Faculty Bibliography

BACKGROUND:Intraoperative catastrophes during robotic anatomical pulmonary resections are potentially devastating events. The present study aimed to assess the incidence, management, and outcomes of these intraoperative catastrophes for patients with primary lung cancers. METHODS:This was a retrospective, multiinstitutional study that evaluated patients who underwent robotic anatomical pulmonary resections. Intraoperative catastrophes were defined as events necessitating emergency thoracotomy or requiring an additional unplanned major surgical procedure. Standardized data forms were collected from each institution, with questions on intraoperative management strategies of catastrophic events. RESULTS:Overall, 1810 patients underwent robotic anatomical pulmonary resections, including 1566 (86.5%) lobectomies. Thirty-five patients (1.9%) experienced an intraoperative catastrophe. These patients were found to have significantly higher clinical TNM stage (P = .031) and lower forced expiratory volume in 1 second (81% vs 90%; P = .004). A higher proportion of patients who had a catastrophic event underwent preoperative radiotherapy (8.6% vs 2.3%; P = .048), and the surgical procedures performed differed significantly compared with noncatastrophic patients. Patients in the catastrophic group had higher perioperative mortality (5.7% vs 0.5%; P = .018), longer operative duration (195 minutes vs 170 minutes; P = .020), and higher estimated blood loss (225 mL vs 50 mL; P < .001). The most common catastrophic event was intraoperative hemorrhage from the pulmonary artery, followed by injury to the airway, pulmonary vein, and liver. Detailed management strategies were discussed. CONCLUSIONS:The incidence of catastrophic events during robotic anatomical pulmonary resections was low, and the most common complication was pulmonary arterial injury. Awareness of potential intraoperative catastrophes and their management strategies are critical to improving clinical outcomes.

Virtual reality and augmented reality technologies have evolved with a growing presence in both clinical care and surgical training.

BACKGROUND:Our objectives are to present our outcomes of robotic segmentectomy and our preferred technique for nodule localization using indocyanine green both bronchoscopically and intravenously. METHODS:This is a retrospective review of a consecutive series of patients scheduled for robotic segmentectomy from a single surgeon's prospectively collected database. RESULTS:Between January 2010 and October 2018, there were 245 consecutive patients who underwent planned robotic segmentectomy by one surgeon, of which 93 (38%) received indocyanine green via electromagnetic navigational bronchoscopy and all 245 received intravenous indocyanine green. Median time for navigational bronchoscopy was 9 minutes. Navigational bronchoscopy with indocyanine green correctly identified the lesion in 80 cases (86%). Our preferred technique is: 0.5 mL of 25 mg of indocyanine green diluted in 10 mL of saline given bronchoscopically, followed by a 0.5 mL saline flush, staying at least 4 mm from the pleural surface. The remaining 9.5 mL of indocyanine green is administered intravenously after pulmonary artery ligation. An R0 resection was achieved in all 245 patients, a median of 17 lymph nodes were resected, and the average length of stay was 3.1 days (range 1-21 days). Major morbidity occurred in 3 patients and there were no 30 or 90-day mortalities. CONCLUSIONS:Robotic segmentectomy is safe with excellent early clinical outcomes. In our series, electromagnetic navigational bronchoscopy and indocyanine green localization is efficient and effective at identifying the target lesion. Intravenous indocyanine green delineates the intersegmental plane.

BACKGROUND:Minimally invasive techniques are increasingly being used in pulmonary segmentectomy and combined subsegmentectomy. However, there are no reports as yet on robotic combined anatomic subsegmentectomy(CAS). Herein, we describe related clinical data and operative techniques and present our early results METHODS: Clinical data on patients undergoing robotic CAS were retrospectively reviewed. A combined subsegmentectomy was defined as the resection of ≥2 subsegments that involved ≥2 adjacent segments. Patients subjected to completely portal robotic CAS were enrolled in this study. RESULTS:Between May 2015 and January 2018, a single surgeon performed completely portal robotic CAS for 16 patients. In the CAS-treated patients, most of the lesions (75%) were located in the right upper lobe, and none required conversion to thoracotomy. Median operative time was 175 min (range, 75-294 min) and mean postoperative hospital stay was 4 days (range, 2-11 days). Although one patient experienced a prolonged air leak, the other 15 recovered uneventfully. Within a median follow-up period of 15 months, there were no deaths or tumor recurrences. CONCLUSIONS:Completely portal robotic CAS is a safe and effective procedure in a select subset of patients, proving quite suitable for smaller (<2 cm) multi-segment lung cancers, particularly lesions of right upper lobe. A robotics approach facilitates complex and challenging CAS, the disadvantage being lengthy operative times during early acquisition of skills.

BACKGROUND:Robotic segmentectomy has been suggested as a safe and effective management for early lung cancer and benign lung diseases. However, no large case series have documented the learning curve for this technically demanding procedure. METHODS:We conducted a retrospective study for robotic segmentectomy performed by the same surgeon between June 2015 and November 2017. The learning curve was initially analyzed using the cumulative sum (CUSUM) method to assess changes in the total operative times across the case sequence. Subsequently, an in-depth learning curve was generated using the risk-adjusted cumulative sum (RA-CUSUM) method, which considered perioperative risk factors and surgical failure. RESULTS:This study included 104 cases, and 87 were malignant. The median operative time was 145 min (interquartile range, IQR: 120-180 min) and the median blood loss was 100 ml (IQR: 50-100 ml). The median length of stay was 4 d (IQR: 3-5 d). Based on the CUSUM and RA-CUSUM analyses, the learning curve could be divided into 3 different phases: phase I, the initial learning period (1st-21st operation); phase II, the consolidation period (22nd-46th operation); and phase III, the experienced period (47th-104th operation). The operative time and intraoperative blood loss tended to decrease after the initial learning phase. Other perioperative outcomes were not significantly different among the three phases. CONCLUSIONS:The learning curve of robotic segmentectomy consisted of three phases. The technical competency for assuring feasible perioperative outcomes was achieved in phase II at the 40th operation.

BACKGROUND:Prolonged operating room turnover time erodes patient and employee satisfaction and value. METHODS:Lean and value stream mapping was applied to three operating room teams at an academic health center in New York City and a solution called Performance Improvement Team (PIT Crew) was piloted. RESULTS:Overall, 10% of operating room turnover steps were considered non-valued and were eliminated and 25% of previously sequential steps were performed synchronously. Seven institutional dogmas were eliminated, and three hospital policies were changed. After 35 pilot turnovers, median operating room turnover time improved from 37 minutes (range 26-167) in historical matched controls to 14 minutes (range 10-45, p<0.0001) for the PIT Crew. Cost of the PIT Crew was $1,298 daily and estimated return on investment was $19,500 per day. CONCLUSIONS:Lean and value stream mapping identifies non-valued steps in operating room turnover and affords opportunities for efficiency. Once institutional rules and dogma are changed, culture and workflow improve and turnover time significantly improves. This process adds cost but is profitable. Scalability and sustainability is under further study, as is the "halo effect" on the culture in other non-PIT Crew operating rooms.