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PURPOSE: We propose a novel methodology to integrate morphological and functional information of tumor-associated vessels to assist in the diagnosis of suspicious breast lesions. THEORY AND METHODS: Ultrafast, fast, and high spatial resolution DCE-MRI data were acquired on 15 patients with suspicious breast lesions. Segmentation of the vasculature from the surrounding tissue was performed by applying a Hessian filter to the enhanced image to generate a map of the probability for each voxel to belong to a vessel. Summary measures were generated for vascular morphology, as well as the inputs and outputs of vessels physically connected to the tumor. The ultrafast DCE-MRI data was analyzed by a modified Tofts model to estimate the bolus arrival time, Ktrans (volume transfer coefficient), and vp (plasma volume fraction). The measures were compared between malignant and benign lesions via the Wilcoxon test, and then incorporated into a logistic ridge regression model to assess their combined diagnostic ability. RESULTS: A total of 24 lesions were included in the study (13 malignant and 11 benign). The vessel count, Ktrans , and vp showed significant difference between malignant and benign lesions (P = 0.009, 0.034, and 0.010, area under curve [AUC] = 0.76, 0.63, and 0.70, respectively). The best multivariate logistic regression model for differentiation included the vessel count and bolus arrival time (AUC = 0.91). CONCLUSION: This study provides preliminary evidence that combining quantitative characterization of morphological and functional features of breast vasculature may provide an accurate means to diagnose breast cancer.
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Neoplasias de la Mama/irrigación sanguínea , Neoplasias de la Mama/diagnóstico por imagen , Mama/diagnóstico por imagen , Imagen por Resonancia Magnética , Adulto , Anciano , Área Bajo la Curva , Medios de Contraste , Femenino , Humanos , Aumento de la Imagen , Interpretación de Imagen Asistida por Computador/métodos , Procesamiento de Imagen Asistido por Computador , Imagenología Tridimensional , Modelos Logísticos , Microcirculación , Persona de Mediana Edad , Análisis Multivariante , Curva ROC , Análisis de Regresión , Factores de TiempoRESUMEN
OBJECTIVE: The purpose of this study was to validate a kinetic assessment based on visually identified peak enhancement, which is routinely used in clinical practice, for differentiating benign from malignant lesions during fast dynamic contrast-enhanced MRI. MATERIALS AND METHODS: Between January 2015 and December 2016, 90 consecutively registered patients with 105 breast lesions (40 benign, 65 malignant) underwent dynamic contrast-enhanced 1.5-T MRI that included one unenhanced and eight contrast-enhanced fast temporal resolution (10 seconds) whole-breast acquisitions. Histogram analysis was performed to measure the voxel-based enhancement of the entire lesion to obtain 90th, 75th, and 50th percentile values at each time point and to generate kinetic curves. Two observers selected visually identified peak enhancement within the lesions to generate the kinetic curves. The kinetic curves from histogram and visually identified peak enhancement analyses were fitted by means of an empiric mathematic model (EMM): ΔS(t) = A × (1 - e-αt), where A is the upper limit of signal intensity, e indicates the exponential function, and α (min-1) is the rate of increase in signal intensity. The initial slope of the kinetic curve (A × α) and the initial AUC (AUC30) were calculated. These parameters were compared between benign and malignant lesions, and results from visually identified peak enhancement analysis were compared with those from histogram analysis. RESULTS: Benign lesions were successfully differentiated from malignant lesions in both visually identified peak enhancement and histogram analyses (90th and 75th percentile values) on the basis of α, A × α, and AUC30 from the EMM. There was no significant difference in ROC AUC in these EMM parameters between visually identified peak enhancement and histogram analyses (p = 0.21). CONCLUSION: Kinetic assessment with visually identified peak enhancement was acceptable for differentiating benign from malignant lesions.
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Neoplasias de la Mama/patología , Interpretación de Imagen Asistida por Computador/métodos , Imagen por Resonancia Magnética/métodos , Adolescente , Adulto , Anciano , Biopsia , Medios de Contraste , Diagnóstico Diferencial , Femenino , Humanos , Persona de Mediana Edad , Estudios RetrospectivosRESUMEN
PURPOSE: To develop a method for mapping the B1 field using a reference signal from a tissue with known T1. METHODS: Flip angle correction factors were calculated in a region with a known "gold standard" T1; by comparing T1 values from a variable flip angle (VFA) sequence to the "gold standard" and correcting the value of the Ernst angle. The resulting partial B1 map was interpolated for all other regions. In the breast, fat is an ideal reference tissue because its T1 is spatially homogeneous and interpatient variability is low. This method was tested with scans of phantoms and patients (n = 4) on a 3T magnet. The performance of the method was evaluated by comparing the results of VFA T1 mapping with and without B1 correction to inversion recovery (IR) T1 maps. RESULTS: Phantom data determined that a linear inverse distance weighted interpolation accurately recovered the full B1 map. Use of interpolated maps to correct the VFA data in vivo, reduced the average difference in the T1 of parenchyma between VFA and IR results from 58% to 8%. CONCLUSION: This proof-of-principle study showed that it is possible to recover a full and accurate map of the B1 field in the breast by using a reference tissue (fat) with an accurately measured T1.
