Dynamic Contrast-enhanced MRI Studies Research Articles

Abstract PO2-01-01: Biophysical simulation using DCE-MRI to forecast response to NAT in HER2+ patients, with glucose characterization and orthogonal validation using FDG-PET

Abstract Background: Metabolic reprogramming and tumor angiogenesis are two tightly linked hallmarks of cancer. Regions of high metabolic activity within a tumor can become hypoxic or nutrient starved, eliciting a cascade of pro-angiogenic signals that can lead to increased tumor perfusion and in turn greater metabolic activity. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and 18Fluorodeoxyglucose (FDG) positron emission tomography (PET) are two imaging methods commonly used in the diagnosis of cancer; the former can be also used to identify the perfusion of the tumor microenvironment (TME) and the latter provides a coarse readout of glucose metabolic activity. Here, we are presented with a unique cohort of patients who underwent DCE-MRI, 18FDG-PET and 64Cu-DOTA-Traztuzumab offering potential to perform a pilot analysis. First, we characterize the performance of our perfusion model SimBioSys- Microvasculature (SBS-MV) through a stability analysis, as well as comparison with two PET modalities. Finally, we use this model in 3D simulations of individual HER2+ breast cancer patients to forecast responses to neoadjuvant chemotherapy (NAT). Methods: SBS-MV is a modified Tofts model for pharmacokinetic modeling of DCE-MRI data, utilizing a tissue segmentation model developed in-house to inform parameter fits and ensure that the derived parameters fall within acceptable values on a tissue-by-tissue level, in addition its function for standard fitting of DCE time-course data. We first evaluated the stability of the SBS-MV model by analyzing a separate cohort of 10 patients who underwent ultrafast DCE-MRI. Temporal undersampling was performed on the original high temporal resolution data to mimic low temporal resolution from standard-of-care (SoC) DCE studies. Both datasets were processed with SBS-MV model. Next, we analyzed data from a cohort of 18 patients, each of whom underwent a pre-NAT SoC DCE-MRI study, a mid-treatment FDG PET/CT study, and a mid-treatment 64Cu-DOTA-Trastuzumab/CT study during treatment. Tissue segmentation and SBS-MV fits were performed on the pre-NAT DCE MRI. Tightly cropped boxes encompassing the tumor in the 3D SBS-MV volumes as well as the PET volumes were created. Using these identified regions, all summary statistics were calculated and cross-correlated between imaging modalities. Results: SBS-MV was stable to SoC-mimicking temporally undersampled ultrafast DCE MRI series, demonstrating relatively little variability in the output parameters (a voxel wise median deviation of approximately 0.005 min-1 ). Further, we demonstrate that SBS-MV parameters (Ktrans, ve) are correlated with FDG SUVSA and 64Cu SUVSA. In addition, the glucose concentrations used in the biophysical simulations were correlated with FDG SUVSA, indicating that downstream applications of the SBS-MV models still carry this information about perfusion. Finally, using SBS-MV, our biophysical simulations of HER2-targeted therapy accurately predict patient response. In this small cohort, our biophysical simulation platform performed well, yielding predictive accuracy of 0.83, with sensitivity and specificity of 0.83 and 0.83, respectively. These performance metrics are in line with previously published reports. Conclusion: Our MV model is capable of extracting biologically meaningful perfusion parameters from standard clinical DCE MRI time series, providing the same benefits of a comprehensive kinetic analysis, without impacting current clinical workflow. This approach could be used in both the research and clinical settings, offering actionable information on what drives individual patient therapeutic response for a more personalized care. Citation Format: John Whitman, Vikram Adhikarla, Russell Rockne, Lusine Tumyan, Joanne Mortimer, Wei Huang, Joseph Peterson, Dorys Lopez-Ramos, John Cole. Biophysical simulation using DCE-MRI to forecast response to NAT in HER2+ patients, with glucose characterization and orthogonal validation using FDG-PET [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-01-01.

A comparative study between the diagnostic performance of contrast-enhanced digital mammography and dynamic contrast-enhanced MRI in invasive lobular carcinoma of the breast

BackgroundInvasive lobular carcinoma is the second most prevalent histological subtype of breast cancer after invasive duct carcinoma, with a reported increased incidence in the last two decades. It often presents with challenging imaging characteristics that lower the sensitivity of mammography in their detection and delineation of their extent. Moreover, an increased risk of having synchronous lesions in the same or opposite breast was reported in cases with invasive lobular carcinoma. This obviates the need for other imaging modalities, specifically contrast-enhanced imaging modalities, to improve early detection as well as allow precise determination of the extent of the disease. Our aim in this study was to compare the diagnostic performance of contrast-enhanced digital mammography and dynamic contrast-enhanced magnetic resonance imaging (MRI) in the local staging of invasive lobular carcinoma regarding the size, extensions, multiplicity and bilaterality.MethodsThis study included 46 female patients with pathologically proven invasive lobular carcinoma. They underwent full-field digital mammography with a complementary ultrasound examination, contrast-enhanced digital mammography, and dynamic contrast-enhanced MRI. The findings encountered by the three imaging modalities were evaluated independently, and the results were compared with final histopathology.ResultsIn the current study, dynamic contrast-enhanced MRI study was the most sensitive modality in the detection of the index lesion, synchronous ipsilateral and contralateral lesions and achieved a sensitivity of 100% in each analysis as compared to contrast-enhanced digital mammography, which achieved a sensitivity of 97.8%, 85.7% and 80%, respectively. Regarding the assessment of the lesion extent to the surroundings, there was a tendency to overestimation by MRI examination.ConclusionsAlthough dynamic contrast-enhanced MRI is the most sensitive imaging modality for detecting the index lesion, multiplicity and bilaterality, contrast-enhanced digital mammography achieved comparable overall accuracy. Regarding the locoregional staging of invasive lobular carcinoma, there was a tendency for relative overestimation by MRI examination.

