Evaluation of neoadjuvant chemotherapeutic response of breast cancer using dynamic MRI with high temporal resolution

Feasibility Study on Using Dynamic Contrast Enhanced MRI to Assess the Effect of Tyrosine Kinase Inhibitor Therapy within the STAR Trial of Metastatic Renal Cell Cancer

Objective: To identify dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters predictive of early disease progression in patients with metastatic renal cell cancer (mRCC) treated with anti-angiogenic tyrosine kinase inhibitors (TKI). Methods: The study was linked to a phase II/III randomised control trial. Patients underwent DCE-MRI before, at 4- and 10-weeks after initiation of TKI. DCE-MRI parameters at each time-point were derived from a single-compartment tracer kinetic model, following semi-automated tumour segmentation by two independent readers. Primary endpoint was correlation of DCE-MRI parameters with disease progression at 6-months. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values were calculated for parameters associated with disease progression at 6 months. Inter-observer agreement was assessed using the intraclass correlation coefficient (ICC). Results: 23 tumours in 14 patients were measurable. Three patients had disease progression at 6 months. The percentage (%) change in perfused tumour volume between baseline and 4-week DCE-MRI (p = 0.016), mean transfer constant K^trans change (p = 0.038), and % change in extracellular volume (p = 0.009) between 4- and 10-week MRI, correlated with early disease progression (AUC 0.879 for each parameter). Inter-observer agreement was excellent for perfused tumour volume, K^trans and extracellular volume (ICC: 0.928, 0.949, 0.910 respectively). Conclusions: Early measurement of DCE-MRI biomarkers of tumour perfusion at 4- and 10-weeks predicts disease progression at 6-months following TKI therapy in mRCC.

Breast tumour volume and blood flow measured by MRI after one cycle of epirubicin and cyclophosphamide-based neoadjuvant chemotherapy as predictors of pathological response

OBJECTIVES

Better markers of early response to neoadjuvant chemotherapy (NACT) in patients with breast cancer are required to enable the timely identification of non-responders and reduce unnecessary treatment side-effects. Early functional imaging may better predict response to treatment than conventional measures of tumour size. The purpose of this study was to test the hypothesis that the change in tumour blood flow after one cycle of NACT would predict pathological response.

METHODS

In this prospective cohort study, dynamic contrast-enhanced MRI was performed in 35 females with breast cancer before and after one cycle of epirubicin and cyclophosphamide-based NACT (EC90). Estimates of tumour blood flow and tumour volume were compared with pathological response obtained at surgery following completion of NACT.

RESULTS

Tumour blood flow at baseline (mean ± SD; 0.32 ± 0.17 ml/min/ml) reduced slightly after one cycle of NACT (0.28 ± 0.18 ml/min/ml). Following treatment 15 patients were identified as pathological responders and 20 as non-responders. There were no relationships found between tumour blood flow and pathological response. Conversely, tumour volume was found to be a good predictor of pathological response (smaller tumours did better) at both baseline (area under the receiver operating characteristic curve 0.80) and after one cycle of NACT (area under the receiver operating characteristic curve 0.81).

CONCLUSION & ADVANCES IN KNOWLEDGE

The change in breast tumour blood flow following one cycle of EC90 did not predict pathological response. Tumour volume may be a better early marker of response with such agents.

Five-dimensional quantitative low-dose Multitasking dynamic contrast- enhanced MRI: Preliminary study on breast cancer

PURPOSE

To develop a low-dose Multitasking DCE technique (LD-MT-DCE) for breast imaging, enabling dynamic T₁ mapping-based quantitative characterization of tumor blood flow and vascular properties with whole-breast coverage, a spatial resolution of 0.9 × 0.9 × 1.1 mm³ , and a temporal resolution of 1.4 seconds using a 20% gadolinium dose (0.02 mmol/kg).

METHODS

Magnetic resonance Multitasking was used to reconstruct 5D images with three spatial dimensions, one T₁ recovery dimension for dynamic T₁ quantification, and one DCE dimension for contrast kinetics. Kinetic parameters F p , v p , K trans , and v e were estimated from dynamic T₁ maps using the two-compartment exchange model. The LD-MT-DCE repeatability and agreement against standard-dose MT-DCE were evaluated in 20 healthy subjects. In 7 patients with triple-negative breast cancer, LD-MT-DCE image quality and diagnostic results were compared with that of standard-dose clinical DCE in the same imaging session. One-way unbalanced analysis of variance with Tukey test was performed to evaluate the statistical significance of the kinetic parameters between control and patient groups.

RESULTS

The LD-MT-DCE technique was repeatable, agreed with standard-dose MT-DCE, and showed excellent image quality. The diagnosis using LD-MT-DCE matched well with clinical results. The values of F p , v p , and K trans were significantly different between malignant tumors and normal breast tissue (P < .001, < .001, and < .001, respectively), and between malignant and benign tumors (P = .020, .003, and < .001, respectively).

CONCLUSION

The LD-MT-DCE technique was repeatable and showed excellent image quality and equivalent diagnosis compared with standard-dose clinical DCE. The estimated kinetic parameters were capable of differentiating between normal breast tissue and benign and malignant tumors.

Quantitative ultrasound radiomics for therapy response monitoring in patients with locally advanced breast cancer: Multi-institutional study results

BACKGROUND

Neoadjuvant chemotherapy (NAC) is the standard of care for patients with locally advanced breast cancer (LABC). The study was conducted to investigate the utility of quantitative ultrasound (QUS) carried out during NAC to predict the final tumour response in a multi-institutional setting.

METHODS

Fifty-nine patients with LABC were enrolled from three institutions in North America (Sunnybrook Health Sciences Centre (Toronto, Canada), MD Anderson Cancer Centre (Texas, USA), and Princess Margaret Cancer Centre (Toronto, Canada)). QUS data were collected before starting NAC and subsequently at weeks 1 and 4 during chemotherapy. Spectral tumour parametric maps were generated, and textural features determined using grey-level co-occurrence matrices. Patients were divided into two groups based on their pathological outcomes following surgery: responders and non-responders. Machine learning algorithms using Fisher's linear discriminant (FLD), K-nearest neighbour (K-NN), and support vector machine (SVM-RBF) were used to generate response classification models.

RESULTS

Thirty-six patients were classified as responders and twenty-three as non-responders. Among all the models, SVM-RBF had the highest accuracy of 81% at both weeks 1 and week 4 with area under curve (AUC) values of 0.87 each. The inclusion of week 1 and 4 features led to an improvement of the classifier models, with the accuracy and AUC from baseline features only being 76% and 0.68, respectively.

CONCLUSION

QUS data obtained during NAC reflect the ongoing treatment-related changes during chemotherapy and can lead to better classifier performances in predicting the ultimate pathologic response to treatment compared to baseline features alone.

The kinetic analysis of breast cancer: An investigation of the optimal temporal resolution for dynamic contrast-enhanced MR imaging

INTRODUCTION

There is wide agreement that morphologic features and enhancement kinetics should be evaluated for MRI of the breast, although there has been no clear consensus concerning optimal temporal resolutions. The objective of this study was to investigate the optimal temporal resolution for the kinetic analysis of breast cancers.

