Sajendra Nithiananthan

Mobile C-arm cone-beam CT for guidance of spine surgery: Image quality, radiation dose, and integration with interventional guidance

PURPOSE A flat-panel detector based mobile isocentric C-arm for cone-beam CT (CBCT) has been developed to allow intraoperative 3D imaging with sub-millimeter spatial resolution and soft-tissue visibility. Image quality and radiation dose were evaluated in spinal surgery, commonly relying on lower-performance image intensifier based mobile C-arms. Scan protocols were developed for task-specific imaging at minimum dose, in-room exposure was evaluated, and integration of the imaging system with a surgical guidance system was demonstrated in preclinical studies of minimally invasive spine surgery. METHODS Radiation dose was assessed as a function of kilovolt (peak) (80-120 kVp) and milliampere second using thoracic and lumbar spine dosimetry phantoms. In-room radiation exposure was measured throughout the operating room for various CBCT scan protocols. Image quality was assessed using tissue-equivalent inserts in chest and abdomen phantoms to evaluate bone and soft-tissue contrast-to-noise ratio as a function of dose, and task-specific protocols (i.e., visualization of bone or soft-tissues) were defined. Results were applied in preclinical studies using a cadaveric torso simulating minimally invasive, transpedicular surgery. RESULTS Task-specific CBCT protocols identified include: thoracic bone visualization (100 kVp; 60 mAs; 1.8 mGy); lumbar bone visualization (100 kVp; 130 mAs; 3.2 mGy); thoracic soft-tissue visualization (100 kVp; 230 mAs; 4.3 mGy); and lumbar soft-tissue visualization (120 kVp; 460 mAs; 10.6 mGy) - each at (0.3  ×  0.3  ×  0.9 mm3 ) voxel size. Alternative lower-dose, lower-resolution soft-tissue visualization protocols were identified (100 kVp; 230 mAs; 5.1 mGy) for the lumbar region at (0.3  ×  0.3  ×  1.5 mm3 ) voxel size. Half-scan orbit of the C-arm (x-ray tube traversing under the table) was dosimetrically advantageous (prepatient attenuation) with a nonuniform dose distribution (∼2 ×  higher at the entrance side than at isocenter, and ∼3-4 lower at the exit side). The in-room dose (microsievert) per unit scan dose (milligray) ranged from ∼21 μSv/mGy on average at tableside to ∼0.1 μSv/mGy at 2.0 m distance to isocenter. All protocols involve surgical staff stepping behind a shield wall for each CBCT scan, therefore imparting ∼zero dose to staff. Protocol implementation in preclinical cadaveric studies demonstrate integration of the C-arm with a navigation system for spine surgery guidance-specifically, minimally invasive vertebroplasty in which the system provided accurate guidance and visualization of needle placement and bone cement distribution. Cumulative dose including multiple intraoperative scans was ∼11.5 mGy for CBCT-guided thoracic vertebroplasty and ∼23.2 mGy for lumbar vertebroplasty, with dose to staff at tableside reduced to ∼1 min of fluoroscopy time (∼40-60 μSv), compared to 5-11 min for the conventional approach. CONCLUSIONS Intraoperative CBCT using a high-performance mobile C-arm prototype demonstrates image quality suitable to guidance of spine surgery, with task-specific protocols providing an important basis for minimizing radiation dose, while maintaining image quality sufficient for surgical guidance. Images demonstrate a significant advance in spatial resolution and soft-tissue visibility, and CBCT guidance offers the potential to reduce fluoroscopy reliance, reducing cumulative dose to patient and staff. Integration with a surgical guidance system demonstrates precise tracking and visualization in up-to-date images (alleviating reliance on preoperative images only), including detection of errors or suboptimal surgical outcomes in the operating room.

TREK: an integrated system architecture for intraoperative cone-beam CT-guided surgery.

PurposeA system architecture has been developed for integration of intraoperative 3D imaging [viz., mobile C-arm cone-beam CT (CBCT)] with surgical navigation (e.g., trackers, endoscopy, and preoperative image and planning data). The goal of this paper is to describe the architecture and its handling of a broad variety of data sources in modular tool development for streamlined use of CBCT guidance in application-specific surgical scenarios.MethodsThe architecture builds on two proven open-source software packages, namely the cisst package (Johns Hopkins University, Baltimore, MD) and 3D Slicer (Brigham and Women’s Hospital, Boston, MA), and combines data sources common to image-guided procedures with intraoperative 3D imaging. Integration at the software component level is achieved through language bindings to a scripting language (Python) and an object-oriented approach to abstract and simplify the use of devices with varying characteristics. The platform aims to minimize offline data processing and to expose quantitative tools that analyze and communicate factors of geometric precision online. Modular tools are defined to accomplish specific surgical tasks, demonstrated in three clinical scenarios (temporal bone, skull base, and spine surgery) that involve a progressively increased level of complexity in toolset requirements.ResultsThe resulting architecture (referred to as “TREK”) hosts a collection of modules developed according to application-specific surgical tasks, emphasizing streamlined integration with intraoperative CBCT. These include multi-modality image display; 3D-3D rigid and deformable registration to bring preoperative image and planning data to the most up-to-date CBCT; 3D-2D registration of planning and image data to real-time fluoroscopy; infrared, electromagnetic, and video-based trackers used individually or in hybrid arrangements; augmented overlay of image and planning data in endoscopic or in-room video; and real-time “virtual fluoroscopy” computed from GPU-accelerated digitally reconstructed radiographs (DRRs). Application in three preclinical scenarios (temporal bone, skull base, and spine surgery) demonstrates the utility of the modular, task-specific approach in progressively complex tasks.ConclusionsThe design and development of a system architecture for image-guided surgery has been reported, demonstrating enhanced utilization of intraoperative CBCT in surgical applications with vastly different requirements. The system integrates C-arm CBCT with a broad variety of data sources in a modular fashion that streamlines the interface to application-specific tools, accommodates distinct workflow scenarios, and accelerates testing and translation of novel toolsets to clinical use. The modular architecture was shown to adapt to and satisfy the requirements of distinct surgical scenarios from a common code-base, leveraging software components arising from over a decade of effort within the imaging and computer-assisted interventions community.

