A novel ultrasound software system for lumbar level identification in obstetric patients.

PURPOSE: Using machine learning, we developed a proprietary ultrasound software called the Spine Level Identification (SLIDE) system, which automatically identifies lumbar landmarks in real time as the operator slides the transducer over the lumber spine. Here, we assessed the agreement between SLIDE and manual palpation and traditional lumbar ultrasound (LUS) for determining the primary target L3-4 interspace. METHODS: Upon institutional ethics approval and informed consent, 76 healthy term parturients scheduled for elective Caesarean delivery were recruited. The L3-4 interspace was identified by manual palpation and then by the SLIDE method. The reference standard was located using traditional LUS by an experienced operator. The primary outcome was the L3-4 interspace identification agreement of manual palpation and SLIDE with the reference standard, as percentage agreement and Gwet's agreement coefficient (AC1). RESULTS: The raw agreement was 70% with Gwet's agreement coefficient (AC1) = 0.59 (95% confidence interval [CI], 0.41 to 0.77) for manual palpation and 84% with Gwet's AC1 = 0.82 (95% CI, 0.70 to 0.93) for SLIDE. When the levels differ from the reference, the manual palpation method identified L2-3 more often than L4-5 while the SLIDE method identified equally above or below L3-4. The SLIDE system had greater agreement than palpation in locating L3-4 and all other lumber interspaces after controlling for body mass index (adjusted odds ratio, 2.99; 95% CI, 1.21 to 8.7; P = 0.02). CONCLUSION: The SLIDE system had higher agreement with traditional ultrasound than manual palpation did in identifying L3-4 and all other lumber interspaces after adjusting for BMI in healthy term obstetric patients. Future studies should examine factors that affect agreement and ways to improve SLIDE for clinical integration. STUDY REGISTRATION: www. CLINICALTRIALS: gov (NCT02982317); registered 5 December 2016.

RéSUMé: OBJECTIF: À l'aide de l'apprentissage automatique, nous avons développé un logiciel d'échographie propriétaire appelé SLIDE (pour Spine Level Identification, c.-à-d. système d'identification du niveau vertébral), qui identifie automatiquement les points de repère lombaires en temps réel lorsque l'opérateur fait passer le transducteur sur la colonne lombaire. Ici, nous avons évalué l'agrément entre le SLIDE et la palpation manuelle et l'échographie lombaire traditionnelle pour déterminer l'espace intervertébral cible principal L3­L4. MéTHODE: Après avoir obtenu l'approbation du comité d'éthique de l'établissement et le consentement éclairé, 76 parturientes en bonne santé et à terme devant bénéficier d'un accouchement par césarienne programmée ont été recrutées. L'espace intervertébral L3­L4 a été identifié par palpation manuelle puis avec le logiciel SLIDE. L'étalon de référence a été localisé à l'aide d'une échographie lombaire traditionnelle par un opérateur expérimenté. Le critère d'évaluation principal était l'agrément entre l'identification de l'espace intervertébral L3­L4 par palpation manuelle et par logiciel SLIDE avec l'étalon de référence, en pourcentage d'agrément et coefficient d'agrément de Gwet (CA1). RéSULTATS: L'agrément brut était de 70 % avec le coefficient d'agrément de Gwet (CA1) = 0,59 (intervalle de confiance [IC] à 95 %, 0,41 à 0,77) pour la palpation manuelle et de 84 % avec le CA1 de Gwet = 0,82 (IC 95 %, 0,70 à 0,93) pour le logiciel SLIDE. Lorsque les niveaux lombaires différaient de la référence, la méthode de palpation manuelle a identifié L2­L3 plus souvent que L4­L5, tandis que la méthode SLIDE a identifié les vertèbres supérieures ou inférieures à L3­L4 de manière égale. Le système SLIDE a affiché un agrément plus important que la palpation pour localiser L3­L4 et tous les autres espaces intervertébraux lombaires après ajustement pour tenir compte de l'indice de masse corporelle (rapport de cotes ajusté, 2,99; IC 95 %, 1,21 à 8,7; P = 0,02). CONCLUSION: Le système SLIDE avait affiché un agrément plus élevé avec l'échographie traditionnelle que la palpation manuelle pour identifier le niveau L3­L4 et tous les autres espaces intervertébraux lombaires après ajustement pour tenir compte de l'IMC chez les patientes obstétricales à terme en bonne santé. Une étude future devrait examiner les facteurs qui affectent l'agrément et les moyens d'améliorer le logiciel SLIDE pour une intégration clinique. ENREGISTREMENT DE L'éTUDE: www.clinicaltrials.gov (NCT02982317); enregistrée le 5 décembre 2016.

