Dynamic MRI for imaging tumor microvasculature: comparison of susceptibility and relaxivity techniques in pelvic tumors

Association between Dynamic Contrast-Enhanced MRI Parameters and Prognostic Factors in Patients with Primary Rectal Cancer

BACKGROUND

To evaluate the association between perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with prognostic factors in primary rectal cancer patients.

METHODS

A sample of 51 patients with pathologically proven rectal adenocarcinoma through surgery were retrospectively enrolled. All the patients underwent preoperative DCE-MRI including 3D-spoiled gradient echo. Two radiologists determined the tumor border after radiologic-pathologic correlation and drew regions of interest. The perfusion parameters, including the volume transfer constant (K^trans), were calculated under the extended Toft model. The prognostic factors included TN stage, circumferential resection margin, extramural venous invasion, Kirsten-ras mutation, tumor size, carcinoembryonic antigen, and tumor differentiation. The association was assessed via correlation or t-test. For significant prognostic factors, receiver operating characteristic (ROC) curve analyses were performed to estimate the diagnostic predictive values.

RESULTS

K^trans only showed a significant difference according to tumor differentiation, between the well-differentiated (n = 6) and moderately differentiated (n = 45) groups (0.127 ± 0.032, 0.084 ± 0.036, p = 0.036). The AUC was 0.838 (95% CI, 0.702-0.929), and the estimated accuracy, sensitivity, and specificity were 87%, 90%, and 60%, respectively.

CONCLUSIONS

K^trans showed a significant difference based on tumor differentiation, which may be conducive to prediction of prognosis in primary rectal cancer.

Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology

Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.

Novel biomarkers for patient stratification in colorectal cancer: A review of definitions, emerging concepts, and data

Colorectal cancer (CRC) treatment has become more personalised, incorporating a combination of the individual patient risk assessment, gene testing, and chemotherapy with surgery for optimal care. The improvement of staging with high-resolution imaging has allowed more selective treatments, optimising survival outcomes. The next step is to identify biomarkers that can inform clinicians of expected prognosis and offer the most beneficial treatment, while reducing unnecessary morbidity for the patient. The search for biomarkers in CRC has been of significant interest, with questions remaining on their impact and applicability. The study of biomarkers can be broadly divided into metabolic, molecular, microRNA, epithelial-to-mesenchymal-transition (EMT), and imaging classes. Although numerous molecules have claimed to impact prognosis and treatment, their clinical application has been limited. Furthermore, routine testing of prognostic markers with no demonstrable influence on response to treatment is a questionable practice, as it increases cost and can adversely affect expectations of treatment. In this review we focus on recent developments and emerging biomarkers with potential utility for clinical translation in CRC. We examine and critically appraise novel imaging and molecular-based approaches; evaluate the promising array of microRNAs, analyze metabolic profiles, and highlight key findings for biomarker potential in the EMT pathway.

Differentiation of olfactory neuroblastomas from nasal squamous cell carcinomas using MR diffusion kurtosis imaging and dynamic contrast-enhanced MRI

PURPOSE

To evaluate the use of magnetic resonance (MR) diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced MR imaging (DCE-MRI) in the differentiation of olfactory neuroblastomas (ONBs) from squamous cell carcinomas (SCCs).

MATERIALS AND METHODS

DKI and DCE-MRI were performed in 17 patients with ONBs and 23 patients with SCCs on a 3T MR scanner. Parameters derived from DKI and DCE-MRI were measured and compared between ONBs and SCCs using an independent samples t-test. The sensitivity, specificity, accuracy, positive predictive values (PPV), negative predictive values (NPV), and the area under the receiver operating characteristic (ROC) curve were determined.

RESULTS

The mean kurtosis (K) value of ONBs was significantly higher than that of SCCs (P < 0.001), and the mean fractional volume in the extravascular extracellular space (V_e ) value of ONBs was lower than that of SCCs (P < 0.001). The ROC curve analyses yielded a cutoff K value of 0.953, with a sensitivity of 94.1%, a specificity of 69.6%, and an accuracy of 80.0%; the cutoff V_e value was 0.493, with a sensitivity of 70.6%, a specificity of 95.7%, and an accuracy of 85.0%. A parallel test with K value >0.953 or V_e value ≤0.493 achieved a sensitivity of 94.1%, a specificity of 100.0%, and an accuracy of 97.5% for differentiating ONBs from SCCs.

CONCLUSION

The K value of DKI and V_e value of DCE-MRI have potential use in the differentiation of ONBs and SCCs.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:354-361.

Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRI

PURPOSE

To evaluate multiparametric MRI features in predicting pathologic response after preoperative chemoradiation therapy (CRT) for locally advanced rectal cancer (LARC).

