Reduction of inter-observer differences in the delineation of the target in spinal metastases SBRT using an automatic contouring dedicated system

Abstract

Background Approximately one third of cancer patients will develop spinal metastases, that can be associated with back pain, neurological symptoms and deterioration in performance status. Stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) have been offered in clinical practice mainly for the management of oligometastatic and oligoprogressive patients, allowing the prescription of high total dose delivered in one or few sessions to small target volumes, minimizing the dose exposure of normal tissues. Due to the high delivered doses and the proximity of critical organs at risk (OAR) such as the spinal cord, the correct definition of the treatment volume becomes even more important in SBRT treatment, thus making it necessary to standardize the method of target definition and contouring, through the adoption of specific guidelines and specific automatic contouring tools. An automatic target contouring system for spine SBRT is useful to reduce inter-observer differences in target definition. In this study, an automatic contouring tool was evaluated. Methods Simulation CT scans and MRI data of 20 patients with spinal metastases were evaluated. To evaluate the advantage of the automatic target contouring tool (Elements SmartBrush Spine), which uses the identification of different densities within the target vertebra, we evaluated the agreement of the contours of 20 spinal target (2 cervical, 9 dorsal and 9 lumbar column), outlined by three independent observers using the automatic tool compared to the contours obtained manually, and measured by DICE similarity coefficient. Results The agreement of GTV contours outlined by independent operators was superior with the use of the automatic contour tool compared to manually outlined contours (mean DICE coefficient 0.75 vs 0.57, p = 0.048). Conclusions The dedicated contouring tool allows greater precision and reduction of inter-observer differences in the delineation of the target in SBRT spines. Thus, the evaluated system could be useful in the setting of spinal SBRT to reduce uncertainties of contouring increasing the level of precision on target delivered doses.

Clinical Evaluation of an Auto-Segmentation Tool for Spine SBRT Treatment

“…For a spine SBRT approach, correct definition of the treatment volume becomes even more important due to the nature of this treatment with high dose delivery per fraction and the proximity of critical OARs such as the spinal cord. Many studies have already demonstrated that inter-observer variability can be reduced by using the auto-segmentation tool ( 18 ). Our study also supports the findings.…”

“…Moreover, the autosegmentation tool Elements SmartBrush Spine (ESS) was developed for fast target delineation, which can potentially improve the efficiency of the clinical workflow. Giaj−Levra et al have demonstrated that the inter-observer difference can be reduced by using ESS (18) by evaluating the GTV contours. The aim of this study is to evaluate the accuracy of the CTV autosegmentation based on existing GTV contours using ESS for spine SBRT patients.…”

“…Giaj−Levra et al. have demonstrated that the inter-observer difference can be reduced by using ESS ( 18 ) by evaluating the GTV contours. The aim of this study is to evaluate the accuracy of the CTV auto-segmentation based on existing GTV contours using ESS for spine SBRT patients.…”

Evaluation of a Dedicated Software “Elements™ Spine SRS, Brainlab®” for Target Volume Definition in the Treatment of Spinal Bone Metastases With Stereotactic Body Radiotherapy

“…Giaj-Levra et al. evaluated in a recent study the advantage of the new automatic target contouring tool (Elements Spine SRS, Brainlab ® ) for the definition of GTV ( 16 ). Using data of 20 patients with spinal metastases outlined by three independent observers, they showed that the agreement of GTV contours outlined by independent observers was superior with the use of the automatic tool compared to manually outlined contours (mean Dice coefficient 0.75 vs. 0.57, p = 0.048).…”

Man versus machine: Automatic pedicle screw planning using registration‐based techniques compared with manual screw planning for thoracolumbar fusion surgeries

“…metastasis and head-neck cancer treatment planning. [25][26][27] In addition, automatic segmentation of vertebrae is facilitated by augmented reality applications and intraoperative ultrasound in intradural spinal tumour surgery in order to enhance image interpretation and thereby to support the surgeon during the surgical procedure. 28,29…”