Extravascular Extracellular Volume Fraction Research Articles

Diffusion Weighted and Dynamic Contrast-Enhanced MRI as a Predictor of Treatment Response in Head and Neck Cancer to Chemoradiotherapy: The Role of Early Intratreatment Scanning

Background: In locoregionally advanced Head and Neck Squamous Cell Carcinoma (HNSCC), intra-treatment scanning early during the course of Concomitant Chemoradiotherapy (CRT) with advanced functional Magnetic Resonance Imaging (MRI) could potentially allow for modification of treatment to maximize the chance of favourable outcome. The aim of this prospective study was to assess the predictive value of parameters derived from Dynamic Contrast-Enhanced (DCE) and Diffusion Weighted (DW) MRI for treatment response early during the course of CRT in patients with HNSCC.Methods: MRI scans were performed in 20 patients with locoregionally advanced HNSCC at baseline, after 10 Grays (Gy) and 40 Gy of CRT. DW and DCE derived parameters as well as the volumes were measured from primary tumours and lymph nodes. Tumour kinetic parameters (volume transfer constant (Ktrans), extracellular extravascular volume fraction (ve) and plasma volume fraction (Vp)) were assessed using the extended Tofts model. Relative changes in studied parameters from baseline to 10 Gy and 40 Gy were calculated. Factors predictive for treatment response were identified by the Firth logistic regression. Spearman’s rank correlation coefficient was used to investigate correlations among the parameters.Results: Responders showed a significant decrease in Ktrans after 10 Gy (median, -50.2 %; range, -25.1 to -90.9 %; P = 0.047). In addition, decreased ve after 10 Gy (median, -26.9%; range -76.7 to -126.8%) and increased apparent diffusion coefficient (ADC) after 40 Gy (median, 73.4%; range, 17.8 - 121.6%) were borderline significant (P=0.066 and P=0.079, respectively). Positive correlation between Ktrans and ve after 10 Gy (r = 0.823, P <0.05) was noticed.Conclusion: In HNSCC, early changes in DCE- and DWI-MRI derived parameters appear to predict tumour response before the actual morphologic changes occur.

T2*-Correction in Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Glioblastoma From a Half Dose of High-Relaxivity Contrast Agent.

The aim of this study was to evaluate the arterial input function (AIF) and tissue enhancement time curve (tissue function [TF]) obtained after the administration of a half-dose gadobenate dimeglumine (0.05-mmol/kg body weight [bw]) compared with a full dose (0.1-mmol/kg bw) of a standard-relaxivity contrast agent. We enrolled 40 adult patients with glioblastoma in an interindividual comparative study. Patients were randomized to 1 of the 2 study arms: 20 patients received 0.1-mmol/kg bw of gadoterate; the other 20 patients received 0.05-mmol/kg bw of gadobenate. The patients underwent dynamic contrast-enhanced magnetic resonance imaging examinations. Arterial input function, tissue enhancement time curve (TF), tumor transfer rate (K), and tumor extracellular-extravascular volume fraction (Ve) were calculated for each patients. Averaged AIF, TF, K, and Ve of both groups were compared. A significant difference (P = 0.001) between the peak AIF values obtained with the 2 different gadolinium-based contrast agents was observed. No difference was found between TFs (P = 0.35). Comparison on kinetic parameters revealed a significant difference for K (P = 0.047) but no difference for Ve (P = 0.74). The administration of half dose of the high-relaxivity contrast agent gadobenate is effective in improving AIF by reducing T2*-shortening effects on dynamic contrast-enhanced magnetic resonance imaging and ensuring at the same time an adequate signal enhancement in tumor tissue. The use of 0.05-mmol/kg bw of gadobenate not only is feasible but also can lead to a better estimation of K based on a more accurate AIF assessment.

Correlation of quantitative parameters of magnetic resonance perfusion-weighted imaging with vascular endothelial growth factor, microvessel density and hypoxia-inducible factor-1α in nasopharyngeal carcinoma: Evaluation on radiosensitivity study.

