Pretreatment multimodality imaging can provide useful anatomical and functional data about tumors, including perfusion and possibly hypoxia status. The purpose of our study was to assess non-invasively the tumor microenvironment of neck nodal metastases in patients with head and neck (HN) cancer by investigating the relationship between tumor perfusion measured using Dynamic Contrast Enhanced MRI (DCE-MRI) and hypoxia measured by 18F-fluoromisonidazole (18F-FMISO) PET.
Methods and Materials
Thirteen newly diagnosed HN cancer patients with metastatic neck nodes underwent DCE-MRI and 18F-FMISO PET imaging prior to chemotherapy and radiation therapy. The matched regions of interests from both modalities were analyzed. To examine the correlations between DCE-MRI parameters and standard uptake value (SUV) measurements from 18F-FMISO PET, the non-parametric Spearman correlation coefficient was calculated. Furthermore, DCE-MRI parameters were compared between nodes with 18F-FMISO uptake and nodes with no 18F-FMISO uptake using Mann-Whitney U tests.
For the 13 patients, a total of 18 nodes were analyzed. The nodal size strongly correlated with the 18F-FMISO SUV (ρ=0.74, p<0.001). There was a strong negative correlation between the median kep (ρ=−0.58, p=0.042) and the 18F-FMISO SUV. Hypoxic nodes (moderate to severe 18F-FMISO uptake) had significantly lower median Ktrans (p=0.049) and median kep (p=0.027) values than did non-hypoxic nodes (no 18F-FMISO uptake).
This initial evaluation of the preliminary results support the hypothesis that in metastatic neck lymph nodes, hypoxic nodes are poorly perfused (i.e., have significantly lower kep and Ktrans values) compared to non-hypoxic nodes.
Dynamic Contrast Enhanced-MRI (DCE-MRI); 18F-fluoromisonidazole (FMISO) PET; 18F-fluorodeoxyglucose (FDG); head and neck (HN) cancer
To evaluate the value of dynamic contrast enhanced Magnetic Resonance Imaging (DCE-MRI) without endorectal coil (EC) in the detection of local recurrent prostate cancer (PC) after radical prostatectomy (RP).
Material and methods
Thirty-three patients with recurrent PC underwent DCE-MRI without EC before salvage radiotherapy (RT). At median 15 (mean 16±4.9, range 12–27) months after completion of RT all patients showed complete biochemical response. Additional follow up post RT DCE-MRI scans were available. Prostate specific antigen (PSA) levels at the time of imaging were correlated to the imaging findings.
In 22/33 patients (67%) early contrast enhancing nodules were detected in the post-prostatectomy fossa on pre-RT DCE-MRI images. The average pre-RT PSA level of the 22 patients with positive pre-RT DCE-MRI findings was significantly higher (mean, 0.74±0.64 ng/mL) compared to the pre-RT PSA level of the 11 patients with negative pre-RT DCE-MRI (mean, 0.24±0.13 ng/mL) (p<0.001). All post-RT DCE-MRI images showed complete resolution of initial suspicious lesions. A pre-RT PSA cut-off value of ≥0.54 ng/ml readily predicted a positive DCE-MRI finding.
This is the first study that shows that DCE-MRI without EC can detect local recurrent PC with an estimated accuracy of 83% at low PSA levels. All false negative DCE-MRI scans were detected using a PSA cut-off of ≥0.54 ng/mL.
Prostate cancer; PSA recurrence; Salvage radiotherapy; Dynamic contrast enhanced MRI; Gross tumor volume
The aim of this study was to compare the MR imaging features between estrogen receptor (ER) positive and negative breast cancers.
Materials and Methods
Breast MRI of 90 consecutive patients confirmed with invasive ductal carcinoma, 51 ER positive and 39 ER negative, were studied. The tumor morphology and dynamic contrast enhanced (DCE) kinetics were evaluated and compared based on ACR BI-RADS MRI lexicon. Enlarged axillary lymph nodes on MRI and choline detection using MR spectroscopy were also analyzed and compared. For patients receiving axillary node dissection the pathological nodal status was also compared.
ER negative breast cancer had bigger tumors compared to ER positive cancer (3.6 ± 2.0 cm vs. 1.8 ± 1.3 cm, P < 0.00005). ER negative cancer was more likely to exhibit non-mass type enhancements compared to ER positive cancer (P < 0.005). Enlarged axillary lymph nodes were more frequently identified on MRI in ER negative compared to ER positive patients (P < 0.05 ). After excluding patients with more aggressive disease undergoing neoadjuvant chemotherapy, MRI and pathological axillary lymph node did not find significant differences between them. ER negative cancer was more likely to show the malignant type enhancement kinetics (P = 0.15), rim enhancement (P = 0.15), and choline detection on MRS (P = 0.23) compared to ER positive cancer, but not reaching the statistical significance level.
ER negative breast cancer was more aggressive, with larger tumor size and more non-mass type enhancement lesions, and was more likely to show malignant DCE kinetics and MRS features. These might be related to its poorer cellular differentiation and/or a higher angiogenesis.