Evaluation of a System for High-Accuracy 3D Image-Based Registration of Endoscopic Video to C-Arm Cone-Beam CT for Image-Guided Skull Base Surgery

The safety of endoscopic skull base surgery can be enhanced by accurate navigation in preoperative computed tomography (CT) or, more recently, intraoperative cone-beam CT (CBCT). The ability to register real-time endoscopic video with CBCT offers an additional advantage by rendering information directly within the visual scene to account for intraoperative anatomical change. However, tracker localization error (~1-2 mm ) limits the accuracy with which video and tomographic images can be registered. This paper reports the first implementation of image-based video-CBCT registration, conducts a detailed quantitation of the dependence of registration accuracy on system parameters, and demonstrates improvement in registration accuracy achieved by the image-based approach. Performance was evaluated as a function of parameters intrinsic to the image-based approach, including system geometry, CBCT image quality, and computational runtime. Overall system performance was evaluated in a cadaver study simulating transsphenoidal skull base tumor excision. Results demonstrated significant improvement (p <; 0.001) in registration accuracy with a mean reprojection distance error of 1.28 mm for the image-based approach versus 1.82 mm for the conventional tracker-based method. Image-based registration was highly robust against CBCT image quality factors of noise and resolution, permitting integration with low-dose intraoperative CBCT.

High-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery

Registration of endoscopic video to preoperative CT facilitates high-precision surgery of the head, neck, and skull-base. Conventional video-CT registration is limited by the accuracy of the tracker and does not use the underlying video or CT image data. A new image-based video registration method has been developed to overcome the limitations of conventional tracker-based registration. This method adds to a navigation system based on intraoperative C-arm cone-beam CT (CBCT), in turn providing high-accuracy registration of video to the surgical scene. The resulting registration enables visualization of the CBCT and planning data within the endoscopic video. The system incorporates a mobile C-arm, integrated with an optical tracking system, video endoscopy, deformable registration of preoperative CT with intraoperative CBCT, and 3D visualization. Similarly to tracker-based approach, the image-based video-CBCT registration the endoscope is localized with optical tracking system followed by a direct 3D image-based registration of the video to the CBCT. In this way, the system achieves video-CBCT registration that is both fast and accurate. Application in skull-base surgery demonstrates overlay of critical structures (e.g., carotid arteries) and surgical targets with sub-mm accuracy. Phantom and cadaver experiments show consistent improvement of target registration error (TRE) in video overlay over conventional tracker-based registration-e.g., 0.92mm versus 1.82mm for image-based and tracker-based registration, respectively. The proposed method represents a two-fold advance-first, through registration of video to up-to-date intraoperative CBCT, and second, through direct 3D image-based video-CBCT registration, which together provide more confident visualization of target and normal tissues within up-to-date images.

Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach.

PURPOSE Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (<10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. METHODS The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process. RESULTS The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3-5 mm within the target wedge) and critical structure avoidance (∼1-2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed. CONCLUSIONS The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1-2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system.

Intraoperative C-arm cone-beam computed tomography: quantitative analysis of surgical performance in skull base surgery.

To determine whether incorporation of intraoperative imaging via a new cone‐beam computed tomography (CBCT) image‐guidance system improves accuracy and facilitates resection in sinus and skull‐base surgery through quantification of surgical performance.

