Collision tumour involving a rectal gastrointestinal stromal tumour with invasion of the prostate and a prostatic adenocarcinoma

Background: Gastrointestinal stromal tumours (GISTs) are the most common primary mesenchymal neoplasia in the gastrointestinal tract, although they represent only a small fraction of total gastrointestinal malignancies in adults (<2%). GISTs can be located at any level of the gastrointestinal tract; the stomach is the most common location (60-70%), in contrast to the rectum, which is most rare (4%). When a GIST invades into the adjacent prostate tissue, it can simulate prostate cancer. In this study, we report on a case comprising the unexpected collision between a rectal GIST tumour and a prostatic adenocarcinoma. Findings: We describe the complexity of the clinical, endoscopic and radiological diagnosis, of the differential diagnosis based on tumour biopsy, and of the role of neoadjuvant therapy using imatinib prior to surgical treatment. Conclusions: Although isolated cases of coexisting GISTs and prostatic adenocarcinomas have reviously been described, this is the first reported case in the medical literature of a collision tumour involving a rectal GIST and prostatic adenocarcinoma components.

Guided Bus Rapid Transit

Electrical Bus Rapid Transit (eBRT) is a charging electrical public transport which brings a clean, high performance, and affordable cost alternative from the conventional traffic vehicles which work with combustion and hybrid technology. These buses charge the battery in every bus stop to arrive at the next station. But, this charging system needs an appropriate infrastructure called pantograph, and it requires a high precision bus location to maintain battery lifetime, energy saving and charging time. To overcome this issue Vicomtech and Datik has planned a project based on computer vision to help to the driver to locate the vehicle in the correct place. In this document, we present a mono camera bus driver guided fast algorithm because these vehicles embedded computers do not support high computation and precision operations. In addition to the frequent lane sign, there are more accurate geometric beacons painted on the road to bring metric information to the vision system. This method uses segmentation to binarize the image discriminating the background space. Besides it detects, tracks and counts different lane mark contours in addition to classify each special painted mark. Besides it does not need any calibration task to calculate longitudinal and cross distances because we know the lane mark sizes.