Clinical, genetic, epidemiologic, evolutionary, and functional delineation of TSPEAR-related autosomal recessive ectodermal dysplasia 14.

TSPEAR variants cause autosomal recessive ectodermal dysplasia (ARED) 14. The function of TSPEAR is unknown. The clinical features, the mutation spectrum, and the underlying mechanisms of ARED14 are poorly understood. Combining data from new and previously published individuals established that ARED14 is primarily characterized by dental anomalies such as conical tooth cusps and hypodontia, like those seen in individuals with WNT10A-related odontoonychodermal dysplasia. AlphaFold-predicted structure-based analysis showed that most of the pathogenic TSPEAR missense variants likely destabilize the ß-propeller of the protein. Analysis of 100000 Genomes Project (100KGP) data revealed multiple founder TSPEAR variants across different populations. Mutational and recombination clock analyses demonstrated that non-Finnish European founder variants likely originated around the end of the last ice age, a period of major climatic transition. Analysis of gnomAD data showed that the non-Finnish European population TSPEAR gene-carrier rate is ∼1/140, making it one of the commonest AREDs. Phylogenetic and AlphaFold structural analyses showed that TSPEAR is an ortholog of drosophila Closca, an extracellular matrix-dependent signaling regulator. We, therefore, hypothesized that TSPEAR could have a role in enamel knot, a structure that coordinates patterning of developing tooth cusps. Analysis of mouse single-cell RNA sequencing (scRNA-seq) data revealed highly restricted expression of Tspear in clusters representing enamel knots. A tspeara -/-;tspearb -/- double-knockout zebrafish model recapitulated the clinical features of ARED14 and fin regeneration abnormalities of wnt10a knockout fish, thus suggesting interaction between tspear and wnt10a. In summary, we provide insights into the role of TSPEAR in ectodermal development and the evolutionary history, epidemiology, mechanisms, and consequences of its loss of function variants.

Evaluation of 39 medical implants at 7.0 T.

OBJECTIVE: With increased signal to noise ratios, 7.0-T MRI has the potential to contribute unique information regarding anatomy and pathophysiology of a disease. However, concerns for the safety of subjects with metallic medical implants have hindered advancement in this field. The purpose of the present research was to evaluate the MRI safety for 39 commonly used medical implants at 7.0 T. METHODS: Selected metallic implants were tested for magnetic field interactions, radiofrequency-induced heating and artefacts using standardized testing techniques. RESULTS: 5 of the 39 implants tested may be unsafe for subjects undergoing MRI at 7.0 T. CONCLUSION: Implants were deemed either "MR Conditional" or "MR Unsafe" for the 7.0-T MRI environment. Further research is needed to expand the existing database categorizing implants that are acceptable for patients referred for MRI examinations at 7.0 T. ADVANCES IN KNOWLEDGE: Lack of MRI testing for common metallic medical implants limits the translational potential of 7.0-T MRI. For safety reasons, patients with metallic implants are not allowed to undergo a 7.0-T MRI scan, precluding part of the population that can benefit from the detailed resolution of ultra-high-field MRIs. This investigation provides necessary MRI testing of common medical implants at 7.0 T.

Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer.

The purpose of this work was to determine the relationship between the apparent diffusion coefficient (ADC, from diffusion-weighted (DW) MRI), the extravascular, extracellular volume fraction (ve , from dynamic contrast-enhanced (DCE) MRI), and histological measurement of the extracellular space fraction. Athymic nude mice were injected with either human epidermal growth factor receptor 2 positive (HER2+) BT474 (n = 15) or triple negative MDA-MB-231 (n = 20) breast cancer cells, treated with either Herceptin (n = 8), Abraxane (low dose n = 7, high dose n = 6), or saline (n = 7 for each cell line), and imaged using DW- and DCE-MRI before, during, and after treatment. After the final imaging acquisition, the tissue was resected and evaluated by histological analysis. H&E-stained central slices were scanned using a digital brightfield microscope and evaluated with thresholding techniques to calculate the extracellular space. For both BT474 and MDA-MB-231, the median ADC of the central slice exhibited a significantly positive correlation with the corresponding central slice extracellular space as measured by H&E (p = 0.03, p < 0.01, respectively). Median ve calculated from the central slice showed differing results between the two cell lines. For BT474, a significant correlation between ve and extracellular space was calculated (p = 0.02), while MDA-MB-231 tumors did not demonstrate a significant correlation (p = 0.64). Additionally, there was no correlation discovered between ADC and ve with either whole tumor analysis or central slice analysis (p > 0.05). While ADC correlates well with the histologically determined fraction of extracellular space, these data add to the growing body of literature that suggests that ve derived from DCE-MRI is not a reliable biomarker of extracellular space for a range of physiological conditions.