Artificial intelligence enhanced ultrasound (AI-US) in a severe obese parturient: a case report.

BACKGROUND: Neuraxial anesthesia in obese parturients can be challenging due to anatomical and physiological modifications secondary to pregnancy; this led to growing popularity of spine ultrasound in this population for easing landmark identification and procedure execution. Integration of Artificial Intelligence with ultrasound (AI-US) for image enhancement and analysis has increased clinicians' ability to localize vertebral structures in patients with challenging anatomical conformation. CASE PRESENTATION: We present the case of a parturient with extremely severe obesity, with a Body Mass Index (BMI) = 64.5 kg/m2, in which the AI-Enabled Image Recognition allowed a successful placing of an epidural catheter. CONCLUSIONS: Benefits gained from AI-US implementation are multiple: immediate recognition of anatomical structures leads to increased first-attempt success rate, making easier the process of spinal anesthesia execution compared to traditional palpation methods, reducing needle placement time for spinal anesthesia and predicting best needle direction and target structure depth in peridural anesthesia.

Point of Care Ultrasound on Labor and Delivery.

Point of care ultrasound (POCUS) in the field of obstetric anesthesiology, including cardiac, pulmonary, neuraxial, gastric, and airway ultrasound, can facilitate rapid diagnosis, management, and clinical decision-making surrounding common maternal peripartum comorbidities, and obstetric complications. Routine and proficient utilization of POCUS can ultimately aid in anesthesiologists' role as critical care physicians in the multidisciplinary practice on labor and delivery, with potential future research aiming to determine the potential impact on maternal morbidity and mortality.

Feasibility of Spinal Anesthesia Placement Using Automated Interpretation of Lumbar Ultrasound Images: A Prospective Randomized Controlled Trial.

BACKGROUND: This study evaluated the efficacy of spinal anesthesia administration by resident physicians when using an ultrasound system with automated neuraxial landmark detection capabilities. METHODS: 150 patients were enrolled in this trial. Anesthesiology residents placed spinals in subjects undergoing scheduled cesarean delivery using one of three techniques to identify neuraxial landmarks: palpation, ultrasound, or combined palpation and ultrasound. Ultrasound was performed using a handheld system that automatically identified neuraxial landmarks (e.g. midline, intervertebral spaces). All residents watched a 10-minute video and received 20 minutes of hands-on training prior to participating in the study. First insertion success rate was the primary end point. RESULTS: Among all patients, use of ultrasound resulted in a 11% greater first-insertion success rate (RR: 1.11 [0.85-1.47], p=0.431), a 15% reduction in needle insertions (RR: 0.85, p=0.052), and a 26% decrease in needle passes (RR: 0.74, p=0.070). In obese patients of BMI ≥ 30 kg/m2, use of ultrasound resulted in 26% greater first-insertion success rates (RR: 1.26, p=0.187), a 21% decrease in needle insertions (RR: 0.79, p=0.025), a 38% decrease in needle passes (RR: 0.62, p=0.030), and a 75% decrease in patients reporting neutral or low patient satisfaction with anesthesia administration (RR: 0.25, p=0.004). DISCUSSION: Resident anesthesiologists competently utilized the ultrasound system after receiving minimal training. Technical endpoints and patient satisfaction trended towards improvement when ultrasound was used prior to spinal placement, with stronger trends observed in obese patients. Additional study is required to fully characterize the impact of the ultrasound system on clinical efficacy.