3D Lung Reconstructions Using Open-source Software for Lung Cancer Surgery

Study Overview
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Brief Summary
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Preoperative three-dimensional (3D) lung reconstructions can reduce intraoperative blood loss, conversion rate, and operation duration. Commercial products predominantly provide these 3D reconstructions, hence the aim of this study was to assess the usability and performance of preoperative 3D lung reconstructions created with open-source software.

Detailed Description
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A single-center prospective pilot study is conducted within the thoracic surgery department of the Zuyderland Medical Center, Heerlen, the Netherlands. Patients are recruited during preoperative consultation with the thoracic surgeon. The aim of this study is to include at least 12 patients in this pilot study based on the sample size for pilot studies. Before the pilot study, the surgeons involved in the study set several requirements for the 3D lung reconstructions. A technical physician, a healthcare professional in the Netherlands who combines knowledge of technology and medicine and is licensed to perform medical interventions, creates three-dimensional lung reconstructions using open-source 3D Slicer software that fulfills these aforementioned requirements and uses the available preoperative diagnostic late arterial phase contrast-enhanced CT scans. Three thoracic surgeons (with at least five years of uniportal VATS experience) and one surgical resident in thoracic surgery assess these 3D lung reconstructions for preoperative planning of uniportal VATS anatomical resections and compare the outcome measures based on the 3D lung reconstructions with the 2D CT scan and intraoperative findings. Patient characteristics, including age, sex, Eastern Cooperative Oncology Group (ECOG) performance status, body mass index, American Society of Anesthesiologists classification, forced expiratory volume in 1s (FEV1), diffusion capacity of the lung for carbon monoxide by the single-breath technique (DLCO-SB), intoxications, clinical Tumor Nodule Metastasis (TNM) classification 8th edition, previous thoracic surgery, and comorbidities are extracted from patient records. The following perioperative and postoperative data are collected: surgical approach, planned lung resection, performed lung resection, surgery duration, conversion, blood loss, surgery difficulty, the radicality of resection, pathological TNM classification 8th edition, tumor size, final pathology, drain duration, length of hospital stay, and complications within 30 days of surgery. The difficulty of the surgical procedure will be assessed by the thoracic surgeon and rated on a 5-point Likert scale from 1 (very easy) to 5 (very difficult). Length of hospital stay is defined as the number of days between the first day after surgery and the day the patient was clinically discharged. Descriptive statistical analyses are performed in IBM SPSS Statistics v28 (MacOS, Armonk, New York, United States). Missing data will be reported as such.

Official Title
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Evaluating Three-dimensional Lung Reconstructions for Uniportal Thoracoscopic Lung Resections Using Open-source Software

Conditions
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Lung Cancer, Lobectomy, Thoracic Surgery, Video-Assisted, Segmentectomy, Humans, Surgery

Intervention / Treatment
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* Device: Preoperative 3D lung reconstruction created with open-source software


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients with suspected or biopsy-proven lung cancer scheduled for video-assisted thoracoscopy surgery for lobectomy or segmentectomy Exclusion Criteria: Computed Tomography scan contained motion artifacts Surgery was canceled Planned surgery changed intraoperatively to another procedure Patients who did not provide informed consent
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Device Feasibility
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Preoperative 3D lung reconstruction<br>Patients who were planned for an anatomical lung resection with preoperative 3D lung reconstruction. | Device: Preoperative 3D lung reconstruction created with open-source software<br>* Preoperative 3D lung reconstruction created with open-source software 3D Slicer<br>* Other names: 3D Slicer;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| System Usability Score | System Usability Score Questionnaire. This questionnaire includes 10 statements rated from 1 (strongly disagree) to 5 (strongly agree). The even-numbered questions contributed to the scale position 5 minus the scale position, while the odd-numbered questions contributed to the scale position minus 1. The final score was calculated by the sum of the even and uneven-numbered questions, multiplied by 2.5. The minimum system usability score is 0 and the maximum is 100. A system usability score above 68 is considered above average. | Single-point evaluation after surgery (at day 0) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Segmental lung nodule location | The performance of the 3D lung reconstructions is evaluated based on the anatomical validity of the 3D lung reconstructions compared to the two-dimensional (2D) CT scan and intraoperative findings. Before surgery, a number of anatomical components of the 3D lung reconstructions are assessed. During surgery, the anatomical validity of these anatomical components is verified. One of the anatomical components includes the segmental location of the lung nodule. | Baseline and during surgery (at day 0) | 
| Number of arteries to target lobe or segment | The performance of the 3D lung reconstructions is evaluated based on the anatomical validity of the 3D lung reconstructions compared to the two-dimensional (2D) CT scan and intraoperative findings. Before surgery, a number of anatomical components of the 3D lung reconstructions are assessed. During surgery, the anatomical validity of these anatomical components is verified. One of the anatomical components includes the number of arteries towards the target lobe or segment. | Baseline and during surgery (at day 0) | 
| Anatomical variations | The performance of the 3D lung reconstructions is evaluated based on the anatomical validity of the 3D lung reconstructions compared to the two-dimensional (2D) CT scan and intraoperative findings. Before surgery, a number of anatomical components of the 3D lung reconstructions are assessed. During surgery, the anatomical validity of these anatomical components is verified. One of the anatomical components includes the presence of (a) anatomical variation(s). | Baseline and during surgery (at day 0) | 
| Potential change of surgery or surgical plan | As another part of the evaluation of the performance, the potential impact of the 3D lung reconstructions on the surgical plan was also considered. Therefore, the surgeon was asked after surgery if the 3D lung reconstruction would have resulted in a preoperative change in surgical approach. | Single-point evaluation after surgery (at day 0) | 
| Intraoperative use of 3D lung reconstruction | As final part of the evaluation of the performance, the potential value during surgery of the 3D lung reconstructions was also considered. Therefore, the surgeon was asked after surgery whether they would like to have used the 3D lung reconstruction during surgery via a tablet for example. | Single-point evaluation after surgery (at day 0) | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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video-assisted thoracoscopic surgery, lung cancer, three-dimensional reconstruction, open-source software, three-dimensional simulation