MR imaging; estrogen receptor; progesterone receptor; breast cancer; invasive ductal carcinoma; MR spectroscopy
Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) of the breast is a routinely used imaging method which is highly sensitive for detecting breast malignancy. Specificity, though, remains suboptimal. Dynamic susceptibility contrast magnetic resonance imaging (DSC MRI), an alternative dynamic contrast imaging technique, evaluates perfusion-related parameters unique from DCE MRI. Previous work has shown that the combination of DSC MRI with DCE MRI can improve diagnostic specificity, though an additional administration of intravenous contrast is required. Dual-echo MRI can measure both T1W DCE MRI and T2*W DSC MRI parameters with a single contrast bolus, but has not been previously implemented in breast imaging. We have developed a dual-echo gradient-echo sequence to perform such simultaneous measurements in the breast, and use it to calculate the semi-quantitative T1W and T2*W related parameters such as peak enhancement ratio, time of maximal enhancement, regional blood flow, and regional blood volume in 20 malignant lesions and 10 benign fibroadenomas in 38 patients. Imaging parameters were compared to surgical or biopsy obtained tissue samples. Receiver operating characteristic (ROC) curves and area under the ROC curves were calculated for each parameter and combination of parameters. The time of maximal enhancement derived from DCE MRI had a 90% sensitivity and 69% specificity for predicting malignancy. When combined with DSC MRI derived regional blood flow and volume parameters, sensitivity remained unchanged at 90% but specificity increased to 80%. In conclusion, we show that dual-echo MRI with a single administration of contrast agent can simultaneously measure both T1W and T2*W related perfusion and kinetic parameters in the breast and the combination of DCE MRI and DSC MRI parameters improves the diagnostic performance of breast MRI to differentiate breast cancer from benign fibroadenomas.
Pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) time-course data allows estimation of quantitative parameters such as Ktrans (rate constant for plasma/interstitium contrast agent transfer), ve (extravascular extracellular volume fraction), and vp (plasma volume fraction). A plethora of factors in DCE-MRI data acquisition and analysis can affect accuracy and precision of these parameters and, consequently, the utility of quantitative DCE-MRI for assessing therapy response. In this multicenter data analysis challenge, DCE-MRI data acquired at one center from 10 patients with breast cancer before and after the first cycle of neoadjuvant chemotherapy were shared and processed with 12 software tools based on the Tofts model (TM), extended TM, and Shutter-Speed model. Inputs of tumor region of interest definition, pre-contrast T1, and arterial input function were controlled to focus on the variations in parameter value and response prediction capability caused by differences in models and associated algorithms. Considerable parameter variations were observed with the within-subject coefficient of variation (wCV) values for Ktrans and vp being as high as 0.59 and 0.82, respectively. Parameter agreement improved when only algorithms based on the same model were compared, e.g., the Ktrans intraclass correlation coefficient increased to as high as 0.84. Agreement in parameter percentage change was much better than that in absolute parameter value, e.g., the pairwise concordance correlation coefficient improved from 0.047 (for Ktrans) to 0.92 (for Ktrans percentage change) in comparing two TM algorithms. Nearly all algorithms provided good to excellent (univariate logistic regression c-statistic value ranging from 0.8 to 1.0) early prediction of therapy response using the metrics of mean tumor Ktrans and kep (=Ktrans/ve, intravasation rate constant) after the first therapy cycle and the corresponding percentage changes. The results suggest that the interalgorithm parameter variations are largely systematic, which are not likely to significantly affect the utility of DCE-MRI for assessment of therapy response.
Cervical tumors of 38 cervix cancer patients were scanned by T1-weighted dynamic contrast enhanced (DCE) MRI and then by DCE-CT on the same day. Gadodiamide and iohexol were respectively used as the low-molecular-weight contrast agent in DCE-MRI and DCE-CT. Under an extended Tofts model, DCE-MRI data were analyzed using either individual arterial input functions estimated by a multiple reference tissue method or a population arterial input function by Parker et al., whereas DCE-CT data were analyzed using the arterial input function directly measured from the external iliac arteries. The derived quantitative parameters of cervical tumors were compared between DCE-MRI and DCE-CT. When using the individual multiple reference tissue method arterial input functions to analyze the DCE-MRI data, the correlation coefficients between DCE-MRI- and DCE-CT-derived parameters were, respectively, back-flux rate constant (r = 0.80), extravascular extracellular fractional volume (r = 0.73), contrast agent transfer rate (r = 0.62), and blood plasma volume (r = 0.32); when using the Parker population arterial input function, the correlation coefficients were back-flux rate constant (r = 0.79), extravascular extracellular fractional volume (r = 0.77), contrast agent transfer rate (r = 0.63), and blood plasma volume (r = 0.58). Tumor parametric maps derived by DCE-MRI and DCE-CT had very similar morphologies. However, the means of most derived quantitative parameters were significantly different between the two imaging methods. Close correlation of quantitative parameters derived from two independent imaging modalities suggests both are measuring similar tumor physiologic variables.
dynamic contrast enhanced MRI; dynamic contrast enhanced CT; quantitative analysis; correlation; tracer kinetic modeling; T1 MRI
To assess the early predictive power of MRI perfusion and volume parameters, during early treatment of cervical cancer, for primary tumor control and disease-free-survival.