METHODS

Thirty-four patients with 34 enhancing lesions of breast cancer who underwent dynamic contrast-enhanced MRI (DCE-MRI) on a 3.0-T scanner were included in this retrospective study. DCE-MRI was performed with an original temporal resolution of 10-s, and the values of pharmacokinetic parameters (Ktrans, Ve, Kep, and area under the curve (AUC)) were compared with selected data of 30-s and 60-s time intervals.

RESULTS

Among the 34 lesions, 10 showed a wash out pattern, 16 showed a plateau pattern, and 8 showed a persistent enhancement pattern. The Ktrans value in the wash-out pattern was significantly higher than that of other time-intensity curve patterns (p < 0.01). The Kep and AUC also showed significant differences between the wash-out pattern and other types (p < 0.01). On comparing the perfusion parameters among different temporal resolutions, simulations showed that only the AUC differed significantly between the data acquired at a 10-s temporal resolution and that acquired at a 60-s time interval (p < 0.01). Although the comparison of the AUC between the 30-s and 60-s data also showed significant differences (p = 0.01), there was no significant difference between the 10-s and 30-s data (p = 0.17).

CONCLUSIONS

DCE-MRI with a temporal resolution of 30-s preserves the kinetic information. Further prospective studies will be needed to investigate the trade-off between temporal and spatial resolution in DCE-MRI.

Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review

PURPOSE

MRI-based tumor response prediction to neoadjuvant systemic therapy (NST) in breast cancer patients is increasingly being studied using radiomics with outcomes that appear to be promising. The aim of this study is to systematically review the current literature and reflect on its quality.

METHODS

PubMed and EMBASE databases were systematically searched for studies investigating MRI-based radiomics for tumor response prediction. Abstracts were screened by two reviewers independently. The quality of the radiomics workflow of eligible studies was assessed using the Radiomics Quality Score (RQS). An overview of the methodologies used in steps of the radiomics workflow and current results are presented.

RESULTS

Sixteen studies were included with cohort sizes ranging from 35 to 414 patients. The RQS scores varied from 0 % to 41.2 %. Methodologies in the radiomics workflow varied greatly, especially region of interest segmentation, features selection, and model development with heterogeneous outcomes as a result. Seven studies applied univariate analysis and nine studies applied multivariate analysis. Most studies performed their analysis on the pretreatment dynamic contrast-enhanced T1-weighted sequence. Entropy was the best performing individual feature with AUC values ranging from 0.83 to 0.85. The best performing multivariate prediction model, based on logistic regression analysis, scored a validation AUC of 0.94.

CONCLUSION

This systematic review revealed large methodological heterogeneity for each step of the MRI-based radiomics workflow, consequently, the (overall promising) results are difficult to compare. Consensus for standardization of MRI-based radiomics workflow for tumor response prediction to NST in breast cancer patients is needed to further improve research.

Meta-Analysis of Quantitative Dynamic Contrast-Enhanced MRI for the Assessment of Neoadjuvant Chemotherapy in Breast Cancer

The purpose of this meta-analysis was to determine the value of quantitative dynamic contrast-enhanced (DCE) MRI (DCE-MRI) in evaluating the response of breast cancer to neoadjuvant chemotherapy (NAC). PubMed, Embase, and Cochrane Library databases (from building to July 31, 2018) were searched to collect articles about the therapeutic evaluation of NAC using the quantitative DCE-MRI in patients with breast cancer. The sensitivities and specificities of quantitative DCE-MRI in the evaluation of NAC for breast cancer were extracted from the articles. Meta-DiSc1.4 was applied to evaluate the efficacy of the sensitivity and specificity; forest figure and summary receiver operating characteristics (SROC) were created. A total of 356 articles were enrolled in this study, including 739 cases in total, in which 218 cases were effective and the other 521 cases were ineffective to NAC, considering the pathological results as the gold standard. The sensitivity and specificity in the included 14 articles of quantitative DCE-MRI ( Ktrans, kep, and ve) in comprehensively evaluating NAC for breast cancer were 84 per cent (95% confidence interval (CI): 78–88%) and 83 per cent (95% CI: 79–86%), respectively. The area under SROC was 0.899 (95% CI: 0.867–0.943). The sensitivity and specificity in the three articles of Ktrans evaluating NAC for breast cancer were 84.1 per cent (95% CI: 71.0–92.1%) and 81.3 per cent (95% CI: 70.5%-88.5%), respectively. The area under SROC was 0.899 (95% CI: 0.834–0.962). Our study confirmed that the quantitative DCE-MRI is able to monitor NAC treatment for breast cancer because of its high sensitivity and specificity. However, there is a high degree of heterogeneity in published studies, highlighting the lack of standardization in the field.

Dynamic contrast-enhanced MRI of malignant pleural mesothelioma: a comparative study of pharmacokinetic models and correlation with mRECIST criteria

Background

Malignant pleural mesothelioma (MPM) is a rare and aggressive thoracic malignancy that is difficult to cure. Dynamic contrast-enhanced (DCE) MRI is a functional imaging technique used to analyze tumor microvascular properties and to monitor therapy response. Purpose of this study was to compare two tracer kinetic models, the extended Tofts (ET) and the adiabatic approximation tissue homogeneity model (AATH) for analysis of DCE-MRI and examine the value of the DCE parameters to predict response to chemotherapy in patients with MPM.

Method

This prospective, longitudinal, single tertiary radiology center study was conducted between October 2013 and July 2015. Patient underwent DCE-MRI studies at three time points: prior to therapy, during and after cisplatin-based chemotherapy. The images were analyzed using ET and AATH models. In short-term follow-up, the patients were classified as having disease control or progressive disease according to modified response evaluation criteria in solid tumors (mRECIST) criteria.

Receiver operating characteristic curve analysis was used to examine specificity and sensitivity of DCE parameters for predicting response to therapy. Comparison tests were used to analyze whether derived parameters are interchangeable between the two models.

Results

Nineteen patients form the study population. The results indicate that the derived parameters are not interchangeable between the models.

Significant correlation with response to therapy was found for AATH-calculated median pre-treatment efflux rate (k_ep) showing sensitivity of 83% and specificity of 100% (AUC 0.9). ET-calculated maximal pre-treatment k_ep showed 100% sensitivity and specificity for predicting treatment response during the early phase of the therapy and reached a favorable trend to significant prognostic value post-therapy.

Conclusion

Both models show potential in predicting response to therapy in MPM. High pre-treatment k_ep values suggest MPM disease control post-chemotherapy.

Electronic supplementary material

The online version of this article (10.1186/s40644-019-0189-5) contains supplementary material, which is available to authorized users.

DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma: a preliminary report

Purpose

Neoadjuvant chemotherapy is recommended in patients with locally advanced breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables evaluation of the tumour neovasculature that occurs prior to any volume change, which helps identify early treatment failures and allows prompt implementation of second-line therapy.

