Impact of contrast agent injection duration on dynamic contrast-enhanced MRI quantification in prostate cancer.
ABSTRACT: The volume transfer constant Ktrans , which describes the leakage of contrast agent (CA) from vasculature into tissue, is the most commonly reported quantitative parameter for dynamic contrast-enhanced (DCE-) MRI. However, the variation in reported Ktrans values between studies from different institutes is large. One of the primary sources of uncertainty is quantification of the arterial input function (AIF). The aim of this study is to determine the influence of the CA injection duration on the AIF and tracer kinetic analysis (TKA) parameters (i.e. Ktrans , kep and ve ). Thirty-one patients with prostate cancer received two DCE-MRI examinations with an injection duration of 5 s in the first examination and a prolonged injection duration in the second examination, varying between 7.5 s and 30 s. The DCE examination was carried out on a 3.0 T MRI scanner using a transversal T1 -weighted 3D spoiled gradient echo sequence (300 s duration, dynamic scan time of 2.5 s). Data of 29 of the 31 were further analysed. AIFs were determined from the phase signal in the left and right femoral arteries. Ktrans , kep and ve were estimated with the standard Tofts model for regions of healthy peripheral zone and tumour tissue. We observed a significantly smaller peak height and increased width in the AIF for injection durations of 15 s and longer. However, we did not find significant differences in Ktrans , kep or ve for the studied injection durations. The study demonstrates that the TKA parameters Ktrans , kep and ve , measured in the prostate, do not show a significant change as a function of injection duration.
Project description:The aim of this work is to develop a data-driven quantitative dynamic contrast-enhanced (DCE) MRI technique using Golden-angle RAdial Sparse Parallel (GRASP) MRI with high spatial resolution and high flexible temporal resolution and pharmacokinetic (PK) analysis with an arterial input function (AIF) estimated directly from the data obtained from each patient. DCE-MRI was performed on 13 patients with gynecological malignancy using a 3-T MRI scanner with a single continuous golden-angle stack-of-stars acquisition and image reconstruction with two temporal resolutions, by exploiting a unique feature in GRASP that reconstructs acquired data with user-defined temporal resolution. Joint estimation of the AIF (both AIF shape and delay) and PK parameters was performed with an iterative algorithm that alternates between AIF and PK estimation. Computer simulations were performed to determine the accuracy (expressed as percentage error [PE]) and precision of the estimated parameters. PK parameters (volume transfer constant [K<sup>trans</sup> ], fractional volume of the extravascular extracellular space [v<sub>e</sub> ], and blood plasma volume fraction [v<sub>p</sub> ]) and normalized root-mean-square error [nRMSE] (%) of the fitting errors for the tumor contrast kinetic data were measured both with population-averaged and data-driven AIFs. On patient data, the Wilcoxon signed-rank test was performed to compare nRMSE. Simulations demonstrated that GRASP image reconstruction with a temporal resolution of 1 s/frame for AIF estimation and 5 s/frame for PK analysis resulted in an absolute PE of less than 5% in the estimation of K<sup>trans</sup> and v<sub>e</sub> , and less than 11% in the estimation of v<sub>p</sub> . The nRMSE (mean ± SD) for the dual temporal resolution image reconstruction and data-driven AIF was 0.16 ± 0.04 compared with 0.27 ± 0.10 (p < 0.001) with 1 s/frame using population-averaged AIF, and 0.23 ± 0.07 with 5 s/frame using population-averaged AIF (p < 0.001). We conclude that DCE-MRI data acquired and reconstructed with the GRASP technique at dual temporal resolution can successfully be applied to jointly estimate the AIF and PK parameters from a single acquisition resulting in data-driven AIFs and voxelwise PK parametric maps.