To investigate the correlation of parameters of magnetic resonance perfusion-weighted imaging (MR-PWI) with the expression of vascular endothelial growth factor (VEGF), hypoxia-inducible factor-1α (HIF-1α) and microvessel density (MVD) in nasopharyngeal carcinoma (NPC) so as to explore the value of predicting radiosensitivity. A prospective study. Department of Head-and-neck radiotherapy in Hunan Cancer Hospital. Ninety-four patients of NPC were included between December 2013 and December 2014. The expression of VEGF, MVD and HIF-1α was studied by immunohistochemistry, and magnetic resonance perfusion-weighted imaging (MR-PWI) was performed before and after undergoing radiotherapy (20Gy dose). Parameters of MR-PWI, volume of primary tumour and rate of tumour remission were measured and calculated. Patients with primary local tumour were then divided into completely response group (CR group) and partially response group (non-CR group) according to tumour regression condition. Relevant parameters were analysed by Spearman, and diagnostic efficiency of radiosensitivity was analysed by receiver operating characteristic curve (ROC). The expression of VEGF was positively correlated with MVD (r=.322,P<.05), but the expression of HIF-1α was no significant correlations with VEGF and MVD. The expression VEGF was in positive correlation with fractional plasma volume (fpv) (r=.339, P=.05) before radiotherapy. There was a significant difference in the quantitative parameters of MR-PWI between CR group and non-CR group during the course of radiotherapy and at the end of radiotherapy treatment. The change of blood reflux constant (Δkep20) and extravascular extracellular space volume fraction (ΔVe20) before and after treatment was positively correlated with primary local tumour remission condition after 3month treatment; Δkep and ΔVe were negatively correlated with primary local tumour remission condition after 3months. Tumour regression rate was only positively correlated with Ve and the average volume of primary tumour after 2week treatment (V1). ROC curve showed that R20≥65.69%, and was considered as a threshold to predict primary local tumour remission, with a sensitivity of 0.84 and specificity of 0.69, and area under the curve was 0.819 (P=.000). The parameters of MR-PWI with the expression of VEGF, HIF-1α and MVD could be guidance for predicting radiosensitivity in NPC.

Effects of sampling frequency on the accuracy of phenomenological and pharmacokinetic parameters derived from dynamic contrast enhanced MRI data

The sampling frequencies (fs) at which dynamic contrast enhanced (DCE) MRI data are acquired is known to affects the accuracy of derived parameters. Phenomenological parameters empirically characterise the shape and structure of the signal-time curves, whereas pharmacokinetic approaches estimate physiologically relevant parameters from the concentration-time curves, such as the volume-transfer constant (Ktrans) and the extravascular-extracellular fractional volume (ve). Both of these approaches have shown promise in the detection of prostate cancer, however to date a method has been lacking to quantitatively compare MR-measured to known ‘ground truth’ parameter values. In the present work, a newly developed anthropomorphic DCE-MRI prostate phantom was utilised to this end. Precisely known ‘healthy’ and ‘tumorous’ curves were measured using a 3T scanner (Philips, Netherlands) and 32-channel detector coil (3D-SPGR, TR/TE = 4.3/1.4 ms, α = 10°, FOV = 224 × 224 × 80 mm3, voxels = 1 × 1 × 4 mm3) at fs = 0.5, 0.26, 0.19, 0.12, 0.061, and 0.041 Hz. Phenomenological analysis revealed that wash-in was measured with the lowest errors ( 15%) at fs ⩾ 0.12 Hz, whereas wash-out gave comparatively higher errors (up to 27%) across this same range of fs. Lowest errors in time-to-peak ( 11%) were measured using fs = 2 s and 8.1 s. Pharmacokinetic analysis using the Tofts model gave errors in Ktrans and ve values 14% and 10%, for acquisitions with fs ⩾ 0.12 Hz and fs ⩾ 0.061 respectively, with errors increasing dramatically (up to 172%) with fs 0.061 Hz. Quantitative phantom-based approaches, such as the one used herein, offers the prospect of a standardisation in the way DCE-MRI is performed in the prostate, and possibly a wider acceptance of the technique for routine clinical use. Acknowledgement This work is funded by Irish Cancer Society Research Scholarship CRS13KNI (supported by Movember).

DCE- and DW-MRI as early imaging biomarkers of treatment response in a preclinical model of triple negative breast cancer.

This work evaluates quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) parameters as early biomarkers of response in a preclinical model of triple negative breast cancer (TNBC). The standard Tofts' model of DCE-MRI returns estimates of the volume transfer constant (Ktrans ) and the extravascular extracellular volume fraction (ve ). DW-MRI returns estimates of the apparent diffusion coefficient (ADC). Mice (n=38) were injected subcutaneously with MDA-MB-231. Tumors were grown to approximately 275mm3 and sorted into the following groups: saline controls, low-dose Abraxane (15mg/kg) and high-dose Abraxane (25mg/kg). Animals were imaged at days zero, one and three. On day three, tumors were extracted for immunohistochemistry. The positive percentage change in ADC on day one was significantly higher in both treatment groups relative to the control group (p<0.05). In addition, the positive percentage change in Ktrans was significantly higher than controls (p<0.05) on day one for the high-dose group and on days one and three for the low-dose group. The percentage change in tumor volume was significantly different between the high-dose and control groups on day three (p=0.006). Histology confirmed differences at day three through reduced numbers of proliferating cells (Ki67 staining) in the high-dose group (p=0.03) and low-dose group (p=0.052) compared with the control group. Co-immunofluorescent staining of vascular maturity [using von Willebrand Factor (vWF) and α-smooth muscle actin (α-SMA)] indicated significantly higher vascular maturation in the low-dose group compared with the controls on day three (p=0.03), and trending towards significance in the high-dose group compared with controls on day three (p=0.052). These results from quantitative imaging with histological validation indicate that ADC and Ktrans have the potential to serve as early biomarkers of treatment response in murine studies of TNBC.

