A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings

Institutional Variability in Ultrafast Breast MR Imaging: Comparing Compressed Sensing and View Sharing Techniques with Different Patient Populations and Contrast Injection Protocols

PURPOSE

To assess the institutional variability in ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI using time-resolved angiography with stochastic trajectories (TWIST)-volumetric interpolated breath-hold examination (VIBE) and compressed sensing (CS)-VIBE sequences acquired at 2 different institutions with different patient populations and contrast injection protocols.

METHODS

UF-DCE MR images of 18 patients from site A acquired using a TWIST-VIBE sequence, and UF-DCE MR images of 18 patients from site B acquired with a CS-VIBE sequence, were retrospectively evaluated and compared. The 2-site patient cohort was matched for patient age, background parenchymal enhancement, malignancy or benignity, and lesion size. Qualitative assessments included noise, blurring, poor fat suppression, aliasing artifact, motion artifact, lesion conspicuity, lesion morphology, time-intensity-curve smoothness, and vessel delineation. For quantitative assessment, the bolus arrival time was evaluated for each lesion, and its diagnostic performance in discriminating between benign and malignant lesions was examined using receiver operating characteristics analysis.

RESULTS

Thirteen malignant and five benign lesions were included from each site. Qualitative evaluation revealed that poor fat suppression and aliasing artifacts were visible in images from site A with TWIST-VIBE (P = 0.004 and P < 0.001), whereas motion artifacts were present in images from site B with CS-VIBE (P = 0.04). Lesion morphology assessments (P < 0.001) and vessel delineation (P < 0.001) were superior for images from site B with CS-VIBE. Bolus arrival time was significantly longer with TWIST-VIBE than with CS-VIBE, for both benign and malignant lesions (P < 0.001). The area under the receiver operating characteristics curve was 0.55 for site A and 0.69 for site B (P = 0.39).

CONCLUSION

Both acquisitions allowed evaluation of breast lesions with good lesion conspicuity and time-intensity-curve smoothness, whereas CS-VIBE was superior to TWIST-VIBE for morphological evaluation of breast lesions and depiction of blood vessels in the breast. Injection rate appears to have a significant impact on semi-quantitative parameters derived from UF-DCE MRI.

Initial experience in implementing quantitative DCE-MRI to predict breast cancer therapy response in a multi-center and multi-vendor platform setting

Quantitative dynamic contrast-enhanced (DCE) MRI as a promising method for the prediction of breast cancer response to neoadjuvant chemotherapy (NAC) has been demonstrated mostly in single-center and single-vendor platform studies. This preliminary study reports the initial experience in implementing quantitative breast DCE-MRI in multi-center (MC) and multi-vendor platform (MP) settings to predict NAC response. MRI data, including B1 mapping, variable flip angle (VFA) measurements of native tissue R1 (R1,0), and DCE-MRI, were acquired during NAC at three sites using 3T systems with Siemens, Philips, and GE platforms, respectively. High spatiotemporal resolution DCE-MRI was performed using similar vendor product sequences with k-space undersampling during acquisition and view sharing during reconstruction. A breast phantom was used for quality assurance/quality control (QA/QC) across sites. The Tofts model (TM) and shutter-speed model (SSM) were used for pharmacokinetic (PK) analysis of the DCE data. Additionally, tumor region of interest (ROI)- vs. voxel-based analyses in combination with the use of VFA-measured R1,0 vs. fixed, literature-reported R1,0 were investigated to determine the optimal analysis approach. Results from 15 patients who completed the study are reported. Voxel-based PK analysis using fixed R1,0 was deemed the optimal approach, which allowed the inclusion of data from one vendor platform where VFA measurements produced ≥100% overestimation of R1,0. The semi-quantitative signal enhancement ratio (SER) and quantitative PK parameters outperformed the tumor longest diameter (LD) in the prediction of pathologic complete response (pCR) vs. non-pCR after the first NAC cycle, whereas Ktrans consistently provided more accurate predictions than both SER and LD after the first NAC cycle and at the NAC midpoint. Both TM and SSM Ktrans and kep were excellent predictors of response at the NAC midpoint with ROC AUC >0.90, while the SSM parameters (AUC ≥0.80) performed better than their TM counterparts (AUC <0.80) after the first NAC cycle. The initial experience of this ongoing study indicates the importance of QA/QC using a phantom and suggests that deploying voxel-based PK analysis using a fixed R1,0 may mitigate random errors from R1,0 measurements across platforms and potentially eliminate the need for B1 and VFA acquisitions in MC and MP trials.

Dynamic Contrast Enhanced MRI Mapping of Vascular Permeability for Evaluation of Breast Cancer Neoadjuvant Chemotherapy Response Using Image-to-Image Conditional Generative Adversarial Networks

Dynamic contrast enhanced (DCE) MRI is a non-invasive imaging technique that has become a quantitative standard for assessing tumor microvascular permeability. Through the application of a pharmacokinetic (PK) model to a series of T1-weighed MR images acquired after an injection of a contrast agent, several vascular permeability parameters can be quantitatively estimated. These parameters, including Ktrans, a measure of capillary permeability, have been widely implemented for assessing tumor vascular function as well as tumor therapeutic response. However, conventional PK modeling for translation of DCE MRI to PK vascular permeability parameter maps is complex and time-consuming for dynamic scans with thousands of pixels per image. In recent years, image-to-image conditional generative adversarial network (cGAN) is emerging as a robust approach in computer vision for complex cross-domain translation tasks. Through a sophisticated adversarial training process between two neural networks, image-to-image cGANs learn to effectively translate images from one domain to another, producing images that are indistinguishable from those in the target domain. In the present study, we have developed a novel image-to-image cGAN approach for mapping DCE MRI data to PK vascular permeability parameter maps. The DCE-to-PK cGAN not only generates high-quality parameter maps that closely resemble the ground truth, but also significantly reduces computation time over 1000-fold. The utility of the cGAN approach to map vascular permeability is validated using open-source breast cancer patient DCE MRI data provided by The Cancer Imaging Archive (TCIA). This data collection includes images and pathological analyses of breast cancer patients acquired before and after the first cycle of neoadjuvant chemotherapy (NACT). Importantly, in good agreement with previous studies leveraging this dataset, the percentage change of vascular permeability Ktrans derived from the DCE-to-PK cGAN enables early prediction of responders to NACT.

Quantitative Perfusion-Weighted Magnetic Resonance Imaging in Uveal Melanoma

Purpose

Perfusion-weighted imaging (PWI; magnetic resonance imaging [MRI]) has been shown to provide valuable biological tumor information in uveal melanoma (UM). Clinically used semiquantitative methods do not account for tumor pigmentation and eye movement. We hypothesize that a quantitative PWI method that incorporates these, provides a more accurate description of tumor perfusion than the current clinical method. The aim of this study was to test this in patients with UM before and after radiotherapy.

Methods

Perfusion-weighted 3T MRIs were retrospectively analyzed in 47 patients with UM before and after radiotherapy. Tofts pharmacokinetic modeling was performed to determine vascular permeability (Ktrans), extracellular extravascular space (ve), and reflux rate (kep). These were compared with semiquantitative clinical parameters including peak intensity and outflow percentage.

Results

The effect of tumor pigmentation on peak intensity and outflow percentage was statistically significant (P < 0.01) and relative peak intensity was significantly different between melanotic and amelanotic tumors (1.5 vs. 1.9, P < 0.01). Before radiotherapy, median tumor Ktrans was 0.63 min-1 (range = 0.06-1.42 min-1), median ve was 0.23 (range = 0.09-0.63), and median kep was 2.3 min-1 (range = 0.6-5.0 min-1). After radiotherapy, 85% showed a decrease in Ktrans and kep (P < 0.01). Changes in tumor pigmentation before and after radiotherapy were small and not significant (median increase in T1 of 33 ms, P = 0.55).

Conclusions

Quantitative PWI parameters decreased significantly after radiotherapy and can therefore can serve as an early biomarker for treatment response assessment. However, due to the nonsignificant changes in tumor pigmentation before and after radiotherapy, the current semiquantitative method appears to be sufficiently sensitive for detection of changes in tumor perfusion.

