Utility of Artificial Intelligence for Real-Time Anatomical Landmark Identification in Ultrasound-Guided Thoracic Paravertebral Block

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 , …”

“…In the available sources, a variety of human image interpretation was used as the ground truth. This included a range in the number of humans used in the ground truth from one, 7 , 23 , 24 , 25 , 31 , 32 , 34 , 35 , 36 , 38 , 46 , 49 , 58 , 60 , 67 , 72 , 77 two, 8 , 9 , 19 , 21 , 26 , 30 , 33 , 44 , 61 three, 51 , 52 , 53 , 63 , 65 and up to 15. 48 Some sources cited ‘multiple’ humans, used a plural term (e.g.…”

“…Sources described their ground truth human(s) as a volunteer, 64 doctor/physician, 48 , 52 , 63 , 65 sonographer, 7 , 30 , 31 , 32 , 33 , 34 , 35 , 60 , 75 , 77 clinical professional, 27 , 38 or (regional) anaesthetist. 8 , 17 , 18 , 19 , 20 , 21 , 23 , 25 , 26 , 36 , 44 , 45 , 46 , 49 , 51 , 53 , 54 , 58 , 61 , 62 , 67 , 69 The level of expertise of those providing the ground truth was described as trained, 64 experienced, 21 , 30 , 31 , 32 , 33 , 34 , 46 , 48 , 52 , 65 expert, 7 , 8 , 17 , 18 , 19 , 20 , 25 , 26 , 27 , 33 , …”

“…The most common output for models processing PNB ultrasound images was segmentation (the outline/colour overlay of features in the image). 9 , 11 , 12 , 19 , 20 , 22 , 23 , 25 , 27 , 36 , 38 , 39 , 40 , 41 , 42 , 43 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 57 , 58 , 59 , 60 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 71 , 72 , 78 , 79 Less common outputs included the use of bounding boxes to identify the location of the structure, 8 , 17 , 18 , 26 , 61 attempting to locate the centre of a nerve and placing expanding circular rings from the centre, 21 or placing name tags over structures in question. 9 , 43 , 45 , 47 , 50 …”

“…the outline of a blood vessel) were intersection over union (IoU; Jaccard similarity coefficient) and the Dice similarity coefficient. 8 , 17 , 18 , 19 , 20 , 23 , 25 , 27 , 28 , 38 , 42 , 46 , 49 , 51 , 52 , 53 , 54 , 55 , 57 , 58 , 59 , 60 , 62 , 63 , 64 , 65 , 66 , 68 , 69 , 71 , 79 The Hausdorff metric/distance was used to compare the proximity of lines (e.g. a fascial plane).…”