Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.

Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines.

CD8 T cells play a key role in mediating protective immunity against selected pathogens after vaccination. Understanding the mechanism of this protection is dependent upon definition of the heterogeneity and complexity of cellular immune responses generated by different vaccines. Here, we identify previously unrecognized subsets of CD8 T cells based upon analysis of gene-expression patterns within single cells and show that they are differentially induced by different vaccines. Three prime-boost vector combinations encoding HIV Env stimulated antigen-specific CD8 T-cell populations of similar magnitude, phenotype, and functionality. Remarkably, however, analysis of single-cell gene-expression profiles enabled discrimination of a majority of central memory (CM) and effector memory (EM) CD8 T cells elicited by the three vaccines. Subsets of T cells could be defined based on their expression of Eomes, Cxcr3, and Ccr7, or Klrk1, Klrg1, and Ccr5 in CM and EM cells, respectively. Of CM cells elicited by DNA prime-recombinant adenoviral (rAd) boost vectors, 67% were Eomes(-) Ccr7(+) Cxcr3(-), in contrast to only 7% and 2% stimulated by rAd5-rAd5 or rAd-LCMV, respectively. Of EM cells elicited by DNA-rAd, 74% were Klrk1(-) Klrg1(-)Ccr5(-) compared with only 26% and 20% for rAd5-rAd5 or rAd5-LCMV. Definition by single-cell gene profiling of specific CM and EM CD8 T-cell subsets that are differentially induced by different gene-based vaccines will facilitate the design and evaluation of vaccines, as well as enable our understanding of mechanisms of protective immunity.

Image guided critical screw placement precision in the cervical spine : important or incidental? : results of a series of 91 consecutive cases using OVEM

Study design: A retrospective study of image guided cervical implant placement precision. Objective: To describe a simple and precise classification of cervical critical screw placement. Summary of Background Data: "Critical" screw placement is defined as implant insertion into a bone corridor which is surrounded circumferentially by neurovascular structures. While the use of image guidance has improved accuracy, there is currently no classification which provides sufficient precision to assess the navigation success of critical cervical screw placement. Methods: Based on postoperative clinical evaluation and CT imaging, the orthogonal view evaluation method (OVEM) is used to classify screw accuracy into grade I (no cortical breach), grade la (screw thread cortical breach), grade II (internal diameter cortical breach) and grade III (major cortical breach causing neural or vascular injury). Grades II and III are considered to be navigation failures, after accounting for bone corridor / screw mismatch (minimal diameter of targeted bone corridor being smaller than an outer screw diameter). Results: A total of 276 screws from 91 patients were classified into grade I (64.9%), grade la (18.1%), and grade II (17.0%). No grade III screw was observed. The overall rate of navigation failure was 13%. Multiple logistic regression indicated that navigational failure was significantly associated with the level of instrumentation and the navigation system used. Navigational failure was rare (1.6%) when the margin around the screw in the bone corridor was larger than 1.5 mm. Conclusions: OVEM evaluation appears to be a useful tool to assess the precision of critical screw placement in the cervical spine. The OVEM validity and reliability need to be addressed. Further correlation with clinical outcomes will be addressed in future studies.