Project description:<h4>Purpose</h4>To investigate whether preoperative histogram parameters of dynamic contrast-enhanced MRI (DCE-MRI) can assess the expression of Ki-67 in prostate cancer (PCa).<h4>Materials and methods</h4>A consecutive series of 76 patients with pathology-proven PCa who underwent routine DCE-MRI scans were retrospectively recruited. Quantitative parameters including the volume transfer constant (K<sup>trans</sup> ), rate contrast (K<sub>ep</sub> ), extracellular-extravascular volume fraction (V<sub>e</sub> ), and plasma volume (V<sub>p</sub> ) by outlining the three-dimensional volume of interest (VOI) of all lesions were processed. Then, the histogram analyses of these quantitative parameters were performed. The Spearman rank correlation analysis was used to evaluate the correlation of these parameters and Ki-67 expression of PCa. Receiver operating characteristic (ROC) curve analysis was adopted to evaluate the efficacy of these quantitative histogram parameters in identifying high Ki-67 expression from low Ki-67 expression of PCa.<h4>Results</h4>Eighty-eight PCa lesions were enrolled in this study, including 31 lesions with high Ki-67 expression and 57 lesions with low Ki-67 expression. The median, mean, 75th percentile, and 90th percentile derived from K<sup>trans</sup> and K<sub>ep</sub> had a moderately positive correlation with Ki-67 expression (r = 0.361-0.450, p < 0.05), in which both the median and mean of K<sup>trans</sup> had the highest positive correlation (r = 0.450, p < 0.05). The diagnostic efficacy of the K<sup>trans</sup> median, mean, 75th percentile, and 90th percentile, along with the K<sub>ep</sub> -based median and mean was assessed by the ROC curve. The area under the curve (AUC) of the mean for K<sup>trans</sup> was the highest (0.826). When the cut-off of the mean for K<sup>trans</sup> was ≥0.47/min, its Youden index, sensitivity, and specificity were 0.625, 0.871, and 0.754, respectively. The AUC of the median of K<sub>ep</sub> was the lowest (0.772).<h4>Conclusion</h4>The histogram of DCE-MRI quantitative parameters is correlated with Ki-67 expression, which has the potential to noninvasively assess the expression of Ki-67 with patients of PCa.
Project description:<h4>Objective</h4>This study assessed dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) parameters to prospectively predict survival outcomes in participants with advanced hepatocellular carcinoma (HCC) who received lenalidomide, a dual antiangiogenic and immunomodulatory agent, as second-line therapy in a Phase II clinical trial.<h4>Materials and methods</h4>Forty-four participants with advanced HCC who had progression after sorafenib as first-line treatment were prospectively enrolled. Pretreatment MRI parameters-obtained from DCE-MRI (peak, slope, AUC, K<sup>trans</sup>, K<sub>ep</sub>, and V<sub>e</sub>), apparent diffusion coefficient (ADC), and IVIM DWI (pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f))-were derived from the largest hepatic tumor. The Cox model was used to investigate the associations of the parameters with progression-free survival (PFS) and overall survival (OS).<h4>Results</h4>Median PFS and OS were 2.3 and 8.0 months, respectively. Univariate analysis showed that participants with a high slope (<i>p</i> = 0.024), K<sub>ep</sub> (<i>p</i> < 0.001), and ADC (<i>p</i> = 0.018) values had longer PFS than those with low values; participants with a small tumor size (<i>p</i> = 0.006), high slope (<i>p</i> = 0.01), ADC (<i>p</i> = 0.015), and f (<i>p</i> = 0.012) values had longer OS than those with low values did. Cox multivariable analysis revealed that K<sub>ep</sub> (<i>p</i> < 0.001) and ADC (<i>p</i> = 0.009) remained independent predictors of PFS; slope (<i>p</i> = 0.003) and ADC (<i>p</i> = 0.009) remained independent predictors of OS. Moreover, K<sub>ep</sub> and slope were still significant after Bonferroni correction was performed (<i>p</i> < 0.005).<h4>Conclusion</h4>Both pretreatment DCE-MRI and IVIM DWI parameters, especially slope and ADC, may predict PFS and OS in participants with HCC receiving lenalidomide as second-line therapy.
