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Neizert CA, Do HNC, Zibell M, Sinden D, Rieder C, Albrecht J, Niehues SM, Lehmann KS, Poch FGM. Optimizing microwave ablation planning with the ablation success ratio. Sci Rep 2025; 15:10450. [PMID: 40140611 PMCID: PMC11947081 DOI: 10.1038/s41598-025-94957-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 03/18/2025] [Indexed: 03/28/2025] Open
Abstract
The size of hepatic microwave ablations (MWA) is often difficult to predict due to cooling effects from liver vessels. This study introduces a simplified predictive model, the Ablation Success Ratio (ASR), which estimates the likelihood of a successful ablation based on tumor size and specific ablation parameters. The ASR model is based on the three-dimensional minimum ablation radius (r3Dmin), defining the spherical region within which complete ablation is achieved. To validate the ASR, standardized MWAs were performed in an ex vivo porcine liver model using a glass tube to simulate the vascular cooling effect. Ablations (n = 148) were conducted at 100 W for 5 min, with antenna-to-vessel (A-V) distances set at 2.5, 5.0, and 10.0 mm. Subsequently, the r3Dmin was calculated. Without vascular cooling (0 ml/min, corresponding to an intraoperative Pringle maneuver), an ASR of 100% was achieved for ablation diameters up to 20 mm. However, in the presence of vascular cooling (1-500 ml/min), the ASR reached 100% only for ablation diameters up to 12 mm, demonstrating that the ASR effectively includes the impact of vascular cooling effects. The ASR is a promising and simple approach for predicting ablation success while also accounting for vascular cooling effects in hepatic MWA.
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Affiliation(s)
- Christina A Neizert
- Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany.
| | - Hoang N C Do
- Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Miriam Zibell
- Landesamt für Gesundheit und Soziales, Turmstraße 21, 10559, Berlin, Germany
| | - David Sinden
- Fraunhofer Institute for Digital Medicine MEVIS, Max-Von-Laue-Straße 2, 28359, Bremen, Germany
| | - Christian Rieder
- Fraunhofer Institute for Digital Medicine MEVIS, Max-Von-Laue-Straße 2, 28359, Bremen, Germany
| | - Jakob Albrecht
- Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Stefan M Niehues
- Department of Radiology, Caritas-Klinik Dominikus, Kurhausstraße 30, 13467, Berlin, Germany
| | - Kai S Lehmann
- Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Franz G M Poch
- Department of General and Visceral Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany
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Zhang J, Wu F, Chang W, Kong D. Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey. ENTROPY (BASEL, SWITZERLAND) 2022; 24:465. [PMID: 35455128 PMCID: PMC9031516 DOI: 10.3390/e24040465] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/21/2022] [Accepted: 03/23/2022] [Indexed: 02/01/2023]
Abstract
Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this field. These methods are classified into five categories according to their methodological characteristics. The overview and brief assessment of each category are provided in the corresponding chapters, respectively. We provide a comprehensive summary among the cited publications, image modalities and datasets from various aspects, which hope to reveal the pros and cons of every method, summarize its achievements and discuss the challenges and future trends.
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Affiliation(s)
- Jianfeng Zhang
- School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China; (J.Z.); (W.C.)
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua 321004, China
| | - Fa Wu
- Zhejiang Demetics Medical Technology Co., Ltd., Hangzhou 310012, China;
| | - Wanru Chang
- School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China; (J.Z.); (W.C.)
| | - Dexing Kong
- School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China; (J.Z.); (W.C.)
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua 321004, China
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