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
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
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
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
Experimental targeted treatments for neoadjuvant chemotherapy for triple-negative breast cancer are currently underway, and a current challenge is predicting which patients will respond to these therapies. In this study, we use data from dynamic contrast-enhanced MRI (DCE-MRI) images to predict whether patients with triple negative breast cancer will respond to an experimental neoadjuvant chemotherapy regimen. Using pre-therapy image-based features that are both qualitative (e.g., morphological BI-RADS categories) and quantitative (e.g., lesion texture), we built a model that was able to predict whether patients will have residual invasive cancer with lymph nodes metastases following therapy (receiver operating characteristic area under the curve of 0.83, sensitivity=0.73, specificity=0.83). This model’s performance is at a level that is potentially clinically valuable for predicting which patients may or may not benefit from similar treatments in the future.
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
Dynamic contrast-enhanced-MRI (DCE-MRI) can provide information regarding tumor perfusion and permeability and has shown prognostic value in certain tumors types. The goal of the present study was to assess the prognostic value of pretreatment DCE-MRI in head and neck squamous cell carcinoma (HNSCC) patients with nodal disease undergoing chemoradiation therapy or surgery.
Methods and Materials
Seventy-four patients with histologically proven squamous cell carcinoma and neck nodal metastases were eligible for the study. Pretreatment DCE-MRI was performed on a 1.5T MRI. Clinical follow-up was a minimum of 12 months. DCE-MRI data were analyzed using Tofts model. DCE-MRI parameters were related to treatment outcome (progression free survival [PFS] and overall survival [OS]). Patients were grouped as no evidence of disease (NED), alive with disease (AWD), dead with disease (DOD) or dead of other causes (DOC). Prognostic significance was assessed using the log rank test for single variables and Cox proportional hazards regression for combinations of variables.
At last clinical follow-up, for stage III, all 12 pts were NED, for stage IV, 43 patients were NED, 4 were AWD, 11 were DOD, and 4 were DOC. Ktrans is volume transfer constant. In a stepwise Cox regression skewness of Ktrans was the strongest predictor for stage IV patients (PFS and OS: p<0.001).
Our study shows that skewness of Ktrans was the strongest predictor of PFS and OS in stage IV HNSCC patients with nodal disease. This study suggests an important role for pretreatment DCE-MRI parameter Ktrans as a predictor of outcome in these patients.
Dynamic Contrast Enhanced-MRI (DCE-MRI); head and neck squamous cell carcinoma (HNSCC); volume transfer constant (Ktrans)
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
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
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
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
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.
In this paper, we present a method of quantifying the heterogeneity of cervical cancer tumors for use in radiation treatment outcome prediction. Features based on the distribution of masked wavelet decomposition coefficients in the tumor region of interest (ROI) of temporal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies were used along with the imaged tumor volume to assess the response of the tumors to treatment. The wavelet decomposition combined with ROI masking was used to extract local intensity variations in the tumor. The developed method was tested on a data set consisting of 23 patients with advanced cervical cancer who underwent radiation therapy; 18 of these patients had local control of the tumor, and five had local recurrence. Each patient participated in two DCE-MRI studies: one prior to treatment and another early into treatment (2–4 weeks). An outcome of local control or local recurrence of the tumor was assigned to each patient based on a posttherapy follow-up at least 2 years after the end of treatment. Three different supervised classifiers were trained on combinational subsets of the full wavelet and volume feature set. The best-performing linear discriminant analysis (LDA) and support vector machine (SVM) classifiers each had mean prediction accuracies of 95.7%, with the LDA classifier being more sensitive (100% vs. 80%) and the SVM classifier being more specific (100% vs. 94.4%) in those cases. The K-nearest neighbor classifier performed the best out of all three classifiers, having multiple feature sets that were used to achieve 100% prediction accuracy. The use of distribution measures of the masked wavelet coefficients as features resulted in much better predictive performance than those of previous approaches based on tumor intensity values and their distributions or tumor volume alone.
Cervical cancer; treatment outcome prediction; dynamic contrast-enhanced MRI; wavelet
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.
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
To use a novel Morpho-Physiological Tumor Score (MPTS) generated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict response to treatment.