Dynamic contrast-enhanced and diffusion-weighted MR imaging in the characterisation of small, non-palpable solid testicular tumours.

To explore the role of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), using semiquantitative and quantitative parameters, and diffusion-weighted (DW) MRI in differentiating benign from malignant small, non-palpable solid testicular tumours. We calculated the following DCE-MRI parameters of 47 small, non-palpable solid testicular tumours: peak enhancement (PE), time to peak (TTP), percentage of peak enhancement (Epeak), wash-in-rate (WIR), signal enhancement ratio (SER), volume transfer constant (Ktrans), rate constant (Kep), extravascular extracellular space volume fraction (Ve) and initial area under the curve (iAUC). DWI signal intensity and apparent diffusion coefficient (ADC) values were evaluated. Epeak, WIR, Ktrans , Kep and iAUC were higher and TTP shorter in benign compared to malignant lesions (p < 0.05). All tumours had similar ADC values (p > 0.07). Subgroup analysis limited to the most frequent histologies - Leydig cell tumours (LCTs) and seminomas - replicated the findings of the entire set. Best diagnostic cutoff value for identification of seminomas: Ktrans ≤0.135 min-1, Kep ≤0.45 min-1, iAUC ≤10.96, WIR ≤1.11, Epeak ≤96.72, TTP >99 s. DCE-MRI parameters are valuable in differentiating between benign and malignant small, non-palpable testicular tumours, especially when characterising LCTs and seminomas. • DCE-MRI may be used to differentiate benign from malignant non-palpable testicular tumours. • Seminomas show lower Ktrans, Kep and iAUC values. • ADC values are not valuable in differentiating seminomas from LCTs. • Semiquantitative DCE-MRI may be used to characterise small, solid testicular tumours.

Diagnostic value of quantitative pharmacokinetic parameters and relative quantitative pharmacokinetic parameters in breast lesions with dynamic contrast-enhanced MRI

Objective: To explore the differential between the value of dynamic contrast-enhanced MRI quantitative pharmacokinetic parameters and relative pharmacokinetic quantitative parameters in breast lesions. Methods: Retrospective analysis of 255 patients(262 breast lesions) who was obtained by clinical palpation , ultrasound or full-field digital mammography , and then all lessions were pathologically confirmed in Zhongda Hospital, Southeast University from May 2012 to May 2016. A 3.0 T MRI scanner was used to obtain the quantitative MR pharmacokinetic parameters: volume transfer constant (K(trans)), exchange rate constant (k(ep))and extravascular extracellular volume fraction (V(e)). And measured the quantitative pharmacokinetic parameters of normal glands tissues which on the same side of the same level of the lesions; and then calculated the value of relative pharmacokinetic parameters: rK(rans)、rk(ep) and rV(e).To explore the diagnostic value of two pharmacokinetic parameters in differential diagnosis of benign and malignant breast lesions using receiver operating curves and model of logistic regression. Results: (1)There were significant differences between benign lesions and malignant lesions in K(trans) and k(ep) (t=15.489, 15.022, respectively, P<0.05), there were no significant differences between benign lesions and malignant lesions in V(e)(t=-2.346, P>0.05). The areas under the ROC curve(AUC)of K(trans), k(ep) and V(e) between malignant and benign lesions were 0.933, 0.948 and 0.387, the sensitivity of K(trans), k(ep) and V(e) were 77.1%, 85.0%, 51.0% , and the specificity of K(trans), k(ep) and V(e) were 96.3%, 93.6%, 60.8% for the differential diagnosis of breast lesions if taken the maximum Youden's index as cut-off. (2)There were significant differences between benign lesions and malignant lesions in rK(trans), rk(ep) and rV(e) (t=14.177, 11.726, 2.477, respectively, P<0.05). The AUC of rK(trans), rk(ep) and rV(e) between malignant and benign lesions were 0.963, 0.903 and 0.575, the sensitivity of rK(trans), rk(ep) and rV(e) were 85.6%, 71.9%, 52.9% , and the specificity of rK(trans), rk(ep) and rV(e) were 94.5%, 92.7%, 60.6% for the differential diagnosis of breast lesions.(3)There was no significant difference in the area under the ROC curve between the predictive probability of quantitative pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters(Z=0.867, P=0.195). Conclusion: There was no significant difference between the quantitative parameter values (K(trans,) k(ep)) and the relative quantitative parameter values (rK(trans,) rk(ep)) in diagnosis of breast lesions, which were important parameters in differential diagnosis of benign and malignant breast lesions.