Magnetic Resonance Perfusion Imaging for Breast Cancer

Breast cancer is the most frequently diagnosed cancer among women worldwide, carrying a significant socioeconomic burden. Breast cancer is a heterogeneous disease with 4 major subtypes identified. Each subtype has unique prognostic factors, risks, treatment responses, and survival rates. Advances in targeted therapies have considerably improved the 5-year survival rates for primary breast cancer patients largely due to widespread screening programs that enable early detection and timely treatment. Imaging techniques are indispensable in diagnosing and managing breast cancer. While mammography is the primary screening tool, MRI plays a significant role when mammography results are inconclusive or in patients with dense breast tissue. MRI has become standard in breast cancer imaging, providing detailed anatomic and functional data, including tumor perfusion and cellularity. A key characteristic of breast tumors is angiogenesis, a biological process that promotes tumor development and growth. Increased angiogenesis in tumors generally indicates poor prognosis and increased risk of metastasis. Dynamic contrast-enhanced (DCE) MRI measures tumor perfusion and serves as an in vivo metric for angiogenesis. DCE-MRI has become the cornerstone of breast MRI, boasting a high negative-predictive value of 89% to 99%, although its specificity can vary. This review presents a thorough overview of magnetic resonance (MR) perfusion imaging in breast cancer, focusing on the role of DCE-MRI in clinical applications and exploring emerging MR perfusion imaging techniques.

Criteria for the translation of radiomics into clinically useful tests

Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structures and processes as captured by medical imaging, interest in such computer-extracted measurements has increased substantially. However, despite the thousands of radiomic studies, the number of settings in which radiomics has been successfully translated into a clinically useful tool or has obtained FDA clearance is comparatively small. This relative dearth might be attributable to factors such as the varying imaging and radiomic feature extraction protocols used from study to study, the numerous potential pitfalls in the analysis of radiomic data, and the lack of studies showing that acting upon a radiomic-based tool leads to a favourable benefit-risk balance for the patient. Several guidelines on specific aspects of radiomic data acquisition and analysis are already available, although a similar roadmap for the overall process of translating radiomics into tools that can be used in clinical care is needed. Herein, we provide 16 criteria for the effective execution of this process in the hopes that they will guide the development of more clinically useful radiomic tests in the future.

Perfusion Maps Acquired From Dynamic Angiography MRI Using Deep Learning Approaches

BACKGROUND

A typical stroke MRI protocol includes perfusion-weighted imaging (PWI) and MR angiography (MRA), requiring a second dose of contrast agent. A deep learning method to acquire both PWI and MRA with single dose can resolve this issue.

PURPOSE

To acquire both PWI and MRA simultaneously using deep learning approaches.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 60 patients (30-73 years old, 31 females) with ischemic symptoms due to occlusion or ≥50% stenosis (measured relative to proximal artery diameter) of the internal carotid artery, middle cerebral artery, or anterior cerebral artery. The 51/1/8 patient data were used as training/validation/test.

FIELD STRENGTH/SEQUENCE

A 3 T, time-resolved angiography with stochastic trajectory (contrast-enhanced MRA) and echo planar imaging (dynamic susceptibility contrast MRI, DSC-MRI).

ASSESSMENT

We investigated eight different U-Net architectures with different encoder/decoder sizes and with/without an adversarial network to generate perfusion maps from contrast-enhanced MRA. Relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), mean transit time (MTT), and time-to-max (T_max ) were mapped from DSC-MRI and used as ground truth to train the networks and to generate the perfusion maps from the contrast-enhanced MRA input.

STATISTICAL TESTS

Normalized root mean square error, structural similarity (SSIM), peak signal-to-noise ratio (pSNR), DICE, and FID scores were calculated between the perfusion maps from DSC-MRI and contrast-enhanced MRA. One-tailed t-test was performed to check the significance of the improvements between networks. P values < 0.05 were considered significant.

RESULTS

The four perfusion maps were successfully extracted using the deep learning networks. U-net with multiple decoders and enhanced encoders showed the best performance (pSNR 24.7 ± 3.2 and SSIM 0.89 ± 0.08 for rCBV). DICE score in hypo-perfused area showed strong agreement between the generated perfusion maps and the ground truth (highest DICE: 0.95 ± 0.04).

DATA CONCLUSION

With the proposed approach, dynamic angiography MRI may provide vessel architecture and perfusion-relevant parameters simultaneously from a single scan.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 5.

Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging to predict lymphovascular invasion and survival outcome in breast cancer

BACKGROUND

Lymphovascular invasion (LVI) predicts a poor outcome of breast cancer (BC), but LVI can only be postoperatively diagnosed by histopathology. We aimed to determine whether quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can preoperatively predict LVI and clinical outcome of BC patients.

METHODS

A total of 189 consecutive BC patients who underwent multiparametric MRI scans were retrospectively evaluated. Quantitative (K^trans, V_e, K_ep) and semiquantitative DCE-MRI parameters (W_- in, W_- out, TTP), and clinicopathological features were compared between LVI-positive and LVI-negative groups. All variables were calculated by using univariate logistic regression analysis to determine the predictors for LVI. Multivariate logistic regression was used to build a combined-predicted model for LVI-positive status. Receiver operating characteristic (ROC) curves evaluated the diagnostic efficiency of the model and Kaplan-Meier curves showed the relationships with the clinical outcomes. Multivariate analyses with a Cox proportional hazard model were used to analyze the hazard ratio (HR) for recurrence-free survival (RFS) and overall survival (OS).

RESULTS

LVI-positive patients had a higher K_ep value than LVI-negative patients (0.92 ± 0.30 vs. 0.81 ± 0.23, P = 0.012). N2 stage [odds ratio (OR) = 3.75, P = 0.018], N3 stage (OR = 4.28, P = 0.044), and K_ep value (OR = 5.52, P = 0.016) were associated with LVI positivity. The combined-predicted LVI model that incorporated the N stage and K_ep yielded an accuracy of 0.735 and a specificity of 0.801. The median RFS was significantly different between the LVI-positive and LVI-negative groups (31.5 vs. 34.0 months, P = 0.010) and between the combined-predicted LVI-positive and LVI-negative groups (31.8 vs. 32.0 months, P = 0.007). The median OS was not significantly different between the LVI-positive and LVI-negative groups (41.5 vs. 44.0 months, P = 0.270) and between the combined-predicted LVI-positive and LVI-negative groups (42.8 vs. 43.5 months, P = 0.970). LVI status (HR = 2.40), N2 (HR = 3.35), and the combined-predicted LVI model (HR = 1.61) were independently associated with disease recurrence.

CONCLUSION

The quantitative parameter of K_ep could predict LVI. LVI status, N stage, and the combined-predicted LVI model were predictors of a poor RFS but not OS.

Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study

INTRODUCTION

Breast cancer patients treated with neoadjuvant chemotherapy (NACT) are at risk of recurrence depending on clinicopathological characteristics. This preliminary study aimed to investigate the predictive performances of quantitative dynamic contrast-enhanced (DCE) MRI parameters, alone and in combination with clinicopathological variables, for prediction of recurrence in patients treated with NACT.

METHODS

Forty-seven patients underwent pre- and post-NACT MRI exams including high spatiotemporal resolution DCE-MRI. The Shutter-Speed model was employed to perform pharmacokinetic analysis of the DCE-MRI data and estimate the Ktrans, ve, kep, and τi parameters. Univariable logistic regression was used to assess predictive accuracy for recurrence for each MRI metric, while Firth logistic regression was used to evaluate predictive performances for models with multi-clinicopathological variables and in combination with a single MRI metric or the first principal components of all MRI metrics.

RESULTS

Pre- and post-NACT DCE-MRI parameters performed better than tumor size measurement in prediction of recurrence, whether alone or in combination with clinicopathological variables. Combining post-NACT Ktrans with residual cancer burden and age showed the best improvement in predictive performance with ROC AUC = 0.965.

CONCLUSION

Accurate prediction of recurrence pre- and/or post-NACT through integration of imaging markers and clinicopathological variables may help improve clinical decision making in adjusting NACT and/or adjuvant treatment regimens to reduce the risk of recurrence and improve survival outcome.