Materials and Methods
Three MRI examinations were obtained in 101 patients before and during therapy (at 2–2.5 and 4–5 weeks) for serial dynamic contrast enhanced (DCE) perfusion MRI and 3-dimensional (3D) tumor volume measurement. Plateau Signal Intensity (SI) of the DCE curves for each tumor pixel of all 3 MRI examinations was generated, and pixel-SI distribution histograms were established to characterize the heterogeneous tumor. The degree and quantity of the poorly-perfused tumor subregions, which were represented by low-DCE pixels, was analyzed by using various lower percentiles of SI (SI%) from the pixel histogram. SI% ranged from SI2.5% to SI20% with increments of 2.5%. SI%, mean SI, and 3D-volume of the tumor were correlated with primary tumor control and disease-free-survival, using Student t-test, Kaplan-Meier analysis and log-rank test. The mean post-therapy follow-up time for outcome assessment was 6.8 years (range: 1.2–12.3 years).
Tumor volume, mean SI, and SI% showed significant prediction of the long-term clinical outcome, and this prediction was provided as early as 2–2.5 weeks into treatment. An SI5% of <2.05 and residual tumor volume of ≥30 cm3 in the MRI obtained at 2–2.5 weeks of therapy provided the best prediction of unfavorable 8-year primary tumor control (73% vs. 100%, p=0.006) and disease-free-survival rate (47% vs. 79%, p=0.001), respectively.
Our results show that MRI parameters quantifying perfusion status and residual tumor volume provide very early prediction of primary tumor control and disease-free-survival. This functional imaging based outcome predictor can be obtained in the very early phase of cytotoxic therapy within 2–2.5 weeks of therapy start. The predictive capacity of these MRI parameters, indirectly reflecting the heterogeneous delivery pattern of cytotoxic agents, tumor oxygenation and the bulk of residual presumably therapy-resistant tumor, requires future study.
MRI; Functional; Microcirculation; Uterine cervical neoplasms; Radiotherapy
The objective of our study was to predict response to chemoradiation therapy in patients with head and neck squamous cell carcinoma (HNSCC) by combined use of diffusion-weighted imaging (DWI) and high-spatial-resolution, high-temporal-resolution dynamic contrast-enhanced MRI (DCE-MRI) parameters from primary tumors and metastatic nodes.
SUBJECTS AND METHODS
Thirty-two patients underwent pretreatment DWI and DCE-MRI using a modified radial imaging sequence. Postprocessing of data included motion-correction algorithms to reduce motion artifacts. The median apparent diffusion coefficient (ADC), volume transfer constant (Ktrans), extracellular extravascular volume fraction (ve), and plasma volume fraction (vp) were computed from primary tumors and nodal masses. The quality of the DCE-MRI maps was estimated using a threshold median chi-square value of 0.10 or less. Multivariate logistic regression and receiver operating characteristic curve analyses were used to determine the best model to discriminate responders from nonresponders.
Acceptable χ2 values were observed from 84% of primary tumors and 100% of nodal masses. Five patients with unsatisfactory DCE-MRI data were excluded and DCEMRI data for three patients who died of unrelated causes were censored from analysis. The median follow-up for the remaining patients (n = 24) was 23.72 months. When ADC and DCE-MRI parameters (Ktrans, ve, vp) from both primary tumors and nodal masses were incorporated into multivariate logistic regression analyses, a considerably higher discriminative accuracy (area under the curve [AUC] = 0.85) with a sensitivity of 81.3% and specificity of 75% was observed in differentiating responders (n = 16) from nonresponders (n = 8).
The combined use of DWI and DCE-MRI parameters from both primary tumors and nodal masses may aid in prediction of response to chemoradiation therapy in patients with HNSCC.
diffusion-weighted imaging; dynamic contrast-enhanced MRI; metastatic lymph nodes; primary tumors; squamous cell carcinomas of head and neck
High interstitial fluid pressure (IFP) in the primary tumor is associated with poor disease-free survival in locally advanced cervical carcinoma. A noninvasive assay is needed to identify cervical cancer patients with highly elevated tumor IFP because these patients may benefit from particularly aggressive treatment. It has been suggested that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with gadolinium diethylene-triamine penta-acetic acid (Gd-DTPA) as contrast agent may provide useful information on the IFP of cervical carcinomas. In this preclinical study, we investigated whether DCE-MRI with contrast agents with higher molecular weights (MW) than Gd-DTPA would be superior to Gd-DTPA-based DCE-MRI.
