Research Project Core 2

研究项目核心2

基本信息

项目摘要

PROJECT 2 ABSTRACT “DERIVATION AND VALIDATION OF IMAGING BIOMARKERS FOR CKD PROGRESSION” There is a need for biomarkers that can identify children with Congenital Anomalies of the Kidneys and Urinary Tract (CAKUT) early in life at high risk of future CKD progression. Early identification of children who are at highest risk of CKD progression would help guide trials of therapies for those most likely to benefit from early treatment and spare those patients at low risk of progression potential treatment-associated harms. Two potential biomarkers of CKD progression that are available immediately after birth are renal parenchymal area (RPA) and kidney echogenicity. RPA is the gross area of the kidney in maximal longitudinal length minus the area of the collecting system. RPA “corrects” for a dilated collecting system, which is present in many children with CAKUT, and thus better estimates the functional area of the kidney than the currently used measurement of kidney length. RPA may measure the functional reserve of the kidneys, with smaller areas associated with lower nephron mass and greater probability of CKD progression. Kidney echogenicity is easily assessed on ultrasound and may predict CKD progression independent of RPA. If RPA estimates the quantity of the kidney parenchyma, echogenicity measures the quality of the remaining nephron mass. However, because kidney echogenicity is currently subjectively assessed and ways to measure kidney echogenicity have not been developed, its present utility as a clinical biomarker of CKD progression is limited. This proposed research will develop a method to objectively measure kidney echogenicity and then, using the Chronic Kidney Disease in Children (CKiD) study, will validate RPA and kidney echogenicity as two novel anatomic biomarkers of CKD progression among children with CAKUT. The advantages of these biomarkers are that they may predict CKD progression prior to the appearance of later serum or urine biomarkers, such as nadir creatinine or proteinuria, and can be measured non-invasively immediately after birth on routine clinical imaging. We will evaluate the use of RPA as a predictor of kidney function decline, and will develop an automated method to reliably and accurately measure kidney echogenicity among a cohort of 100 children without and with CKD at CHOP, and then will use ROC analysis to validate these imaging biomarkers of CKD progression among children with CAKUT enrolled in CKiD.
项目2摘要 “ CKD进展的成像生物标志物的衍生和验证” 需要生物标志物,可以识别出肾脏和尿的先天性异常的儿童 生命的早期(cakut)以未来CKD进展的高风险。早期确定在 CKD进展的最高风险将有助于指导最有可能从早期受益的人的疗法试验 治疗并避免那些具有进展潜在治疗相关危害的患者。两个潜力 出生后立即获得的CKD进展的生物标志物是肾脏副群体(RPA)和 肾脏回声。 RPA是肾脏的总区域,最大纵向长度减去 收集系统。 RPA“纠正”用于扩张的收集系统,该系统存在于许多Cakut的孩子中 因此,比当前使用的肾脏长度测量更好地估计了肾脏的功能区域。 RPA可以测量肾脏的功能储备,较小的区域与较低的肾单位质量相关 CKD进展的可能性更大。在超声波上很容易评估肾脏回声性 预测与RPA无关的CKD进程。如果RPA估计肾脏实质的数量,则 回声性测量其余肾单位质量的质量。但是,因为肾脏回声是 目前尚未开发主观评估和测量肾脏回声性的方法,目前 用作CKD进展的临床生物标志物的实用性有限。这项拟议的研究将开发一种方法 客观地测量肾脏回声性,然后使用儿童慢性肾脏疾病(CKID)研究, 将验证RPA和肾脏回声性作为CKD进展的两个新型解剖生物标志物 与Cakut。这些生物标志物的优点是,它们可以预测CKD的进展 以后的血清或尿液生物标志物的外观,例如nadir肌酐或蛋白尿,可以测量 出生后在常规临床成像上出生后立即进行非侵入性。我们将评估RPA作为预测指标的使用 肾功能下降的下降,并将开发一种自动化方法,以可靠,准确地测量肾脏 100名没有CKD和CKD的100名儿童的回声性,然后将使用ROC分析来 验证CKID儿童中CKD进展的这些成像生物标志物。

项目成果

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Gregory Edward Tasian其他文献

Gregory Edward Tasian的其他文献

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{{ truncateString('Gregory Edward Tasian', 18)}}的其他基金

Center for Machine Learning in Urology
泌尿外科机器学习中心
  • 批准号:
    10260577
  • 财政年份:
    2020
  • 资助金额:
    $ 3.61万
  • 项目类别:
Center for Machine Learning in Urology-Admin Core
泌尿科机器学习中心-管理核心
  • 批准号:
    10260578
  • 财政年份:
    2020
  • 资助金额:
    $ 3.61万
  • 项目类别:
Research Project Core 2
研究项目核心2
  • 批准号:
    10241470
  • 财政年份:
    2017
  • 资助金额:
    $ 3.61万
  • 项目类别:
Identifying and Mitigating Risk Factors for Dehydration-Mediated Nephrolithiasis in Adolescents
识别和减轻青少年脱水介导的肾结石的危险因素
  • 批准号:
    9282810
  • 财政年份:
    2015
  • 资助金额:
    $ 3.61万
  • 项目类别:
Identifying and Mitigating Risk Factors for Dehydration-Mediated Nephrolithiasis in Adolescents
识别和减轻青少年脱水介导的肾结石的危险因素
  • 批准号:
    8947453
  • 财政年份:
    2015
  • 资助金额:
    $ 3.61万
  • 项目类别:
Research Project Core 2
研究项目核心2
  • 批准号:
    9380708
  • 财政年份:
  • 资助金额:
    $ 3.61万
  • 项目类别:

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