Predicting Colonic Neoplasia Surgical Complications: A Machine Learning Approach.

BACKGROUND: A range of statistical approaches have been used to help predict outcomes associated with colectomy. The multifactorial nature of complications suggests that machine learning algorithms may be more accurate in determining postoperative outcomes by detecting nonlinear associations, which are not readily measured by traditional statistics. OBJECTIVE: The aim of this study was to investigate the utility of machine learning algorithms to predict complications in patients undergoing colectomy for colonic neoplasia. DESIGN: Retrospective analysis using decision tree, random forest, and artificial neural network classifiers to predict postoperative outcomes. SETTINGS: National Inpatient Sample database (2003-2017). PATIENTS: Adult patients who underwent elective colectomy with anastomosis for neoplasia. MAIN OUTCOME MEASURES: Performance was quantified using sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve to predict the incidence of anastomotic leak, prolonged length of stay, and inpatient mortality. RESULTS: A total of 14,935 patients (4731 laparoscopic, 10,204 open) were included. They had an average age of 67 ± 12.2 years, and 53% of patients were women. The 3 machine learning models successfully identified patients who developed the measured complications. Although differences between model performances were largely insignificant, the neural network scored highest for most outcomes: predicting anastomotic leak, area under the receiver operating characteristic curve 0.88/0.93 (open/laparoscopic, 95% CI, 0.73-0.92/0.80-0.96); prolonged length of stay, area under the receiver operating characteristic curve 0.84/0.88 (open/laparoscopic, 95% CI, 0.82-0.85/0.85-0.91); and inpatient mortality, area under the receiver operating characteristic curve 0.90/0.92 (open/laparoscopic, 95% CI, 0.85-0.96/0.86-0.98). LIMITATIONS: The patients from the National Inpatient Sample database may not be an accurate sample of the population of all patients undergoing colectomy for colonic neoplasia and does not account for specific institutional and patient factors. CONCLUSIONS: Machine learning predicted postoperative complications in patients with colonic neoplasia undergoing colectomy with good performance. Although validation using external data and optimization of data quality will be required, these machine learning tools show great promise in assisting surgeons with risk-stratification of perioperative care to improve postoperative outcomes. See Video Abstract . PREDICCIN DE LAS COMPLICACIONES QUIRRGICAS DE LA NEOPLASIA DE COLON UN ENFOQUE DE MODELO DE APRENDIZAJE AUTOMTICO: ANTECEDENTES:Se han utilizado una variedad de enfoques estadísticos para ayudar a predecir los resultados asociados con la colectomía. La naturaleza multifactorial de las complicaciones sugiere que los algoritmos de aprendizaje automático pueden ser más precisos en determinar los resultados posoperatorios al detectar asociaciones no lineales, que generalmente no se miden en las estadísticas tradicionales.OBJETIVO:El objetivo de este estudio fue investigar la utilidad de los algoritmos de aprendizaje automático para predecir complicaciones en pacientes sometidos a colectomía por neoplasia de colon.DISEÑO:Análisis retrospectivo utilizando clasificadores de árboles de decisión, bosques aleatorios y redes neuronales artificiales para predecir los resultados posoperatorios.AJUSTE:Base de datos de la Muestra Nacional de Pacientes Hospitalizados (2003-2017).PACIENTES:Pacientes adultos sometidos a colectomía electiva con anastomosis por neoplasia.INTERVENCIONES:N/A.PRINCIPALES MEDIDAS DE RESULTADO:El rendimiento se cuantificó utilizando la sensibilidad, especificidad, precisión y la característica operativa del receptor del área bajo la curva para predecir la incidencia de fuga anastomótica, duración prolongada de la estancia hospitalaria y mortalidad de los pacientes hospitalizados.RESULTADOS:Se incluyeron un total de 14.935 pacientes (4.731 laparoscópicos, 10.204 abiertos). Presentaron una edad promedio de 67 ± 12,2 años y el 53% eran mujeres. Los tres modelos de aprendizaje automático identificaron con éxito a los pacientes que desarrollaron las complicaciones medidas. Aunque las diferencias entre el rendimiento del modelo fueron en gran medida insignificantes, la red neuronal obtuvo la puntuación más alta para la mayoría de los resultados: predicción de fuga anastomótica, característica operativa del receptor del área bajo la curva 0,88/0,93 (abierta/laparoscópica, IC del 95%: 0,73-0,92/0,80-0,96); duración prolongada de la estancia hospitalaria, característica operativa del receptor del área bajo la curva 0,84/0,88 (abierta/laparoscópica, IC del 95%: 0,82-0,85/0,85-0,91); y mortalidad de pacientes hospitalizados, característica operativa del receptor del área bajo la curva 0,90/0,92 (abierto/laparoscópico, IC del 95%: 0,85-0,96/0,86-0,98).LIMITACIONES:Los pacientes de la base de datos de la Muestra Nacional de Pacientes Hospitalizados pueden no ser una muestra precisa de la población de todos los pacientes sometidos a colectomía por neoplasia de colon y no tienen en cuenta factores institucionales y específicos del paciente.CONCLUSIONES:El aprendizaje automático predijo con buen rendimiento las complicaciones postoperatorias en pacientes con neoplasia de colon sometidos a colectomía. Aunque será necesaria la validación mediante datos externos y la optimización de la calidad de los datos, estas herramientas de aprendizaje automático son muy prometedoras para ayudar a los cirujanos con la estratificación de riesgos de la atención perioperatoria para mejorar los resultados posoperatorios. (Traducción-Dr. Fidel Ruiz Healy ).

