Ignite Creation Date:
2024-05-06 @ 5:02 PM
Last Modification Date:
2024-10-26 @ 2:21 PM
Study NCT ID:
NCT05170282
Status:
UNKNOWN
Last Update Posted:
2021-12-27
First Post:
2021-12-08
Brief Title:
Deep Learning Magnetic Resonance Imaging Radiomics for Diagnostic Value of Hepatic Tumors in Infants
Sponsor:
West China Hospital
Organization:
West China Hospital
Study Overview
Official Title:
Deep Learning Magnetic Resonance Imaging Radiomics for Diagnostic Value of Hepatic Tumors in Infants
Status:
UNKNOWN
Status Verified Date:
2021-12
Last Known Status:
RECRUITING
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:
Hepatic tumors in the perinatal period are associated with significant morbidity and mortality in affected patients The conventional diagnostic tool such as alpha-fetoprotein AFP shows limited value in diagnosis of infantile hepatic tumors This retrospective-prospective study is aimed to evaluate the diagnostic efficiency of the deep learning system through analysis of magnetic resonance imaging MRI images before initial treatment
Detailed Description:
Hepatic tumors seldom occur in the perinatal period They comprise approximately 5 of the total neoplasms of various types occurring in the fetus and neonate Infantile hemangioendothelioma is the leading primary hepatic tumor followed by hepatoblastoma It should be mentioned that alpha-fetoprotein AFP is highly elevated during the first several months after birth even in normal infants thus the diagnostic value of AFP is limited for infantile patients with hepatic tumors This study is a retrospective-prospective design by West China Hospital Sichuan University including clinical data and radiological images A retrospective database was enrolled for patients with definite histological diagnosis and available magnetic resonance imaging MRI images from June 2010 and December 2020 The investigators have constructed a deep learning radiomics diagnostic model on this retrospective cohort and validated it internally A prospective cohort would recruit infantile patients diagnosed as liver tumor since January 2021 The proposed deep learning model would also be validated in this prospective cohort externally The established model would be able to assist diagnosis for hepatic tumor in infants
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