Project description:Temporal and spatial resolution of dynamic contrast-enhanced MR imaging (DCE-MRI) is critical to reproducibility, and the reproducibility of high-resolution (HR) DCE-MRI was evaluated. Thirty consecutive patients suspected to have brain tumors were prospectively enrolled with written informed consent. All patients underwent both HR-DCE (voxel size, 1.1 × 1.1 × 1.1 mm<sup>3</sup>; scan interval, 1.6 s) and conventional DCE (C-DCE; voxel size, 1.25 × 1.25 × 3.0 mm<sup>3</sup>; scan interval, 4.0 s) MRI. Regions of interests (ROIs) for enhancing lesions were segmented twice in each patient with glioblastoma (n = 7) to calculate DCE parameters (K<sup>trans</sup>, V<sub>p</sub>, and V<sub>e</sub>). Intraclass correlation coefficients (ICCs) of DCE parameters were obtained. In patients with gliomas (n = 25), arterial input functions (AIFs) and DCE parameters derived from T2 hyperintense lesions were obtained, and DCE parameters were compared according to WHO grades. ICCs of HR-DCE parameters were good to excellent (0.84-0.95), and ICCs of C-DCE parameters were moderate to excellent (0.66-0.96). Maximal signal intensity and wash-in slope of AIFs from HR-DCE MRI were significantly greater than those from C-DCE MRI (31.85 vs. 7.09 and 2.14 vs. 0.63; p < 0.001). Both 95<sup>th</sup> percentile K<sup>trans</sup> and V<sub>e</sub> from HR-DCE and C-DCE MRI could differentiate grade 4 from grade 2 and 3 gliomas (p < 0.05). In conclusion, HR-DCE parameters generally showed better reproducibility than C-DCE parameters, and HR-DCE MRI provided better quality of AIFs.
Project description:<h4>Objectives</h4>Hypoxia is associated with poor prognosis and treatment resistance in breast cancer. However, the temporally variant nature of hypoxia can complicate interpretation of imaging findings. We explored the relationship between hypoxia and vascular function in breast tumours through combined <sup>18</sup>F-fluoromisonidazole (<sup>18</sup> F-FMISO) PET/MRI, with simultaneous assessment circumventing the effect of temporal variation in hypoxia and perfusion.<h4>Methods</h4>Women with histologically confirmed, primary breast cancer underwent a simultaneous <sup>18</sup>F-FMISO-PET/MR examination. Tumour hypoxia was assessed using influx rate constant K<sub>i</sub> and hypoxic fractions (%HF), while parameters of vascular function (K<sup>trans</sup>, k<sub>ep</sub>, v<sub>e</sub>, v<sub>p</sub>) and cellularity (ADC) were derived from dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI, respectively. Additional correlates included histological subtype, grade and size. Relationships between imaging variables were assessed using Pearson correlation (r).<h4>Results</h4>Twenty-nine women with 32 lesions were assessed. Hypoxic fractions >?1% were observed in 6/32 (19%) cancers, while 18/32 (56%) tumours showed a %HF of zero. The presence of hypoxia in lesions was independent of histological subtype or grade. Mean tumour K<sup>trans</sup> correlated negatively with K<sub>i</sub> (r?=?-?0.38, p?=?0.04) and %HF (r?=?-?0.33, p?=?0.04), though parametric maps exhibited intratumoural heterogeneity with hypoxic regions colocalising with both hypo- and hyperperfused areas. No correlation was observed between ADC and DCE-MRI or PET parameters. %HF correlated positively with lesion size (r?=?0.63, p?=?0.001).<h4>Conclusion</h4>Hypoxia measured by <sup>18</sup>F-FMISO-PET correlated negatively with K<sup>trans</sup> from DCE-MRI, supporting the hypothesis of perfusion-driven hypoxia in breast cancer. Intratumoural hypoxia-perfusion relationships were heterogeneous, suggesting that combined assessment may be needed for disease characterisation, which could be achieved using simultaneous multimodality imaging.<h4>Key points</h4>• At the tumour level, hypoxia measured by <sup>18</sup>F-FMISO-PET was negatively correlated with perfusion measured by DCE-MRI, which supports the hypothesis of perfusion-driven hypoxia in breast cancer. • No associations were observed between 18F-FMISO-PET parameters and tumour histology or grade, but tumour hypoxic fractions increased with lesion size. • Intratumoural hypoxia-perfusion relationships were heterogeneous, suggesting that the combined hypoxia-perfusion status of tumours may need to be considered for disease characterisation, which can be achieved via simultaneous multimodality imaging as reported here.
