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Conference Paper: Primary tumour and lymph node radiomics assessment in PET-CT in non-metastatic nasopharyngeal carcinoma patients

TitlePrimary tumour and lymph node radiomics assessment in PET-CT in non-metastatic nasopharyngeal carcinoma patients
Authors
Issue Date2020
PublisherEuropean Society of Radiology / SpringerOpen. The Book of Abstracts is located at https://doi.org/10.1186/s13244-020-00851-0. The Journal's web site is located at http://www.springer.com/medicine/radiology/journal/13244
Citation
European Congress of Radiology (ECR), Vienna, Austria, 15-19 July 2020. In Insights into Imaging, 2020, v. 11 n. Suppl. 1, p. 133, abstract no. RPS 108-2 How to Cite?
AbstractPurpose: To evaluate the prognostic value of radiomic features extracted from pre-treatment PET-CT images of the primary tumours (PT) and lymph nodes (LNs) in locally advanced nasopharyngeal carcinoma (NPC) patients. Methods and materials: A total of 145 consecutive patients (median age 48 years, 75.2% male) with newly diagnosed NPC were included. Radiomics analysis was performed on 118 PT and 66 LN images. Conventional PET parameters (SUVmax, SUVmean, and TLG), shape-based features, and 6 robust texture features were extracted. This data was used to analyse the correlation with 3-year overall survival (OS) and progression-free survival (PRFS) based on a Kaplan-Meier log-rank test. Results: One PET radiomics feature (LN sphericity) was significantly predictive of OS (p=0.024) and PRFS (p=0.002). Independent CT predictive radiomic features were PT GLRM LRE (p=0.011), LN sphericity (p=0.011), and compactness (p=0.042) for OS, and PT GLRM LRE (p = 0.039) and LN sphericity (p = 0.008) for PRFS. Conclusion: CT shape-based features and texture features extracted from primary tumours and LNs provide significant predictive value for survival in patients with NPC. LN PET radiomics information was significantly predictive for survival and performed better than primary features. The unity of LN radiomics can be further validated by prospective randomised trials, considering their potential in predicting clinical outcomes of tumour patients.
DescriptionHead and Neck - RPS 108: Advanced imaging in head and neck tumours - no. RPS 108-2
Congress was originally planned for 11-15 March 2020 could not be held, due to Convid-19. The ECR 2020 Online Congress Programme taking place between 15-19 July 2020
Persistent Identifierhttp://hdl.handle.net/10722/283295
ISSN
2020 Impact Factor: 5.231
2020 SCImago Journal Rankings: 1.405

 

DC FieldValueLanguage
dc.contributor.authorXia, C-
dc.contributor.authorChen, Y-
dc.contributor.authorVardhanabhuti, V-
dc.date.accessioned2020-06-22T02:54:40Z-
dc.date.available2020-06-22T02:54:40Z-
dc.date.issued2020-
dc.identifier.citationEuropean Congress of Radiology (ECR), Vienna, Austria, 15-19 July 2020. In Insights into Imaging, 2020, v. 11 n. Suppl. 1, p. 133, abstract no. RPS 108-2-
dc.identifier.issn1869-4101-
dc.identifier.urihttp://hdl.handle.net/10722/283295-
dc.descriptionHead and Neck - RPS 108: Advanced imaging in head and neck tumours - no. RPS 108-2-
dc.descriptionCongress was originally planned for 11-15 March 2020 could not be held, due to Convid-19. The ECR 2020 Online Congress Programme taking place between 15-19 July 2020-
dc.description.abstractPurpose: To evaluate the prognostic value of radiomic features extracted from pre-treatment PET-CT images of the primary tumours (PT) and lymph nodes (LNs) in locally advanced nasopharyngeal carcinoma (NPC) patients. Methods and materials: A total of 145 consecutive patients (median age 48 years, 75.2% male) with newly diagnosed NPC were included. Radiomics analysis was performed on 118 PT and 66 LN images. Conventional PET parameters (SUVmax, SUVmean, and TLG), shape-based features, and 6 robust texture features were extracted. This data was used to analyse the correlation with 3-year overall survival (OS) and progression-free survival (PRFS) based on a Kaplan-Meier log-rank test. Results: One PET radiomics feature (LN sphericity) was significantly predictive of OS (p=0.024) and PRFS (p=0.002). Independent CT predictive radiomic features were PT GLRM LRE (p=0.011), LN sphericity (p=0.011), and compactness (p=0.042) for OS, and PT GLRM LRE (p = 0.039) and LN sphericity (p = 0.008) for PRFS. Conclusion: CT shape-based features and texture features extracted from primary tumours and LNs provide significant predictive value for survival in patients with NPC. LN PET radiomics information was significantly predictive for survival and performed better than primary features. The unity of LN radiomics can be further validated by prospective randomised trials, considering their potential in predicting clinical outcomes of tumour patients.-
dc.languageeng-
dc.publisherEuropean Society of Radiology / SpringerOpen. The Book of Abstracts is located at https://doi.org/10.1186/s13244-020-00851-0. The Journal's web site is located at http://www.springer.com/medicine/radiology/journal/13244-
dc.relation.ispartofEuropean Congress of Radiology (ECR), 2000-
dc.relation.ispartofInsights into Imaging-
dc.titlePrimary tumour and lymph node radiomics assessment in PET-CT in non-metastatic nasopharyngeal carcinoma patients-
dc.typeConference_Paper-
dc.identifier.emailVardhanabhuti, V: varv@hku.hk-
dc.identifier.authorityVardhanabhuti, V=rp01900-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.hkuros310384-
dc.identifier.volume11-
dc.identifier.issueSuppl. 1-
dc.identifier.spage133-
dc.identifier.epage133-
dc.publisher.placeGermany-
dc.identifier.issnl1869-4101-

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