MR Fingerprinting and Computerized Decision Support for Prostate Cancer
MR Fingerprinting and Computerized Decision Support for Prostate Cancer
批准号:
10219975
负责人:
Vikas Gulani
金额:
$58.17万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-03-02 至 2024-02-29
关键词:
Algorithmic AnalysisAlgorithmsBenignBiopsyCancer PatientClinicalComplementDataDetectionDevelopmentDiagnosisDiffusionDiscriminationDiseaseEvaluationExclusionFailureFingerprintGoalsHeterogeneityImageImage AnalysisImaging TechniquesImaging technologyIndolentLearningLesionLiteratureMagnetic ResonanceMagnetic Resonance ImagingMalignant NeoplasmsMalignant neoplasm of prostateMapsMeasurementMonitorMorphologyNeoplasmsOperative Surgical ProceduresOrganOutcomePalpablePatientsPatternPerformancePeriodicityPeripheralProbabilityPropertyProstateProstate-Specific AntigenProtocols documentationPublishingRiskScanningSiteSliceStressTechnologyTestingTextureTissuesTreatment ProtocolsValidationVariantVisualWorkaggressive therapybaseblindcancer heterogeneitycohortcomputerizedcostdisorder riskimprovedinnovationmenpatient subsetsprospectiveprostate biopsyprostatitisradiomicssupport toolstooltumor
中文摘要
项目摘要
前列腺仍然是唯一的器官,其中盲非靶向活检进行没有预先确定的
疑似肿瘤病灶。可触及异常或前列腺特异性抗原升高的男性必须
忍受经直肠活检的相关费用,不适,压力和并发症,因为它不是
不可能客观可靠地确定谁不需要活检。美国有超过50万人
没有前列腺癌的证据仍然接受前列腺活检,仅仅是因为PSA,一个D级测试
根据USPTF。因此,显然存在未满足的需求,即开发更好的成像技术,
能够改进前列腺的非侵入性表征的技术和图像分析算法
癌症和区分低级别惰性癌症从更具侵略性的中级到高级
变体。这将有助于引导和监测适当的患者在不太积极的治疗方案,
主动监视
目前,MRI对于检测高级别前列腺癌(PCa)是极好的,但是对于低级别和高级别前列腺癌(PCa)是不太准确的。
中度疾病。排除疾病,因此需要在一个子集的活检,
病人是不可能的。此外,选择主动监测的患者不能仅通过成像进行随访,
需要反复定期活检。磁共振指纹识别(MRF)是由我们的团队开创的一个框架。
团队同时量化多种组织特性与MRI,并已被用于量化T1和
T2比以前更有效、更准确、更精确。大量的初步数据显示,
该技术与表观扩散系数(ADC)标测相结合的实用性,
周围区域的潜在癌症。同时,我们的团队一直在开发和验证计算机化的
决策支持(CDS)工具,可以诊断,分级和表征PCa在外周和
移行区的影像我们建议开发一种前列腺癌的MRF检查,
同时绘制T1、T2和ADC图,用于有效和定量分离PCa与正常人
前列腺和分离低风险和更具侵略性的疾病。我们还将开发综合CDS
从MRF衍生图中识别其他图像衍生特征(放射组学)的工具,
补充MRF测量,以便更准确地检测和分级外周和外周中的PCa
和过渡区。这种MRF+CDS联合检查的准确性将在
活检前扫描的250名男性队列。
英文摘要
PROJECT SUMMARY
The prostate remains the only organ in which blind untargeted biopsies are conducted without a pre-identified
suspected focus of neoplasm. Men with palpable abnormalities or elevated prostate specific antigen must
endure trans-rectal biopsy with related costs, discomfort, stress, and complications, because it is not
impossible to objectively and reliably identify who does not require a biopsy. Well over 500,000 men in the US
with no evidence of prostate cancer still undergo prostate biopsies, solely on account of PSA, a grade D test
according to the USPTF. Consequently there is clearly an unmet need to develop both better imaging
techniques and image analysis algorithms that can enable improved non-invasive characterization of prostate
cancer and distinguish low grade indolent cancers from the more aggressive intermediate to high grade
variants. This would help channel and monitor appropriate patients in less aggressive treatment protocols such
as active surveillance.
