Genetic alterations in prostate cancer as diagnostic and prognostic markers

Prostate cancer is the second-most frequently diagnosed cancer in men worldwide. Serum prostatespecific antigen is currently used for the early detection of prostate cancer. However, new biomarkers are needed to decrease over diagnosis and over treatment of prostate cancer due to limitations of prostate-specific antigen. Recently, molecular biomarkers have shown promising results for diagnosis and prognosis of prostate cancer. Molecular biomarkers have improved the sensitivity and specificity of prostate-specific antigen and studies are ongoing to identify molecular biomarkers as a replacement for prostate-specific antigen. This review aims to give an overview of emerging molecular biomarkers for diagnosis and prognosis of prostate cancer.

Autonomous robotic laparoscopic surgery for intestinal anastomosis

Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeon's skill and experience. Autonomous anastomosis is a challenging soft-tissue surgery task because it requires intricate imaging, tissue tracking, and surgical planning techniques, as well as a precise execution via highly adaptable control strategies often in unstructured and deformable environments. In the laparoscopic setting, such surgeries are even more challenging because of the need for high maneuverability and repeatability under motion and vision constraints. Here we describe an enhanced autonomous strategy for laparoscopic soft tissue surgery and demonstrate robotic laparoscopic small bowel anastomosis in phantom and in vivo intestinal tissues. This enhanced autonomous strategy allows the operator to select among autonomously generated surgical plans and the robot executes a wide range of tasks independently. We then use our enhanced autonomous strategy to perform in vivo autonomous robotic laparoscopic surgery for intestinal anastomosis on porcine models over a 1-week survival period. We compared the anastomosis quality criteria-including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure-of the developed autonomous system, manual laparoscopic surgery, and robot-assisted surgery (RAS). Data from a phantom model indicate that our system outperforms expert surgeons' manual technique and RAS technique in terms of consistency and accuracy. This was also replicated in the in vivo model. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.

Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques

Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.

Semi-autonomous Robotic Anastomoses of Vaginal Cuffs Using Marker Enhanced 3D Imaging and Path Planning

Autonomous robotic anastomosis has the potential to improve surgical outcomes by performing more consistent suture spacing and bite size compared to manual anastomosis. However, due to soft tissue's irregular shape and unpredictable deformation, performing autonomous robotic anastomosis without continuous tissue detection and three-dimensional path planning strategies remains a challenging task. In this paper, we present a novel three-dimensional path planning algorithm for Smart Tissue Autonomous Robot (STAR) to enable semi-autonomous robotic anastomosis on deformable tissue. The algorithm incorporates (i) continuous detection of 3D near infrared (NIR) markers manually placed on deformable tissue before the procedure, (ii) generating a uniform and consistent suture placement plan using 3D path planning methods based on the locations of the NIR markers, and (iii) updating the remaining suture plan after each completed stitch using a non-rigid registration technique to account for tissue deformation during anastomosis. We evaluate the path planning algorithm for accuracy and consistency by comparing the anastomosis of synthetic vaginal cuff tissue completed by STAR and a surgeon. Our test results indicate that STAR using the proposed method achieves 2.6 times better consistency in suture spacing and 2.4 times better consistency in suture bite sizes than the manual anastomosis.

Autonomous Laparoscopic Robotic Suturing with a Novel Actuated Suturing Tool and 3D Endoscope

Compared to open surgical techniques, laparoscopic surgical methods aim to reduce the collateral tissue damage and hence decrease the patient recovery time. However, constraints imposed by the laparoscopic surgery, i.e. the operation of surgical tools in limited spaces, turn simple surgical tasks such as suturing into time-consuming and inconsistent tasks for surgeons. In this paper, we develop an autonomous laparoscopic robotic suturing system. More specific, we expand our smart tissue anastomosis robot (STAR) by developing i) a new 3D imaging endoscope, ii) a novel actuated laparoscopic suturing tool, and iii) a suture planning strategy for the autonomous suturing. We experimentally test the accuracy and consistency of our developed system and compare it to sutures performed manually by surgeons. Our test results on suture pads indicate that STAR can reach 2.9 times better consistency in suture spacing compared to manual method and also eliminate suture repositioning and adjustments. Moreover, the consistency of suture bite sizes obtained by STAR matches with those obtained by manual suturing.

A Confidence-Based Shared Control Strategy for the Smart Tissue Autonomous Robot (STAR)

Autonomous robotic assisted surgery (RAS) systems aim to reduce human errors and improve patient outcomes leveraging robotic accuracy and repeatability during surgical procedures. However, full automation of RAS in complex surgical environments is still not feasible and collaboration with the surgeon is required for safe and effective use. In this work, we utilize our Smart Tissue Autonomous Robot (STAR) to develop and evaluate a shared control strategy for the collaboration of the robot with a human operator in surgical scenarios. We consider 2D pattern cutting tasks with partial blood occlusion of the cutting pattern using a robotic electrocautery tool. For this surgical task and RAS system, we i) develop a confidence-based shared control strategy, ii) assess the pattern tracking performances of manual and autonomous controls and identify the confidence models for human and robot as well as a confidence-based control allocation function, and iii) experimentally evaluate the accuracy of our proposed shared control strategy. In our experiments on porcine fat samples, by combining the best elements of autonomous robot controller with complementary skills of a human operator, our proposed control strategy improved the cutting accuracy by 6.4%, while reducing the operator work time to 44 % compared to a pure manual control.

Gamma-secretase inhibitor does not modulate angiogenesis in colon adenocarcinoma in obese mice

BACKGROUND

Notch is a signaling molecule which plays a role in angiogenesis and γ-secretase is required for processing of Notch. In this study, we investigated the effect of γ-secretase inhibitor (DAPT) on tumor angiogenesis in diet-induced obese mice.

METHODS

18 mice were divided into three groups; control, obese (diet-induced) and obese+DAPT. After 15 weeks, the obese mice were subjected for tumor induction of CT26 colon adenocarcinoma cells (5 x 105 cells). When the tumor size reached approximately 350 ± 50 mm3, half of the obese animals received DAPT (10mg/kg/day) subcutaneously. Blood samples were taken after 14 days and the tumors harvested for immunohistochemical staining and capillary density were reported as CD31 positive cells/mm2.

RESULTS

The obese animals had higher serum leptin and NO concentrations, while, serum VEGF and VEGFR-1 concentrations were not different compare to control group. Administration of DAPT in obese mice significantly reduced serum VEGFR-1 and leptin concentrations and increased serum NO level (p < 0.05). Capillary density in the tumors of obese animals was not different compare to control groups. DAPT administration could not alter capillary density in the tumors.

CONCLUSION

Administration of DAPT in obese mice altered serum angiogenic factors, however, it could not modulate tumor angiogenesis in diet-induced obese mice (Fig. 4, Ref. 26).