An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques

Advances in accelerated magnetic resonance imaging (MRI) continue to push the bounds on achievable spatial and temporal resolution while maintaining a clinically acceptable image quality. Validation tools, including numerical simulations, are needed to characterize the repeatability and reproducibility of such methods for use in quantitative imaging applications. We describe the development of a simulation framework for analyzing and optimizing accelerated MRI acquisition and reconstruction techniques used in dynamic contrast enhanced (DCE) breast imaging. The simulation framework, in the form of a digital reference object (DRO), consists of four modules that control different aspects of the simulation, including the appearance and physiological behavior of the breast tissue as well as the MRI acquisition settings, to produce simulated k-space data for a DCE breast exam. The DRO design and functionality are described along with simulation examples provided to show potential applications of the DRO. The included simulation results demonstrate the ability of the DRO to simulate a variety of effects including the creation of simulated lesions, tissue enhancement modeled by the generalized kinetic model, T1-relaxation, fat signal precession and saturation, acquisition SNR, and changes in temporal resolution.

Eye-specific quantitative dynamic contrast-enhanced MRI analysis for patients with intraocular masses

OBJECTIVE

Dynamic contrast enhanced (DCE)-MRI is currently not generally used for intraocular masses as lesions are small, have an inhomogeneous T₁ and the eye is prone to motion. The aim of this paper is to address these eye-specific challenges, enabling accurate ocular DCE-MRI.

MATERIALS & METHODS

DCE-MRI of 19 uveal melanoma (UM) patients was acquired using a fat-suppressed 3D spoiled gradient echo sequence with TWIST (time-resolved angiography with stochastic trajectories sequence). The analysis consisted of a two-step registration method to correct for both head and eye motion. A T₁ map was calculated to convert signal intensities to concentrations. Subsequently, the Tofts model was fitted voxel wise to obtain K^trans and v_e.

RESULTS

Registration significantly improved the concentration curve quality (p < 0.001). The T₁ of melanotic lesions was significantly lower than amelanotic lesions (888 ms vs 1350 ms, p = 0.03). The average achieved B₁⁺ in the lesions was 91%. The average K^trans was 0.46 min^-1 (range 0.13-1.0) and the average v_e was 0.22 (range 0.10-0.51).

CONCLUSION

Using this eye-specific analysis, DCE of intraocular masses is possible which might aid in the diagnosis, prognosis and follow-up of UM.

Disposable point-of-care portable perfusion phantom for quantitative DCE-MRI

PURPOSE

To develop a disposable point-of-care portable perfusion phantom (DP4) and validate its clinical utility in a multi-institutional setting for quantitative dynamic contrast-enhanced magnetic resonance imaging (qDCE-MRI).

METHODS

The DP4 phantom was designed for single-use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE-MRI measurement of human tissues. The change of contrast-agent concentration in the phantom was measured using liquid chromatography-mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE-MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4-based error correction.

RESULTS

The contrast-agent concentration in the DP4 phantom was linearly increased over 10 min (0.17 mM/min, measurement accuracy: 96%) after injecting gadoteridol (100 mM) at a constant rate (0.24 ml/s, 4 ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, K^trans , was the highest of the PK parameters regardless of the PK models. The ICCs of K^trans in the TM, ETM, and SSM before DP4-based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction.

CONCLUSIONS

The DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE-MRI measurements.

Optical breast atlas as a testbed for image reconstruction in optical mammography

We present two optical breast atlases for optical mammography, aiming to advance the image reconstruction research by providing a common platform to test advanced image reconstruction algorithms. Each atlas consists of five individual breast models. The first atlas provides breast vasculature surface models, which are derived from human breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using image segmentation. A finite element-based method is used to deform the breast vasculature models from their natural shapes to generate the second atlas, compressed breast models. Breast compression is typically done in X-ray mammography but also necessary for some optical mammography systems. Technical validation is presented to demonstrate how the atlases can be used to study the image reconstruction algorithms. Optical measurements are generated numerically with compressed breast models and a predefined configuration of light sources and photodetectors. The simulated data is fed into three standard image reconstruction algorithms to reconstruct optical images of the vasculature, which can then be compared with the ground truth to evaluate their performance.

AI-Enhanced Diagnosis of Challenging Lesions in Breast MRI: A Methodology and Application Primer

Computer-aided diagnosis (CAD) systems have become an important tool in the assessment of breast tumors with magnetic resonance imaging (MRI). CAD systems can be used for the detection and diagnosis of breast tumors as a "second opinion" review complementing the radiologist's review. CAD systems have many common parts, such as image preprocessing, tumor feature extraction, and data classification that are mostly based on machine-learning (ML) techniques. In this review article, we describe applications of ML-based CAD systems in MRI covering the detection of diagnostically challenging lesions of the breast such as nonmass enhancing (NME) lesions, and furthermore discuss how multiparametric MRI and radiomics can be applied to the study of NME, including prediction of response to neoadjuvant chemotherapy (NAC). Since ML has been widely used in the medical imaging community, we provide an overview about the state-of-the-art and novel techniques applied as classifiers to CAD systems. The differences in the CAD systems in MRI of the breast for several standard and novel applications for NME are explained in detail to provide important examples, illustrating: 1) CAD for detection and diagnosis, 2) CAD in multiparametric imaging, 3) CAD in NAC, and 4) breast cancer radiomics. We aim to provide a comparison between these CAD applications and to illustrate a global view on intelligent CAD systems based on machine and deep learning in MRI of the breast. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study

We aimed to compare diagnostic performance in discriminating malignant and benign breast lesions between two intravoxel incoherent motion (IVIM) analysis methods for diffusion-weighted magnetic resonance imaging (DW-MRI) data and between DW- and dynamic contrast-enhanced (DCE)-MRI, and to determine if combining DW- and DCE-MRI further improves diagnostic accuracy. DW-MRI with 12 b-values and DCE-MRI were performed on 26 patients with 28 suspicious breast lesions before biopsies. The traditional biexponential fitting and a 3-b-value method were used for independent IVIM analysis of the DW-MRI data. Simulations were performed to evaluate errors in IVIM parameter estimations by the two methods across a range of signal-to-noise ratio (SNR). Pharmacokinetic modeling of DCE-MRI data was performed. Conventional radiological MRI reading yielded 86% sensitivity and 21% specificity in breast cancer diagnosis. At the same sensitivity, specificity of individual DCE- and DW-MRI markers improved to 36%–57% and that of combined DCE- or combined DW-MRI markers to 57%–71%, with DCE-MRI markers showing better diagnostic performance. The combination of DCE- and DW-MRI markers further improved specificity to 86%–93% and the improvements in diagnostic accuracy were statistically significant (P < .05) when compared with standard clinical MRI reading and most individual markers. At low breast DW-MRI SNR values (<50), like those typically seen in clinical studies, the 3-b-value approach for IVIM analysis generates markers with smaller errors and with comparable or better diagnostic performances compared with biexponential fitting. This suggests that the 3-b-value method could be an optimal IVIM-MRI method to be combined with DCE-MRI for improved diagnostic accuracy.

Quantitative kinetic parameters of primary tumor can be used to predict pelvic lymph node metastasis in early-stage cervical cancer

PURPOSE

To investigate the role of kinetic parameters of primary tumor derived from dynamic contrast-enhanced MRI (DCE-MRI) in predicting pelvic lymph node metastasis (PLNM) in patients with cervical cancer.

METHODS

66 women with newly diagnosed cervical cancer were included between July 2017 and August 2019. All patients had a FIGO stage IB-IIA cancer and treated with hysterectomy and bilateral lymphadenectomy. Kinetic parameters of the primary tumor were derived from DCE-MRI data. The tumor diameter, ADC value, kinetic parameters, and nodal short-axis diameter were compared between patients with or without PLNM. Logistic regression analysis was used to determine the independent predictors for PLNM and receiver operator characteristic curve was used to evaluate the predictive performance.

RESULTS

There were 20 patients with PLNM and 46 patients without PLNM. Tumor diameter, the efflux rate constant (Kep), and nodal short-axis diameter were significantly higher in patients with PLNM (P < 0.01). Multivariate logistic regression analysis showed that Kep and short-axis diameter were independent predictors for PLNM. Combining Kep and nodal short-axis diameter yielded the highest area under the curve (AUC) of 0.839. Combined with Kep, the sensitivity, specificity, negative predictive value, and positive predictive value of nodal short-axis diameter increased from 0.500, 0.957, 0.815, and 0.833 to 0.600, 0.978, 0.923, and 0.849, respectively. With 1.113 min-1 as threshold, the sensitivity and specificity values of Kep in predicting PLNM in patients with normal-sized lymph nodes were 0.909 and 0.667, respectively.