High-performance C-arm cone-beam CT guidance of thoracic surgery

Localizing sub-palpable nodules in minimally invasive video-assisted thoracic surgery (VATS) presents a significant challenge. To overcome inherent problems of preoperative nodule tagging using CT fluoroscopic guidance, an intraoperative C-arm cone-beam CT (CBCT) image-guidance system has been developed for direct localization of subpalpable tumors in the OR, including real-time tracking of surgical tools (including thoracoscope), and video-CBCT registration for augmentation of the thoracoscopic scene. Acquisition protocols for nodule visibility in the inflated and deflated lung were delineated in phantom and animal/cadaver studies. Motion compensated reconstruction was implemented to account for motion induced by the ventilated contralateral lung. Experience in CBCT-guided targeting of simulated lung nodules included phantoms, porcine models, and cadavers. Phantom studies defined low-dose acquisition protocols providing contrast-to-noise ratio sufficient for lung nodule visualization, confirmed in porcine specimens with simulated nodules (3-6mm diameter PE spheres, ~100-150HU contrast, 2.1mGy). Nodule visibility in CBCT of the collapsed lung, with reduced contrast according to air volume retention, was more challenging, but initial studies confirmed visibility using scan protocols at slightly increased dose (~4.6-11.1mGy). Motion compensated reconstruction employing a 4D deformation map in the backprojection process reduced artifacts associated with motion blur. Augmentation of thoracoscopic video with renderings of the target and critical structures (e.g., pulmonary artery) showed geometric accuracy consistent with camera calibration and the tracking system (2.4mm registration error). Initial results suggest a potentially valuable role for CBCT guidance in VATS, improving precision in minimally invasive, lungconserving surgeries, avoid critical structures, obviate the burdens of preoperative localization, and improve patient safety.

Clinical implementation of intraoperative cone-beam CT in head and neck surgery

A prototype mobile C-arm for cone-beam CT (CBCT) has been translated to a prospective clinical trial in head and neck surgery. The flat-panel CBCT C-arm was developed in collaboration with Siemens Healthcare, and demonstrates both sub-mm spatial resolution and soft-tissue visibility at low radiation dose (e.g., <1/5th of a typical diagnostic head CT). CBCT images are available ~15 seconds after scan completion (~1 min acquisition) and reviewed at bedside using custom 3D visualization software based on the open-source Image-Guided Surgery Toolkit (IGSTK). The CBCT C-arm has been successfully deployed in 15 head and neck cases and streamlined into the surgical environment using human factors engineering methods and expert feedback from surgeons, nurses, and anesthetists. Intraoperative imaging is implemented in a manner that maintains operating field sterility, reduces image artifacts (e.g., carbon fiber OR table) and minimizes radiation exposure. Image reviews conducted with surgical staff indicate bony detail and soft-tissue visualization sufficient for intraoperative guidance, with additional artifact management (e.g., metal, scatter) promising further improvements. Clinical trial deployment suggests a role for intraoperative CBCT in guiding complex head and neck surgical tasks, including planning mandible and maxilla resection margins, guiding subcranial and endonasal approaches to skull base tumours, and verifying maxillofacial reconstruction alignment. Ongoing translational research into complimentary image-guidance subsystems include novel methods for real-time tool tracking, fusion of endoscopic video and CBCT, and deformable registration of preoperative volumes and planning contours with intraoperative CBCT.

Deformable Registration of the Inflated and Deflated Lung for Cone-Beam CT-Guided Thoracic Surgery.

Intraoperative cone-beam CT (CBCT) could offer an important advance to thoracic surgeons in directly localizing subpalpable nodules during surgery. An image-guidance system is under development using mobile C-arm CBCT to directly localize tumors in the OR, potentially reducing the cost and logistical burden of conventional preoperative localization and facilitating safer surgery by visualizing critical structures surrounding the surgical target (e.g., pulmonary artery, airways, etc.). To utilize the wealth of preoperative image/planning data and to guide targeting under conditions in which the tumor may not be directly visualized, a deformable registration approach has been developed that geometrically resolves images of the inflated (i.e., inhale or exhale) and deflated states of the lung. This novel technique employs a coarse model-driven approach using lung surface and bronchial airways for fast registration, followed by an image-driven registration using a variant of the Demons algorithm to improve target localization to within ~1 mm. Two approaches to model-driven registration are presented and compared - the first involving point correspondences on the surface of the deflated and inflated lung and the second a mesh evolution approach. Intensity variations (i.e., higher image intensity in the deflated lung) due to expulsion of air from the lungs are accounted for using an a priori lung density modification, and its improvement on the performance of the intensity-driven Demons algorithm is demonstrated. Preliminary results of the combined model-driven and intensity-driven registration process demonstrate accuracy consistent with requirements in minimally invasive thoracic surgery in both target localization and critical structure avoidance.

Demons deformable registration for cone-beam CT guidance: registration of pre- and intra-operative images

High-quality intraoperative 3D imaging systems such as cone-beam CT (CBCT) hold considerable promise for imageguided surgical procedures in the head and neck. With a large amount of preoperative imaging and planning information available in addition to the intraoperative images, it becomes desirable to be able to integrate all sources of imaging information within the same anatomical frame of reference using deformable image registration. Fast intensity-based algorithms are available which can perform deformable image registration within a period of time short enough for intraoperative use. However, CBCT images often contain voxel intensity inaccuracy which can hinder registration accuracy - for example, due to x-ray scatter, truncation, and/or erroneous scaling normalization within the 3D reconstruction algorithm. In this work, we present a method of integrating an iterative intensity matching step within the operation of a multi-scale Demons registration algorithm. Registration accuracy was evaluated in a cadaver model and showed that a conventional Demons implementation (with either no intensity match or a single histogram match) introduced anatomical distortion and degradation in target registration error (TRE). The iterative intensity matching procedure, on the other hand, provided robust registration across a broad range of intensity inaccuracies.