Material and methods

We conducted a prospective study in 14 patients with histopathologically proven breast cancer. DCE-MRI data were acquired using multisection, T1-weighted, 3D vibe sequences with fat suppression before, during, and after IV bolus injection (0.1 mmol/kg body weight, Gadoversetamide, Optimark). Post-processing of dynamic contrast perfusion data was done with the vendor’s Tissue 4D software to generate various dynamic contrast parameters, i.e. Ktrans, Kep, Ve, initial area under the time signal curve (IAUC), apparent diffusion coefficient (ADC), and enhancement curve. Patients underwent MRI examinations at baseline, and then after two cycles, and finally at completion of chemotherapy.

Results

Based on Sataloff criteria for pathological responses, four patients out of 14 were responders, and 10 were non-responders. At the 2nd MRI examination, IAUC was significantly smaller in responders than in non-responders (p = 0.023). When the results of the first and second MRI examinations were compared, Kep decreased from baseline to the second MRI (p = 0.03) in non-responders and in responders (p = 0.04). This change was statistically significant in both groups. The ADC values increased significantly in responders from baseline to the third MRI (p = 0.012).

Conclusions

In our study, IAUC and ADC were the only parameters that reliably differentiated responders from non-responders after two and three cycles of chemotherapy.

Estimating breast tumor blood flow during neoadjuvant chemotherapy using interleaved high temporal and high spatial resolution MRI

PURPOSE

To evaluate an interleaved MRI sampling strategy that acquires both high temporal resolution (HTR) dynamic contrast-enhanced (DCE) data for quantifying breast tumor blood flow (TBF) and high spatial resolution (HSR) DCE data for clinical reporting, following a single standard injection of contrast agent.

METHODS

A simulation study was used to evaluate the performance of the interleaved technique under different conditions. In a prospective clinical study, 18 patients with primary breast cancer, who were due to undergo neoadjuvant chemotherapy (NACT), were examined using interleaved HTR and HSR DCE-MRI at 1.5 Tesla. Tumor regions of interest were analyzed with a two-compartment tracer kinetic model. Paired parameters (n = 10) from the data acquired before and post-cycle 2 of NACT were compared using the nonparametric Wilcoxon signed-rank test.

RESULTS

Simulations demonstrated that TBF was reliably estimated using the proposed strategy. The region of interest analysis revealed significant changes in TBF (0.81-0.43 mL/min/mL; P = 0.002) following two cycles of NACT. The HSR data were reported in the normal way and enabled the assessment of tumor volume, which decreased by 53% following NACT (P = 0.065).

CONCLUSIONS

TBF can be measured reliably using the proposed strategy without compromising a standard clinical protocol. Furthermore, in our feasibility study, TBF decreased significantly following NACT, whereas capillary permeability surface-area product did not. Magn Reson Med 79:317-326, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Role of MR-DWI and MR-PWI in the radiotherapy of implanted pulmonary VX-2 carcinoma in rabbits

OBJECTIVE

To detect the activity of tumor cells and tumor blood flow before and after the radiotherapy of implanted pulmonary VX-2 carcinoma in rabbit models by using magnetic resonance diffusion-weighted imaging (MR-DWI) and magnetic resonance perfusion weighted imaging (MR-PWI), and to evaluate the effectiveness and safety of the radiotherapy based on the changes in the MR-DWI and MR-PWI parameters at different treatment stages.

METHODS

A total of 56 rabbit models with implanted pulmonary VX-2 carcinoma were established, and then equally divided into treatment group and control group. MR-DWI and MR-PWI were separately performed using a Philips Acheiva 1.5T MRI machine (Philips, Netherland). MRI image processing was performed using special perfusion software and the WORKSPACE advanced workstation for MRI. MR-DWI was applied for the observation of tumor signals and the measurement of apparent diffusion coefficient (ADC) values; whereas MR-PWI was used for the measurement of wash in rate (WIR), wash out rate (WOR), and maximum enhancement rate (MER). The radiation treatment was performed using Siemens PRIMUS linear accelerator. In the treatment group, the radiotherapy was performed 21 days later on a once weekly dosage of 1,000 cGy to yield a total dosage of 5,000 cGy.

RESULTS

THE ADC PARAMETERS IN THE REGION OF INTEREST ON DWI WERE AS FOLLOWS: on the treatment day for the implanted pulmonary VX-2 carcinoma, the t values at the center and the edge of the lesions were 1.352 and 1.461 in the treatment group and control group (P>0.05). During weeks 0-1 after treatment, the t values at the center and the edge of the lesions were 1.336 and 1.137 (P>0.05). During weeks 1-2, the t values were 1.731 and 1.736 (P<0.05). During weeks 2-3, the t values were 1.742 and 1.749 (P<0.05). During weeks 3-4, the t values were 2.050 and 2.127 (P<0.05). During weeks 4-5, the t values were 2.764 and 2.985 (P<0.05). The ADC values in the treatment group were significantly higher than in the control group. After the radiotherapy (5,000 cGy), the tumors remarkably shrank, along with low signal on DWI, decreased signal on ADC map, and remarkably increased ADC values. As shown on PWI, on the treatment day for the implanted pulmonary VX-2 carcinoma, the t values of the WIR, WOR, and MER at the center of the lesions were 1.05, 1.31, and 1.33 in the treatment group and control group (P>0.05); in addition, the t values of the WIR, WOR, and MER at the edge of the lesions were 1.35, 1.07, and 1.51 (P>0.05). During weeks 0-1 after treatment, the t values of the WIR, WOR, and MER at the center of the lesions were 1.821, 1.856, and 1.931 (P<0.05); in addition, the t values of the WIR, WOR, and MER at the edge of the lesions were 1.799, 2.016, and 2.137 (P<0.05). During weeks 1-1 after treatment, the t values of the WIR, WOR, and MER at the center of the lesions were 2.574, 2.156, and 2.059 (P<0.05) and the t values of the WIR, WOR, and MER at the edge of the lesions were 1.869, 2.058, and 2.057 (P<0.05). During weeks 2-3 after treatment, the t values of the WIR, WOR, and MER at the center of the lesions were 2.461, 2.098, and 2.739 (P<0.05) and the t values of the WIR, WOR, and MER at the edge of the lesions were 2.951, 2.625, and 2.154 (P<0.05). During weeks 3-4 after treatment, the t values of the WIR, WOR, and MER at the center of the lesions were 2.584, 2.107, and 2.869 (P<0.05) and the t values of the WIR, WOR, and MER at the edge of the lesions were 2.057, 2.637, and 2.951 (P<0.05). During weeks 4-5 after treatment, the t values of the WIR, WOR, and MER at the center of the lesions were 2.894, 2.827, and 3.285 (P<0.05) and the t values of the WIR, WOR, and MER at the edge of the lesions were 3.45, 3.246, and 3.614 (P<0.05). After the radiotherapy (500 cGy), the tumors shrank on the T1WI, WIR, WOR, and MER; meanwhile, the PWI parameter gradually decreased and reached its minimum value.

CONCLUSIONS

MR-DWI and MR-PWI can accurately and directly reflect the inactivation of tumor cells and the tumor hemodynamics in rabbit models with implanted pulmonary VX-2 carcinoma, and thus provide theoretical evidences for judging the clinical effectiveness of radiotherapy for the squamous cell carcinoma of the lung.

