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During fibroproliferation, protein-associated extracellular aldehydes are formed by the oxidation of lysine residues on extracellular matrix proteins to form the aldehyde allysine. Here we report three Mn(II)-based, small molecule magnetic resonance (MR) probes that contain α-effect nucleophiles to target allysine in vivo and report on tissue fibrogenesis. We used a rational design approach to develop turn-on probes with a 4-fold increase in relaxivity upon targeting. The effects of aldehyde condensation rate and hydrolysis kinetics on the performance of the probes to detect tissue fibrogenesis noninvasively in mouse models were evaluated by a systemic aldehyde tracking approach. We showed that for highly reversible ligations, off-rate was a stronger predictor of in vivo efficiency, enabling histologically validated, three-dimensional characterization of pulmonary fibrogenesis throughout the entire lung. The exclusive renal elimination of these probes allowed for rapid imaging of liver fibrosis. Reducing the hydrolysis rate by forming an oxime bond with allysine enabled delayed phase imaging of kidney fibrogenesis. The imaging efficacy of these probes, coupled with their rapid and complete elimination from the body, make them strong candidates for clinical translation.

Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R2 = 0.98, p Grade = 2.4 ± 0.4, ISGrade = 2.7 ± 0.3, IQRank = 3.7 ± 0.3, ISRank = 3.9 ± 0.3) compared to MEDI (IQGrade = 2.1 ± 0.5, ISGrade = 2.1 ± 0.6, IQRank = 2.4 ± 0.6, ISRank = 2.9 ± 0.2) and FANSI-TGV (IQGrade = 2.2 ± 0.6, ISGrade = 2.1 ± 0.6, IQRank = 2.7 ± 0.3, ISRank = 2.2 ± 0.2). We illustrated the modularity of PnP QSM by interchanging two additional patch-based denoisers. PnP QSM reconstruction was feasible, and its flexibility was shown using several patch-based denoisers. This technique may allow rapid prototyping and validation of new denoisers for QSM reconstruction for an array of useful clinical applications.

OBJECTIVES Clinical assessment of uterine artery (UtA) hemodynamics is currently limited to Doppler ultrasound (US) velocimetry. We have demonstrated previously the feasibility of applying four-dimensional (4D) flow magnetic resonance imaging (MRI) to evaluate UtA hemodynamics during pregnancy, allowing flow quantification of the entire course of the vessel. In this study, we sought to further validate the physiological relevance of 4D flow MRI measurement of UtA blood flow by exploring its association with pregnancy outcome relative to US-based metrics. METHODS Recruited into this prospective, cross-sectional study were 87 women with a singleton pregnancy who underwent 4D flow MRI between May 2016 and April 2019 to measure the UtA pulsatility index (MRI-PI) and blood flow rate (MRI-flow, in mL/min). UtA-PI was also measured using US (US-PI). The primary outcome was a composite (COMP) of pre-eclampsia (PE) and/or small-for-gestational-age (SGA) neonate, and secondary outcomes were PE and SGA neonate individually. We assessed the ability of MRI-flow, MRI-PI and US-PI to distinguish between outcomes, and evaluated whether MRI-flow changed as gestation progressed. RESULTS Following 4D flow postprocessing and exclusions from the analysis, 74 women had 4D flow MRI data analyzed for both UtAs. Of these, 18 developed a COMP outcome: three developed PE only, 11 had a SGA neonate only and four had both. A comparison of the COMP group vs the no-COMP group found no differences in maternal age, body mass index, nulliparity, gravidity or race. For 66 of the 74 subjects, US data were also available. In these subjects, both median MRI-PI (0.95 vs 0.70; P

