Abstract
Background
The adoption of minimally invasive liver resection (MILR) is increasing globally; however, the impact of robotic platforms on total operating room time (TORT) remains poorly investigated. This study aimed to compare the TORTs for robot-assisted liver resection (RLR) and laparoscopic liver resection (LLR) by analyzing five distinct surgical phases.
Methods
This single-center retrospective study included 268 patients who underwent pure MILR (166 RLR and 102 LLR) between January 2018 and December 2025. The TORT was divided into five surgical phases: in-room to cut time, cut to transection time, transection time, transection to close time, and close to wheel-out time. Multivariable linear regression analyses were performed to identify predictors of TORT.
Results
The median TORT was significantly shorter for RLR than for LLR (RLR vs. LLR; 254 vs. 352 min, P < 0.001). It was consistently shorter across almost all phases of the RLR: room-to-cut time (51 vs. 78 min, P < 0.001), cut-to-transection time (46 vs. 68 min, P < 0.001), transection time (56 vs. 98 min, P < 0.001), and transection to close time (50 vs. 63 min, P < 0.001). Multivariable analyses identified central venous catheterization (estimate: 17.4 min; 95% CI, 7.7–27.0; P < 0.001), posterosuperior tumor location (estimate: 31.8; 95% CI, 22.8–40.7; P < 0.001), anatomic resection (estimate: 35.4; 95% CI, 26.6–44.2; P < 0.001), and LLR (estimate: 43.9; 95% CI, 34.4–53.4; P < 0.001) as independent predictors of prolonged TORT. Phase-specific analysis revealed that the robotic approach was an independent factor for shortening all surgical phases, except for the close to wheels-out time.
Conclusion
The TORT for RLR was significantly shorter because of reduced time requirements across nearly all surgical phases. The robotic approach may enhance the operational efficiency of the operating room workflow for MILR.
Keywords: Robotic liver resection, Laparoscopic liver resection, Total operating room time
Minimally invasive liver resection (MILR), comprising laparoscopic liver resection (LLR) and robot-assisted liver resection (RLR), has increasingly become the standard of care for hepatic resections owing to its superior short-term perioperative outcomes compared to open liver resection [1–3]. RLR is widely recognized for its technical advantages over LLR, including enhanced 3D visualization, superior dexterity, and greater surgeon comfort [4,5]. However, RLR frequently prolongs the time spent in the operating room (OR) because of the extended docking and setup times of the robotic platform [6–8].
A comprehensive analysis of the total operating room time (TORT), encompassing anesthesia, docking, setup, operative time, and turnover, is critical for assessing robotic efficiency, as robotic systems often introduce longer nonoperative phases than traditional laparoscopy [9]. Although robotic surgery is often associated with higher costs and prolonged TORT in gynecological surgery, standardized workflows can mitigate these time extensions [10,11]. Only a few studies have reported a longer TORT for robotic cholecystectomy and colorectal surgery than for laparoscopic surgery [12–14]. Although robotic preparation takes longer than conventional laparoscopy, it can be balanced by shorter surgical duration by a trained surgical team, resulting in no significant difference in TORT [15]. However, few studies have comprehensively investigated the OR timelines for MILR.
This study aimed to compare the TORTs of RLR and LLR and identify the independent predictors of TORT at a high-volume center in Japan. This study was part of a Training program at Okayama University for minimally invasive surgery (TAKUMI-8).
Materials and methods
Study design
This single-center retrospective cohort study included patients who underwent RLR and LLR at Okayama University Hospital between January 2018 and December 2025. The RLR was introduced at our institution in 2022 in accordance with national insurance coverage in Japan. This study was approved by the Ethics Committee of our institution (approval no. 2301–023) and conducted in accordance with the Declaration of Helsinki. The requirement for informed consent was waived due to the retrospective nature of this study.
