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Updated: Aug 12, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Magnetic resonance diffusion imaging of ovarian masses: a first experience with 12 cases
Gordon E Sarty1, Edward J Kendall, John Loewy
1Department of Psychology, University of Saskatchewan, Saskatoon, Sasketchewan, Canada. gordon.sarty@usask.ca
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.
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