Quantitative susceptibility mapping employs regularization to reduce artifacts, yet many recent denoisers are unavailable for reconstruction. We developed a plug-and-play approach to QSM reconstruction (PnP QSM) and show its flexibility using several patch-based denoisers. We developed PnP QSM using alternating direction method of multiplier framework and applied collaborative filtering denoisers. We apply the technique to the 2016 QSM Challenge and in 10 glioblastoma multiforme datasets. We compared its performance with four published QSM techniques and a multi-orientation QSM method. We analyzed magnetic susceptibility accuracy using brain region-of-interest measurements, and image quality using global error metrics. Reconstructions on glioblastoma data were analyzed using ranked and semiquantitative image grading by three neuroradiologist observers to assess image quality (IQ) and sharpness (IS). PnP-BM4D QSM showed good correlation (β = 0.84, R

The purpose of this systematic review is to identify trends and extent of variability in intracranial vessel wall MR imaging (VWI) techniques and protocols. Although variability in selection of protocol design and pulse sequence type is known, data on what and how protocols vary are unknown. Three databases were searched to identify publications using intracranial VWI. Publications were screened by predetermined inclusion/exclusion criteria. Technical development publications were scored for completeness of reporting using a modified Nature Reporting Summary Guideline to assess reproducibility. From 2,431 articles, 122 met the inclusion criteria. Trends over the last 23 years (1995-2018) show increased use of 3-Tesla MR (P < .001) and 3D volumetric T1-weighted acquisitions (P < .001). Most (65%) clinical VWI publications report achieving a noninterpolated in-plane spatial resolution of ≤.55 mm. In the last decade, an increasing number of technical development (n = 20) and 7 Tesla (n = 12) publications have been published, focused on pulse sequence development, improving cerebrospinal fluid suppression, scan efficiency, and imaging ex vivo specimen for histologic validation. Mean Reporting Summary Score for the technical development publications was high (.87, range: .63-1.0) indicating strong scientific technical reproducibility. Innovative work continues to emerge to address implementation challenges. Gradual adoption into the research and scientific community was suggested by a shift in the name in the literature from "high-resolution MR" to "vessel wall imaging," specifying diagnostic intent. Insight into current practices and identifying the extent of technical variability in the literature will help to direct future clinical and technical efforts to address needs for implementation.

Purpose Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, we investigated MRI to quantify iron as an imaging biomarker for TAMs in GBM patients. Methods 21 adult patients with GBM underwent a 3D single echo gradient echo MRI sequence and quantitative susceptibility maps were generated. In 3 subjects, ex vivo imaging of surgical specimens was performed on a 9.4 Tesla MRI using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated. Each specimen was stained with hematoxylin and eosin, as well as CD68, CD86, CD206, and L-Ferritin. Results Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r =0.56, p=0.018) and the combination of tumor’s enhancing zone and necrotic core and the L-Ferritin positivity percent (r=0.72; p=0.001). The mean susceptibility significantly correlated with positivity percent for CD68 (ρ = 0.52, p=0.034) and CD86 (r=0.7 p=0.001), but not for CD206 (ρ = 0.09; p=0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r =0.6, p=0.016). Similarly, mean R2* values significantly correlated with CD86 (r=0.54, p=0.03) but not with CD206 (r=0.15, p=0.5). Conclusion MR quantitative susceptibility mapping can quantify the iron content of GBM and provide a non-invasive method for TAM quantification and phenotyping.

