Stanley Kisinde1, Xiaobang Hu2, Shea Hesselbacher1, Isador H Lieberman3. 1. Scoliosis and Spine Tumor Center, Texas Back Institute, 6020 West Parker Road, Suite 200A, Plano, TX, 75093, USA. 2. University of Texas South Western Medical Center, Dallas, TX, 75390, USA. 3. Scoliosis and Spine Tumor Center, Texas Back Institute, 6020 West Parker Road, Suite 200A, Plano, TX, 75093, USA. ilieberman@texasback.com.
Abstract
BACKGROUND: Navigation and robotic-guided systems are being used more often to facilitate efficient and accurate placement of hardware during spinal surgeries. Preoperative surgical planning is a key step in the safe use of these tools. No studies have yet investigated the predictive accuracy of surgical planning using a robotic guidance system. METHODS: Data were prospectively collected from patients in whom Mazor X-Align ™ [Medtronic Inc., Minneapolis, MN., USA] robotic guidance system software was used to plan their spinal instrumentation in order to achieve the best possible correction and the plans executed intraoperatively under robotic guidance. RESULTS: A total of 33 patients (26 females, 7 males) were included. Their mean age was 51 years (12-79), and their mean BMI was 23.90 (15.55-35.91). Their primary diagnoses were scoliosis (20), kyphosis (5), spondylolisthesis (4), adjacent segment degeneration (3), and metastatic tumor (1). Preoperatively, the patients' mean coronal Cobb Angle (CA) was 36.5 ± 14.4°, and their mean sagittal CA was 27.7 ± 20.0°. The mean planned correction coronal CA was 0.2 ± 1.2°, and the mean planned correction sagittal CA was 28.4 ± 16.7°. Postoperatively, the patients' mean coronal CA that was achieved was 5.8 ± 7.4°, and their mean sagittal CA was 31.0 ± 18.3°. The mean difference between the planned and achieved angles was 5.5 ± 7.4° for the coronal, and 9.03 ± 9.01° for the sagittal CA. For the thoracic kyphosis and lumbar lordosis, the mean difference between the planned and postoperatively measured values was 15.3 ± 10.8 and 12.8 ± 9.6, respectively. CONCLUSION: This study indicates that the predictive accuracy of the use of preoperative planning software and robotic guidance to facilitate the surgical plan is within 6° and 9° in the coronal and sagittal planes, respectively.
BACKGROUND: Navigation and robotic-guided systems are being used more often to facilitate efficient and accurate placement of hardware during spinal surgeries. Preoperative surgical planning is a key step in the safe use of these tools. No studies have yet investigated the predictive accuracy of surgical planning using a robotic guidance system. METHODS: Data were prospectively collected from patients in whom Mazor X-Align ™ [Medtronic Inc., Minneapolis, MN., USA] robotic guidance system software was used to plan their spinal instrumentation in order to achieve the best possible correction and the plans executed intraoperatively under robotic guidance. RESULTS: A total of 33 patients (26 females, 7 males) were included. Their mean age was 51 years (12-79), and their mean BMI was 23.90 (15.55-35.91). Their primary diagnoses were scoliosis (20), kyphosis (5), spondylolisthesis (4), adjacent segment degeneration (3), and metastatic tumor (1). Preoperatively, the patients' mean coronal Cobb Angle (CA) was 36.5 ± 14.4°, and their mean sagittal CA was 27.7 ± 20.0°. The mean planned correction coronal CA was 0.2 ± 1.2°, and the mean planned correction sagittal CA was 28.4 ± 16.7°. Postoperatively, the patients' mean coronal CA that was achieved was 5.8 ± 7.4°, and their mean sagittal CA was 31.0 ± 18.3°. The mean difference between the planned and achieved angles was 5.5 ± 7.4° for the coronal, and 9.03 ± 9.01° for the sagittal CA. For the thoracic kyphosis and lumbar lordosis, the mean difference between the planned and postoperatively measured values was 15.3 ± 10.8 and 12.8 ± 9.6, respectively. CONCLUSION: This study indicates that the predictive accuracy of the use of preoperative planning software and robotic guidance to facilitate the surgical plan is within 6° and 9° in the coronal and sagittal planes, respectively.
Authors: Michael Akbar; Jamie Terran; Christopher P Ames; Virginie Lafage; Frank Schwab Journal: Neurosurg Clin N Am Date: 2013-04 Impact factor: 2.509
Authors: Mohammed F Shamji; Stephen Parker; Chad Cook; Ricardo Pietrobon; Christopher Brown; Robert E Isaacs Journal: Neurosurgery Date: 2009-09 Impact factor: 4.654