Surgical procedure and perioperative management
Detailed surgical techniques for RLR and LLR have been reported previously [16–18]. LLR and RLR were introduced in 2010 and 2022, respectively, at our center. During the study period, LLR and RLR were performed by the same surgical team. Our multidisciplinary team, which included surgeons, anesthesiologists, scrub nurses, and medical engineers, was dedicated to robotic surgery before the initiation of this study [19]. Therefore, scrub nurses were shared across different operating rooms during the study period. RLR was performed using a robotic platform with a da Vinci Xi or Si system (Intuitive Surgical, Sunnyvale, CA, USA). For RLR, a console surgeon performed liver parenchymal dissection using the clamp-crush technique and a laparoscopic Cavitron Ultrasonic Surgical Aspirator (CUSA; Integra Life Sciences, Princeton, NJ, USA). For LLR, the liver parenchyma was transected using a CUSA. The Pringle maneuver is routinely performed using an extracorporeal or intracorporeal tourniquet system. The anesthesia protocols and perioperative procedures were selected at the discretion of the anesthesiologists. Epidural anesthesia was omitted from the standard protocol for RLR. Central venous catheter (CVC) placement and transversus abdominis plane (TAP) block were performed if needed. All patients were intraoperatively monitored through an arterial line.
OR timeline and definitions
The TORT was defined as the duration from the entry of the patient into the OR to wheels-out. To evaluate the efficiency of the OR workflow, the TORT was divided into five surgical phases (Fig. 1): in-room to cut time (IRCT), which starts from patient entry into the OR to the initial skin incision and includes anesthesia induction, epidural anesthesia, CVC placement, patient positioning, skin preparation, robot draping and docking preparation; cut to transection time (CTTT), which starts from the skin incision to the commencement of liver parenchymal transection and includes port placement, robotic docking (in RLR), preparation for the Pringle maneuver, liver mobilization, and hilar dissection; transection time (TT), which starts from the initial incision of the liver surface to the completion of parenchymal transection; transection to close time (TTCT), which starts from the completion of liver transection to the completion of skin closure, including hemostasis, drain placement, specimen extraction, robotic undocking (in RLR), and skin closure; and close to wheels-out time (CTWO), which starts from the completion of skin closure to patient wheels-out from the OR, representing patient repositioning, TAP block, the anesthesia emergence phase, and postoperative X-ray.
Fig. 1.
Operating room timeline for minimally invasive liver resection. CTTT cut to transection time, CTWO close to wheels-out time, IRCT: in-room to cut time, TT transection time, TTCT transection time to close time, CVC central venous catheter, TAP transversus abdominis plane, RLR robot-assisted liver resection
Data collection
The following clinical data were retrieved from a prospectively maintained database: age, sex, body mass index, Child–Pugh score, American Society of Anesthesiologists physical status, primary disease, anesthetic factors (epidural anesthesia, CVC, TAP block), procedure, surgical difficulty according to the IWATE criteria (low, intermediate, advanced, and expert) [20], duration of surgery, estimated blood loss, mortality, postoperative major complications (Clavien–Dindo grade ≥ IIIa) [21], bile leakage (≥ Grade B) [22], length of hospital stay, and readmission within 30 days after surgery. Specific timestamps for the OR timeline were retrieved from anesthesia records. The liver transection time was measured using intraoperative videos.
Statistical analysis
The background data and surgical outcomes of patients in the RLR and LLR groups were compared. To evaluate OR workflow efficiency, the TORT and duration of each phase were analyzed. Multivariable linear regression analysis was performed to evaluate the distribution of clinical factors, and variables with P < 0.20 were subsequently entered into further multivariable analyses. Using a backward elimination method, the independent factors predictive of the duration of each phase were identified. Finally, the TORT and duration of each surgical phase were calculated using a linear regression model with the least-squares method. The adjusted coefficient of determination (R2) was used to assess the predictability of these models. Clinical variables were compared using the Mann–Whitney U test for continuous data and the chi-square or Fisher's exact test for cate.
gorical data. Continuous variables were presented as medians and interquartile ranges (IQRs). Regression coefficients (estimates) and 95% confidence intervals (CIs) were calculated. Statistical significance was set at P < 0.05. Statistical analyses were performed using JMP version 17 (SAS Institute Inc., Cary, NC, USA).