Clinical Utility of Laser Speckle Contrast Imaging and Real-Time Quantification of Bowel Perfusion in Minimally Invasive Left-Sided Colorectal Resections.

BACKGROUND: Left-sided colorectal surgery demonstrates high anastomotic leak rates, with tissue ischemia thought to influence outcomes. Indocyanine green is commonly used for perfusion assessment, but evidence remains mixed for whether it reduces colorectal anastomotic leaks. Laser speckle contrast imaging provides dye-free perfusion assessment in real-time through perfusion heat maps and quantification. OBJECTIVE: This study investigates the efficacy of advanced visualization (indocyanine green versus laser speckle contrast imaging), perfusion assessment, and utility of laser speckle perfusion quantification in determining ischemic margins. DESIGN: Prospective intervention group using advanced visualization with case-matched, retrospective control group. SETTINGS: Single academic medical center. PATIENTS: Forty adult patients undergoing elective, minimally invasive, left-sided colorectal surgery. INTERVENTIONS: Intraoperative perfusion assessment using white light imaging and advanced visualization at 3 time points: T1-proximal colon after devascularization, before transection, T2-proximal/distal colon before anastomosis, and T3-completed anastomosis. MAIN OUTCOME MEASURES: Intraoperative indication of ischemic line of demarcation before resection under each visualization method, surgical decision change using advanced visualization, post hoc laser speckle perfusion quantification of colorectal tissue, and 30-day postoperative outcomes. RESULTS: Advanced visualization changed surgical decision-making in 17.5% of cases. For cases in which surgeons changed a decision, the average discordance between the line of demarcation in white light imaging and advanced visualization was 3.7 cm, compared to 0.41 cm ( p = 0.01) for cases without decision changes. There was no statistical difference between the line of ischemic demarcation using laser speckle versus indocyanine green ( p = 0.16). Laser speckle quantified lower perfusion values for tissues beyond the line of ischemic demarcation while suggesting an additional 1 cm of perfused tissue beyond this line. One (2.5%) anastomotic leak occurred in the intervention group. LIMITATIONS: This study was not powered to detect differences in anastomotic leak rates. CONCLUSIONS: Advanced visualization using laser speckle and indocyanine green provides valuable perfusion information that impacts surgical decision-making in minimally invasive left-sided colorectal surgeries. See Video Abstract . UTILIDAD CLNICA DE LAS IMGENES DE CONTRASTE MOTEADO CON LSER Y LA CUANTIFICACIN EN TIEMPO REAL DE LA PERFUSIN INTESTINAL EN RESECCIONES COLORRECTALES DEL LADO IZQUIERDO MNIMAMENTE INVASIVAS: ANTECEDENTES:La cirugía colorrectal del lado izquierdo demuestra altas tasas de fuga anastomótica, y se cree que la isquemia tisular influye en los resultados. El verde de indocianina se utiliza habitualmente para evaluar la perfusión, pero la evidencia sobre si reduce las fugas anastomóticas colorrectales sigue siendo contradictoria. Las imágenes de contraste moteado con láser proporcionan una evaluación de la perfusión sin colorantes en tiempo real a través de mapas de calor de perfusión y cuantificación.OBJETIVO:Este estudio investiga la eficacia de la evaluación de la perfusión mediante visualización avanzada (verde de indocianina versus imágenes de contraste moteado con láser) y la utilidad de la cuantificación de la perfusión con moteado láser para determinar los márgenes isquémicos.DISEÑO:Grupo de intervención prospectivo que utiliza visualización avanzada con un grupo de control retrospectivo de casos emparejados.LUGARES:Centro médico académico único.PACIENTES:Cuarenta pacientes adultos sometidos a cirugía colorrectal electiva, mínimamente invasiva, del lado izquierdo.INTERVENCIONES:Evaluación de la perfusión intraoperatoria mediante imágenes con luz blanca y visualización avanzada en tres puntos temporales: T1-colon proximal después de la devascularización, antes de la transección; T2-colon proximal/distal antes de la anastomosis; y T3-anastomosis completa.PRINCIPALES MEDIDAS DE VALORACIÓN:Indicación intraoperatoria de la línea de demarcación isquémica antes de la resección bajo cada método de visualización, cambio de decisión quirúrgica mediante visualización avanzada, cuantificación post-hoc de la perfusión con láser moteado del tejido colorrectal y resultados posoperatorios a los 30 días.RESULTADOS:La visualización avanzada cambió la toma de decisiones quirúrgicas en el 17,5% de los casos. Para los casos en los que los cirujanos cambiaron una decisión, la discordancia promedio entre la línea de demarcación en las imágenes con luz blanca y la visualización avanzada fue de 3,7 cm, en comparación con 0,41 cm (p = 0,01) para los casos sin cambios de decisión. No hubo diferencias estadísticas entre la línea de demarcación isquémica utilizando láser moteado versus verde de indocianina (p = 0,16). El moteado con láser cuantificó valores de perfusión más bajos para los tejidos más allá de la línea de demarcación isquémica y al mismo tiempo sugirió 1 cm adicional de tejido perfundido más allá de esta línea. Se produjo una fuga anastomótica (2,5%) en el grupo de intervención.LIMITACIONES:Este estudio no tuvo el poder estadístico suficiente para detectar diferencias en las tasas de fuga anastomótica.CONCLUSIONES:La visualización avanzada utilizando moteado láser y verde de indocianina proporciona información valiosa sobre la perfusión que impacta la toma de decisiones quirúrgicas en cirugías colorrectales mínimamente invasivas del lado izquierdo. (Traducción-Dr. Ingrid Melo).

