A one‐step biomarker quantification methodology for DCE‐MRI of adnexal masses: Capturing kinetic pattern from early to late enhancement

Abstract

Purpose To develop a one‐step quantification approach that accounts for joint preprocessing and quantification of whole‐range kinetics (early and late‐phase washout) of dynamic contrast‐enhanced (DCE) MRI of indeterminate adnexal masses. Methods Preoperative DCE‐MRI of 43 (24 benign, 19 malignant) sonographically indeterminate adnexal masses were analyzed prospectively. A five‐parameter sigmoid function was implemented to model the enhancement curves calculated within regions of interest. Diagnostic performance of five‐parameter sigmoid model parameters (P1 through P5) was compared with pharmacokinetic (PK) modeling, semiquantitative analysis, and three‐parameter sigmoid. Statistical analysis was performed using two‐tailed student's t‐test. Results The results revealed that P2, representing the enhancement amplitude, is significantly higher, and P5, indicating the terminal phase, is generally negative in malignant lesions (P < 0.001). P2 (sensitivity = 79%, specificity = 87.5%, accuracy = 84%, area under the receiver operating characteristic curve = 91%) outperforms classification performances of PK and semiquantitative parameters. A combination of P2 and P5 shows comparable performance (sensitivity = 79%, specificity = 87.5%, accuracy = 84%, area under the receiver operating characteristic curve = 92%) to that of the combination of PK parameters, whereas the five‐parameter sigmoid function maintains fewer assumptions than PK. Conclusions The presented one‐step quantification approach is helpful for accurate discrimination of benign from malignant indeterminate adnexal masses. Accordingly, P2 has considerably high diagnostic performance and terminal slope (P5), as a previously overlooked feature, contributes more than widely accepted early‐enhancement kinetic features. Magn Reson Med 79:1165–1171, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging for malignant ovarian tumors: a systematic review and meta-analysis

“…Of them, one study investigated both quantitative and semi-quantitative parameters (37). Therefore, 11 articles (37–47) reported semi-quantitative DCE-MRI data for detecting MOTs, while four articles (37,48–50) reported quantitative DCE-MRI data (Table 1). It should be noted that one study included two cases of cancer of the fallopian tubes (48); however, this study was included because the guidelines of the National Comprehensive Cancer Network (NCCN) (3) suggest that the procedure of diagnosis and treatment for fallopian tube cancer and epithelial ovarian cancer are consistent.…”

“…Therefore, different scanning devices and protocols could generate different diagnostic thresholds. Additionally, of the four included studies, three (37,49,50) applied the Tofts model (one type of pharmacokinetic model) and one (48) used another more complex model, which might also be a cause of the high threshold effect. Therefore, care must be taken when measuring diagnostic value from pooled results.…”

ADC‐derived spatial features can accurately classify adnexal lesions

“…Limitations of mean ADC for characterization of adnexal masses has encouraged many researchers to interrogate the role of other advanced MRI techniques, such as qualitative and quantitative dynamic contrast‐enhanced (DCE) MRI. While these additional techniques have shown potential, employing a well‐designed DWI acquisition integrated with an accurate postprocessing spatial quantification technique for helping the radiologists with their diagnosis may obviate the requirement for administration of contrast agents and could reduce the scan time.…”

Editorial for “Added‐Value of Quantitative Analysis of Diffusion‐Weighted Imaging in Ovarian‐Adnexal Reporting and Data System Magnetic Resonance Imaging (O‐RADS MRI): A Prospective Cohort Study”

“…For ovarian mases, the most common reported imaging biomarkers were different coefficients calculated from quantitative diffusion‐weighted MRI, especially the apparent diffusion coefficient (ADC) value. However, it remains controversial on the diagnostic contribution of these imaging biomarkers for differentiating malignant and benign ovarian lesions 6,7 . First, performing diffusion‐weighted MRI in ovarian lesions is a great challenge, because of the highly heterogeneous compositions in ovarian lesions, including the cysts filled with mucous or serous fluid, and different solid components such as lipid and hemorrhage.…”

“…However, it remains controversial on the diagnostic contribution of these imaging biomarkers for differentiating malignant and benign ovarian lesions. 6,7 First, performing diffusion-weighted MRI in ovarian lesions is a great challenge, because of the highly heterogeneous compositions in ovarian lesions, including the cysts filled with mucous or serous fluid, and different solid components such as lipid and hemorrhage. The mean ADC value from the whole lesion is closer to the high value of massive cystic components, rather than the low value of any small malignant portion.…”