Influence of scan duration on dynamic contrast -enhanced magnetic resonance imaging pharmacokinetic parameters for brain lesions

OBJECTIVE

Gadolinium-based contrast agent needs time to leak into the extravascular-extracellular space, leak back into the vascular space, and reach an equilibrium state. For this reason, acquisition times of <10 min may cause inaccurate estimation of pharmacokinetic parameters. Since no studies have been conducted on the influence of long scan times on DCE-MRI parameters in brain tumors, the aim of this study is to investigate the variation of DCE-MRI-derived kinetic parameters as a function of acquisition time, from 5 to 10 min in brain tumors.

MATERIALS AND METHODS

Fifty-two patients with histologically confirmed brain tumors were enrolled in this retrospective study, and examination at 3 T, DCE-MRI, with scan duration of 10 min, was used for retrospective generation of 6 sets of quantitative DCE-MRI maps (Ktrans, Ve and Kep) from 5 to 10 min. Features were extracted from the DCE-MRI maps in contrast enhancement (CE) volumes. Kruskal-Wallis with post-hoc correction and coefficient of variation (CoV) were used as statistical test to compare DCE-MRI maps obtained from 6 data sets.

SIGNIFICANCE

p < 0.05.

RESULTS

No differences in Ktrans features in CE volumes between different scan durations. Ve, Kep features in CE volumes were influenced by different data length. The highest number of significantly different Ve and Kep features in CE volumes were between 5 min and 10 min (p < 0.013), 5 min and 9 min (p < 0.044), 6 min and 10 min (p < 0.040). CoV of Kep was reduced from 5 min to 10 min, going from highly variable (CoV = 0.70) to mildly variable (CoV = 0.42).

CONCLUSION

Kep and Ve were time-dependent in brain tumors, so a longer scan time is needed to obtain reliable parameter values. Ktrans was found to be time-independent, as it remains the same in all 6 acquisition times and is the only reliable parameter with short acquisition times.

High-temporal resolution DCE-MRI improves assessment of intra- and peri-breast lesions categorized as BI-RADS 4

BACKGROUND

BI-RADS 4 breast lesions are suspicious for malignancy with a range from 2 to 95%, indicating that numerous benign lesions are unnecessarily biopsied. Thus, we aimed to investigate whether high-temporal-resolution dynamic contrast-enhanced MRI (H_DCE-MRI) would be superior to conventional low-temporal-resolution DCE-MRI (L_DCE-MRI) in the diagnosis of BI-RADS 4 breast lesions.

METHODS

This single-center study was approved by the IRB. From April 2015 to June 2017, patients with breast lesions were prospectively included and randomly assigned to undergo either H_DCE-MRI, including 27 phases, or L_DCE-MRI, including 7 phases. Patients with BI-RADS 4 lesions were diagnosed by the senior radiologist in this study. Using a two-compartment extended Tofts model and a three-dimensional volume of interest, several pharmacokinetic parameters reflecting hemodynamics, including K^trans, K_ep, V_e, and V_p, were obtained from the intralesional, perilesional and background parenchymal enhancement areas, which were labeled the Lesion, Peri and BPE areas, respectively. Models were developed based on hemodynamic parameters, and the performance of these models in discriminating between benign and malignant lesions was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

A total of 140 patients were included in the study and underwent H_DCE-MRI (n = 62) or L_DCE-MRI (n = 78) scans; 56 of these 140 patients had BI-RADS 4 lesions. Some pharmacokinetic parameters from H_DCE-MRI (Lesion_K^trans, K_ep, and V_p; Peri_K^trans, K_ep, and V_p) and from L_DCE-MRI (Lesion_K_ep, Peri_V_p, BPE_K^trans and BPE_V_p) were significantly different between benign and malignant breast lesions (P < 0.01). ROC analysis showed that Lesion_K^trans (AUC = 0.866), Lesion_K_ep (AUC = 0.929), Lesion_V_p (AUC = 0.872), Peri_K^trans (AUC = 0.733), Peri_K_ep (AUC = 0.810), and Peri_V_p (AUC = 0.857) in the H_DCE-MRI group had good discrimination performance. Parameters from the BPE area showed no differentiating ability in the H_DCE-MRI group. Lesion_K_ep (AUC = 0.767), Peri_V_p (AUC = 0.726), and BPE_K^trans and BPE_V_p (AUC = 0.687 and 0.707) could differentiate between benign and malignant breast lesions in the L_DCE-MRI group. The models were compared with the senior radiologist's assessment for the identification of BI-RADS 4 breast lesions. The AUC, sensitivity and specificity of Lesion_K_ep (0.963, 100.0%, and 88.9%, respectively) in the H_DCE-MRI group were significantly higher than those of the same parameter in the L_DCE-MRI group (0.663, 69.6% and 75.0%, respectively) for the assessment of BI-RADS 4 breast lesions. The DeLong test was conducted, and there was a significant difference only between Lesion_K_ep in the H_DCE-MRI group and the senior radiologist (P = 0.04).