Combined diffusion-weighted imaging and dynamic contrast-enhanced MRI for differentiating radiologically indeterminate malignant from benign orbital masses

To evaluate the performance of the combination of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for differentiating radiologically indeterminate malignant from benign orbital masses. Sixty-five patients with orbital masses (36 benign and 29 malignant) underwent DW and DCE MRI examinations for pre-treatment evaluation. The apparent diffusion coefficient (ADC) was derived from DW imaging data using the mono-exponential model. The volume transfer constant (Ktrans), the flux rate constant between the extravascular extracellular space and the plasma (Kep), and the extravascular extracellular volume fraction (Ve) were calculated using modified Tofts model. Differences in quantitative metrics were tested using independent-samples t test. Receiver operating characteristic (ROC) curve analyses were used to determine and compare the diagnostic ability of each significant metric. The malignant group demonstrated significantly lower ADC (0.711±0.260 versus 1.187±0.389, p<0.001) and higher Kep values (1.265±0.637 versus 0.871±0.610, p=0.008) than the benign group. Optimal diagnostic performance (area under the ROC curve [AUC], 0.941; sensitivity, 0.966; specificity, 0.917) could be achieved using combined ADC and Kep values as the diagnostic index. The diagnostic performance of the combination of ADC and Kep was significantly better than Kep alone (p=0.006). Compared with ADC alone, combined ADC and Kep values also showed higher AUC (0.941 versus 0.898), although the difference did not reach statistical significance (p=0.220). Kep and ADC could help to differentiate radiologically indeterminate malignant from benign orbital masses. The combination of DW and DCE MRI might improve the differentiating performance.

Correlation between histogram analysis of dynamic contrast enhanced MRI and diffusion weighted imaging intravoxel incoherent motion quantitative parameters and Gleason score of prostate cancer

Objective To investigate the value and diagnostic efficiency of the quantitative dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) parameters using three dimention (3D)-histogram analysis for discriminating the Gleason score (GS) of prostate cancer. Methods A total of 53 patients pathologically confirmed as prostate cancer by systemic prostate biopsy who had routine, DCE and DWI-MRI scans were retrospectively analyzed. There were 15 cases for low-risk and 38 cases for intermediate/high-risk prostate cancer. The 3D ROI of all lesions based on T2WI was achieved by image registration to get the quantitative parameters of DCE-MRI and DWI-IVIM. The parameters of DCE-MRI contains: transfer constant (Ktrans), rate constant (Kep) and extracellular-extravascular volume fraction (Ve).The DWI-IVIM related quantitative parameters were ADC, diffusion coefficient (D), diffusion coefficient related to perfusion (D*) and perfusion fraction (f). Then the histogram analysis of these quantitative parameters was performed to get the mean, median, 25th percentile, 75th percentile, Skewness and Kurtosis. Using the Spearman rank correlation analysis to evaluate the correlation of these parameters and GS of prostate cancer. The diagnostic performance of these quantitative histogram parameters related to the GS in identifying low-risk and intermediate/high-risk of prostate cancer was carried by ROC. Results The Kep and Ktrans (mean, median, 25th, 75th) of DCE-MRI were positively correlated with GS (r value was 0.346 to 0.696, P<0.05). The ADC (mean, median, 25th, 75th), D (mean, median, 25th, 75th, Skewness, Kurtosis) and D*(25th) of DWI-IVIM were correlated with GS (r value was -0.544 to 0.428, P<0.05). The DCE-MRI quantitative parameters Kep (25th) had the highest area under curve (AUC, 0.961); The ADC (median) and D (25th) had higher AUC (0.832, 0.888) in the quantitative parameters of DWI-IVIM, the difference between Kep(25th) and ADC (median) was statistically significant (Z value was 2.212, P value was 0.027). The difference of AUC between Kep (25th) and D (25th), D (25th) and ADC (median) was not statistically significant (Z values were 1.027 and 1.398, P values were 0.162 and 0.304, respectively). Conclusion DCE and IVIM quantitative parameters (Kep, Ktrans, ADC, D) histogram analysis results are correlated with GS, and can be used for distinguishing low-risk from intermediate/high-risk prostate cancer. Key words: Prostate neoplasms; Magnetic resonance imaging; Comparative study

Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI

PurposeKinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model. Material and methods74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux Ktrans and kep and, their ratio, ve, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction vp] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)]. ResultsArterial AIF more often led to implausible ve >100% values (p<0.0001). AIF source alteration rendered different absolute kinetic parameters (p<0.0001), except for kep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08–0.87) and only consistent >0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with vp derived from an AIF in the SSS (p=0.03; AUC 0.74). ConclusionThe AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by vp) and showed the least number of implausible ve values.