Evaluating treatment response using DW-MRI and DCE-MRI in trastuzumab responsive and resistant HER2-overexpressing human breast cancer xenografts.

We report longitudinal diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast enhanced (DCE)-MRI (7 T) studies designed to identify functional changes, prior to volume changes, in trastuzumab-sensitive and resistant HER2+ breast cancer xenografts. Athymic mice (N = 33) were subcutaneously implanted with trastuzumab-sensitive (BT474) or trastuzumab-resistant (HR6) breast cancer cells. Tumor-bearing animals were distributed into four groups: BT474 treated and control, HR6 treated and control. DW- and DCE-MRI were conducted at baseline, day 1, and day 4; trastuzumab (10 mg/kg) or saline was administered at baseline and day 3. Animals were sacrificed on day 4 and tumors resected for histology. Voxel-based DW- and DCE-MRI analyses were performed to generate parametric maps of ADC, K(trans), and ve. On day 1, no differences in tumor size were observed between any of the groups. On day 4, significant differences in tumor size were observed between treated vs. control BT474, treated BT474 vs. treated HR6, and treated vs. control HR6 (P < .0001). On day 1, ve was significantly higher in the BT474 treated group compared to BT474 control (P = .002) and HR6 treated (P = .004). On day 4, ve and K(trans) were significantly higher in the treated BT474 tumors compared to BT474 controls (P = .0007, P = .02, respectively). A significant decrease in Ki67 staining reinforced response in the BT474 treated group compared to BT474 controls (P = .02). This work demonstrated that quantitative MRI biomarkers have the sensitivity to differentiate treatment response in HER2+ tumors prior to changes in tumor size.

Assessing reproducibility of diffusion-weighted magnetic resonance imaging studies in a murine model of HER2+ breast cancer.

BACKGROUND AND PURPOSE: The use of diffusion-weighted magnetic resonance imaging (DW-MRI) as a surrogate biomarker of response in preclinical studies is increasing. However, before a biomarker can be reliably employed to assess treatment response, the reproducibility of the technique must be established. There is a paucity of literature that quantifies the reproducibility of DW-MRI in preclinical studies; thus, the purpose of this study was to investigate DW-MRI reproducibility in a murine model of HER2+ breast cancer. MATERIALS AND METHODS: Test-Retest DW-MRI scans separated by approximately six hours were acquired from eleven athymic female mice with HER2+ xenografts using a pulsed gradient spin echo diffusion-weighted sequence with three b values [150, 500, and 800s/mm(2)]. Reproducibility was assessed for the mean apparent diffusion coefficient (ADC) from tumor and muscle tissue regions. RESULTS: The threshold to reflect a change in tumor physiology in a cohort of mice is defined by the 95% confidence interval (CI), which was±0.0972×10(-3)mm(2)/s (±11.8%) for mean tumor ADC. The repeatability coefficient defines this threshold for an individual mouse, which was±0.273×10(-3)mm(2)/s. The 95% CI and repeatability coefficient for mean ADC of muscle tissue were±0.0949×10(-3)mm(2)/s (±8.30%) and±0.266×10(-3)mm(2)/s, respectively. CONCLUSIONS: Mean ADC of tumors is reproducible and appropriate for detecting treatment-induced changes on both an individual and mouse cohort basis.

The School for Science and Math at Vanderbilt: An Innovative Research-Based Program for High School Students.