CONCLUSIONS

Kep of primary tumor can be used as a surrogate marker to predict PLNM in cervical cancer.

A preliminary study of the combination of ultrafast and abbreviated dynamic contrast: Enhanced breast magnetic resonance imaging

We combined the abbreviated and ultrafast magnetic resonance imaging (MRI) technique with the standard MRI protocol and compared lesion characterization quantitatively and qualitatively to the standard MRI protocol.Fifty-six patients with breast cancer who underwent MRI from June 2017 to May 2018 and fulfilled our inclusion criteria were included. Three radiologists measured the lesion sizes, described the MRI findings using BI-RADS lexicon, and demarcated the regions of interest to extract the volumetric quantitative and semi-quantitative parameters. We used Pearson's correlation analysis comparing the quantitative and semi-quantitative parameters. To evaluate the inter-observer variability, we calculated the intra-correlation coefficient (ICC). We also analysed the correlation in BI-RADS lexicon.There were 45 (80.4%) luminal and 11 (19.6%) non-luminal breast cancers, and the most common tumour subtype was invasive carcinoma (n = 48, 85.7%), followed by ductal carcinoma in situ (n = 8, 14.3%). Regarding correlation between the quantitative and semi-quantitative parameters, K significantly correlated with the wash-in factor (r, 0.862; P < .001) and AUC value (r, 0.951; P < .001). The lesion size measured by standard and combined abbreviated-ultrafast phases and that from the surgical pathological specimens showed moderate agreement (ICC range, 0.516-0.578). The ICCs among the 3 readers were excellent for lesion size measurement, BI-RADS lexicon regarding lesion type, mass shape, margin, internal enhancement, non-mass enhancement distribution, and internal enhancement by the standard and combined abbreviated-ultrafast protocols.The use of the modified and combined abbreviated-ultrafast MRI protocol provides a reliable measurement of the quantitative parameters and may aid in the screening of breast cancer.

Image quality of the CAIPIRINHA-Dixon-TWIST-VIBE technique for ultra-fast breast DCE-MRI: Comparison with the conventional GRE technique

PURPOSE

The aim of this study was to evaluate image quality of the CAIPIRINHA-Dixon-TWIST-Volume-Interpolated Breath-hold Examination (CDT-VIBE) technique for ultra-fast breast dynamic contrast enhanced (DCE) MRI with respect to conventional Gradient-Recalled Echo (GRE) technique.

METHODS

A total of 58 patients underwent a DCE-MRI based on CDT-VIBE sequence (temporal resolution: 11.9 s), immediately followed by 1 phase of a conventional T1 weighted GRE sequence (acquisition time: 68 s). The Signal-to-Noise Ratio (SNR) on phantom images, lesion/parenchyma signal ratio (LPSR), image quality, and morphological characterization were compared between the last phase of CDT-VIBE and conventional GRE images. The image quality was assessed by visual grading analysis (VGA). Reader agreement was assessed using Kappa analysis.

RESULTS

There was no significant difference in SNR (phantom) or LPSR (patient) between CDT-VIBE and conventional GRE images (P > 0.05). Significant parallel acquisition technique (PAT) noise and mild blurriness was observed on CDT-VIBE images. Visual grading analysis (VGA) confirmed significantly worse ratings for CDT-VIBE compared to the conventional GRE sequence in terms of PAT noise, lesion's internal feature clarity, and therefore overall image quality (area under contrast curve [AUC] values: 0.578 ‒ 0.764, P < 0.05), but edge sharpness and lesion conspicuity were equivalent (P > 0.05). Kappa analysis revealed good agreement on image quality scores (к = 0.725 ‒ 0.908) and on morphologic terms (к = 0.745-1.000).

CONCLUSION

The CDT-VIBE sequence provides excellent spatial resolution and adequate image quality in ultra-fast breast DCE-MRI. Further improvement in PAT noise and internal structure blurriness may be necessary.

MR and CT Imaging of the Normal Eyelid and its Application in Eyelid Tumors

T-staging of most eyelid malignancies includes the assessment of the integrity of the tarsal plate and orbital septum, which are not clinically accessible. Given the contribution of MRI in the characterization of orbital tumors and establishing their relations to nearby structures, we assessed its value in identifying different eyelid structures in 38 normal eyelids and evaluating tumor extension in three cases of eyelid tumors. As not all patients can receive an MRI, we evaluated those same structures on CT and compared both results. All eyelid structures were identified on MRI and CT, except for the conjunctiva on both techniques and for the tarsal muscles on CT. Histopathology confirmed the MRI findings of orbital septum invasion in one patient, and the MRI findings of intact tarsus and orbital septum in another patient. Histopathology could not confirm or exclude tarsal invasion seen on MRI on two patients. Although imaging the eyelid is challenging, the identification of most eyelid structures is possible with MRI and, to a lesser extent, with CT and can, therefore, have an important contribution to the T-staging of eyelid tumors, which may improve treatment planning and outcome.

Evaluation of image quality of pituitary dynamic contrast-enhanced MRI using time-resolved angiography with interleaved stochastic trajectories (TWIST) and iterative reconstruction TWIST (IT-TWIST)

BACKGROUND

Time-resolved angiography with interleaved stochastic trajectories (TWIST) is a keyhole imaging with frequent sampling of central k-space data and view-sharing for the peripheral k-space of dynamic phases. IT-TWIST is a technique to reconstruct images with a smaller temporal footprint using the same raw data obtained with TWIST by iterative reconstruction.

PURPOSE

To compare image quality between TWIST and IT-TWIST in 3D pituitary DCE-MRI.

STUDY TYPE

Retrospective observation study.

POPULATION

Fifty-one patients (23 men, 28 women) who underwent 3D pituitary DCE-MRI using TWIST between July 2016 and April 2017.

FIELD STRENGTH/SEQUENCE

3T/TWIST and IT-TWIST.

ASSESSMENT

Visual evaluation was conducted for image quality of delineation of the pituitary stalk and posterior lobe during the early arterial phase, cerebral white matter near the sella turcica, and the mass lesion. Bolus sharpness of the pituitary stalk, posterior lobe, and bilateral cavernous sinus was evaluated on the enhancement slope map calculated from TWIST and IT-TWIST. Temporal stability of intensity of the nonenhanced area was evaluated on temporal standard deviation (SD) maps calculated from TWIST and IT-TWIST.

STATISTICAL TESTS

Paired t-test or Wilcoxon rank-sum test was used to test the differences between TWIST and IT-TWIST in both visual evaluation and region of interest evaluation.

RESULTS

Scores of visual evaluations for IT-TWIST were significantly better than those for TWIST (P < 0.001) in all items. Enhancement slope for IT-TWIST was significantly higher than that for TWIST in posterior lobe, and right and left cavernous sinus (P < 0.001). Temporal SD for IT-TWIST was significantly lower than that for TWIST in all items, with statistical significance (P < 0.001).

DATA CONCLUSION

IT-TWIST yielded better visualization, and better enhancement slope, and less temporal SD compared with TWIST in 3D pituitary DCE-MRI. Evidence Level: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1497-1506.

New parameters of ultrafast dynamic contrast-enhanced breast MRI using compressed sensing

BACKGROUND

Ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI is considered a promising method of accelerated breast MRI. However, the value of new kinetic parameters derived from UF-DCE need clinical evaluation.

PURPOSE

To evaluate the diagnostic performance of the maximum slope (MS), time to enhancement (TTE), and time interval between arterial and venous visualization (AVI) derived from UF-DCE MRI using compressed sensing (CS).

STUDY TYPE

Retrospective.

POPULATION

Seventy-five patients with histologically proven breast lesions. The total number of analyzed lesions was 90 (61 malignant and 29 benign).

FIELD STRENGTH/SEQUENCE

3T MRI with UF-DCE MRI based on the 3D gradient-echo volumetric interpolated breath-hold examination (VIBE) sequence using incoherent k-space sampling combined with a CS reconstruction followed by conventional DCE MRI.