BACKGROUND Uterine artery (UtA) hemodynamics might be used to predict risk of hypertensive pregnancy disorders, including preeclampsia and intrauterine growth restriction. PURPOSE OR HYPOTHESIS To determine the feasibility of 4D flow MRI in pregnant subjects by characterizing UtA anatomy, computing UtA flow, and comparing UtA velocity, and pulsatility and resistivity indices (PI, RI) with transabdominal Doppler ultrasound (US). STUDY TYPE Prospective cross-sectional study from June 6, 2016, to May 2, 2018. POPULATION OR SUBJECTS OR PHANTOM OR SPECIMEN OR ANIMAL MODEL Forty-one singleton pregnant subjects (age [range] = 27.0 ± 5.9 [18-41] years) in their second or third trimester. We additionally scanned three subjects who had prepregnancy diabetes or chronic hypertension. FIELD STRENGTH/SEQUENCE The subjects underwent UtA and placenta MRI using noncontrast angiography and 4D flow at 1.5T. ASSESSMENT UtA anatomy was described based on 4D flow-derived noncontrast angiography, while UtA flow properties were characterized by net flow, systolic/mean/diastolic velocity, PI and RI through examination of 4D flow data. PI and RI are standard hemodynamic parameters routinely reported on Doppler US. STATISTICAL TESTS Spearman's rank correlation, Wilcoxon signed rank tests, and Bland-Altman plots were used to preliminarily investigate the relationships between flow parameters, gestational age, and Doppler US. or RESULTS: 4D flow MRI and UtA flow quantification was feasible in all subjects. There was considerable heterogeneity in UtA geometry in each subject between left and right UtAs and between subjects. Mean 4D flow-based parameters were: mean bilateral flow rate = 605.6 ± 220.5 mL/min, PI = 0.72 ± 0.2, and RI = 0.47 ± 0.1. Bilateral flow did not change with gestational age. We found that MRI differed from US in terms of lower PI (mean difference -0.1) and RI (mean difference

Conventional X-ray mammography has low diagnostic sensitivity for women with dense breasts. As a result, alternative contrast-enhanced screening tools such as dual energy mammography (DEM), computed tomography (CT), magnetic resonance imaging (MRI), and near-infrared fluorescence (NIRF) imaging are being used or investigated for these women. However, currently available contrast agents are non-ideal, have safety issues, and each imaging technique requires a different contrast agent. We therefore sought to develop a multimodal contrast agent that is functional for each breast imaging modality to simplify the diagnosis process and address the issues of existing contrast agents. Herein, we present a novel “all-in-one” nanoparticle (AION) multimodal imaging probe that has potent DEM, CT, MRI, and NIRF contrast properties and improved biocompatibility. AION were formed by co-encapsulation of a near-infrared fluorophore (DiR), silver sulfide nanoparticles (Ag(2)S-NP), and iron oxide nanoparticles (IO-NP) in PEGylated micelles. AION showed negligible cytotoxicity, which was in agreement with its minimal silver ion release profiles. AION generated strong contrast with all imaging modalities as demonstrated in phantom imaging. AION allowed in vivo tumor imaging as evidenced by the increase in contrast after injection. This study indicates the potential of AION as an effective multimodal contrast agent for breast cancer diagnosis with a range of imaging methods.

PURPOSE: To perform automated myocardial segmentation and uptake classification from whole-body fluorine 18 fluorodeoxyglucose (FDG) PET. MATERIALS AND METHODS: In this retrospective study, consecutive patients who underwent FDG PET imaging for oncologic indications were included (July–August 2018). The left ventricle (LV) on whole-body FDG PET images was manually segmented and classified as showing no myocardial uptake, diffuse uptake, or partial uptake. A total of 609 patients (mean age, 64 years ± 14 [standard deviation]; 309 women) were included and split between training (60%, 365 patients), validation (20%, 122 patients), and testing (20%, 122 patients) datasets. Two sequential neural networks were developed to automatically segment the LV and classify the myocardial uptake pattern using segmentation and classification training data provided by human experts. Linear regression was performed to correlate findings from human experts and deep learning. Classification performance was evaluated using receiver operating characteristic (ROC) analysis. RESULTS: There was moderate agreement of uptake pattern between experts and deep learning (as a fraction of correctly categorized images) with 78% (36 of 46) for no uptake, 71% (34 of 48) for diffuse uptake, and 71% (20 of 28) for partial uptake. There was no bias in LV volume for partial or diffuse uptake categories (P = .56); however, deep learning underestimated LV volumes in the no uptake category. There was good correlation for LV volume (R(2) = 0.35, b = .71). ROC analysis showed the area under the curve for classifying no uptake and diffuse uptake was high (> 0.90) but lower for partial uptake (0.77). The feasibility of a myocardial uptake index (MUI) for quantifying the degree of myocardial activity patterns was shown, and there was excellent visual agreement between MUI and uptake patterns. CONCLUSION: Deep learning was able to segment and classify myocardial uptake patterns on FDG PET images. Keywords: PET, Heart, Computer Aided Diagnosis, Computer Application-Detection/Diagnosis Supplemental material is available for this article. ©RSNA, 2021