The School for Science and Math at Vanderbilt (SSMV) is an innovative partnership program between a Research I private university and a large urban public school system. The SSMV was started in 2007 and currently has 101 students enrolled in the program, with a total of 60 students who have completed the 4-yr sequential program. Students attend the SSMV for one full day per week during the school year and 3-6 wk in the summers following their ninth- to 11th-grade years, with each grade of 26 students coming to the Vanderbilt campus on a separate day. The research-based curriculum focuses on guiding students through the process of learning to develop questions and hypotheses, designing projects and performing analyses, and communicating results of these projects. The SSMV program has elevated the learning outcomes of students as evidenced by increased achievement scores relative to a comparison group of students; has provided a rigorous research-based science, technology, engineering, and mathematics elective curriculum that culminates in a Summer research internship; has produced 27 Intel and Siemens semifinalists and regional finalists over the past 4 yr; and has supported the development of writing and communication skills resulting in regional and national oral presentations and publications in scientific journals.

A diffusion-compensated model for the analysis of DCE-MRI data: theory, simulations and experimental results.

Accurate quantification of pharmacokinetic parameters in dynamic contrast-enhanced (DCE) MRI may be affected by the passive diffusion of contrast agent (CA) within the tissue. By introducing an additional term into the standard Tofts-Kety (STK) model, we correct for the effects of CA diffusion. We first develop the theory describing a CA diffusion corrected STK model (DTK). The model is then tested in simulation with simple models of diffusion. The DTK model is also fit to 18 in vivo DCE-MRI acquisitions from murine models of cancer and results are compared to those from the STK model. The DTK model returned estimates with significantly lower error than the STK model (p ≪ 0.001). In poorly perfused (i.e., K(trans) ≤ 0.05 min(-1)) regions the STK model returned unphysical ve values, while the DTK model estimated ve with less than 7% error in noise-free simulations. Results in vivo data revealed similar trends. For voxels with low K(trans) values and late peak concentration times the STK model returned ve estimates >1.0 in 40% of the voxels as compared to only 16% for the DTK model. The DTK model presented here shows promise in estimating accurate kinetic parameters in the presence of passive contrast agent diffusion.

Assessing the reproducibility of dynamic contrast enhanced magnetic resonance imaging in a murine model of breast cancer.

Quantitative dynamic contrast enhanced magnetic resonance imaging estimates parameters related to tissue vascularity and volume fractions; additionally, semiquantitative parameters such as the initial area under the curve can be utilized to describe tissue behavior. The aim of this study was to establish the reproducibility of quantitative and semiquantitative analysis of dynamic contrast enhanced magnetic resonance imaging in a murine model of breast cancer. For each animal, a T1-weighted, gradient-echo sequence was used to acquire two sets of dynamic contrast enhanced magnetic resonance imaging data separated by 5 h. Data were acquired at both a 0.05 mm3 (128(2) , n=12) and a 0.2 mm3 (64(2), n=12) resolution, and analysis was performed using both the Tofts-Kety (to estimate Ktrans and ve) and extended Tofts-Kety (Ktrans, ve, and vp) models. Reproducibility analysis was performed for both the center slice and the total tumor volume for all parameters. For the total volume analysis, the repeatability index for Ktrans is 0.073 min(-1) in the standard model analysis and 0.075 min(-1) in the extended model analysis at the 128(2) acquisition. For the 64(2) acquisition, the values are 0.089 and 0.063 min(-1) for the standard and extended models, respectively. The repeatability index for initial area under the curve was 0.0039 and 0.0042 mM min for the 128(2) and 64(2) acquisitions, respectively.

Practical dynamic contrast enhanced MRI in small animal models of cancer: data acquisition, data analysis, and interpretation.

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) consists of the continuous acquisition of images before, during, and after the injection of a contrast agent. DCE-MRI allows for noninvasive evaluation of tumor parameters related to vascular perfusion and permeability and tissue volume fractions, and is frequently employed in both preclinical and clinical investigations. However, the experimental and analytical subtleties of the technique are not frequently discussed in the literature, nor are its relationships to other commonly used quantitative imaging techniques. This review aims to provide practical information on the development, implementation, and validation of a DCE-MRI study in the context of a preclinical study (though we do frequently refer to clinical studies that are related to these topics).