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Mama/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador/métodos , Imagen por Resonancia Magnética/métodos , Adulto , Algoritmos , Femenino , Humanos , Persona de Mediana Edad , Fantasmas de Imagen , Adulto JovenAsunto(s)
Neoplasias de la Mama , Neoplasias de la Mama Triple Negativas , Protocolos de Quimioterapia Combinada Antineoplásica , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/tratamiento farmacológico , Quimioterapia Adyuvante , Femenino , Humanos , Imagen por Resonancia Magnética , Terapia Neoadyuvante , Resultado del Tratamiento , Neoplasias de la Mama Triple Negativas/diagnóstico por imagen , Neoplasias de la Mama Triple Negativas/tratamiento farmacológico , Carga TumoralRESUMEN
OBJECTIVE: The purposes of this study were to evaluate diagnostic parameters measured with ultrafast MRI acquisition and with standard acquisition and to compare diagnostic utility for differentiating benign from malignant lesions. MATERIALS AND METHODS: Ultrafast acquisition is a high-temporal-resolution (7 seconds) imaging technique for obtaining 3D whole-breast images. The dynamic contrast-enhanced 3-T MRI protocol consists of an unenhanced standard and an ultrafast acquisition that includes eight contrast-enhanced ultrafast images and four standard images. Retrospective assessment was performed for 60 patients with 33 malignant and 29 benign lesions. A computer-aided detection system was used to obtain initial enhancement rate and signal enhancement ratio (SER) by means of identification of a voxel showing the highest signal intensity in the first phase of standard imaging. From the same voxel, the enhancement rate at each time point of the ultrafast acquisition and the AUC of the kinetic curve from zero to each time point of ultrafast imaging were obtained. RESULTS: There was a statistically significant difference between benign and malignant lesions in enhancement rate and kinetic AUC for ultrafast imaging and also in initial enhancement rate and SER for standard imaging. ROC analysis showed no significant differences between enhancement rate in ultrafast imaging and SER or initial enhancement rate in standard imaging. CONCLUSION: Ultrafast imaging is useful for discriminating benign from malignant lesions. The differential utility of ultrafast imaging is comparable to that of standard kinetic assessment in a shorter study time.
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Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Aumento de la Imagen/métodos , Interpretación de Imagen Asistida por Computador/métodos , Imagen por Resonancia Magnética/métodos , Adulto , Anciano , Medios de Contraste/farmacocinética , Diagnóstico Diferencial , Femenino , Humanos , Imagenología Tridimensional , Meglumina/análogos & derivados , Meglumina/farmacocinética , Persona de Mediana Edad , Compuestos Organometálicos/farmacocinética , Estudios RetrospectivosRESUMEN
OBJECTIVES: To quantify kinetic heterogeneity of breast masses that were initially detected with dynamic contrast-enhanced MRI, using whole-lesion kinetic distribution data obtained from computer-aided evaluation (CAE), and to compare that with standard kinetic curve analysis. METHODS: Clinical MR images from 2006 to 2011 with breast masses initially detected with MRI were evaluated with CAE. The relative frequencies of six kinetic patterns (medium-persistent, medium-plateau, medium-washout, rapid-persistent, rapid-plateau, rapid-washout) within the entire lesion were used to calculate kinetic entropy (KE), a quantitative measure of enhancement pattern heterogeneity. Initial uptake (IU) and signal enhancement ratio (SER) were obtained from the most-suspicious kinetic curve. Mann-Whitney U test and ROC analysis were conducted for differentiation of malignant and benign masses. RESULTS: Forty benign and 37 malignant masses comprised the case set. IU and SER were not significantly different between malignant and benign masses, whereas KE was significantly greater for malignant than benign masses (p = 0.748, p = 0.083, and p < 0.0001, respectively). Areas under ROC curve for IU, SER, and KE were 0.479, 0.615, and 0.662, respectively. CONCLUSION: Quantification of kinetic heterogeneity of whole-lesion time-curve data with KE has the potential to improve differentiation of malignant from benign breast masses on breast MRI. KEY POINTS: ⢠Kinetic heterogeneity can be quantified by computer-aided evaluation of breast MRI ⢠Kinetic entropy was greater in malignant masses than benign masses ⢠Kinetic entropy has the potential to improve differentiation of breast masses.
