Assessment of Response to Chemotherapy in Pancreatic Cancer with Liver Metastasis: CT Texture as a Predictive Biomarker

In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer...

Full description

Saved in:
Bibliographic Details
Published inDiagnostics (Basel) Vol. 11; no. 12; p. 2252
Main Authors Cheng, Sihang, Jin, Zhengyu, Xue, Huadan
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.12.2021
MDPI
Subjects
Online AccessGet full text

Cover

Loading…
Abstract In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response (p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP (p = 0.016) and confirmed in the validation cohort (p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.
AbstractList In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response ( < 0.05 vs. = 0.398, = 0.142, and = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP ( = 0.016) and confirmed in the validation cohort ( = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.
In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response (p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP (p = 0.016) and confirmed in the validation cohort (p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.
In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response ( p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP ( p = 0.016) and confirmed in the validation cohort ( p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.
In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response (p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP (p = 0.016) and confirmed in the validation cohort (p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine if texture parameters correlate with measured time to progression (TTP). This retrospective study included 110 patients with pancreatic cancer with liver metastasis, and mean, entropy, kurtosis, skewness, mean of positive pixels, and standard deviation (SD) values were extracted during texture analysis. Response assessment was also obtained by using RECIST 1.1, Choi and modified Choi criteria, respectively. The correlation of texture parameters and existing assessment criteria with TTP were evaluated using Kaplan-Meier and Cox regression analyses in the training cohort. Kaplan-Meier curves of the proportion of patients without disease progression were significantly different for several texture parameters, and were better than those for RECIST 1.1-, Choi-, and modified Choi-defined response (p < 0.05 vs. p = 0.398, p = 0.142, and p = 0.536, respectively). Cox regression analysis showed that percentage change in SD was an independent predictor of TTP (p = 0.016) and confirmed in the validation cohort (p = 0.019). In conclusion, CT texture parameters have the potential to become predictive imaging biomarkers for response evaluation in pancreatic cancer with liver metastasis.
Author Cheng, Sihang
Xue, Huadan
Jin, Zhengyu
AuthorAffiliation Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China; chengsihangscu@foxmail.com (S.C.); zhengyu_jin@163.com (Z.J.)
AuthorAffiliation_xml – name: Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China; chengsihangscu@foxmail.com (S.C.); zhengyu_jin@163.com (Z.J.)
Author_xml – sequence: 1
  givenname: Sihang
  surname: Cheng
  fullname: Cheng, Sihang
– sequence: 2
  givenname: Zhengyu
  surname: Jin
  fullname: Jin, Zhengyu
– sequence: 3
  givenname: Huadan
  surname: Xue
  fullname: Xue, Huadan
BackLink https://www.ncbi.nlm.nih.gov/pubmed/34943489$$D View this record in MEDLINE/PubMed