Prediction of pathological complete response of breast cancer patients undergoing neoadjuvant chemotherapy: usefulness of breast MRI computer-aided detection

OBJECTIVE

To evaluate the usefulness of MR computer-aided detection (CAD) in patients undergoing neoadjuvant chemotherapy for prediction of the pathological complete response of tumours.

METHODS

148 patients with breast cancer (mean age, 47.3 years; range, 29-72 years) who underwent neoadjuvant chemotherapy were included in our study. They underwent MRI before and after neoadjuvant chemotherapy, and we reviewed the pathological result as the gold standard. The computer-generated kinetic features for each lesion were recorded, and the features analysed included "threshold enhancement" at 50% and 100% minimum thresholds; degree of initial peak enhancement; and enhancement profiles comprising lesion percentages of washout, plateau and persistent enhancement. The final pathological size and character of tumours were correlated with post-chemotherapy mammography, ultrasonography and MR CAD findings. Kruskal-Wallis test and intraclass correlation coefficient were used to analyse the findings.

RESULTS

We divided the 148 patients into complete pathological response and non-complete pathological response groups. A complete pathological response was defined as no histopathological evidence of any residual invasive cancer cells in the breast or axillary lymph nodes. 39 patients showed complete pathological response, and 109 patients showed non-complete pathological response. Between enhancement profiles of MR CAD, plateau proportion of tumours was significantly correlated with the pathological response of tumours (mean proportion of plateau on complete pathological response group was 27%, p = 0.007).

CONCLUSION

When plateau proportion of tumours is high, we can predict non-complete pathological response of neoadjuvant chemotherapy.

ADVANCES IN KNOWLEDGE

MR CAD can be a useful tool for the assessment of response to neoadjuvant chemotherapy and prediction of pathological results.

Transport properties of pancreatic cancer describe gemcitabine delivery and response

BACKGROUND

The therapeutic resistance of pancreatic ductal adenocarcinoma (PDAC) is partly ascribed to ineffective delivery of chemotherapy to cancer cells. We hypothesized that physical properties at vascular, extracellular, and cellular scales influence delivery of and response to gemcitabine-based therapy.

METHODS

We developed a method to measure mass transport properties during routine contrast-enhanced CT scans of individual human PDAC tumors. Additionally, we evaluated gemcitabine infusion during PDAC resection in 12 patients, measuring gemcitabine incorporation into tumor DNA and correlating its uptake with human equilibrative nucleoside transporter (hENT1) levels, stromal reaction, and CT-derived mass transport properties. We also studied associations between CT-derived transport properties and clinical outcomes in patients who received preoperative gemcitabine-based chemoradiotherapy for resectable PDAC.

RESULTS

Transport modeling of 176 CT scans illustrated striking differences in transport properties between normal pancreas and tumor, with a wide array of enhancement profiles. Reflecting the interpatient differences in contrast enhancement, resected tumors exhibited dramatic differences in gemcitabine DNA incorporation, despite similar intravascular pharmacokinetics. Gemcitabine incorporation into tumor DNA was inversely related to CT-derived transport parameters and PDAC stromal score, after accounting for hENT1 levels. Moreover, stromal score directly correlated with CT-derived parameters. Among 110 patients who received preoperative gemcitabine-based chemoradiotherapy, CT-derived parameters correlated with pathological response and survival.

CONCLUSION

Gemcitabine incorporation into tumor DNA is highly variable and correlates with multiscale transport properties that can be derived from routine CT scans. Furthermore, pretherapy CT-derived properties correlate with clinically relevant endpoints.

TRIAL REGISTRATION

Clinicaltrials.gov NCT01276613.

FUNDING

Lustgarten Foundation (989161), Department of Defense (W81XWH-09-1-0212), NIH (U54CA151668, KCA088084).

Analyzing Spatial Heterogeneity in DCE- and DW-MRI Parametric Maps to Optimize Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer

The purpose of this study is to investigate the ability of multivariate analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) parametric maps, obtained early in the course of therapy, to predict which patients will achieve pathologic complete response (pCR) at the time of surgery. Thirty-three patients underwent DCE-MRI (to estimate K (trans), v e, k ep, and v p) and DW-MRI [to estimate the apparent diffusion coefficient (ADC)] at baseline (t 1) and after the first cycle of neoadjuvant chemotherapy (t 2). Four analyses were performed and evaluated using receiver-operating characteristic (ROC) analysis to test their ability to predict pCR. First, a region of interest (ROI) level analysis input the mean K (trans), v e, k ep, v p, and ADC into the logistic model. Second, a voxel-based analysis was performed in which a longitudinal registration algorithm aligned serial parameters to a common space for each patient. The voxels with an increase in k ep, K (trans), and v p or a decrease in ADC or v e were then detected and input into the regression model. In the third analysis, both the ROI and voxel level data were included in the regression model. In the fourth analysis, the ROI and voxel level data were combined with selected clinical data in the regression model. The overfitting-corrected area under the ROC curve (AUC) with 95% confidence intervals (CIs) was then calculated to evaluate the performance of the four analyses. The combination of k ep, ADC ROI, and voxel level data achieved the best AUC (95% CI) of 0.87 (0.77-0.98).

Early assessment of breast cancer response to neoadjuvant chemotherapy by semi-quantitative analysis of high-temporal resolution DCE-MRI: preliminary results

PURPOSE

To evaluate whether semi-quantitative analysis of high temporal resolution dynamic contrast-enhanced MRI (DCE-MRI) acquired early in treatment can predict the response of locally advanced breast cancer (LABC) to neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

As part of an IRB-approved prospective study, 21 patients with LABC provided informed consent and underwent high temporal resolution 3T DCE-MRI before and after 1cycle of NAC. Using measurements performed by two radiologists, the following parameters were extracted for lesions at both examinations: lesion size (short and long axes, in both early and late phases of enhancement), radiologist's subjective assessment of lesion enhancement, and percentages of voxels within the lesion demonstrating progressive, plateau, or washout kinetics. The latter data were calculated using two filters, one selecting for voxels enhancing ≥50% over baseline and one for voxels enhancing ≥100% over baseline. Pretreatment imaging parameters and parameter changes following cycle 1 of NAC were evaluated for their ability to discriminate patients with an eventual pathological complete response (pCR).

RESULTS

All 21 patients completed NAC followed by surgery, with 9 patients achieving a pCR. No pretreatment imaging parameters were predictive of pCR. However, change after cycle 1 of NAC in percentage of voxels demonstrating washout kinetics with a 100% enhancement filter discriminated patients with an eventual pCR with an area under the receiver operating characteristic curve (AUC) of 0.77. Changes in other parameters, including lesion size, did not predict pCR.

CONCLUSION

Semi-quantitative analysis of high temporal resolution DCE-MRI in patients with LABC can discriminate patients with an eventual pCR after one cycle of NAC.