Comparisons of the efficacy of a Jak1/2 inhibitor (AZD1480) with a VEGF signaling inhibitor (cediranib) and sham treatments in mouse tumors using DCE-MRI, DW-MRI, and histology.

Jak1/2 inhibition suppresses STAT3 phosphorylation that is characteristic of many cancers. Activated STAT3 promotes the transcription of factors that enhance tumor growth, survival, and angiogenesis. AZD1480 is a novel small molecule inhibitor of Jak1/2, which is a key mediator of STAT3 activation. This study examined the use of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) biomarkers in assessing early tumor response to AZD1480. Cediranib (AZD2171), a vascular endothelial growth factor signaling inhibitor, was used as a comparator. Thirty mice were injected with Calu-6 lung cancer cells and randomized into the three treatment groups: AZD1480, cediranib, and sham. DW-MRI and DCE-MRI protocols were performed at baseline and at days 3 and 5 after treatment. The percent change from baseline measurements for K(trans), ADC, and v(e) were calculated and compared with hematoxylin and eosin (H&E), CD31, cParp, and Ki-67 histology data. Decreases in K(trans) of 29% (P < .05) and 53% (P < .05) were observed at days 3 and 5, respectively, for the cediranib group. No significant changes in K(trans) occurred for the AZD1480 group, but a significant increase in ADC was demonstrated at days 3 (63%, P < .05) and 5 (49%, P < .05). CD31 staining indicated diminished vasculature in the cediranib group, whereas significantly increased cParp staining for apoptotic activity and extracellular space by image analysis of H&E were present in the AZD1480 group. These imaging biomarker changes, and corresponding histopathology, support the use of ADC, but not K(trans), as a pharmacodynamic biomarker of response to AZD1480 at these time points.

A quantitative comparison of the influence of individual versus population-derived vascular input functions on dynamic contrast enhanced-MRI in small animals.

For quantitative analysis of dynamic contrast enhanced magnetic resonance imaging data, the time course of the concentration of the contrast agent in the blood plasma, or vascular input function (VIF), is required. We compared pharmacokinetic parameters derived using individual and population-based VIFs in mice for two different contrast agents, gadopentetate dimeglumine and P846. Eleven mice with subcutaneous 4T(1) breast cancer xenografts were imaged at 7 T. A precontrast T(1) map was acquired along with dynamic T(1) -weighted gradient echo images before, during, and after a bolus injection of contrast agent delivered via a syringe pump. Each animal's individual VIF and derived population-averaged VIF were used to extract parameters from the signal-time curves of tumor tissue at both the region of interest and voxel level. The results indicate that for both contrast agents, K(trans) values estimated using population-averaged VIF have a high correlation (concordance correlation coefficient > 0.85) with K(trans) values estimated using individual VIF on both a region of interest and voxel level. This work supports the validity of using of a population-based VIF with a stringent injection protocol in preclinical dynamic contrast enhanced magnetic resonance imaging studies.

A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer.

Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIF(ind), and compute a population-averaged AIF, AIF(pop). The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for K(trans), v(p) and v(e) as estimated by AIF(ind) and AIF(pop) are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for K(trans), v(p) and v(e), respectively. This work indicates that K(trans) and v(p) show good agreement between AIF(pop) and AIF(ind) while there is a weak agreement on v(e).

Quantitative effects of using compressed sensing in dynamic contrast enhanced MRI.