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Neoplasias de la Mama/patología , Neoplasias de la Mama/fisiopatología , Medios de Contraste , Entropía , Femenino , Humanos , Interpretación de Imagen Asistida por Computador/métodos , Cinética , Imagen por Resonancia Magnética/métodos , Persona de Mediana Edad , Curva ROC , Estudios Retrospectivos , Estadísticas no ParamétricasRESUMEN
Purpose: Validation of quantitative imaging biomarkers is a challenging task, due to the difficulty in measuring the ground truth of the target biological process. A digital phantom-based framework is established to systematically validate the quantitative characterization of tumor-associated vascular morphology and hemodynamics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Approach: A digital phantom is employed to provide a ground-truth vascular system within which 45 synthetic tumors are simulated. Morphological analysis is performed on high-spatial resolution DCE-MRI data (spatial/temporal resolution = 30 to 300 µm/60 s) to determine the accuracy of locating the arterial inputs of tumor-associated vessels (TAVs). Hemodynamic analysis is then performed on the combination of high-spatial resolution and high-temporal resolution (spatial/temporal resolution = 60 to 300 µm/1 to 10 s) DCE-MRI data, determining the accuracy of estimating tumor-associated blood pressure, vascular extraction rate, interstitial pressure, and interstitial flow velocity. Results: The observed effects of acquisition settings demonstrate that, when optimizing the DCE-MRI protocol for the morphological analysis, increasing the spatial resolution is helpful but not necessary, as the location and arterial input of TAVs can be recovered with high accuracy even with the lowest investigated spatial resolution. When optimizing the DCE-MRI protocol for hemodynamic analysis, increasing the spatial resolution of the images used for vessel segmentation is essential, and the spatial and temporal resolutions of the images used for the kinetic parameter fitting require simultaneous optimization. Conclusion: An in silico validation framework was generated to systematically quantify the effects of image acquisition settings on the ability to accurately estimate tumor-associated characteristics.
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The high spatial and temporal resolution of dynamic contrast-enhanced MRI (DCE-MRI) can improve the diagnostic accuracy of breast cancer screening in patients who have dense breasts or are at high risk of breast cancer. However, the spatiotemporal resolution of DCE-MRI is limited by technical issues in clinical practice. Our earlier work demonstrated the use of image reconstruction with enhancement-constrained acceleration (ECA) to increase temporal resolution. ECA exploits the correlation in k-space between successive image acquisitions. Because of this correlation, and due to the very sparse enhancement at early times after contrast media injection, we can reconstruct images from highly under-sampled k-space data. Our previous results showed that ECA reconstruction at 0.25 seconds per image (4 Hz) can estimate bolus arrival time (BAT) and initial enhancement slope (iSlope) more accurately than a standard inverse fast Fourier transform (IFFT) when k-space data is sampled following a Cartesian based sampling trajectory with adequate signal-to-noise ratio (SNR). In this follow-up study, we investigated the effect of different Cartesian based sampling trajectories, SNRs and acceleration rates on the performance of ECA reconstruction in estimating contrast media kinetics in lesions (BAT, iSlope and Ktrans) and in arteries (Peak signal intensity of first pass, time to peak, and BAT). We further validated ECA reconstruction with a flow phantom experiment. Our results show that ECA reconstruction of k-space data acquired with 'Under-sampling with Repeated Advancing Phase' (UnWRAP) trajectories with an acceleration factor of 14, and temporal resolution of 0.5 s/image and high SNR (SNR ≥ 30 dB, noise standard deviation (std) < 3%) ensures minor errors (5% or 1 s error) in lesion kinetics. Medium SNR (SNR ≥ 20 dB, noise std ≤ 10%) was needed to accurately measure arterial enhancement kinetics. Our results also suggest that accelerated temporal resolution with ECA with 0.5 s/image is practical.