Results
Study cohort
Data from 268 of 310 MILRs (166 RLR and 102 LLR) performed between January 2018 and December 2025 were included (Fig. 2). Patient characteristics and surgical outcomes of the RLR and LLR groups are summarized in Table 1. No significant differences in patient characteristics, tumor factors, surgical procedures, or surgical difficulties were observed between the two groups. However, anesthetic factors differed significantly between the groups. Epidural anesthesia was more commonly used in the LLR group (RLR vs. LLR, 1.8 vs. 59.8%; P < 0.001) and CVC placement was more frequently performed in the LLR group (RLR vs. LLR, 21.1 vs. 58.8%; P < 0.001). Conversely, the TAP block was more frequently performed in the RLR group (RLR vs. LLR; 21.7 vs. 10.8%; P = 0.02). Regarding surgical outcomes, the RLR group had a significantly shorter duration of surgery (166 vs. 240 min; P < 0.001) and less blood loss (20 vs. 73 mL; P < 0.001). Significant correlations between operative time and blood loss were found in all cohorts (coefficient of correlation, 0.46; P < 0.001), RLR (coefficient of correlation, 0.41; P < 0.001), and LLR (coefficient of correlation, 0.55; P < 0.001). The postoperative outcomes in the two groups were comparable. The overall incidence of major complications was 6.0% (n = 16) and required the following interventions: drain exchange (n = 7), percutaneous drainage (n = 5), endoscopic drainage (n = 1), interventional radiology (n = 1), and others (n = 2). Bile leak (≥ Grade B) was developed in five patients who were treated by drain exchange (n = 3), percutaneous drainage (n = 1), and endoscopic drainage (n = 1).
Fig. 2.
Flowchart of this study. Patients who underwent procedures involving hand-assisted laparoscopic surgery (HALS) or hybrid approaches (n = 14), combined resection of other organs (n = 12), or conversion to open surgery (n = 7), or who had an unavailable operative video (n = 9) were excluded from this study
Table 1.
Patient characteristics and outcomes of robotic and laparoscopic liver resection
| All cases (n = 268) |
RLR (n = 166) |
LLR (n = 102) |
P value | |
|---|---|---|---|---|
| Patient factor | ||||
| Age, years | 69 (59–75) | 69 (60–76) | 69 (59–74) | 0.16 |
| Sex | ||||
| Female | 106 (39.6) | 60 (36.1) | 46 (45.1) | 0.15 |
| Male | 162 (60.4) | 106 (63.9) | 56 (54.9) | |
| Body mass index, kg/m2 | 23 (21–27) | 23 (21–27) | 24 (21–27) | 0.69 |
| Child Pugh score A | 255 (99.6) | 165 (99.4) | 89 (100) | 0.47 |
| ASA-PS | ||||
| 1–2 | 221 (82.4) | 133 (80.1) | 88 (86.3) | 0.20 |
| 3 | 47 (17.5) | 33 (19.9) | 14 (13.7) | |
| Past surgical history | ||||
| Upper abdominal operation | 71 (26.5) | 46 (27.7) | 25 (24.5) | 0.56 |
| Hepatectomy | 36 (13.4) | 25 (15.1) | 11 (10.8) | 0.32 |
| Tumor factor | ||||
| Primary disease | ||||
| Hepatocellular carcinoma | 109 (40.7) | 70 (42.2) | 39 (38.2) | 0.74 |
| Metastatic tumor | 126 (47.0) | 75 (45.2) | 51 (50.0) | |
| Others | 33 (12.3) | 21 (12.7) | 12 (11.8) | |
| Tumor location | ||||
| Anterolateral tumors | 178 (66.4) | 111 (66.9) | 67 (65.7) | 0.84 |
| Posterosuperior tumors | 90 (33.6) | 55 (33.1) | 35 (34.3) | |
| Tumor size, mm | 20 (15–38) | 22 (15–37) | 20 (12–40) | 0.24 |
| Anesthetic factor | ||||
| Epidural anesthesia | 64 (23.9) | 3 (1.8) | 61 (59.8) | < .001 |
| Central venous catheter | 95 (35.4) | 35 (21.1) | 60 (58.8) | < .001 |
| Transversus abdominis plane block | 47 (17.5) | 36 (21.7) | 11 (10.8) | 0.02 |
| Procedure | ||||
| Partial resection | 165 (61.6) | 107 (64.5) | 58 (56.9) | 0.21 |
| Anatomical resection | 103 (38.4) | 59 (35.5) | 44 (43.1) | |
| Segmentectomy | 20 (19.4) | 17 (28.8) | 3 (6.8) | |