Abstract A024: DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies

Abstract Background Regions of high metabolic activity within a tumor can increase tumor perfusion. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and 18Fluorodeoxyglucose (FDG) positron emission tomography (PET) are imaging methods used in cancer diagnosis; the former identifies perfusion of the tumor microenvironment and the latter provides a coarse readout of glucose metabolic activity. Here, we perform a pilot analysis in a unique cohort of patients who underwent DCE-MRI, 18FDG-PET and 64Cu-DOTA-Traztuzumab. We characterize the performance of our perfusion model SimBioSys-Microvasculature (SBS-MV). We use this model in 3D simulations of individual HER2+ breast cancer patients to forecast response to neoadjuvant chemotherapy (NAT). Methods SBS-MV is a modified Tofts model for pharmacokinetic modeling of DCE-MRI data, utilizing a tissue segmentation model developed in-house to inform parameter fits and ensure that the derived parameters fall within acceptable values on a tissue-by-tissue level. We evaluated the stability of the SBS-MV model by analyzing a separate cohort of 10 patients who underwent ultrafast DCE-MRI. By undersampling the original high temporal resolution data, we mimicked possible variation in standard-of-care (SoC) DCE studies and accessed the variability of our fits with respect to different subsets. Next, we analyzed data from a different cohort of 18 patients, each of whom underwent a pre-NAT SoC DCE-MRI study, a mid-treatment FDG PET study, and a mid-treatment 64Cu-DOTA-Trastuzumab study during treatment. Tissue segmentation and SBS-MV fits were performed on the pre-NAT DCE-MRI. Tightly cropped boxes encompassing the tumor in the 3D SBS-MV volumes and the PET volumes were created. Using these identified regions, all summary statistics were calculated and cross-correlated between imaging modalities. Results SBS-MV was stable to SoC-mimicking temporally undersampled ultrafast DCE-MRI series, demonstrating relatively little variability in the output parameters (a voxel wise median deviation of approximately 0.005 min−1). Further, we demonstrate that SBS-MV parameters (Ktrans, ve) are correlated with FDG SUVSA and 64Cu SUVSA. The glucose concentrations used in the biophysical simulations, which are derived from SBS-MV fits, were correlated with FDG SUVSA, indicating that downstream applications of the SBS-MV models still carry this perfusion information. Finally, using SBS-MV, our biophysical simulations of HER2-targeted therapy accurately predict patient response. In this small cohort, our biophysical simulations performed well, yielding predictive accuracy of 0.83 (sensitivity=0.83, specificity=0.83). Conclusion Our MV model extracts biologically meaningful perfusion parameters from standard clinical DCE-MRI time series, providing the same benefits of a comprehensive kinetic analysis without impacting clinical workflow. This approach could be used in research and clinical settings, offering actionable information on what drives individual patient therapeutic response for a more personalized care. Citation Format: John Whitman, Vikram Adhikarla, Russell Rockne, Lusine Tumyan, Joanne Mortimer, Wei Huang, Dorys Lopez Ramos, Joseph R. Peterson, John A. Cole. DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A024.

Radiation source personalization for nanoparticle-enhanced radiotherapy using dynamic contrast-enhanced MRI in the treatment planning process

Nanoparticle-enhanced radiotherapy offers the potential to selectively increase the radiation dose imparted to the tumor while at the same time sparing the healthy structures around it. Among the recommendations of an interdisciplinary group for the clinical translation of this treatment modality, is the developing of methods to quantify the effects that the nanoparticle concentration has on the radiation dosimetry and incorporate these effects into the treatment planning process. In this work, using Monte Carlo simulations and dynamic contrast-enhanced MRI images, treatment plans for nanoparticle-enhanced radiotherapy are calculated in order to evaluate the effects that realistic distributions of the nanoparticles have on the resultant plans and to devise treatment strategies to account for these effects, including the selection of the proper x-ray source configuration in terms of energy and collimation. Dynamic contrast-enhanced MRI studies were obtained for two treatment sites, namely brain and breast. A model to convert the MRI signal to contrast agent concentration was applied to each set of images. Two treatment modalities, 3D conformal radiotherapy and Stereotactic Body Radiation Therapy, were evaluated at three different x-ray spectra, namely 6 MV from a linear accelerator, 110 kVp and 220 kVp from a tungsten target. For the breast patient, as the nanoparticle distribution varies markedly with time, the treatment plans were obtained at two different times after administration. It was determined that maximum doses to the healthy structures around the tumor are mostly determined by the minimum nanoparticle concentration in the tumor. The presence of highly hypoxic or necrotic tissue, which fails to accumulate the nanoparticles, or leakage of the contrast agent into the surrounding healthy tissue, make irradiation with conventional conformal radiotherapy unfeasible for kilovoltage beam energies, as the uniform beam apertures lack the ability to compensate for the non-uniform distribution of the nanoparticles. Therefore, proper quantification of the nanoparticle distribution not only in the target volume but also in the surrounding tissues and structures is crucial for the proper planning of nanoparticle-enhanced radiotherapy and a treatment delivery with a high-degree of freedom, such as small-field stereotactic body radiotherapy, should be the method of choice for this treatment modality.