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Neoplasias de la Mama , Imagen por Resonancia Magnética , Femenino , Humanos , Mama/diagnóstico por imagen , Neoplasias de la Mama/diagnóstico por imagen , Medios de Contraste/farmacocinética , Estudios de Seguimiento , Aumento de la Imagen/métodos , Imagen por Resonancia Magnética/métodosRESUMEN
PURPOSE: To assess whether measurement of the bilateral asymmetry of semiquantitative and quantitative perfusion parameters from ultrafast dynamic contrast-enhanced MRI (DCE-MRI), allows early prediction of pathologic response after neoadjuvant chemotherapy (NAC) in patients with HER2+ breast cancer. MATERIALS AND METHODS: Twenty-eight female patients with HER2+ breast cancer treated with NAC who underwent pre-NAC ultrafast DCE-MRI (3-9 s/phase) were enrolled for this study. Four semiquantitative and two quantitative parenchymal parameters were calculated for each patient. Ipsilateral/contralateral (I/C) ratio (for four parameters) and the difference between (for two parameters) ipsi- and contra-lateral parenchymal kinetic parameters (kBPE) were compared for patients with pathologic complete response (pCR) and those having residual disease. Lasso regression with leave-one-out cross validation was used to determine the optimal combination of parameters for a regression model and multivariable logistic regression was used to identify independent predictors for pCR. Chi-squared test, two-sided t-test and Kruskal-Wallis test were used. RESULTS: The Ktrans I/C ratio cutoff value of 1.11 had a sensitivity of 83.3% and specificity of 75% for pCR. The ve I/C ratio cutoff value of 1.1 had a sensitivity of 75% and specificity of 81.3% for pCR. The area under the receiver operating characteristic curve of the three-kBPE parameter model, including initial area under the enhancement curve (AUC30) I/C ratio, KtransI/C ratio and ve I/C ratio, was 0.89 with sensitivity of 91.7% at specificity of 81.3%. CONCLUSION: Quantitative assessment of bilateral asymmetry kBPE from pre-NAC ultrafast DCE-MRI can predict pCR in patients with HER2+ breast cancer.
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OBJECTIVE: This study establishes a fluid dynamics model personalized with patient-specific imaging data to optimize neoadjuvant therapy (i.e., doxorubicin) protocols for breast cancers. METHODS: Ten patients recruited at the University of Chicago were included in this study. Quantitative dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging data are leveraged to estimate patient-specific hemodynamic properties, which are then used to constrain the mechanism-based drug delivery model. Then, computer simulations of this model yield the subsequent drug distribution throughout the breast. By systematically varying the dosing schedule, we identify an optimized regimen for each patient using the maximum safe therapeutic duration (MSTD), which is a metric balancing treatment efficacy and toxicity. RESULTS: With an individually optimized dose (range = 12.11-15.11 mg/m2 per injection), a 3-week regimen consisting of a uniform daily injection significantly outperforms all other scheduling strategies (P < 0.001). In particular, the optimal protocol is predicted to significantly outperform the standard protocol (P < 0.001), improving the MSTD by an average factor of 9.93 (range = 6.63 to 14.17). CONCLUSION: A clinical-mathematical framework was developed by integrating quantitative MRI data, advanced image processing, and computational fluid dynamics to predict the efficacy and toxicity of neoadjuvant therapy protocols, thus enabling the rational identification of an optimal therapeutic regimen on a patient-specific basis. SIGNIFICANCE: Our clinical-computational approach has the potential to enable optimization of therapeutic regimens on a patient-specific basis and provide guidance for prospective clinical trials aimed at refining neoadjuvant therapy protocols for breast cancers.
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Neoplasias de la Mama , Terapia Neoadyuvante , Humanos , Femenino , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/patología , Hidrodinámica , Estudios Prospectivos , Doxorrubicina/uso terapéutico , Resultado del TratamientoRESUMEN
RATIONALE AND OBJECTIVES: To determine whether kinetics measured with ultrafast dynamic contrast-enhanced magnetic resonance imaging in tumor and normal parenchyma pre- and post-neoadjuvant therapy (NAT) can predict the response of breast cancer to NAT. MATERIALS AND METHODS: Twenty-four patients with histologically confirmed invasive breast cancer were enrolled. They were scanned with ultrafast dynamic contrast-enhanced magnetic resonance imaging (3-7 seconds/frame) pre- and post-NAT. Four kinetic parameters were calculated in the segmented tumors, and ipsi- and contra-lateral normal parenchyma: (1) tumor (tSE30) or background parenchymal relative enhancement at 30 seconds (BPE30), (2) maximum relative enhancement slope (MaxSlope), (3) bolus arrival time (BAT), and (4) area under relative signal enhancement curve for the initial 30 seconds (AUC30). The tumor kinetics and the differences between ipsi- and contra-lateral parenchymal kinetics were compared for patients achieving pathologic complete response (pCR) vs those who had residual disease after NAT. The chi-squared test and two-sided t-test were used for baseline demographics. The Wilcoxon rank sum test and one-way analysis of variance were used for differential responses to therapy. RESULTS: Patients with similar pre-NAT mean BPE30, median BAT and mean AUC30 in the ipsi- and contralateral normal parenchyma were more likely to achieve pCR following NAT (p < 0.02). Patients classified as having residual cancer burden (RCB) II after NAT showed higher post-NAT tSE30 and tumor AUC30 and higher post-NAT MaxSlope in ipsilateral normal parenchyma compared to those classified as RCB I or pCR (p < 0.05). CONCLUSION: Bilateral asymmetry in normal parenchyma could predict treatment outcome prior to NAT. Post-NAT tumor kinetics could evaluate the aggressiveness of residual tumor.
