Gastrectomy

From September 1994 to December 2005, 1,557 GC patients underwent curative gastrectomy at Samsung Medical Center. Among those, 1,107 patients were selected based on following criteria: histologically confirmed adenocarcinoma of the stomach; surgical resection of tumour without macroscopic or microscopic residual disease; age ≥18; pathology stage IB (T2bN0, T1N1 but not T2aN0) to IV, according to the American Joint Committee on Cancer (AJCC) staging system (6^th Ed); complete surgical record and treatment record, and patients receiving the INT-0116 regimen as adjuvant treatment [7] (link). The study was approved by the institutional review board of the Samsung Medical Center, Seoul, South Korea (IRB approval number: SMC 2010-10-025). All study participants provided written informed consent form recommended by the IRB. In the patients who have deceased at the time of study entry, written informed consent forms were waived by the IRB. Study design and patient cohorts are provided according to REMARK guideline (Figure 1A, 1B, File S1, Section 1). Of the cohort of 1,107 patients, a discovery set of 520 patients and a validation set of 587 patients were randomly assigned and allocated to 6 batches stratified by tumor size and year of surgery for WG-DASL assay.
To avoid false-positive conclusions due to over-fitting, prognostic algorithms and their predefined cut-points were tested in independent cohorts that were not used for prognostic gene discovery and algorithm building. A 4-phase study was designed, with 4 pre-defined independent cohorts recruited from the Samsung Medical Center. The first 3 cohorts include patients with similar clinical and pathological features from chemoradiotherapy-treated study cohorts (File S1, Section 2). The first phase (discovery phase) of the study included GC patients from all clinical stages who were treated with chemo-radiotherapy (N = 520) [8] (link). Tumor blocks from these patients were subjected to prognostic gene discovery using the WG-DASL (Illumina, San Diego, CA), a microarray gene expression profiling method for FFPE [7] (link). An ad-hoc external validation of the gene set was performed to minimize any bias from single institutional cohort. The second phase (algorithm development) was to translate findings from the first phase into a clinically applicable test format. We chose the nCounter platform (Nanostring Technologies, Seattle, WA), because of its ability to interrogate the expression levels of up to 800 genes using total RNA extracted from FFPE in a single-tube reaction [8] (link). We screened stage II patients from the first phase (N = 186) for de novo discovery of prognostic genes, selected ideal combinations of genes using the gradient least absolute shrinkage and selection operator (LASSO) algorithm [10] (link), and then built a first-generation GCPS (GCPS-g1) by adding the products of normalized gene expression and coefficients from the Cox model for DFS. In the third cohort of stage II patients (N = 216). In the fourth phase (testing of clinical utility in a surgery-only setting), we tested the potential clinical utility of GCPS in stage II patients treated with surgery only. A time stamp protocol (Figure S12) was developed before processing of this final cohort. We subsequently developed a refined second-generation GCPS (GCPS-g2) (the final gene set) by analyzing the combined stage II cohorts from the second and third phases of the study.

This study was designed as a prospective single-arm observational study allowing for comparison with the control group after propensity-score matching. We enrolled gastric cancer patients who were scheduled for robotic surgery for distal subtotal gastrectomy. We included patients aged 18 years or older who had an abdominopelvic CT according to the established protocol. We excluded patients whose major vascular structures around the stomach had been altered due to previous surgery and those with history of any gastric surgery. We also excluded patients who could not have a CT scan due to contrast agent allergy, creatinine level above 1.5 times the normal maximum, and claustrophobia. To perform robotic subtotal gastrectomy using surgical navigation in 30 patients, this clinical trial was designed to enroll 36 patients considering 20% drop out and exclusion of enrolled participants during 6 months enrollment period.
The control group was selected among 175 patients who took CT angiography with an established protocol capable of 3-D model reconstruction between September 2014 and September 2021 from the prospectively collected gastric cancer database. We used the same eligibility criteria for the control and the experimental group. After excluding 28 patients who underwent total gastrectomy or proximal gastrectomy, 147 gastric cancer patients underwent robotic distal gastrectomy. Of these 147 patients, we used propensity-score matching for control group selection to balance the two groups for different clinical and surgical features. A control group was selected using 1:1 propensity-score matching with covariates of patient demographics (age, sex, body mass index) and operative factors (extent of lymph node dissection and reconstruction type). We set the caliper value of 0.1 for 1:1 matching using the nearest method without replacement.
This study was approved by the Institutional Review Board (IRB) of Severance Hospital, Yonsei University Health System (1-2021-0036). Written informed consent was obtained from patients after a full explanation of the study. Informed consent for patients included in the control group was waived by the IRB because of its retrospective nature.

The primary outcome was the feasibility of RUS™ for robotic gastrectomy. The feasibility was evaluated as the successful use of RUS™ without any error in delivering the 3-D model or inability to perform robotic gastrectomy by generating a 3-D model until its use for operation. Secondary outcomes were the turnaround time, the accuracy of detecting vascular anatomy with its variations, and the comparison of perioperative outcomes with a control group. The turnaround time was defined as the time from the patient’s CT DICOM file and demographic information transfer until the creation of a patient-specific 3-D model for RUS™ use. When a 3-D model is developed, the feasibility of regular operation is checked so that the anatomical structures can be reviewed before surgery. We assessed the 3-D model information regarding the origin, location, and variations of vessels encountered when performing robotic subtotal gastrectomy. We compared the accuracy of the anatomy of each blood vessel identified by RUS™ with the actual intraoperative findings. We measured the distance from each vascular structure to the specific reference point. Distance from the reference point was measured using the function of RUS™ and confirmed by measuring distance using a flexible ruler during the surgery.