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) involves the acquisition of images before, during and after the injection of a contrast agent. In order to perform quantitative modeling on the resulting signal intensity time course, data must be acquired rapidly, which compromises spatial resolution, signal to noise and/or field of view. One approach that may allow for gains in temporal or spatial resolution or signal to noise of an individual image is to use compressed sensing (CS) MRI. In this study, we demonstrate the accuracy of extracted pharmacokinetic parameters from DCE-MRI data obtained as part of pre-clinical and clinical studies in which fully sampled acquisitions have been retrospectively undersampled by factors of 2, 3 and 4 in Fourier space and then reconstructed with CS. The mean voxel-level concordance correlation coefficient for K(trans) (i.e. the volume transfer constant) obtained from the 2× accelerated and the fully sampled data is 0.92 and 0.90 for mouse and human data, respectively; for 3×, the results are 0.79 and 0.79, respectively; for 4×, the results are 0.64 and 0.70, respectively. The mean error in the tumor mean K(trans) for the mouse and human data at 2× acceleration is 1.8% and -4.2%, respectively; at 3×, 3.6% and -10%, respectively; at 4×, 7.8% and -12%, respectively. These results suggest that CS combined with appropriate reduced acquisitions may be an effective approach to improving image quality in DCE-MRI.

Earlier detection of tumor treatment response using magnetic resonance diffusion imaging with oscillating gradients.

An improved method for detecting early changes in tumors in response to treatment, based on a modification of diffusion-weighted magnetic resonance imaging, has been demonstrated in an animal model. Early detection of therapeutic response in tumors is important both clinically and in pre-clinical assessments of novel treatments. Noninvasive imaging methods that can detect and assess tumor response early in the course of treatment, and before frank changes in tumor morphology are evident, are of considerable interest as potential biomarkers of treatment efficacy. Diffusion-weighted magnetic resonance imaging is sensitive to changes in water diffusion rates in tissues that result from structural variations in the local cellular environment, but conventional methods mainly reflect changes in tissue cellularity and do not convey information specific to microstructural variations at sub-cellular scales. We implemented a modified imaging technique using oscillating gradients of the magnetic field for evaluating water diffusion rates over very short spatial scales that are more specific for detecting changes in intracellular structure that may precede changes in cellularity. Results from a study of orthotopic 9L gliomas in rat brains indicate that this method can detect changes as early as 24 h following treatment with 1,3-bis(2-chloroethyl)-1-nitrosourea, when conventional approaches do not find significant effects. These studies suggest that diffusion imaging using oscillating gradients may be used to obtain an earlier indication of treatment efficacy than previous magnetic resonance imaging methods.

Coregistration of ultrasonography and magnetic resonance imaging with a preliminary investigation of the spatial colocalization of vascular endothelial growth factor receptor 2 expression and tumor perfusion in a murine tumor model.

We present an ultrasonography (US)-magnetic resonance imaging (MRI) coregistration technique and examine its application in a preliminary multimodal, multiparametric study in a preclinical model of breast cancer. Nine mice were injected with 67NR breast cancer cells and imaged 6 and 9 days later with 4.7 T MRI and high-frequency US. Tumor volumes from each data set were segmented independently by two investigators and coregistered using an iterative closest point algorithm. In addition to anatomic images, vascular endothelial growth factor receptor 2 (VEGFR2) distribution images from the central tumor slice using VEGFR2-targeted ultrasound contrast agent (UCA) and measurements of perfusion and extravascular-extracellular volume fraction using dynamic contrast-enhanced MRI were acquired from five mice for multiparametric coregistration. Parametric maps from each modality were coregistered and examined for spatial correlation. Average registration root mean square (RMS) error was 0.36 +/- 0.11 mm, less than approximately two voxels. Segmented volumes were compared between investigators to minimize interobserver variability; the average RMS error was 0.23 +/- 0.09 mm. In the preliminary study, VEGFR2-targeted UCA data did not demonstrate direct spatial correlation with magnetic resonance measures of vascular properties. In summary, a method for accurately coregistering small animal US and MRI has been presented that allows for comparison of quantitative metrics provided by the two modalities.

A spatial model of tumor-host interaction: application of chemotherapy.