| Sectionectomy | 55 (53.4) | 26 (44.1) | 29 (65.9) | |
| Hemi-hepatectomy | 28(27.2) | 16(27.1) | 12(27.3) | |
| Multisite resection | 47 (17.5) | 30 (18.1) 17 (16.7) | 0.79 | |
| Difficulty level (Iwate criteria*) | ||||
| Low | 90 (33.6) | 56 (33.7) 34 (33.3) | 0.86 | |
| Intermediate | 117 (43.7) | 73 (44.0) 44 (43.1) | ||
| Advanced | 37 (13.8) | 24 (14.5) 13 (12.8) | ||
| Expert | 24 (9.0) | 13 (7.8) 11 (10.8) | ||
| Surgical outcome | ||||
| Operative time, min | 190 (138–244) | 166 (125–205) | 240 (178–302) | < .001 |
| Blood loss, mL | 48 (0–130) | 20 (0–100) | 73 (9–200) | < .001 |
| Mortality | 0 (0) | 0 (0) | 0 (0) | 1.00 |
|
Major complication (CDc ≥ Illa |
16 (6.0) | 10 (6.1) | 6 (5.9) | 0.94 |
| Bile leak (≥ Grade B) | 5 (1.9) | 4 (2.4) | 1 (1.0) | 0.40 |
| Hospital stay, day | 7 (6–9) | 7 (6–9) | 7 (6–9) | 0.33 |
| Readmission | 7 (2.6) | 4 (2.4) | 3 (2.9) | 0.79 |
Values are reported as n (%), or median (interquartile range)
ASA-PS American Society of Anesthesiologists physical status, CDc Clavien–Dindo classification
*Surgical difficulty level according to the IWATE criteria [20]: low (difficulty index 0– 4), intermediate (4–6), advanced (7–9), and expert (10–12)
Operating room timeline
The operating room timelines for both the groups are presented in Table 2. The TORT was significantly shorter in the RLR than for the LLR group (RLR vs. LLR; 254 vs. 352 min; P < 0.001). During the phase-specific analysis, the RLR group demonstrated significantly shorter durations for four of the five phases: IRCT (51 vs. 78 min, P < 0.001), CTTT (46 vs. 68 min, P < 0.001), TT (56 vs. 98 min, P < 0.001), and TTCT (50 vs. 63 min, P < 0.001). The CTWO did not differ between the groups.
Table 2.
Comparison of operating room timeline divided into five surgical phases between RLR and LLR
| All cases (n = 268) |
RLR (n = 166) |
LLR (n = 102) |
P value | |
|---|---|---|---|---|
| IRCT, min | 58 (48–73) | 51 (46–59) | 78 (66–88) | < .001 |
| CTTT, min | 53 (38–75) | 46 (37–61) | 68 (48–105) | < .001 |
| TT, min | 69 (41–107) | 56 (31–90) | 98 (65–137) | < .001 |
| TTCT, min | 54 (40–72) | 50 (37–65) | 63 (46–81) | < .001 |
| CTWO, min | 36 (32–43) | 37 (32–44) | 36 (31–42) | 0.22 |
| TORT, min | 285 (226–353) | 254 (210–300) | 352 (295–434) | < .001 |
Values are reported as median (interquartile range)
RLR robotic liver resection, LLR laparoscopic liver resection, IRCT in-room to cut time, CTTT cut to transection time, TT transection time, TTCT transection time to close time, CTWO close to wheels-out time, TORT total operating room time
Predictors associated with TORT
The results of the multivariable linear regression analysis for TORT are shown in Table 3. The first multivariable analysis revealed that epidural anesthesia, use of CVC, TAP block, tumor size, tumor location, extent of resection, and surgical approach (RLR vs. LLR) were potential predictors of TORT. Further multivariable analyses using backward elimination revealed that the use of CVC, TAP block, posterosuperior tumor location, anatomical resection, and LLR were significantly associated with TORT. The TORT was predicted using a linear regression model with the least-squares method based on these five independent factors (adjusted R2 = 0.50; P < 0.001). Laparoscopic liver resection was the most significant contributor to prolonged TORT (estimate: 43.9 min; 95% CI, 34.4–53.4; P < 0.001). The use of a CVC (estimate: 17.4 min; 95% CI, 7.7–27.0; P < 0.001), posterosuperior tumor location (estimate: 31.8 min; 95% CI, 22.8–40.7; P < 0.001), and anatomic resection (estimate: 35.4 min; 95% CI, 26.6–44.2; P < 0.001) were also identified as independent predictors of prolonged TORT.