BACKGROUND: Quantitative susceptibility mapping (QSM) uses prior information to reconstruct maps, but prior information may not show pathology and introduce inconsistencies with susceptibility maps, degrade image quality and inadvertently smoothing image features. PURPOSE: To develop a local field data-driven QSM reconstruction that does not depend on spatial edge prior information. STUDY TYPE: Retrospective. SUBJECTS, ANIMAL MODELS: A dataset from 2016 ISMRM QSM Challenge, 11 patients with glioblastoma, a patient with microbleeds and porcine heart. SEQUENCE/FIELD STRENGTH: 3D gradient echo sequence on 3T and 7T scanners. ASSESSMENT: Accuracy was compared to Calculation of Susceptibility through Multiple Orientation Sampling (COSMOS), and several published techniques using region of interest (ROI) measurements, root-mean-squared error (RMSE), structural similarity index metric (SSIM), and high-frequency error norm (HFEN). Numerical ranking and semiquantitative image grading was performed by three expert observers to assess overall image quality (IQ) and image sharpness (IS). STATISTICAL TESTS: Bland–Altman, Friedman test, and Conover multiple comparisons. RESULTS: Loss adaptive dipole inversion (LADI) (β = 0.82, R(2) = 0.96), morphology-enabled dipole inversion (MEDI) (β = 0.91, R(2) = 0.97), and fast nonlinear susceptibility inversion (FANSI) (β = 0.81, R(2) = 0.98) had excellent correlation with COSMOS and no bias was detected (bias = 0.006 ± 0.014, P < 0.05). In glioblastoma patients, LADI showed consistently better performance (IQ(Grade) = 2.6 ± 0.4, IS(Grade) = 2.6 ± 0.3, IQ(Rank) = 3.5 ± 0.4, IS(Rank) = 3.9 ± 0.2) compared with MEDI (IQ(Grade) = 2.1 ± 0.3, IS(Grade) = 2 ± 0.5, IQ(Rank) = 2.4 ± 0.5, IS(Rank) = 2.8 ± 0.2) and FANSI (IQ(Grade) = 2.2 ± 0.5, IS(Grade) = 2 ± 0.4, IQ(Rank) = 2.8 ± 0.3, IS(Rank) = 2.1 ± 0.2). Dark artifact visible near the infarcted region in MEDI (Inf(MEDI) = −0.27 ± 0.06 ppm) was better mitigated by FANSI (Inf(FANSI-TGV) = −0.17 ± 0.05 ppm) and LADI (Inf(LADI) = −0.18 ± 0.05 ppm). CONCLUSION: For neuroimaging applications, LADI preserved image sharpness and fine features in glioblastoma and microbleed patients. LADI performed better at mitigating artifacts in cardiac QSM. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY STAGE: 1

Background Endogenous contrast T1ρ cardiovascular magnetic resonance (CMR) can detect scar or infiltrative fibrosis in patients with ischemic or non-ischemic cardiomyopathy. Existing 2D T1ρ techniques have limited spatial coverage or require multiple breath-holds. The purpose of this project was to develop an accelerated, free-breathing 3D T1ρ mapping sequence with whole left ventricle coverage using a multicoil, compressed sensing (CS) reconstruction technique for rapid reconstruction of undersampled k-space data. Methods We developed a cardiac- and respiratory-gated, free-breathing 3D T1ρ sequence and acquired data using a variable-density k-space sampling pattern (A = 3). The effect of the transient magnetization trajectory, incomplete recovery of magnetization between T1ρ-preparations (heart rate dependence), and k-space sampling pattern on T1ρ relaxation time error and edge blurring was analyzed using Bloch simulations for normal and chronically infarcted myocardium. Sequence accuracy and repeatability was evaluated using MnCl2 phantoms with different T1ρ relaxation times and compared to 2D measurements. We further assessed accuracy and repeatability in healthy subjects and compared these results to 2D breath-held measurements. Results The error in T1ρ due to incomplete recovery of magnetization between T1ρ-preparations was T1ρhealthy = 6.1% and T1ρinfarct = 10.8% at 60 bpm and T1ρhealthy = 13.2% and T1ρinfarct = 19.6% at 90 bpm. At a heart rate of 60 bpm, error from the combined effects of readout-dependent magnetization transients, k-space undersampling and reordering was T1ρhealthy = 12.6% and T1ρinfarct = 5.8%. CS reconstructions had improved edge sharpness (blur metric = 0.15) compared to inverse Fourier transform reconstructions (blur metric = 0.48). There was strong agreement between the mean T1ρ estimated from the 2D and accelerated 3D data (R2 = 0.99; P

