RECENT MR IMAGING STRATEGY FOR DIAGNOSIS OF OVARIAN NEOPLASMS
Mohamed el-sayedaliahmedel-ambougi;
Abstract
Ovarian tumors are categorized as benign, borderline and malignant based on histological features. Ovarian cancer is the second most common gynaecological malignancy with the highest mortality rate of all gynaecological malignancies and an overall 5-year survival rate of 46%. An important reason for this high mortality is the extensive disease at the time of diagnosis which makes it important to characterize these lesions early in its course.
Exclusion of malignancy in ovarian mass is of paramount importance. It is the most crucial step after identification of a mass and it has a profound effect on the patient’s management. So, A reliablemethod with which to differentiate a benign from amalignant ovarian mass would provide a basis for optimal preoperativeplanning and may also reduce the number of unnecessarylaparotomiesfor patients undergoing treatment for benigndisease.
This study was performed over a period from October2010 to December 2013 using 1.5 Teslasystems (Philips Achieva). It included 60 patientswith clinically suspected ovarian neoplasms referred to radio-diagnosis department at Ain Shams University Hospital or Zagazig University Hospital. 22 lesions were benign, 7 wereborderline, and 31were malignant.
The Conventional MRI characteristics of each ovarian lesion wereseparately recorded according to lesion components, signal Intensity and contrast enhancement. Then, the following criteria suggestive of malignancy have been utilized for differentiation between benign and malignant ovarian masses: presence of vegetations in a cystic lesion and necrosis in a solid lesion, size larger than 4 cm, wall thickening greater than 3 mm; multiple (more than five) septa; and the presence of bilateral masses.
For differentiation of benign and malignant ovarian neoplasms, conventional MRIhad 89.5% sensitivity, 72.7% specificity, 85% PPV, 80%NPV and 83.3% accuracy.
Diffusion-weighted MRI was acquired in the axial plane prior to administration of contrast medium, then, signal intensity strength were assessed and graded as grade1: low, grade 2: intermediate, grade 3:high and grade 4: mixedsignal.
We defined lesions with grade 3 and 4 signalintensityasmalignant ovarian lesions while lesions with grade 1 and 2 signalintensityas benign ovarian lesions.
For differentiation of benign and malignant ovarian neoplasms, DW –MRI had84.2 % sensitivity, 63.6% specificity, 80% PPV, 70%NPV and 76.7% accuracy.
Exclusion of malignancy in ovarian mass is of paramount importance. It is the most crucial step after identification of a mass and it has a profound effect on the patient’s management. So, A reliablemethod with which to differentiate a benign from amalignant ovarian mass would provide a basis for optimal preoperativeplanning and may also reduce the number of unnecessarylaparotomiesfor patients undergoing treatment for benigndisease.
This study was performed over a period from October2010 to December 2013 using 1.5 Teslasystems (Philips Achieva). It included 60 patientswith clinically suspected ovarian neoplasms referred to radio-diagnosis department at Ain Shams University Hospital or Zagazig University Hospital. 22 lesions were benign, 7 wereborderline, and 31were malignant.
The Conventional MRI characteristics of each ovarian lesion wereseparately recorded according to lesion components, signal Intensity and contrast enhancement. Then, the following criteria suggestive of malignancy have been utilized for differentiation between benign and malignant ovarian masses: presence of vegetations in a cystic lesion and necrosis in a solid lesion, size larger than 4 cm, wall thickening greater than 3 mm; multiple (more than five) septa; and the presence of bilateral masses.
For differentiation of benign and malignant ovarian neoplasms, conventional MRIhad 89.5% sensitivity, 72.7% specificity, 85% PPV, 80%NPV and 83.3% accuracy.
Diffusion-weighted MRI was acquired in the axial plane prior to administration of contrast medium, then, signal intensity strength were assessed and graded as grade1: low, grade 2: intermediate, grade 3:high and grade 4: mixedsignal.
We defined lesions with grade 3 and 4 signalintensityasmalignant ovarian lesions while lesions with grade 1 and 2 signalintensityas benign ovarian lesions.
For differentiation of benign and malignant ovarian neoplasms, DW –MRI had84.2 % sensitivity, 63.6% specificity, 80% PPV, 70%NPV and 76.7% accuracy.
Other data
| Title | RECENT MR IMAGING STRATEGY FOR DIAGNOSIS OF OVARIAN NEOPLASMS | Other Titles | الخطة الحديثة باستخدام الرنين المغناطيسي في تشخيص أورام المبيض | Authors | Mohamed el-sayedaliahmedel-ambougi | Issue Date | 2014 |
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