BookMark eNp9kltrFDEUxwep2Iv9BIIEfPFlNbeZTHwQ6lK1sGKR9TmcSc7sZp2drEm2td_erFtLW8QQyCH5nf-55bg6GMOIVfWC0TdCaPrWeViMIWVvE2OMc17zJ9URp6qeSMnag3v2YXWa0oqWpZloef2sOhRSSyFbfVRdn6WEKa1xzCT05BumTRgTkhzIdInrkJcYYXND_EguYbQRoYQk02JiJNc-L8nMXxXzC2ZIZfv0jkznZI6_8jYigUSAXEZ03ubCkQ8-rCH-wPi8etrDkPD09jypvn88n08_T2ZfP11Mz2YTK7XOE9vXXaupal3TOCs6q3vUHHvbSyd1ozraAOMOKW_qVmDNUDW1dMxy3gIoECfVxV7XBViZTfQl_I0J4M2fixAXBmIpaUDjlO0brahjLciuB9AMeecQGwWd6rFovd9rbbbdGp0tPYswPBB9-DL6pVmEK9MqSmvRFIHXtwIx_Nxiymbtk8VhgBHDNhneMMllreQOffUIXYVtHEurdhRXtRZSFOrl_YzuUvk73wKIPWBjSClif4cwanYfyfzjIxUv_cjL-lwGH3Zl-eG_vr8B_4LUOw
CitedBy_id crossref_primary_10_3390_diagnostics13010149
Cites_doi 10.1007/s00261-014-0318-3
10.1102/1470-7330.2013.9045
10.1148/rg.335125214
10.1200/JCO.2006.07.3411
10.1016/j.ejrad.2016.08.014
10.1007/s00330-018-5933-x
10.1148/radiol.11110264
10.1016/j.ecl.2010.09.006
10.2214/AJR.09.2941
10.1158/1078-0432.CCR-07-4534
10.1038/sj.bjc.6605567
10.1056/NEJMoa1011923
10.1102/1470-7330.2013.0015
10.1177/2050640615601603
10.2214/AJR.19.21152
10.1200/JCO.2016.67.1412
10.1056/NEJM200104053441404
10.1007/978-1-4614-5915-6_2
10.1634/theoncologist.2013-0114
10.1016/j.ejca.2008.10.026
10.1109/10.900272
10.1097/RCT.0000000000000239
10.1148/rg.2017170056
10.1148/radiol.12112428
10.1016/S0140-6736(16)00141-0
10.4161/cbt.9.1.10340
10.1016/j.ejrad.2019.02.009
10.1245/s10434-020-09581-5
10.2105/AJPH.86.5.726
10.1016/j.ejrad.2018.02.031
10.3322/caac.21551
10.1186/s12885-017-3150-7
10.1200/JCO.2006.07.3049
10.1056/NEJMoa1304369
10.2214/AJR.09.3456
ContentType Journal Article
Copyright 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2021 by the authors. 2021
Copyright_xml – notice: 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2021 by the authors. 2021
DBID AAYXX
CITATION
NPM
3V.
7XB
8FK
8G5
ABUWG
AFKRA
AZQEC
BENPR
CCPQU
DWQXO
GNUQQ
GUQSH
M2O
MBDVC
PHGZM
PHGZT
PIMPY
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
Q9U
7X8
5PM
DOA
DOI 10.3390/diagnostics11122252
DatabaseName CrossRef
PubMed
ProQuest Central (Corporate)
ProQuest Central (purchase pre-March 2016)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Research Library
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest Central
ProQuest One Community College
ProQuest Central
ProQuest Central Student
Research Library Prep
Research Library
Research Library (Corporate)
ProQuest Central Premium
ProQuest One Academic
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest Central Basic
MEDLINE - Academic
PubMed Central (Full Participant titles)
Directory of Open Access Journals (DOAJ)
DatabaseTitle CrossRef
PubMed
Publicly Available Content Database
Research Library Prep
ProQuest Central Student
ProQuest One Academic Middle East (New)
ProQuest Central Basic
ProQuest Central Essentials
ProQuest One Academic Eastern Edition
ProQuest Central (Alumni Edition)
ProQuest One Community College
Research Library (Alumni Edition)
ProQuest Central China
ProQuest Central
ProQuest One Academic UKI Edition
ProQuest Central Korea
ProQuest Research Library
ProQuest Central (New)
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList PubMed
CrossRef


Publicly Available Content Database
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ (Directory of Open Access Journals)
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 3
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 2075-4418
ExternalDocumentID oai_doaj_org_article_d7cf6970d18a4bfaa91e2bdee67ab7fe
PMC8700536
34943489
10_3390_diagnostics11122252
Genre Journal Article
GeographicLocations United States--US
GeographicLocations_xml – name: United States--US
GroupedDBID 53G
5VS
8G5
AADQD
AAFWJ
AAYXX
ABDBF
ABUWG
ACUHS
ADBBV
AFKRA
AFPKN
AFZYC
ALMA_UNASSIGNED_HOLDINGS
AOIJS
AZQEC
BCNDV
BENPR
BPHCQ
CCPQU
CITATION
DWQXO
EBD
ESX
GNUQQ
GROUPED_DOAJ
GUQSH
HYE
IAO
IHR
ITC
KQ8
M2O
M48
MODMG
M~E
OK1
PGMZT
PHGZM
PHGZT
PIMPY
PQQKQ
PROAC
RPM
3V.
