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Quantitative Prostate Diffusion MRI and Multi-Dimensional Diffusion-Relaxation Correlation MRI for Characterization of Prostate Cancer- [electronic resource]
Quantitative Prostate Diffusion MRI and Multi-Dimensional Diffusion-Relaxation Correlation...
Quantitative Prostate Diffusion MRI and Multi-Dimensional Diffusion-Relaxation Correlation MRI for Characterization of Prostate Cancer- [electronic resource]

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자료유형  
 학위논문파일 국외
최종처리일시  
20240214101207
ISBN  
9798379648268
DDC  
610
저자명  
Zhang, Zhaohuan.
서명/저자  
Quantitative Prostate Diffusion MRI and Multi-Dimensional Diffusion-Relaxation Correlation MRI for Characterization of Prostate Cancer - [electronic resource]
발행사항  
[S.l.]: : University of California, Los Angeles., 2023
발행사항  
Ann Arbor : : ProQuest Dissertations & Theses,, 2023
형태사항  
1 online resource(196 p.)
주기사항  
Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
주기사항  
Advisor: Wu, Holden H.
학위논문주기  
Thesis (Ph.D.)--University of California, Los Angeles, 2023.
사용제한주기  
This item must not be sold to any third party vendors.
초록/해제  
요약Prostate Cancer (PCa) remains the second most common cause of cancer-related death in men in the U.S. Multi-parametric (mp) MRI is playing an increasingly important role for the localization, detection, and risk stratification of PCa. However, prostate mp-MRI still misses PCa in up to 45% of men and faces challenges in distinguishing clinically significant PCa from indolent PCa. Therefore, MRI technology must be improved to enhance diagnostic performance for PCa. This thesis aimed to improve prostate MRI by addressing two challenges. First, the diffusion-weighted imaging (DWI) component of mp-MRI often suffers from artifacts such as distortion and low signal-to-noise ratio (SNR), which can lead to low diagnostic image quality. Second, prostate microstructure features are key determinants for histopathological assessment of cancer aggressiveness; however, current MRI techniques have limitations in capturing this information.To address the first challenge, in Aim 1, we translated and evaluated an eddy current-nulled convex optimized diffusion encoding (ENCODE) based prostate DWI technique that achieves short echo time (TE) to maintain SNR while reducing prostate geometric distortion from eddy currents and susceptibility effects. Further, in Aim 2, we developed a combined TE-minimized ENCODE diffusion encoding acquisition with a random matrix theory-based denoising reconstruction technique to improve the SNR and robustness of high-resolution (in-plane: 1.0x1.0 mm2 ) prostate DWI and apparent diffusion coefficient mapping.To address the second challenge, in Aim 3, we performed a first proof-of-concept ex vivo evaluation and validation of the diffusion-relaxation correlation spectrum imaging (DR-CSI) technique at 3T for quantifying microscopic tissue compartments (epithelium, stroma, and lumen) in PCa using whole-mount digital histopathology as the reference standard. Further, in Aim 4, we explored and evaluated sequential backward selection analysis for the acceleration of DR-CSI through subsampling of the diffusion-relaxation contrast encoding space while maintaining the accuracy of prostate microstructure mapping in PCa.
일반주제명  
Biomedical engineering.
일반주제명  
Medical imaging.
일반주제명  
Oncology.
일반주제명  
Bioengineering.
키워드  
Diffusion MRI
키워드  
Microstructure
키워드  
Prostate Cancer
키워드  
Prostate microstructure
키워드  
Quantitative imaging
기타저자  
University of California, Los Angeles Bioengineering 0288
기본자료저록  
Dissertations Abstracts International. 84-12B.
기본자료저록  
Dissertation Abstract International
전자적 위치 및 접속  
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MARC