Table 3.
Multivariable linear regression analysis of factors associated with total operative room time
| Variable | Estimate | 95% intervals |
confidence P value |
|---|---|---|---|
| Epidural anesthesia | – | Removed | – |
| Central venous catheter | + 17.4 | 7.7–27.0 | < .001 |
| TAP block | + 11.1 | −0.1–22.3 | 0.052 |
| Tumor size (≥ 3 cm) | – | Removed | – |
| Posterosuperior tumors | + 31.8 | 22.8–40.7 | < .001 |
| Anatomic resection | + 35.4 | 26.6–44.2 | < .001 |
| Laparoscopic liver resection | + 43.9 | 34.4–53.4 | < .001 |
| Adjusted R2 | 0.50 |
TAP transversus abdominis plane
Variable selection was performed using backward elimination with a P-value threshold of 0.05. Factors with "—" were excluded during the stepwise process
Subgroup analyses in individual surgical phases
Multivariable linear regression analysis was performed for each surgical phase (Fig. 3). Regarding the IRCT, the use of epidural anesthesia (estimate: 8.3; 95% CI, 6.2–10.4; P < 0.001), CVC (estimate: 6.5; 95% CI, 5.0–7.9; P < 0.001), posterosuperior tumor location (estimate: 2.9; 95% CI, 1.5–4.3; P < 0.001), and LLR (estimate: 4.9; 95% CI, 3.1–6.8; P < 0.001) were independent predictors of prolonged TORT. History of upper abdominal surgery (estimate: 7.3; 95% CI, 2.7–11.9; P = 0.002), posterosuperior tumor location (estimate: 7.8; 95% CI, 3.5–12.0; P < 0.001), anatomic resection (estimate: 6.8; 95% CI, 2.6–11.0; P = 0.002), and LLR (estimate: 14.5; 95% CI, 10.4–18.6; P < 0.001) were significantly correlated with prolonged CTTT. Multisite resection (estimate: 14.3; 95% CI, 7.9–20.7; P < 0.001), posterosuperior tumor location (estimate: 15.0; 95% CI, 9.9–20.0; P < 0.001), anatomic resection (estimate: 17.5; 95% CI, 12.3–22.8; P < 0.001), and LLR (estimate: 18.4; 95% CI, 13.6–23.2; P < 0.001) emerged as influential factors for TT. Similarly, the TTCT was primarily affected by anatomic resection (estimate: 12.1; 95% CI, 9.2–15.0; P < 0.001) and LLR (estimate: 5.5; 95% CI, 2.6–8.4; P < 0.001). Finally, the use of a TAP block was significantly associated with prolonged CTWO (estimate: 5.1; 95% CI, 3.5–6.6; P < 0.001).
Fig. 3.
Multivariable analysis of independent predictors for the duration of each surgical phase. The horizontal bars represent the unadjusted time difference in minutes, and the whiskers indicate the 95% confidence intervals. A positive estimate indicates an increase in the duration of surgery associated with that factor. The adjusted coefficient of determination represents the proportion of variance in the duration of surgery explained by the identified independent factors. BMI body mass index, CTTT cut to transection time, CTWO close to wheels-out time, CVC Central venous catheter, IRCT in-room to cut time, LLR laparoscopic liver resection, PS performance status RLR robotic liver resection, TAP transversus abdominis plane, TT transection time, TTCT transection time to close time
Discussion
This study investigated the TORTs for the RLR and LLR and identified their independent predictors in a high-volume center in Japan. The results show significantly shorter durations across most surgical phases in the RLR group than in the LLR group. Moreover, multivariable analysis identified LLR as an independent predictor of prolonged TORT, along with CVC placement, tumors in the posterosuperior segments, and anatomical resection. To the best of our knowledge, this is the first study to comprehensively evaluate the OR timeline for RLR and LLR using a detailed surgical phase analysis.
