Borderline ovarian malignancy: ultrasound and fast dynamic MR findings

Vierzen, P.B.J. van; Massuger, L.F.A.G.; Ruys, S. H. J.; Barentsz, Jelle O.

doi:10.1016/s0720-048x(97)00122-8

Cited by 43 publications

(31 citation statements)

References 12 publications

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“…The high temporal resolution that we obtained therefore allows excellent characterization of the [Gd] uptake curves, which should improve the ability to detect changes in the pharmacokinetic modeling parameters, especially K trans . Previous studies have noted the association between ovarian malignancy and early enhancement following gadolinium injection (13,14), and a recent paper has found that malignant ovarian tumors showed increases in semiquantitative parameters such as enhancement amplitude and maximum slope of enhancement in comparison with benign ovarian tumors (15). Quantitative pharmacokinetic parameters have been calculated from DCE-MRI data at 1.5 T in a variety of pelvic tumors by Lankester et al (30), who assessed the correlations between DCE-MRI and perfusion measurements from a subsequently acquired dynamic susceptibility contrast dataset.…”

Section: Discussionmentioning

confidence: 99%

“…Some peritoneal deposits are quite small, and a particular problem is that many lesions are partially or predominantly cystic, so measurement of contrast-enhanced kinetics can be problematic. However, two studies have evaluated the role of multiphase contrast-enhanced MRI in characterization of ovarian lesions, with encouraging results (13,14). Additionally, a recent study (15) investigated the role of DCE-MRI in ovarian cancer and found that semiquantitative parameters such as maximum slope can differentiate between benign and malignant ovarian tumors.…”

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confidence: 99%

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Dynamic contrast-enhanced MRI in ovarian cancer: Initial experience at 3 tesla in primary and metastatic disease

et al. 2010

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The aim of this study was to develop and demonstrate a methodology for dynamic contrast-enhanced MRI at 3 T in patients with advanced ovarian cancer and to report the results from pharmacokinetic modeling of the data. Nineteen patients with suspected advanced ovarian carcinoma (FIGO stage 3 or higher) were enrolled in this prospective study. Up to three marker lesions were identified: primary ovarian mass, omental ''cake'', and peritoneal deposits. Dynamic contrastenhanced MRI was performed using a three-dimensional T 1 -weighted gradient-echo acquisition with a temporal resolution of 1.6 sec, following intravenous administration of 0.1 mmol/ kg gadobutrol. Precontrast T 1 mapping, using an inversion-recovery fast gradient-echo sequence, was also performed. Imaging was completed in 18/19 patients, although two were subsequently excluded based on pathology results. Pharmacokinetic modeling of the data was performed according to the extended Kety model, using an arterial input function formed by concatenation of the Fritz-Hansen and Weinmann curves. No statistically significant differences were found between the results for the three marker lesions. In the future, this work will allow kinetic modeling results from ovarian dynamic contrast-enhanced MRI to be correlated with response to treatment. The high temporal resolution allows good characterization of the rapid contrast agent uptake in these vascular tumors.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Dynamic contrast-enhanced MRI in ovarian cancer: Initial experience at 3 tesla in primary and metastatic disease

et al. 2010

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“…Other studies 24,25 declared that early enhancement on post-contrast MRI is one of the diagnostic factors in distinguishing borderline and malignant from benign ovarian masses. But, they have not focused on the kinetic parameters as a valued criterion in their evaluation.…”

Section: Discussionmentioning

confidence: 99%

Semi-quantitative contrast-enhanced MR analysis of indeterminate ovarian tumours: when to say malignancy?