Correlation of Perfusion Metrics with Ki-67 Proliferation Index and Axillary Involvement as a Prognostic Marker in Breast Carcinoma Cases: A Dynamic Contrast-Enhanced Perfusion MRI Study.

Our study aims to reveal clinically helpful prognostic markers using quantitative radiologic data from perfusion magnetic resonance imaging for patients with locally advanced carcinoma, using the Ki-67 index as a surrogate. Patients who received a breast cancer diagnosis and had undergone dynamic contrast-enhanced magnetic resonance imaging of the breast for pretreatment evaluation and follow-up were searched retrospectively. We evaluated the MRI studies for perfusion parameters and various categories and compared them to the Ki-67 index. Axillary involvement was categorized as low (N0-N1) or high (N2-N3) according to clinical stage. A total sum of 60 patients' data was included in this study. Perfusion parameters and Ki-67 showed a significant correlation with the transfer constant (Ktrans) (ρ = 0.554 p = 0.00), reverse transfer constant (Kep) (ρ = 0.454 p = 0.00), and initial area under the gadolinium curve (IAUGC) (ρ = 0.619 p = 0.00). The IAUGC was also significantly different between axillary stage groups (Z = 2.478 p = 0.013). Outside of our primary hypothesis, associations between axillary stage and contrast enhancement (x2 = 8.023 p = 0.046) and filling patterns (x2 = 8.751 p = 0.013) were detected. In conclusion, these parameters are potential prognostic markers in patients with moderate Ki-67 indices, such as those in our study group. The relationship between axillary status and perfusion parameters also has the potential to determine patients who would benefit from limited axillary dissection.

Can the Gleason score be predicted in patients with prostate cancer? A dynamic contrast-enhanced MRI, (68)Ga-PSMA PET/CT, PSA, and PSA-density comparison study.

The present study aims to evaluate whether perfusion parameters in prostate magnetic resonance imaging (MRI), (68)Ga-prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT), prostate-specific antigen (PSA), and PSA density can be used to predict the lesion grade in patients with prostate cancer (PCa). The study included a total of 137 PCa cases in which 12-quadrant transrectal ultrasound-guided prostate biopsy (TRUSBx) was performed, the Gleason score (GS) was determined, and pre-biopsy multiparametric prostate MRI and (68)Ga-PSMA PET/CT examinations were undertaken. The patient population was evaluated in three groups according to the GS: (1) low risk; (2) intermediate risk; (3) high risk. The PSA, PSA density, pre-TRUSBx (68)Ga-PSMA PET/CT maximum standardized uptake value (SUVmax), perfusion MRI parameters [maximum enhancement, maximum relative enhancement, T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1)] were retrospectively evaluated. There was no significant difference between the three groups in relation to the PSA, PSA density, and (68)Ga-PSMA PET/CT SUVmax (P > 0.05). However, the values of maximum enhancement, maximum relative enhancement (%), T0 (s), time to peak (s), wash-in rate (s-1), and wash-out rate (s-1) significantly differed among the groups. A moderate positive correlation was found among the prostate volume, PSA (r = 0.490), and (68)Ga-PSMA SUVmax (r = 0.322) in the patients. The wash-out rate (s-1) and wash-in rate (s-1) had the best diagnostic test performance (area under the curve: 89.1% and 78.4%, respectively). No significant correlation was found between the (68)Ga-PSMA PET/CT SUVmax and the GS. The wash-out rate was more successful in estimating the pretreatment GS than the (68)Ga-PSMA PET/CT SUVmax.

Weakly supervised breast lesion detection in DCE-MRI using self-transfer learning.

