Heterogeneity of Adenosine Triphosphate-Based Chemotherapy Response Assay in Colorectal Cancer - Secondary Publication

PURPOSE: Adenosine triphosphate-based chemotherapy response assay (ATP-CRA) is a well-documented and validated technology that can individualize chemotherapy for patients with lung, stomach, or breast cancer. This study explored the feasibility of ATP-CRA as a chemosensitivity test in patients with colorectal cancer. MATERIALS AND METHODS: A total of 118 patients who underwent surgical resection for colorectal adenocarcinoma were analyzed for chemosensitivity to 6 anticancer drugs using ATP-CRA. We calculated the cell death rate (CDR) by measuring intracellular ATP levels of drug-exposed cells and untreated controls. RESULTS: Interpretable results were available for 85.5% (118/138) of patients. The mean coefficient of variation for triplicate ATP measurements was 9.2%. The highest CDR was observed in irinotecan (34.0%) and the lowest CDR in etoposide (21.0%). Paclitaxel had the broadest range of CDR (0-86.7%) and 5-FU had the narrowest range of CDR (0-56.8%). The overall highest responsiveness was seen most prevalently in irinotecan (24.7%, 23/93 patients). Irinotecan had the greatest responsiveness in patients with well differentiated and moderately differentiated carcinoma. CONCLUSION: Our study suggests that ATP-CRA could be used to identify patients with colorectal cancer who might benefit from treatment with a specific chemotherapeutic agent.ope

Association of age-adjusted shock index with mortality in children with trauma: a single-center study in Korea

Purpose This study was performed to investigate the association of high age-adjusted shock index (AASI) with mortality in Korean children with trauma. Methods The data of children (aged < 15 years) with trauma who visited a university hospital in Korea from 2010 through 2018 were reviewed. High AASI was defined by age groups as follows: < 12 months, ≥ 2.7; 12-23 months, ≥ 2.1; 2-4 years, ≥ 1.9; 5-11 years, ≥ 1.5; and 12-14 years, ≥ 1.1. Age, sex, transfer status, injury mechanism, hypotension, tachycardia, base deficit, hemoglobin concentration, trauma scores, hemorrhage-related procedures (transfusion and surgical interventions), and severe traumatic brain injury were compared according to high AASI and in-hospital mortality. The association of high AASI with the mortality was analyzed using logistic regression. Results Of the 363 enrolled children, 29 (8.0%) had high AASI and 24 (6.6%) died. The children with high AASI showed worse trauma scores and underwent hemorrhage-related procedures more frequently, without a difference in the rate of the traumatic brain injury. High AASI was associated with in-hospital mortality (survivors, 6.5% vs. non-survivors, 29.2%; P = 0.001). This association remained significant after adjustment (adjusted odds ratio, 6.42; 95% confidence interval, 1.38-29.82). The other predictors were Glasgow Coma Scale (for increment of 1 point; 0.62; 0.53-0.72) and age (for increment of 1 year; 0.84; 0.73-0.97). High AASI showed a 29.2% sensitivity and 93.5% specificity for the mortality. Conclusion High AASI is associated with mortality, and have a high specificity but low sensitivity in Korean children with trauma. This predictor of mortality can be used prior to obtaining the results of laboratory markers of shock

Structure stability evaluation of offshore heave compensator using multi-body dynamics analysis method

Heave compensator attenuate vessel heave motion during drilling operation of drillship. Heave compensator functions as damping form motion of drillship, such as principle spring of suspension system. The load transfers on the parts of heave compensator. Stress and deformation of all parts is evaluated to diagnose the stability of the compensator. This study makes a decision on the safety of structure. Results of analysis confirm the structure stability of heave compensator for simulation. This result can be used as data for structural analysis to determine safety of a structure

Complete Remission of Unresectable Colon Cancer after Preoperative Chemotherapy Selected by Adenosine Triphosphate-Based Chemotherapy Response Assay

The adenosine triphosphate-based chemotherapy response assay (ATP-CRA) is a chemosensitivity test that offers the potential of selecting cancer treatments based on the responsiveness of individual tumors. We report a case of 47-yr-old male, presented with sigmoid colon cancer with multiple liver and peritoneal metastases, in which there was a complete response for the primary colon cancer after administration of preoperative chemotherapy selected by ATP-CRA. Oxaliplatin was the most sensitive drug based on the ATP-CRA where the specimen obtained by ultrasound-guided percutaneous liver biopsy was used. After twelve cycles of oxaliplatin-capecitabine chemotherapy, abdominopelvic computed tomography revealed marked shrinkage of the liver metastases and positron emission tomography showed no uptake of 18F-fluoro-deoxy-glucose (FDG) either in the liver or peritoneum except localized uptake in the sigmoid colon. The patient underwent an anterior resection and radiofrequency ablation of the liver metastases, which resulted in a macroscopic curative resection of the cancer cells. Histological examination revealed no residual cancer cells in the resected specimen of the sigmoid colon. This result suggested that preoperative chemotherapy chosen by ATP-CRA may be useful for treating advanced colon cancer with unresectable liver and peritoneal metastases

Panoptic Segmentation on Panoramic Radiographs: Deep Learning-Based Segmentation of Various Structures Including Maxillary Sinus and Mandibular Canal

Panoramic radiographs, also known as orthopantomograms, are routinely used in most dental clinics. However, it has been difficult to develop an automated method that detects the various structures present in these radiographs. One of the main reasons for this is that structures of various sizes and shapes are collectively shown in the image. In order to solve this problem, the recently proposed concept of panoptic segmentation, which integrates instance segmentation and semantic segmentation, was applied to panoramic radiographs. A state-of-the-art deep neural network model designed for panoptic segmentation was trained to segment the maxillary sinus, maxilla, mandible, mandibular canal, normal teeth, treated teeth, and dental implants on panoramic radiographs. Unlike conventional semantic segmentation, each object in the tooth and implant classes was individually classified. For evaluation, the panoptic quality, segmentation quality, recognition quality, intersection over union (IoU), and instance-level IoU were calculated. The evaluation and visualization results showed that the deep learning-based artificial intelligence model can perform panoptic segmentation of images, including those of the maxillary sinus and mandibular canal, on panoramic radiographs. This automatic machine learning method might assist dental practitioners to set up treatment plans and diagnose oral and maxillofacial diseases.Y