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Neoplasias de la Mama , Mama/patología , Neoplasias de la Mama/diagnóstico por imagen , Neoplasias de la Mama/patología , Neoplasias de la Mama/terapia , Medios de Contraste , Femenino , Humanos , Cinética , Imagen por Resonancia Magnética/métodos , Terapia Neoadyuvante , Estudios RetrospectivosRESUMEN
In patients with dense breasts or at high risk of breast cancer, dynamic contrast enhanced MRI (DCE-MRI) is a highly sensitive diagnostic tool. However, its specificity is highly variable and sometimes low; quantitative measurements of contrast uptake parameters may improve specificity and mitigate this issue. To improve diagnostic accuracy, data need to be captured at high spatial and temporal resolution. While many methods exist to accelerate MRI temporal resolution, not all are optimized to capture breast DCE-MRI dynamics. We propose a novel, flexible, and powerful framework for the reconstruction of highly-undersampled DCE-MRI data: enhancement-constrained acceleration (ECA). Enhancement-constrained acceleration uses an assumption of smooth enhancement at small time-scale to estimate points of smooth enhancement curves in small time intervals at each voxel. This method is tested in silico with physiologically realistic virtual phantoms, simulating state-of-the-art ultrafast acquisitions at 3.5s temporal resolution reconstructed at 0.25s temporal resolution (demo code available here). Virtual phantoms were developed from real patient data and parametrized in continuous time with arterial input function (AIF) models and lesion enhancement functions. Enhancement-constrained acceleration was compared to standard ultrafast reconstruction in estimating the bolus arrival time and initial slope of enhancement from reconstructed images. We found that the ECA method reconstructed images at 0.25s temporal resolution with no significant loss in image fidelity, a 4x reduction in the error of bolus arrival time estimation in lesions (p < 0.01) and 11x error reduction in blood vessels (p < 0.01). Our results suggest that ECA is a powerful and versatile tool for breast DCE-MRI.
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Algoritmos , Neoplasias de la Mama/diagnóstico , Mama/patología , Medios de Contraste , Aumento de la Imagen/métodos , Imagen por Resonancia Magnética/métodos , Fantasmas de Imagen , Simulación por Computador , Femenino , Humanos , Interpretación de Imagen Asistida por ComputadorRESUMEN
Quantitative evaluation of an image processing method to perform as designed is central to both its utility and its ability to guide the data acquisition process. Unfortunately, these tasks can be quite challenging due to the difficulty of experimentally obtaining the "ground truth" data to which the output of a given processing method must be compared. One way to address this issue is via "digital phantoms", which are numerical models that provide known biophysical properties of a particular object of interest. In this contribution, we propose an in silico validation framework for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition and analysis methods that employs a novel dynamic digital phantom. The phantom provides a spatiotemporally-resolved representation of blood-interstitial flow and contrast agent delivery, where the former is solved by a 1D-3D coupled computational fluid dynamic system, and the latter described by an advection-diffusion equation. Furthermore, we establish a virtual simulator which takes as input the digital phantom, and produces realistic DCE-MRI data with controllable acquisition parameters. We assess the performance of a simulated standard-of-care acquisition (Protocol A) by its ability to generate contrast-enhanced MR images that separate vasculature from surrounding tissue, as measured by the contrast-to-noise ratio (CNR). We find that the CNR significantly decreases as the spatial resolution (SRA, where the subscript indicates Protocol A) or signal-to-noise ratio (SNRA) decreases. Specifically, with an SNRA / SRA = 75 dB / 30 µm, the median CNR is 77.30, whereas an SNRA / SRA = 5 dB / 300 µm reduces the CNR to 6.40. Additionally, we assess the performance of simulated ultra-fast acquisition (Protocol B) by its ability to generate DCE-MR images that capture contrast agent pharmacokinetics, as measured by error in the signal-enhancement ratio (SER) compared to ground truth (PESER). We find that PESER significantly decreases the as temporal resolution (TRB) increases. Similar results are reported for the effects of spatial resolution and signal-to-noise ratio on PESER. For example, with an SNRB / SRB / TRB = 5 dB / 300 µm / 10 s, the median PESER is 21.00%, whereas an SNRB / SRB / TRB = 75 dB / 60 µm / 1 s, yields a median PESER of 0.90%. These results indicate that our in silico framework can generate virtual MR images that capture effects of acquisition parameters on the ability of generated images to capture morphological or pharmacokinetic features. This validation framework is not only useful for investigations of perfusion-based MRI techniques, but also for the systematic evaluation and optimization new MRI acquisition, reconstruction, and image processing techniques.