Breast cancer is a typically diagnosed and life-threatening cancer in women. Thus, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast lesion detection and diagnosis because of the high resolution of soft tissues. Moreover, supervised detection methods have been implemented for breast lesion detection. However, these methods require substantial time and specialized staff to develop the labeled training samples. To investigate the potential of weakly supervised deep learning models for breast lesion detection. A total of 1003 breast DCE-MRI studies were collected, including 603 abnormal cases with 770 breast lesions and 400 normal subjects. The proposed model was trained using breast DCE-MRI considering only the image-level labels (normal and abnormal) and optimized for classification and detection sub-tasks simultaneously. Ablation experiments were performed to evaluate different convolutional neural network (CNN) backbones (VGG19 and ResNet50) as shared convolutional layers, as well as to evaluate the effect of the preprocessing methods. Our weakly supervised model performed better with VGG19 than with ResNet50 (p < 0.05). The average precision (AP) of the classification sub-task was 91.7% for abnormal cases and 88.0% for normal samples. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.939 (95% confidence interval [CI]: 0.920-0.941). The weakly supervised detection task AP was 85.7%, and the correct location (CorLoc) was 90.2%. A sensitivity of 84.0% at two-false positives per image was assessed based on free-response ROC (FROC) curve. The results confirm that a weakly supervised CNN based on self-transfer learning is an effective and promising auxiliary tool for detecting breast lesions.

A multi-modality medical imaging head and neck phantom: Part 2. Medical imaging

The head and neck phantom discussed in an accompanying paper (part 1), is imaged with MRI, X-ray CT, PET and ultrasound. MRI scans show a distinct image contrast between the brain compartment and other anatomical regions of the head. The silicone matrix that was used to create a porous brain compartment has a relatively high proton density and a spin–spin relaxation time (T2) that is long enough to provide an MRI signal. While the longitudinal magnetization was found to recover according to a mono-exponential, a bi-exponential decay was observed for the transverse relaxation with a slow T2 relaxation component corresponding to the perfusate and a fast T2 relaxation component corresponding to the silicone. The fraction of the slow T2 relaxation component increases upon perfusion. A dynamic contrast enhanced (DCE) MRI experiment is conducted in which the injection rate of the contrast agent is varied. Parametric DCE maps are created and reveal regional differences in contrast agent kinetics as a result of differences in porosity. The skull, vertebra and the brain compartment are clearly visible on X-ray CT. Dynamic PET scanning has been performed while the carotic arterial input function is monitored by use of a Geiger-Müller counter. Similar regions of perfusion are found in the PET study as in the DCE MRI study. By doping the perfusate with a lipid micelle emulsion, the phantom is applicable for carotic Doppler ultrasound demonstration and validation.

Abstract P4-06-02: Clinically feasible pharmacokinetic model of dynamic contrast-enhanced MRI is prognostic of recurrence free survival in breast cancer patients treated with neoadjuvant therapy

Abstract Background Dynamic contrast-enhanced (DCE) MRI is commonly used for diagnosis and treatment planning of cancers. Its main use is the identification of tumors in soft tissues, where the tumor progression-induced angiogenic changes result in leaky vasculature which is readily highlighted by contrast enhancement. While allowing tumor morphology assessment, DCE MRI also contains rich information on perfusion and permeability which can be modeled as a pharmacokinetic (PK) process, a subject of extensive investigation in the clinical research setting. Several breast DCE MRI studies have suggested that PK parameters might be indicative of response to therapy and recurrence. However, these studies rely on high temporal resolution DCE MRI for accurate PK modeling, which presents a hurdle to adoption in clinical settings where DCE MRI is acquired with low temporal resolution. Methods We present a novel two-parameter modeling framework which circumvents this temporal limitation, allowing kinetic parameters to be extracted from clinical DCE MRI containing 3-6 timepoints spaced 60-90 seconds apart. We sought to examine whether these kinetic parameters (hereafter KP1 and KP2) binned into "high" and "low" values had prognostic value in determining disease recurrence. KP1 reflects the rate of leakiness from vessels into extravascular space, while KP2 reflects the rate of the reverse process. A study was conducted with a cohort of 458 breast cancer patients treated with neoadjuvant therapy (NAT) in which 117 recurrences occurred. Model parameters were extracted from pre-treatment clinical DCE MRI with low temporal resolution. Univariate and multivariate (Cox Proportional Hazard; CPH) analyses were performed to test the prognostic value of covariates in predicting recurrence free survival (RFS). Results A CPH model was constructed that included age, receptor status, cancer stage, kinetic parameters, and pathologic complete response (pCR) as covariates (Table 1). KP2 and pCR were statistically significantly prognostic markers of RFS (p&amp;lt;0.05). KP1 was not a significant prognostic marker of RFS (p=0.055). Interestingly, KP2 had a hazard ratio (HR) similar to pCR (HR: -1.04 [-1.75, -0.33]; p&amp;lt;0.0039 vs. HR: -0.97 [-1.5, -0.44], p&amp;lt;0.00034). Using univariate analysis, we investigated whether KP2 was prognostic of recurrence. Patients were stratified by therapy type, whether they achieved pCR or had residual disease (RD), and by disease subtype. KP2 was found to be predictive of RFS for patients with RD after treatment with NAT chemotherapy (p&amp;lt;0.0004, n=241, log-rank test), but not for patients treated with anti-HER2 NAT (p=0.84, n=124) or patients that achieved pCR (p=0.68, n=139). KP2 was also found to be prognostic in Hormone Receptor+/HER2- patients with RD (p&amp;lt;0.012, n=151) and Hormone Receptor-/HER2+ patients treated with NAT chemotherapy (p&amp;lt;0.001, n=64). The parameter was not found to be prognostic in patients with triple-negative disease. Conclusions We developed a new prognostic imaging marker for disease recurrence in breast cancer patients treated with NAT that relies on only pre-treatment standard-of-care, low temporal resolution DCE MRI. Since the marker was found to have similar prognostic value in terms of hazard ratio as pCR, but in patients with RD, it could prove to be a powerful tool in patient management after surgery. Table 1.Results of Cox Proportional Hazard model.FactorHazard Ratio95% CIp-valueAge-0.01[-0.02, 0.01]0.51ER+-0.35[-0.85, 0.15]0.17HER2+0.02[-0.38, 0.41]0.93PR+0.05[-0.46, 0.56]0.85Stage II0.54[-0.62, 1.7]0.36Stage III1.08[-0.1, 2.27]0.074KP1-0.68[-1.38, 0.01]0.055KP2-1.04[-1.75, -0.33]0.0039pCR-0.97[-1.5, -0.44]0.00034 Citation Format: Joseph R Peterson, Tyler M. Earnest, Wei Huang, Hiroyuki Abe, John A Cole, Jr. Clinically feasible pharmacokinetic model of dynamic contrast-enhanced MRI is prognostic of recurrence free survival in breast cancer patients treated with neoadjuvant therapy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-06-02.