Preliminary study of CT in combination with MRI perfusion imaging to assess hemodynamic changes during angiogenesis in a rabbit model of lung cancer

Background

This study used CT (computed tomography) and magnetic resonance imaging (MRI) to identify correlations between perfusion parameters for squamous cell lung carcinoma and tumor angiogenesis in a rabbit model of VX2 lung cancer.

Methods

VX2 tumors were implanted in the lungs of 35 New Zealand White rabbits. CT and MRI perfusion scanning were performed on days 14, 17, 21, 25, and 28 after tumor implantation. CT perfusion parameters were perfusion, peak enhanced increment, transit time peak, and blood volume, and MRI perfusion parameters were wash in rate, wash out rate, maximum enhancement rate, and transit time peak. CT and MRI perfusion parameters were obtained at the tumor rim, in the tumor tissue, and in the muscle tissue surrounding the tumor.

Results

On CT perfusion imaging, t values for perfusion, peak enhanced increment, and blood volume (tumor rim versus muscle) were 16.31, 11.79, and 5.21, respectively (P < 0.01); t values for perfusion, peak enhanced increment, and blood volume (tumor versus muscle) were 9.87, 4.09, and 5.35, respectively (P < 0.01); and t values for transit time peak were 1.52 (tumor rim versus muscle) and 1.29 (tumor versus muscle), respectively (P > 0.05). On MRI perfusion imaging, t values for wash in rate, wash out rate, and maximum enhancement rate (tumor rim versus muscle) were 18.14, 8.79, and 6.02, respectively (P < 0.01); t values for muscle wash in rate, wash out rate, and maximum enhancement rate (tumor versus muscle) were 9.45, 8.23, and 4.21, respectively (P < 0.01); and t values for transit time peak were 1.21 (tumor rim versus muscle) and 1.05 (tumor versus muscle), respectively (P > 0.05).

Conclusion

A combination of CT and MRI perfusion imaging demonstrated hemodynamic changes in a rabbit model of VX2 lung cancer, and provides a theoretical foundation for treatment of human squamous cell lung carcinoma.

DCE-MRI analysis methods for predicting the response of breast cancer to neoadjuvant chemotherapy: pilot study findings

PURPOSE

The purpose of this pilot study is to determine (1) if early changes in both semiquantitative and quantitative DCE-MRI parameters, observed after the first cycle of neoadjuvant chemotherapy in breast cancer patients, show significant difference between responders and nonresponders and (2) if these parameters can be used as a prognostic indicator of the eventual response.

METHODS

Twenty-eight patients were examined using DCE-MRI pre-, post-one cycle, and just prior to surgery. The semiquantitative parameters included longest dimension, tumor volume, initial area under the curve, and signal enhancement ratio related parameters, while quantitative parameters included K(trans), v(e), k(ep), v(p), and τ(i) estimated using the standard Tofts-Kety, extended Tofts-Kety, and fast exchange regime models.

RESULTS

Our preliminary results indicated that the signal enhancement ratio washout volume and k(ep) were significantly different between pathologic complete responders from nonresponders (P < 0.05) after a single cycle of chemotherapy. Receiver operator characteristic analysis showed that the AUC of the signal enhancement ratio washout volume was 0.75, and the AUCs of k(ep) estimated by three models were 0.78, 0.76, and 0.73, respectively.

CONCLUSION

In summary, the signal enhancement ratio washout volume and k(ep) appear to predict breast cancer response after one cycle of neoadjuvant chemotherapy. This observation should be confirmed with additional prospective studies.

Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy

Reliable early assessment of breast cancer response to neoadjuvant therapy (NAT) would provide considerable benefit to patient care and ongoing research efforts, and demand for accurate and noninvasive early-response biomarkers is likely to increase. Response assessment techniques derived from quantitative magnetic resonance imaging (MRI) hold great potential for integration into treatment algorithms and clinical trials. Quantitative MRI techniques already available for assessing breast cancer response to neoadjuvant therapy include lesion size measurement, dynamic contrast-enhanced MRI, diffusion-weighted MRI, and proton magnetic resonance spectroscopy. Emerging yet promising techniques include magnetization transfer MRI, chemical exchange saturation transfer MRI, magnetic resonance elastography, and hyperpolarized MR. Translating and incorporating these techniques into the clinical setting will require close attention to statistical validation methods, standardization and reproducibility of technique, and scanning protocol design.

Diffusion-weighted and dynamic contrast-enhanced MRI in evaluation of early treatment effects during neoadjuvant chemotherapy in breast cancer patients

PURPOSE

To use dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MRI at 3 Tesla (T) for early evaluation of treatment effects in breast cancer patients undergoing neoadjuvant chemotherapy (NAC), and assess the reliability of DW-MRI.

MATERIALS AND METHODS

DW- and DCE-MRI acquisitions of 15 breast cancer patients were performed before and after one cycle of NAC. MRI tumor diameter and volume, apparent diffusion coefficient (ADC) and kinetic parameters (K(trans), v(e)) were derived. The reliability of ADC before NAC was assessed. Changes in MRI parameters after NAC were analyzed, and logistic regression analysis was used to find the best predictors for pathologic response.

RESULTS

The reliability for ADC values was high, with intraclass correlation coefficient of 0.84 (P = 0.001). After one cycle of NAC, MRI tumor diameter (8%, P = 0.005) and tumor volume (30%, P = 0.008) was reduced for all patients, while ADC mean values increased (0.12 mm(2)/s, P = 0.008). The best predictor for treatment response was a change in MRI tumor diameter with mean error rate of 0.167 (13% for responders, 5% for nonresponders, P = 0.291).

CONCLUSION

Changes in MRI derived tumor diameter and ADC after only one cycle of NAC could provide a valuable tool for early evaluation of treatment effects in breast cancer patients.

MRI in breast cancer therapy monitoring

Breast MRI has several roles in the clinical management of breast cancer, including as a screening method for high-risk women, as a diagnostic tool used as an adjunct to mammography and ultrasound, and for the staging of disease extent prior to treatment. In addition to these uses, MRI is also employed to track small changes in tumor size and microenvironment. MRI has produced several early indicators of treatment response in clinical trials over the last 10  years, including initial lesion pattern, changes in lesion size, kinetic parameters, apparent diffusion coefficient and T(2) value; the related technique of (1) H MRS has also shown that choline concentration, T(2) value and water-to-fat ratio are response indicators. In addition to measuring anatomical changes in the lesion size, as performed in traditional radiology, MRI has the ability to track vascular and cellular changes using dynamic contrast-enhanced MRI and diffusion-weighted MRI, respectively. By adding (1) H MRS to MRI examinations, metabolic changes can also be determined. These functional imaging techniques allow studies to focus on early time points relative to neoadjuvant treatment. Early treatment response predictors may allow therapy to be tailored to individual patients and thus aid in the realization of the goal of personalized medicine.