EXPERIMENTAL DESIGN

Forty-eight consecutive patients (January 2012-November 2014) receiving neoadjuvant CRT were enrolled. All underwent anatomical T1/T2, diffusion-weighted MRI (DWI) and dynamic contrast-enhanced (DCE) MRI before CRT. A total of 103 imaging features, analyzed using both volume-averaged and voxelized methods, were extracted for each patient. Univariate analyses were performed to evaluate the capability of each individual parameter in predicting pathologic complete response (pCR) or good response (GR) evaluated based on tumor regression grade. Artificial neural network with 4-fold validation technique was further utilized to select the best predictor sets to classify different response groups and the predictive performance was calculated using receiver operating characteristic (ROC) curves.

RESULTS

The conventional volume-averaged analysis could provide an area under ROC curve (AUC) ranging from 0.54 to 0.73 in predicting pCR. While if the models were replaced by voxelized heterogeneity analysis, the prediction accuracy measured by AUC could be improved to 0.71-0.79. Similar results were found for GR prediction. In addition, each subcategory images could generate moderate power in predicting the response, which if combining all information together, the AUC could be further improved to 0.84 for pCR and 0.89 for GR prediction, respectively.

CONCLUSIONS

Through a systematic analysis of multiparametric MR imaging features, we are able to build models with improved predictive value over conventional imaging metrics. The results are encouraging, suggesting the wealth of imaging radiomics should be further explored to help tailoring the treatment into the era of personalized medicine. Clin Cancer Res; 22(21); 5256-64. ©2016 AACR.

Clinical Trial of Oral Nelfinavir before and during Radiation Therapy for Advanced Rectal Cancer

PURPOSE

Nelfinavir, a PI3K pathway inhibitor, is a radiosensitizer that increases tumor blood flow in preclinical models. We conducted an early-phase study to demonstrate the safety of nelfinavir combined with hypofractionated radiotherapy (RT) and to develop biomarkers of tumor perfusion and radiosensitization for this combinatorial approach.

EXPERIMENTAL DESIGN

Ten patients with T3-4 N0-2 M1 rectal cancer received 7 days of oral nelfinavir (1,250 mg b.i.d.) and a further 7 days of nelfinavir during pelvic RT (25 Gy/5 fractions/7 days). Perfusion CT (p-CT) and DCE-MRI scans were performed pretreatment, after 7 days of nelfinavir and prior to the last fraction of RT. Biopsies taken pretreatment and 7 days after the last fraction of RT were analyzed for tumor cell density (TCD).

RESULTS

There were 3 drug-related grade 3 adverse events: diarrhea, rash, and lymphopenia. On DCE-MRI, there was a mean 42% increase in medianKtrans, and a corresponding median 30% increase in mean blood flow on p-CT during RT in combination with nelfinavir. Median TCD decreased from 24.3% at baseline to 9.2% in biopsies taken 7 days after RT (P= 0.01). Overall, 5 of 9 evaluable patients exhibited good tumor regression on MRI assessed by tumor regression grade (mrTRG).

CONCLUSIONS

This is the first study to evaluate nelfinavir in combination with RT without concurrent chemotherapy. It has shown that nelfinavir-RT is well tolerated and is associated with increased blood flow to rectal tumors. The efficacy of nelfinavir-RT versus RT alone merits clinical evaluation, including measurement of tumor blood flow.

Reproducibility of Dynamic Contrast-Enhanced MRI in Renal Cell Carcinoma: A Prospective Analysis on Intra- and Interobserver and Scan-Rescan Performance of Pharmacokinetic Parameters

