Ignite Creation Date:
2024-05-06 @ 4:07 PM
Last Modification Date:
2024-10-26 @ 2:04 PM
Study NCT ID:
NCT04878783
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-05-09
First Post:
2021-05-06
Brief Title:
Radiomics and Molecular Expression Predictive Model for Esophago-Gastric Junction and Gastric Cancer TRG
Sponsor:
University of Roma La Sapienza
Organization:
University of Roma La Sapienza
Study Overview
Official Title:
CT Scan-Based Radiomics and Molecular Expression Predictive Model to Assess Tumor Regression Grade Following Perioperative Chemotherapy in Esophago-Gastric Junction and Gastric Cancer
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The aim of this study is to develop a CT scan-based radiomics predictive model about tumor regression grade TRG in patients with esophago-gastric junction EGJ ang gastric cancer undergoing perioperative chemotherapy The molecular expression of the neoplasms will be evaluated to assess its association with the TRG and the radiomic features
Detailed Description:
To compare the radiomic features of the CT scans at the time of diagnosis T0 and at the end of the preoperative chemotherapy T1 in order to predict the TRG with the texture analysis on the first CT scan
A non-good response non-GR has shown to be predictable with texture analysis on the pre-treatment CT scan
Therefore we hypothesize that texture analysis could let to identify the good response patients
To find correlation between the molecular expression of the tumor and the radiomics features
Texture analysis on the pre-chemotherapy CT scan founded that entropy and compactness were higher and uniformity lower in responders Nonetheless the association between radiomics features and molecular expression has not been investigated yet
Therefore we hypothesize to add some others radiomics signatures to the analysis and to find an association with the molecular expression
To find correlation between the molecular expression of the tumor and the TRG
MSI gastric cancer has been shown to be less responsive to preoperative chemotherapy
Therefore we hypothesize to confirm this result
A non-good response non-GR has shown to be predictable with texture analysis on the pre-treatment CT scan
Therefore we hypothesize that texture analysis could let to identify the good response patients
To find correlation between the molecular expression of the tumor and the radiomics features
Texture analysis on the pre-chemotherapy CT scan founded that entropy and compactness were higher and uniformity lower in responders Nonetheless the association between radiomics features and molecular expression has not been investigated yet
Therefore we hypothesize to add some others radiomics signatures to the analysis and to find an association with the molecular expression
To find correlation between the molecular expression of the tumor and the TRG
MSI gastric cancer has been shown to be less responsive to preoperative chemotherapy
Therefore we hypothesize to confirm this result
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None