Breast MR with special focus on DW-MRI and DCE-MRI

The use of magnetic resonance imaging (MRI) for the assessment of breast lesions was first described in the 1970s; however, its wide application in clinical routine is relatively recent. The basic principles for diagnosis of a breast lesion rely on the evaluation of signal intensity in T2-weighted sequences, on morphologic assessment and on the evaluation of contrast enhancement behaviour. The quantification of dynamic contrast behaviour by dynamic contrast-enhanced (DCE) MRI and evaluation of the diffusivity of water molecules by means of diffusion-weighted MRI (DW-MRI) have shown promise in the work-up of breast lesions. Therefore, breast MRI has gained a role for all indications that could benefit from its high sensitivity, such as detection of multifocal lesions, detection of contralateral carcinoma and in patients with familial disposition. Breast MRI has been shown to have a role in monitoring of neoadjuvant chemotherapy, for the evaluation of therapeutic results during the course of therapy. Breast MRI can improve the determination of the remaining tumour size at the end of therapy in patients with a minor response. DCE-MRI and DW-MRI have shown potential for improving the early assessment of tumour response to therapy and the assessment of residual tumour after the end of therapy. Breast MRI is important in the postoperative work-up of breast cancers. High sensitivity and specificity have been reported for the diagnosis of recurrence; however, pitfalls such as liponecrosis and changes after radiation therapy have to be carefully considered.

[Breast magnetic resonance imaging: state of the art and clinical applications]

Breast magnetic resonance imaging is a modality that is being progressively integrated into the breast radiologist's daily clinical practice. There is consensus on the minimal technical requirements that a breast MR exam should have in order to attain diagnostic quality. Diagnostic criteria are mainly based on the American College of Radiology's BI-RADS magnetic resonance imaging categories. Breast cancer staging is a main clinical application, but it is not universally accepted. Other applications are: response evaluation in patients treated with chemotherapy, screening in high-risk patients, cancer of unknown origin, assessment of a possible relapse and breast implant evaluation.

Magnetic resonance imaging: a potential tool in assessing the addition of hyperthermia to neoadjuvant therapy in patients with locally advanced breast cancer

The poor overall survival for patients with locally advanced breast cancers has led over the past decade to the introduction of numerous neoadjuvant combined therapy regimens to down-stage the disease before surgery. At the same time, more evidence suggests the need for treatment individualisation with a wide variety of new targets for cancer therapeutics and also multi modality therapies. In this context, early determination of whether the patient will fail to respond can enable the use of alternative therapies that can be more beneficial. The purpose of this review is to examine the potential role of magnetic resonance imaging (MRI) in early prediction of treatment response and prognosis of overall survival in locally advanced breast cancer patients enrolled on multi modality therapy trials that include hyperthermia. The material is organised with a review of dynamic contrast (DCE)-MRI and diffusion weighted (DW)-MRI for characterisation of phenomenological parameters of tumour physiology and their potential role in estimating therapy response. Most of the work published in this field has focused on responses to neoadjuvant chemotherapy regimens alone, so the emphasis will be there, however the available data that involves the addition of hyperthermia to the regimen will be discussed The review will also include future directions that include the potential use of MRI imaging techniques in establishing the role of hyperthermia alone in modifying breast tumour microenvironment, together with specific challenges related to performing such studies.

Comparison of mammography, sonography, MRI and clinical examination in patients with locally advanced or inflammatory breast cancer who underwent neoadjuvant chemotherapy

OBJECTIVES

The purpose of this study was to determine the relative accuracies of mammography, sonography, MRI and clinical examination in predicting residual tumour size and pathological response after neoadjuvant chemotherapy for locally advanced or inflammatory breast cancer. Each prediction method was compared with the gold standard of surgical pathology.

METHODS

43 patients (age range, 25-62 years; mean age, 42.7 years) with locally advanced or inflammatory breast cancer who had been treated by neoadjuvant chemotherapy were enrolled prospectively. We compared the predicted residual tumour size and the predicted response on imaging and clinical examination with residual tumour size and response on pathology. Statistical analysis was performed using weighted kappa statistics and intraclass correlation coefficients (ICC).

RESULTS

The ICC values between predicted tumour size and pathologically determined tumour size were 0.65 for clinical examination, 0.69 for mammography, 0.78 for sonography and 0.97 for MRI. Agreement between the response predictions at mid-treatment and the responses measured by pathology had kappa values of 0.28 for clinical examination, 0.32 for mammography, 0.46 for sonography and 0.68 for MRI. Agreement between the final response predictions and the responses measured by pathology had kappa values of 0.43 for clinical examination, 0.44 for mammography, 0.50 for sonography and 0.82 for MRI.

CONCLUSION

Predictions of response and residual tumour size made on MRI were better correlated with the assessments of response and residual tumour size made upon pathology than were predictions made on the basis of clinical examination, mammography or sonography. Thus, the evaluation of predicted response using MRI could provide a relatively sensitive early assessment of chemotherapy efficacy.

[MRI evaluation of residual breast carcinoma after neoadjuvant chemotherapy]

PURPOSE

This study aims to evaluate the sensibility and specificity of MRI in the detection and size measuring of residual breast cancer in patients treated with neoadjuvant chemotherapy before surgery.

PATIENTS AND METHODS

This is a retrospective study of 32 women, who underwent breast MRI before and after neoadjuvant treatment. MRI has been confronted to surgical pathology results.

RESULTS

The sensibility of MRI to assess pathologic Complete Response (no invasive residual tumor) was excellent (100%) but the specificity was low (55,5%). There was no false negative case and four false positive cases (Two ductal carcinomas in situ and two scars-like fibrosis). When MRI outcomes were compared with the presence or absence of invasive or in situ residual carcinoma, only one false negative case was noticed (one "in situ" residual tumor). The correlation between tumor size measured by MRI and histopathology was low (r=0,32). Underestimations of tumor size were due to non-continuous tumor regression or invasive lobular carcinoma or association of invasive carcinoma and intra ductal breast cancer. Over estimations of tumor size were due to chemotherapy-induced changes.

CONCLUSION

MRI is a sensitive but poorly specific method to assess the pathological complete response after neoadjuvant chemotherapy. Estimation of tumor size and detection of isolated residual in situ carcinoma are fare. Therefore, surgical intervention remains necessary whatever the MRI outcomes.

DCE-MRI parameters have potential to predict response of locally advanced breast cancer patients to neoadjuvant chemotherapy and hyperthermia: a pilot study

Combined therapies represent a staple of modern medicine. For women treated with neoadjuvant chemotherapy (NA ChT) for locally advanced breast cancer (LABC), early determination of whether the patient will fail to respond can enable the use of alternative, more beneficial therapies. This is even more desirable when the combined therapy includes hyperthermia (HT), an efficient way to improve drug delivery, however, more costly and time consuming. There is data showing that this goal can be achieved using magnetic resonance imaging (MRI) with contrast agent (CA) enhancement. This work for the first time proposes combining the information extracted from pre-treatment MR imaging into a morpho-physiological tumour score (MPTS) with the hypothesis that this score will increase the prognostic efficacy, compared to each of its MR-derived components: morphological (derived from the shape of the tumour enhancement) and physiological (derived from the CA enhancement variance dynamics parameters). The MPTS was correlated with response as determined by both pathologic residual tumour and MRI imaging, and was shown to have potential to predict response. The MPTS was extracted from pre-treatment MRI parameters, so independent of the combined therapy used.

