Current clinical MR imaging practices rely on the qualitative assessment of images for diagnosis and treatment planning. While contrast in MR images is dependent on the spin parameters of the imaged ...tissue, pixel values on MR images are relative and are not scaled to represent any tissue properties. Synthetic MR is a fully featured imaging workflow consisting of efficient multi‐parameter mapping acquisition, synthetic image generation, and volume quantitation of brain tissues. As the application becomes more widely available on multiple vendors and scanner platforms, it has also gained widespread adoption as clinicians begin to recognize the benefits of rapid quantitation. This review will provide details about the sequence with a focus on the physical principles behind its relaxometry mechanisms. It will present an overview of the products in their current form and some potential issues when implementing it in the clinic. It will conclude by highlighting some recent advances of the technique, including a 3D mapping method and its associated applications.
To evaluate a vendor-agnostic multiparametric mapping scheme based on 3D quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) for whole-brain ...T1, T2, and proton density (PD) mapping.
This prospective, multi-institutional study was conducted between September 2021 and February 2022 using five different 3T systems from four prominent MRI vendors. The accuracy of this technique was evaluated using a standardized MRI system phantom. Intra-scanner repeatability and inter-vendor reproducibility of T1, T2, and PD values were evaluated in 10 healthy volunteers (6 men; mean age ± SD, 28.0 ± 5.6 y) who underwent scan-rescan sessions on each scanner (total scans = 100). To evaluate the feasibility of 3D-QALAS, nine patients with multiple sclerosis (nine women; mean age ± SD, 48.2 ± 11.5 y) underwent imaging examination on two 3T MRI systems from different manufacturers.
Quantitative maps obtained with 3D-QALAS showed high linearity (R
= 0.998 and 0.998 for T1 and T2, respectively) with respect to reference measurements. The mean intra-scanner coefficients of variation for each scanner and structure ranged from 0.4% to 2.6%. The mean structure-wise test-retest repeatabilities were 1.6%, 1.1%, and 0.7% for T1, T2, and PD, respectively. Overall, high inter-vendor reproducibility was observed for all parameter maps and all structure measurements, including white matter lesions in patients with multiple sclerosis.
The vendor-agnostic multiparametric mapping technique 3D-QALAS provided reproducible measurements of T1, T2, and PD for human tissues within a typical physiological range using 3T scanners from four different MRI manufacturers.
The task group (TG) on magnetic resonance imaging (MRI) implementation in high‐dose‐rate (HDR) brachytherapy (BT)—Considerations from simulation to treatment, TG 303, was constituted by the American ...Association of Physicists in Medicine's (AAPM's) Science Council under the direction of the Therapy Physics Committee, the Brachytherapy Subcommittee, and the Working Group on Brachytherapy Clinical Applications. The TG was charged with developing recommendations for commissioning, clinical implementation, and on‐going quality assurance (QA). Additionally, the TG was charged with describing HDR BT workflows and evaluating practical consideration that arise when implementing MR imaging. For brevity, the report is focused on the treatment of gynecologic and prostate cancer. The TG report provides an introduction and rationale for MRI implementation in BT, a review of previous publications on topics including available applicators, clinical trials, previously published BT‐related TG reports, and new image‐guided recommendations beyond CT‐based practices. The report describes MRI protocols and methodologies, including recommendations for the clinical implementation and logical considerations for MR imaging for HDR BT. Given the evolution from prescriptive to risk‐based QA, an example of a risk‐based analysis using MRI‐based, prostate HDR BT is presented. In summary, the TG report is intended to provide clear and comprehensive guidelines and recommendations for commissioning, clinical implementation, and QA for MRI‐based HDR BT that may be utilized by the medical physics community to streamline this process. This report is endorsed by the American Brachytherapy Society.
Because magnetic resonance imaging-guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has ...increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into account relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility-induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility-induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.
Background
Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple‐negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region ...(PTR) has been reported to be a negative prognostic factor in TNBC.
Purpose
To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field‐of‐view (rFOV) diffusion‐weighted imaging (DWI) predict the response to NAST in TNBC.
