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Magnetic resonance diffusion imaging of ovarian masses: a first experience with 12 cases
Authors:Email author" target="_blank">Gordon E?SartyEmail author  Edward J?Kendall  John?Loewy  Anita?Dhir  Olufemi A?Olatunbosun  Roger A?Pierson
Affiliation:(1) Department of Psychology, University of Saskatchewan, Saskatoon, Sasketchewan, Canada;(2) Department of Medical Imaging, University of Saskatchewan, Saskatoon, Sasketchewan, Canada;(3) Department of Obstetrics, Gynecology and Reproductive Sciences, University of Saskatchewan Saskatoon,, Sasketchewan, Canada;(4) University of Saskatchewan, Saskatoon, Saskatchewan, Canada;(5) Department of Medical Imaging, Humber River Regional Hospital, Toronto, Ontario, Canada;(6) Department of Psychology, 9 Campus Drive, Saskatoon, Saskatchewan S7N 5A5, Canada
Abstract:Objective: The objective of the study was to determine the feasibility of using apparent diffusion coefficient (ADC) measurement for the differential diagnosis of malignancy in ovarian masses. Materials and methods: Twelve cases involving ovarian masses were imaged using spin echo diffusion magnetic resonance imaging (MRI). Five cases involved malignant ovarian masses, on the basis of postoperative histologic examination, and the rest involved benign masses. The ovarian masses were imaged in vivo (10 cases) before surgery and ex vivo (8 cases) after surgical resection. Diffusion-weighted data were corrected for motion using the phase data from unweighted data in nine cases. Multifactorial analysis of variance was used to evaluate the effects of malignancy, location (in vivo versus ex vivo), and motion correction on the measurement of ADC intensity and texture. Results: Motion correction caused an undesirable spatial smoothing of the ADC maps and a significant interaction ( $p=0.047$ ) was found between location and motion correction. ADC value ( $p=0.028$ ) and texture ( $p=0.001$ ) differences were found between malignant and nonmalignant ovarian masses. Conclusion: Measurement of ADC intensity and texture has the potential to differentially diagnose malignancy in individual ovarian masses if the problem of image motion artifact can be eliminated through the use of faster imaging sequences.Acknowledgements. The cooperation of Dr. Vance Chow in the acquisition of the in vivo diffusion MRI data is gratefully acknowledged. Thanks to Ron Borowsky for discussions on the statistical data analysis. Data management, final data analysis, and figure preparation was completed by Jennifer Hadley. This work was supported by the Canadian Institutes for Health Research (CIHR) and the Saskatchewan Health Services Utilization and Research Commission (HSURC).
Keywords:Cancer  MRI  Differential diagnosis  Ovary  Diffusion imaging
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