Skewness and Kurtosis of Apparent Diffusion Coefficient in Human Brain Lesions to Distinguish Benign and Malignant Using MRI

The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion...

Full description

Saved in:
Bibliographic Details
Published inRecent Trends in Image Processing and Pattern Recognition Vol. 1036; pp. 189 - 199
Main Authors Vijithananda, Sahan M., Jayatilake, Mohan L., Weerakoon, Bimali S., Wathsala, P. G. S., Thevapriya, S., Thasanky, S., Kalupahana, Tharindu D., Wijerathne, Thusitha K.
Format Book Chapter
LanguageEnglish
Published Singapore Springer 2019
Springer Singapore
SeriesCommunications in Computer and Information Science
Subjects
Online AccessGet full text
ISBN9789811391835
9811391831
ISSN1865-0929
1865-0937
DOI10.1007/978-981-13-9184-2_17

Cover

Loading…
Abstract The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion assessment. Therefore, this study presents the utility of skewness and kurtosis of Apparent Diffusion Coefficient (ADC) to distinguish between benign and malignant brain lesions. All the Magnetic Resonance Imaging (MRI) scans were performed with a 3 Tesla Siemens Skyra MR system using a head coil. The sample consists of six subjects with locally advanced brain lesion. The Echo-Planar Imaging pulse sequence was used to acquire axial DW MRI data with a flip angle =  $$90^{\circ }$$ , Time of Echo/Time of Repetition (TE/TR) = 98/6400 ms, Field of View (FOV) = 256 mm, matrix size = 256  $$\times $$  256, slice thickness of 1 mm and two levels of diffusion sensitization ( $${\text {b} = 0 \text { and } 1000\,\text {s}/\text {mm}^2}$$ ). MATLAB 2014 Simulink software was used for the data analysis. The Region of Interest (ROI) the brain lesion was selected. The mean values of both the skewness and kurtosis of ADC within the ROI were determined and finally, the values were compared between benign and malignant brain lesions. The mean kurtosis and skewness of malignant and benign are 3.201, 3.738 and 0.071, 0.463 respectively. The mean kurtosis of benign is significantly high whereas mean skewness is significantly low. Therefore, there is a possibility of utilizing mean skewness and kurtosis pixel values as a potential biomarker to differentiate between benign and malignant brain lesions. ...
AbstractList The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion assessment. Therefore, this study presents the utility of skewness and kurtosis of Apparent Diffusion Coefficient (ADC) to distinguish between benign and malignant brain lesions. All the Magnetic Resonance Imaging (MRI) scans were performed with a 3 Tesla Siemens Skyra MR system using a head coil. The sample consists of six subjects with locally advanced brain lesion. The Echo-Planar Imaging pulse sequence was used to acquire axial DW MRI data with a flip angle =  $$90^{\circ }$$ , Time of Echo/Time of Repetition (TE/TR) = 98/6400 ms, Field of View (FOV) = 256 mm, matrix size = 256  $$\times $$  256, slice thickness of 1 mm and two levels of diffusion sensitization ( $${\text {b} = 0 \text { and } 1000\,\text {s}/\text {mm}^2}$$ ). MATLAB 2014 Simulink software was used for the data analysis. The Region of Interest (ROI) the brain lesion was selected. The mean values of both the skewness and kurtosis of ADC within the ROI were determined and finally, the values were compared between benign and malignant brain lesions. The mean kurtosis and skewness of malignant and benign are 3.201, 3.738 and 0.071, 0.463 respectively. The mean kurtosis of benign is significantly high whereas mean skewness is significantly low. Therefore, there is a possibility of utilizing mean skewness and kurtosis pixel values as a potential biomarker to differentiate between benign and malignant brain lesions. ...
Author Weerakoon, Bimali S.
Wathsala, P. G. S.
Thasanky, S.
Wijerathne, Thusitha K.
Jayatilake, Mohan L.
Kalupahana, Tharindu D.
Vijithananda, Sahan M.
Thevapriya, S.
Author_xml – sequence: 1
  givenname: Sahan M.
  surname: Vijithananda
  fullname: Vijithananda, Sahan M.
  email: deanahs@pdn.ac.lk, aquamarine.sahan@gmail.com
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 2
  givenname: Mohan L.
  surname: Jayatilake
