Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/56674
Title: Sonographic diagnosis of tubal cancer with IOTA simple rules plus pattern recognition
Authors: Theera Tongsong
Chanane Wanapirak
Charuwan Tantipalakorn
Dangcheewan Tinnangwattana
Keywords: Biochemistry, Genetics and Molecular Biology
Medicine
Issue Date: 1-Nov-2017
Abstract: Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85035020151&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/56674
ISSN: 2476762X
15137368
Appears in Collections:CMUL: Journal Articles

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