PURPOSE

To use a novel morpho-physiological tumour 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 min following bolus injection of gadopentetate-based contrast agent. Parametric maps were generated by fitting the signal intensity to a double exponential curve and were used to derive a morphological characterisation of the lesions. Enhancement-variance dynamics parameters, wash-in and wash-out parameters (WiP, WoP), were extracted. The morphological characterisation 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 pathological residual tumour and MRI imaging.

RESULTS

The contrast agent in all tumours typically peaked in the first 1-4 min. The tumours' WiP and WoP varied considerably. The MPTS was highly correlated with whether the patients had a pathological 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] 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.

What's new in neoadjuvant therapy for breast cancer?

Neoadjuvant treatment of breast cancer is currently being used in patients with advanced disease as well as with increasing application in those that present with initially operable breast cancer. The current clinical benefits of the use of NAC include: NAC increases the possibility of the use of BCS, the safety of NAC is comparable with that of adjuvant chemotherapy, and pCR may be predictive of overall survival. Although there are still unresolved clinical questions regarding the use of neoadjuvant therapy in initially operable breast cancer, there appears to be equivalent survival to the standard of care. Future research should be aimed at tailoring treatment to individual patients using specific tumor characteristics that may predict response to different types of chemotherapy, molecular targeted therapy, and endocrine therapy.

Assessment of residual tumour by FDG-PET: conventional imaging and clinical examination following primary chemotherapy of large and locally advanced breast cancer

Background:

The aim of this was to evaluate FDG-PET (2-(fluorine-18)-fluoro-2-deoxy-D-glucose positron emission tomography) for assessment of residual tumour after primary chemotherapy of large and locally advanced breast cancer in comparison with conventional imaging modalities.

Methods:

In a prospective multicentre trial, 99 patients underwent one or more breast imaging modalities before surgery in addition to clinical examination, namely, FDG-PET (n=89), mammography (n=47), ultrasound (n=46), and magnetic resonance imaging (MRI) (n=46). The presence of residual tumour by conventional imaging, dichotomised as positive or negative, and the level of FDG uptake (standardised uptake values, SUV) were compared with histopathology, which served as the reference standard. Patients with no residual tumour or only small microscopic foci of residual tumour were classified as having minimal residual disease and those with extensive microscopic and macroscopic residual tumour tissue were classified as having gross residual disease.

Results:

By applying a threshold SUV of 2.0, the sensitivity of FDG-PET for residual tumour was 32.9% (specificity, 87.5%) and increased to 57.5% (specificity, 62.5%) at a threshold SUV of 1.5. Conventional imaging modalities were more sensitive in identifying residual tumour, but had a low corresponding specificity; sensitivity and specificity were as follows: MRI 97.6 and 40.0%, mammography 92.5 and 57.1%, ultrasound 92.0 and 37.5%, respectively. Breast MRI provided the highest accuracy (91.3%), whereas FDG-PET had the lowest accuracy (42.7%).

Conclusions:

FDG-PET does not provide an accurate assessment of residual tumour after primary chemotherapy of breast cancer. Magnetic resonance imaging offers the highest sensitivity, but all imaging modalities have distinct limitations in the assessment of residual tumour tissue when compared with histopathology.

Temporal sampling requirements for reference region modeling of DCE-MRI data in human breast cancer

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 (K(trans) and v(e)) 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 seconds) 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 K(trans) and v(e) 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% confidence interval [CI]: 1.021, 1.029), Pearson's correlation r = 0.943 (95% CI: 0.940, 0.945) for K(trans), and 1.023 (95% CI: 1.021. 1.025), r = 0.979 (95% CI: 0.978, 0.980) for v(e). For the 64-second temporal resolution data the results were: 0.890 (95% CI: 0.894, 0.905), r = 0.8645, (95% CI: 0.858, 0.871) for K(trans), and 1.041 (95% CI: 1.039, 1.043), r = 0.970 (95% CI: 0.968, 0.971) for v(e).

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.

Dynamic contrast-enhanced MRI in the diagnosis and management of breast cancer

Dynamic contrast-enhanced MRI (DCE-MRI) is an evolving tool for determining breast disease, which benefits from the move to imaging at 3 T. It has major capabilities for the diagnosis, detection and monitoring of malignancy. It benefits from being non-invasive and three-dimensional, allowing visualisation of the extent of disease and its angiogenic properties, visualisation of lesion heterogeneity, detection of changes in angiogenic properties before morphological alterations, and the potential to predict the overall response either before the start of therapy or early during treatment. In addition, DCE-MRI is emerging as a powerful tool for screening high-risk patients and for detecting high-grade ductal carcinoma in situ. However, there are also a number of limitations, including the overlap in enhancement patterns between malignant and benign disease, the failure to resolve microscopic disease particularly in the neoadjuvant setting, and the inconsistent predictive value of the enhancement pattern for clinical outcome. Careful consideration should be given to the technical requirements of individual examinations and the need for automation of post-processing techniques to appropriately handle the growing volume of data acquired. Research continues, focusing on the use of higher field strengths with improved spatial and temporal resolution data, improving understanding of the mechanism of contrast enhancement at the cellular level, and developing macromolecular and targeted contrast agents.

Metabolic and vascular features of dynamic contrast-enhanced breast magnetic resonance imaging and (15)O-water positron emission tomography blood flow in breast cancer

RATIONALE AND OBJECTIVES

We sought to (1) describe associations between measures of tumor perfusion by dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI), blood flow by (15)O-water positron emission tomography (PET) and metabolism by (18)F-fluorodeoxyglucose ((18)F)-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 (15)O-water/(18)F-FDG PET within 1 month of clinical DCE-MRI between February 2004 and August 2006. The (15)O-water PET blood flow and (18)F-FDG metabolic rate and tissue transport constant (K(1)) in the primary malignancy were calculated. DCE-MRI peak percent enhancement 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 = .002) and K(1) (r = 0.76, P = .001). However, peak SER did not correlate significantly with FDG metabolic rate (r = 0.44, P = .101). There were no significant correlations between peak percent enhancement and any of the PET parameters.

CONCLUSIONS

Our findings suggest that tumor perfusion, represented by (15)O-water PET blood flow, is an important factor in the MRI enhancement of locally advanced breast cancer. A lack of correlation of FDG metabolic rate with blood flow and DCE-MRI kinetics suggests that (18)F-FDG PET provides complementary metabolic information independent of vascular factors.

A review of current evidence-based clinical applications for breast magnetic resonance imaging

Magnetic resonance imaging (MRI) is an important new tool for imaging of the breast. MRI has now been demonstrated to be the most sensitive imaging method for detecting breast carcinoma, allowing depiction of cancers that are occult on mammography, ultrasound, and clinical breast examination. This is tempered by imperfect specificity due to overlap in the features of benign and malignant lesions, and by higher examination cost and more limited availability compared to other breast imaging tests. This article describes the current evidence-based clinical indications for use of breast MRI. Specifically, MRI has been shown to be advantageous for cancer assessment for screening patients at high risk, evaluating patients with a new breast cancer diagnosis, monitoring patients undergoing neoadjuvant chemotherapy, and evaluating patients with metastatic axillary adenocarcinoma and unknown primary site. This tool has also been shown to be useful for the evaluation of silicone breast implant integrity. Employment of breast MRI as a problem solving technique for equivocal mammographic or clinical findings is controversial. For each of these clinical applications, the evidence regarding the diagnostic accuracy of breast MRI will be reviewed. An understanding of the current evidence will facilitate the most appropriate utilization of this important medical resource.

