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Minimally invasive surgery for gastro-oesophageal junction adenocarcinoma: Current evidence and future perspectives

World Journal of Gastrointestinal Oncology 2023年第10期15卷 1675-1690页

作者： Rodica Birla Petre Hoara Florin Achim Valeriu Dinca Diana Ciuc Silviu constantinoiu adrian constantin Department of General Surgery Carol Davila UniversityBucharest 011172Romania Department of General Surgery Carol Davila University of Medicine and PharmacyBucharest 020021Romania Faculty of Medicine “Titu Maiorescu”UniversityBucharest 031593Romania

Minimally invasive surgery is increasingly indicated in the management of malignant *** oesophagectomy is a difficult operation,with a long learning curve,there is actually a shift towards the laparoscopic/thoracoscopic/robotic approach,due to the advantages of visualization,surgeon comfort(robotic surgery)and the possibility of the whole team to see the operation as well as and the operating *** currently there are still many controversial topics,about the surgical treatment of patients with gastro-oesophageal junction(GOJ)adenocarcinoma,such as the type of open or minimally invasive surgical approach,the type of oesophago-gastric resection,the type of lymph node dissection and others,the minimally invasive approach has proven to be a way to reduce postoperative complications of resection,especially by decreasing pulmonary *** implementation of new technologies allowed the widening of the range of indications for this type of surgical *** short-term and long-term results,as well as the benefits for the patient-reduced surgical trauma,quick and easy recovery-offer this type of surgical treatment the premises for future *** article reviews the updates and perspectives on the minimally invasive approach for GOJ adenocarcinoma.

关键词： Gastro-oesophageal adenocarcinoma Minimally invasive oesophagectomy Laparoscopic gastrectomy Abdomino-mediastinal lymph node dissection Indocyanine green fluorescence imaging

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Contrast-enhanced ultrasonography parameters in neural network diagnosis of liver tumors

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World Journal of Gastroenterology 2012年第32期18卷 4427-4434页

作者： Costin Teodor Streba Mihaela Ionescu Dan Ionut Gheonea Larisa Sandulescu Tudorel Ciurea adrian Saftoiu Cristin constantin Vere Ion Rogoveanu Research Center of Gastroenterology and Hepatology University of Medicine and Pharmacy of Craiova200349 CraiovaRomania Department of Bioinformatics and Statistics University of Medicine and Pharmacy Craiova200349 CraiovaRomania

AIM:To study the role of time-intensity curve(TIC) analysis parameters in a complex system of neural networks designed to classify liver ***:We prospectively included 112 patients with hepatocellular carcinoma(HCC)(n = 41),hypervascular(n = 20) and hypovascular(n = 12) liver metastases,hepatic hemangiomas(n = 16) or focal fatty changes(n = 23) who underwent contrast-enhanced ultrasonography in the Research Center of Gastroenterology and Hepatology,Craiova,*** recorded full length movies of all contrast uptake phases and post-processed them offline by selecting two areas of interest(one for the tumor and one for the healthy surrounding parenchyma) and consecutive TIC *** difference in maximum intensities,the time to reaching them and the aspect of the late/portal phase,as quantified by the neural network and a ratio between median intensities of the central and peripheral areas were analyzed by a feed forward back propagation multi-layer neural network which was trained to classify data into five distinct classes,corresponding to each type of liver ***:The neural network had 94.45% training accuracy(95% CI:89.31%-97.21%) and 87.12% testing accuracy(95% CI:86.83%-93.17%).The automatic classification process registered 93.2% sensitivity,89.7% specificity,94.42% positive predictive value and 87.57% negative predictive *** artificial neural networks(ANN) incorrectly classified as hemangyomas three HCC cases and two hypervascular metastases,while in turn misclassifying four liver hemangyomas as HCC(one case) and hypervascular metastases(three cases).Comparatively,human interpretation of TICs showed 94.1% sensitivity,90.7% specificity,95.11% positive predictive value and 88.89% negative predictive *** accuracy and specificity of the ANN diagnosis system was similar to that of human interpretation of the TICs(P = 0.225 and P = 0.451,respectively).Hepatocellular carcinoma cases showed contrast uptake during the arterial phase

关键词： Hepatocellular carcinoma Liver tumors Contrast enhanced ultrasound Time-intensity curve Artificial neural network Computer-aided diagnosis system

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