Study Type
Prospective.
Population/Subjects
A total of 108 patients with biopsy‐proven TNBC who underwent NAST and definitive surgery during 2015–2020.
Field Strength/Sequence
A 3.0 T/rFOV single‐shot diffusion‐weighted echo‐planar imaging sequence (DWI).
Assessment
Three scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat‐dominant pixels.
Statistical Tests
ADC features were tested for prediction of pCR, both individually using Mann–Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k‐fold cross‐validation. A P value < 0.05 was considered statistically significant.
Results
Fifty‐one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mm2/sec). The top‐performing feature for prediction of pCR was the maximum ADC from the 5‐mm fat‐inclusive PTR after cycle 4 of NAST (AUC: 0.74; 95% confidence interval: 0.64, 0.84). Multivariable models of ADC features performed similarly for fat‐inclusive and fat‐exclusive PTRs, with AUCs ranging from 0.68 to 0.72 for the cycle 2 and cycle 4 scans.
Data Conclusion
Quantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC.
Evidence Level
1
Technical Efficacy
Stage 4
Background
Dynamic contrast‐enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves ...in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response.
Purpose
To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple‐negative breast cancer (TNBC).
Study Type
Prospective.
Population/Subjects
Sixty patients with biopsy‐confirmed TNBC between December 2016 and September 2020.
Field Strength/Sequence
A 3.0 T/3D fast spoiled gradient echo‐based DCE MRI
Assessment
Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5‐minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing.
Statistical Tests
Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann–Whitney U test.
Results
About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non‐pCR, with AUC (95% confidence interval CI) = 0.85 (0.74,0.95) (P < 0.05). The 1‐minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05).
Data Conclusion
FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC.
Level of Evidence
1
Technical Efficacy
4
Abstract Objective To develop a method for the assessment and characterization of 3D geometric distortion as part of routine quality assurance for MRI scanners commissioned for Radiation Therapy ...planning. Materials and Methods In this study, the in-plane and through-plane geometric distortion on a 1.5T GE MRI-SIM unit are characterized and the 2D and 3D correction algorithms provided by the vendor are evaluated. We used a phantom developed by GE Healthcare that covers a large field of view of 500mm, and consists of layers of foam embedded with a matrix of ellipsoidal markers. An in-house Java-based software module was developed to automatically assess the geometric distortion by calculating the center of each marker using the center of mass method, correcting of gross rotation errors and comparing the corrected positions with a CT gold standard data set. Spatial accuracy of typical pulse sequences used in RT planning was assessed (2D T1/T2 FSE, 3D CUBE, T1 SPGR) using the software. The accuracy of vendor specific geometric distortion correction (GDC) algorithms was quantified by measuring distortions before and after the application of the 2D and 3D correction algorithms. Results Our algorithm was able to accurately calculate geometric distortion with sub-pixel precision. For all typical MR sequences used in Radiotherapy, the vendors GDC were able to substantially reduce the distortions. Our results showed also that the impact of the acquisition produced a maximum variation of 0.2mm over a radial distance of 200mm. It has been shown that while the 2D correction algorithm remarkably reduces the in-plane geometric distortion, 3D geometric distortion further reduced the geometric distortion by correcting both in-plane and through-palne distortion in all acquisitions. Conclusion The presented methods represent a valuable tool for routine quality assurance of MR applications that require stringent spatial accuracy assessment such as radiotherapy. The phantom used in this study provides three dimensional arrays of control points. These tools and the detailed results can be also used for developing new geometric distortion correction algorithms or improving the existing ones.
Purpose
A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to ...therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.
OBJECTIVESQuantitative synthetic magnetic resonance imaging (MRI) enables synthesis of various contrast-weighted images as well as simultaneous quantification of T1 and T2 relaxation times and proton ...density. However, to date, it has been challenging to generate magnetic resonance angiography (MRA) images with synthetic MRI. The purpose of this study was to develop a deep learning algorithm to generate MRA images based on 3D synthetic MRI raw data.