The objective of this study was to investigate the intra- and interobserver as well as scan-rescan reproducibility of quantitative parameters of renal cell carcinomas (RCCs) with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A total of 21 patients with clear cell RCCs (17 men, 4 woman; age 37-69 years, mean age 54.6 years, mean size, 5.0 ± 2.2 cm) were prospectively recruited from September 2012 to November 2012. Patients underwent paired DCE-MRI studies on a 3.0 T MR system with an interval of 48 to 72 hours. The extended-Tofts model and population-based arterial input function were used to calculate kinetic parameters. Three observers defined the 2-dimensional whole-tumor region of interest at the slice with the maximum diameter of the RCC. Intraobserver and scan-rescan differences were assessed using paired t tests, whereas interobserver differences using two-way analysis of variance. Intra- and interobserver reproducibility and scan-rescan reproducibility were evaluated using within-subject coefficient of variation (wCoV) and intraclass correlation coefficient (ICC). There were no significant intra-, interobserver, or scan-rescan differences in parameters (all P > 0.05). All ICCs for intra- and interobserver agreements were >0.75 (P < 0.05), whereas the scan-rescan agreement was moderate to good; V(e) (0.764, 95% confidence interval [CI]: 0.378-0.925) and K(ep) (0.906, 95% CI: 0.710-0.972) had higher ICC than K(trans) (0.686; 95% CI: 0.212-0.898) and V(p) (0.657; 95% CI: 0.164-0.888). In intra- and interobserver variability analyses, all parameters except V(p) had low wCoV values. K(trans) and V(e) had slightly lower intraobserver wCoV (1.2% and 0.9%) compared with K(ep) (3.7%), whereas all 3 of these parameters had similar interobserver wCoV values (2.5%, 3.1%, and 2.9%, respectively). Regarding scan-rescan variability, K(trans) and K(ep) showed slightly higher variation (15.6% and 15.4%) than V(e) (10.1%). V(p) had the largest wCoV in all variability analyses (all >30%). DCE-MRI demonstrated good intra- and interobserver reproducibility and moderate to good scan-rescan performance in the assessment of RCC using K(trans), K(ep), and V(e) as parameters under noncontinuous scanning mode. V(p) showed poor reproducibility, and thus may not be suitable for this scanning protocol.

Dependence of DCE-MRI biomarker values on analysis algorithm

Background

Dynamic contrast-enhanced MRI (DCE-MRI) biomarkers have proven utility in tumors in evaluating microvascular perfusion and permeability, but it is unclear whether measurements made in different centers are comparable due to methodological differences.

Purpose

To evaluate how commonly utilized analytical methods for DCE-MRI biomarkers affect both the absolute parameter values and repeatability.

Materials and Methods

DCE-MRI was performed on three consecutive days in twelve rats bearing C6 xenografts. Endothelial transfer constant (K^trans), extracellular extravascular space volume fraction (v_e), and contrast agent reflux rate constant (k_ep) measures were computed using: 2-parameter (“Tofts” or “standard Kety”) vs. 3-parameter (“General Kinetic” or “extended Kety”) compartmental models (including blood plasma volume fraction (v_p) with 3-parameter models); individual- vs. population-based vascular input functions (VIFs); and pixel-by-pixel vs. whole tumor-ROI. Variability was evaluated by within-subject coefficient of variation (wCV) and variance components analyses.

Results

DCE-MRI absolute parameter values and wCVs varied widely by analytical method. Absolute parameter values ranged, as follows, median K^trans, 0.09–0.18 min^-1; k_ep, 0.51–0.92 min^-1; v_e, 0.17–0.23; and v_p, 0.02–0.04. wCVs also varied widely by analytical method, as follows: mean K^trans, 32.9–61.9%; k_ep, 11.6–41.9%; v_e, 16.1–54.9%; and v_p, 53.9–77.2%. K^trans and k_ep values were lower with 3- than 2-parameter modeling (p<0.0001); k_ep and v_p were lower with pixel- than whole-ROI analyses (p<0.0006). wCVs were significantly smaller for v_e, and larger for k_ep, with individual- than population-based VIFs.

Conclusions

DCE-MRI parameter values and repeatability can vary widely by analytical methodology. Absolute values of DCE-MRI biomarkers are unlikely to be comparable between different studies unless analyses are carefully standardized.

Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients

OBJECTIVES

This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.

METHODS

Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.

RESULTS

CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.

CONCLUSIONS

DSC-MRI is highly repeatable in high-grade glioma patients.

Functional MRI and CT biomarkers in oncology

Imaging biomarkers derived from MRI or CT describe functional properties of tumours and normal tissues. They are finding increasing numbers of applications in diagnosis, monitoring of response to treatment and assessment of progression or recurrence. Imaging biomarkers also provide scope for assessment of heterogeneity within and between lesions. A wide variety of functional parameters have been investigated for use as biomarkers in oncology. Some imaging techniques are used routinely in clinical applications while others are currently restricted to clinical trials or preclinical studies. Apparent diffusion coefficient, magnetization transfer ratio and native T1 relaxation time provide information about structure and organization of tissues. Vascular properties may be described using parameters derived from dynamic contrast-enhanced MRI, dynamic contrast-enhanced CT, transverse relaxation rate (R2*), vessel size index and relative blood volume, while magnetic resonance spectroscopy may be used to probe the metabolic profile of tumours. This review describes the mechanisms of contrast underpinning each technique and the technical requirements for robust and reproducible imaging. The current status of each biomarker is described in terms of its validation, qualification and clinical applications, followed by a discussion of the current limitations and future perspectives.