Quantitative evaluation of simultaneous spatial and temporal regularization in dynamic contrast-enhanced MRI of the liver using Gd-EOB-DTPA

The purpose of this study was to quantitatively evaluate the usefulness of simultaneous spatial and temporal regularization using total variation (TV), total generalized variation (TGV), a combination of low-rank decomposition (LRD) and TV (LRD+TV), a combination of LRD and TGV (LRD+TGV), and nuclear norm (NN) when applied to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in rats with concanavalin A (ConA)-induced acute hepatic injury.The rats were divided into three groups: normal control (NC) (n = 10), ConA10 (n = 8), and ConA20 (n = 7). Rats in the ConA10 and ConA20 groups were intravenously injected with 10 and 20 mg/kg of ConA, respectively; those in the NC group were intravenously injected with the same volume of saline. DCE-MRI studies were performed using gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA; 0.025 mmol Gd/kg) as a contrast agent (CA), 24 h after the ConA or saline injection. After the DCE-MRI study, we generated zero-filled and undersampled k-space data from the original images using a pseudoradial sampling scheme with 4 to 64 spokes. We subsequently reconstructed images from these data using the above regularizers and calculated the signal-to-error ratio (SERimg) and structural similarity index measure (SSIM) using the original and reconstructed images. We also calculated the area under the curve (AUC), rate of CA washout (λw), maximum relative enhancement (REmax), and time to REmax (Tmax) from time-intensity curves using an empirical mathematical model (EMM) and the signal-to-error ratio for curve fitting (SERfit) from the original and fit curves. We also compared the parameters obtained using the pseudoradial and Cartesian sampling schemes in the NC group.When using LRD+TV and LRD+TGV, both SERimg and SSIM were greater than those for the other regularizers at all spoke numbers studied; the SERfit for TGV was the greatest. When using TGV and LRD+TGV, in the majority of cases the AUCs did not significantly differ from those obtained from the original images, whereas those for LRD+TV and NN were significantly less at several spoke numbers. The λw for NN was significantly greater at numerous spoke numbers in the NC group; the REmax values for LRD+TV and NN were significantly less at several spoke numbers in all groups. The Tmax values for TV, TGV, and LRD+TGV were significantly greater at numerous spoke numbers in the NC group. Although there were significant differences in SERimg and SSIM between the pseudoradial and Cartesian sampling schemes, the kinetic parameters obtained by the EMM did not significantly differ between the two sampling schemes, with certain exceptions.In conclusion, our results suggest that simultaneous spatial and temporal regularization using TGV or LRD+TGV is useful for accelerating DCE-MRI without significant reduction in the accuracy of the kinetic parameter estimation, even at extremely low sampling factors.

Magnetic Resonance-Guided High-Intensity Focused Ultrasound Ablation of Uterine Fibroids-Efficiency Assessment with the Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging and the Potential Role of the Administration of Uterotonic Drugs.

Objective: The assessment of the usefulness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) when qualifying patients with uterine fibroids (UFs) for magnetic resonance-guided high-intensity ultrasound (MR-HIFU). Material and methods: This retrospective, single center study included 283 women who underwent DCE-MRI and were treated with MR-HIFU. The patients were divided according to non-perfused volume (NPV) as well as by the type of curve for patients with a washout curve in the DCE-MRI study and patients without a washout curve. The studied women were assessed in three groups according to the type of uterotonics administered. Group A (57 patients) received one dose of misoprostol/diclofenac transvaginally and group B (71 patients) received oxytocin intravenously prior to the MR-HIFU procedure. The remaining 155 women (group C) were treated with the traditional non-drug enhanced MR-HIFU procedure. Results: The average NPV value was higher in no washout group, and depended on the uterotonics used. Conclusions: We demonstrated a correlation between dynamic contrast enhancement curve types and the therapeutic efficacy of MR-HIFU. Our results suggest that DCE-MRI has the potential to assess treatment outcomes among patients with UFs, and patients with UFs that present with a washout curve may benefit from the use of uterotonic drugs. More studies are required to draw final conclusions.

