Related Articles

Purposes

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.

Results

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.

Conclusion

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.

Purpose

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.

Results

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).

Conclusion

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.

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 (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.

OBJECTIVE

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.

RESULTS

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).

CONCLUSION

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.

Background:

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.

Methods:

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.

Results:

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.

Conclusion:

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.

OBJECTIVE

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.

RESULTS

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).

CONCLUSION

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.

Purpose

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.

Results

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).

Conclusion

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.

Purpose

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.

Results

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).

Conclusion

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.

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.

Purpose

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).

Results

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.

Conclusions

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.

Purpose

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.

Results

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.

Conclusions

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.

Purpose

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.

Results

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.

Conclusions

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.

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.

RESULTS

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.

CONCLUSIONS

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.

Introduction:

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.

Aim:

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.

Results:

The incidence of synchronous contralateral malignancy detected by preoperative MRI mammography done for evaluation of extent of disease was 4.1%.

Conclusion:

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.

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.

Background

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.

Methods

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.

Results

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.

Conclusion

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.

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.

Purpose

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.

Results

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.

Conclusion

DCE-MRI may provide useful prognostic information in terms of histologic differentiation and angiogenesis in rectal cancer.

Background

This study utilized the imaging data of primary liver cancer (PLC) treated with floxuridine (FUDR) and bevacizumab to test the hypothesis that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters correlate with tissue hypoxia markers and treatment outcome.

Methods

Seventeen patients with PLC were treated with hepatic artery infusional (HAI) FUDR for 14 days followed by systemic bevacizumab therapy. DCE-MRI images were obtained at baseline and after HAI FUDR and bevacizumab therapy. The parameters (Ktrans, AUC) pertaining to perfusion and vascular permeability of the tumor and adjacent liver parenchyma were measured with DCE-MRI. Tissue obtained at baseline was stained for hypoxia markers (anti-hypoxia inducible factor-1α, anti-carbonic anhydrase IX, and vascular endothelial growth factor). Changes in DCE-MRI parameters were correlated with tissue hypoxia and time to progression (TTP).

Results

The median TTP was 8.8 months. Significant decreases in AUC90 (P = 0.004), AUC180 (P = 0.004), and Ktrans (P = 0.05) were noted in tumors after bevacizumab but not in nontumor areas. TTP correlated inversely with changes in AUC90 and AUC180 after bevacizumab (P = 0.002 and P = 0.0001). Reductions in tumor perfusion (AUC90 and AUC180) were greater in tumors expressing anti-hypoxia inducible factor-1α (P = 0.02 and 0.03), vascular endothelial growth factor (P = 0.01 and P = 0.01), and anti-carbonic anhydrase IX (P = 0.009 and P = 0.009).

Conclusions

In patients with PLC, bevacizumab induces a reduction in tumor perfusion measured by DCE-MRI. These changes correlate with TTP and tissue markers of tumor hypoxia.

Summary

Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for the detection of breast cancer. Its specificity is equivalent to that of mammography. Nowadays, breast MRI is an absolutely essential breast imaging method. Technical innovations allow dynamic contrast-enhanced (DCE) MRI of both breasts with high image quality. Thereby, DCE breast MRI should always be performed with regard to current standards. New quantitative techniques such as diffusion-weighted MRI are promising. However, they still have potential pitfalls, in particular with regard to the diagnosis of non-mass lesions and small breast lesions. Ongoing technical innovations can possibly help to further optimize breast MRI.

Purpose

To investigate the effectiveness of a polydisulfide-based biodegradable macromolecular contrast agent, (Gd-DTPA)-cystamine copolymers (GDCC), in assessing the efficacy of indocyanine green enhanced photothermal cancer therapy using dynamic contrast enhanced MRI (DCE-MRI).

Materials and Methods

Breast cancer xenografts in mice were injected with indocyanine green and irradiated with laser. The efficacy was assessed using DCE-MRI with GDCC of 40 KDa (GDCC-40) at 4 hours and 7 days after the treatment. The uptake of GDCC-40 by the tumors was fit to a two-compartment model to obtain tumor vascular parameters, including fractional plasma volume (fPV), endothelium transfer coefficient (KPS), and permeability surface area product (PS).

Results

GDCC-40 resulted in similar tumor vascular parameters at three doses with larger standard deviations at lower doses. The values of fPV, KPS and PS of the treated tumors were smaller (p < 0.05) than those of untreated tumors at 4 hours after the treatment and recovered to pretreatment values (p > 0.05) at 7 days after the treatment.

Conclusion

DCE-MRI with GDCC-40 is effective for assessing tumor early response to dye-enhanced photothermal therapy and detecting tumor relapse after the treatment. GDCC-40 has a potential to non-invasively monitor anticancer therapies with DCE-MRI.

In this contribution we investigate the applicability of different methods from the field of independent component analysis (ICA) for the examination of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data from breast cancer research. DCE-MRI has evolved in recent years as a powerful complement to X-ray based mammography for breast cancer diagnosis and monitoring. In DCE-MRI the time related development of the signal intensity after the administration of a contrast agent can provide valuable information about tissue states and characteristics. To this end, techniques related to ICA, offer promising options for data integration and feature extraction at voxel level. In order to evaluate the applicability of ICA, topographic ICA and tree-dependent component analysis (TCA), these methods are applied to twelve clinical cases from breast cancer research with a histopathologically confirmed diagnosis. For ICA these experiments are complemented by a reliability analysis of the estimated components. The outcome of all algorithms is quantitatively evaluated by means of receiver operating characteristics (ROC) statistics whereas the results for specific data sets are discussed exemplarily in terms of reification, score-plots and score images.

Purpose

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.

Results

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.

Conclusion

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.

Purpose

To assess the temporal sampling requirements needed for quantitative analysis of dynamic contrast enhanced MRI (DCE-MRI) data with a reference region (RR) model in human breast cancer.

Materials and Methods

Simulations were used to study errors in pharmacokinetic parameters (Ktrans and ve) estimated by the RR model using six DCE-MRI acquisitions over a range of pharmacokinetic parameter values, arterial input functions, and temporal samplings. DCE-MRI data were acquired on 12 breast cancer patients and parameters were estimated using the native resolution data (16.4 second) and compared to downsampled 32.8 second and 65.6 second data.

Results

Simulations show that, in the majority of parameter combinations, the RR model results in an error less than 20% in the extracted parameters with temporal sampling as poor as 35.6 seconds. The experimental results show a high correlation between Ktrans and ve estimates from data acquired at 16.4 second temporal resolution compared to the downsampled 32.8 second data: the slope of the regression line was 1.025 (95% CI: 1.021, 1.029), Pearson's correlation r = 0.943 (CI: 0.940, 0.945) for Ktrans, and 1.023 (CI: 1.021. 1.025), r = 0.979 (CI: 0.978, 0.980) for ve. For the 64 second temporal resolution data the results were: 0.890 (CI: 0.894, 0.905), r = 0.8645, (CI: 0.858, 0.871) for Ktrans, and 1.041 (CI:1.039, 1.043), r = 0.970 (CI:0.968, 0.971) for ve.

Conclusion

RR analysis allows for a significant reduction in temporal sampling requirements and this lends itself to analyze DCE-MRI data acquired in practical situations.