CONCLUSIONS

Pharmacokinetic parameters (K^trans, K_ep and V_p) from the intralesional and perilesional regions on high-temporal-resolution DCE-MRI, especially the intralesional K_ep parameter, can improve the assessment of benign and malignant BI-RADS 4 breast lesions to avoid unnecessary biopsy.

Ktrans Calculation Using Reference Method Corrected Native T10 for Breast Cancer Diagnosis

Purpose

The objective of the study is to use multiple tube phantoms to generate correction factor at different spatial locations for each breast coil cuff to correct the native T10 value in the corresponding spatial location of the breast lesion. The corrected T10 value was used to compute Ktrans and analyze its diagnostic accuracy in the classification of target condition, i.e., breast tumors into malignant and benign.

Materials and Methods

Both in vitro phantom study (external reference) and patient's studies were acquired on simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) Biograph molecular magnetic resonance (mMR) system using 4 channel mMR breast coil. The spatial correction factors derived using multiple tube phantom were used for a retrospective analysis of dynamic contrast-enhanced (DCE) MRI data of 39 patients with a mean age of 50 years (31-77 years) having 51 enhancing breast lesions.

Results

Corrected and non-corrected receiver operating characteristic (ROC) curve analysis revealed a mean Ktrans value of 0.64 min-1 and 0.60 min-1, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy for non-corrected data were 86.21%, 81.82%, 86.20%, 81.81%, and 84.31%, respectively, and for corrected data were 93.10%, 86.36%, 90%, 90.47%, and 90.20% respectively. The area under curve (AUC) of corrected data was improved to 0.959 (95% confidence interval [CI] 0.862-0.994) from 0.824 (95% CI 0.694-0.918) of non-corrected data, and for NPV, it was improved to 90.47% from 81.81%, respectively.

Conclusion

T10 values were normalized using multiple tube phantom which was used for computation of Ktrans. We found significant improvement in the diagnostic accuracy of corrected Ktrans values that results in better characterization of breast lesions.

Use of Multiple-Tube Phantom: A Method to Globally Correct Native T1 Relaxation Time Inhomogeneity in Dedicated Molecular Magnetic Resonance Breast Coil

Background:

Native T1 relaxation time (T1₀) presents an important prerequisite to reliably quantify pharmacokinetic parameter like K^trans (volume transfer constant). Native T1 value can be varied because of the inhomogeneity in the breast coil, thus influencing the K^trans measurement.

Purpose:

The current study aims to design and use a phantom with multiple tubes for both breast cuffs to assess native T1 inhomogeneity across the dedicated molecular magnetic resonance (mMR) breast coil and adopt corrective method to spatially normalize T1 values to improve homogeneity.

Materials and Methods:

Two phantoms with multiple tubes (19 tubes) specially designed and filled with contrast medium with known T1 value were placed in each mMR breast coil cuff. Native T1 at various spatial locations was calculated applying dual flip angle sequence. Correction factors were derived at various spatial locations as a function of deviation of the native T1 value from phantom and applied to correct the native T1 relaxation time.

Results:

A statistically significant difference between native T1 values of the right and left anterior (P = 0.0095), middle (P = 0.0081), and posterior (P = 0.0004) parts of the breast coil. No significant difference was seen in the corrected T1 values between anterior (P = 0.402), middle (P = 0.305), and posterior (P = 0.349) aspects of both sides of the breast coil.

Conclusion:

Inhomogeneity in the native T1 value exists in dedicated mMR breast coil, and significant improvement can be achieved using specially designed external phantom with multiple tubes.

Spatiotemporal Flexible Sparse Reconstruction for Rapid Dynamic Contrast-enhanced MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a tissue perfusion imaging technique. Some versatile free-breathing DCE-MRI techniques combining compressed sensing (CS) and parallel imaging with golden-angle radial sampling have been developed to improve motion robustness with high spatial and temporal resolution. These methods have demonstrated good diagnostic performance in clinical setting, but the reconstruction quality will degrade at high acceleration rates and overall reconstruction time remains long. In this paper, we proposed a new parallel CS reconstruction model for DCE-MRI that enforces flexible weighted sparse constraint along both spatial and temporal dimensions. Weights were introduced to flexibly adjust the importance of time and space sparsity, and we derived a fast-thresholding algorithm which was proven to be simple and efficient for solving the proposed reconstruction model. Results on both the brain tumor DCE and liver DCE show that, at relatively high acceleration factor of fast sampling, lowest reconstruction error and highest image structural similarity are obtained by the proposed method. Besides, the proposed method achieves faster reconstruction for liver datasets and better physiological measures are also obtained on tumor images.

