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Contribution of diffusion-weighted imaging to conventional MRI for detection of haemorrhagic infarction in ovary torsion

Overview of attention for article published in BMC Medical Imaging, November 2017
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Title
Contribution of diffusion-weighted imaging to conventional MRI for detection of haemorrhagic infarction in ovary torsion
Published in
BMC Medical Imaging, November 2017
DOI 10.1186/s12880-017-0232-6
Pubmed ID
Authors

Oğuzhan Özdemir, Yavuz Metin, Nurgül Orhan Metin, Ali Küpeli

Abstract

To assess the role of DWI in differentiation haemorrhagic ovary infarction from non-haemorrhagic one. For this prospectively designed study, of 117 female patients who presented with acute lower quadrant pain and underwent MRI for suspicion of ovary torsion, results of only 29 patients (mean age, 24.7; SD, ±5.7; age range, 18-37), with surgical and pathological confirmation of adnexal torsion, were included to the study. All patients underwent DWI after conventional MRI. Quantitative and qualitative analysis of both the torsed and contralateral normal ovary were performed. Results of conventional MRI and DWI were noted. At operation 15 patients were found to have haemorrhagic infarction while 14 had non-haemorrhagic infarction. Of the 29 patients, 17 torsed ovaries could be salvaged in a viable state. We found statistically significant correlation of the ADC values, between haemorrhagic and non-haemorrhagic ovary infarction. The ADC values were significantly lower in patients with haemorrhagic infarction than non-haemorrhagic ones (p < 0.001). Using an ADC threshold of 1.27, the sensitivity of DWI for haemorrhagic infarction was 0.93 and specificity 0.85. DWI may be used with a significant success for the preoperative diagnosis of haemorrhagic infarction. This may be alerting for pre-emptive surgery in avoiding serious complications and preventing irreversible structural damage of the ovary.

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The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 23%
Researcher 2 15%
Professor > Associate Professor 2 15%
Professor 1 8%
Other 1 8%
Other 2 15%
Unknown 2 15%
Readers by discipline Count As %
Nursing and Health Professions 4 31%
Medicine and Dentistry 2 15%
Psychology 1 8%
Materials Science 1 8%
Engineering 1 8%
Other 0 0%
Unknown 4 31%