Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke

Gaddamanugu, Siddhartha; Shafaat, Omid; Sotoudeh, Houman; Sarrami, Amir Hossein; Rezaei, Abbas; Saadatpour, Zahra; Singhal, Aparna

doi:10.1007/s00234-021-02819-3

Cited by 24 publications

(15 citation statements)

References 85 publications

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“…Accordingly, we acquired the T1W and ADC value brain maps sequentially in the sham-operation group 14 min after BOPTA-Gd injection. Glymphatic transport kinetics were determined based on the SI in T1WIs, while cytotoxic edema was identified as cases of DWI hyperintensity with reduced diffusion and with ADC dark signal ( 27 ). When we measured molecular motion with DWI, only the ADC value was calculated.…”

Section: Resultsmentioning

confidence: 99%

Impaired Glymphatic Transport Kinetics Following Induced Acute Ischemic Brain Edema in a Mouse pMCAO Model

et al. 2022

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BackgroundCerebral edema forms immediately after blood flow interruption in ischemic stroke, which largely increased the death and disability. The glymphatic (glial-lymphatic) pathway is a major regulator of the brain liquid dynamics and homeostasis. This study aimed to investigate the transport kinetics of the glymphatic system after the appearance of ischemic edema.MethodsIn this study, a coated filament was attached to the left middle cerebral artery (MCA) of mice to establish a mouse model of permanent middle cerebral artery occlusion with an intact blood-brain barrier (BBB). The glymphatic function was then quantified using contrast-enhanced MRI (11.7T) by employing an injection of gadobenate dimeglumine (BOPTA-Gd) into the cisterna magna of mice. We then evaluated the expression and polarization of aquaporin-4 (AQP4) as a proxy for the physiological state of the glymphatic system.ResultsOur results revealed a positive correlation between the signal intensity in T1-weighted images and the corresponding apparent diffusion coefficient (ADC) values in the cortex, striatum, and periventricular zone, suggesting that impaired glymphatic transport kinetics in these regions is correlated to the cytotoxic edema induced by the occlusion of MCA. Furthermore, the increased depolarization of AQP4 in the parenchyma perivascular space (PVS) was consistent with glymphatic failure following the induced early cerebral ischemic edema.ConclusionsGlymphatic transport kinetics were suppressed between the onset of cytotoxic edema and the disruption of the BBB, which correlated with the diminishing ADC values that vary based on edema progression, and is associated with depolarization of AQP4 in the parenchyma PVSs.

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Section: Resultsmentioning

confidence: 99%

Impaired Glymphatic Transport Kinetics Following Induced Acute Ischemic Brain Edema in a Mouse pMCAO Model

et al. 2022

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“…Diffusion MRI methods are appropriate to estimate structural neurological integrity defects caused by, for example, neurodegeneration, acute ischemia, tumors, and other lesions, edemas, infections, and protein (Aβ and Tau) plaques [ 39 , 40 , 41 ]. The methodological principle is based on the measurements of the diffusion of water molecules (random Brownian motion) in the extracellular fluid space.…”

Section: Neuroimaging In the Cognitive Impairmentmentioning

confidence: 99%

Imaging Methods Applicable in the Diagnostics of Alzheimer’s Disease, Considering the Involvement of Insulin Resistance

Hnilicová

Kantorová

Šutovský

et al. 2023

IJMS

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Alzheimer’s disease (AD) is an incurable neurodegenerative disease and the most frequently diagnosed type of dementia, characterized by (1) perturbed cerebral perfusion, vasculature, and cortical metabolism; (2) induced proinflammatory processes; and (3) the aggregation of amyloid beta and hyperphosphorylated Tau proteins. Subclinical AD changes are commonly detectable by using radiological and nuclear neuroimaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Furthermore, other valuable modalities exist (in particular, structural volumetric, diffusion, perfusion, functional, and metabolic magnetic resonance methods) that can advance the diagnostic algorithm of AD and our understanding of its pathogenesis. Recently, new insights into AD pathoetiology revealed that deranged insulin homeostasis in the brain may play a role in the onset and progression of the disease. AD-related brain insulin resistance is closely linked to systemic insulin homeostasis disorders caused by pancreas and/or liver dysfunction. Indeed, in recent studies, linkages between the development and onset of AD and the liver and/or pancreas have been established. Aside from standard radiological and nuclear neuroimaging methods and clinically fewer common methods of magnetic resonance, this article also discusses the use of new suggestive non-neuronal imaging modalities to assess AD-associated structural changes in the liver and pancreas. Studying these changes might be of great clinical importance because of their possible involvement in AD pathogenesis during the prodromal phase of the disease.

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“…Radiomics provides valuable information on tumor responses to therapy by incorporating AI into the glioblastoma multiforme (GBM) assessment of tumors using data from images. Radiomics uses sophisticated image analysis methods, such as diffusion and perfusion imaging, to provide accurate diagnosis and treatment of GBM [ 154 ]. Deep radiomic characteristics demonstrated markedly better precision ( p < 0.05), with an AUC of 89.15%, compared to 78.07% for standard radiomic characteristics, for short and long-term survival prediction in patients with recurrent GBM [ 155 ].…”

Section: Ai In Brain Tumor Imagingmentioning

confidence: 99%

Artificial Intelligence and Precision Medicine: A New Frontier for the Treatment of Brain Tumors

Philip

Samuel

Bhatia

et al. 2022

Life

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Brain tumors are a widespread and serious neurological phenomenon that can be life- threatening. The computing field has allowed for the development of artificial intelligence (AI), which can mimic the neural network of the human brain. One use of this technology has been to help researchers capture hidden, high-dimensional images of brain tumors. These images can provide new insights into the nature of brain tumors and help to improve treatment options. AI and precision medicine (PM) are converging to revolutionize healthcare. AI has the potential to improve cancer imaging interpretation in several ways, including more accurate tumor genotyping, more precise delineation of tumor volume, and better prediction of clinical outcomes. AI-assisted brain surgery can be an effective and safe option for treating brain tumors. This review discusses various AI and PM techniques that can be used in brain tumor treatment. These new techniques for the treatment of brain tumors, i.e., genomic profiling, microRNA panels, quantitative imaging, and radiomics, hold great promise for the future. However, there are challenges that must be overcome for these technologies to reach their full potential and improve healthcare.

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Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke

Cited by 24 publications

References 85 publications

Impaired Glymphatic Transport Kinetics Following Induced Acute Ischemic Brain Edema in a Mouse pMCAO Model

Impaired Glymphatic Transport Kinetics Following Induced Acute Ischemic Brain Edema in a Mouse pMCAO Model

Imaging Methods Applicable in the Diagnostics of Alzheimer’s Disease, Considering the Involvement of Insulin Resistance

Artificial Intelligence and Precision Medicine: A New Frontier for the Treatment of Brain Tumors

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