Mansour

Saraya

El-Faissal

2015

BJR

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Objective: To evaluate the ability of dynamic post-contrast sequence to specify indeterminate ovarian masses with inconclusive MR features of malignancy. Since management is dramatically different, special focus on the ability to differentiate borderline from invasive malignancy was considered. Methods: 150 ovarian masses were detected by pelvic ultrasound in 124 patients. Masses had been considered for dynamic post-contrast MRI. We expressed the kinetic parameters (i.e. enhancement amplitude, time peak of maximal uptake and maximal slope) in the form of maximum relative enhancement percentage (MRE%), time of maximal peak of contrast uptake (T max ) and slope enhancement ratio (SER) curves. Histological findings were the gold standard of reference. Results: Malignant ovarian masses showed higher MRE% than benign and borderline masses (p , 0.001). T max was shorter for malignant than benign (p , 0.01) and borderline (p , 0.001) ovarian masses. SER curves were the most suggestive of malignancy with a specificity and accuracy of 85.7% and 84.7%, respectively. Conclusion: Dynamic contrast-enhanced MRI could be a specific sequence to differentiate ovarian masses with indeterminate MR morphology with a special discrimination for low potential from invasive ovarian malignancy. Advances in knowledge: The study evaluated the diagnostic performance of the individual parameters of dynamic post-contrast MR sequence in evaluating ovarian masses. Management divert between benign, borderline and invasive malignant masses; our work presented a cut-off value for the peak of contrast uptake of 120%, which helped in the differentiation between benign and malignant tumours; the SER curves with Type III (early washout) pattern that was indicative of invasive malignancy was more specific than borderline malignancy.

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“…Contrast MRI enhancement and anatomical features, such as increased septal thickness and solid portion sizes could be helpful, but cannot be used to confidently differentiate these entities [1,13]. Although CA-125 is a well-known biomarker for the detection of ovarian cancer recurrence, with high accuracy and a high positive predictive value [14], CA-125 levels were only found to be marginally increased in patients with BOT [15].…”

Section: Discussionmentioning

confidence: 99%

Differential Diagnosis of Borderline Ovarian Tumors from Stage I Malignant Ovarian Tumors using FDG PET/CT

Kim

Chung

et al. 2013

Nucl Med Mol Imaging

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Purpose Borderline ovarian tumors (BOTs) are more common in young women of reproductive age, and exhibit a better prognosis than malignant ovarian tumors (MOTs). Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) were compared in their ability to differentiate BOTs from stage I MOTs. Methods Among 173 patients who had preoperative FDG PET/CT due to ovarian neoplasms between November 2006 and March 2009, there were 13 patients with BOTs or stage I MOTs. For differential diagnosis of the two tumors, cancer antigen-125 (CA-125) level, the longest diameter of tumors, metabolic indices including maximum standardized uptake value (SUV max ), and volumetric indices including metabolic tumor volume (MTV) were compared, respectively. Results The BOT group (n=7) was comprised of five mucinous and two serous tumors, and the MOT group (n=6) was comprised of three endometrioid, two clear cell and one mucinous tumors. Among the comparisons between two groups, SUV max of the BOT group was significantly lower than that of the MOT group (2.9±1.5 vs. 6.6±2.9, p=0. 0223); otherwise, no significant difference was found in age, CA-125, diameter, or MTV. By receiver-operating characteristic curve analysis, SUV max of 3.7 was the best cutoff value to differentiate BOTs from stage I MOTs, with a sensitivity of 83.3 % and specificity of 85.7, and the area under curve of 0.893 (p=0.0001, 95 % CI: 0.601∼0.993). Conclusions We demonstrated that SUV max could distinguish BOTs from stage I MOTs, with a high sensitivity and specificity. Metabolic indices determined by FDG PET/CT were more suitable than volumetric indices for differential diagnosis of the two tumors.

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Borderline ovarian malignancy: ultrasound and fast dynamic MR findings

Cited by 43 publications

References 12 publications

Dynamic contrast-enhanced MRI in ovarian cancer: Initial experience at 3 tesla in primary and metastatic disease

Dynamic contrast-enhanced MRI in ovarian cancer: Initial experience at 3 tesla in primary and metastatic disease

Semi-quantitative contrast-enhanced MR analysis of indeterminate ovarian tumours: when to say malignancy?

Differential Diagnosis of Borderline Ovarian Tumors from Stage I Malignant Ovarian Tumors using FDG PET/CT

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