Is laparoscopy equal to laparotomy in detecting and treating small bowel injuries in a porcine model?

AIM: To evaluate the safety and effectiveness of laparoscopy compared with laparotomy for diagnosing and treating small bowel injuries (SBIs) in a porcine model. METHODS: Twenty-eight female pigs were anesthetized and laid in the left recumbent position. The SBI model was established by shooting at the right lower quadrant of the abdomen. The pigs were then randomized into either the laparotomy group or the laparoscopy group. All pigs underwent routine exploratory laparotomy or laparoscopy to evaluate the abdominal injuries, particularly the types, sites, and numbers of SBIs. Traditional open surgery or therapeutic laparoscopy was then performed. All pigs were kept alive within the observational period (postoperative 72 h). The postoperative recovery of each pig was carefully observed. RESULTS: The vital signs of all pigs were stable within 1-2 h after shooting and none of the pigs died from gunshot wounds or SBIs immediately. The SBI model was successfully established in all pigs and definitively diagnosed with single or multiple SBIs either by exploratory laparotomy or laparoscopy. Compared with exploratory laparotomy, laparoscopy took a significantly longer time for diagnosis (41.27 ± 12.04 min vs 27.64 ± 13.32 min, P = 0.02), but the time for therapeutic laparoscopy was similar to that of open surgery. The length of incision was significantly reduced in the laparoscopy group compared with the laparotomy group (5.27 ± 1.86 cm vs 15.73 ± 1.06 cm, P < 0.01). In the final post-mortem examination 72 h after surgery, both laparotomy and laparoscopy offered a definitive diagnosis with no missed injuries. Postoperative complications occurred in four cases (three following laparotomy and one following laparoscopy, P = 0.326). The average recovery period for bowel function, vital appearance, and food re-intake after laparoscopy was 10.36 ± 4.72 h, 14.91 ± 3.14 h, and 15.00 ± 7.11 h, respectively. All of these were significantly shorter than after laparotomy (21.27 ± 10.17 h, P = 0.004; 27.82 ± 9.61 h, P < 0.001; and 24.55 ± 9.72 h, respectively, P = 0.016). CONCLUSION: Compared with laparotomy, laparoscopy offers equivalent efficacy for diagnosing and treating SBIs, and reduces postoperative complications as well as recovery period.

Multisensor Remote Sensing Imagery Super-Resolution with Conditional GAN

Despite the promising performance on benchmark datasets that deep convolutional neural networks have exhibited in single image super-resolution(SISR),there are two underlying limitations to existing methods.First,current supervised learningbased SISR methods for remote sensing satellite imagery do not use paired real sensor data,instead operating on simulated high-resolution(HR)and low-resolution(LR)image-pairs(typically HR images with their bicubic-degraded LR counterparts),which often yield poor performance on real-world LR images.Second,SISR is an ill-posed problem,and the super-resolved image from discriminatively trained networks with l p norm loss is an average of the infinite possible HR images,thus,always has low perceptual quality.Though this issue can be mitigated by generative adversarial network(GAN),it is still hard to search in the whole solution-space and find the best solution.In this paper,we focus on real-world application and introduce a new multisensor dataset for real-world remote sensing satellite imagery super-resolution.In addition,we propose a novel conditional GAN scheme for SISR task which can further reduce the solution-space.Therefore,the super-resolved images have not only high fidelity,but high perceptual quality as well.Extensive experiments demonstrate that networks trained on the introduced dataset can obtain better performances than those trained on simulated data.Additionally,the proposed conditional GAN scheme can achieve better perceptual quality while obtaining comparable fidelity over the state-of-the-art methods.