CK-160 human cervical carcinoma xenografts were subjected to DCE-MRI with Gd-DTPA (MW of 0.55 kDa) or gadomelitol (MW of 6.5 kDa) as contrast agent before tumor IFP was measured invasively with a Millar SPC 320 catheter. The DCE-MRI was carried out at a spatial resolution of 0.23 × 0.23 × 2.0 mm3 and a time resolution of 14 s by using a 1.5-T whole-body scanner and a slotted tube resonator transceiver coil constructed for mice. Parametric images were derived from the DCE-MRI recordings by using the Tofts iso-directional transport model and the Patlak uni-directional transport model.
When gadomelitol was used as contrast agent, significant positive correlations were found between the parameters of both pharmacokinetic models and tumor IFP. On the other hand, significant correlations between DCE-MRI-derived parameters and IFP could not be detected with Gd-DTPA as contrast agent.
Gadomelitol is a superior contrast agent to Gd-DTPA in DCE-MRI of the IFP of CK-160 cervical carcinoma xenografts. Clinical studies attempting to develop DCE-MRI-based assays of the IFP of cervical carcinomas should involve contrast agents with higher MW than Gd-DTPA.
Cervical carcinoma xenografts; DCE-MRI; Gadomelitol; Gd-DTPA; Interstitial fluid pressure
RATIONALE AND OBJECTIVES
To (1) describe associations between measures of tumor perfusion by dynamic contrast-enhanced breast MRI (DCE-MRI), blood flow by 15O-water PET and metabolism by 18F-FDG PET and (2) improve our understanding of tumor enhancement on MRI through independent measures of tumor metabolism and blood flow.
MATERIALS AND METHODS
We performed a retrospective analysis of the existing PET and MRI databases from the departments of Nuclear Medicine and Radiology. We identified patients with locally advanced breast cancer who underwent 15O-water/18F-FDG PET within 1 month of clinical DCE-MRI between February 2004 and August 2006. The 15O-water PET blood flow and 18F-FDG metabolic rate (MR) and tissue transport constant (K1) in the primary malignancy were calculated. DCE-MRI peak percent enhancement (PE) and peak signal enhancement ratio (SER) were measured for each tumor. Correlations and regression analysis of these variables were performed.
Fifteen patients with complete PET and DCE-MRI data were included in the analysis cohort. Peak SER correlated significantly with blood flow (r=0.73, p=0.002) and K1 (r=0.76, p=0.001). However, peak SER did not correlate significantly with FDG MR (r=0.44, p=0.101). There were no significant correlations between peak PE and any of the PET parameters.
Our findings suggest that tumor perfusion, represented by 15O-water PET blood flow, is an important factor in the MRI enhancement of LABC. A lack of correlation of FDG MR with blood flow and DCE-MRI kinetics suggests that 18F-FDG PET provides complementary metabolic information independent of vascular factors.
To investigate the relationship between changes in vascularity and metabolic activity measured by dynamic contrast-enhanced MRI (DCE-MRI) and dynamic 18F-FDG-positron emission tomography (PET) in breast tumors undergoing neoadjuvant chemotherapy.
Materials and Methods
PET and MRI examinations were performed in 14 patients with locally advanced breast cancer (LABC) before and after chemotherapy. Dynamic 18F-FDG PET measures included 18F-FDG transport rate constant from blood to tissue (K1) and metabolism flux constant (Ki). DCE-MRI measures included initial peak enhancement (PE), signal enhancement ratio (SER), and tumor volume. Spearman rank-order correlations were assessed between changes in PET and MRI parameters, and measures were compared between patients with and without pathologic complete response (pCR) by Mann-Whitney U test.
Changes in glucose delivery (PET K1) were closely correlated with changes in tumor vascularity as reflected by DCE-MRI SER (ρ=0.83, p<0.001). Metabolic changes in PET Ki showed moderate correlations with vascularity changes as reflected by SER (ρ=0.71) and PE (ρ=0.76), and correlated closely with MRI tumor volume (ρ=0.79, p<0.001). Decreases in K1, Ki, SER, and PE were greater for patients with pCR compared to those with residual disease (p<0.05).
Dynamic 18F-FDG PET and DCE-MRI tumor measures of tumor metabolism, vascularity, and volume were well correlated for assessing LABC response to neoadjuvant chemotherapy and significantly discriminated pathologic complete responders. Further work is necessary to assess the value of combined PET and MRI for evaluating tumor pharmacodynamics in response to novel therapy.
dynamic 18F-FDG positron emission tomography (PET); dynamic contrast-enhanced MRI (DCE-MRI); pathologic response; treatment; locally advanced breast cancer
We evaluated the value of a combined approach of T1-weighted (T1W) imaging, T2-weighted (T2W) imaging, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and diffusion-weighted imaging (DWI) for the detection of prostate cancer and extracapsular extension (ECE) in patients with prostate cancer by using pathologic data after radical prostatectomy.
Materials and Methods
From April 2009 to December 2011, 126 patients who underwent radical prostatectomy and prostate MRI for prostate cancer were analyzed retrospectively. The MRI findings were compared with the pathologic findings of the radical prostatectomy specimens in each patient. The sensitivity, specificity, and accuracy of the detection of prostate cancer and extracapsular extension were analyzed.