Effects of k-space orders on the time-intensity curves in dynamic contrast-enhanced magnetic resonance imaging of the breast based on simulation study

PurposeThis study aims to investigate the influence of time-intensity curves (TICs) on the shapes using a dynamic contrast-enhanced magnetic resonance imaging (MRI) study depending on the Cartesian and radial orders for benign and cancerous breast tumors. MethodsBased on kinetic curve parameters, the signal intensities of six concentration gradients comprising two benign and four cancer models were used. The study aimed to construct a dynamic simulated image by creating a digital phantom image according to the following steps: (1) creating a simple numerical phantom, (2) setting the signal intensity in the contrast area, (3) creating the k-space in each time phase, (4) extracting data from k-space in each time phase, (5) filling in the k-space and adding data to the k-space assembly, and (6) creating a magnitude image. The TICs of Cartesian (centric and sequential) and radial (full-length [RFL] and half-length [RHL]) orders were created and sigmoid curve fitting was performed to compare these curves. Maximum slope (MS, s−1), width of the response (WOR, s), and primary signal response (PSR) were then calculated. Phase encode steps were set for 512 and 256. ResultsMS was significantly decreased by radial order in the cancer model. No change was observed in WOR in Cartesian order, whereas RFL and RHL orders increased in the cancer models. PSR increased remarkably in the radial orders of cancer models.The difference in the fill slope in radial orders was remarkable when the TIC was steeper compared with when it was gentle, especially RHL. In WOR, both radial RFL and RHL were well matched except for the one benign model, and the shape of radial TIC was similar to sequential order as compared to centric order in 256 steps. ConclusionThe effects of Cartesian and radial orders on the patterns of TICs in a dynamic contrast-enhanced MRI study of benign and cancerous breast tumors were revealed. Interestingly, the TIC gradient of radial orders became gentler, particularly in the breast cancer MRI.

Mapping of CSF transport using high spatiotemporal resolution dynamic contrast-enhanced MRI in mice: Effect of anesthesia.

Dynamic contrast-enhanced MRI (DCE-MRI) represents the only available approach for glymphatic cerebrospinal fluid (CSF) flow 3D mapping in the brain of living animals and humans. The purpose of this study was to develop a novel DCE-MRI protocol for mapping of the glymphatic system transport with improved spatiotemporal resolution, and to validate the new protocol by comparing the transport in mice anesthetized with either isoflurane or ketamine/xylazine. The contrast agent, gadobutrol, was administered into the CSF of the cisterna magna and its transport visualized continuously on a 9.4T preclinical scanner using 3D fast-imaging with a steady-state free-precession sequence (3D-FISP), which has a spatial resolution of 0.001 mm3 and a temporal resolution of 30 s. The MR signals were measured dynamically for 60 min in multiple volumes of interest covering the entire CSF space and brain parenchyma. The results confirm earlier findings that glymphatic CSF influx is higher under ketamine/xylazine than with isoflurane anesthesia. This was extended to account for new details about the distinct CSF efflux pathways under the two anesthetic regimens. Dynamic contrast MR shows that CSF clearance occurs mainly along the vagus nerve near the jugular vein under isoflurane and via the olfactory bulb under ketamine/xylazine. The improved spatial and temporal sampling rates afforded by 3D-FISP shed new light on the pharmacological modulation of CSF efflux paths. The present observations may have the potential to set a new standard for future experimental DCE-MRI studies of the glymphatic system.

Comparison of DCE-MRI parametric mapping using MP2RAGE and variable flip angle T1 mapping

Quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) measures the rate of transfer of contrast agent from the vascular space to the tissue space by fitting signal-time data to pharmacokinetic models. However, these models are very sensitive to errors in T1 mapping. Accurate T1 mapping is necessary for high quality quantitative DCE-MRI studies. This study compares magnetization prepared rapid (two) gradient echo sequence (MP2RAGE) T1-mapping accuracy to the conventional variable flip angle (VFA) approach, and also determines the effect of the new T1-mapping method on the Ktrans parameter. VFA and MP2RAGE T1 values were compared to the gold standard inverse recovery (IR) method in phantom over manually drawn ROIs. In vivo, ROIs were manually drawn over prostate and prostatic lesions. Average T1 values over ROIs were compared and Ktrans maps for each method were calculated via the extended Tofts model. VFA-T1 maps overestimated T1 values by up to 50% compared to gold standard IR T1 values in phantom. MP2RAGE differed by up to 9%. MP2RAGE-T1 and Ktrans values were significantly different from VFA values over prostatic lesions (p < 0.05). Ktrans was consistently underestimated using VFA compared to MP2RAGE (p < 0.05). MP2RAGE T1 maps are shown to be more accurate, leading to more reliable pharmacokinetic modeling. This can potentially lead to better lesion characterization and improve clinical outcomes.

Meningeal blood-brain barrier disruption in acute traumatic brain injury.

