CE-NC-VesselSegNet: Supervised by contrast-enhanced CT images but utilized to segment pulmonary vessels from non-contrast-enhanced CT images

BackgroundSurgery, including lobectomy and segmentectomy, is the major curative intervention for lung cancer. Surgical planning for pulmonary surgery is difficult due to the high variation rate of pulmonary arteries and needs a fine-grained atlas as a reference. We conducted a study to create a surgically oriented atlas and analyzed the error encountered during the production.MethodA total of 100 Chest CTs performed at Peking University People’s Hospital from 2013.09 to 2020.10 were randomly selected for segmental artery labeling. Dicom files were collected for 3D reconstruction. Manual segmentation of each segmental artery was performed by 4 thoracic surgeons. Cross-validation by surgeons was performed to establish the golden standard based on their consensus. Initial recognition errors were recorded accordingly.ResultThe most frequently seen variants for the right upper lobe is 2-branch RA1+2rec+3 and RA2asc; right middle lobe 2-branch RA4a and RA4b+5; right lower lobe 3-branch RA7, RA8 and RA9+10; left upper lobe 3-branch LA1+2a+3, LA1+2b, LA1+2c and 1-branch LA4+5; left lower lobe 2-branch LA8 and LA9+10. Top 5 segmental error occurs in RA4 (23%), LA8 (17%), RA9 (17%), RA8 (14%) and LA9 (11%). A rapid surgical planning tool form was created based on high frequency anatomic variants.ConclusionOur research provided an atlas for lobectomy and segmentectomy at the subsegmental or more distal level. We demonstrated that the recognition accuracy of pulmonary arteries in a non-time-sensitive experimental scenario was still unfavorable. We also suggest that extra attention should be paid to certain surgeries during the surgical planning process.

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“…has proved the technical feasibility ( 16 ), Wang etc. ( 17 ) and Li etc. ( 18 ) also provided clinically feasible algorithms.…”

Section: Discussionmentioning

confidence: 99%