quantitative susceptibility mapping
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2022 ◽  
Vol 12 ◽  
Author(s):  
Huimin Mao ◽  
Weiqiang Dou ◽  
Xinyi Wang ◽  
Kunjian Chen ◽  
Xinyu Wang ◽  
...  

Purpose: This study aimed to use quantitative susceptibility mapping (QSM) to systematically investigate the changes of iron content in gray matter (GM) nuclei in patients with long-term anterior circulation artery stenosis (ACAS) and posterior circulation artery stenosis (PCAS).Methods: Twenty-five ACAS patients, 25 PCAS patients, and 25 age- and sex-matched healthy controls underwent QSM examination. Patients were scored using the National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS) to assess the degree of neural function deficiency. On QSM images, iron related susceptibility of GM nuclei, including bilateral caudate nucleus, putamen (PU), globus pallidus (GP), thalamus (TH), substantia nigra (SN), red nucleus, and dentate nucleus (DN), were assessed. Susceptibility was compared between bilateral GM nuclei in healthy controls, ACAS patients, and PCAS patients. Partial correlation analysis, with age as a covariate, was separately performed to assess the relationships of susceptibility with NIHSS and mRS scores.Results: There were no significant differences between the susceptibilities for left and right hemispheres in all seven GM nucleus subregions for healthy controls, ACAS patients, and PCAS patients. Compared with healthy controls, mean susceptibility of bilateral PU, GP, and SN in ACAS patients and of bilateral PU, GP, SN, and DN in PCAS patients were significantly increased (all P < 0.05). In addition, mean susceptibility of bilateral TH and SN in PCAS patients was significantly higher than in ACAS patients (both P < 0.05). With partial correlation analysis, mean susceptibility at bilateral PU of ACAS patients was significantly correlated with mRS score (r = 0.415, P < 0.05), and at bilateral PU in PCAS patients was correlated with NIHSS score (r = 0.424, P < 0.05).Conclusion: Our findings indicated that abnormal iron metabolism may present in different subregions of GM nuclei after long-term ACAS and PCAS. In addition, iron content of PU in patients with ACAS and PCAS was correlated with neurological deficit scores. Therefore, iron quantification measured by QSM susceptibility may provide a new insight to understand the pathological mechanism of ischemic stroke caused by ACAS and PCAS.


2021 ◽  
pp. 0271678X2110651
Author(s):  
Brenda L Bartnik-Olson ◽  
Arlin B Blood ◽  
Michael H Terry ◽  
Shawn FL Hanson ◽  
Christopher Day ◽  
...  

Prominence of cerebral veins using susceptibility weighted magnetic resonance imaging (SWI) has been used as a qualitative indicator of cerebral venous oxygenation (CvO2). Quantitative susceptibility mapping (QSM) adds more precision to the assessment of CvO2, but has not been applied to neonatal hypoxic ischemic injury (HII). We proposed to study QSM measures of venous susceptibility and their correlation with direct measures of brain oxygenation and cerebral blood flow (CBF) in the neonatal piglet. The association of QSM intravascular cerebral venous susceptibility, with brain tissue O2 tension, CBF, cortical tissue oxyhemoglobin saturation, and the partial pressure of oxygen in arterial blood measurement during various oxygenation states was determined by linear regression. Compared to normoxia, venous susceptibility in the straight sinus increased 56.8 ± 25.4% during hypoxia, while decreasing during hyperoxia (23.5 ± 32.9%) and hypercapnia (23.3 ± 73.1%), which was highly correlated to all other measures of oxygenation (p < 0.0001) but did not correlate to CBF (p = 0.82). These findings demonstrate a strong relationship between venous susceptibility and brain tissue O2 tension. Our results suggest that QSM-derived venous susceptibility is sensitive to cerebral oxygenation status across various oxygenation states.


2021 ◽  
Vol 15 ◽  
Author(s):  
Zichun Yan ◽  
Huan Liu ◽  
Xiaoya Chen ◽  
Qiao Zheng ◽  
Chun Zeng ◽  
...  

Objectives: To implement a machine learning model using radiomic features extracted from quantitative susceptibility mapping (QSM) in discriminating multiple sclerosis (MS) from neuromyelitis optica spectrum disorder (NMOSD).Materials and Methods: Forty-seven patients with MS (mean age = 40.00 ± 13.72 years) and 36 patients with NMOSD (mean age = 42.14 ± 12.34 years) who underwent enhanced gradient-echo T2*-weighted angiography (ESWAN) sequence in 3.0-T MRI were included between April 2017 and October 2019. QSM images were reconstructed from ESWAN, and QSM-derived radiomic features were obtained from seven regions of interest (ROIs), including bilateral putamen, globus pallidus, head of the caudate nucleus, thalamus, substantia nigra, red nucleus, and dentate nucleus. A machine learning model (logistic regression) was applied to classify MS and NMOSD, which combined radiomic signatures and demographic information to assess the classification accuracy using the area under the receiver operating characteristic (ROC) curve (AUC).Results: The radiomics-only models showed better discrimination performance in almost all deep gray matter (DGM) regions than the demographic information-only model, with the highest AUC in DN of 0.902 (95% CI: 0.840–0.955). Moreover, the hybrid model combining radiomic signatures and demographic information showed the highest discrimination performance which achieved the AUC of 0.927 (95% CI: 0.871–0.984) with fivefold cross-validation.Conclusion: The hybrid model based on QSM and powered with machine learning has the potential to discriminate MS from NMOSD.


2021 ◽  
Vol 17 (S1) ◽  
Author(s):  
Oluwatobi F Adeyemi ◽  
Olivier Mougin ◽  
Richard Bowtell ◽  
Gowland Penny ◽  
Akram A. Hosseini

NeuroImage ◽  
2021 ◽  
Vol 244 ◽  
pp. 118574
Author(s):  
Marta Lancione ◽  
Mauro Costagli ◽  
Giacomo Handjaras ◽  
Michela Tosetti ◽  
Emiliano Ricciardi ◽  
...  

2021 ◽  
Author(s):  
Oliver C. Kiersnowski ◽  
Anita Karsa ◽  
Stephen J. Wastling ◽  
John S. Thornton ◽  
Karin Shmueli

Purpose: Quantitative susceptibility mapping (QSM) is increasingly used for clinical research where oblique image acquisition is commonplace but its effects on QSM accuracy are not well understood. Theory and Methods: The QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic field B0 with respect to the acquired image volume axes. The direction of B0 is dependent upon the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in-vivo acquisitions, we analysed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the root-mean-squared error and QSM-tuned structural similarity index (XSIM). Results: Rotation of wrapped phase images gave severe artefacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment with B0. LBV and VSHARP background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularisation and weighted linear total variation regularisation all performed most accurately when local field maps were rotated into alignment with B0 before susceptibility calculation. Conclusion: For accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment with B0 should be carried out after phase unwrapping and before background field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.


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