ASSESSMENT

The diagnostic performance of the MS, TTE, AVI, and conventional kinetic analysis was analyzed and compared with histology.

STATISTICAL TESTS

Wilcoxon rank sum test, receiver operating characteristic analysis.

RESULTS

The MS was larger and the TTE and AVI were smaller for malignant lesions compared with benign lesions: MS: 29.3%/s and 18.4%/s (P < 0.001), TTE: 7.0 and 12.0 seconds (P < 0.001), AVI: 2.7 and 4.4 frames (P = 0.006) for malignant and benign lesions. The discriminating power of the MS (area under the curve [AUC], 0.76) was slightly better than that of conventional kinetic analysis (AUC, 0.69) and comparable to that of the TTE and AVI (AUC, 0.78 and 0.76 for TTE and AVI, respectively). Invasive lobular carcinoma had smaller MS (21.8%/s) among malignant lesions (29.3%/s).

DATA CONCLUSION

The MS, TTE, and AVI can be used to evaluate breast lesions with clinical performance equivalent to that of conventional kinetic analysis. These parameters vary among histologies.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:164-174.

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.

Quantitative Multiparametric MRI May Augment the Response to Radiotherapy in Mid-Treatment Assessment of Patients with Esophageal Carcinoma

OBJECTIVE

The purpose of this study was to assess the mid-treatment response to radiotherapy (RT) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in patients with esophageal cancer (EC).

METHODS

42 patients with squamous EC were prepared for DCE-MRI and DWI scans both before treatment (NRT) and after the fifth radiotherapy (5th RT). The patients were classified into two groups (complete response [CR] and partial response [PR]) according to tumor regression after treatment. The quantitative parameters of DCE-MRI (Ktrans, Kep, Ve, and ADC) were measured. A receiver operating characteristic curve (ROC) was used to detect the efficiency of the above parameters.

RESULTS

After 1 month of RT, 29 patients were classified as CR and 11 patients were classified as PR. In the NRT group, the p values of Ktrans, Kep, Ve, and ADC were 0.004, 0.078, 0.0008, and <0.0001, respectively. After the 5th RT, the p values of the above parameters were <0.001, 0.005, 0.108, and 0.365, respectively. In the NRT group, the areas under the ROC curves of Ktrans, Ve, and ADC were 0.790, 0.617, and 0.737; the sensitivity values were 89.3, 92.5, and 90.0%; the specificity values were 69.4, 27.5, and 50.0%. In the 5th RT group, the areas under the ROC curves of Ktrans and Kep were 0.816 and 0.804; the sensitivity values were 71.2 and 95.0%; the specificity values were 81.6 and 50.0%.

CONCLUSION

DCE-MRI combined with DWI is effective in the early prediction of radiotherapeutic response of EC after the 5th RT other than after the traditional final treatment.

MRI of Uveal Melanoma

Uveal Melanoma (UM) is the most common primary malignant ocular tumor. The high soft tissue contrast and spatial resolution, and the possibility of generating 3D volumetric and functional images, make Magnetic Resonance Imaging (MRI) a valuable diagnostic imaging technique in UM. Current clinical MRI protocols, however, are not optimized for UM and therefore lack the quality for accurate assessments. We therefore developed a dedicated protocol at a 3 Tesla MRI, using an eye coil, consisting of multi-slice 2D sequences, different isotropic sequences and diffusion and perfusion-weighted images. This protocol was prospectively evaluated in 9 uveal melanoma patients. The multi-slice 2D sequences had the highest in-plane resolution, being the most suited for lesion characterization and local extension evaluation. The isotropic 3D Turbo-Spin Echo (TSE) sequences were the most suitable for accurate geometric measurements of the tumor and are therefore important for therapy planning. Diffusion and perfusion-weighted images aid in differentiating benign from malignant lesions and provide quantitative measures on tumor hemodynamics and cellularity, which have been reported to be effective in predicting and assessing treatment outcome. Overall, this dedicated MRI protocol provides high-quality imaging of UM, which can be used to improve its diagnosis, treatment planning, and follow-up.

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

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate K^trans (volume transfer rate constant), v_e (extravascular, extracellular volume fraction), k_ep (efflux rate constant), and τ_i (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T₁ values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for K^trans, v_e, k_ep, and τ_i, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in K^trans and v_e (wCV = 0.50 and 0.10, respectively), but had smaller effects on k_ep and τ_i (wCV = 0.39 and 0.22, respectively). k_ep is less sensitive to AIF variation than K^trans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τ_i parameter may have advantages over the conventional PK parameters in a longitudinal study.

Comprehensive Dynamic Contrast-Enhanced 3D Magnetic Resonance Imaging of the Breast With Fat/Water Separation and High Spatiotemporal Resolution Using Radial Sampling, Compressed Sensing, and Parallel Imaging

OBJECTIVES

The aim of this study was to assess the applicability of Dixon radial volumetric encoding (Dixon-RAVE) for comprehensive dynamic contrast-enhanced 3D magnetic resonance imaging (MRI) of the breast using a combination of radial sampling, model-based fat/water separation, compressed sensing, and parallel imaging.

MATERIALS AND METHODS

In this Health Insurance Portability and Accountability Act-compliant prospective study, 24 consecutive patients underwent bilateral breast MRI, including both conventional fat-suppressed and non-fat-suppressed precontrast T1-weighted volumetric interpolated breath-hold examination (VIBE). Afterward, 1 continuous Dixon-RAVE scan was performed with the proposed approach while the contrast agent was injected. This scan was immediately followed by the acquisition of 4 conventional fat-saturated VIBE scans. From the comprehensive Dixon-RAVE data set, different image contrasts were reconstructed that are comparable to the separate conventional VIBE scans.Two radiologists independently rated image quality, conspicuity of fibroglandular tissue from fat (FG), and degree of fat suppression (FS) on a 5-point Likert-type scale for the following 3 comparisons: precontrast fat-suppressed (pre-FS), precontrast non-fat-suppressed (pre-NFS), and dynamic fat-suppressed (dyn-FS) images.

RESULTS

When scores were averaged over readers, Dixon-RAVE achieved significantly higher (P < 0.001) degree of fat suppression compared with VIBE, for both pre-FS (4.25 vs 3.67) and dyn-FS (4.10 vs 3.46) images. Although Dixon-RAVE had lower image quality score compared with VIBE for the pre-FS (3.56 vs 3.67, P = 0.490), the pre-NFS (3.54 vs 3.88, P = 0.009), and the dyn-FS images (3.06 vs 3.67, P < 0.001), acceptable or better diagnostic quality was achieved (score ≥ 3). The FG score for Dixon-RAVE in comparison to VIBE was significantly higher for the pre-FS image (4.23 vs 3.85, P = 0.044), lower for the pre-NFS image (3.98 vs 4.25, P = 0.054), and higher for the dynamic fat-suppressed image (3.90 vs 3.85, P = 0.845).

CONCLUSIONS

Dixon-RAVE can serve as a one-stop-shop approach for comprehensive T1-weighted breast MRI with diagnostic image quality, high spatiotemporal resolution, reduced overall scan time, and improved fat suppression compared with conventional imaging.

Dynamic field-of-view imaging to increase temporal resolution in the early phase of contrast media uptake in breast DCE-MRI: A feasibility study

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.