Materials and Methods
A protocol was designed to acquire DCE-MRI images of 20 locally advanced breast cancer (LABC) patients treated with neoadjuvant chemotherapy (NA ChT) and hyperthermia (HT). Imaging was done over 30 minutes following bolus injection of Gd-based contrast agent. Parametric maps were generated by fitting the signal intensity to a double exponential curve and were used to derive a morphological characterization of the lesions. Enhancement-variance dynamics parameters, washin and washout parameters (WiP, WoP) were extracted. The morphological characterization and the WiP and WoP were combined into a MPTS with the intent of achieving better prognostic efficacy. The MPTS was correlated with response to NA therapy as determined by pathologic residual tumor and MRI imaging.
The contrast agent in all tumors typically peaked in the first 1–4 minutes. The tumors WiP and WoP varied considerably. The MPTS was highly correlated with whether the patients had a pathologic response. This scoring system has a specificity of 78% and a sensitivity of 91% for predicting response to NA chemotherapy. The kappa was 0.69 with a 95% confidence interval of [0.38, 1.0] and a p-value of 0.002.
This pilot study shows that the MPTS derived using pre-treatment MRI images has the potential to predict response to NA ChT and HT in LABC patients. Further prospective studies are needed to confirm the validity of these results.
neoadjuvant therapy; locally advanced breast cancer; hyperthermia; MR prognostic factors; magnetic resonance imaging
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
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.
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.
Contralateral breast cancer can be synchronous and/or metachronous in patients with cancer of one breast. Detection of a synchronous breast cancer may affect patient management. Dynamic contrast-enhanced MRI of the breast (DCE-MRI) is a sensitive technique for detecting contralateral lesions occult on the other imaging modalities in women already diagnosed with cancer of one breast.
The aim was to assess the incidence of mammographically occult synchronous contralateral breast cancer in patients undergoing MRI mammography for the evaluation of a malignant breast lesion.
Materials and Methods:
A total of 294 patients with recently diagnosed breast cancer who underwent MRI of the breast were evaluated for lesions in the opposite breast.
The incidence of synchronous contralateral malignancy detected by preoperative MRI mammography done for evaluation of extent of disease was 4.1%.
Preoperative breast MRI may detect clinically and mammographically occult synchronous contralateral cancer, and can help the patient avoid an additional second surgery or a second course of chemotherapy later; also, as theoretically these lesions are smaller, there may be a survival benefit as well.
Bilateral breast cancer; MR mammography; synchronous breast cancer
Permeability parameters from dynamic contrast-enhanced MRI (DCE-MRI) and apparent diffusion coefficient (ADC) value on diffusion-weighted imaging (DWI) can be quantitative physiologic metrics for gliomas. The transfer constant (Ktrans) has shown efficacy in grading gliomas. Volume fraction of extravascular extracellular space (ve) has been underutilized to grade gliomas. The purpose of this study was to evaluate ve in its ability to grade gliomas and to assess the correlation with other permeability parameters and ADC values.
Materials and Methods
A total of 33 patients diagnosed with pathologically-confirmed gliomas were examined by 3 T MRI including DCE-MRI and ADC map. A region of interest analyses for permeability parameters from DCE-MRI and ADC were performed on the enhancing solid portion of the tumors. Permeability parameters form DCE-MRI and ADC between low- and high-grade gliomas; the diagnostic performances of presumptive metrics and correlation among those metrics were statistically analyzed.
High-grade gliomas showed higher Ktrans (0.050 vs. 0.010 in median value, p = 0.002) and higher ve (0.170 vs. 0.015 in median value, p = 0.001) than low-grade gliomas. Receiver operating characteristic curve analysis showed significance in both Ktrans and ve for glioma grading. However, there was no significant difference in diagnostic performance between Ktrans and ve. ADC value did not correlate with any of the permeability parameters from DCE-MRI.
Extravascular extracellular space (ve) appears to be comparable with transfer constant (Ktrans) in differentiating high-grade gliomas from low-grade gliomas. ADC value does not show correlation with any permeability parameters from DCE-MRI.