The meninges serve as a functional barrier surrounding the brain, critical to the immune response, and can be compromised following head trauma. Meningeal enhancement can be detected on contrast-enhanced MRI in patients presenting with acute traumatic brain injury, even when head CT is negative. Following head trauma, gadolinium-based contrast appears to extravasate from the vasculature, enhancing the dura within minutes, and later permeates the subarachnoid space. The aims of this study were to characterize the initial kinetics of the uptake of contrast agent after injury and the delayed redistribution of contrast enhancement in the subarachnoid space in hyperacute patients. Neuroimaging was obtained prospectively in two large ongoing observational studies of patients aged 18 years or older presenting to the emergency department with suspected acute head injury. Dynamic contrast-enhanced MRI studies in a cohort of consecutively enrolling patients with mild traumatic brain injury (n = 36) determined that the kinetic half-life of dural-related meningeal enhancement was 1.3 ± 0.6 min (95% enhancement within 6 min). The extravasation of contrast into the subarachnoid space was investigated in a cohort of CT negative mild traumatic brain injury patients initially imaged within 6 h of injury (hyperacute) who subsequently underwent a delayed MRI, with no additional contrast administration, several hours after the initial MRI. Of the 32 patients with delayed post-contrast imaging, 18 (56%) had conspicuous expansion of the contrast enhancement into the subarachnoid space, predominantly along the falx and superior sagittal sinus. Patients negative for traumatic meningeal enhancement on initial hyperacute MRI continued to have no evidence of meningeal enhancement on the delayed MRI. These studies demonstrate that (i) the initial enhancement of the traumatically injured meninges occurs within minutes of contrast injection, suggesting highly permeable meningeal vasculature, and that (ii) contrast in the meninges redistributes within the subarachnoid space over the period of hours, suggesting a compromise in the blood-brain and/or blood-cerebrospinal barriers. Data from the parent study indicate that up to one in two patients with mild traumatic brain injury have traumatic brain injury on acute (<48 h) MRI, with a higher prevalence seen in patients with moderate or severe traumatic brain injury. The current study's findings of traumatic meningeal enhancement and the subsequent delayed extravasation of contrast into the subarachnoid spaces indicate that a substantial percentage of patients with even mild traumatic brain injury may have a transient disruption in barriers separating the vasculature from the brain.

Increase in blood\u2013brain barrier leakage in healthy, older adults

Blood–brain barrier (BBB) breakdown can disrupt nutrient supply and waste removal, which affects neuronal functioning. Currently, dynamic contrast-enhanced (DCE) MRI is the preferred in-vivo method to quantify BBB leakage. Dedicated DCE MRI studies in normal aging individuals are lacking, which could hamper value estimation and interpretation of leakage rate in pathological conditions. Therefore, we applied DCE MRI to investigate the association between BBB disruption and age in a healthy sample. Fifty-seven cognitively and neurologically healthy, middle-aged to older participants (mean age: 66 years, range: 47–91 years) underwent MRI, including DCE MRI with intravenous injection of a gadolinium-based contrast agent. Pharmacokinetic modeling was applied to contrast concentration time-curves to estimate BBB leakage rate in each voxel. Subsequently, leakage rate was calculated in the white and gray matter, and primary (basic sensory and motor functions), secondary (association areas), and tertiary (higher-order cognition) brain regions. A difference in vulnerability to deterioration was expected between these regions, with especially tertiary regions being affected by age. Higher BBB leakage rate was significantly associated with older age in the white and gray matter, and also in tertiary, but not in primary or secondary brain regions. Even in healthy individuals, BBB disruption was stronger in older persons, which suggests BBB disruption is a normal physiologically aging phenomenon. Age-related increase in BBB disruption occurred especially in brain regions most vulnerable to age-related deterioration, which may indicate that BBB disruption is an underlying mechanism of normal age-related decline.Netherlands Trial Register number: NL6358, date of registration: 2017-03-24.

MR guided high intensity focused ultrasound (MRgFUS) for the treatment of oligometastatic prostate cancer bone metastasis.

e17600 Background: With improvements in diagnostic modalities such as functional imaging, oligometastatic prostate cancer is being diagnosed with greater frequency than ever before. Our aim was to determine MRgFUS ability to downstage patients with oligometastatic bone disease with single session of non-invasive metastasis-directed therapy. Methods: The study was designed with intention-to-treat metastatic bone lesions. Patients were enrolled if they had accessible bone metastasis and could safely undergo MRgFUS (InSightec, Israel). Baseline measurable characteristics included dynamic contrast enhanced MRI study (DCE; Gd-BOPTA, Bracco; GE 750 3T magnet) with semiquantitative perfusion analysis, PSA level (ng/ml) and choline PET (SUV). Measurable variables were obtained at treatment time, 3 months, 12 months and 24 months follow-up. Results: 18 patients fulfilled the inclusion criteria and safely underwent MRgFUS procedure of metastatic bone ablations. Lesions were located in the pelvis (11), scapula (3) and long bones (4). At baseline all lesions showed a significant DCE perfusion (highly vascular) with mean perfusion reduction of 88% at 3 months follow-up (CI: 100-50; p &lt; 0.001) stable at subsequent follow-up scans. Similarly PSA levels decreased from a mean baseline of 19 (ng/ml) to 7.1, 2.9 and 2.1, at 3-12 and 24 moths respectively. SUV values showed similar trend with reduction from baseline (mean 8.9 to 3.0, 2.3 and 1.7: p &lt; 0.001). In all patients single MRgFUS session was appropriate without any major or minor adverse events reported. Conclusions: MRgFUS is a totally non-invasive procedure that can obtain complete bone ablation in patients with oligometastatic prostate disease. The technique features a radiation-free approach that can be of incremental value in long-survivor subset on oncological patients, significantly reducing risk of toxic effects. Concurrent chemo regimen is not a contraindication.