NPM
7XB
8FK
MBDVC
PKEHL
PQEST
PQUKI
PRINS
Q9U
7X8
5PM
PUEGO
ID FETCH-LOGICAL-c499t-cf5b89078d66dc3bc9fe92efcf4d4967b06a12de026583e51e7654d1c228aa7a3
IEDL.DBID M48
ISSN 2075-4418
IngestDate Wed Aug 27 01:29:32 EDT 2025
Thu Aug 21 18:43:16 EDT 2025
Fri Jul 11 00:29:39 EDT 2025
Sun Jun 29 12:35:10 EDT 2025
Thu Jan 02 22:56:02 EST 2025
Tue Jul 01 02:35:53 EDT 2025
Thu Apr 24 23:00:21 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 12
Keywords liver metastasis
pancreatic cancer
chemotherapy
response
texture analysis
Language English
License https://creativecommons.org/licenses/by/4.0
Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c499t-cf5b89078d66dc3bc9fe92efcf4d4967b06a12de026583e51e7654d1c228aa7a3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink http://journals.scholarsportal.info/openUrl.xqy?doi=10.3390/diagnostics11122252
PMID 34943489
PQID 2612759343
PQPubID 2032410
ParticipantIDs doaj_primary_oai_doaj_org_article_d7cf6970d18a4bfaa91e2bdee67ab7fe
pubmedcentral_primary_oai_pubmedcentral_nih_gov_8700536
proquest_miscellaneous_2614245746
proquest_journals_2612759343
pubmed_primary_34943489
crossref_primary_10_3390_diagnostics11122252
crossref_citationtrail_10_3390_diagnostics11122252
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2021-12-01
PublicationDateYYYYMMDD 2021-12-01
PublicationDate_xml – month: 12
  year: 2021
  text: 2021-12-01
  day: 01
PublicationDecade 2020
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
– name: Basel
PublicationTitle Diagnostics (Basel)
PublicationTitleAlternate Diagnostics (Basel)
PublicationYear 2021
Publisher MDPI AG
MDPI
Publisher_xml – name: MDPI AG
– name: MDPI
References Miles (ref_34) 2013; 13
Ahn (ref_15) 2016; 85
Borhani (ref_17) 2020; 214
Hayano (ref_31) 2015; 39
Lubner (ref_13) 2017; 37
Kretowski (ref_35) 2001; 48
Nakanishi (ref_36) 2021; 28
Goh (ref_10) 2011; 261
Tian (ref_18) 2014; 40
Tirkes (ref_22) 2013; 33
Durot (ref_32) 2019; 29
Beckers (ref_16) 2018; 102
Smith (ref_28) 2010; 194
Cheng (ref_14) 2019; 113
Rao (ref_11) 2016; 4
Ronot (ref_23) 2014; 19
Ganeshan (ref_12) 2013; 13
Benjamin (ref_26) 2007; 25
Aickin (ref_19) 1996; 86
Sohal (ref_4) 2016; 34
Joensuu (ref_20) 2001; 344
ref_24
Nathan (ref_9) 2010; 9
Smith (ref_27) 2010; 194
Meijerink (ref_8) 2010; 102
Kamisawa (ref_2) 2016; 388
Choi (ref_25) 2007; 25
Ervin (ref_6) 2013; 369
ref_29
Conroy (ref_5) 2011; 364
Ganeshan (ref_30) 2013; 266
Taylor (ref_33) 2008; 14
Siegel (ref_1) 2019; 69
Faivre (ref_21) 2010; 39
Hand (ref_3) 2019; 37
Eisenhauer (ref_7) 2009; 45
References_xml – volume: 40
  start-page: 1705
  year: 2014
  ident: ref_18
  article-title: Response assessment to neoadjuvant therapy in soft tissue sarcomas: Using CT texture analysis in comparison to tumor size, density, and perfusion
  publication-title: Abdom. Imaging
  doi: 10.1007/s00261-014-0318-3
– volume: 13
  start-page: 400
  year: 2013
  ident: ref_34
  article-title: CT texture analysis using the filtration-histogram method: What do the measurements mean?