Breast MRI for cancer detection and characterization: a review of evidence-based clinical applications

RATIONALE AND OBJECTIVES

Breast MRI is an important new tool in the imaging armamentarium for the detection and characterization of breast carcinoma. Understanding the evidence-supported benefits and potential harms of breast MRI is important to ensure the appropriate utilization of this medical resource.

MATERIALS AND METHODS

This article reviews the clinical settings in which MRI for breast cancer assessment has been shown to be advantageous. The evidence regarding the diagnostic accuracy of MRI and the impact of this imaging tool on clinical outcomes are described. Novel breast MRI techniques which may lead to future improvements in performance are discussed.

RESULTS

Breast MRI has been shown in multiple studies to be advantageous for screening patients at high risk, evaluating patients with a new breast cancer diagnosis, monitoring treatment response in patients undergoing neoadjuvant chemotherapy and evaluating patients with metastatic axillary adenocarcinoma and unknown primary site. Among the limitations of MRI are its high cost and modest specificity resulting in false positive examinations.

CONCLUSIONS

When used in evidence-supported clinical settings, the high sensitivity of MRI results in earlier cancer detection or greater accuracy of detection compared to existing tests for breast carcinoma. Further scientific endeavors are crucial to optimize the future performance and application of breast MRI.

Lesion T2 relaxation times and volumes predict the response of malignant breast lesions to neoadjuvant chemotherapy

The aim of this study was to investigate the utility of the water T(2) values of malignant breast lesions in predicting response after the first and second cycles of neoadjuvant chemotherapy (NAC), both alone and in combination with lesion volumes. Thirty-five patients were scanned before the commencement of chemotherapy and again after the first, second and final treatment cycles. Two methods of obtaining lesion T(2) were used: imaging, where a series of T(2)-weighted images was acquired (T(R)/T(E)=1000/30, 60, 90 and 120 ms), and spectroscopy, where the T(2) value of unsuppressed water signal was determined with a multiecho sequence (T(R)=1.5 s; initial T(E)=35 ms; 64 steps of 2.5 ms; 2 unsuppressed acquisitions per T(E)). Lesion volumes were computed from contrast-enhanced 3D fat-suppressed images. The study found that, using the imaging method of obtaining T(2), the ratio of the product of lesion T(2) and volume after the second cycle of NAC to pretreatment value is a good predictor of ultimate lesion response, defined as a > or =65% reduction in tumor volume after the final treatment cycle, with positive and negative predictive values of 95.5% and 84.6%, respectively.

Lumbar bone marrow microcirculation measurements from dynamic contrast-enhanced magnetic resonance imaging is a predictor of event-free survival in progressive multiple myeloma

PURPOSE

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with high temporal resolution enables the detection of microcirculation variables amplitude A and exchange rate constant k(ep). In this study, the prognostic value of the DCE-MRI variables for overall survival and event-free survival in patients with progressive multiple myeloma was investigated.

EXPERIMENTAL DESIGN

Between 1999 and 2001, 65 patients with progressive or relapse of multiple myeloma requiring therapy were investigated with DCE-MRI of the lumbar spine before start of therapy. The contrast uptake was quantified using a two-compartment model with the output variables amplitude A and exchange rate constant k(ep) reflecting bone marrow microcirculation. The estimated median follow-up was 56 months. Event-free survival and overall survival were investigated for DCE-MRI variables and for established prognosis variables (beta(2)-microglobulin, lactate dehydrogenase, albumin, and age).

RESULTS

Using a multivariate Cox regression model, beta(2)-microglobulin and amplitude A of DCE-MRI were identified as statistically significant prognostic variable of event-free survival with Ps of 0.01 and 0.02, respectively. A statistical correlation of DCE-MRI variables with overall survival could not be found. The multivariate analysis of beta(2)-microglobulin, age, lactate dehydrogenase, and albumin revealed beta(2)-microglobulin as statistically significant prognostic factor for overall survival in this group of patients (P < 0.001).

CONCLUSIONS

This analysis identifies contrast-enhanced DCE-MRI variable amplitude A reflecting increased bone marrow microcirculation and angiogenesis as a novel and possibly useful prognostic factor in patients with multiple myeloma. Prospective studies are currently done to further investigate this functional variable for prognosis and stratification of myeloma patients.

AG-013736, a novel inhibitor of VEGF receptor tyrosine kinases, inhibits breast cancer growth and decreases vascular permeability as detected by dynamic contrast-enhanced magnetic resonance imaging

Dynamic contrast-enhanced MRI (DCE-MRI) was used to noninvasively evaluate the effects of AG-03736, a novel inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, on tumor microvasculature in a breast cancer model. First, a dose response study was undertaken to determine the responsiveness of the BT474 human breast cancer xenograft to AG-013736. Then, DCE-MRI was used to study the effects of a 7-day treatment regimen on tumor growth and microvasculature. Two DCE-MRI protocols were evaluated: (1) a high molecular weight (MW) contrast agent (albumin-(GdDTPA)(30)) with pharmacokinetic analysis of the contrast uptake curve and (2) a low MW contrast agent (GdDTPA) with a clinically utilized empirical parametric analysis of the contrast uptake curve, the signal enhancement ratio (SER). AG-013736 significantly inhibited growth of breast tumors in vivo at all doses studied (10-100 mg/kg) and disrupted tumor microvasculature as assessed by DCE-MRI. Tumor endothelial transfer constant (K(ps)) measured with albumin-(GdDTPA)(30) decreased from 0.034+/-0.005 to 0.003+/-0.001 ml min(-1) 100 ml(-1) tissue (P<.0022) posttreatment. No treatment-related change in tumor fractional plasma volume (fPV) was detected. Similarly, in the group of mice studied with GdDTPA DCE-MRI, AG-013736-induced decreases in tumor SER measures were observed. Additionally, our data suggest that 3D MRI-based volume measurements are more sensitive than caliper measurements for detecting small changes in tumor volume. Histological staining revealed decreases in tumor cellularity and microvessel density with treatment. These data demonstrate that both high and low MW DCE-MRI protocols can detect AG-013736-induced changes in tumor microvasculature. Furthermore, the correlative relationship between microvasculature changes and tumor growth inhibition supports DCE-MRI methods as a biomarker of VEGF receptor target inhibition with potential clinical utility.

Imaging breast cancer

Imaging has a significant role in diagnosing, treating, and monitoring breast cancer. Advances in this field are having a great impact in the clinical management of this disease. Breast cancer has now become an "outpatient cancer". This article describes the role and advances of imaging in breast cancer.