CT and MRI scans are complementary preoperative imaging investigations for planning complex musculoskeletal bone tumours resection and reconstruction. Conventionally, tumour surgeons analyse two-dimensional (2-D) imaging information, mentally integrate and formulate a three-dimensional (3-D) surgical plan. Difficulties are anticipated with increase in case complexity and distorted surgical anatomy. Incorporating computer technology to aid in this surgical planning and executing the intended resection may improve precision. Although computer-assisted surgery has been widely used in cranial biopsies and tumour resection, only small case series using CT-based navigation are recently reported in the field of musculoskeletal tumor surgery. We investigated the results of CT/MRI image fusion for Computer Assisted Tumor Surgery (CATS) with the help of a navigation system.

We studied 21 patients with 22 musculoskeletal tumours who underwent CATS from March 2006 to July 2009. A commercially available CT-based spine navigation system (Stryker Navigation; CT spine) was used. Of the 22 patients, 10 were males, 11 were females, and the mean age was 32 years at the time of surgery (range, 6–80 years). Five tumours were located in the pelvis, seven sacrum, eight femurs, and two tibia. The primary diagnosis was primary bone tumours in 16 (3 benign, 13 sarcoma) and metastatic carcinoma in four. The minimum follow-up was 17 months (average, 35.5 months; range, 17–52 months). Preoperative CT and MRI scan of each patient were performed. Axial CT slices of 0.0625mm or 1.25mm thickness and various sequences of MR images in Digital Imaging and Communications in Medicine (DICOM) format were obtained. CT and MR images for 22 cases were fused using the navigation software. All the reconstructed 2-D and 3-D images were used for preoperative surgical planning. The plane of tumour resection was defined and marked using multiple virtual screws sited along the margin of the planned resection. We also integrated the computer-aided design (CAD) data of custom-made prostheses in the final navigation resection planning for eight cases.

All tumour resections could be carried out as planned under navigation guidance. Navigation software enabled surgeons to examine all fused image datasets (CT/MRI scans) together in two spatial and three spatial dimensions. It allowed easier understanding of the exact anatomical tumor location and relationship with surrounding structures. Intraoperatively, image guidance with the help of fusion images, provided precise visual orientation, easy identification of tumor extent, neural structures and intended resection planes in all cases. The mean time for preoperative navigation planning was 1.85 hours (1 to 3.8). The mean time for intraoperative navigation procedures was 29.6 minutes (13 to 60). The time increased with case complexity but lessened with practice. The mean registration error was 0.47mm (0.31 to 0.8). The virtual preoperative images matched well with the patients' operative anatomy. A postoperative superficial wound infection developed in one patient with sacral chordoma that resolved with antibiotic whereas a wound infection in another with sacral osteosarcoma required surgical debridement and antibiotic. After a mean follow-up of 35.5 months (17–52 months), five patients died of distant metastases. Three out of four patients with local recurrence had tumors at sacral region. Three of them were soft tissue tumour recurrence. The mean functional MSTS score in patients with limb salvage surgery was 28.3 (23 to 30). All patients (except one) with limb sparing surgery and prosthetic reconstruction could walk without aids.

Multimodal image fusion yields hybrid images that combine the key characteristics of each image technique. Back conversion of custom prosthesis in CAD to DICOM format allowed fusion with navigation resection planning and prosthesis reconstruction in musculoskeletal tumours. CATS with image fusion offers advanced preoperative 3-D surgical planning and supports surgeons with precise intraoperative visualisation and identification of intended resection for pelvic, sacral tumors. It enables surgeons to reliably perform joint sparing intercalated tumor resection and accurately fit CAD custom-made prostheses for the resulting skeletal defect.