The prostate cancer detection rate by use of T1W and T2W imaging, DCE-MRI, and their combination was 65.1%, 69.0%, and 80.2%, respectively (p=0.023). The detection rate using T1W and T2W imaging, DCE-MRI, DWI, and their combination was 57.7%, 65.4%, 67.3%, and 80.8%, respectively (p=0.086). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of combination MRI (T1W, T2W, and DCE-MRI) for ECE were 46.4%, 91.4%, 83.9%, and 68.1%, respectively. The sensitivity of combination MRI (T1W, T2W, and DCE-MRI) for ECE tended to increase as the prostate-specific antigen level rose (p=0.010). The sensitivity, specificity, PPV, and NPV of combination MRI (T1W, T2W, DCE-MRI, and DWI) for ECE were 65.0%, 87.5%, 76.5%, and 80.0%, respectively.
A combined approach of T1W, T2W, and DCE-MRI with DWI demonstrated an accurate detection rate of prostate cancer. Also, combination approaches showed a high specificity for predicting ECE, although sensitivity was relatively lower. Therefore, these methods are reliable for predicting prostate cancer. However, a new protocol is necessary to enhance the sensitivity for predicting ECE.
Diagnosis; Magnetic resonance imaging; Prostatic neoplasms
To investigate the correlations between parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and prognostic factors in rectal cancer.
Materials and Methods
We studied 29 patients with rectal cancer who underwent gadolinium contrast-enhanced, T1-weighted DCE-MRI with a three Tesla scanner prior to surgery. Signal intensity on DCE-MRI was independently measured by two observers to examine reproducibility. A time-signal intensity curve was generated, from which four semiquantitative parameters were calculated: steepest slope (SLP), time to peak (Tp), relative enhancement during a rapid rise (Erise), and maximal enhancement (Emax). Morphologic prognostic factors including T stage, N stage, and histologic grade were identified. Tumor angiogenesis was evaluated in terms of microvessel count (MVC) and microvessel area (MVA) by morphometric study. As molecular factors, the mutation status of the K-ras oncogene and microsatellite instability were assessed. DCE-MRI parameters were correlated with each prognostic factor using bivariate correlation analysis. A p-value of <0.05 was considered significant.
Erise was significantly correlated with N stage (r=-0.387 and -0.393, respectively, for two independent data), and Tp was significantly correlated with histologic grade (r=0.466 and 0.489, respectively). MVA was significantly correlated with SLP (r=-0.532 and -0.535, respectively) and Erise (r=-0.511 and -0.446, respectively). MVC was significantly correlated with Emax (r=-0.435 and -0.386, respectively). No significant correlations were found between DCE-MRI parameters and T stage, K-ras mutation, or microsatellite instability.
DCE-MRI may provide useful prognostic information in terms of histologic differentiation and angiogenesis in rectal cancer.
Colorectal neoplasms; prognosis; diagnostic imaging; magnetic resonance imaging
Dynamic contrast enhanced MRI (DCE-MRI) can estimate parameters relating to blood flow and tissue volume fractions and therefore may be used to characterize the response of breast tumors to treatment. To assess treatment response, values of these DCE-MRI parameters are observed at different time points during the course of treatment. We propose a method whereby DCE-MRI data sets obtained in separate imaging sessions can be co-registered to a common image space, thereby retaining spatial information so that serial DCE-MRI parameter maps can be compared on a voxel-by-voxel basis. In performing inter-session breast registration, one must account for patient repositioning and breast deformation, as well as changes in tumor shape and volume relative to other imaging sessions. One challenge is to optimally register the normal tissues while simultaneously preventing tumor distortion. We accomplish this by extending the adaptive bases algorithm (ABA) through adding a tumor-volume preserving constraint in the cost function. We also propose a novel method to generate the simulated breast MR images, which can be used to evaluate the proposed registration algorithm quantitatively. The proposed nonrigid registration algorithm is applied to both simulated and real longitudinal 3D high resolution MR images and the obtained transformations are then applied to lower resolution physiological parameter maps obtained via DCE-MRI. The registration results demonstrate the proposed algorithm can successfully register breast MR images acquired at different time points and allow for analysis of the registered parameter maps.
Breast Cancer; image registration; DCE-MRI; neoadjuvant chemotherapy; treatment monitoring
To correlate proton magnetic resonance spectroscopy (1H-MRS), dynamic contrast-enhanced MRI (DCE-MRI) and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) in nodal metastases of patients with head and neck squamous cell carcinoma (HNSCC) for assessment of tumor biology. Additionally, pretreatment multimodality imaging (MMI) was evaluated for its efficacy in predicting short-term response to treatment.