  publication-title: Cancer Imaging
  doi: 10.1102/1470-7330.2013.9045
– volume: 33
  start-page: 1323
  year: 2013
  ident: ref_22
  article-title: Response Criteria in Oncologic Imaging: Review of Traditional and New Criteria
  publication-title: Radiographics
  doi: 10.1148/rg.335125214
– volume: 25
  start-page: 1760
  year: 2007
  ident: ref_26
  article-title: We Should Desist Using RECIST, at Least in GIST
  publication-title: J. Clin. Oncol.
  doi: 10.1200/JCO.2006.07.3411
– volume: 85
  start-page: 1867
  year: 2016
  ident: ref_15
  article-title: Prediction of the therapeutic response after FOLFOX and FOLFIRI treatment for patients with liver metastasis from colorectal cancer using computerized CT texture analysis
  publication-title: Eur. J. Radiol.
  doi: 10.1016/j.ejrad.2016.08.014
– volume: 29
  start-page: 3183
  year: 2019
  ident: ref_32
  article-title: Metastatic melanoma: Pretreatment contrast-enhanced CT texture parameters as predictive biomarkers of survival in patients treated with pembrolizumab
  publication-title: Eur. Radiol.
  doi: 10.1007/s00330-018-5933-x
– volume: 261
  start-page: 165
  year: 2011
  ident: ref_10
  article-title: Assessment of Response to Tyrosine Kinase Inhibitors in Metastatic Renal Cell Cancer: CT Texture as a Predictive Biomarker
  publication-title: Radiology
  doi: 10.1148/radiol.11110264
– volume: 39
  start-page: 811
  year: 2010
  ident: ref_21
  article-title: Novel Anticancer Agents in Clinical Trials for Well-Differentiated Neuroendocrine Tumors
  publication-title: Endocrinol. Metab. Clin. N. Am.
  doi: 10.1016/j.ecl.2010.09.006
– volume: 194
  start-page: 157
  year: 2010
  ident: ref_27
  article-title: Assessing Tumor Response and Detecting Recurrence in Metastatic Renal Cell Carcinoma on Targeted Therapy: Importance of Size and Attenuation on Contrast-Enhanced CT
  publication-title: Am. J. Roentgenol.
  doi: 10.2214/AJR.09.2941
– volume: 14
  start-page: 5977
  year: 2008
  ident: ref_33
  article-title: Validation of Biomarker-Based Risk Prediction Models
  publication-title: Clin. Cancer Res.
  doi: 10.1158/1078-0432.CCR-07-4534
– volume: 102
  start-page: 803
  year: 2010
  ident: ref_8
  article-title: Choi response criteria for early prediction of clinical outcome in patients with metastatic renal cell cancer treated with sunitinib
  publication-title: Br. J. Cancer
  doi: 10.1038/sj.bjc.6605567
– volume: 364
  start-page: 1817
  year: 2011
  ident: ref_5
  article-title: FOLFIRINOX versus Gemcitabine for Metastatic Pancreatic Cancer
  publication-title: N. Engl. J. Med.
  doi: 10.1056/NEJMoa1011923
– volume: 13
  start-page: 140
  year: 2013
  ident: ref_12
  article-title: Quantifying tumour heterogeneity with CT
  publication-title: Cancer Imaging
  doi: 10.1102/1470-7330.2013.0015
– volume: 4
  start-page: 257
  year: 2016
  ident: ref_11
  article-title: CT texture analysis in colorectal liver metastases: A better way than size and volume measurements to assess response to chemotherapy?
  publication-title: United Eur. Gastroenterol. J.
  doi: 10.1177/2050640615601603
– volume: 214
  start-page: 362
  year: 2020
  ident: ref_17
  article-title: Assessment of Response to Neoadjuvant Therapy Using CT Texture Analysis in Patients with Resectable and Borderline Resectable Pancreatic Ductal Adenocarcinoma
  publication-title: Am. J. Roentgenol.