Feasibility study of dual parametric 2D histogram analysis of breast lesions with dynamic contrast-enhanced and diffusion-weighted MRI

Background

This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions.

Methods

This study included 116 patients with 72 malignant and 44 benign breast lesions who underwent CAIPIRINHA-Dixon-TWIST-VIBE dynamic contrast-enhanced (CDT-VIBE DCE) and readout-segmented diffusion-weighted magnetic resonance examination. The volume of interest (VOI), which encompassed the entire lesion, was segmented from the last phase of DCE images. For each VOI, a 1D histogram analysis (mean, median, 10th percentile, 90th percentile, kurtosis and skewness) was performed on apparent diffusion coefficient (ADC) and volume transfer constant (Ktrans) maps; a 2D histogram image (Ktrans-ADC) was generated from the pixelwise aligned maps, and its kurtosis and skewness were calculated. Each parameter was correlated with pathological results using the Mann–Whitney test and receiver operating characteristic curve analysis.

Results

For the Ktrans histogram, the area under the curve (AUC) of the mean, median, 90th percentile and kurtosis had statistically diagnostic values (mean: 0.760; median: 0.661; 90th percentile: 0.781; and kurtosis: 0.620). For the ADC histogram, the AUC of the mean, median, 10th percentile, skewness and kurtosis had statistically diagnostic values (mean: 0.661; median: 0.677; 10th percentile: 0.656; skewness: 0.664; and kurtosis: 0.620). For the 2D Ktrans-ADC histogram, the skewness and kurtosis had statistically higher diagnostic values (skewness: 0.831, kurtosis: 0.828) than those of the 1D histogram (all P < 0.05).

Conclusions

The dual-parametric 2D histogram analysis revealed better diagnostic accuracy for breast lesions than single parametric histogram analysis of either Ktrans or ADC maps.

Dynamic contrast-enhanced MRI versus 18F-FDG PET/CT: Which is better in differentiation between malignant and benign solitary pulmonary nodules?

Objective

To prospectively compare the discriminative capacity of dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) with that of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) in the differentiation of malignant and benign solitary pulmonary nodules (SPNs).

Methods

Forty-nine patients with SPNs were included in this prospective study. Thirty-two of the patients had malignant SPNs, while the other 17 had benign SPNs. All these patients underwent DCE-MRI and ¹⁸F-FDG PET/CT examinations. The quantitative MRI pharmacokinetic parameters, including the trans-endothelial transfer constant (K^trans), redistribution rate constant (K_ep), and fractional volume (V_e), were calculated using the Extended-Tofts Linear two-compartment model. The ¹⁸F-FDG PET/CT parameter, maximum standardized uptake value (SUV_max), was also measured. Spearman's correlations were calculated between the MRI pharmacokinetic parameters and the SUV_max of each SPN. These parameters were statistically compared between the malignant and benign nodules. Receiver operating characteristic (ROC) analyses were used to compare the diagnostic capability between the DCE-MRI and ¹⁸F-FDG PET/CT indexes.

Results

Positive correlations were found between K^trans and SUV_max, and between K_ep and SUV_max (P<0.05). There were significant differences between the malignant and benign nodules in terms of the K^trans, K_ep and SUV_max values (P<0.05). The areas under the ROC curve (AUC) of K^trans, K_ep and SUV_max between the malignant and benign nodules were 0.909, 0.838 and 0.759, respectively. The sensitivity and specificity in differentiating malignant from benign SPNs were 90.6% and 82.4% for K^trans; 87.5% and 76.5% for K_ep; and 75.0% and 70.6% for SUV_max, respectively. The sensitivity and specificity of K^trans and K_ep were higher than those of SUV_max, but there was no significant difference between them (P>0.05).

Conclusions

DCE-MRI can be used to differentiate between benign and malignant SPNs and has the advantage of being radiation free.

Perfusion Parameters on Breast Dynamic Contrast-Enhanced MRI Are Associated With Disease-Specific Survival in Patients With Triple-Negative Breast Cancer

OBJECTIVE

The aim of this study was to investigate the association between perfusion parameters on MRI performed before treatment and survival outcome (disease-free survival [DFS], disease-specific survival [DSS]) in patients with triple-negative breast cancer (TNBC).