Initial experience with enhanced recovery after surgery (ERAS) and early discharge protocols after robotic extended totally extraperitoneal (eTEP) hernia surgery.

BACKGROUND: Though robotic adoption for eTEP surgery has decreased technical barriers to minimally invasive repairs of large ventral hernias, relatively few studies have examined outcomes of robotic-specific eTEP surgery. This study evaluates safety, feasibility, and early outcomes of ERAS/same-day discharge protocols for robotic eTEP ventral hernia repairs. METHODS: A retrospective chart review was performed for all robotic eTEP hernia surgeries at a single institution between 2019 and 2022. Analysis included patient demographics, hernia characteristics, intraoperative data, and post-operative outcomes at 30 days. ERAS protocol included: judicious use of urinary catheters with removal at end of case if placed, bilateral transversus abdominus plane (TAP) blocks, post-operative abdominal wall binder, and opioid-sparing perioperative analgesia. Patients were discharged same day from post-anesthesia care unit (PACU) if they lacked comorbidities requiring observation post-anesthesia and demonstrated stable vital signs, adequate pain control, ability to void, and ability to ambulate. Hospital length of stay (LOS) was considered 0 for same-day PACU discharges or hospitalizations < 24 h. RESULTS: 102 patients were included in this case series. 69% (70/102) of patients were discharged same-day (mean LOS 0.47 ± 0.80 days). Within 30 post-operative days, 3% (3/102) of patients presented to the ER, 2% (2/102) were readmitted to the hospital, and 1% (1/102) required reoperation. There was 1 serious complication (Clavien-Dindo grade 3/4) with an aggregate complication rate of 7.8%. CONCLUSIONS: Our initial experience with ERAS protocols and same-day discharges after robotic eTEP repair demonstrates this approach is safe and feasible with acceptable short-term patient outcomes. Compared to traditional open surgery for large ventral hernias, robotic eTEP may enable significant reductions in hospital LOS as adoption increases.

Utility and usability of laser speckle contrast imaging (LSCI) for displaying real-time tissue perfusion/blood flow in robot-assisted surgery (RAS): comparison to indocyanine green (ICG) and use in laparoscopic surgery.