Methods and Materials
Metastatic neck nodes were imaged with 1H-MRS, DCE-MRI and 18F-FDG PET in 16 patients with newly diagnosed HNSCC before treatment. Short-term radiological response was evaluated at 3–4 months. The correlations between 1H-MRS (choline concentration, Cho/W), DCE-MRI (volume transfer constant, Ktrans; volume fraction of the extravascular extracellular space, ve; and redistribution rate constant, kep) and 18F-FDG PET (standard uptake value, SUV; and total lesion glycolysis, TLG) were calculated using non-parametric Spearman rank correlation. To predict the short-term response, logistic regression analysis was performed.
A significant positive correlation was found between Cho/W and TLG (ρ = 0.599, p = 0.031). Cho/W correlated negatively with heterogeneity measures std(ve) (ρ = −0.691, p = 0.004) and std(kep) (ρ = −0.704, p = 0.003). SUVmax values correlated strongly with MRI tumor volume (ρ = 0.643, p = 0.007). Logistic regression indicated that std(Ktrans) and SUVmean were significant predictors of short-term response (p < 0.07).
Pretreatment multi-modality imaging using 1H-MRS, DCE-MRI and 18F-FDG PET is feasible in HNSCC patients with nodal metastases. Additionally, combined DCE-MRI and 18F-FDG PET parameters were predictive of short-term response to treatment.
Head and neck squamous cell carcinoma; 1H-MRS; DCE-MRI; 18F-FDG PET; short-term treatment response
Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1–2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss’ κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm3 sRes. There were no significant differences in signal-to-noise (P = 0.45) and contrast-to-noise (P = 0.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P < 0.0001) for lesion size to 1.00 (P < 0.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis.
Rationale and Objectives
Normal-appearing stromal tissues surrounding breast tumors can harbor abnormalities that lead to increased risk of local recurrence. The objective of this study was to develop a new imaging methodology to characterize the signal patterns of stromal tissue and to investigate their association with recurrence-free survival following neoadjuvant chemotherapy.
Materials and Methods
Fifty patients with locally-advanced breast cancer were imaged with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before (V1) and after one cycle (V2) of adriamycin-cytoxan therapy. Contrast enhancement in normal-appearing stroma around the tumor was characterized by the mean percent enhancement (PE) and mean signal enhancement ratio (SER) in distance bands of 5 mm from the tumor edge. Global PE and SER were calculated by averaging all stromal bands 5 to 40 mm from tumor. Proximity-dependent PE and SER were analyzed using a linear mixed effects model and Cox proportional hazards model for recurrence-free survival.
The mixed effects model displayed a decreasing radial trend in PE at both V1 and V2. An increasing trend was less pronounced in SER. Survival analysis showed that the hazard ratio estimates for each unit decrease in global SER was statistically significant at V1 [estimated hazard ratio = 0.058, 95% Wald CI (0.003, 1.01), likelihood ratio p = 0.03]; but was not so for V2.
These findings show that stromal tissue outside the tumor can be quantitatively characterized by DCE-MRI, and suggest that stromal enhancement measurements may be further developed for use as a potential predictor of recurrence/disease-free survival following therapy.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables tumor vascular physiology to be assessed. Within the tumor tissue, contrast agents (gadolinium chelates) extravasate from intravascular into the extravascular extracellular space (EES), which results in a signal increase on T1-weighted MRI. The rate of contrast agents extravasation to EES in the tumor tissue is determined by vessel leakiness and blood flow. Thus, the signal measured on DCE-MRI represents a combination of permeability and perfusion. The semi-quantitative analysis is based on the calculation of heuristic parameters that can be extracted from signal intensity-time curves. These enhancing curves can also be deconvoluted by mathematical modeling to extract quantitative parameters that may reflect tumor perfusion, vascular volume, vessel permeability and angiogenesis. Because hepatocellular carcinoma (HCC) is a hypervascular tumor, many emerging therapies focused on the inhibition of angiogenesis. DCE-MRI combined with a pharmacokinetic model allows us to produce highly reproducible and reliable parametric maps of quantitative parameters in HCC. Successful therapies change quantitative parameters of DCE-MRI, which may be used as early indicators of tumor response to anti-angiogenesis agents that modulate tumor vasculature. In the setting of clinical trials, DCE-MRI may provide relevant clinical information on the pharmacodynamic and biologic effects of novel drugs, monitor treatment response and predict survival outcome in HCC patients.
Dynamic contrast-enhanced magnetic resonance imaging; Perfusion magnetic resonance imaging; Hepatocellular carcinoma; Angiogenesis inhibitors; Clinical trials
Poor disease-free and overall survival rates in locally advanced cervical cancer are associated with a tumor micro-environment characterized by extensive hypoxia, interstitial hypertension, and high lactate concentrations. The potential of gadolinium diethylenetriamine pentaacetic acid-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the microenvironment and microenvironment-associated aggressiveness of cervical carcinomas was investigated in this preclinical study. CK-160 and TS-415 cervical carcinoma xenografts were used as tumor models. DCE-MRI was carried out at 1.5 T, and parametric images of Ktrans and ve were produced by pharmacokinetic analysis of the DCE-MRI series. Pimonidazole was used as a marker of hypoxia. A Millar catheter was used to measure tumor interstitial fluid pressure (IFP). The concentrations of glucose, adenosine triphosphate (ATP), and lactate were measured by induced metabolic bioluminescence imaging. High incidence of lymph node metastases was associated with high hypoxic fraction and high lactate concentration in CK-160 tumors and with high IFP and high lactate concentration in TS-415 tumors. Low Ktrans was associated with high hypoxic fraction, low glucose concentration, and high lactate concentration in tumors of both lines and with high incidence of metastases in CK-160 tumors. Associations between ve and microenvironmental parameters or metastatic propensity were not detected in any of the tumor lines. Taken together, this preclinical study suggests that Ktrans is a potentially useful biomarker for poor outcome of treatment in advanced cervical carcinoma. The possibility that Ktrans may be used to identify patients with cervical cancer who are likely to benefit from particularly aggressive treatment merits thorough clinical investigations.