In this paper we consider chemotherapy in a spatial model of tumor growth. The model, which is of reaction-diffusion type, takes into account the complex interactions between the tumor and surrounding stromal cells by including densities of endothelial cells and the extra-cellular matrix. When no treatment is applied the model reproduces the typical dynamics of early tumor growth. The initially avascular tumor reaches a diffusion limited size of the order of millimeters and initiates angiogenesis through the release of vascular endothelial growth factor (VEGF) secreted by hypoxic cells in the core of the tumor. This stimulates endothelial cells to migrate towards the tumor and establishes a nutrient supply sufficient for sustained invasion. To this model we apply cytostatic treatment in the form of a VEGF-inhibitor, which reduces the proliferation and chemotaxis of endothelial cells. This treatment has the capability to reduce tumor mass, but more importantly, we were able to determine that inhibition of endothelial cell proliferation is the more important of the two cellular functions targeted by the drug. Further, we considered the application of a cytotoxic drug that targets proliferating tumor cells. The drug was treated as a diffusible substance entering the tissue from the blood vessels. Our results show that depending on the characteristics of the drug it can either reduce the tumor mass significantly or in fact accelerate the growth rate of the tumor. This result seems to be due to complicated interplay between the stromal and tumor cell types and highlights the importance of considering chemotherapy in a spatial context.

A method for assessing the microvasculature in a murine tumor model using contrast-enhanced ultrasonography.

OBJECTIVE: The purpose of this study was to develop a method for assessing tumor vascularity in a preclinical model of breast cancer using contrast-enhanced ultrasonography. METHODS: Eight mice were injected with 67NR breast cancer cells on their hind limbs and imaged with ultrasonography 8 days later. Mice were injected with an ultrasound contrast agent (UCA), and a sequence of images of the resultant backscattered echoes was recorded before and after high-power "destruction" pulses for each of multiple parallel planes. From these, data maps of the maximum contrast enhancement (within each time course) were constructed for each pixel, which enabled reconstruction of high-resolution coregistered sections into a 3-dimensional (3D) volume reflecting tumor vascularity. Additional studies were performed to determine the duration and repeatability of image enhancement, and images were correlated with conventional 3D power Doppler measurements. RESULTS: The lifetime of the UCA in vivo was found to be 4.3 +/- 1.09 minutes (mean +/- SD). The 3D contrast-enhanced ultrasonographic technique produced images that correlated well with power Doppler images in specific regions but also depicted additional regions of flow surrounding the power Doppler signal. The mean correlation coefficient between voxel measurements of the central slice for each animal was 0.64 +/- 0.07 (P < .01). In addition, sequential studies in each animal were reproducible. CONCLUSIONS: A method producing high-resolution volumetric assessments of tumor vascularity in a preclinical model of breast cancer is shown that correlates with other ultrasonographic measures of blood flow, which may provide greater sensitivity to the microvasculature.

Contrast-enhanced transvaginal sonography of benign versus malignant ovarian masses: preliminary findings.

OBJECTIVE: The aim of this prospective study was to evaluate differences in contrast enhancement and contrast enhancement kinetics in benign versus malignant ovarian masses with pulse inversion harmonic transvaginal sonography. METHODS: Seventeen consecutive patients with 23 morphologically abnormal ovarian masses (solid or cystic with papillary excrescences, focally thickened walls, or irregular solid areas) smaller than 10 cm received a microbubble contrast agent intravenously while undergoing pulse inversion harmonic transvaginal sonography. The following parameters were assessed in all tumors: detectable contrast enhancement, time to peak enhancement (wash-in), peak contrast enhancement, half wash-out time, and area under the enhancement curve. Tumor histologic analysis was used to distinguish benign from malignant ovarian tumors. RESULTS: Fourteen benign masses and 9 malignancies were studied. There was a statistically significant difference in the peak enhancement (mean +/- SD, 23.3 +/- 2.8 versus 12.3 +/- 3.9 dB; P < .01), half wash-out time (139.9 +/- 43.6 versus 46.3 +/- 19.7 seconds; P < .01), and area under the enhancement curve (2012.9 +/- 532.9 versus 523.9 +/- 318 seconds(-1); P < .01) in malignant masses compared with benign disease. There was no statistically significant difference in the time to peak enhancement (26.1 +/- 6.3 versus 24.9 +/- 7.6 seconds; P = .07). CONCLUSIONS: Overall, our data showed a significant difference in the contrast enhancement kinetic parameters between benign and malignant ovarian masses.