Evidence map›Paper›PMID 40591242›Full record

ArticleInternational journal of computer assisted radiology and surgery2025

The impact of 3-dimensional models and surgical navigation for open liver surgery.

Karin A Olthof, Matteo Fusaglia, Anne G den Hartog, Niels F M Kok, Theo J M Ruers, Koert F D Kuhlmann

Abstract read
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Article in International journal of computer assisted radiology and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Karin A OlthofDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands. ka.olthof@nki.nl.ORCID http://orcid.org/0009-0006-1448-8328
Matteo FusagliaDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands.
Anne G den HartogDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands.
Niels F M KokDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands.
Theo J M RuersDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands.
Koert F D KuhlmannDepartment of Surgical Oncology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek, Plesmanlaan 121, 1066CX, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeUnderstanding patient-specific liver anatomy is crucial for patient safety and achieving complete treatment of all tumors during surgery. This study evaluates the impact of the use of patient-specific 3D liver models and surgical navigation on procedural complexity in open liver surgery.

methodsPatients with colorectal liver metastases scheduled for open liver surgery were included between June 2022 and October 2023 at the Netherlands Cancer Institute. Patient-specific 3D liver models could be used upon request during the surgical procedure. Subsequently, surgeons could request additional surgical navigation by landmark registration using an electromagnetically tracked ultrasound transducer. Postoperatively, surgeons assessed the impact of the use of the model and navigation on procedural complexity on a scale from 1 to 10.

results35 patients were included in this study, with a median number of 8 (ranging from 3 to 25) tumors. 3D models were utilized in all procedures. Additional navigation was requested in 21/35 of patients to improve intraoperative planning and tumor localization. The mean procedural complexity score with navigation was 4.3 (95% CI [3.7, 5.0]), compared to 7.8 (95% CI [6.6, 9.0]) with the 3D model alone. Both visualization methods improved lesion localization and provided better anatomical insight.

conclusion3D models and surgical navigation significantly reduce the complexity of open liver surgery, especially in patients with bilobar disease. These tools enhance intraoperative decision-making and may lead to better surgical outcomes. The stepwise implementation of the visualization techniques in this study underscores the added benefit of surgical navigation beyond 3D modeling alone, supporting its potential for broader clinical implementation.

Indexed as

Colorectal NeoplasmsHepatectomyImaging, Three-DimensionalLiver NeoplasmsPatient-Specific ModelingSurgery, Computer-AssistedAdultAgedAged, 80 and overFemaleHumansLiverMaleMiddle Aged3D modelsComputer-assisted surgeryIntraoperative decision supportLiver surgerySurgical navigation

Identifiers

PMID40591242
PMCPMC12575497

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.