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Medios de Contraste , Imagen por Resonancia Magnética , Simulación por Computador , Humanos , Procesamiento de Imagen Asistido por Computador , Fantasmas de ImagenRESUMEN
There are increasing concerns regarding intracellular accumulation of gadolinium (Gd) after multiple dynamic contrast enhanced (DCE) MRI scans. We investigated whether a low dose (LD) of Gd-based contrast agent is as effective as a high dose (HD) for quantitative analysis of DCE-MRI data, and evaluated the use of a split dose protocol to obtain new diagnostic parameters. Female C3H mice (n = 6) were injected with mammary carcinoma cells in the hind leg. MRI experiments were performed on 9.4 T scanner. DCE-MRI data were acquired with 1.5 s temporal resolution before and after a LD (0.04 mmol/kg), then again after 30 min followed by a HD (0.2 mmol/kg) bolus injection of Omniscan. The standard Tofts model was used to extract physiological parameters (Ktrans and ve) with the arterial input function derived from muscle reference tissue. In addition, an empirical mathematical model was used to characterize maximum contrast agent uptake (A), contrast agent uptake rate (α) and washout rate (ß and γ). There were moderate to strong correlations (r = 0.69-0.97, p < 0001) for parameters Ktrans, ve, A, α and ß from LD versus HD data. On average, tumor parameters obtained from LD data were significantly larger (p < 0.05) than those from HD data. The parameter ratios, Ktrans, ve, A and α calculated from the LD data divided by the HD data, were all significantly larger than 1.0 (p < 0.003) for tumor. T2* changes following contrast agent injection affected parameters calculated from HD data, but this was not the case for LD data. The results suggest that quantitative analysis of LD data may be at least as effective for cancer characterization as quantitative analysis of HD data. In addition, the combination of parameters from two different doses may provide useful diagnostic information.
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Medios de Contraste , Neoplasias , Animales , Modelos Animales de Enfermedad , Femenino , Aumento de la Imagen , Imagen por Resonancia Magnética , Ratones , Ratones Endogámicos C3HRESUMEN
The overall goal of this study is to employ quantitative magnetic resonance imaging (MRI) data to constrain a patient-specific, computational fluid dynamics (CFD) model of blood flow and interstitial transport in breast cancer. We develop image processing methodologies to generate tumor-related vasculature-interstitium geometry and realistic material properties, using dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted MRI (DW-MRI) data. These data are used to constrain CFD simulations for determining the tumor-associated blood supply and interstitial transport characteristics unique to each patient. We then perform a proof-of-principle statistical comparison between these hemodynamic characteristics in 11 malignant and 5 benign lesions from 12 patients. Significant differences between groups (i.e., malignant versus benign) were observed for the median of tumor-associated interstitial flow velocity ( P = 0.028 ), and the ranges of tumor-associated blood pressure (P = 0.016) and vascular extraction rate (P = 0.040). The implication is that malignant lesions tend to have larger magnitude of interstitial flow velocity, and higher heterogeneity in blood pressure and vascular extraction rate. Multivariable logistic models based on combinations of these hemodynamic data achieved excellent differentiation between malignant and benign lesions with an area under the receiver operator characteristic curve of 1.0, sensitivity of 1.0, and specificity of 1.0. This image-based model system is a fundamentally new way to map flow and pressure fields related to breast tumors using only non-invasive, clinically available imaging data and established laws of fluid mechanics. Furthermore, the results provide preliminary evidence for this methodology's utility for the quantitative characterization of breast cancer.