Project description:<h4>Objectives</h4>Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA.<h4>Methods</h4>Fourteen individuals aged 40-60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including K<sup>trans</sup> and IAUC<sub>60</sub>. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months.<h4>Results</h4>K<sup>trans</sup> demonstrated the best test-retest repeatability (K<sup>trans</sup>/IAUC<sub>60</sub>/VEP ICCs 0.90/0.84/0.40, SDDs as % of OA mean 33/71/76%), discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC<sub>60</sub> and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains.<h4>Conclusions</h4>K<sup>trans</sup> demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies.<h4>Key points</h4>• Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies. • This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change. • The DCE-MRI biomarker K<sup>trans</sup> demonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies.
Project description:<h4>Background</h4>Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide biomarkers of the outcome of locally-advanced cervical carcinoma (LACC). There is, however, no agreement on how DCE-MR recordings should be analyzed. Previously, we have analyzed DCE-MRI data of LACC using non-model-based strategies. In the current study, we analyzed DCE-MRI data of LACC using the Tofts pharmacokinetic model, and the biomarkers derived from this analysis were compared with those derived from the non-model-based analyses.<h4>Methods</h4>Eighty LACC patients given cisplatin-based chemoradiotherapy with curative intent were included in the study. Treatment outcome was recorded as disease-free survival (DFS) and overall survival (OS). DCE-MRI series were analyzed voxelwise to produce K<sup>trans</sup> and v<sub>e</sub> frequency distributions, and ROC analysis was used to identify the parameters of the frequency distributions having the greatest potential as biomarkers. The prognostic power of these parameters was compared with that of the non-model-based parameters LETV (low-enhancing tumor volume) and TVIS (tumor volume with increasing signal).<h4>Results</h4>Poor DFS and OS were associated with low values of K<sup>trans</sup>, whereas there was no association between treatment outcome and v<sub>e</sub>. The K<sup>trans</sup> parameters having the greatest prognostic value were p35-K<sup>trans</sup> (the K<sup>trans</sup> value at the 35 percentile of a frequency distribution) and RV-K<sup>trans</sup> (the tumor subvolume with K<sup>trans</sup> values below 0.13?min<sup>-?1</sup>). Multivariate analysis including clinical parameters and p35-K<sup>trans</sup> or RV-K<sup>trans</sup> revealed that RV-K<sup>trans</sup> was the only independent prognostic factor of DFS and OS. There were significant correlations between RV-K<sup>trans</sup> and LETV and between RV-K<sup>trans</sup> and TVIS, and the prognostic power of RV-K<sup>trans</sup> was similar to that of LETV and TVIS.<h4>Conclusions</h4>Biomarkers of the outcome of LACC can be provided by analyzing DCE-MRI series using the Tofts pharmacokinetic model. However, these biomarkers do not appear to have greater prognostic value than biomarkers determined by non-model-based analyses.
Project description:The purpose of this study was to investigate whether ultra-high-field dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast at 7T using quantitative pharmacokinetic (PK) analysis can differentiate between benign and malignant breast tumors for improved breast cancer diagnosis and to predict molecular subtypes, histologic grade, and proliferation rate in breast cancer. In this prospective study, 37 patients with 43 lesions suspicious on mammography or ultrasound underwent bilateral DCE-MRI of the breast at 7T. PK parameters (K<sup>Trans</sup>, k<sub>ep</sub>, V<sub>e</sub>) were evaluated with two region of interest (ROI) approaches (2D whole-tumor ROI or 2D 10 mm standardized ROI) manually drawn by two readers (senior reader, R1, and R2) independently. Histopathology served as the reference standard. PK parameters differentiated benign and malignant lesions (n = 16, 27, respectively) with good accuracy (AUCs = 0.655-0.762). The addition of quantitative PK analysis to subjective BI-RADS classification improved breast cancer detection from 88.4% to 97.7% for R1 and 86.04% to 97.67% for R2. Different ROI approaches did not influence diagnostic accuracy for both readers. Except for K<sup>Trans</sup> for whole-tumor ROI for R2, none of the PK parameters were valuable to predict molecular subtypes, histologic grade, or proliferation rate in breast cancer. In conclusion, PK-enhanced BI-RADS is promising for the noninvasive differentiation of benign and malignant breast tumors.
