Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis

During CT-guided percutaneous thermal ablation, MAM measured based on tumors segmented on PVP images conferred a higher predictive accuracy of ablation outcomes among CRLM patients than those segmented on HAP images, supporting the use of PVP rather than HAP images for segmentation during ablation of CRLMs.

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Publication Details

Journal
Journal of Computer Assisted Tomography
Published
2025-07-24
DOI
https://doi.org/10.1097/rct.0000000000001782
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
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article

Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis

Kristy K. Brock, Peter Schullian, Caleb S. O’Connor, A. Kyle Jones et al.
Journal of Computer Assisted Tomography
Hepatocellular Carcinoma Treatment and Prognosis
article

Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis

Kristy K. Brock, Peter Schullian, Caleb S. O’Connor, A. Kyle Jones, Bruno Calazans Odisio, Reto Bale, Noreen S. Siddiqi, Yuan‐Mao Lin, Yannick Scharll, Jéssica Albuquerque Marques Silva, Gregor Laimer, Iwan Paolucci, Alexandra M. Dunker
article en

Abstract

During CT-guided percutaneous thermal ablation, MAM measured based on tumors segmented on PVP images conferred a higher predictive accuracy of ablation outcomes among CRLM patients than those segmented on HAP images, supporting the use of PVP rather than HAP images for segmentation during ablation of CRLMs.

Journal of Computer Assisted TomographyVol. 50(1)
The University of Texas MD Anderson Cancer Center (US), Innsbruck Medical University (AT)
Good health and well-being
Openalex Percentile: Top 74%
Hepatocellular Carcinoma Treatment and Prognosis
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