Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce...Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce. Aim: To test a novel AI commercially available tool for image analysis on a series of laparoscopic scenes. Methods: The research tools included OPENAI CHATGPT 4.0 with its corresponding image recognition plugin which was fed with a list of 100 laparoscopic selected snapshots from common surgical procedures. In order to score reliability of received responses from image-recognition bot, two corresponding scales were developed ranging from 0 - 5. The set of images was divided into two groups: unlabeled (Group A) and labeled (Group B), and according to the type of surgical procedure or image resolution. Results: AI was able to recognize correctly the context of surgical-related images in 97% of its reports. For the labeled surgical pictures, the image-processing bot scored 3.95/5 (79%), whilst for the unlabeled, it scored 2.905/5 (58.1%). Phases of the procedure were commented in detail, after all successful interpretations. With rates 4 - 5/5, the chatbot was able to talk in detail about the indications, contraindications, stages, instrumentation, complications and outcome rates of the operation discussed. Conclusion: Interaction between surgeon and chatbot appears to be an interesting frontend for further research by clinicians in parallel with evolution of its complex underlying infrastructure. In this early phase of using artificial intelligence for image recognition in surgery, no safe conclusions can be drawn by small cohorts with commercially available software. Further development of medically-oriented AI software and clinical world awareness are expected to bring fruitful information on the topic in the years to come.展开更多
Background: Splenic cysts are infrequent findings in everyday medical practice. They are usually associated with nonspecific symptoms and the diagnosis is incidental. In most instances they are located in the left sub...Background: Splenic cysts are infrequent findings in everyday medical practice. They are usually associated with nonspecific symptoms and the diagnosis is incidental. In most instances they are located in the left subcostal region, except for cases of huge sized cysts which can extend to the whole abdomen or pelvis. Aim: To present a case of a large hypogastric splenic cyst in a nulliparous woman, managed with robotic cystectomy. Review of the literature is included. Case: A 19-year-old woman, presented to the gynecologic department with a painless, palpable mass in the lower abdomen. Ultrasonography revealed a pelvic cystic mass, originally misdiagnosed for an ovarian cyst. Serum biomarkers and?β-hCG were negative. Definite diagnosis was made during explorative laparoscopy where the cyst was found to originate from the spleen. The surgery setup was changed from a lower to upper abdominal procedure. A robotically-assisted cystectomy was performed without concurrent splenectomy, and the splenic cavity was filled with an omental patch. There was no blood loss and the operation time was 163 minutes. Recovery was uneventful and there was no recurrence for a period of 16 months postoperatively. Conclusions: Pelvic splenic cysts are rare, and may be incidental findings during routine abdominal ultrasound scans. Modern minimally invasive approaches such as robotic surgery offer safe and efficient alternatives to standard techniques.展开更多
文摘Introduction: Ultrafast latest developments in artificial intelligence (ΑΙ) have recently multiplied concerns regarding the future of robotic autonomy in surgery. However, the literature on the topic is still scarce. Aim: To test a novel AI commercially available tool for image analysis on a series of laparoscopic scenes. Methods: The research tools included OPENAI CHATGPT 4.0 with its corresponding image recognition plugin which was fed with a list of 100 laparoscopic selected snapshots from common surgical procedures. In order to score reliability of received responses from image-recognition bot, two corresponding scales were developed ranging from 0 - 5. The set of images was divided into two groups: unlabeled (Group A) and labeled (Group B), and according to the type of surgical procedure or image resolution. Results: AI was able to recognize correctly the context of surgical-related images in 97% of its reports. For the labeled surgical pictures, the image-processing bot scored 3.95/5 (79%), whilst for the unlabeled, it scored 2.905/5 (58.1%). Phases of the procedure were commented in detail, after all successful interpretations. With rates 4 - 5/5, the chatbot was able to talk in detail about the indications, contraindications, stages, instrumentation, complications and outcome rates of the operation discussed. Conclusion: Interaction between surgeon and chatbot appears to be an interesting frontend for further research by clinicians in parallel with evolution of its complex underlying infrastructure. In this early phase of using artificial intelligence for image recognition in surgery, no safe conclusions can be drawn by small cohorts with commercially available software. Further development of medically-oriented AI software and clinical world awareness are expected to bring fruitful information on the topic in the years to come.
文摘Background: Splenic cysts are infrequent findings in everyday medical practice. They are usually associated with nonspecific symptoms and the diagnosis is incidental. In most instances they are located in the left subcostal region, except for cases of huge sized cysts which can extend to the whole abdomen or pelvis. Aim: To present a case of a large hypogastric splenic cyst in a nulliparous woman, managed with robotic cystectomy. Review of the literature is included. Case: A 19-year-old woman, presented to the gynecologic department with a painless, palpable mass in the lower abdomen. Ultrasonography revealed a pelvic cystic mass, originally misdiagnosed for an ovarian cyst. Serum biomarkers and?β-hCG were negative. Definite diagnosis was made during explorative laparoscopy where the cyst was found to originate from the spleen. The surgery setup was changed from a lower to upper abdominal procedure. A robotically-assisted cystectomy was performed without concurrent splenectomy, and the splenic cavity was filled with an omental patch. There was no blood loss and the operation time was 163 minutes. Recovery was uneventful and there was no recurrence for a period of 16 months postoperatively. Conclusions: Pelvic splenic cysts are rare, and may be incidental findings during routine abdominal ultrasound scans. Modern minimally invasive approaches such as robotic surgery offer safe and efficient alternatives to standard techniques.