  doi: 10.2214/AJR.19.21152
– volume: 34
  start-page: 2784
  year: 2016
  ident: ref_4
  article-title: Metastatic Pancreatic Cancer: American Society of Clinical Oncology Clinical Practice Guideline
  publication-title: J. Clin. Oncol.
  doi: 10.1200/JCO.2016.67.1412
– volume: 344
  start-page: 1052
  year: 2001
  ident: ref_20
  article-title: Effect of the Tyrosine Kinase Inhibitor STI571 in a Patient with a Metastatic Gastrointestinal Stromal Tumor
  publication-title: N. Engl. J. Med.
  doi: 10.1056/NEJM200104053441404
– ident: ref_29
  doi: 10.1007/978-1-4614-5915-6_2
– volume: 37
  start-page: 319
  year: 2019
  ident: ref_3
  article-title: Pancreatic cancer
  publication-title: Surgery
– volume: 19
  start-page: 394
  year: 2014
  ident: ref_23
  article-title: Alternative Response Criteria (Choi, European Association for the Study of the Liver, and Modified Response Evaluation Criteria in Solid Tumors [RECIST]) Versus RECIST 1.1 in Patients with Advanced Hepatocellular Carcinoma Treated with Sorafenib
  publication-title: Oncologyst
  doi: 10.1634/theoncologist.2013-0114
– volume: 45
  start-page: 228
  year: 2009
  ident: ref_7
  article-title: New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
  publication-title: Eur. J. Cancer
  doi: 10.1016/j.ejca.2008.10.026
– volume: 48
  start-page: 120
  year: 2001
  ident: ref_35
  article-title: Toward a better understanding of texture in vascular CT scan simulated images
  publication-title: IEEE Trans. Biomed. Eng.
  doi: 10.1109/10.900272
– volume: 39
  start-page: 607
  year: 2015
  ident: ref_31
  article-title: Texture Analysis of Non–Contrast-Enhanced Computed Tomography for Assessing Angiogenesis and Survival of Soft Tissue Sarcoma
  publication-title: J. Comput. Assist. Tomogr.
  doi: 10.1097/RCT.0000000000000239
– volume: 37
  start-page: 1483
  year: 2017
  ident: ref_13
  article-title: CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges
  publication-title: Radiographics
  doi: 10.1148/rg.2017170056
– volume: 266
  start-page: 326
  year: 2013
  ident: ref_30
  article-title: Non–Small Cell Lung Cancer: Histopathologic Correlates for Texture Parameters at CT
  publication-title: Radiology
  doi: 10.1148/radiol.12112428
– volume: 388
  start-page: 73
  year: 2016
  ident: ref_2
  article-title: Pancreatic cancer
  publication-title: Lancet
  doi: 10.1016/S0140-6736(16)00141-0
– volume: 9
  start-page: 15
  year: 2010
  ident: ref_9
  article-title: CT response assessment combining reduction in both size and arterial phase density correlates with time to progression in metastatic renal cancer patients treated with targeted therapies
  publication-title: Cancer Biol. Ther.
  doi: 10.4161/cbt.9.1.10340
– volume: 113
  start-page: 188
  year: 2019
  ident: ref_14
  article-title: Unresectable pancreatic ductal adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting outcomes of patients treated with chemotherapy
  publication-title: Eur. J. Radiol.
  doi: 10.1016/j.ejrad.2019.02.009
– volume: 28
  start-page: 2975
  year: 2021
  ident: ref_36
  article-title: Radiomics Texture Analysis for the Identification of Colorectal Liver Metastases Sensitive to First-Line Oxaliplatin-Based Chemotherapy
  publication-title: Ann. Surg. Oncol.
  doi: 10.1245/s10434-020-09581-5
– volume: 86
  start-page: 726
  year: 1996
  ident: ref_19
  article-title: Adjusting for multiple testing when reporting research results: The Bonferroni vs. Holm methods
  publication-title: Am. J. Public Health
  doi: 10.2105/AJPH.86.5.726
– volume: 102
  start-page: 15
  year: 2018
  ident: ref_16
  article-title: CT texture analysis in colorectal liver metastases and the surrounding liver parenchyma and its potential as an imaging biomarker of disease aggressiveness, response and survival
  publication-title: Eur. J. Radiol.