Acidosis within tumor and kidney tissues has previously been quantitatively measured using a molecular imaging technique known as acidoCEST MRI. The previous studies used iopromide and iopamidol, two iodinated contrast agents that are approved for clinical CT diagnoses and have been repurposed for acidoCEST MRI studies. We aimed to compare the performance of the two agents for measuring pH by optimizing image acquisition conditions, correlating pH with a ratio of CEST effects from an agent, and evaluating the effects of concentration, endogenous T1 relaxation time and temperature on the pH-CEST ratio correlation for each agent. These results showed that the two agents had similar performance characteristics, although iopromide produced a pH measurement with a higher dynamic range while iopamidol produced a more precise pH measurement. We then compared the performance of the two agents to measure in vivo extracellular pH (pHe) within xenograft tumor models of Raji lymphoma and MCF-7 breast cancer. Our results showed that the pHe values measured with each agent were not significantly different. Also, iopromide consistently measured a greater region of the tumor relative to iopamidol in both tumor models. Therefore, an iodinated contrast agent for acidoCEST MRI should be selected based on the measurement properties needed for a specific biomedical study and the pharmacokinetic properties of a specific tumor model.

We aimed to develop pixelwise maps of tumor acidosis to aid in evaluating extracellular tumor pH (pHe) in cancer biology.MCF-7 and MDA-MB-231 mouse models were imaged during a longitudinal study. AcidoCEST MRI and a series of image processing methods were used to produce parametric maps of tumor pHe, and tumor pHe was also measured with a pH microsensor.Sufficient contrast-to-noise for producing pHe maps was achieved by using standard image processing methods. A comparison of pHe values measured with acidoCEST MRI and a pH microsensor showed that acidoCEST MRI measured tumor pHe with an accuracy of 0.034 pH units. The MCF-7 tumor model was found to be more acidic compared to the MDA-MB-231 tumor model. The pHe was not related to tumor size during the longitudinal study.These results show that acidoCEST MRI can create pixelwise tumor pHe maps of mouse models of cancer.

Acidosis within tumor and kidney tissues has previously been quantitatively measured using a molecular imaging technique known as acidoCEST MRI. The previous studies used iopromide and iopamidol, two iodinated contrast agents that are approved for clinical CT diagnoses and have been repurposed for acidoCEST MRI studies. We aimed to compare the performance of the two agents for measuring pH by optimizing image acquisition conditions, correlating pH with a ratio of CEST effects from an agent, and evaluating the effects of concentration, endogenous T1 relaxation time and temperature on the pH-CEST ratio correlation for each agent. These results showed that the two agents had similar performance characteristics, although iopromide produced a pH measurement with a higher dynamic range while iopamidol produced a more precise pH measurement. We then compared the performance of the two agents to measure in vivo extracellular pH (pHe) within xenograft tumor models of Raji lymphoma and MCF-7 breast cancer. Our results showed that the pHe values measured with each agent were not significantly different. Also, iopromide consistently measured a greater region of the tumor relative to iopamidol in both tumor models. Therefore, an iodinated contrast agent for acidoCEST MRI should be selected based on the measurement properties needed for a specific biomedical study and the pharmacokinetic properties of a specific tumor model.