Jacob P Christ1, Amy D Willis2, Eric D Brooks1, Heidi Vanden Brink1, Brittany Y Jarrett1, Roger A Pierson3, Donna R Chizen3, Marla E Lujan4. 1. Division of Nutritional Sciences, Cornell University, Ithaca, New York. 2. Department of Statistical Science, Cornell University, Ithaca, New York. 3. Department of Obstetrics, Gynecology & Reproductive Sciences, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. 4. Division of Nutritional Sciences, Cornell University, Ithaca, New York. Electronic address: MEL245@cornell.edu.
Abstract
OBJECTIVE: To compare the diagnostic potential of ultrasonographic markers of ovarian morphology, used alone or in combination, to predict polycystic ovary syndrome (PCOS). DESIGN: A diagnostic test study using cross-sectional data collected from 2006-2011. SETTING: Academic hospital and clinical research unit. PATIENT(S): Eighty-two women with PCOS and 60 healthy female volunteers. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Follicle number per ovary (FNPO), ovarian volume (OV), follicle number per single cross-section (FNPS), follicle distribution pattern, stromal area, ovarian area, stromal-to-ovarian area ratio (S:A), and stromal index (SI). RESULT(S): Follicle number per ovary best predicted PCOS (R(2) = 67%) with 85% sensitivity and 98% specificity, followed by OV (R(2) = 44%), and FNPS (R(2) = 36%). Neither S:A nor SI had predictive power for PCOS. In combination, FNPO+S:A and FNPO+SI most significantly predicted PCOS (R(2) = 74% vs. 73%, respectively). The diagnostic potentials of OV and FNPS were substantially improved when used in combination (OV+FNPO, R(2) = 55%). CONCLUSION(S): As a single metric, FNPO best predicted PCOS. Although the addition of S:A or SI improved the predictive power of FNPO, gains were marginal, suggesting limited use in clinical practice. When image quality precludes a reliable estimation of FNPO, measurements of OV+FNPS provide the next closest level of diagnostic potential.
OBJECTIVE: To compare the diagnostic potential of ultrasonographic markers of ovarian morphology, used alone or in combination, to predict polycystic ovary syndrome (PCOS). DESIGN: A diagnostic test study using cross-sectional data collected from 2006-2011. SETTING: Academic hospital and clinical research unit. PATIENT(S): Eighty-two women with PCOS and 60 healthy female volunteers. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Follicle number per ovary (FNPO), ovarian volume (OV), follicle number per single cross-section (FNPS), follicle distribution pattern, stromal area, ovarian area, stromal-to-ovarian area ratio (S:A), and stromal index (SI). RESULT(S): Follicle number per ovary best predicted PCOS (R(2) = 67%) with 85% sensitivity and 98% specificity, followed by OV (R(2) = 44%), and FNPS (R(2) = 36%). Neither S:A nor SI had predictive power for PCOS. In combination, FNPO+S:A and FNPO+SI most significantly predicted PCOS (R(2) = 74% vs. 73%, respectively). The diagnostic potentials of OV and FNPS were substantially improved when used in combination (OV+FNPO, R(2) = 55%). CONCLUSION(S): As a single metric, FNPO best predicted PCOS. Although the addition of S:A or SI improved the predictive power of FNPO, gains were marginal, suggesting limited use in clinical practice. When image quality precludes a reliable estimation of FNPO, measurements of OV+FNPS provide the next closest level of diagnostic potential.
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