Quantitative susceptibility-weighted imaging in presence of strong susceptibility sources: Application to hemorrhage

De, Ashmita; Sun, Hongfu; Emery, Derek; Butcher, Kenneth; Wilman, Alan H.

doi:10.1016/j.mri.2022.06.010

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…63,66 Streaking artifacts may arise from strong susceptibility sources near borders and within the brain, where the Gaussian noise model breaks down and field estimation becomes erroneous. 106 These artifacts may be suppressed by masking out or reducing the weight of less trustworthy voxels, 106 improving the brain mask, 111,179,180 preconditioning, 181,182 and using in-painting techniques such as MERIT 106 and L 1 data fidelity. 183 Shadowing artifacts may arise from residual background fields.…”

Section: Overviewmentioning

confidence: 99%

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group

Bilgic,

Costagli,

Chan

et al. 2024

Magnetic Resonance in Med

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This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro‐Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi‐echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi‐echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase‐quality‐based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity‐based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

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Section: Overviewmentioning

confidence: 99%

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group

Bilgic,

Costagli,

Chan

et al. 2024

Magnetic Resonance in Med

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show abstract

“…SWI produces a qualitative image; in contrast, QSM produces a quantitative image independent of the imaging parameters. Moreover, unlike SWI, blooming artifacts and phase wrapping are not observed with QSM, which enables reliable monitoring of hemorrhage [ 9 , 10 ]. QSM consists of the processing phase and magnitude images reconstructed from real and imaginary images acquired using three-dimensional (3D) multi-echo GRE.…”

Section: Introductionmentioning

confidence: 99%

“…QSM can be performed using dipole field inversion operations [ 11 ]. Several studies have used SWI and QSM for the evaluation of ICH [ 6 , 9 , 12 ], and a good correlation has been observed between the hemorrhage volumes calculated using CT and QSM [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Quantitative Susceptibility Mapping and Amide Proton Transfer-Chemical Exchange Saturation Transfer for the Evaluation of Intracerebral Hemorrhage Model

Sawaya

Ueda

Saito

2023

IJMS

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This study aimed to evaluate an intracerebral hemorrhage (ICH) model using quantitative susceptibility mapping (QSM) and chemical exchange saturation transfer (CEST) with preclinical 7T-magnetic resonance imaging (MRI) and determine the potential of amide proton transfer-CEST (APT-CEST) for use as a biomarker for the early detection of ICH. Six Wistar male rats underwent MRI, and another six underwent histopathological examinations on postoperative days 0, 3, and 7. The ICH model was created by injecting bacterial collagenase into the right hemisphere of the brain. QSM and APT-CEST MRI were performed using horizontal 7T-MRI. Histological studies were performed to observe ICH and detect iron deposition at the ICH site. T2-weighted images (T2WI) revealed signal changes associated with hemoglobin degeneration in red blood cells, indicating acute-phase hemorrhage on day 0, late-subacute-phase hemorrhage on day 3, and chronic-phase hemorrhage on day 7. The susceptibility alterations in each phase were detected using QSM. QSM and Berlin blue staining revealed hemosiderin deposition in the chronic phase. APT-CEST revealed high magnetization transfer ratios in the acute phase. Abundant mobile proteins and peptides were observed in early ICH, which were subsequently diluted. APT-CEST imaging may be a reliable noninvasive biomarker for the early diagnosis of ICH.

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“…Previously, both in vivo and in vitro imaging of hematoma and animal blood clot phantom has reported a significantly higher susceptibility. [22][23][24][25] In this prospective serial MRI study, we aimed to evaluate the progression of coagulation within the hematomas of patients with acute ICH to develop a noninvasive imaging biomarker for coagulopathy.…”

mentioning

confidence: 99%

Dynamic Imaging of Blood Coagulation Within the Hematoma of Patients With Acute Hemorrhagic Stroke

Haque,

Boren,

Mills

et al. 2024

Stroke

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BACKGROUND: The dynamics of blood clot (combination of Hb [hemoglobin], fibrin, and a higher concentration of aggregated red blood cells) formation within the hematoma of an intracerebral hemorrhage is not well understood. A quantitative neuroimaging method of localized coagulated blood volume/distribution within the hematoma might improve clinical decision-making. METHODS: The deoxyhemoglobin of aggregated red blood cells within extravasated blood exhibits a higher magnetic susceptibility due to unpaired heme iron electrons. We propose that coagulated blood, with higher aggregated red blood cell content, will exhibit (1) a higher positive susceptibility than noncoagulated blood and (2) increase in fibrin polymerization–restricted localized diffusion, which can be measured noninvasively using quantitative susceptibility mapping and diffusion tensor imaging. In this serial magnetic resonance imaging study, we enrolled 24 patients with acute intracerebral hemorrhage between October 2021 to May 2022 at a stroke center. Patients were 30 to 70 years of age and had a hematoma volume >15 cm 3 and National Institutes of Health Stroke Scale score >1. The patients underwent imaging 3×: within 12 to 24 (T1), 36 to 48 (T2), and 60 to 72 (T3) hours of last seen well on a 3T magnetic resonance imaging system. Three-dimensional anatomic, multigradient echo and 2-dimensional diffusion tensor images were obtained. Hematoma and edema volumes were calculated, and the distribution of coagulation was measured by dynamic changes in the susceptibilities and fractional anisotropy within the hematoma. RESULTS: Using a coagulated blood phantom, we demonstrated a linear relationship between the percentage coagulation and susceptibility (R 2 =0.91) with a positive red blood cell stain of the clot. The quantitative susceptibility maps showed a significant increase in hematoma susceptibility (T1, 0.29±0.04 parts per millions; T2, 0.36±0.04 parts per millions; T3, 0.45±0.04 parts per millions; P <0.0001). A concomitant increase in fractional anisotropy was also observed with time (T1, 0.40±0.02; T2, 0.45±0.02; T3, 0.47±0.02; P <0.05). CONCLUSIONS: This quantitative neuroimaging study of coagulation within the hematoma has the potential to improve patient management, such as safe resumption of anticoagulants, the need for reversal agents, the administration of alteplase to resolve the clot, and the need for surgery.

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Quantitative susceptibility-weighted imaging in presence of strong susceptibility sources: Application to hemorrhage

Cited by 4 publications

References 28 publications

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro‐magnetic tissue properties study group

Quantitative Susceptibility Mapping and Amide Proton Transfer-Chemical Exchange Saturation Transfer for the Evaluation of Intracerebral Hemorrhage Model

Dynamic Imaging of Blood Coagulation Within the Hematoma of Patients With Acute Hemorrhagic Stroke

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