Project description:The prediction of monoclonal antibody (mAb) disposition within solid tumors for individual patients is difficult due to inter-patient variability in tumor physiology. Improved a priori prediction of mAb pharmacokinetics in tumors may facilitate the development of patient-specific dosing protocols and facilitate improved selection of patients for treatment with anti-cancer mAb. Here, we report the use of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), with tumor penetration of the contrast agent gadobutrol used as a surrogate, to improve physiologically based pharmacokinetic model (PBPK) predictions of cetuximab pharmacokinetics in epidermal growth factor receptor (EGFR) positive xenografts. In the initial investigations, mice bearing Panc-1, NCI-N87, and LS174T xenografts underwent DCE-MRI imaging with the contrast agent gadobutrol, followed by intravenous dosing of an <sup>125</sup>Iodine-labeled, non-binding mAb (8C2). Tumor concentrations of 8C2 were determined following the euthanasia of mice (3 h-6 days after 8C2 dosing). Potential predictor relationships between DCE-MRI kinetic parameters and 8C2 PBPK parameters were evaluated through covariate modeling. The addition of the DCE-MRI parameter K<sup>trans</sup> alone or K<sup>trans</sup> in combination with the DCE-MRI parameter Vp on the PBPK parameters for tumor blood flow (QTU) and tumor vasculature permeability (σ<sub>TU</sub><sup>V</sup>) led to the most significant improvement in the characterization of 8C2 pharmacokinetics in individual tumors. To test the utility of the DCE-MRI covariates on a priori prediction of the disposition of mAb with high-affinity tumor binding, a second group of tumor-bearing mice underwent DCE-MRI imaging with gadobutrol, followed by the administration of <sup>125</sup>Iodine-labeled cetuximab (a high-affinity anti-EGFR mAb). The MRI-PBPK covariate relationships, which were established with the untargeted antibody 8C2, were implemented into the PBPK model with considerations for EGFR expression and cetuximab-EGFR interaction to predict the disposition of cetuximab in individual tumors (a priori). The incorporation of the K<sup>trans</sup> MRI parameter as a covariate on the PBPK parameters QTU and σ<sub>TU</sub><sup>V</sup> decreased the PBPK model prediction error for cetuximab tumor pharmacokinetics from 223.71 to 65.02%. DCE-MRI may be a useful clinical tool in improving the prediction of antibody pharmacokinetics in solid tumors. Further studies are warranted to evaluate the utility of the DCE-MRI approach to additional mAbs and additional drug modalities.
Project description:The objective of this study was to prospectively evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as an early imaging indicator of tumor histologic response to preoperative chemotherapy and as a possible prognostic factor for event-free survival (EFS) and overall survival in pediatric patients with newly diagnosed, nonmetastatic osteosarcoma who were treated on a single, multi-institutional phase 2 trial.Three serial DCE-MRI examinations at week 0 (before treatment), week 9, and week 12 (tumor resection) were performed in 69 patients with nonmetastatic osteosarcoma to monitor the response to preoperative chemotherapy. Four DCE-MRI kinetic parameters (the influx volume transfer constant [K(trans) ], the efflux rate constant [k(ep) ], the relative extravascular extracellular space [v(e) ], and the relative vascular plasma space [v(p) ]) and the corresponding differences (?K(trans) , ?k(ep) , ?v(e) , and ?v(p) ) of averaged kinetic parameters between the outer and inner halves of tumors were calculated to assess their associations with tumor histologic response, EFS, and overall survival.The parameters K(trans) , v(e) , v(p) , and k(ep) decreased significantly from week 0 to week 9 and week 12. The parameters K(trans) , v(p) , and ?k(ep) at week 9 were significantly different between responders and nonresponders (P = .046, P = .021, and P = .008, respectively). These 3 parameters were indicative of histologic response. The parameter ?v(e) at week 0 was a significant prognostic factor for both EFS (P = .02) and overall survival (P = .03).DCE-MRI was identified as a prognostic factor for EFS and overall survival before treatment on this trial and was indicative of a histologic response to neoadjuvant therapy. Further studies are needed to verify these findings with other treatment regimens and establish the potential role of DCE-MRI in the development of risk-adapted therapy for osteosarcoma.