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      Decision-making based on 3D printed models in laparoscopic liver resections with intraoperative ultrasound: a prospective observational study

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          Abstract

          Objectives

          The aim of this study was to evaluate impact of 3D printed models on decision-making in context of laparoscopic liver resections (LLR) performed with intraoperative ultrasound (IOUS) guidance.

          Methods

          Nineteen patients with liver malignances (74% were colorectal cancer metastases) were prospectively qualified for LLR or radiofrequency ablation in a single center from April 2017 to December 2018. Models were 3DP in all cases based on CT and facilitated optical visualization of tumors’ relationships with portal and hepatic veins. Planned surgical extent and its changes were tracked after CT analysis and 3D model inspection, as well as intraoperatively using IOUS.

          Results

          Nineteen patients were included in the analysis. Information from either 3DP or IOUS led to changes in the planned surgical approach in 13/19 (68%) patients. In 5/19 (26%) patients, the 3DP model altered the plan of the surgery preoperatively. In 4/19 (21%) patients, 3DP independently changed the approach. In one patient, IOUS modified the plan post-3DP. In 8/19 (42%) patients, 3DP model did not change the approach, whereas IOUS did. In total, IOUS altered surgical plans in 9 (47%) cases. Most of those changes (6/9; 67%) were caused by detection of additional lesions not visible on CT and 3DP.

          Conclusions

          3DP can be helpful in planning complex and major LLRs and led to changes in surgical approach in 26.3% (5/19 patients) in our series. 3DP may serve as a useful adjunct to IOUS.

          Key Points

          • 3D printing can help in decision-making before major and complex resections in patients with liver cancer.

          • In 5/19 patients, 3D printed model altered surgical plan preoperatively.

          • Most surgical plan changes based on intraoperative ultrasonography were caused by detection of additional lesions not visible on CT and 3D model.

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          Most cited references37

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          The Southampton Consensus Guidelines for Laparoscopic Liver Surgery

          The European Guidelines Meeting on Laparoscopic Liver Surgery was held in Southampton on February 10 and 11, 2017 with the aim of presenting and validating clinical practice guidelines for laparoscopic liver surgery.
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            Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): guidelines for medical 3D printing and appropriateness for clinical scenarios

            Medical three-dimensional (3D) printing has expanded dramatically over the past three decades with growth in both facility adoption and the variety of medical applications. Consideration for each step required to create accurate 3D printed models from medical imaging data impacts patient care and management. In this paper, a writing group representing the Radiological Society of North America Special Interest Group on 3D Printing (SIG) provides recommendations that have been vetted and voted on by the SIG active membership. This body of work includes appropriate clinical use of anatomic models 3D printed for diagnostic use in the care of patients with specific medical conditions. The recommendations provide guidance for approaches and tools in medical 3D printing, from image acquisition, segmentation of the desired anatomy intended for 3D printing, creation of a 3D-printable model, and post-processing of 3D printed anatomic models for patient care.
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              Laparoscopic versus open major hepatectomy: a systematic review and meta-analysis of individual patient data

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                Author and article information

                Contributors
                michal.pedziwiatr@uj.edu.pl
                Journal
                Eur Radiol
                Eur Radiol
                European Radiology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0938-7994
                1432-1084
                26 November 2019
                26 November 2019
                2020
                : 30
                : 3
                : 1306-1312
                Affiliations
                [1 ]GRID grid.5522.0, ISNI 0000 0001 2162 9631, 2nd Department of General Surgery, , Jagiellonian University Medical College, ; Kopernika 21, 31-501 Krakow, Poland
                [2 ]Center for Research, Training and Innovation in Surgery (CERTAIN Surgery), Krakow, Poland
                [3 ]GRID grid.5522.0, ISNI 0000 0001 2162 9631, Department of Radiology, Jagiellonian University Medical College, ; Kopernika 19, 31-501 Krakow, Poland
                [4 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Mallinckrodt Institute of Radiology, , Washington University School of Medicine, ; St. Louis, MO 63110 USA
                [5 ]GRID grid.9922.0, ISNI 0000 0000 9174 1488, Department of Measurement and Electronics, , AGH University of Science and Technology, ; Al. Mickiewicza 30, 30-065 Krakow, Poland
                Author information
                http://orcid.org/0000-0001-9073-2667
                Article
                6511
                10.1007/s00330-019-06511-2
                7033053
                31773294
                75e63f0e-8039-4113-aa99-b0eb8bcd9674
                © The Author(s) 2019

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 2 August 2019
                : 28 August 2019
                : 11 October 2019
                Funding
                Funded by: Ministerstwo Nauki i Szkolnictwa Wyższego (PL)
                Award ID: 0054/DIA/2018/47
                Award Recipient :
                Categories
                Imaging Informatics and Artificial Intelligence
                Custom metadata
                © European Society of Radiology 2020

                Radiology & Imaging
                3d printing,liver cancer,hepatectomy,decision-making,ultrasonography
                Radiology & Imaging
                3d printing, liver cancer, hepatectomy, decision-making, ultrasonography

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