The type of contrast enhancement kinetic curve (i.e., persistently enhancing, plateau, or washout) seen on dynamic contrast-enhanced MRI (DCE-MRI) of the breast is predictive of malignancy. Qualitative estimates of the type of curve are most commonly used for interpretation of DCE-MRI. The purpose of this study was to compare qualitative and quantitative methods for determining the type of contrast enhancement kinetic curve on DCE-MRI.
MATERIALS AND METHODS
Ninety-six patients underwent breast DCE-MRI. The type of DCE-MRI kinetic curve was assessed qualitatively by three radiologists on two occasions. For quantitative assessment, the slope of the washout curve was calculated. Kappa statistics were used to determine inter- and intraobserver agreement for the qualitative method. Matched sample tables, the McNemar test, and receiver operating characteristic (ROC) curve statistics were used to compare quantitative versus qualitative methods for establishing or excluding malignancy.
Seventy-eight lesions (77.2%) were malignant and 23 (22.8%) were benign. For the qualitative assessment, the intra- and interobserver agreement was good (κ = 0.76–0.88), with an area under the ROC curve (AUC) of 0.73–0.77. For the quantitative method, the highest AUC was 0.87, reflecting significantly higher diagnostic accuracies compared with qualitative assessment (p < 0.01 for the difference between the two methods).
Quantitative assessment of the type of contrast enhancement kinetic curve on breast DCE-MRI resulted in significantly higher diagnostic performance for establishing or excluding malignancy compared with assessment based on the standard qualitative method.
breast cancer; breast imaging; contrast-enhanced MRI; dynamic MRI; kinetic curve; washout
To evaluate the interobserver variability of gross tumor volume (GTV) - delineation of Dominant Intraprostatic Lesions (DIPL) in patients with prostate cancer using published MRI criteria for multiparametric MRI at 3 Tesla by 6 different observers.
Material and methods
90 GTV-datasets based on 15 multiparametric MRI sequences (T2w, diffusion weighted (DWI) and dynamic contrast enhanced (DCE)) of 5 patients with prostate cancer were generated for GTV-delineation of DIPL by 6 observers. The reference GTV-dataset was contoured by a radiologist with expertise in diagnostic imaging of prostate cancer using MRI. Subsequent GTV-delineation was performed by 5 radiation oncologists who received teaching of MRI-features of primary prostate cancer before starting contouring session. GTV-datasets were contoured using Oncentra Masterplan® and iplan® Net. For purposes of comparison GTV-datasets were imported to the Artiview® platform (Aquilab®), GTV-values and the similarity indices or Kappa indices (KI) were calculated with the postulation that a KI > 0.7 indicates excellent, a KI > 0.6 to < 0.7 substantial and KI > 0.5 to < 0.6 moderate agreement. Additionally all observers rated difficulties of contouring for each MRI-sequence using a 3 point rating scale (1 = easy to delineate, 2 = minor difficulties, 3 = major difficulties).
GTV contouring using T2w (KI-T2w = 0.61) and DCE images (KI-DCE = 0.63) resulted in substantial agreement. GTV contouring using DWI images resulted in moderate agreement (KI-DWI = 0.51). KI-T2w and KI-DCE was significantly higher than KI-DWI (p = 0.01 and p = 0.003). Degree of difficulty in contouring GTV was significantly lower using T2w and DCE compared to DWI-sequences (both p < 0.0001). Analysis of delineation differences revealed inadequate comparison of functional (DWI, DCE) to anatomical sequences (T2w) and lack of awareness of non-specific imaging findings as a source of erroneous delineation.
Using T2w and DCE sequences at 3 Tesla for GTV-definition of DIPL in prostate cancer patients by radiation oncologists with knowledge of MRI features results in substantial agreement compared to an experienced MRI-radiologist, but for radiotherapy purposes higher KI are desirable, strengthen the need for expert surveillance. DWI sequence for GTV delineation was considered as difficult in application.
Prostate cancer; Gross tumor volume; Focal dose escalation; Simultaneous integrated boost; 3 Tesla MRI; Interobserver variability
The objective of this study was to assess changes in the water apparent diffusion coefficient (ADC) and in pharmacokinetic parameters obtained from the fast-exchange regime (FXR) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) during neoadjuvant chemotherapy in breast cancer.