BACKGROUND: Utility and usability of laser speckle contrast imaging (LSCI) in detecting real-time tissue perfusion in robot-assisted surgery (RAS) and laparoscopic surgery are not known. LSCI displays a color heatmap of real-time tissue blood flow by capturing the interference of coherent laser light on red blood cells. LSCI has advantages in perfusion visualization over indocyanine green imaging (ICG) including repeat use on demand, no need for dye, and no latency between injection and display. Herein, we report the first-in-human clinical comparison of a novel device combining proprietary LSCI processing and ICG for real-time perfusion assessment during RAS and laparoscopic surgeries. METHODS: ActivSight™ imaging module is integrated between a standard laparoscopic camera and scope, capable of detecting tissue blood flow via LSCI and ICG in laparoscopic surgery. From November 2020 to July 2021, we studied its use during elective robotic-assisted and laparoscopic cholecystectomies, colorectal, and bariatric surgeries (NCT# 04633512). For RAS, an ancillary laparoscope with ActivSight imaging module was used for LSCI/ICG visualization. We determined safety, usability, and utility of LSCI in RAS vs. laparoscopic surgery using end-user/surgeon human factor testing (Likert scale 1-5) and compared results with two-tailed t tests. RESULTS: 67 patients were included in the study-40 (60%) RAS vs. 27 (40%) laparoscopic surgeries. Patient demographics were similar in both groups. No adverse events to patients and surgeons were observed in both laparoscopic and RAS groups. Use of an ancillary laparoscopic system for LSCI/ICG visualization had minimal impact on usability in RAS as evidenced by surgeon ratings of device usability (set-up 4.2/5 and form-factor 3.8/5). LSCI ability to detect perfusion (97.5% in RAS vs 100% in laparoscopic cases) was comparable in both RAS and laparoscopic cases. CONCLUSIONS: LSCI demonstrates comparable utility and usability in detecting real-time tissue perfusion/blood flow in RAS and laparoscopic surgery.

Real-time quantification of intestinal perfusion and arterial versus venous occlusion using laser speckle contrast imaging in porcine model.

PURPOSE: Real-time intraoperative perfusion assessment may reduce anastomotic leaks. Laser speckle contrast imaging (LSCI) provides dye-free visualization of perfusion by capturing coherent laser light scatter from red blood cells and displays perfusion as a colormap. Herein, we report a novel method to precisely quantify intestinal perfusion using LSCI. METHODS: ActivSight™ is an FDA-cleared multi-modal visualization system that can detect and display perfusion via both indocyanine green imaging (ICG) and LSCI in minimally invasive surgery. An experimental prototype LSCI perfusion quantification algorithm was evaluated in porcine models. Porcine small bowel was selectively devascularized to create regions of perfused/watershed/ischemic bowel, and progressive aortic inflow/portal vein outflow clamping was performed to study arterial vs. venous ischemia. Continuous arterial pressure was monitored via femoral line. RESULTS: LSCI perfusion colormaps and quantification distinguished between perfused, watershed, and ischemic bowel in all vascular control settings: no vascular occlusion (p < 0.001), aortic occlusion (p < 0.001), and portal venous occlusion (p < 0.001). LSCI quantification demonstrated similar levels of ischemia induced both by states of arterial inflow and venous outflow occlusion. LSCI-quantified perfusion values correlated positively with higher mean arterial pressure and with increasing distance from ischemic bowel. CONCLUSION: LSCI relative perfusion quantification may provide more objective real-time assessment of intestinal perfusion compared to conventional naked eye assessment by quantifying currently subjective gradients of bowel ischemia and identifying both arterial/venous etiologies of ischemia.

Real-time quantification of bowel perfusion using Laparoscopic Laser Speckle Contrast Imaging (LSCI) in a porcine model.

BACKGROUND/PURPOSE: Real-time quantification of tissue perfusion can improve intraoperative surgical decision making. Here we demonstrate the utility of Laser Speckle Contrast Imaging as an intra-operative tool that quantifies real-time regional differences in intestinal perfusion and distinguishes ischemic changes resulting from arterial/venous obstruction. METHODS: Porcine models (n = 3) consisted of selectively devascularized small bowel loops that were used to measure the perfusion responses under conditions of control/no vascular occlusion, arterial inflow occlusion, and venous outflow occlusion using laser speckle imaging and indocyanine green fluoroscopy. Laser Speckle was also used to assess perfusion differences between small bowel antimesenteric-antimesenteric and mesenteric-mesenteric anastomoses. Perfusion quantification was measured in relative perfusion units calculated from the laser speckle perfusion heatmap. RESULTS: Laser Speckle distinguished between visually identified perfused, watershed, and ischemic intestinal segments with both color heatmap and quantification (p < .00001). It detected a continuous gradient of relative intestinal perfusion as a function of distance from the stapled ischemic bowel edge. Strong positive linear correlation between relative perfusion units and changes in mean arterial pressure resulting from both arterial (R2 = .96/.79) and venous pressure changes (R2 = .86/.96) was observed. Furthermore, Laser Speckle showed that the antimesenteric anastomosis had a higher perfusion than mesenteric anastomosis (p < 0.01). CONCLUSIONS: Laser Speckle Contrast Imaging provides objective, quantifiable tissue perfusion information in both color heatmap and relative numerical units. Laser Speckle can detect spatial/temporal differences in perfusion between antimesenteric and mesenteric borders of a bowel segment and precisely detect perfusion changes induced by progressive arterial/venous occlusions in real-time.