Quantitative dynamic contrast-enhanced magnetic resonance imaging in a VX2 rabbit liver tumour model using different gadolinium-based contrast agents: comparison of DCE-MRI quantitative results between Magnevist and Eovist.

Quantitative dynamic contrast enhanced MRI (DCE-MRI) can offer information related to tumour perfusion and permeability (Ktrans), rate constant (Kep), extravascular extracellular volume fraction (Ve) and distribution volume (Vd). Different types of gadolinium-based contrast agents (GBCAs) may traverse the vascular wall with different velocities owing to their physicochemical characteristics. The purpose of this article was to compare the DCE-MRI quantitative results (Ktrans, Kep, Ve and Vd) between Magnevist and Eovist in a VX2 rabbit liver tumour model. Sixteen rabbits (body weight, 3 Kg; random gender) containing implanted hepatic VX2 carcinomas were randomly divided into two groups based on the regimen of MRI contrast agent administered, eight rabbits in each group. All rabbits underwent a liver DCE-MRscan before tumour transplantation. Fourteen days after tumour transplantation, the eight rabbits in Group A (Magnevist group) underwent a liver DCE-MR scan in a 3.0 T Magnetom Verio MR scanner (Siemens Healthcare, AD, Germany) after the administration of Magnevist at the flow rate of 1 ml s–1. The Group B rabbits underwent the same scan except for the administration of Eovist at the same flow rate. Twenty-four hours after the initial DCE-MRI, repeat DCE-MRI was performed with the cross-over GBCA at the same flow rate in each group. Every rabbit received 0.6 ml GBCA (0.2 ml Kg–1) during each DCE-MRI. Ktrans, Kep, Ve and Vd were measured in the tumour lesion and compared with normal liver tissue in the same slice. A pathologic examination was also performed. Hepatocellular carcinoma was diagnosed in all 16 rabbits by pathologic examination. There were no significant differences in Ktrans, Ve, Kep and Vd between the two groups of rabbits (p > 0.05). The Ktrans, Ve, Kep and Vd of the VX2 rabbit liver tumour model were significantly higher than the normal liver parenchyma (0.742 ± 0.086 vs 0.027 ± 0.002, 7.345 ± 0.043 vs 6.721 ± 0.035, 0.101 ± 0.005 vs 0.101 ± 0.005, 0.419 ± 0.083 vs 0.037 ± 0.005, respectively; p < 0.01). The Ktrans, Ve and Vd of Eovist group were significantly higher compared with the values in the Magnevist group (0.116 ± 0.016 vs 0.010 ± 0.002, respectively, p < 0.01; 0.101 ± 0.005 vs 0.004 ± 0.0009, respectively, p < 0.01; 0.419 ± 0.083 vs 0.037 ± 0.005, respectively, p < 0.001). There was no significant difference in Kep between the Eovist and Magnevist groups (7.345 ± 0.043 vs 6.721 ± 0.035, respectively; p > 0.05). In the VX2 rabbit liver tumour model, DCE-MRI performed with different types of GBCA can develop different quantitative results with respect to Ktrans, Ve and Vd. The liver-specific GBCA, Eovist, is more sensitive than the general GBCA, Magnevist, in detecting tumour perfusion and permeability.

Correlation between perfusion-weighted magnetic resonance imaging parameters and vascular endothelial growth factors, microvascular density, hypoxia-inducible factor 1α

Objective To investigate the relationship between perfusion-weighted magnetic resonance imaging (PWI) parameters and vascular endothelial growth factor (VEGF), microvascular density (MVD) and hypoxia-inducible factor 1α (HIF-1α) in nasopharyngeal carcinoma (NPC). Methods 94 NPC patients were prospectively studied, and the region of interest was noted by fiberscope. Before the treatment , the common magnetic resonance and PWI were used to obtain the images of region of interest and the relative parameters including transfer constant (Ktrans), rate constant of back flux (Kep), extravascular extracellular volume fraction(Ve), fractional plasm volume (fPV) were calculated, then the marking tissues were detected by biopsy. Immunohistochemical staining was conducted to detect the expressions of VEGF, MVD and HIF-1α, and the relationships between the parameters and proteins were analyzed. Results The positive rates of VEGF and HIF-1α in the NPC tissues were 71.27 % (67/94) and 30.85 % (29/94). There was a significant positive correlation between VEGF and MVD [VEGF-positve vs. VEGF-negtive: (31.273 ± 14.81)/mm2 vs. (23.633 ± 16.56)/mm2, r= 0.322, P= 0.037], but the expression of HIF-1α was not significantly correlated with the VEGF and MVD. The significantly positive correlation was found between VEGF and fPV (r= 0.339, P= 0.041), besides, there were no relations among the rest parameters. Conclusion PWI parameter fPV is positively related with VEGF, indicating that PWI could show angiogensis of NPC to some degree, and provide a guidance for predicting the radiosensitivity of NPC. Key words: Nasopharyngeal neoplasms; Magnetic resonance imaging; Perfusion imaging; Vascular endothelial growth factors; Hypoxia-inducible factor 1, alpha subunit; Microvascular density