Retrospective analysis of the utility of multiparametric MRI for differentiating between benign and malignant breast lesions in women in China

We explored the utility of time-resolved angiography with interleaved stochastic trajectories dynamic contrast-enhanced magnetic resonance imaging (TWIST DCE-MRI), readout segmentation of long variable echo-trains diffusion-weighted magnetic resonance imaging- diffusion-weighted magnetic resonance imaging (RESOLVE-DWI), and echo-planar imaging- diffusion-weighted magnetic resonance imaging (EPI-DWI) for distinguishing between malignant and benign breast lesions.This retrospective analysis included female patients with breast lesions seen at a single center in China between January 2016 and April 2016. Patients were allocated to a benign or malignant group based on pathologic diagnosis. All patients received routine MRI, RESOLVE-DWI, EPI-DWI, and TWIST DCE-T1WI. Variables measured included quantitative parameters (K, Kep, and Ve), semiquantitative parameters (rate of contrast enhancement for contrast agent inflow [W-in], rate of contrast decay for contrast agent outflow [W-out], and time-to-peak enhancement after contrast agent injection [TTP]) and apparent diffusion coefficient (ADC) values for RESOLVE-DWI (ADCr) and EPI-DWI (ADCe). Receiver-operating characteristic (ROC) curve analysis was used to evaluate the diagnostic utility of each parameter for differentiating malignant from benign breast lesions.A total of 87 patients were included (benign, n = 20; malignant, n = 67). Compared with the benign group, the malignant group had significantly higher K, Kep and W-in and significantly lower W-out, TTP, ADCe, and ADCr (all P < .05); Ve was not significantly different between groups. RESOLVE-DWI was superior to conventional EPI-DWI at illustrating lesion boundary and morphology, while ADCr was significantly lower than ADCe in all patients. Kep, W-out, ADCr, and ADCe showed the highest diagnostic efficiency (based on AUC value) for differentiating between benign and malignant lesions. Combining 3 parameters (Kep, W-out, and ADCr) had a higher diagnostic efficiency (AUC, 0.965) than any individual parameter and distinguished between benign and malignant lesions with high sensitivity (91.0%), specificity (95.0%), and accuracy (91.9%).An index combining Kep, W-out, and ADCr could potentially be used for the differential diagnosis of breast lesions.

Feasibility analysis of early temporal kinetics as a surrogate marker for breast tumor type, grade, and aggressiveness

BACKGROUND

Screening breast MRI has been shown to preferentially detect high-grade ductal carcinoma in situ (DCIS) and invasive carcinoma, likely due to increased angiogenesis resulting in early initial uptake of contrast. As interest grows in abbreviated screening breast MRI (AB-MRI), markers of early contrast washin that can predict tumor grade and potential aggressiveness are of clinical interest.

PURPOSE

To evaluate the feasibility of using the initial enhancement ratio (IER) as a surrogate marker for tumor grade, hormone receptor status, and prognostic markers, as an initial step to being incorporated into AB-MRI.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 162 women (mean 55.0 years, range 32.8-87.7 years) with 187 malignancies imaged January 2012-November 2015.

FIELD STRENGTH/SEQUENCE

Images were acquired at 3.0T with a T₁ -weighted gradient echo fat-suppressed-volume interpolated breath-hold sequence.

ASSESSMENT

Subjects underwent dynamic contrast-enhanced breast MRI with a 7-channel breast coil. IER (% signal increase over baseline at the first postcontrast acquisition) was assessed and correlated with background parenchymal enhancement, washout curves, stage, and final pathology.

STATISTICAL TESTS

Chi-square test, Spearman rank correlation, Mann-Whitney U-tests, Bland-Altman analysis, and receiver operating characteristic curve analysis.

RESULTS

IER was higher for invasive cancer than for DCIS (R1/R2, P < 0.001). IER increased with tumor grade (R1: r = 0.56, P < 0.001, R2: r = 0.50, P < 0.001), as ki-67 increased (R1: r = 0.35, P < 0.001; R2 r = 0.35, P < 0.001), and for node-positive disease (R1/R2, P = 0.001). IER was higher for human epidermal growth factor receptor two-positive and triple negative cancers than for estrogen receptor-positive / progesterone receptor-positive tumors (R1 P < 0.001-0.002; R2 P = 0.0.001-0.011). IER had higher sensitivity (80.6% vs. 75.5%) and specificity (55.8% vs. 48.1%) than washout curves for positive nodes, higher specificity (48.1% vs. 36.5%) and positive predictive value (70.2% vs. 66.7%) for high ki-67, and excellent interobserver agreement (intraclass correlation coefficient = 0.82).

DATA CONCLUSION

IER, a measurement of early contrast washin, is associated with higher-grade malignancies and tumor aggressiveness and might be potentially incorporated into an AB-MRI protocol.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1692-1700.

Novel High Spatiotemporal Resolution Versus Standard-of-Care Dynamic Contrast-Enhanced Breast MRI: Comparison of Image Quality

OBJECTIVE

Currently, dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI) prioritizes spatial resolution over temporal resolution given the limitations of acquisition techniques. The purpose of our intrapatient study was to assess the ability of a novel high spatial and high temporal resolution DCE breast MRI method to maintain image quality compared with the clinical standard-of-care (SOC) MRI.

MATERIALS AND METHODS

Thirty patients, each demonstrating a focal area of enhancement (29 benign, 1 cancer) on their SOC MRI, consented to undergo a research DCE breast MRI on a second date. For the research DCE MRI, a method (DIfferential Subsampling with Cartesian Ordering [DISCO]) using pseudorandom k-space sampling, view sharing reconstruction, 2-point Dixon fat-water separation, and parallel imaging was used to produce images with an effective temporal resolution 6 times faster than the SOC MRI (27 vs 168 seconds, respectively). Both the SOC and DISCO MRI scans were acquired with matching spatial resolutions of 0.8 × 0.8 × 1.6 mm. Image quality (distortion/artifacts, resolution, fat suppression, lesion conspicuity, perceived signal-to-noise ratio, and overall image quality) was scored by 3 radiologists in a blinded reader study.

RESULTS

Differences in image quality scores between the DISCO and SOC images were all less than 0.8 on a 10-point scale, and both methods were assessed as providing diagnostic image quality in all cases. DISCO images with the same high spatial resolution, but 6 times the effective temporal resolution as the SOC MRI scans, were produced, yielding 20 postcontrast time points with DISCO compared with 3 for the SOC MRI, over the same total time interval.

CONCLUSIONS

DISCO provided comparable image quality compared with the SOC MRI, while also providing 6 times faster effective temporal resolution and the same high spatial resolution.

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6-8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature-map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature-map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response.

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol

PURPOSE

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI.

METHOD

The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate.

RESULT

The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively, compared to AUC values of previous approach of 0.8562 and 0.8311, respectively.

CONCLUSION

The proposed approach based on 2D textural features quantifying spatiotemporal changes of the contrast-agent uptake significantly outperforms the previous approach based on 3D morphology and dynamic analysis in differentiating the malignant and benign breast lesions, showing its potential to aid clinical decision making.

Relationship between carotid plaque surface morphology and perfusion: a 3D DCE-MRI study

Objective

This study aims to explore the relationship between plaque surface morphology and neovascularization using a high temporal and spatial resolution 4D contrast-enhanced MRI/MRA sequence.

Materials and methods

Twenty one patients with either recent symptoms or a carotid artery stenosis ≥40% were recruited in this study. Plaque surface morphology and luminal stenosis were determined from the arterial phase MRA images. Carotid neovascularization was evaluated by a previously validated pharmacokinetic (PK) modeling approach. K^trans (transfer constant) and v_p (partial plasma volume) were calculated in both the adventitia and plaque.

Results

Image acquisition and analysis was successfully performed in 28 arteries. Mean luminal stenosis was 44% (range 11–82%). Both adventitial and plaque K^trans in ulcerated/irregular plaques were significantly higher than smooth plaques (0.079 ± 0.018 vs. 0.064 ± 0.011 min⁻¹, p = 0.02; 0.065 ± 0.013 vs. 0.055 ± 0.010 min⁻¹, p = 0.03, respectively). Positive correlations between adventitial K^trans and v_p against stenosis were observed (r = 0.44, p = 0.02; r = 0.55, p = 0.01, respectively).

Conclusion

This study demonstrates the feasibility of using a single sequence to acquire both high resolution 4D CE-MRA and DCE-MRI to evaluate both plaque surface morphology and function. The results demonstrate significant relationships between lumen surface morphology and neovascularization.

Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts

Objective

To evaluate the validity of two abbreviated protocols (AP) of MRI in breast cancer screening of dense breast tissue.

Materials and Methods

This was a retrospective study in 356 participants with dense breast tissue and negative mammography results. The study was approved by the Nanjing Medical University Ethics Committee. Patients were imaged with a full diagnostic protocol (FDP) of MRI. Two APs (AP-1 consisting of the first post-contrast subtracted [FAST] and maximum-intensity projection [MIP] images, and AP-2 consisting of AP-1 combined with diffusion-weighted imaging [DWI]) and FDP images were analyzed separately, and the sensitivities and specificities of breast cancer detection were calculated.

