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...
Saved in:
Published in | Diagnostics (Basel) Vol. 11; no. 12; p. 2252 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
01.12.2021
MDPI |
Subjects | |
Online Access | Get 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 |