  fullname: Jayatilake, Mohan L.
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 3
  givenname: Bimali S.
  surname: Weerakoon
  fullname: Weerakoon, Bimali S.
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 4
  givenname: P. G. S.
  surname: Wathsala
  fullname: Wathsala, P. G. S.
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 5
  givenname: S.
  surname: Thevapriya
  fullname: Thevapriya, S.
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 6
  givenname: S.
  surname: Thasanky
  fullname: Thasanky, S.
  organization: Department of Radiography/Radiotherapy, Faculty of Allied Health Sciences, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 7
  givenname: Tharindu D.
  surname: Kalupahana
  fullname: Kalupahana, Tharindu D.
  organization: Department of Computer Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya, Sri Lanka
– sequence: 8
  givenname: Thusitha K.
  surname: Wijerathne
  fullname: Wijerathne, Thusitha K.
  organization: Department of Computer Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya, Sri Lanka
BookMark eNpVkMtO5DAQRQ3TIF79Byz8A4EqO07sJTSv1nRrpBlYW07aBkNjhzgRm_n4cQAhzapK99atUp0jMgsxWEJOEc4QoD5XtSyUxAJ5oVCWBdNY75B5lrOKfNLYLjlEWYkCFK9__OdxMfv2mNonR4gIKBVHPCDzlJ4BgDFQKMQh-fvnxb4HmxI1YUN_jv0Qk080OnrRdaa3YaBX3rkx-RjoIlrnfOsn1Qd6N76aQC97k_uVnSYSHWKeT4MPj6NPT_TSBv8YPnavzTa3JkcfUrbp-vfyhOw5s012_lWPycPN9f3irlj9ul0uLlZFh0LWRQ2iBbBSINpKGl4Z4zaOG8FViU1byqaxDePQIHCU4DhsLBopSskqxrJzTNjn3tT1-bTtdRPjS9IIeuKtMzyd6WnkemKrJ945VH6Guj6-jTYN2k6pNj_fm237ZLrB9kkLhaoSQjOUmkHN_wEK7YAr
ContentType Book Chapter
Copyright Springer Nature Singapore Pte Ltd. 2019
Copyright_xml – notice: Springer Nature Singapore Pte Ltd. 2019
DBID FFUUA
DOI 10.1007/978-981-13-9184-2_17
DatabaseName ProQuest Ebook Central - Book Chapters - Demo use only
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Applied Sciences
Engineering
Computer Science
EISBN 9789811391842
981139184X
EISSN 1865-0937
Editor Hegadi, Ravindra S
Santosh, K. C
Editor_xml – sequence: 1
  fullname: Santosh, K. C
– sequence: 2
  fullname: Hegadi, Ravindra S
EndPage 199
ExternalDocumentID EBC5919655_218_207
GroupedDBID 38.
9-X
AABBV
AEJLV
AEKFX
AIFIR
ALEXF
ALMA_UNASSIGNED_HOLDINGS
AYMPB
BBABE
CXBFT
CZZ
EXGDT
FCSXQ
FFUUA
I4C
IEZ
MGZZY
NSQWD
OORQV
SBO
SNUHX
TPJZQ
Z7R
Z7U
Z7X
Z81
Z82
Z83
Z84
Z87
Z88
AAJYQ
AATVQ
ABBUY
ABCYT
ACDTA
ACDUY
AEHEY
AHNNE
ATJMZ
ID FETCH-LOGICAL-p1587-705c00e8511e68a36aafdf3a53941bc48bbeb230b103180f30de1a85482622b23
ISBN 9789811391835
9811391831
ISSN 1865-0929
IngestDate Tue Jul 29 20:12:41 EDT 2025
Fri Apr 11 00:03:44 EDT 2025
IsPeerReviewed false
IsScholarly false
LCCallNum TA1501-1820
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-p1587-705c00e8511e68a36aafdf3a53941bc48bbeb230b103180f30de1a85482622b23
Notes Original Abstract: The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion assessment. Therefore, this study presents the utility of skewness and kurtosis of Apparent Diffusion Coefficient (ADC) to distinguish between benign and malignant brain lesions. All the Magnetic Resonance Imaging (MRI) scans were performed with a 3 Tesla Siemens Skyra MR system using a head coil. The sample consists of six subjects with locally advanced brain lesion. The Echo-Planar Imaging pulse sequence was used to acquire axial DW MRI data with a flip angle = \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$90^{\circ }$$\end{document}, Time of Echo/Time of Repetition (TE/TR) = 98/6400 ms, Field of View (FOV) = 256 mm, matrix size = 256 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document} 256, slice thickness of 1 mm and two levels of diffusion sensitization (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {b} = 0 \text { and } 1000\,\text {s}/\text {mm}^2}$$\end{document}). MATLAB 2014 Simulink software was used for the data analysis. The Region of Interest (ROI) the brain lesion was selected. The mean values of both the skewness and kurtosis of ADC within the ROI were determined and finally, the values were compared between benign and malignant brain lesions. The mean kurtosis and skewness of malignant and benign are 3.201, 3.738 and 0.071, 0.463 respectively. The mean kurtosis of benign is significantly high whereas mean skewness is significantly low. Therefore, there is a possibility of utilizing mean skewness and kurtosis pixel values as a potential biomarker to differentiate between benign and malignant brain lesions. ...