  doi: 10.1016/j.ejrad.2018.02.031
– volume: 69
  start-page: 7
  year: 2019
  ident: ref_1
  article-title: Cancer statistics, 2019
  publication-title: CA Cancer J. Clin.
  doi: 10.3322/caac.21551
– ident: ref_24
  doi: 10.1186/s12885-017-3150-7
– volume: 25
  start-page: 1753
  year: 2007
  ident: ref_25
  article-title: Correlation of Computed Tomography and Positron Emission Tomography in Patients with Metastatic Gastrointestinal Stromal Tumor Treated at a Single Institution with Imatinib Mesylate: Proposal of New Computed Tomography Response Criteria
  publication-title: J. Clin. Oncol.
  doi: 10.1200/JCO.2006.07.3049
– volume: 369
  start-page: 1691
  year: 2013
  ident: ref_6
  article-title: Increased Survival in Pancreatic Cancer with nab-Paclitaxel plus Gemcitabine
  publication-title: N. Engl. J. Med.
  doi: 10.1056/NEJMoa1304369
– volume: 194
  start-page: 1470
  year: 2010
  ident: ref_28
  article-title: Morphology, Attenuation, Size, and Structure (MASS) Criteria: Assessing Response and Predicting Clinical Outcome in Metastatic Renal Cell Carcinoma on Antiangiogenic Targeted Therapy
  publication-title: Am. J. Roentgenol.
  doi: 10.2214/AJR.09.3456
SSID ssj0000913825
Score 2.173606
Snippet In this paper, we assess changes in CT texture of metastatic liver lesions after treatment with chemotherapy in patients with pancreatic cancer and determine...
SourceID doaj
pubmedcentral
proquest
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 2252
SubjectTerms Abdomen
Cancer therapies
Chemotherapy
Liver
liver metastasis
Medical imaging
Medical prognosis
Metastasis
Pancreatic cancer
response
Statistical analysis
texture analysis
Thorax
SummonAdditionalLinks – databaseName: Directory of Open Access Journals (DOAJ)
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1bi9QwFA6yD-KLeLe6SgQfLTvNtfFtd3BZxJFFZmHfSi4nOKCtdDqI_96ctFtmZNEXX5uUpjknJ-drvn6HkLeSQ-AuJqSqQJci1L40SrISfHKh4OUi5hpLq8_q4kp8vJbXe6W-kBM2ygOPE3cStI_K6EWoaitctNZUwFwAUNo6HQGjb9rz9sBUjsEGtfXkKDPEE64_CSNzDbWP0_JGlMMOtqKs2H9bmvknW3Jv-zl_QO5PeSM9Hcf7kNyB9hG5u5pOxh-Tn6ezxCbtIv0yUl-BDh1FTYDpP6tfdNPSy2TonCp6ukSb9xQ_xtJPyNCgKxhsShi3m-17ulzTdYrdux6o3VJLL3t8HMZHerbpviOxp39Crs4_rJcX5VRUofQJ3Aylj9LVCRHXQangufMmgmEQfRRBGKXdQtmKBUjYTNYcZAVaSREqz1htrbb8KTlquxaeE2qCYTFwuwgOhJe2libyYCXzllcVlwVhN_Pb-ElxHAtffGsS8kCjNLcYpSDv5pt-jIIbf-9-hoabu6Jadr6QfKiZfKj5lw8V5PjG7M20hLcNaqtpabjgBXkzN6fFhycqtoVul_vgybEWqiDPRi-ZR4K6P1zUpiD6wH8OhnrY0m6-ZoHvFENTbFQv_se7vST3GNJwMgPnmBwN_Q5epTxqcK_zkvkNeBYjOw