Clinical imaging of tumor angiogenesis

Angiogenesis is an integral part of tumor growth and invasion. This has led to the emergence of several antiangiogenic therapies and stimulated efforts to accurately evaluate the extent of angiogenesis before and in response to anticancer treatment. The most commonly used approach has been the assessment of new vessel formation in histological samples. However, it is becoming apparent that this is insufficient for a full understanding of tumor physiology and for in vivo guidance of cancer management. Imaging has the potential to provide noninvasive and repeatable assessment of the angiogenic process. Imaging approaches use a variety of modalities and are aimed at either assessment of the functional integrity of tumor vasculature or assessment of its molecular status. This review summarizes the aims and methods of clinical tumor angiogenesis imaging, including present technologies and ones that will be developed within the next 5-10 years.

Evaluation of pancreatic cancer by multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging at 3.0T

OBJECTIVE

To investigate the microcirculation in pancreatic cancer by pharmacokinetic analysis of multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging at 3.0T.

MATERIALS AND METHODS

Multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging was performed in 40 healthy volunteers and 40 patients with pancreatic cancer proven by histopathology using an axial three-dimensions fat-saturated T1-weighted spoiled-gradient echo sequence at 3.0T. A two compartment model with T1 correction was used to quantify the transfer constant, the rate constant of backflux from the extravascular extracellular space to the plasma and the extravascular extracellular space fractional volume in pancreatic cancer, obstructive pancreatitis distal to the malignant tumor, adjacent pancreatic tissue proximal to the tumor and normal pancreas. All parameters were statistically analyzed.

RESULTS

Statistical differences were noticed in both the transfer constant (p=0.000075) and the rate constant of backflux (p=0.006) among different tissues. Both the transfer constant and the rate constant of backflux in pancreatic cancer were statistically lower than those in normal pancreas and adjacent pancreatic tissue (p<0.05). Both the transfer constant and the rate constant of backflux in obstructive pancreatitis were statistically lower than those in normal pancreas and adjacent pancreatic tissue (p<0.05). The extravascular extracellular space fractional volume in pancreatic cancer was statistically lager than that in normal pancreas (p=0.002).

CONCLUSION

Multiple breath-hold dynamic contrast-enhanced magnetic resonance imaging offers a useful technique to evaluate the microenvironment in pancreatic cancer at 3.0T. Compared to normal pancreas, pancreatic cancer has lower transfer constant, rate constant of backflux and larger extravascular extracellular space fractional volume.

Functional MRI techniques demonstrate early vascular changes in renal cell cancer patients treated with sunitinib: a pilot study

Objective: To assess the early vascular effects of sunitinib in patients with renal cell carcinoma (RCC) with diffusion-weighted magnetic resonance imaging (DWI), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and T2* perfusion MRI. Patients and methods: In 10 patients with abdominal RCC lesions, DWI, DCE-MRI and T2* perfusion MRI measurements at 3 Tesla were performed at baseline, 3 and 10 days after start of sunitinib. VEGF-A plasma levels were measured on days 0, 3 and 10. Results: DWI showed a significant increase in the apparent diffusion coefficient (×10⁻⁶s/mm²) from baseline (mean 1158, range 814–2003) to day 3 (mean 1306, range 1008–2097, P = 0.015) followed by a decrease to baseline levels at day 10 (mean 1132, range 719–2005, P = 0.001). No significant changes were found in mean DCE-MRI parameters. T2* perfusion MRI showed a significant decrease in relative tumor blood volume (rBV) and relative tumor blood flow (rBF) at day 3 (rBV P = 0.037, rBF P = 0.018) and day 10 (rBV P = 0.006, rBF P = 0.009). VEGF-A plasma levels significantly increased after 10 days, but did not correlate with MRI parameters. Conclusions: Sunitinib induces antiangiogenic effects as measured by DWI and T2*-perfusion MRI, 3 and 10 days after the start of the initial treatment. DCE-MRI did not show significant changes. In the near future, early functional MRI-based evaluation can play an important role in tailoring treatment to the individual patient with RCC. Further investigation is warranted.

Dynamic contrast-enhanced magnetic resonance imaging as a prognostic factor in predicting event-free and overall survival in pediatric patients with osteosarcoma

BACKGROUND

The objective of this study was to prospectively evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as an early imaging indicator of tumor histologic response to preoperative chemotherapy and as a possible prognostic factor for event-free survival (EFS) and overall survival in pediatric patients with newly diagnosed, nonmetastatic osteosarcoma who were treated on a single, multi-institutional phase 2 trial.

