Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06626087
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-10-01
Brief Title:
A Prototype Artificial Intelligence Algorithm Versus Liver Imaging Reporting and Data System LI-RADS Criteria in Diagnosing Hepatocellular Carcinoma on Computed Tomography a Randomized Trial
Sponsor:
None
Organization:
None
Study Overview
Official Title:
A Prototype Artificial Intelligence Algorithm Versus Liver Imaging Reporting and Data System LI-RADS Criteria in Diagnosing Hepatocellular Carcinoma on Computed Tomography a Randomized Trial
Status:
RECRUITING
Status Verified Date:
2023-10
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Hepatocellular
Brief Summary:
This study aims to prospective validate this AI algorithm in comparison with the current standard of radiological reporting in a randomized manner in the at-risk population undergoing triphasic contrast CT This research project is totally independent and separated from the actual clinical reporting of the CT scan by the duty radiologist The primary study outcome is to compare the diagnostic performance of the prototype AI algorithm versus LI-RADS criteria in determining HCC on CT in the at-risk population
Detailed Description:
Liver cancer is the sixth most commonly diagnosed cancer and the fourth leading cause of cancer death worldwide The main disease burden is found in East Asia in which the age-standardized incidence is 268 and 87 per 100000 in men and women respectively In 2017 among the top 10 most common cancers in Hong Kong liver cancer had the highest case fatality rate of 846 The five-year survival rates of hepatocellular carcinoma HCC differ greatly with disease staging ranging from 915 in 2 cm with surgical resection to 11 in 5 cm with adjacent organ involvement The early and accurate diagnosis of HCC is paramount in improving cancer survival
Unlike other common cancers HCC is diagnosed by highly characteristic dynamic patterns on contrast-enhanced cross sectional imaging without the need of pathological confirmation The Liver Imaging Reporting and Data System LI-RADS was established to standardize the lexicon interpretation and communication of radiological findings related to HCC However up to 49 of nodules identified in computed tomography CT in the at-risk population are categorized by LI-RADS as indeterminate further delaying the establishment of diagnosis
There are currently studies pioneering the application of artificial intelligence AI in the field of medical imaging An interdisciplinary research team of clinicians radiologists and statistical scientists based on the clinical and radiological database of over 4000 liver images have developed an AI algorithm to accurately diagnose liver cancer on CT Based on retrospective data an interim analysis found the AI algorithm able to achieve a diagnostic accuracy of 97 and a negative predictive value of 99
If the prototype AI algorithm proves to have a better one-off diagnostic performance when compared to LI-RADS it can facilitate the earlier diagnosis of HCC allowing earlier definitive treatment and improving cancer survival
Unlike other common cancers HCC is diagnosed by highly characteristic dynamic patterns on contrast-enhanced cross sectional imaging without the need of pathological confirmation The Liver Imaging Reporting and Data System LI-RADS was established to standardize the lexicon interpretation and communication of radiological findings related to HCC However up to 49 of nodules identified in computed tomography CT in the at-risk population are categorized by LI-RADS as indeterminate further delaying the establishment of diagnosis
There are currently studies pioneering the application of artificial intelligence AI in the field of medical imaging An interdisciplinary research team of clinicians radiologists and statistical scientists based on the clinical and radiological database of over 4000 liver images have developed an AI algorithm to accurately diagnose liver cancer on CT Based on retrospective data an interim analysis found the AI algorithm able to achieve a diagnostic accuracy of 97 and a negative predictive value of 99
If the prototype AI algorithm proves to have a better one-off diagnostic performance when compared to LI-RADS it can facilitate the earlier diagnosis of HCC allowing earlier definitive treatment and improving cancer survival
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None