MATERIALS AND METHODSEleven healthy volunteers and 4 patients with intracranial aneurysms were included in this study. All participants underwent a time-of-flight (TOF) MRA sequence and a 3D-QALAS synthetic MRI sequence. The 3D-QALAS sequence acquires 5 raw images, which were used as the input for a deep learning network. The input was converted to its corresponding MRA images by a combination of a single-convolution and a U-net model with a 5-fold cross-validation, which were then compared with a simple linear combination model. Image quality was evaluated by calculating the peak signal-to-noise ratio (PSNR), structural similarity index measurements (SSIMs), and high frequency error norm (HFEN). These calculations were performed for deep learning MRA (DL-MRA) and linear combination MRA (linear-MR), relative to TOF-MRA, and compared with each other using a nonparametric Wilcoxon signed-rank test. Overall image quality and branch visualization, each scored on a 5-point Likert scale, were blindly and independently rated by 2 board-certified radiologists.
RESULTSDeep learning MRA was successfully obtained in all subjects. The mean PSNR, SSIM, and HFEN of the DL-MRA were significantly higher, higher, and lower, respectively, than those of the linear-MRA (PSNR, 35.3 ± 0.5 vs 34.0 ± 0.5, P < 0.001; SSIM, 0.93 ± 0.02 vs 0.82 ± 0.02, P < 0.001; HFEN, 0.61 ± 0.08 vs 0.86 ± 0.05, P < 0.001). The overall image quality of the DL-MRA was comparable to that of TOF-MRA (4.2 ± 0.7 vs 4.4 ± 0.7, P = 0.99), and both types of images were superior to that of linear-MRA (1.5 ± 0.6, for both P < 0.001). No significant differences were identified between DL-MRA and TOF-MRA in the branch visibility of intracranial arteries, except for ophthalmic artery (1.2 ± 0.5 vs 2.3 ± 1.2, P < 0.001).
CONCLUSIONSMagnetic resonance angiography generated by deep learning from 3D synthetic MRI data visualized major intracranial arteries as effectively as TOF-MRA, with inherently aligned quantitative maps and multiple contrast-weighted images. Our proposed algorithm may be useful as a screening tool for intracranial aneurysms without requiring additional scanning time.
OBJECTIVESThe aims of this study were to develop an accelerated multiparametric magnetic resonance imaging method based on 3D-quantification using an interleaved Look-Locker acquisition sequence with ...a T2 preparation pulse (3D-QALAS) combined with compressed sensing (CS) and to evaluate the effect of CS on the quantitative mapping, tissue segmentation, and quality of synthetic images.
MATERIALS AND METHODSA magnetic resonance imaging system phantom, containing multiple compartments with standardized T1, T2, and proton density (PD) values; 10 healthy volunteers; and 12 patients with multiple sclerosis were scanned using the 3D-QALAS sequence with and without CS and conventional contrast-weighted imaging. The scan times of 3D-QALAS with and without CS were 5:56 and 11:11, respectively. For healthy volunteers, brain volumetry and myelin estimation were performed based on the measured T1, T2, and PD. For patients with multiple sclerosis, the mean T1, T2, PD, and the amount of myelin in plaques and contralateral normal-appearing white matter (NAWM) were measured. Simple linear regression analysis and Bland-Altman analysis were performed for each metric obtained from the datasets with and without CS. To compare overall image quality and structural delineations on synthetic and conventional contrast-weighted images, case-control randomized reading sessions were performed by 2 neuroradiologists in a blinded manner.
RESULTSThe linearity of both phantom and volunteer measurements in T1, T2, and PD values obtained with and without CS was very strong (R = 0.9901–1.000). The tissue segmentation obtained with and without CS also had high linearity (R = 0.987–0.999). The quantitative tissue values of the plaques and NAWM obtained with CS showed high linearity with those without CS (R = 0.967–1.000). There were no significant differences in overall image quality between synthetic contrast-weighted images obtained with and without CS (P = 0.17–0.99).
CONCLUSIONSMultiparametric imaging of the whole brain based on 3D-QALAS can be accelerated using CS while preserving tissue quantitative values, tissue segmentation, and quality of synthetic images.
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