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Neoplasias de la Mama , Mama/diagnóstico por imagen , Neoplasias de la Mama/diagnóstico por imagen , Medios de Contraste , Imagen de Difusión por Resonancia Magnética , Femenino , Hemodinámica , Humanos , Hidrodinámica , Imagen por Resonancia Magnética , Curva ROC , Estudios Retrospectivos , Sensibilidad y EspecificidadRESUMEN
OBJECTIVES: To compare a low-dose dynamic contrast-enhanced breast MRI protocol (LITE MRI) to standard-dosage using a dual-dose injection technique. METHODS: 8 females with a total of 10 lesions with imaging features compatible with fibroadenoma were imaged using a dual-dose dynamic contrast-enhanced-MRI (DCE-MRI) technique. After pre-contrast scans, 15% of a standard dose of contrast was administered; approximately 10 min later, the remaining 85% of the standard dose was administered. Enhancement kinetic parameters, conspicuity and signal-to-noise ratio were measured quantitatively. RESULTS: One lesion showed no enhancement in either DCE series. All nine of the enhancing lesions were visualized in both the low-dose and standard-dose images. While the (low-to-standard) ratio of contrast doses was roughly 0.18, this did not match the ratios of kinetic parameters. Lesion conspicuity and enhancement rate were both higher in the low-dose images, with (low-to-standard) ratios 1.5 ± 0.1 and 1.2 ± 0.4, respectively. The upper limit of enhancement (ratio 0.3 ± 0.1) and signal-to-noise ratio (ratio 0.5 ± 0.1) were higher in the standard-dose images, but less than expected based on the ratio of the doses. CONCLUSIONS: This preliminary study demonstrates that LITE MRI has the potential to match standard DCE-MRI in the detection of enhancing lesions. Additionally, LITE MRI may enhance sensitivity to contrast media dynamics. ADVANCES IN KNOWLEDGE: Lower doses of MRI contrast media may be equally effective in the detection of breast lesions, and increase sensitivity to contrast media dynamics. LITE MRI may help increase screening compliance and long-term patient safety.
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Neoplasias de la Mama/diagnóstico , Fibroadenoma/diagnóstico , Adolescente , Adulto , Medios de Contraste/administración & dosificación , Medios de Contraste/farmacocinética , Relación Dosis-Respuesta a Droga , Femenino , Gadolinio/administración & dosificación , Gadolinio/farmacocinética , Humanos , Imagen por Resonancia Magnética/métodos , Persona de Mediana Edad , Relación Señal-Ruido , Adulto JovenRESUMEN
The Tofts pharmacokinetic model requires multiple calculations for analysis of dynamic contrast enhanced (DCE) MRI. In addition, the Tofts model may not be appropriate for the prostate. This can result in error propagation that reduces the accuracy of pharmacokinetic measurements. In this study, we present a compact solution allowing estimation of physiological parameters K trans and v e from ultrafast DCE acquisitions, without fitting DCE-MRI data to the standard Tofts pharmacokinetic model. Since the standard Tofts model can be simplified to the Patlak model at early times when contrast efflux from the extravascular extracellular space back to plasma is negligible, K trans can be solved explicitly for a specific time. Further, v e can be estimated directly from the late steady-state signal using the derivative form of Tofts model. Ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The contrast media concentration as function of time was calculated over each ROI using gradient echo signal equation with pre-contrast tissue T1 values, and using the 'reference tissue' model with a linear approximation. There was strong correlation (r = 0.88-0.91, pâ < 0.0001) between K trans extracted from the Tofts model and K trans estimated from the compact solution for prostate cancer and normal tissue. Additionally, there was moderate correlation (r = 0.65-0.73, pâ < 0.0001) between extracted versus estimated v e. Bland-Altman analysis showed moderate to good agreement between physiological parameters extracted from the Tofts model and those estimated from the compact solution with absolute bias less than 0.20 min-1 and 0.10 for K trans and v e, respectively. The compact solution may decrease systematic errors and error propagation, and could increase the efficiency of clinical workflow. The compact solution requires high temporal resolution DCE-MRI due to the need to adequately sample the early phase of contrast media uptake.