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: ProQuest Central
  dbid: BENPR
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1ba9RAFB50C-KLeDdaZQQfDd3MfXyR7tJSxC1L2ULfwmQudkGTmuwi_nvnJLPRldLXzIQMOZecy5fvIPSBU-9oFWKmKrzMmVM214KT3NuoQs7yaehnLC3Oxdkl-3LFr1LBrUuwyp1P7B21ayzUyI-A6kpyTRn9fPMzh6lR0F1NIzTuo4PogpWaoIPZyfnyYqyyAOtlzIEGuiEa8_sjNyDYgAM5mjlkO2Tvk9Qz998Wbv6PmvznM3T6GD1K8SM-HgT-BN3z9VP0YJE65M_Qr-ORahM3AV8MEFiPNw0GboD0v9VvvK7xMgq8DxktnoPsWwxFWfwVkBp44TcmBo7duvuE5yu8ij5823psOmzwsoXHgZ_Es3XzAwA-7XN0eXqymp_labhCbmOSs8lt4JWKmbFyQjhLK6uD18QHG5hjWshqKkxBnI85GlfU88JLwZkrLCHKGGnoCzSpm9q_Qlg7TYKjZuoqzyw3iutAneHEGloUlGeI7N5vaRPzOAzA-F7GDASEUt4ilAx9HG-6GYg37t4-A8GNW4E1u7_QtN_KZISlkzYILaeuUIZVwRhdeFI574U0lQw-Q4c7sZfJlLvyr-Jl6P24HI0QOium9s223wMdZMlEhl4OWjKeBPh_KFM6Q3JPf_aOur9Sr697ou_oS6OPFK_vPtYb9JAA0KbH2Byiyabd-rcxUtpU75I5_AE1UBm7
  priority: 102
  providerName: ProQuest
Title Assessment of Response to Chemotherapy in Pancreatic Cancer with Liver Metastasis: CT Texture as a Predictive Biomarker
URI https://www.ncbi.nlm.nih.gov/pubmed/34943489
https://www.proquest.com/docview/2612759343
https://www.proquest.com/docview/2614245746
https://pubmed.ncbi.nlm.nih.gov/PMC8700536
https://doaj.org/article/d7cf6970d18a4bfaa91e2bdee67ab7fe
Volume 11
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1ba9swFBalhdKX0d3ddUGDPc5bbN2swRhNaCljKaEk0Dcj67IFOntzHLb---nIF5qR7WGvloSF9Z2j80nH30HoNSPWkMJ5psqtiKnJdCw5S2OrPYSMZmMXaizNrvjlkn66YTd7qK-K2n3A9U5qB_WklvXt218_7j56g_8AjNNT9nemTUoDWWNvuUBgvE8-8FuTgJIGsy7eD65ZguQea9WH_jb2CB2CZguhUPr93mYVNP13BaJ_5lPe26AujtGDLrLEZy0UHqI9Wz5Ch7Pu7vwx-nk2iHDiyuHrNjnW4qbCoBrQ_Yl1h1clnnsohGBS4ymgosZwXIs_Qw4HntlG-ZByvVq_x9MFXnjvvqktVmus8LyG14EHxZNV9Q1Sf-onaHlxvphexl3ZhVh7-tPE2rEi85w5M5wbTQotnZWpddpRQyUXxZirJDXWszeWEcsSKzijJtFpmiklFHmK9suqtM8RlkamzhA1NoWlmqmMSUeMYqlWJEkIi1Daf99cd5rkUBrjNvfcBNYn37E-EXozDPreSnL8u_sEFm7oCnra4UFVf8k788yN0I5LMTZJpmjhlJKJTQtjLReqEM5G6LRf9rzHaA7qa4JJQkmEXg3N3jzhzkWVttqEPnC3LCiP0LMWJcNMepRFSGzhZ2uq2y3l6muQAPde1ntPfvLfI1-goxSyc0Jizinab-qNfenDq6YYoYPJ-dX8ehSOJ0bBgH4Dd54tyw
linkProvider Scholars Portal