Dynamic contrast-enhanced MRI; Apparent diffusion coefficient; Glioma
The expressions of different vascular endothelial growth factor (VEGF) isoforms are associated with the degree of tumor invasiveness and the patient's prognosis in human cancers. We hypothesized that different VEGF isoforms can exert different effects on the functional and structural characteristics of tumor angiogenesis. We used dynamic contrast-enhanced MRI (DCE-MRI) and steady-state contrast-enhanced MRI (SSCE-MRI) to evaluate in vivo vascular functions (e.g., perfusion and permeability) and structural characteristics (e.g., vascular size and vessel density) of the tumor angiogenesis induced by different VEGF isoforms (VEGF121, VEGF165, and VEGF189) in a murine xenograft model of human lung cancer. Tumors overexpressing VEGF189 were larger than those overexpressing the other two VEGF isoforms. The Ktrans map obtained from DCE-MRI revealed that the perfusion and permeability functions of tumor microvessels was highest in both the rim and core regions of VEGF189-overexpressing tumors (p<0.001 for both tumor rim and core). The relative vessel density and relative vessel size indexes derived from SSCE-MRI revealed that VEGF189-overexpressing tumors had the smallest (p<0.05) and the most-dense (p<0.01) microvessels, which penetrated deeply from the tumor rim into the core, followed by the VEGF165-overepxressing tumor, whose microvessels were located mainly in the tumor rim. The lowest-density microvessels were found in the VEGF121-overexpressing tumor; these microvessels had a relatively large lumen and were found mainly in the tumor rim. We conclude that among the three VEGF isoforms evaluated, VEGF189 induces the most densely sprouting and smallest tumor microvessels with the highest in vivo perfusion and permeability functions. These characteristics of tumor microvessels may contribute to the reported adverse effects of VEGF189 overexpression on tumor progression, metastasis, and patient survival in several human cancers, including non-small cell lung cancer, and suggest that applying aggressive therapy may be necessary in human cancers in which VEGF189 is overexpressed.
Optic pathway gliomas (OPGs) are common pediatric brain tumors that pose significant clinical challenges with regard to predicting which tumors are likely to become symptomatic and require treatment. These tumors can arise sporadically or in the context of the inherited cancer predisposition syndrome, Neurofibromatosis type 1 (NF1). Few studies have suggested biological or imaging markers which predict the clinical course of this disease.
In this cross-sectional study, we hypothesize that the clinical behavior of OPGs in children can be differentiated by diffusion-weighted (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).
27 patients with OPG were studied using DWI and DCE MRI protocols. Diffusivity and permeability were calculated and correlated to OPG clinical behavior.
Mean diffusivity values of 1.39 μm2/ms and mean permeability values of 2.10 ml min−1 per 100 cc of tissue were measured. “Clinically-aggressive” OPGs had significantly higher mean permeability values (P=.05) than “clinically stable” tumors. In addition, there was a strong correlation between clinical aggressiveness and the absence of NF1 (P < 0.01).
These results suggest that DCE might be a useful biomarker for “clinically aggressive” OPG, which should be confirmed in larger prospective longitudinal studies.
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
MRI techniques have been developed that can noninvasively probe the apparent diffusion coefficient (ADC) of water via diffusion weighted MRI (DW-MRI). These methods have found much application in cancer where it is often found that the ADC within tumors is inversely correlated with tumor cell density, so that an increase in ADC in response to therapy can be interpreted as an imaging biomarker of positive treatment response. Dynamic contrast enhanced MRI (DCE-MRI) methods have also been developed and can noninvasively report on the extravascular extracellular volume fraction of tissues (denoted by ve). By conventional reasoning the ADC should therefore also be directly proportional to ve. Here we report measurements of both ADC and ve obtained from breast cancer patients at both 1.5T and 3.0T. The 1.5T data were acquired as part of normal standard-of-care, while the 3.0T data were obtained from a dedicated research protocol. We found no statistically significant correlation between ADC and ve for the 1.5T or 3.0T patient sets on either a voxel-by-voxel or ROI basis. These data, combined with similar results from other disease sites in the literature, may indicate that the conventional interpretation of either ADC, ve, or their relationship are not sufficient to explain experimental findings.