MATERIALS AND METHODS

Sixty-one patients (median age, 50 years; age range, 27-77 years) with TNBC (tumor size on MRI: median, 25.5 mm; range, 11.0-142.0 mm) were included. We analyzed clinical and pathologic variables and MRI parameters. Cox proportional hazards models were used to determine associations with survival outcome.

RESULTS

The median follow-up time was 46.1 months (range, 13.9-58.4 months). Eleven of 61 (18.0%) patients had events (i.e., local, regional, or distant recurrence or contralateral breast cancer) and seven (11.5%) died of breast cancer. Among the pretreatment variables, a larger tumor size on MR images (hazard ratio [HR] = 1.024, p = 0.003) was associated with worse DFS at univariate analysis. In multivariate pretreatment models for DSS, a higher fractional volume of extravascular extracellular space per unit volume of tissue (v_e) value (HR = 1.658, p = 0.038), higher peak enhancement (HR = 1.843, p = 0.018), and a larger tumor size on MR images (HR = 1.060, p = 0.001) were associated with worse DSS. In multivariate posttreatment models, a larger pathologic tumor size (HR for DFS, 1.074 [p = 0.005]; HR for DSS, 1.050 [p = 0.042]) and metastasis in surgically resected axillary lymph nodes (HR for DFS, 5.789 [p = 0.017]; HR for DSS, 23.717 [p = 0.005]) were associated with worse survival outcome.

CONCLUSION

A higher v_e value, higher peak enhancement, and larger tumor size of the primary tumor on pretreatment MRI were independent predictors of worse DSS in patients with TNBC.

Role of pharmacokinetic parameters derived with high temporal resolution DCE MRI using simultaneous PET/MRI system in breast cancer: A feasibility study

PURPOSE

To evaluate the reliability of pharmacokinetic parameters like K^trans, Kep and v_e derived through DCE MRI breast protocol using 3T Simultaneous PET/MRI (3Tesla Positron Emission Tomography/Magnetic Resonance Imaging) system in distinguishing benign and malignant lesions.

MATERIALS AND METHODS

High temporal resolution DCE (Dynamic Contrast Enhancement) MRI performed as routine breast MRI for diagnosis or as a part of PET/MRI for cancer staging using a 3T simultaneous PET/MRI system in 98 women having 109 breast lesions were analyzed for calculation of pharmacokinetic parameters (K^trans, v_e, and Kep) at 60s time point using an in-house developed computation scheme.

RESULTS

Receiver operating characteristic (ROC) curve analysis revealed a cut off value for K^trans, Kep, v_e as 0.50, 2.59, 0.15 respectively which reliably distinguished benign and malignant breast lesions. Data analysis revealed an overall accuracy of 94.50%, 79.82% and 87.16% for K^trans, Kep, v_e respectively. Introduction of native T1 normalization with an externally placed phantom showed a higher accuracy (94.50%) than without native T1 normalization (93.50%) with an increase in specificity of 87% vs 84%.

CONCLUSION

Overall the results indicate that reliable measurement of pharmacokinetic parameters with reduced acquisition time is feasible in a 3TMRI embedded PET/MRI system with reasonable accuracy and application may be extended to exploit the potential of simultaneous PET/MRI in further work on breast cancer.

Mathematical Models of Contrast Transport Kinetics for Cancer Diagnostic Imaging: A Review

Angiogenesis plays a fundamental role in cancer growth and the formation of metastasis. Novel cancer therapies aimed at inhibiting angiogenic processes and/or disrupting angiogenic tumor vasculature are currently being developed and clinically tested. The need for earlier and improved cancer diagnosis, and for early evaluation and monitoring of therapeutic response to angiogenic treatment, have led to the development of several imaging methods for in vivo noninvasive assessment of angiogenesis. The combination of dynamic contrast-enhanced imaging with mathematical modeling of the contrast agent kinetics enables quantitative assessment of the structural and functional changes in the microvasculature that are associated with tumor angiogenesis. In this paper, we review quantitative imaging of angiogenesis with dynamic contrast-enhanced magnetic resonance imaging, computed tomography, and ultrasound.

The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge

Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as K^trans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and v_e (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T₁ were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of K^trans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in K^trans than v_e and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, k_ep (= K^trans/v_e), was less sensitive to AIF variation than K^trans (wCV for unadjusted AIFs: 0.45 for k_epvs. 0.74 for K^trans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than K^trans.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.