OCLC 1110189311
PQID EBC5919655_218_207
PageCount 11
ParticipantIDs springer_books_10_1007_978_981_13_9184_2_17
proquest_ebookcentralchapters_5919655_218_207
PublicationCentury 2000
PublicationDate 2019
PublicationDateYYYYMMDD 2019-01-01
PublicationDate_xml – year: 2019
  text: 2019
PublicationDecade 2010
PublicationPlace Singapore
PublicationPlace_xml – name: Singapore
PublicationSeriesTitle Communications in Computer and Information Science
PublicationSeriesTitleAlternate Communic.Comp.Inf.Science
PublicationSubtitle Second International Conference, RTIP2R 2018, Solapur, India, December 21-22, 2018, Revised Selected Papers, Part II
PublicationTitle Recent Trends in Image Processing and Pattern Recognition
PublicationYear 2019
Publisher Springer
Springer Singapore
Publisher_xml – name: Springer
– name: Springer Singapore
RelatedPersons Barbosa, Simone Diniz Junqueira
Zhou, Lizhu
Kotenko, Igor
Filipe, Joaquim
Ghosh, Ashish
Yuan, Junsong
RelatedPersons_xml – sequence: 1
  givenname: Simone Diniz Junqueira
  surname: Barbosa
  fullname: Barbosa, Simone Diniz Junqueira
  organization: Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil
– sequence: 2
  givenname: Joaquim
  surname: Filipe
  fullname: Filipe, Joaquim
  organization: Polytechnic Institute of Setúbal, Setúbal, Portugal
– sequence: 3
  givenname: Ashish
  surname: Ghosh
  fullname: Ghosh, Ashish
  organization: Indian Statistical Institute, Kolkata, India
– sequence: 4
  givenname: Igor
  surname: Kotenko
  fullname: Kotenko, Igor
  organization: St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia
– sequence: 5
  givenname: Junsong
  surname: Yuan
  fullname: Yuan, Junsong
  organization: University at Buffalo, The State University of New York, Buffalo, USA
– sequence: 6
  givenname: Lizhu
  surname: Zhou
  fullname: Zhou, Lizhu
  organization: Tsinghua University , Beijing, China
SSID ssj0002209155
ssj0000580895
ssib054953581
Score 1.5702453
Snippet The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has...
SourceID springer
proquest
SourceType Publisher
StartPage 189
SubjectTerms ADC (Apparent Diffusion Coefficient)
Benign
Brain tumor
DWI (Diffusion Weighted Imaging)
Malignant
ROI (Region of Interest)
Title Skewness and Kurtosis of Apparent Diffusion Coefficient in Human Brain Lesions to Distinguish Benign and Malignant Using MRI
URI http://ebookcentral.proquest.com/lib/SITE_ID/reader.action?docID=5919655&ppg=207
http://link.springer.com/10.1007/978-981-13-9184-2_17
Volume 1036
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ3BbtQwEIYtWC7AoVBAFFrkA7eVkeM4qXNk263a0iKEWtSbZScOqoAs6maFhHh4Zhw7myy9lEuUdbJWlC-azExmfhPy1uVWVM5JlgqrmMxKw0wpLOPKgMdfCGty7Hc-_5gfX8rTq-wqLnEfukta-678fWtfyf9QhTHgil2ydyDbTwoDsA98YQuEYbvh_I7TrEEiFgsrp-ui1pMfvv6mq_yPvYefvH4mpulDoVD87B4aQb65X97Y4bkfVjftIgiUgHdqvHDT4XVdrzClBqbDeb0JHEWFLJ_-n-ESE9Mzt_QFdeDIHqLRaL6uUClp5hpc9rOr5fgOu4Bx2hUpnH8-GSYcsMdplHCICcdRIFqoBFxJMA_ZyLLyTtzkHzO9rsyAP7IEv_8ryYTu2jjHqtiCbwz6l-98dpAVqIaYaXBStEBBgfv7Sk7Ig_fz07MvfZ5NCI4S-J3W0voyIUDvfySDlsrbrmkUfGx8L_duyMUT8hhbUyj2jMBVPiX3XLNNtkIgQYOZXm6TRwOVyWfkT4RMAQSNkOmiphEy7SHTAWR63VAPmXrINECm7YIOINMOsp-7h0w9ZAqQn5PLo_nFwTELi26wn0kGL5x9npWcO3TEXa5MmhtTV3VqsrSQiS2lstZZiFstrg-ieJ3yyiVGQeArciHgyAsyaRaNe0loWXFRlKquZApRbiGtc3BK6pKyyA2M7RAW76v2pQGhHrns7uJSbxDeIdN48zWevtRRcxuoaaCmk1QjNY3UXt1x9tfk4fpp3yWT9mbl9sDhbO2b8Ez9BfL9flM
linkProvider Library Specific Holdings
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.title=Recent+Trends+in+Image+Processing+and+Pattern+Recognition&rft.atitle=Skewness+and+Kurtosis+of+Apparent+Diffusion+Coefficient+in+Human+Brain+Lesions+to+Distinguish+Benign+and+Malignant+Using+MRI&rft.date=2019-01-01&rft.pub=Springer&rft.isbn=9789811391835&rft.volume=1036&rft_id=info:doi/10.1007%2F978-981-13-9184-2_17&rft.externalDBID=207&rft.externalDocID=EBC5919655_218_207
thumbnail_s http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Febookcentral.proquest.com%2Fcovers%2F5919655-l.jpg