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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a610
■1001  ▼aZhang,  Zhaohuan.
■24510▼aQuantitative  Prostate  Diffusion  MRI  and  Multi-Dimensional  Diffusion-Relaxation  Correlation  MRI  for  Characterization  of  Prostate  Cancer▼h[electronic  resource]
■260    ▼a[S.l.]:▼bUniversity  of  California,  Los  Angeles.  ▼c2023
■260  1▼aAnn  Arbor  :▼bProQuest  Dissertations  &  Theses,  ▼c2023
■300    ▼a1  online  resource(196  p.)
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  84-12,  Section:  B.
■500    ▼aAdvisor:  Wu,  Holden  H.
■5021  ▼aThesis  (Ph.D.)--University  of  California,  Los  Angeles,  2023.
■506    ▼aThis  item  must  not  be  sold  to  any  third  party  vendors.
■520    ▼aProstate  Cancer  (PCa)  remains  the  second  most  common  cause  of  cancer-related  death  in  men  in  the  U.S.  Multi-parametric  (mp)  MRI  is  playing  an  increasingly  important  role  for  the  localization,  detection,  and  risk  stratification  of  PCa.  However,  prostate  mp-MRI  still  misses  PCa  in  up  to  45%  of  men  and  faces  challenges  in  distinguishing  clinically  significant  PCa  from  indolent  PCa.  Therefore,  MRI  technology  must  be  improved  to  enhance  diagnostic  performance  for  PCa. This  thesis  aimed  to  improve  prostate  MRI  by  addressing  two  challenges.  First,  the  diffusion-weighted  imaging  (DWI)  component  of  mp-MRI  often  suffers  from  artifacts  such  as  distortion  and  low  signal-to-noise  ratio  (SNR),  which  can  lead  to  low  diagnostic  image  quality.  Second,  prostate  microstructure  features  are  key  determinants  for  histopathological  assessment  of  cancer  aggressiveness;  however,  current  MRI  techniques  have  limitations  in  capturing  this  information.To  address  the  first  challenge,  in  Aim  1,  we  translated  and  evaluated  an  eddy  current-nulled  convex  optimized  diffusion  encoding  (ENCODE)  based  prostate  DWI  technique  that  achieves  short  echo  time  (TE)  to  maintain  SNR  while  reducing  prostate  geometric  distortion  from  eddy  currents  and  susceptibility  effects.  Further,  in  Aim  2,  we  developed  a  combined  TE-minimized  ENCODE  diffusion  encoding  acquisition  with  a  random  matrix  theory-based  denoising  reconstruction  technique  to  improve  the  SNR  and  robustness  of  high-resolution  (in-plane:  1.0x1.0  mm2  )  prostate  DWI  and  apparent  diffusion  coefficient  mapping.To  address  the  second  challenge,  in  Aim  3,  we  performed  a  first  proof-of-concept  ex  vivo  evaluation  and  validation  of  the  diffusion-relaxation  correlation  spectrum  imaging  (DR-CSI)  technique  at  3T  for  quantifying  microscopic  tissue  compartments  (epithelium,  stroma,  and  lumen)  in  PCa  using  whole-mount  digital  histopathology  as  the  reference  standard.  Further,  in  Aim  4,  we  explored  and  evaluated  sequential  backward  selection  analysis  for  the  acceleration  of  DR-CSI  through  subsampling  of  the  diffusion-relaxation  contrast  encoding  space  while  maintaining  the  accuracy  of  prostate  microstructure  mapping  in  PCa.
■590    ▼aSchool  code:  0031.
■650  4▼aBiomedical  engineering.
■650  4▼aMedical  imaging.
■650  4▼aOncology.
■650  4▼aBioengineering.
■653    ▼aDiffusion  MRI
■653    ▼aMicrostructure
■653    ▼aProstate  Cancer
■653    ▼aProstate  microstructure
■653    ▼aQuantitative  imaging
■690    ▼a0541
■690    ▼a0574
■690    ▼a0992
■690    ▼a0202
■71020▼aUniversity  of  California,  Los  Angeles▼bBioengineering  0288.
■7730  ▼tDissertations  Abstracts  International▼g84-12B.
■773    ▼tDissertation  Abstract  International
■790    ▼a0031
■791    ▼aPh.D.
■792    ▼a2023
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16933128▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.
■980    ▼a202402▼f2024

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