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELdGJ8FeEN8EBhgJ3oiW2LEdIyG0lk0da6tq6qS9BccfrBIkI2017Z_ib8SXpIGiaW97jZ3E8v18vvOdf4fQO0atobnzniq3IkxMqkPJGQmt9hAymkWurrE0nvDhafL1jJ1tod_ruzCQVrnWibWiNqWGM_I9oLoSTNKEfr74FULVKIiurktoNLA4tleX3mVbfDr64uX7npDDg9lgGLZVBULtrftlqB3LU-8SpoZzo2mupbOSWKddYhLJRR5xFRNjvXPCUmpZbAVniYk1IalSQlH_3TtoO6E8Ij203T-YTE-6Ux1g2fQ-V0NvRKmM9kyTMQecy16tgHdFNrbAulLAdebt_1ma_2x7hw_Q_dZexfsNwB6iLVs8QnfHbUT-Mbrc76g9cenwSZNya_GyxMBF0N7vusLzAk89wGoTVeMBYK3CcAiMR5AZgsd2qbyhupgvPuLBDM_8nrGqLFYLrPC0gt-BXsb9efkTEoqqJ-j0Vqb9KeoVZWGfIyyNJM5QFZncJpqplElHjWJEKxrHlAWIrOc30y3TORTc-JF5jweEkl0jlAB96F66aIg-bu7eB8F1XYGlu35QVt-zdtFnRmjHpYhMnKokd0rJ2JLcWMuFyoWzAdpdiz1rVcci-wv0AL3tmv2ih0iOKmy5qvtAxFokPEDPGpR0IwG-IZqkMkBiAz8bQ91sKebnNbG4191eJ_MXNw_rDbo3nI1H2ehocvwS7RBI8qnze3ZRb1mt7CtvpS3z1-3SwOjbba_GP95ZV1I
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1bb9MwFLZGJ028IO4LDDASvBG1sWM7RkJo7VZtbK2qqZP2FhxfoBIkI2017a_x6_DJDYqmve01dhIr5_jzOfaX7yD0jlFraOZ8psqtCGOT6FByRkKrvQsZzQauqrE0mfKj8_jLBbvYQr_bf2GAVtliYgXUptCwR94HqSvBJI1p3zW0iNnB-PPlrxAqSMFJa1tOo3aRE3t95dO35afjA2_r94SMD-ejo7CpMBBqH-mvQu1Ylvj0MDGcG00zLZ2VxDrtYhNLLrIBVxEx1icqLKGWRVZwFptIE5IoJRT1z72HtgVkRT20PTyczs66HR5Q3PT5Vy11RKkc9E3NngP9ZQ8xkGmRjeWwqhpwU6j7P2PznyVw_BA9aGJXvF872yO0ZfPHaGfSnM4_QVf7ncwnLhw-q-m3Fq8KDLoEzb9e13iR45l3tipc1XgEfldi2BDGp8ASwRO7Uj5oXS6WH_FojufeCOvSYrXECs9KeB1gNB4uip9ALiqfovM7-ezPUC8vcruLsDSSOEPVwGQ21kwlTDpqFCNa0SiiLECk_b6pblTPofjGj9RnP2CU9AajBOhDd9NlLfpxe_chGK7rCord1YWi_JY2AJAaoR2XYmCiRMWZU0pGlmTGWi5UJpwN0F5r9rSBkWX61-kD9LZr9gAApzoqt8W66gOn1yLmAXpee0k3EtAeonEiAyQ2_GdjqJst-eJ7JTLucdzjM39x-7DeoB0_C9PT4-nJS3SfAN-novrsod6qXNtXPmBbZa-bmYHR17uejH8AcmFbhw
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%3Ajournal&rft.genre=article&rft.atitle=Assessment+of+Response+to+Chemotherapy+in+Pancreatic+Cancer+with+Liver+Metastasis%3A+CT+Texture+as+a+Predictive+Biomarker&rft.jtitle=Diagnostics+%28Basel%29&rft.au=Cheng%2C+Sihang&rft.au=Jin%2C+Zhengyu&rft.au=Xue%2C+Huadan&rft.date=2021-12-01&rft.pub=MDPI&rft.eissn=2075-4418&rft.volume=11&rft.issue=12&rft_id=info:doi/10.3390%2Fdiagnostics11122252&rft_id=info%3Apmid%2F34943489&rft.externalDocID=PMC8700536
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2075-4418&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2075-4418&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2075-4418&client=summon