Results

Of the 356 women, 67 lesions were detected in 67 women (18.8%) by standard MR protocol, and histological examination revealed 14 malignant lesions and 53 benign lesions. The average interpretation time of AP-1 and AP-2 were 37 seconds and 54 seconds, respectively, while the average interpretation time of the FDP was 3 minutes and 25 seconds. The sensitivities of the AP-1, AP-2, and FDP were 92.9, 100, and 100%, respectively, and the specificities of the three MR protocols were 86.5, 95.0, and 96.8%, respectively. There was no significant difference among the three MR protocols in the diagnosis of breast cancer (p > 0.05). However, the specificity of AP-1 was significantly lower than that of AP-2 (p = 0.031) and FDP (p = 0.035), while there was no difference between AP-2 and FDP (p > 0.05).

Conclusion

The AP may be efficient in the breast cancer screening of dense breast tissue. FAST and MIP images combined with DWI of MRI are helpful to improve the specificity of breast cancer detection.

Interobserver variability in identification of breast tumors in MRI and its implications for prognostic biomarkers and radiogenomics

PURPOSE

To assess the interobserver variability of readers when outlining breast tumors in MRI, study the reasons behind the variability, and quantify the effect of the variability on algorithmic imaging features extracted from breast MRI.

METHODS

Four readers annotated breast tumors from the MRI examinations of 50 patients from one institution using a bounding box to indicate a tumor. All of the annotated tumors were biopsy proven cancers. The similarity of bounding boxes was analyzed using Dice coefficients. An automatic tumor segmentation algorithm was used to segment tumors from the readers' annotations. The segmented tumors were then compared between readers using Dice coefficients as the similarity metric. Cases showing high interobserver variability (average Dice coefficient <0.8) after segmentation were analyzed by a panel of radiologists to identify the reasons causing the low level of agreement. Furthermore, an imaging feature, quantifying tumor and breast tissue enhancement dynamics, was extracted from each segmented tumor for a patient. Pearson's correlation coefficients were computed between the features for each pair of readers to assess the effect of the annotation on the feature values. Finally, the authors quantified the extent of variation in feature values caused by each of the individual reasons for low agreement.

RESULTS

The average agreement between readers in terms of the overlap (Dice coefficient) of the bounding box was 0.60. Automatic segmentation of tumor improved the average Dice coefficient for 92% of the cases to the average value of 0.77. The mean agreement between readers expressed by the correlation coefficient for the imaging feature was 0.96.

CONCLUSIONS

There is a moderate variability between readers when identifying the rectangular outline of breast tumors on MRI. This variability is alleviated by the automatic segmentation of the tumors. Furthermore, the moderate interobserver variability in terms of the bounding box does not translate into a considerable variability in terms of assessment of enhancement dynamics. The authors propose some additional ways to further reduce the interobserver variability.

Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue

RATIONALE AND OBJECTIVES

The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue.

MATERIALS AND METHODS

There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols.

RESULTS

Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ² = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ² = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods.

CONCLUSIONS

The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening.

Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions

OBJECTIVES

To investigate time to enhancement (TTE) as novel dynamic parameter for lesion classification in breast magnetic resonance imaging (MRI).

METHODS

In this retrospective study, 157 women with 195 enhancing abnormalities (99 malignant and 96 benign) were included. All patients underwent a bi-temporal MRI protocol that included ultrafast time-resolved angiography with stochastic trajectory (TWIST) acquisitions (1.0×0.9×2.5mm, temporal resolution 4.32s), during the inflow of contrast agent. TTE derived from TWIST series and relative enhancement versus time curve type derived from volumetric interpolated breath-hold examination (VIBE) series were assessed and combined with basic morphological information to differentiate benign from malignant lesions. Receiver operating characteristic analysis and kappa statistics were applied.

RESULTS

TTE had a significantly better discriminative ability than curve type (p<0.001 and p=0.026 for reader 1 and 2, respectively). Including morphology, sensitivity of TWIST and VIBE assessment was equivalent (p=0.549 and p=0.344, respectively). Specificity and diagnostic accuracy were significantly higher for TWIST than for VIBE assessment (p<0.001). Inter-reader agreement in differentiating malignant from benign lesions was almost perfect for TWIST evaluation (κ=0.86) and substantial for conventional assessment (κ=0.75).

CONCLUSIONS

TTE derived from ultrafast TWIST acquisitions is a valuable parameter that allows robust differentiation between malignant and benign breast lesions with high accuracy.

Comparison of conventional DCE-MRI and a novel golden-angle radial multicoil compressed sensing method for the evaluation of breast lesion conspicuity

PURPOSE

To compare a novel multicoil compressed sensing technique with flexible temporal resolution, golden-angle radial sparse parallel (GRASP), to conventional fat-suppressed spoiled three-dimensional (3D) gradient-echo (volumetric interpolated breath-hold examination, VIBE) MRI in evaluating the conspicuity of benign and malignant breast lesions.

MATERIALS AND METHODS

Between March and August 2015, 121 women (24-84 years; mean, 49.7 years) with 180 biopsy-proven benign and malignant lesions were imaged consecutively at 3.0 Tesla in a dynamic contrast-enhanced (DCE) MRI exam using sagittal T1-weighted fat-suppressed 3D VIBE in this Health Insurance Portability and Accountability Act-compliant, retrospective study. Subjects underwent MRI-guided breast biopsy (mean, 13 days [1-95 days]) using GRASP DCE-MRI, a fat-suppressed radial "stack-of-stars" 3D FLASH sequence with golden-angle ordering. Three readers independently evaluated breast lesions on both sequences. Statistical analysis included mixed models with generalized estimating equations, kappa-weighted coefficients and Fisher's exact test.

RESULTS

All lesions demonstrated good conspicuity on VIBE and GRASP sequences (4.28 ± 0.81 versus 3.65 ± 1.22), with no significant difference in lesion detection (P = 0.248). VIBE had slightly higher lesion conspicuity than GRASP for all lesions, with VIBE 12.6% (0.63/5.0) more conspicuous (P < 0.001). Masses and nonmass enhancement (NME) were more conspicuous on VIBE (P < 0.001), with a larger difference for NME (14.2% versus 9.4% more conspicuous). Malignant lesions were more conspicuous than benign lesions (P < 0.001) on both sequences.

CONCLUSION

GRASP DCE-MRI, a multicoil compressed sensing technique with high spatial resolution and flexible temporal resolution, has near-comparable performance to conventional VIBE imaging for breast lesion evaluation.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;45:1746-1752.

Kinetic Analysis of Benign and Malignant Breast Lesions With Ultrafast Dynamic Contrast-Enhanced MRI: Comparison With Standard Kinetic Assessment

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.

Multiparametric MR Imaging of Breast Cancer

Breast MR imaging has increased in popularity over the past 2 decades due to evidence of its high sensitivity for cancer detection. Current clinical MR imaging approaches rely on the use of a dynamic contrast-enhanced acquisition that facilitates morphologic and semiquantitative kinetic assessments of breast lesions. The use of more functional and quantitative parameters holds promise to broaden the utility of MR imaging and improve its specificity. Because of wide variations in approaches for measuring these parameters and the considerable technical challenges, robust multicenter data supporting their routine use are not yet available, limiting current applications of many of these tools to research purposes.

Ultrafast Bilateral DCE-MRI of the Breast with Conventional Fourier Sampling: Preliminary Evaluation of Semi-quantitative Analysis

RATIONALE AND OBJECTIVES

The study aimed to evaluate the feasibility and advantages of a combined high temporal and high spatial resolution protocol for dynamic contrast-enhanced magnetic resonance imaging of the breast.

MATERIALS AND METHODS

Twenty-three patients with enhancing lesions were imaged at 3T. The acquisition protocol consisted of a series of bilateral, fat-suppressed "ultrafast" acquisitions, with 6.9- to 9.9-second temporal resolution for the first minute following contrast injection, followed by four high spatial resolution acquisitions with 60- to 79.5-second temporal resolution. All images were acquired with standard uniform Fourier sampling. A filtering method was developed to reduce noise and detect significant enhancement in the high temporal resolution images. Time of arrival (TOA) was defined as the time at which each voxel first satisfied all the filter conditions, relative to the time of initial arterial enhancement.