Currently MRI is excellent for detecting high grade prostate cancer (PCa), but is less accurate for low and
intermediate grade disease. Definitive exclusion of disease, and thus the need for biopsy in a subset of
patients, is not possible. Also, patients who opt for active surveillance cannot be followed by imaging alone and
require repeated periodic biopsy. Magnetic resonance fingerprinting (MRF) is a framework pioneered by our
team for simultaneously quantifying multiple tissue properties with MRI, and has been used to quantify T1 and
T2 more efficiently, accurately, and precisely than previously possible. Extensive preliminary data show the
utility of this technology in combination with apparent diffusion coefficient (ADC) mapping, to separate normal
peripheral zone from potential cancer. In parallel our team has been developing and validating computerized
decision support (CDS) tools which can diagnose, grade, and characterize PCa both in the peripheral and
transitional zones on MRI. We propose to develop an MRF exam for prostate cancer that allows
simultaneous mapping of T1, T2, and ADC for efficient and quantitative separation of PCa from normal
prostate and to separate low risk and more aggressive disease. We will also develop integrated CDS
tools to identify additional image derived features (radiomics) from the MRF derived maps to
complement MRF measurements for more accurate detection and grading of PCa both in the peripheral
and transitional zones. The accuracy of this combined MRF+CDS exam will be prospectively validated in a
cohort of 250 men scanned prior to biopsy.
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DOI:
10.4103/jpi.jpi_60_18
发表时间:
2018-01-01
期刊:
Journal of pathology informatics
影响因子:
--
作者:
[Hipp, Jason D, Johann, Donald J, Tangrea, Michael A]
通讯作者:
Tangrea, Michael A
DOI:
10.1038/srep46450
发表时间:
2017-04-18
期刊:
Scientific reports
影响因子:
4.6
作者:
[Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih NNC, Tomaszewski J, González FA, Madabhushi A]
通讯作者:
Madabhushi A
DOI:
10.1038/s41698-023-00404-w
发表时间:
2023-06-02
期刊:
NPJ precision oncology
影响因子:
7.9
作者:
[]
通讯作者:
DOI:
10.1186/s13058-017-0846-1
发表时间:
2017-05-18
期刊:
Breast cancer research : BCR
影响因子:
--
作者:
[Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A]
通讯作者:
Madabhushi A
DOI:
10.1371/journal.pone.0196828
发表时间:
2018
期刊:
PloS one
影响因子:
3.7
作者:
[Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih N, Tomaszewski J, Madabhushi A, González F]
通讯作者:
González F
共 11 条
MR Fingerprinting and Computerized Decision Support for Prostate Cancer
-
批准号:10090051
-
项目类别:
-
资助金额:$59.37万
-
财政年份:2017
-
负责人:Vikas Gulani
-
依托单位:
Comprehensive quantitative ultrafast 3D liver MRI
-
批准号:8704436
-
项目类别:
-
资助金额:$50.28万
-
财政年份:2013
-
负责人:Vikas Gulani
-
依托单位:
Comprehensive quantitative ultrafast 3D liver MRI
-
批准号:8579414
-
项目类别:
-
资助金额:$49.27万
-
财政年份:2013
-
负责人:Vikas Gulani
-
依托单位:
Comprehensive quantitative ultrafast 3D liver MRI
-
批准号:8905601
-
项目类别:
-
资助金额:$52.94万
-
财政年份:2013
-
负责人:Vikas Gulani
-
依托单位:
BRAIN FUNCTION IMAGING USING DIFFUSION WEIGHTED MRI
-
批准号:2883347
-
项目类别:
-
资助金额:$2.3万
-
财政年份:1999
-
负责人:Vikas Gulani
-
依托单位:
BRAIN FUNCTION IMAGING USING DIFFUSION WEIGHTED MRI
-
批准号:2668812
-
项目类别:
-
资助金额:$2.21万
-
财政年份:1998
-
负责人:Vikas Gulani
-
依托单位:
BRAIN FUNCTION IMAGING USING DIFFUSION WEIGHTED MRI
-
批准号:2379149
-
项目类别:
-
资助金额:$1.71万
-
财政年份:1997
-
负责人:Vikas Gulani
-
依托单位:
BRAIN FUNCTION IMAGING USING DIFFUSION WEIGHTED MRI
-
批准号:2242527
-
项目类别:
-
资助金额:$1.79万
-
财政年份:1996
-
负责人:Vikas Gulani
-
依托单位:
BRAIN FUNCTION IMAGING USING DIFFUSION WEIGHTED MRI
-
批准号:2242526
-
项目类别:
-
资助金额:$1.52万
-
财政年份:1995
-
负责人:Vikas Gulani
-
依托单位:
海外基金