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Linking and characterizing biologic scales of imaging data

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TitleInfo
Title
Linking and characterizing biologic scales of imaging data
SubTitle
applications to prostate cancer diagnosis
Name (type = personal)
NamePart (type = family)
Sparks
NamePart (type = given)
Rachel
NamePart (type = date)
1985-
DisplayForm
Rachel Sparks
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Madabhushi
NamePart (type = given)
Anant
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Anant Madabhushi
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Cai
NamePart (type = given)
Li
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Li Cai
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Pierce
NamePart (type = given)
Mark
DisplayForm
Mark Pierce
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Tomaszewksi
NamePart (type = given)
John
DisplayForm
John Tomaszewksi
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2014
DateOther (qualifier = exact); (type = degree)
2014-01
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Prostate cancer is the second most commonly diagnosed cancer of men, an estimated 192,000 men are diagnosed each year in the United States (source: American Cancer Society). The current gold standard for prostate cancer diagnosis is pathologist inspection of prostate needle biopsy samples obtained using transrectal ultrasound (TRUS). TRUS-guided biopsy is routine because TRUS is widely available and acquires real-time imagery. However, TRUS-guided biopsy has a low sensitivity, and initial biopsy misses approximately half of all men with prostate cancer. Multi-parametric Magnetic Resonance Imaging (MRI) has shown promise in detecting, localizing, and grading prostate cancer. MRI-TRUS fusion, whereby MRI is acquired pre-operatively then aligned to TRUS during biopsy, allows for both modalities to be leveraged. MRI-TRUS fusion will enable the construction of joint classifiers, which leverage imaging characteristics on both MRI and TRUS, to detect, localize, and grade prostate cancer. In order to train and validate these classifiers, ground truth spatial extent and aggressiveness of prostate cancer must be obtained. Manual pathologist inspection provides the ultimate definitive diagnosis of prostate cancer, with the Gleason grading system providing a measure of prostate cancer aggressiveness. Therefore whole mount histopathology (WMH) is aligned to fused MRI-TRUS imagery to provide ground truth of cancer location and aggressiveness. A drawback to this approach is that Gleason grade is subject to inter- and intra-observer variability. Hence there is a need for reproducible, computer assisted grading of pathology which can serve as a surrogate for ground truth prostate cancer aggressiveness. In Aim 1 we develop a novel registration algorithm, multi-attribute probabilistic elastic registration (MAPPER), to align MRI and TRUS prostate imagery. In Aim 2 we align WMH with fused MRI-TRUS imagery (Aim 1). In Aim 3 we develop novel morphologic features to distinguish between aggressive and non-aggressive prostate cancer on histopathology. This will enable WMH to serve as ground truth for prostate cancer aggressiveness in order to train a MRI-TRUS classifier. Future work will leverage the tools developed to combine signatures of prostate cancer appearance across MRI, TRUS, and WMH and enable the development of tools to target biopsy to aggressive prostate cancer.
Subject (authority = RUETD)
Topic
Biomedical Engineering
Subject (authority = ETD-LCSH)
Topic
Prostate--Cancer--Early detection
Subject (authority = ETD-LCSH)
Topic
Prostate--Magnetic resonance imaging
Subject (authority = ETD-LCSH)
Topic
Cancer--Ultrasonic imaging
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5274
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xxvi, 147 p. : ill.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Rachel Sparks
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3MC8X4G
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Sparks
GivenName
Rachel
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2014-01-02 13:40:53
AssociatedEntity
Name
Rachel Sparks
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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