Brachial Plexus Nerve Trunk Segmentation Using Deep Learning: A Comparative Study with Doctors' Manual Segmentation

Abstract

Ultrasound-guided nerve block anesthesia (UGNB) is a high-tech visual nerve block anesthesia method that can observe the target nerve and its surrounding structures, the puncture needle's advancement, and local anesthetics spread in real-time. The key in UGNB is nerve identification. With the help of deep learning methods, the automatic identification or segmentation of nerves can be realized, assisting doctors in completing nerve block anesthesia accurately and efficiently. Here, we establish a public dataset containing 320 ultrasound images of brachial plexus (BP). Three experienced doctors jointly produce the BP segmentation ground truth and label brachial plexus trunks. We design a brachial plexus segmentation system (BPSegSys) based on deep learning. BPSegSys achieves experienced-doctor-level nerve identification performance in various experiments. We evaluate BPSegSys' performance in terms of intersection-over-union (IoU), a commonly used performance measure for segmentation experiments. Considering three dataset groups in our established public dataset, the IoU of BPSegSys are 0.5238, 0.4715, and 0.5029, respectively, which exceed the IoU 0.5205, 0.4704, and 0.4979 of experienced doctors. In addition, we show that BPSegSys can help doctors identify brachial plexus trunks more accurately, with IoU improvement up to 27%, which has significant clinical application value.

Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines

“…Early approaches, most published before 2016–17, typically involved steps of feature extraction from the ultrasound image, followed by classification of these features, for both PNB 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 and CNB. 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 Around this point, there has been an increase in published data where the dominant technique was deep learning for both PNB 9 , 11 , 12 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 and CNB, 7 , 74 , 75 , …”

Brachial Plexus Nerve Trunk Recognition From Ultrasound Images: A Comparative Study of Deep Learning Models

“…To obtain brachial plexus ultrasound images, we cooperate with the Affiliated Hospital of Medicine School of Ningbo University and the Sixth Hospital of Ningbo to collect 340 brachial plexus ultrasound images [25]. To increase the heterogeneity of the data, we collect data from as many patients as possible rather than multiple images from the same patient.…”

“…It is worth noting that all current studies in brachial plexus identification are to segment a nerve block region rather than individual nerve trunks. However, compared with segmenting only a nerve block region, segmenting individual nerve trunks can assist doctors in locating the position of each brachial plexus trunk more accurately to improve the effectiveness of the brachial plexus block [25]. Therefore, in this study, we segment individual brachial plexus trunks.…”

“…Therefore, in this study, we segment individual brachial plexus trunks. We use a new dataset containing 340 ultrasound images of brachial plexus and labeled by three clinicians [25]. Then we implement 12 deep learning models and comprehensively evaluate their performance from the following aspects to find the model and training strategy suitable for this nerve segmentation task.…”

Optimal View Detection for Ultrasound-guided Supraclavicular Block using Deep Learning Approaches

“…7 Pneumothorax can also be prevented, as the rst rib may act as a barrier to prevent the needle from being directed into the pleura. 8 Techniques for the segmentation and detection of the BP 9,10 or its identi cation at the interscalene level have been described, 11,12 as have arti cial intelligence (AI)-based computer-aided diagnosis (CADx) systems that assist nerve block, including SCB. 13 These studies, however, simply focused identi cation of anatomical structures on the ultrasound.…”