Multiparametric approach with diffusion-weighted imaging and dynamic contrast-enhanced MRI: a comparison study for differentiating between benign and malignant bone lesions in adults

To evaluate and compare the diagnostic performance of quantitative parameters derived from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating benign and malignant bone tumours. Fifty-five patients (age range, 21-82 years; mean age, 55 years) underwent pretreatment MRI. Apparent diffusion coefficient (ADC) values were calculated by DWI. The DCE-MRI data were analysed for the volume transfer constant (Ktrans), extravascular extracellular volume fraction (Ve), and volume rate constant (Kep), and Ktrans/ADC ratio. Each parameter's performance was evaluated using the area under the receiver operating characteristic (ROC) curv (AUC), and their AUCs were compared. ROC curves were analysed and each parameter's optimal cut-off value was determined, from which each parameter was evaluated for sensitivity, specificity, accuracy, and positive and negative predictive values. The odds ratio (OR) with 95% confidence interval for detecting malignant bone lesions after adjusting the age factor of each parameter was estimated. All parameter values (except Ve) were significantly different between benign and malignant bone tumours (p<0.05). The Ktrans had a significantly greater AUC than Ve (p=0.03). The Ktrans/ADC and Kep had the best sensitivity (0.917) and specificity (0.632), respectively. The Kep and Ktrans/ADC had the best positive (0.811) and negative (0.769) predictive values, respectively. The OR was highest for Ktrans/ADC (17.38; p=0.0013). The Ktrans, Kep, ADC, and Ktrans/ADC could help to detect malignant lesions from bone tumours and Ktrans/ADC appears to be the superior variable among them.

Evaluation of optimized magnetic resonance perfusion imaging scanning time window after contrast agent injection for differentiating benign and malignant breast lesions.

The aim of the study was evaluate the 3.0 T magnetic resonance (MR) perfusion imaging scanning time window following contrast injection for differentiating benign and malignant breast lesions and to determine the optimum scanning time window for increased scanner usage efficiency and reduced diagnostic adverse risk factors. A total of 52 women with breast abnormalities were selected for conventional MR imaging and T1 dynamic-enhanced imaging. Quantitative parameters [volume transfer constant (Ktrans), rate constant (Kep) and extravascular extracellular volume fraction (Ve)] were calculated at phases 10, 20, 30, 40 and 50, which represented time windows at 5, 10, 15, 20 and 25 min, respectively, following injection of contrast agent. The association of the parameters at different phases with benign and malignant tumor diagnosis was analyzed. MR perfusion imaging was verified as an effective modality in the diagnosis of breast malignancies and the best scanning time window was identified: i) Values of Ktrans and Kep at all phases were statistically significant in differentiating benign and malignant tumors (P<0.05), while the value of Ve had statistical significance only at stage 10, but not at any other stages (P>0.05); ii) values of Ve in benign tumors increased with phase number, but achieved no obvious changes at different phases in malignant tumors; iii) the optimum scanning time window of breast perfusion imaging with 3.0 T MR was between phases 10 and 30 (i.e., between 5 and 15 min after contrast agent injection). The variation trend of Ve values at different phases may serve as a diagnostic reference for differentiating benign and malignant breast abnormalities. The most efficient scanning time window was indicated to be 5 min after contrast injection, based on the observation that the Ve value only had statistical significance in diagnosis at stage 10. However, the optimal scanning time window is from 5 to 15 min following the injection of contrast agent, since that the variation trend of Ve is able to serve as a diagnostic reference.

Abstract A23: A finite element model of perfusion and diffusion within tumors based on dynamic contrast enhanced magnetic resonance imaging