Our center introduced RLR in 2022 based on the national health insurance system and has been gradually expanding its application. The surgical approach changed during the study period, but patient characteristics, tumor factors, surgical procedures, and surgical difficulty were comparable across the groups (Table 1). Before the introduction of RLR in 2022, we had implemented robot-assisted pancreatectomy in 2020 [19]. In 2020, perioperative protocols and a multidisciplinary team were dedicated to robotic surgeries. Regarding anesthesia protocols for robotic surgery, epidural anesthesia was omitted, and CVC was placed only in necessary cases. Therefore, significant differences in perioperative management were observed between the groups; these included less frequent CVC placement and epidural anesthesia in the RLR group. As our group has previously reported that RLR is significantly associated with less blood loss and a lower risk of conversion to open surgery [16,17], we did not change the anesthesia protocol for RLR. This simplified perioperative management likely contributed to the efficient workflow in the RLR group. Although not significantly different, a higher proportion of partial resections appeared to have been performed in RLR than in LLR. Because we did not change the surgical indications for RLR and LLR, this finding may be associated with increased experience, such as performing more repeat liver resections using robotic surgery. The Iwate criteria were initially developed to predict the surgical difficulty of LLR [20], and the difficulty may differ between RLR and LLR. However, we used the Iwate criteria to determine the differences in surgical difficulty between the groups in this study and found no differences. Regarding surgical outcomes, the RLR group had significantly less blood loss and a shorter surgical duration than the LLR group, with comparable postoperative outcomes.
As shown in Table 2, the TORT was significantly shorter in the RLR group than in the LLR group. The reduction in the TORT resulted from time savings during almost all phases, except for CTWO. The RLR group had a shorter IRCT despite the additional requirements for robotic setup. The robotic platform is traditionally criticized for its time-consuming setup process [23]; however, standardized protocols in high-volume centers enable the surgical team to achieve a high level of proficiency and improve preparation efficiency [17,24,25]. Our multidisciplinary team building for RLR may help shorten IRCT. For CTTT, the articulated robotic platform facilitated preparation for the Pringle maneuver and intraoperative ultrasound procedures. Moreover, multi-jointed instruments allow easier liver mobilization than LLR [26]. TT was also significantly shorter in the RLR group. The two-surgeon technique ensured seamless coordination between the console surgeon and assistant, thereby improving transection speed [17]. During the TTCT, the robotic platform enabled secure hemostasis and efficient drain placement. These technical and procedural advantages likely contributed to the efficiency of liver surgery observed in this study. Since CTWO comprises the anesthesia emergence phase until the patient wheels-out from the OR, no differences were observed between the groups in this specific phase.
In the present study, multivariable analyses identified LLR, CVC placement, posterosuperior tumor location, and anatomical resection as independent predictors of increased TORT (Table 3). The LLR was the most significant contributor to prolonged TORT. This finding suggests that surgical platform is a critical determinant of OR efficiency. Anatomical resection and posterosuperior tumor location were also significantly associated with a longer TORT, as they are established indicators of surgical difficulty [27]. Specifically, posterosuperior tumors extended the IRCT because of left lateral positioning, the CTTT because of extensive liver mobilization, and the TT because of difficult accessibility (Fig. 3). For anatomical resections, CTTT and TT were prolonged because of the requirement for hilar dissection and wide parenchymal transection, respectively. The TTCT was extended because a separate incision is often required to extract larger surgical specimens. Regarding the anesthetic factor, epidural anesthesia and CVC placement were identified as independent predictors for prolonged IRCT. The linear regression model demonstrated moderate predictability, with an adjusted R2 of 0.50. This model may serve as a useful benchmark for optimizing OR scheduling in high-volume centers.
This study had several limitations. First, it is a single-center retrospective study with a relatively small sample size; therefore, a potential selection bias may exist. Second, the choice of anesthesia protocol was at the discretion of the anesthesiologists, which may have influenced the results. Finally, the results were obtained at a high-volume center with an experienced surgical team. The observed efficiency of the robotic setup and two-surgeon technique may not be directly generalizable to centers during the early stages of the learning curve. Further multicenter studies are required to validate these findings.
Conclusions
The TORT was shorter for RLR than for LLR because of the reduced time requirements across nearly all surgical phases. This suggests that the robotic approach may enhance the operational efficiency of the OR workflow.
Funding
Open Access funding provided by Okayama University. This study did not receive any specific grants from funding agencies in the public, commercial, or not-for-profit sectors.
Declarations
Disclosures
Tomokazu Fuji, Kosei Takagi, Kazuya Yasui, Takeyoshi Nishiyama, Jiro Kimura, Naohiro Okada, and Toshiyoshi Fujiwara have no conflicts of interest or financial ties to disclose.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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