Objective: Our objective was to compare prospectively the abilities of MR imaging, CT, and sonography to reveal puerperal septic thrombophlebitis in the pelvis.
Subjects And Methods: Seventy-six women with puerperal fever for 5 days refractory to antimicrobial therapy underwent MR imaging, CT, and sonography. We obtained unenhanced axial CT images followed by enhanced images after the administration of an oral contrast agent for which we followed a specific protocol. Axial T1- and T2-weighted spin-echo MR images with phase reconstruction and sagittal T1-weighted MR images were obtained. Real-time sonography was performed using Doppler color flow mapping and spectral waveform analysis.
Results: Of the 76 women, 64 completed studies with all three techniques. Ovarian vein thrombosis was diagnosed in 12 women. True-positive results were indicated when at least two of the three studies showed the presence of a clot; true-negative results were indicated when at least two of the three studies showed a lack of thrombosis. MR imaging and CT revealed both ovarian veins in all cases (64/64). Sonography revealed 33 (52%) of 64 right ovarian veins and 15 (23%) of 64 left ovarian veins. MR imaging (sensitivity, 92%; specificity, 100%) and CT (sensitivity, 100%; specificity 99%) were comparable in all but two cases. In one such case, MR imaging showed patency, CT revealed findings interpreted as thrombosis, and sonography showed flow in the partially occluded vein. In the second such case, bilateral thrombosis was seen on CT, but interpretations based on sonography and MR imaging were left-sided thrombosis only. Sonography correctly revealed six of the 12 cases of ovarian vein thrombosis.
Conclusion: CT and MR imaging proved to be the studies of choice in the evaluation of ovarian vein thrombosis.
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http://dx.doi.org/10.2214/ajr.169.4.9308461 | DOI Listing |
Br J Hosp Med (Lond)
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Department of Obstetrics and Gynecology, The First Clinical Medical College of Three Gorges University, Yichang Central People's Hospital, Yichang, Hubei, China.
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Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Warsaw, Poland.
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Sensors (Basel)
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School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety.
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Joyce and Irving Goldman Medical School, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.
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View Article and Find Full Text PDFJ Clin Med
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Department of Urology, Faculty of Medicine, Recep Tayyip Erdogan University, 53000 Rize, Turkey.
Semen analysis is universally regarded as the gold standard for diagnosing male infertility, while ultrasonography plays a vital role as a complementary diagnostic tool. This study aims to assess the effectiveness of artificial intelligence (AI)-driven deep learning algorithms in predicting semen analysis parameters based on testicular ultrasonography images. This study included male patients aged 18-54 who sought evaluation for infertility at the Urology Outpatient Clinic of our hospital between February 2022 and April 2023.
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