Abstract Quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data provides estimates of physiological parameters that characterize tissue volume fractions, blood flow, and vascular permeability. While it provides a reasonable description of well-vascularized tissue, the standard models do not include the effects of intra-voxel diffusion, which is hypothesized to play a significant role in distributing contrast agent in poorly vascularized voxels1. This mechanism has been studied in silico using simulated tissue regions, but the results have yet to be tested with experimental data. We hypothesize that explicit incorporation of the contrast agent diffusion into the standard models is required to accurately model delivery and retention of the contrast agent within poorly vascularized regions. To investigate the effect of the diffusion of contrast agent within a tumor, nude athymic mice are subcutaneously implanted with BT474 cancer cells, and tumors develop for 4-6 weeks prior to performing DCE-MRI. Following imaging, the tumors are extracted, sectioned, and stained for vascularity (CD31) and viability/cellularity (H&amp;E). Stained central slice sections were digitized in high resolution, segmented in MATLAB (Natick, MA), and a finite element model (FEM) was developed. A population arterial input function (AIF)2 serves as the source of contrast agent delivery into the FEM at the vascular boundaries, while the diffusion equation distributes the contrast agent through the extracellular space. The distribution of contrast agent over time within an imaging voxel is converted from concentration to MR signal intensity, and fit to the extended Tofts model3, providing estimates of vascular permeability and perfusion (Ktrans), extravascular extracellular volume fraction (ve), and vascular volume fraction (vp). These values are then compared to the true tissue volume fractions, determined by tissue segmentation, and an assigned (reasonable) set of Ktrans values. In order to verify the accuracy of the histologically segmented FEM, the simulated DCE-MRI signal is compared to in vivo experimental DCE-MRI scans of the same tumor. Comparison is completed by registering DCE-MRI voxels to simulated voxel domains, and directly measuring the difference between simulated and experimental signal intensities. Using a Ktrans of 0.4 min-1 and a diffusion constant of 3 x 10-5 mm2/s, the extended Tofts model poorly predicts tissue properties, with predicted Ktrans errors ranging from -95% to 68%, ve errors ranging -80% to 13%, and vp errors ranging 32% to 381%. Notably, necrotic regions of the tumor are subject to the highest level of error in the Tofts approximation of these parameters. Each of the maximum absolute prediction errors listed above occur in voxels with a vp value below 0.5% and ve above 80%. In contrast, the Tofts model can more accurately predict vp when the true value is above 5%, and most accurately predicts ve when its true value is below 70%. These results indicate that the lack of a diffusion term in the extended Tofts model can lead to significant errors in the estimates of physiological properties of tumor tissue in vivo. This is especially notable in regions with both a low vp and high ve, where the tissue is necrotic and poorly perfused. These results call for the inclusion of a diffusive term in the analysis of DCE-MRI in order to accurately model and understand contrast agent perfusion in a tumor. By including such a term, the diagnostic and predictive power of Ktrans ¸ vp, and ve, could be further improved. Our ongoing efforts for this research include further refining histology segmentation and model validation by comparing both simulated and measured DCE-MRI signal intensities. 1. Barnes, et al. PLoS One . 2014;9:e108726 2. Loveless, et al. Magn Reson Med . 2012; 67:226-236. 3. Tofts &amp; Kermode. Magn Reson Med . 1991;17:357-367. Citation Format: Ryan T. Woodall, Stephanie L. Eldridge, Anna G. Sorace, Thomas E. Yankeelov. A finite element model of perfusion and diffusion within tumors based on dynamic contrast enhanced magnetic resonance imaging. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A23.

Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast.

Purpose Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGVα2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes. Results NN produced the lowest image error (SER: 29.1), while TV/TGVα2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799). Conclusion TV/TGVα2 should be used as temporal constraints for CS DCE-MRI of the breast.

Dynamic contrast-enhanced MRI of gastric cancer: Correlations of the pharmacokinetic parameters with histological type, Lauren classification, and angiogenesis

PurposeTo compare the pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in gastric cancers of different histological type and Lauren classification, and to investigate whether DCE-MRI parameters correlate with vascular endothelial growth factor (VEGF) expression levels in gastric cancer. MethodsIncluded were 32 patients with gastric cancer who underwent DCE-MRI of the upper abdomen before tumor resection. DCE-MRI parameters including the volume transfer coefficient (Ktrans), reverse reflux rate constant (Kep), and extracellular extravascular volume fraction (Ve) were calculated from the tumor region. Post-operative specimens were used for determination of histological differentiation (i.e., non-mucinous, mucinous, or signet-ring-cell adenocarcinoma) as well as Lauren classification (intestinal type or diffuse type). VEGF expression was examined for assessing angiogenesis. DCE-MRI parameters with different histological type and Lauren classification were compared using independent samples t-test and analysis of variance, respectively. Correlations between DCE-MRI parameters and VEGF expression grades were tested using Spearman correlation analysis. ResultsAmong gastric adenocarcinomas of three different histological types, mucinous adenocarcinomas showed a higher Ve and lower Ktrans than the others (P<0.01). Between the two Lauren classifications, the diffuse type showed a higher Ve than the intestinal type (P<0.001). The mean Ktrans showed a significantly positive correlation with VEGF (r=0.762, P<0.001). ConclusionDCE-MRI permits noninvasive prediction of tumor histological type and Lauren classification and estimation of tumor angiogenesis in gastric cancer. DCE-MRI parameters can be used as imaging biomarkers to predict the biologic aggressiveness of a tumor as well as patient prognosis.

