Background Neuraxial procedures are commonly performed for therapeutic and diagnostic indications. Currently, they are typically performed via palpation-guided surface landmark. We devised a novel intelligent image processing system that identifies spinal landmarks using ultrasound images. Our primary aim was to evaluate the first attempt success rate of spinal anesthesia using landmarks obtained from the automated spinal landmark identification technique. Methods In this prospective cohort study, we recruited 100 patients who required spinal anesthesia for surgical procedures. The video from ultrasound scan image of the L3/4 interspinous space in the longitudinal view and the posterior complex in the transverse view were recorded. The demographic and clinical characteristics were collected and analyzed based on the success rates of the spinal insertion. Results Success rate (95%CI) for dural puncture at first attempt was 92.0% (85.0–95.9%). Median time to detection of posterior complex was 45.0 [IQR: 21.9, 77.3] secs. There is good correlation observed between the program-recorded depth and the clinician-measured depth to the posterior complex (r = 0.94). Conclusions The high success rate and short time taken to obtain the surface landmark with this novel automated ultrasound guided technique could be useful to clinicians to utilise ultrasound guided neuraxial techniques with confidence to identify the anatomical landmarks on the ultrasound scans. Future research would be to define the use in more complex patients during the administration of neuraxial blocks. Trial registration This study was retrospectively registered on clinicaltrials.gov registry ( NCT03535155 ) on 24 May 2018.

There is predominantly moderate-certainty evidence that AMB is similar to BI for maintaining epidural analgesia for labour for all measured outcomes and may have the benefit of decreasing the risk of breakthrough pain and improving maternal satisfaction while decreasing the amount of local anaesthetic needed.

This paper presents an automatic lumbar spine level identification system based on image processing of ultrasound images. The goal is to aid anesthetists in identifying the correct spinal level during epidural anesthesia. Spine level identification is initiated by detecting the location of the sacrum using a classifier based on a support vector machine. Image stitching is then conducted to produce a panorama image of the spinal area. During this process, the location of spinal processes are enhanced using a Gabor filter and detected through template matching. The locations of the spinal processes are tracked and used as an overlay on the ultrasound image in real-time. The system then informs the anesthetists when the correct spinal level has been reached. The system was evaluated on forty volunteers by two anesthetists with varying experience level and was able to detect the correct position of the L3-L4 spinal level in all of the volunteers. The average time taken to produce the location of the L3-L4 spinal level was 30.92 seconds. The results show that the system can quickly and accurately detect the location of the target spinal level.

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Severe pulmonary hemorrhage occurred through the endotracheal tube during an emergency cesarean delivery. Intubation trauma was excluded with fiberoptic bronchoscopy. Episodes of hemoptysis continued for 48 hours. The patient was subsequently diagnosed with diffuse alveolar hemorrhage because of systemic lupus erythematosus. The diagnostic workup, successful management, and literature review are presented.