METHODS

Three serial DCE-MRI examinations at week 0 (before treatment), week 9, and week 12 (tumor resection) were performed in 69 patients with nonmetastatic osteosarcoma to monitor the response to preoperative chemotherapy. Four DCE-MRI kinetic parameters (the influx volume transfer constant [K(trans) ], the efflux rate constant [k(ep) ], the relative extravascular extracellular space [v(e) ], and the relative vascular plasma space [v(p) ]) and the corresponding differences (ΔK(trans) , Δk(ep) , Δv(e) , and Δv(p) ) of averaged kinetic parameters between the outer and inner halves of tumors were calculated to assess their associations with tumor histologic response, EFS, and overall survival.

RESULTS

The parameters K(trans) , v(e) , v(p) , and k(ep) decreased significantly from week 0 to week 9 and week 12. The parameters K(trans) , v(p) , and Δk(ep) at week 9 were significantly different between responders and nonresponders (P = .046, P = .021, and P = .008, respectively). These 3 parameters were indicative of histologic response. The parameter Δv(e) at week 0 was a significant prognostic factor for both EFS (P = .02) and overall survival (P = .03).

CONCLUSIONS

DCE-MRI was identified as a prognostic factor for EFS and overall survival before treatment on this trial and was indicative of a histologic response to neoadjuvant therapy. Further studies are needed to verify these findings with other treatment regimens and establish the potential role of DCE-MRI in the development of risk-adapted therapy for osteosarcoma.

Dynamic contrast enhanced-MRI for the detection of pathological complete response to neoadjuvant chemotherapy for locally advanced rectal cancer

OBJECTIVE

To determine the ability of dynamic contrast enhanced (DCE-MRI) to predict pathological complete response (pCR) after preoperative chemotherapy for rectal cancer.

METHODS

In a prospective clinical trial, 23/34 enrolled patients underwent pre- and post-treatment DCE-MRI performed at 1.5T. Gadolinium 0.1 mmol/kg was injected at a rate of 2 mL/s. Using a two-compartmental model of vascular space and extravascular extracellular space, K(trans), k(ep), v(e), AUC90, and AUC180 were calculated. Surgical specimens were the gold standard. Baseline, post-treatment and changes in these quantities were compared with clinico-pathological outcomes. For quantitative variable comparison, Spearman's Rank correlation was used. For categorical variable comparison, the Kruskal-Wallis test was used. P ≤ 0.05 was considered significant.

RESULTS

Percentage of histological tumour response ranged from 10 to 100%. Six patients showed pCR. Post chemotherapy K(trans) (mean 0.5 min(-1) vs. 0.2 min(-1), P = 0.04) differed significantly between non-pCR and pCR outcomes, respectively and also correlated with percent tumour response and pathological size. Post-treatment residual abnormal soft tissue noted in some cases of pCR prevented an MR impression of complete response based on morphology alone.

CONCLUSION

After neoadjuvant chemotherapy in rectal cancer, MR perfusional characteristics have been identified that can aid in the distinction between incomplete response and pCR.

KEY POINTS

Dynamic contrast enhanced (DCE) MRI provides perfusion characteristics of tumours. These objective quantitative measures may be more helpful than subjective imaging alone Some parameters differed markedly between completely responding and incompletely responding rectal cancers. Thus DCE-MRI can potentially offer treatment-altering imaging biomarkers.

Perfusion MRI in the early clinical development of antivascular drugs: decorations or decision making tools?

INTRODUCTION

Classically, the first step in the clinical development of drugs in oncology involves assessments of dose limiting toxicity (DLT) and maximum tolerated dose (MTD). New paradigms are needed for antiangiogenic drugs and vascular disrupting agents (VDAs) as they are active at doses well below the MTD and as single agents their use might not translate into anti-tumour efficacy. MRI is able to assess the antivascular effects of antivascular drugs via changes in functional kinetic parameters; however, the usefulness of MRI in decision making has been questioned by many.

OBJECTIVES

Our aim is to review the experience of using dynamic contrast-enhanced MRI (DCE-MRI) in early clinical development of vascular directed anticancer therapies over the last decade. Thirty-nine phase I and II studies including data on more than 700 patients have been published as abstracts and/or papers, documenting DCE-MRI changes after the administration of antiangiogenic drugs and VDAs.

DISCUSSION

Perfusion MRI is helpful in assessing whether mechanistic goals are achieved, in assisting dose selection for phase II studies, in selecting subpopulations enriched for response and in predicting patient benefit. Imaging tools are increasingly available. Future challenges for imaging include correlation with clinical measures of efficacy and determining relationships with blood and serum biomarkers.

Reproducibility and correlation between quantitative and semiquantitative dynamic and intrinsic susceptibility-weighted MRI parameters in the benign and malignant human prostate

PURPOSE

To assess the reproducibility of relaxivity- and susceptibility-based dynamic contrast-enhanced magnetic resonance imaging (MRI) in the benign and malignant prostate gland and to correlate the kinetic parameters obtained.