Dynamic contrast-enhanced MRI in oncology: how we do it.

Magnetic resonance imaging (MRI) is particularly attractive for clinical application in perfusion imaging thanks to the absence of ionizing radiation and limited volumes of contrast agent (CA) necessary. Dynamic contrast-enhanced MRI (DCE-MRI) involves sequentially acquiring T1-weighted images through an organ of interest during the passage of a bolus administration of CA. It is a particularly flexible approach to perfusion imaging as the signal intensity time course allows not only rapid qualitative assessment, but also quantitative measures of intrinsic perfusion and permeability parameters. We examine aspects of the T1-weighted image series acquisition, CA administration, post-processing that constitute a DCE-MRI study in clinical practice, before considering some heuristics that may aid in interpreting the resulting contrast enhancement time series. While qualitative DCE-MRI has a well-established role in the diagnostic assessment of a range of tumours, and a central role in MR mammography, clinical use of quantitative DCE-MRI remains limited outside of clinical trials. The recent publication of proposals for standardized acquisition and analysis protocols for DCE-MRI by the Quantitative Imaging Biomarker Alliance may be an opportunity to consolidate and advance clinical practice.

Effect of Bias in Contrast Agent Concentration Measurement on Estimated Pharmacokinetic Parameters in Brain Dynamic Contrast-Enhanced Magnetic Resonance Imaging Studies

Introduction: Pharmacokinetic (PK) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely applied in tumor diagnosis and treatment evaluation. Precision analysis of the estimated PK parameters is essential when they are used as a measure for therapy evaluation or treatment planning. In this study, the accuracy of PK parameters in brain DCE-MRI studies was quantified in relation to two major sources of error(including pre-contrast longitudinal-relaxation time, T1,0 and flip angle, α). Material and Methods: 3470 dynamic contrast-enhanced-curves were simulated using a wide variation of the PK parameters. The bias of contrast concentration due to the systematic biases in α and T1,0 was calculated and added to both contrast concentration and AIF profiles. Thereafter, the PK parameters were estimated for each simulated curve in the presence of different percentages of relative biases in α and T1,0. The mean percentage error (MPE) of PK parameters was then calculated for all simulated curves. Results: The results indicated that plasma volume(vp) was the most sensitive parameter to bias of contrast concentration, which may overestimate up to 700% in 10% coincidence relative bias in α and T1,0. The lowest MPE was related to the backward transfer constant (kep), which was ~2%-15% in 10% coincidence relative bias in each α and T1, 0. Conclusion: Utilization of a nested model selection technique, along with an accurate estimator, such as maximum-likelihood estimation, created a unique approach for investigating the effect of the bias in the concentration measurement to the estimated PK parameters without the addition of any extra biases to the parameters during the estimation.

The Influence of Signal to Noise Ratio on the Pharmacokinetic Analysis in DCE-MRI Studies

Purpose: Recruiting the Pharmacokinetic (PK) parameters estimated from non-invasive methods such as Dynamic Contrast Enhanced MRI (DCE-MRI) to evaluate or plan treatment procedure is widely investigated in clinical practices. Interpretation of the DCE-MRI data is highly dependent to precision and accuracy of the estimated parameters. One of the most effective factors on the DCE-MR images and on the contrast concentration profile is the Signal to Noise Ratio (SNR). This work focuses on the analytical evaluation of the noise effect on accuracy of the estimated PK parameters in DCE-MRI studies.&#x0D; Materials and Methods: Tofts model as a popular pharmacokinetic model and model selection technique was used to simulate 3470 time curves of contrast concentration. Maximum likelihood estimator as a minimum variance unbiased estimator was recruited to estimate the PK parameters. Eleven levels of signal to noise ratios (SNR= 5, 8, 10, 13, 15, 20, 25, 30, 35, 50, Noiseless) were added to the simulated CA concentration profiles. The PK parameters were estimated for 11 series data and then Mean Percentage Error (MPE) was calculated for estimated parameters.&#x0D; Results: The results indicate that the most sensitive parameter to the SNR of the DCE-MR images is inverse transfer constant. A SNR greater than 25 was found to ensure a reasonable error (MPE &lt;5%) in all models parameters.&#x0D; Conclusion: Clinical decision based on the DCE-MRI data analysis and estimated PK parameters needs a good image quality (SNR&gt;25), an accurate and robust estimator and correct pharmacokinetic model selection