Novel Non-Invasive Radiomic Signature on CT Scans Predicts Response to Platinum-Based Chemotherapy and Is Prognostic of Overall Survival in Small Cell Lung Cancer.
chemotherapy
computed tomography
overall survival
progression-free survival
radiomics
small cell lung cancer (SCLC)
Journal
Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867
Informations de publication
Date de publication:
2021
2021
Historique:
received:
20
07
2021
accepted:
29
09
2021
entrez:
8
11
2021
pubmed:
9
11
2021
medline:
9
11
2021
Statut:
epublish
Résumé
Small cell lung cancer (SCLC) is an aggressive malignancy characterized by initial chemosensitivity followed by resistance and rapid progression. Presently, there are no predictive biomarkers that can accurately guide the use of systemic therapy in SCLC patients. This study explores the role of radiomic features from both within and around the tumor lesion on pretreatment CT scans to a) prognosticate overall survival (OS) and b) predict response to chemotherapy. One hundred fifty-three SCLC patients who had received chemotherapy were included. Lung tumors were contoured by an expert reader. The patients were divided randomly into approximately equally sized training (S A univariable Cox regression analysis indicated that RRS was significantly associated with OS in S Radiomic features extracted within and around the lung tumor on CT images were both prognostic of OS and predictive of response to chemotherapy in SCLC patients.
Sections du résumé
BACKGROUND
BACKGROUND
Small cell lung cancer (SCLC) is an aggressive malignancy characterized by initial chemosensitivity followed by resistance and rapid progression. Presently, there are no predictive biomarkers that can accurately guide the use of systemic therapy in SCLC patients. This study explores the role of radiomic features from both within and around the tumor lesion on pretreatment CT scans to a) prognosticate overall survival (OS) and b) predict response to chemotherapy.
METHODS
METHODS
One hundred fifty-three SCLC patients who had received chemotherapy were included. Lung tumors were contoured by an expert reader. The patients were divided randomly into approximately equally sized training (S
RESULTS
RESULTS
A univariable Cox regression analysis indicated that RRS was significantly associated with OS in S
CONCLUSIONS
CONCLUSIONS
Radiomic features extracted within and around the lung tumor on CT images were both prognostic of OS and predictive of response to chemotherapy in SCLC patients.
Identifiants
pubmed: 34745966
doi: 10.3389/fonc.2021.744724
pmc: PMC8564480
doi:
Types de publication
Journal Article
Langues
eng
Pagination
744724Informations de copyright
Copyright © 2021 Jain, Khorrami, Gupta, Rajiah, Bera, Viswanathan, Fu, Dowlati and Madabhushi.
Déclaration de conflit d'intérêts
AM is an equity holder in Elucid Bioimaging and in Inspirata, Inc. In addition, he has served as a scientific advisory board member for Inspirata, Inc., AstraZeneca, Bristol Meyers-Squibb, and Merck. Currently, he serves on the advisory board of Aiforia Inc. He also has sponsored research agreements with Philips, AstraZeneca, Boehringer-Ingelheim, and Bristol Meyers-Squibb. His technology has been licensed to Elucid Bioimaging. He is also involved in a NIH U24 grant with PathCore Inc. and three different R01 grants with Inspirata, Inc. AD has received consultancy fees for advisory committees from BMS, AZ, Bayer, and Jazz Pharmaceuticals. AG has received research support from General Electric Healthcare. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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