Jocelyne Troccaz

Alireza Asvadi, Guillaume Dardenne, Jocelyne Troccaz et al.

In this study, we investigated a method allowing the determination of the femur bone surface as well as its mechanical axis from some easy-to-identify bony landmarks. The reconstruction of the whole femur is therefore performed from these landmarks using a Statistical Shape Model (SSM). The aim of this research is therefore to assess the impact of the number, the position, and the accuracy of the landmarks for the reconstruction of the femur and the determination of its related mechanical axis, an important clinical parameter to consider for the lower limb analysis. Two statistical femur models were created from our in-house dataset and a publicly available dataset. Both were evaluated in terms of average point-to-point surface distance error and through the mechanical axis of the femur. Furthermore, the clinical impact of using landmarks on the skin in replacement of bony landmarks is investigated. The predicted proximal femurs from bony landmarks were more accurate compared to on-skin landmarks while both had less than 3.5 degrees mechanical axis angle deviation error. The results regarding the non-invasive determination of the mechanical axis are very encouraging and could open very interesting clinical perspectives for the analysis of the lower limb either for orthopedics or functional rehabilitation.

Chunxia Qin, Xiaojun Chen, Jocelyne Troccaz

Precise determination of target is an essential procedure in prostate interventions, such as the prostate biopsy, lesion detection and targeted therapy. However, the prostate delineation may be tough in some cases due to tissue ambiguity or lack of partial anatomical boundary. To address this problem, we proposed a weakly supervised registration-based framework for the precise prostate segmentation, by combining convolutional neural network (CNN) with statistical shape model (SSM). To obtain the prostate region, an inception-based neural network (SSM-Net) was firstly exploited to predict the model transform, shape control parameters and a fine-tuning vector, for the generation of prostate boundary. According to the inferred boundary, a normalized distance map was calculated. Then, a residual U-net (ResU-Net) was employed to predict a probability label map from the input images. Finally, the average of the distance map and the probability map was regarded as the prostate segmentation. After that, two public dataset PROMISE12 and NCI- ISBI 2013 were utilized for the model computation and for the network training and testing. The validation results demonstrate that the segmentation framework using a SSM with 9500 nodes achieved the best performance, with a dice of 0.904 and an average surface distance of 1.88 mm. In addition, we verified the impact of model elasticity augmentation and fine-tuning item on the network segmentation capability. As a result, both factors have improved the delineation accuracy, with dice increased by 10% and 7% respectively. In conclusion, via the combination of two weakly supervised neural networks, our segmentation method might be an effective and robust approach for prostate segmentation.

Jean-Alexandre Long, Jacques Tostain, Cecilia Lanchon et al.

Purpose: To report the feasibility and the safety of a surgeon-controlled robotic endoscope holder in laparoscopic surgery. Materials and methods: From March 2010 to September 2010, 20 patients were enrolled prospectively to undergo a laparoscopic surgery using an innovative robotic endoscope holder. Two surgeons performed 6 adrenalectomies, 4 sacrocolpopexies, 5 pyeloplasties, 4 radical prostatectomies and 1 radical nephrectomy. Demographic data, overall set-up time, operative time, number of assistants needed were reviewed. Surgeon's satisfaction regarding the ergonomics was assessed using a ten point scale. Postoperative clinical outcomes were reviewed at day 1 and 1 month postoperatively. Results: The per-protocol analysis was performed on 17 patients for whom the robot was effectively used for surgery. Median age was 63 years, 10 patients were female (59%). Median BMI was 26.8. Surgical procedures were completed with the robot in 12 cases (71 %). Median number of surgical assistant was 0. Overall set-up time with the robot was 19 min, operative time was 130 min) during which the robot was used 71% of the time. Mean hospital stay was 6.94 days $\pm$ 2.3. Median score regarding the easiness of use was 7. Median pain level was 1.5/10 at day 1 and 0 at 1 month postoperatively. Open conversion was needed in 1 case (6 %) and 4 minor complications occurred in 2 patients (12%). Conclusion: This use of this novel robotic laparoscope holder is safe, feasible and it provides a good comfort to the surgeon.

Jean-Alexandre Long, Nikolai Hungr, Michael Baumann et al.

Purpose: We report what is to our knowledge the initial experience with a new 3-dimensional ultrasound robotic system for prostate brachytherapy assistance, focal therapy and prostate biopsies. Its ability to track prostate motion intraoperatively allows it to manage motions and guide needles to predefined targets. Materials and Methods: A robotic system was created for transrectal ultrasound guided needle implantation combined with intraoperative prostate tracking. Experiments were done on 90 targets embedded in a total of 9 mobile, deformable, synthetic prostate phantoms. Experiments involved trying to insert glass beads as close as possible to targets in multimodal anthropomorphic imaging phantoms. Results were measured by segmenting the inserted beads in computerized tomography volumes of the phantoms. Results: The robot reached the chosen targets in phantoms with a median accuracy of 2.73 mm and a median prostate motion of 5.46 mm. Accuracy was better at the apex than at the base (2.28 vs 3.83 mm, p <0.001), and similar for horizontal and angled needle inclinations (2.7 vs 2.82 mm, p = 0.18). Conclusions: To our knowledge this robot for prostate focal therapy, brachytherapy and targeted prostate biopsies is the first system to use intraoperative prostate motion tracking to guide needles into the prostate. Preliminary experiments show its ability to reach targets despite prostate motion.