The Poised Cannula Technique Reduces the Stereotactic Error of the Fiducial-Less Frameless DBS Procedure.

Background: In this study, we describe a technique of optimizing the accuracy of frameless deep brain stimulation (DBS) lead placement through the use of a cannula poised at the entry to predict the location of the fully inserted device. This allows real-time correction of error prior to violation of the deep gray matter.

Methods: We prospectively gathered data on radial error during the operative placements of 40 leads in 28 patients using frameless fiducial-less DBS surgery.

A Comparative Study of Fiducial-Based and Fiducial-Less Registration Utilizing the O-Arm.

Background: Frameless stereotactic surgery utilizing fiducial-based (FB) registration is an established tool in the armamentarium of deep brain stimulation (DBS) surgeons. Fiducial-less (FL) registration via intraoperative CT, such as the O-arm, has been routinely used in spine surgery, but its accuracy for DBS surgery has not been studied in a clinical setting.

Objective: We undertook a study to analyze the accuracy of the FL technique in DBS surgery and compare it to the FB method.

A quantitative assessment of the accuracy and reliability of O-arm images for deep brain stimulation surgery.

Background: Deep brain stimulation (DBS) surgery has an average accuracy of 2 to 3 mm (range, 0-6 mm). Intraoperative detection of track location may be useful in interpreting physiological results and thus limit the number of brain penetrations as well as decrease the incidence of reoperations. The O-arm has been used to identify the DBS lead position; however, early results have indicated a significant discrepancy with lead position on postoperative imaging.

4D Cone-beam CT reconstruction using a motion model based on principal component analysis.

Purpose: To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm.

Methods: The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT.

Reconstruction of a cone-beam CT image via forward iterative projection matching.

Purpose: To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set.

Methods: A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set.

The quantized DCT and its application to DCT-based video coding.

The two-dimensional (2-D) discrete cosine transform (DCT) and the subsequent quantization of the transform coefficients are two computationally demanding steps of any DCT-based video encoder. In this paper, we propose an efficient joint implementation of these two steps, where the precision in computing the DCT can be exchanged for a reduction in the computational complexity. First, the quantization is embedded in the DCT, thus eliminating the need to explicitly quantize the transform coefficients.