Materials and Methods
Eleven patients with locally advanced breast cancer underwent MRI examination prior to and after chemotherapy but prior to surgery. A 1.5-T scanner was used to obtain T1, ADC and DCE-MRI data. DCE-MRI data were analyzed by the FXR model returning estimates of Ktrans (volume transfer constant), νe (extravascular extracellular volume fraction) and τsi (average intracellular water lifetime). Histogram and correlation analyses assessed parameter changes post-treatment.
Significant ( P <.05) changes or trends towards significance ( P <.10) were seen in all parameters except τi, although there was qualitative reduction in τi values post-treatment. In particular, there was reduction ( P <.035) in voxels with Ktrans values in the range 0.2–0.5 min-1 and a decrease ( P <.05) in voxels with ADC values in the range 0.99×10-3 to 1.35×10-3 mm2/s. ADC and νe were negatively correlated (r = -.60, P <.02). Parameters sensitive to water distribution and geometry (T1, νe,τsi and ADC) correlated with a multivariable linear regression model.
The analysis presented here is sensitive to longitudinal changes in breast tumor status; Ktrans and ADC are most sensitive to these changes. Relationships between parameters provide information on water distribution and geometry in the tumor environment.
DCE-MRI; ADC; Neoadjuvant chemotherapy; Fast-exchange regime
With advances in MRI technology, Dynamic-Contrast-Enhanced (DCE) MRI is approaching the capability to simultaneously deliver both high spatial- and temporal-resolutions for clinical applications. However, Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR) considerations, and their impacts regarding pharmacokinetic modeling of the time-course data continue to represent challenges in the design of DCE-MRI acquisitions. Given that many acquisition parameters can affect the nature of DCE-MRI data, minimizing tissue-specific data acquisition discrepancy (among sites and scanner models) is as important as synchronizing pharmacokinetic modeling approaches.
For cancer related DCE-MRI studies where rapid contrast reagent (CR) extravasation is expected, current DCE-MRI protocols often adopt a 3D fast low-angle shot (FLASH) sequence to achieve spatial-temporal resolution requirements. Based on breast and prostate DCE-MRI data acquired with different FLASH sequence parameters, this paper elucidates a number of SNR and CNR considerations for acquisition optimization and pharmacokinetic modeling implications therein. Simulations based on ROI data further indicate that the effects of intercompartmental water exchange often play an important role in DCE time-course data modeling, especially for protocols optimized for post-CR SNR.
Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) and computed tomography (CT) are emerging as valuable tools to quantitatively map the spatial distribution of vascular parameters such as perfusion, vascular permeability, blood volume, and mean transit time in tumors and normal organs. DCE MRI/CT have shown prognostic and predictive value for response of certain cancers to chemo and radiation therapy. DCE MRI/CT offer the promise of early assessment of tumor response to radiation therapy, opening a window for adaptively optimizing radiation therapy based upon functional alterations that occur earlier than morphological changes. DCE MRI/CT have also shown the potential of mapping dose-responses in normal organs and tissue for evaluation of individual sensitivity to radiation, providing additional opportunities to minimize risks of radiation injury. The evidence for potentially applying DCE MRI and CT for selection and delineation of radiation boost targets is growing. The clinical use of DCE MRI and CT as a biomarker or even a surrogate endpoint for radiation therapy assessment of tumor and normal organs must consider technical validation issues, including standardization, reproducibility, accuracy and robustness, as well as clinical validation of the sensitivity and specificity for each specific problem of interest. Although holding great promise, to date DCE MRI and CT have not been qualified as a surrogate endpoint for radiation therapy assessment or for treatment modification in any prospective phase III clinical trial for any tumor site.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) contains crucial information about tumour heterogeneity and the transport limitations that reduce drug efficacy. Mathematical modelling of drug delivery and cellular responsiveness based on underutilised DCE-MRI data has the unique potential to predict therapeutic responsiveness for individual patients.
To interpret DCE-MRI data, we created a modelling framework that operates over multiple time and length scales and incorporates intracellular metabolism, nutrient and drug diffusion, trans-vascular permeability, and angiogenesis. The computational methodology was used to analyse DCE-MR images collected from eight breast cancer patients at Baystate Medical Center in Springfield, MA.
Computer simulations showed that trans-vascular transport was correlated with tumour aggressiveness because increased vessel growth and permeability provided more nutrients for cell proliferation. Model simulations also indicate that vessel density minimally affects tissue growth and drug response, and nutrient availability promotes growth. Finally, the simulations indicate that increased transport heterogeneity is coupled with increased tumour growth and poor drug response.
Mathematical modelling based on DCE-MRI has the potential to aid treatment decisions and improve overall cancer care. This model is the critical first step in the creation of a comprehensive and predictive computational method.
dynamic contrast-enhanced magnetic resonance imaging; tumour growth model; therapeutic response; predictive multiscale model; tumour heterogeneity