuries.

SUBMITTER: Li X

PROVIDER: S-EPMC6130784 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Accurate Monitoring of Renal Injury State through in Vivo Magnetic Resonance Imaging with Ferric Coordination Polymer Nanodots.

Li Xiaodong X Chen Hongda H Liu Fuyao F Chen Yixin Y Zhang Huimao H Wang Zhenxin Z

ACS omega 20180504 5

It is highly challenging to detect the pathophysiology of the diseased kidneys and achieve precise diagnosis because there are few in vivo noninvasive imaging techniques to quantitatively assess kidney dysfunction. This longstanding challenge is normally attributed to the limited molecular contrast agents which can be addressed with renal clearable nanoprobes. In this report, we demonstrate the use of magnetic resonance imaging along with renal clearable ferric coordination polymer nanodots (Fe- ...[more]

PMID: 30221228

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Project description:The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: (1) that accurately identify individuals as having chronic vs episodic migraine vs being a healthy control; and (2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine.Study participants underwent magnetic resonance imaging for determination of regional cortical thickness, cortical surface area, and volume. Principal components analysis combined structural measurements into principal components accounting for 85% of variability in brain structure. Models consisting of these principal components were developed to achieve the classification objectives. Tenfold cross validation assessed classification accuracy within each of the 10 runs, with data from 90% of participants randomly selected for classifier development and data from the remaining 10% of participants used to test classification performance. Headache frequency thresholds ranging from 5-15 headache days/month were evaluated to determine the threshold allowing for the most accurate subclassification of individuals into lower and higher frequency subgroups.Participants were 66 migraineurs and 54 healthy controls, 75.8% female, with an average age of 36?+/-?11 years. Average classifier accuracies were: (1) 68% for migraine (episodic?+?chronic) vs. healthy controls; (2) 67.2% for episodic migraine vs healthy controls; (3) 86.3% for chronic migraine vs. healthy controls; and (4) 84.2% for chronic migraine vs episodic migraine. The classifiers contained principal components consisting of several structural measures, commonly including the temporal pole, anterior cingulate cortex, superior temporal lobe, entorhinal cortex, medial orbital frontal gyrus, and pars triangularis. A threshold of 15 headache days/month allowed for the most accurate subclassification of migraineurs into lower frequency and higher frequency subgroups.Classifiers consisting of cortical surface area, cortical thickness, and regional volumes were highly accurate for determining if individuals have chronic migraine. Furthermore, results provide objective support for the current use of 15 headache days/month as a threshold for dividing migraineurs into lower frequency (i.e., episodic migraine) and higher frequency (i.e., chronic migraine) subgroups.

Dataset Information

Accurate Monitoring of Renal Injury State through in Vivo Magnetic Resonance Imaging with Ferric Coordination Polymer Nanodots.

Publications

Accurate Monitoring of Renal Injury State through in Vivo Magnetic Resonance Imaging with Ferric Coordination Polymer Nanodots.

Similar Datasets

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