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Imagen por Resonancia Magnética/métodos , Neoplasias de la Próstata/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética/normas , Masculino , Persona de Mediana Edad , Reproducibilidad de los ResultadosRESUMEN
RATIONALE AND OBJECTIVES: To evaluate whether parameters from empirical mathematical model (EMM) for ultrafast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) correlate with histological microvessel density (MVD) in invasive breast cancer. MATERIALS AND METHODS: Ninety-eight consecutive patients with invasive breast cancer underwent an institutional review board-approved ultrafast DCE-MRI including a pre- and 18 postcontrast whole breast ultrafast scans (3 seconds) followed by four standard scans (60 seconds) using a 3T system. Region of interest was placed within each lesion where the highest signal increase was observed on ultrafast DCE-MRI, and the increase rate of enhancement was calculated as follows: ΔSâ¯=â¯(SIpost - SIpre)/SIpre. The kinetic curve obtained from ultrafast DCE-MRI was analyzed using a truncated EMM: ΔS(t)â¯=â¯A(1â¯-â¯e-αt), where A is the upper limit of the signal intensity, α (min-1) is the rate of signal increase. The initial slope of the kinetic curve is given by Aα. Initial area under curve (AUC30) and time of initial enhancement was calculated. From the standard DCE-MRI, the initial enhancement rate (IER) and the signal enhancement ratio (SER) were calculated as follows: IERâ¯=â¯(SIearlyâ¯-â¯SIpre)/SIpre, SERâ¯=â¯(SIearlyâ¯-â¯SIpre)/(SIdelayedâ¯-â¯SIpre). The parameters were compared to MVD obtained from surgical specimens. RESULTS: A, α, Aα, AUC30, and time of initial enhancement significantly correlated with MVD (râ¯=â¯0.29, 0.40, 0.51, 0.43, and -0.32 with p = 0.0027, p < 0.0001, p < 0.0001, p < 0.0001, and p = 0.0012, respectively), whereas IER and SER from standard DCE-MRI did not. CONCLUSION: The parameters of the EMM, especially the initial slope or Aα, for ultrafast DCE-MRI correlated with MVD in invasive breast cancer.
Asunto(s)
Neoplasias de la Mama/diagnóstico por imagen , Medios de Contraste , Aumento de la Imagen/métodos , Interpretación de Imagen Asistida por Computador/métodos , Imagen por Resonancia Magnética/métodos , Microvasos/diagnóstico por imagen , Adulto , Anciano , Anciano de 80 o más Años , Mama/diagnóstico por imagen , Mama/patología , Neoplasias de la Mama/patología , Femenino , Humanos , Cinética , Persona de Mediana Edad , Modelos Teóricos , Reproducibilidad de los Resultados , Estudios RetrospectivosRESUMEN
PURPOSE: To increase diagnostic accuracy of breast MRI by increasing temporal resolution and more accurately sampling the early kinetics of contrast media uptake. We tested the feasibility of accelerating bilateral breast DCE-MRI by reducing the FOV, allowing aliasing, and unfolding the resulting images. METHODS: Previous experience with an "ultrafast" protocol for bilateral breast DCE-MRI (6-10 s temporal resolution) showed that the number of significantly enhancing voxels is very low in the first 30-45 s after contrast media injection. This suggests that overlap of enhancing voxels in aliased images will be very infrequent. Therefore, aliased images can be acquired during the first 30-45 s after contrast media injection and unfolded to produce full-FOV images with few errors. In a proof-of-principle test, aliased images were simulated from the first 30 s of full-FOV acquisitions. Cases with relatively dense early enhancement were selected to test this method in a worst-case scenario. In an initial test, an FOV of 60% the size of the full FOV was simulated. To reduce the probability of errors due to overlapping voxels in aliased images, we then tested a dynamic FOV approach. The FOV was progressively increased so that enhancing voxels could not overlap at multiple time-points, and areas where enhancing voxels overlapped at a given time-point could be unfolded by interpolating between the preceding and subsequent time-points (acquired with different FOVs). The simulated FOV sizes for each of the time-points were 31%, 44%, and 77% of the full FOV. Subtraction images (post- minus precontrast) were generated for aliased images and filtered to select significantly enhancing voxels. Comparison of early, highly aliased images, with later, less aliased images then helped to identify the true locations of enhancing voxels. RESULTS: In the initial aliasing simulations, an average of 2.9% of the enhancing voxels above the chest wall overlapped in the aliased images (range 0.1%-6.7%). The similarity between simulated unfolded images and the correct full-FOV images, evaluated using CW-SSIM (complex wavelet similarity index), was 0.50 ± 0.26, 0.76 ± 0.09, and 0.80 ± 0.10 for the first, second, and third time-point, respectively (numbers closer to 1 indicate more similar images). For the dynamic FOV tests, an average of 11% of the enhancing voxels above the chest wall overlapped (range 0%-40%) due to greater aliasing at early time-points. Despite more voxels overlapping, the CW-SSIM values for the data acquired with dynamic FOVs were 0.64 ± 0.25, 0.93 ± 0.04, and 0.97 ± 0.02 for the first, second, and third time-points, respectively. CONCLUSIONS: Dynamic FOV imaging allows accelerated bilateral breast DCE-MRI during the early contrast media uptake phase. This method relies on the sparsity of enhancement at the early phases of DCE-MRI of the breast. The results of simulations suggest that dynamic FOV imaging and unfolding produces images that are very close to fully sampled images, and allows temporal resolution as high as 2 s per image.