TY - JOUR
T1 - Serial ultrasonographic evaluation of ovarian abnormalities with a morphology index
AU - Elder, Jeffrey W.
AU - Pavlik, Edward J.
AU - Long, Ashleigh
AU - Miller, Rachel W.
AU - Desimone, Christopher P.
AU - Hoff, John T.
AU - Ueland, Walker R.
AU - Kryscio, Richard J.
AU - Van Nagell, John R.
AU - Ueland, Frederick R.
N1 - Publisher Copyright:
© 2014 Elsevier Inc.
PY - 2014/10/1
Y1 - 2014/10/1
N2 - Objective. Transvaginal ultrasonographywith tumor morphology index (MI) has been used to predict the risk of ovarianmalignancy. Our objective was to analyze changes in serialMI scores for malignant and non-malignant ovarian tumors in a large and asymptomatic population.Methods. Eligible subjects participated in the University of Kentucky Ovarian Cancer Screening Program and had abnormalities that included cysts, cysts with septations, complex cysts with solid areas, and solid masses. Analysis included: MI, change in MI (delta MI), delta MI per scan and per month, number and duration of scans.Results. From1987 to 2012, 38,983women received 218,445 scans.Of the 7104 eligible subjects, 6758 tumors were observedwithout surgery and 472 were surgically removed. Eighty-six percent (5811) of observed tumors were resolved. Therewere 74malignant and 272 non-malignant tumors. Eighty-five percent ofmalignancies had MI≥5 at decision for surgery. The risk of malignancy based on MI was: MI = 5 (3%), MI = 6 (3.7%), MI = 7 (12.6%), MI=8 (26.7%), MI=9 (27.8%), MI=10 (33.3%). The mean delta MI per month decreased for tumors that resolved (delta MI-1.0, p b 0.001) or persisted without surgery (delta MI-0.7, p <0.001). For abnormalities surgically removed, the mean delta MI per month increased significantly more for malignancies than for benign tumors (delta MI +1.6 vs. +0.3, p <0.001).Conclusions. The mean MI for malignant ovarian tumors increases over time, while non-malignant tumors have a decreasing or stable MI. SerialMI analysis can improve the prediction of ovarian malignancy by reducing false-positive results, thereby decreasing the number of operations performed for benign abnormalities.
AB - Objective. Transvaginal ultrasonographywith tumor morphology index (MI) has been used to predict the risk of ovarianmalignancy. Our objective was to analyze changes in serialMI scores for malignant and non-malignant ovarian tumors in a large and asymptomatic population.Methods. Eligible subjects participated in the University of Kentucky Ovarian Cancer Screening Program and had abnormalities that included cysts, cysts with septations, complex cysts with solid areas, and solid masses. Analysis included: MI, change in MI (delta MI), delta MI per scan and per month, number and duration of scans.Results. From1987 to 2012, 38,983women received 218,445 scans.Of the 7104 eligible subjects, 6758 tumors were observedwithout surgery and 472 were surgically removed. Eighty-six percent (5811) of observed tumors were resolved. Therewere 74malignant and 272 non-malignant tumors. Eighty-five percent ofmalignancies had MI≥5 at decision for surgery. The risk of malignancy based on MI was: MI = 5 (3%), MI = 6 (3.7%), MI = 7 (12.6%), MI=8 (26.7%), MI=9 (27.8%), MI=10 (33.3%). The mean delta MI per month decreased for tumors that resolved (delta MI-1.0, p b 0.001) or persisted without surgery (delta MI-0.7, p <0.001). For abnormalities surgically removed, the mean delta MI per month increased significantly more for malignancies than for benign tumors (delta MI +1.6 vs. +0.3, p <0.001).Conclusions. The mean MI for malignant ovarian tumors increases over time, while non-malignant tumors have a decreasing or stable MI. SerialMI analysis can improve the prediction of ovarian malignancy by reducing false-positive results, thereby decreasing the number of operations performed for benign abnormalities.
KW - Morphology
KW - Ovary
KW - Screening
KW - Tumor
KW - Ultrasound
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U2 - 10.1016/j.ygyno.2014.07.091
DO - 10.1016/j.ygyno.2014.07.091
M3 - Article
C2 - 25068975
AN - SCOPUS:84908029476
SN - 0090-8258
VL - 135
SP - 8
EP - 12
JO - Gynecologic Oncology
JF - Gynecologic Oncology
IS - 1
ER -