RESULTS

Ultrafast images improved visualization of the vasculature feeding and draining lesions. A small percentage of the entire field of view (<6%) enhanced significantly in the 30 seconds following contrast injection. Lesion conspicuity was highest in early ultrafast images, especially in cases with marked parenchymal enhancement. Although the sample size was relatively small, the average TOA for malignant lesions was significantly shorter than the TOA for benign lesions. Significant differences were also measured in other parameters descriptive of early contrast media uptake kinetics (P < 0.05).

CONCLUSIONS

Ultrafast imaging in the first minute of dynamic contrast-enhanced magnetic resonance imaging of the breast has the potential to add valuable information on early contrast dynamics. Ultrafast imaging could allow radiologists to confidently identify lesions in the presence of marked background parenchymal enhancement.

Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters K^trans (contrast agent plasma/interstitium transfer rate constant), v_e (extravascular and extracellular volume fraction), k_ep (intravasation rate constant)_, and SSM-unique τ_i (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. v_e values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT K^trans, τ_i, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τ_i parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.

Highly accelerated dynamic contrast enhanced imaging

PURPOSE

Dynamic contrast-enhanced imaging provides unique physiological information, notably the endothelial permeability (K(trans)), and may improve the diagnosis and management of multiple pathologies. Current acquisition methods provide limited spatial-temporal resolution and field-of-view, often preventing characterization of the entire pathology and precluding measurement of the arterial input function. We present a method for highly accelerated dynamic imaging and demonstrate its utility for dynamic contrast-enhanced modeling.

METHODS

We propose a novel Poisson ellipsoid sampling scheme and enforce multiple spatial and temporal l1-norm constraints during image reconstruction. Retrospective and prospective analyses were performed to validate the approach.

RESULTS

Retrospectively, no mean bias or diverging trend was observed as the acceleration rate was increased from 3× to 18×; less than 10% error was measured in K(trans) at any individual rates in this range. Prospectively accelerated images at a rate of 36× enabled full brain coverage with 0.94 × 0.94 × 1.9 mm(3) spatial and 4.1 s temporal resolutions. Images showed no visible degradation and provided accurate K(trans) values when compared to a clinical population.

CONCLUSION

Highly accelerated dynamic MRI using compressed sensing and parallel imaging provides accurate permeability modeling and enables full brain, high resolution acquisitions.

Initial Experience of Applying TWIST-Dixon With Flexible View Sharing in Breast DCE-MRI

INTRODUCTION

We developed a new fast imaging technique with flexible time-resolved angiography with stochastic trajectories (TWIST) view sharing to achieve variable temporal resolution and with flexible echo time Dixon to achieve robust fat suppression and to evaluate its application in breast dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI).

MATERIALS AND METHODS

The TWIST-Dixon technique was improved with more flexible view sharing and echo times (TWIST-Dixon-Flex). In a dynamic series, each measurement can be separately prescribed as "full," "partial," or "center-only." The spatial and temporal resolution can then be adjusted throughout the measurements to match the dynamic characteristics of contrast enhancement at different phases. The potential advantages of TWIST-Dixon-Flex were evaluated with 18 clinical breast DCE MRI cases. A mixed-effects analysis of variance (ANOVA) was performed to compare the image quality with that of the conventional images.

RESULTS

The ANOVA showed that the quality of postcontrast TWIST-Dixon-Flex images was significantly higher than that of the conventional images. The TWIST-Dixon-Flex technique also provided the capability to detect differences in rapid contrast uptake from different regions of the breast tumor, which is not possible with conventional breast DCE-MRI.

CONCLUSION

The new TWIST-Dixon-Flex technique provides potentially valuable information about early tumor enhancement, and maintains excellent image quality at peak and postcontrast enhancement. This technique could help overcome the compromise on spatial over temporal resolution in clinical breast imaging.

Effect of T2* correction on contrast kinetic model analysis using a reference tissue arterial input function at 7 T

OBJECTIVES

We aimed to investigate the effect of T2* correction on estimation of kinetic parameters from T1-weighted dynamic contrast enhanced (DCE) MRI data when a reference-tissue arterial input function (AIF) is used.

MATERIALS AND METHODS

DCE-MRI data were acquired from seven mice with 4T1 mouse mammary tumors using a double gradient echo sequence at 7 T. The AIF was estimated from a region of interest in the muscle. The extended Tofts model was used to estimate pharmacokinetic parameters in the enhancing part of the tumor, with and without T2* correction of the lesion and AIF. The parameters estimated with T2* correction of both the AIF and lesion time-intensity curve were assumed to be the reference standard.

RESULTS

For the whole population, there was significant difference (p < 0.05) in transfer constant (K(trans)) between T2* corrected and not corrected methods, but not in interstitial volume fraction (ve). Individually, no significant differences were found in K(trans) and ve of four and six tumors, respectively, between the T2* corrected and not corrected methods. In contrast, K(trans) was significantly underestimated, if the T2* correction was not used, in other tumors for which the median K(trans) was larger than 0.4 min(-1).

CONCLUSION

T2* effect on tumors with high K(trans) may not be negligible in kinetic model analysis, even if AIF is estimated from reference tissue where the concentration of contrast agent is relatively low.

Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score

OBJECTIVE

To improve specificity of breast MRI by integrating Apparent Diffusion Coefficient (ADC) values with contrast enhanced MRI (CE-MRI) using a simple sum score.

METHODS

Retrospective analysis of a consecutive series of patients referred to breast MRI at 1.5 T for further workup of breast lesions. Reading results of CE-MRI were dichotomized into score 1 (suspicious) or 0 (benign). Lesion's ADC-values (in *10-3 mm2/s) were assigned two different scores: ADC2: likely malignant (score +1, ADC ≤ 1), indeterminate (score 0, ADC >1- ≤ 1.4) and likely benign (score -1, ADC > 1.4) and ADC1: indeterminate (score 0, ADC ≤ 1.4) and likely benign (score -1, ADC > 1.4). Final added CE-MRI and ADC scores >0 were considered suspicious. Reference standard was histology and imaging follow-up of >24 months. Diagnostic parameters were compared using McNemar tests.

RESULTS

A total of 150 lesions (73 malignant) were investigated. Reading of CE-MRI showed a sensitivity of 100 % (73/73) and a specificity of 81.8 % (63/77). Additional integration of ADC scores increased specificity (ADC2/ADC1, P = 0.008/0.001) without causing false negative results.

CONCLUSION

Using a simple sum score, ADC-values can be integrated with CE-MRI of the breast, improving specificity. The best approach is using one threshold to exclude cancer.

KEY POINTS

ADC is used to assign levels of suspicion to breast lesions. ADC values >1.4 *10 (-3)   mm (2) /s are likely benign and effectively rule out malignancy. ADC values below ≤1*10 (-3)   mm (2) /s) are likely malignant but may be false positive. CE-MRI (+1: suspicious, 0: benign) and ADC (0: indeterminate, -1: benign) scores are added. Sum scores >0 should be biopsied.

High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement

PURPOSE

To demonstrate the feasibility of the improved temporal resolution by using compressed sensing (CS) combined imaging sequence in dynamic contrast-enhanced MRI (DCE-MRI) of kidney, and investigate its quantitative effects on renal perfusion measurements.

MATERIALS AND METHODS

Ten rabbits were included in the accelerated scans with a CS-combined 3D pulse sequence. To evaluate the image quality, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the proposed CS strategy and the conventional full sampling method. Moreover, renal perfusion was estimated by using the separable compartmental model in both CS simulation and realistic CS acquisitions.

RESULTS

The CS method showed DCE-MRI images with improved temporal resolution and acceptable image contrast, while presenting significantly higher SNR than the fully sampled images (p<.01) at 2-, 3- and 4-X acceleration. In quantitative measurements, renal perfusion results were in good agreement with the fully sampled one (concordance correlation coefficient=0.95, 0.91, 0.88) at 2-, 3- and 4-X acceleration in CS simulation. Moreover, in realistic acquisitions, the estimated perfusion by the separable compartmental model exhibited no significant differences (p>.05) between each CS-accelerated acquisition and the full sampling method.

CONCLUSION

The CS-combined 3D sequence could improve the temporal resolution for DCE-MRI in kidney while yielding diagnostically acceptable image quality, and it could provide effective measurements of renal perfusion.