Navigation-Assisted Surgery for Locally Advanced Primary and Recurrent Rectal Cancer

Abstract

Background: In some surgical disciplines, navigation-assisted surgery has become standard of care, but in rectal cancer, indications for navigation and the utility of different technologies remain undetermined.

Methods: The NAVI-LARRC prospective study (NCT04512937; IDEAL Stage 2a) evaluated feasibility of navigation in patients with locally advanced primary (LARC) and recurrent rectal cancer (LRRC). Included patients had advanced tumours with high risk of incomplete (R1/R2) resection, and navigation was considered likely to improve the probability of complete resection (R0). Tumours were classified according to pelvic compartmental involvement, as suggested by the Royal Marsden group. The Brainlab^TM navigation platform was used for preoperative segmentation of tumour and pelvic anatomy, and for intraoperative navigation with optical tracking. R0 resection rates, surgeons' experiences, and adherence to the preoperative resection plan were assessed.

Results: Seventeen patients with tumours involving the posterior/lateral compartments underwent navigation-assisted procedures. Fifteen patients required abdominosacral resection, and 3 had resection of the sciatic nerve. R0 resection was obtained in 6/8 (75%) LARC and 6/9 (69%) LRRC cases. Preoperative segmentation was time-consuming (median 3.5 h), but intraoperative navigation was accurate. Surgeons reported navigation to be feasible, and adherence to the resection plan was satisfactory.

Conclusions: Navigation-assisted surgery using optical tracking was feasible. The preoperative planning was time-consuming, but intraoperative navigation was accurate and resulted in acceptable R0 resection rates. Selected patients are likely to benefit from navigation-assisted surgery.

Keywords: Feasibility study; Image-guided surgery; Locally advanced rectal cancer; Locally recurrent rectal cancer; Navigation-assisted surgery; Optical tracking.

Fig. 1

Preoperative segmentation and virtual 3-dimensional (3D) model. a Tumour (red) and the adjacent S2 nerve (yellow) manually segmented on axial MRI. b Axial CT image. c Segmented structures transposed to axial CT image after fusion of MRI and CT. d Virtual 3D model with automatically segmented pelvic bone and manually segmented tumour and S2 nerve

Fig. 2

Intraoperative imaging. a Camera (red arrow) for optical tracking (with infrared light) of reflective spheres, on the fluoroscopy unit b and the patient tracker c. The position of fluoroscopy image data was registered relative to the patient tracker during image acquisition

Fig. 3

Intraoperative navigation. a Reflective spheres on chisel. b Reflective spheres on patient tracker. c Resection of the sciatic spine using a navigated chisel. d The chisel visualised in the 3D model. e The chisel visualised in the axial CT image containing the tip of the chisel

Fig. 4

Surgeons’ responses to statements in questionnaire. The numbers indicate the number of a given response to a statement (percentages relative to the total number of responses to that statement)

Fig. 5

Structures identified and resected with navigation. a Sagittal CT image with navigated chisel resecting the sacrum S4, cranial to the tumour (red). b Axial CT image with navigated chisel identifying the right sacral neuroforamen S3. c Axial CT image with navigated chisel during resection of the right sciatic spine lateral to the tumour (red). d 3D model with navigated pointer (green) identifying the S2 nerve (yellow) distal to the tumour (red)