Automated Processing of Dynamic Contrast-Enhanced MRI: Correlation of Advanced Pharmacokinetic Metrics with Tumor Grade in Pediatric Brain Tumors.

Pharmacokinetic parameters from dynamic contrast-enhanced MR imaging have proved useful for differentiating brain tumor grades in adults. In this study, we retrospectively reviewed dynamic contrast-enhanced perfusion data from children with newly diagnosed brain tumors and analyzed the pharmacokinetic parameters correlating with tumor grade. Dynamic contrast-enhanced MR imaging data from 38 patients were analyzed by using commercially available software. Subjects were categorized into 2 groups based on pathologic analyses consisting of low-grade (World Health Organization I and II) and high-grade (World Health Organization III and IV) tumors. Pharmacokinetic parameters were compared between the 2 groups by using linear regression models. For parameters that were statistically distinct between the 2 groups, sensitivity and specificity were also estimated. Eighteen tumors were classified as low-grade, and 20, as high-grade. Transfer constant from the blood plasma into the extracellular extravascular space (Ktrans), rate constant from extracellular extravascular space back into blood plasma (Kep), and extracellular extravascular volume fraction (Ve) were all significantly correlated with tumor grade; high-grade tumors showed higher Ktrans, higher Kep, and lower Ve. Although all 3 parameters had high specificity (range, 82%-100%), Kep had the highest specificity for both grades. Optimal sensitivity was achieved for Ve, with a combined sensitivity of 76% (compared with 71% for Ktrans and Kep). Pharmacokinetic parameters derived from dynamic contrast-enhanced MR imaging can effectively discriminate low- and high-grade pediatric brain tumors.

A cannabinoid link between mitochondria and memory

To evaluate the performance of the combination of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for differentiating radiologically indeterminate malignant from benign orbital masses.Sixty-five patients with orbital masses (36 benign and 29 malignant) underwent DW and DCE MRI examinations for pre-treatment evaluation. The apparent diffusion coefficient (ADC) was derived from DW imaging data using the mono-exponential model. The volume transfer constant (Ktrans), the flux rate constant between the extravascular extracellular space and the plasma (Kep), and the extravascular extracellular volume fraction (Ve) were calculated using modified Tofts model. Differences in quantitative metrics were tested using independent-samples t test. Receiver operating characteristic (ROC) curve analyses were used to determine and compare the diagnostic ability of each significant metric.The malignant group demonstrated significantly lower ADC (0.711±0.260 versus 1.187±0.389, p<0.001) and higher Kep values (1.265±0.637 versus 0.871±0.610, p=0.008) than the benign group. Optimal diagnostic performance (area under the ROC curve [AUC], 0.941; sensitivity, 0.966; specificity, 0.917) could be achieved using combined ADC and Kep values as the diagnostic index. The diagnostic performance of the combination of ADC and Kep was significantly better than Kep alone (p=0.006). Compared with ADC alone, combined ADC and Kep values also showed higher AUC (0.941 versus 0.898), although the difference did not reach statistical significance (p=0.220).Kep and ADC could help to differentiate radiologically indeterminate malignant from benign orbital masses. The combination of DW and DCE MRI might improve the differentiating performance.

Dynamic contrast enhanced MR imaging for evaluation of angiogenesis of hepatocellular nodules in liver cirrhosis in N-nitrosodiethylamine induced rat model.

To investigate whether dynamic contrast -enhanced MRI (DCE-MRI) can distinguish the type of liver nodules in a rat model with N-nitrosodiethylamine- induced cirrhosis. Liver nodules in cirrhosis were induced in 60 male Wistar rats via 0.01%N-nitrosodiethylamine in the drinking water for 35-100 days. The nodules were divided into three groups: regenerative nodule (RN), dysplastic nodule (DN), and hepatocellular carcinoma (HCC). DCE-MRI was performed, and parameters including transfer constant (Ktrans), rate constant (Kep), extravascular extracellular space volume fraction (Ve), and initial area under the contrast concentration versus time curve (iAUC) were measured and compared. The highest Ktrans and iAUC values were seen in HCC, followed by DN and RN (all P < 0.05). The area under the receiver operating characteristic curve (AUROC) for DN and HCC were 0.738 and 0.728 for Ktrans and iAUC, respectively. The AUROC for HCC were 0.850 and 0.840 for Ktrans and iAUC, respectively. Ordinal logistic regression analysis showed that Ktrans had a high goodness of fit (0.970, 95% confidence interval, 13.751-24.958). DCE-MRI is a promising method to differentiate of liver nodules. Elevated Ktrans suggested that the nodules may be transformed into HCC. • DCE-MRI is promising for differentiating among RN, DN, and HCC • K trans and iAUC positively correlated with malignancy degree of liver nodules • Elevated K trans suggests that the nodules may be transformed into HCC.