MATERIALS AND METHODS

Twenty patients with prostate cancer underwent paired scans before and after androgen deprivation therapy. Quantitative parametric maps for T(1)- and T(2)*-weighted parameters were calculated (K(trans), k(ep),v(e), IAUC(60), rBV, rBF, and R(2)*). The reproducibility of and correlation between each parameter were determined using standard methods at both timepoints.

RESULTS

T(1)-derived parameters are more reproducible than T(2)*-weighted measures, both becoming more variable following androgen deprivation (variance coefficients for prostate K(trans) and rBF increased from 13.9%-15.8% and 42.5%-90.8%, respectively). Tumor R(2)* reproducibility improved after androgen ablation (23.3%-11.8%). IAUC(60) correlated strongly with K(trans), v(e), and k(ep) (all P < 0.001). R(2)* did not correlate with other parameters.

CONCLUSION

This study is the first to document the variability and repeatability of T(1)- and T(2)*-weighted dynamic MRI and intrinsic susceptibility-weighted MRI for the various regions of the human prostate gland before and after androgen deprivation. These data provide a valuable source of reference for groups that plan to use dynamic contrast-enhanced MRI or intrinsic susceptibility-weighted MRI for the assessment of treatment response in the benign or malignant prostate.

Dynamic contrast-enhanced CT for prostate cancer: relationship between image noise, voxel size, and repeatability

PURPOSE

To evaluate the relationship between image noise, voxel size, and voxel-wise repeatability of a dynamic contrast agent-enhanced (DCE) computed tomographic (CT) examination for prostate cancer.

MATERIALS AND METHODS

This prospective study was approved by the local research ethics committee, and all patients gave written informed consent. Twenty-nine patients (mean age, 69.1 years; range, 56-80 years) with biopsy-proved prostate cancer underwent two DCE CT examinations within 1 week prior to radiation therapy. Parameter maps of transfer constant (K(trans)), the fraction of blood plasma (v(p)), the fraction of extravascular extracellular space (v(e)), and the flux rate constant between the extravascular extracellular space and plasma (k(ep)) were calculated at 15 different image resolutions, with kernel sizes ranging from 0.002 to 2.57 cm(3). Statistical analysis to quantify the voxel-wise repeatability was performed by using a Bland-Altman analysis on all tracer kinetic model parameter maps of each patient. From this analysis, the within-voxel standard deviation (wSD) was calculated as a function of spatial resolution.

RESULTS

A kernel size in the range of 0.1-0.3 cm(3) yields reliable information. At 0.15 cm(3), the median wSDs of K(trans), k(ep), v(p), and v(e) are 0.047 min(-1), 0.144 min(-1), 0.011, and 0.104, respectively. With increasing kernel size, these values reach stable levels of approximately 0.02 min(-1), 0.05 min(-1), 0.005, and 0.05, respectively.

CONCLUSION

There is a high voxel-wise repeatability of the DCE CT imaging technique for prostate cancer for kernel sizes as small as 0.1 cm(3). With the relationship between kernel size, image noise and voxel-wise repeatability, it becomes possible to estimate for alternative DCE CT protocols (eg, those with a reduced radiation dose) at what kernel size a sufficient repeatability can be obtained.

Study of onset time-shift and injection duration in DCE-MRI: a comparison of a reference region model with the general kinetic model

In dynamic contrast-enhanced MR imaging (DCE-MRI), sampling of the arterial input function (AIF) is required for analysis using the general kinetic model (GKM). Alternatively, the recently proposed reference region model (RRM) may be employed to avoid the need of acquiring the AIF. This study aimed to evaluate the influence of the AIF onset-time shift and the injection duration, under various sampling intervals, on physiological parameter estimation in DCE-MRI using the GKM, and to compare the performance between GKM and RRM. Computer simulations were performed to assess the mean error (ME) and coefficient of variation (CoV) of K(trans,TOI) and v(e,TOI) from shifted and dispersed AIF with temporal resolution of 1, 5 and 10 s. With 5-s sampling, the maximal ME of K(trans,TOI) was roughly 22% for the GKM and 0.5% for the RRM. With 10-s sampling, they increased to around 28% and 0.7%, respectively. The maximal MEs of v(e,TOI) for all cases were under 5%. However, owing to the lower SNR in the reference region, the CoV obtained by the RRM were all higher than those by the GKM. The results suggested that with compromised temporal resolution, the RRM was relatively less sensitive to the AIF onset-time shift and the injection duration compared with the GKM.

Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy

There is an increasing awareness that anatomical approaches based on measurements of tumor size have significant limitations for assessing therapy response. Functional imaging techniques are increasing being used to monitor response to therapies with novel mechanisms of action, often predicting the success of therapy before conventional measurements have changed. Dynamic contrast-enhanced and diffusion magnetic resonance imaging (MRI) are the most advanced in their evidence base, and in this manuscript we focus on them as response parameters. Technology, data gathering methods, and current limitations for these techniques are addressed. With few exceptions, most studies shows that successful treatment is reflected by increases in tumor water diffusion values visible as increased apparent diffusion coefficient values. Most response assessment studies also show that successful treatment results in decreases in tumor vascularization and microvessel permeability.

Dynamic contrast-enhanced MRI in ovarian cancer: Initial experience at 3 tesla in primary and metastatic disease

The aim of this study was to develop and demonstrate a methodology for dynamic contrast-enhanced MRI at 3 T in patients with advanced ovarian cancer and to report the results from pharmacokinetic modeling of the data. Nineteen patients with suspected advanced ovarian carcinoma (FIGO stage 3 or higher) were enrolled in this prospective study. Up to three marker lesions were identified: primary ovarian mass, omental ''cake'', and peritoneal deposits. Dynamic contrast-enhanced MRI was performed using a three-dimensional T(1)-weighted gradient-echo acquisition with a temporal resolution of 1.6 sec, following intravenous administration of 0.1 mmol/kg gadobutrol. Precontrast T(1) mapping, using an inversion-recovery fast gradient-echo sequence, was also performed. Imaging was completed in 18/19 patients, although two were subsequently excluded based on pathology results. Pharmacokinetic modeling of the data was performed according to the extended Kety model, using an arterial input function formed by concatenation of the Fritz-Hansen and Weinmann curves. No statistically significant differences were found between the results for the three marker lesions. In the future, this work will allow kinetic modeling results from ovarian dynamic contrast-enhanced MRI to be correlated with response to treatment. The high temporal resolution allows good characterization of the rapid contrast agent uptake in these vascular tumors.

Reproducibility of perfusion parameters in dynamic contrast-enhanced MRI of lung and liver tumors: effect on estimates of patient sample size in clinical trials and on individual patient responses

OBJECTIVE

Dynamic contrast-enhanced MRI (DCE-MRI) is a potentially useful noninvasive technique for assessing tissue perfusion, particularly in the context of solid tumors and targeted antiangiogenic and antivascular therapies. Our aim was to determine the reproducibility of perfusion parameters derived at DCE-MRI of tumors of the lung and liver, the most common sites of metastasis.

SUBJECTS AND METHODS

Patients with lung and liver tumors underwent two sequential DCE-MRI examinations 2-7 days apart without any intervening therapy. The volume transfer constant between blood plasma and the extravascular extracellular space (K(trans)) and blood-normalized initial area under the signal intensity-time curve (initial AUC(BN)) were computed with a two-compartment pharmacokinetic model. Differences in parameters were assessed with within-patient coefficients of variation.

RESULTS

Twenty-three patients had evaluable tumors (12 lung, 11 liver). The within-patient coefficients of variation for K(trans) and initial AUC(BN) for liver lesions were 8.9% and 9.9% and for lung lesions were 17.9% and 18.2%. Sample sizes for reductions in these parameters from 10% to 50% were estimated to range from two to 102 subjects. Estimates of confidence that changes observed in a given patient were due to intervening therapy rather than variability of the technique were calculated to range from 71% to 87% if a 20% reduction in a parameter was observed.

CONCLUSION

The rate of reproducibility of DCE-MRI parameters is in the range of 10%-20% and is influenced by lesion location, parameters being significantly more reproducible in the liver than in the lung. These findings provide the foundation for interpretation of results and design of clinical trials in which DCE-MRI studies are used to assess objective responses.

Vessel growth and function: depiction with contrast-enhanced MR imaging

Magnetic resonance (MR) imaging is a versatile noninvasive diagnostic tool that can be applied to the entire human body to revealing morphologic, functional, and metabolic information. The authors review how MR imaging can depict both the established and the developing vasculature with techniques involving intravenously administered contrast agents. In addition to macrovascular morphology and flow, MR imaging is able to exploit microvascular properties, including vessel size distribution, hyperpermeability, flow heterogeneity, and possibly also upregulation of endothelial biomarkers. For each MR method, the basic principles, potential acquisition and interpretation pitfalls, solutions, and applications are described. Furthermore, discussion includes current shortcomings and the impact of future developments (eg, higher magnetic field strength systems, targeted macromolecular contrast agents) on the visualization of blood vessel growth and function with contrast-enhanced MR imaging.

Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer

PURPOSE

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) allows noninvasive, in vivo measurements of tissue microvessel perfusion and permeability. We examined whether DCE-MRI done after two cycles of neoadjuvant chemotherapy could predict final clinical and pathologic response in primary breast cancers.

EXPERIMENTAL DESIGN

Thirty-seven patients with primary breast cancer, due to receive six cycles of neoadjuvant 5-fluorouracil, epirubicin and cyclophosphamide chemotherapy, were examined using DCE-MRI before neoadjuvant chemotherapy and after two cycles of treatment. Changes in DCE-MRI kinetic parameters (K(trans), k(ep), v(e), MaxGd, rBV, rBF, MTT) were correlated with the final clinical and pathologic response to neoadjuvant chemotherapy. Test-retest variability was used to determine individual patient response.

RESULTS

Twenty-eight patients were evaluable for response (19 clinical responders and 9 nonresponders; 11 pathologic responders and 17 nonresponders). Changes in the DCE-MRI kinetic parameters K(trans), k(ep), MaxGd, rBV, and rBF were significantly correlated with both final clinical and pathologic response (P < 0.01). Change in K(trans) was the best predictor of pathologic nonresponse (area under the receiver operating characteristic curve, 0.93; sensitivity, 94%; specificity, 82%), correctly identifying 94% of nonresponders and 73% of responders. Change in MRI-derived tumor size did not predict for pathologic response.

CONCLUSION

Changes in breast tumor microvessel functionality as depicted by DCE-MRI early on after starting anthracycline-based neoadjuvant chemotherapy can predict final clinical and pathologic response. The ability to identify nonresponders early may allow the selection of patients who may benefit from a therapy change.

Semiquantitative assessment of MR imaging in prediction of efficacy of gonadotropin-releasing hormone agonist for volume reduction of uterine leiomyoma: initial experience

PURPOSE

To prospectively determine if semiquantitative assessment of R2* images and T1-weighted magnetic resonance (MR) images of leiomyomas correlates with the efficacy of gonadotropin-releasing hormone (GnRH) agonist treatment for volume reduction.

MATERIALS AND METHODS

Internal review board approval and informed consent were obtained for this study. Twenty women (mean age, 36.3 years) with intramyometrial leiomyomas were enrolled in this study. Single-section double-echo dynamic MR imaging was performed before GnRH agonist administration. T2-weighted images were obtained before and after two or three GnRH agonist injections (1.88 mg leuprorelin acetate). The steepest signal intensity (SI) upslope on T1-weighted images and the area under the curve (AUC) on R2* images were determined by using a 16 x 16-voxel matrix that was placed in the center of a leiomyoma. Pearson correlation analysis was performed to compare the percentage of volume reduction with SI upslope and AUC. Unpaired t test was performed to evaluate the difference between leiomyomas with AUC and SI upslope values that were less than or greater than the mean.

RESULTS

Percentage of volume reduction ranged from 6.2% to 51.1%. The mean AUC and mean SI upslope were 39.2 and 9.83% per second, respectively. There was a significant correlation between the AUC and the percentage of volume reduction (r = 0.81, P < .001), although no significant correlation was observed between the SI upslope and the percentage of volume reduction. A significant difference in percentage of volume reduction was observed in leiomyomas by using mean AUC as a cutoff value (P = .003).

CONCLUSION

AUC on R2* images correlates with the efficacy of GnRH agonist before initiation of treatment for volume reduction of leiomyoma.

Chapter 7. Molecular imaging of tumor vasculature

Cancer, with more than 10 million new cases a year worldwide, is the third leading cause of death in developed countries. One critical requirement during cancer progression is angiogenesis, the formation of new blood vessels. Structural and functional imaging of tumor vasculature has been studied using various imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound. Molecular imaging, a key component of the 21st-century cancer-patient management strategy, takes advantage of these traditional imaging techniques and introduces molecular probes to determine the expression of indicative molecular markers at different stages of cancer development. In this chapter, we will focus on two tumor vasculature-related targets: integrin alpha(v)beta(3) and vascular endothelial growth factor receptor (VEGFR). For imaging of integrin alpha(v)beta(3) on the tumor vasculature, only nanoparticle-based probes will be discussed. VEGFR imaging will be discussed in depth, and we will give a detailed example of positron emission tomography (PET) imaging of VEGFR expression using radio-labeled VEGF(121) protein. Future clinical translation will be critical for maximum patient benefit from these agents. To achieve this goal, multidisciplinary approaches and cooperative efforts from many individuals, institutions, industries, and organizations are needed to quickly translate multimodality tumor vasculature imaging into multiple facets of cancer patient management.