Literature DB >> 32035822

A systematic review of automated feeder detection software for locoregional treatment of hepatic tumors.

Z Cui1, P A Shukla2, P Habibollahi3, H S Park3, A Fischman4, M K Kolber5.   

Abstract

PURPOSE: The purpose of this study was to perform a systematic review of current literature describing the efficacy and technical outcomes of transarterial liver therapies using automated feeder detection (AFD) software.
MATERIALS AND METHODS: This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. A structured search was performed in the PubMed, SCOPUS, and Embase databases of patients undergoing locoregional therapy of liver tumors utilizing AFD software. Demographic data, procedure data (including radiometrics) and tumor response rate were recorded. Where available, performance of AFD was compared to conventional digital subtraction angiography (DSA) and cone-beam CT (CBCT) without AFD.
RESULTS: A total of 14 full-text manuscripts met inclusion criteria, comprising 1042 tumors in 604 patients (305 men, 156 women; mean age, 68.6±6.0 [SD] years), including 537 patients with hepatocellular carcinoma, 8 with metastases from neuroendocrine tumors, and 59 patients without reported etiology. Reported sensitivity of AFD ranged between 86% and 98.5%, compared to DSA alone (38% - 64%) or DSA in combination with CBCT (69% - 81%). Three studies reported tumor response by modified response evaluation criteria in solid tumors (mRECIST) guidelines, with complete response in the range of 60% - 69%.
CONCLUSION: AFD is a promising new technology for the identification of intrahepatic and extrahepatic tumor-feeding arteries and should be considered a useful adjunct to conventional DSA and CBCT in the treatment of liver tumors.
Copyright © 2020 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Angiography; Automated feeder detection; Cone-beam computed tomography; Digital subtraction; Liver neoplasm

Mesh:

Year:  2020        PMID: 32035822     DOI: 10.1016/j.diii.2020.01.011

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  4 in total

1.  Injection Simulation Software Identifies Missed Tumor-Supplying Vessel in a Patient with Residual Disease After Transarterial Chemoembolization for Hepatocellular Carcinoma.

Authors:  Ana K Ortiz; Kyungmouk S Lee; Raphael Doustaly; Adam D Talenfeld; David C Madoff
Journal:  Cardiovasc Intervent Radiol       Date:  2021-01-03       Impact factor: 2.740

Review 2.  Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures.

Authors:  Chiara Floridi; Michaela Cellina; Giovanni Irmici; Alessandra Bruno; Nicolo' Rossini; Alessandra Borgheresi; Andrea Agostini; Federico Bruno; Francesco Arrigoni; Antonio Arrichiello; Roberto Candelari; Antonio Barile; Gianpaolo Carrafiello; Andrea Giovagnoni
Journal:  J Clin Med       Date:  2022-07-12       Impact factor: 4.964

3.  Retrospective Use of Breathing Motion Compensation Technology (MCT) Enhances Vessel Detection Software Performance.

Authors:  Fourat Ridouani; Raphael Doustaly; Hooman Yarmohammadi; Stephen B Solomon; Adrian J Gonzalez-Aguirre
Journal:  Cardiovasc Intervent Radiol       Date:  2021-01-20       Impact factor: 2.740

4.  Simulation of superselective catheterization for cerebrovascular lesions using a virtual injection software.

Authors:  Sri Hari Sundararajan; Srirajkumar Ranganathan; Vaishnavi Kishore; Raphael Doustaly; Athos Patsalides
Journal:  CVIR Endovasc       Date:  2021-06-14
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.