scholarly journals Microcephaly with altered cortical layering in GIT1 deficiency revealed by quantitative neuroimaging

2021 ◽  
Vol 76 ◽  
pp. 26-38
Author(s):  
Alexandra Badea ◽  
Robert Schmalzigaug ◽  
Woojoo Kim ◽  
Pamela Bonner ◽  
Umer Ahmed ◽  
...  
Keyword(s):  
Quantitative Neuroimaging

Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician

2021 ◽  
pp. 1-19
Author(s):  
Erin D. Bigler ◽  
Steven Allder
Keyword(s):  
Neural Network ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Diffusion Tensor ◽  
Neuropsychological Test ◽  
Region Of Interest ◽  
Neural Network Approach ◽  
Additional Tool ◽  
Network Analyses ◽  
Quantitative Neuroimaging

BACKGROUND: Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician. OBJECTIVE: Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained. METHODS: Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach. RESULTS: Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI. CONCLUSIONS: Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.

scholarly journals Quantitative neuroimaging of volume loss in persons with Alzheimer’s dementia

2020 ◽  
Vol 16 (S5) ◽  
Author(s):  
Somayeh Meysami ◽  
Cyrus A. Raji ◽  
David A. Merrill ◽  
Verna R. Porter ◽  
Mario F. Mendez
Keyword(s):  
Alzheimer’S Dementia ◽  
Volume Loss ◽  
Alzheimer's Dementia ◽  
Quantitative Neuroimaging

scholarly journals A Theoretical Model of Oxygen Delivery and Metabolism for Physiologic Interpretation of Quantitative Cerebral Blood Flow and Metabolic Rate of Oxygen

2003 ◽  
Vol 23 (11) ◽  
pp. 1314-1323 ◽  
Author(s):  
Takuya Hayashi ◽  
Hiroshi Watabe ◽  
Nobuyuki Kudomi ◽  
Kyeong Min Kim ◽  
Jun-Ichiro Enmi ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Theoretical Model ◽  
Metabolic Rate ◽  
Oxygen Delivery ◽  
Oxygen Extraction Fraction ◽  
Biologic Response ◽  
Quantitative Neuroimaging ◽  
The Relationship ◽  
Active Change

The coupling of cerebral blood flow (CBF) and metabolic rate of oxygen (CMRO2) during physiologic and pathophysiologic conditions remains the subject of debate. In the present study, we have developed a theoretical model for oxygen delivery and metabolism, which describes the diffusion of oxygen at the capillary-tissue interface and the nonlinear nature of hemoglobin (Hb) affinity to oxygen, allowing a variation in simple-capillary oxygen diffusibility, termed “effective oxygen diffusibility (EOD).” The model was used to simulate the relationship between CBF and CMRO2, as well as oxygen extraction fraction (OEF), when various pathophysiologic conditions were assumed involving functional activation, ischemia, hypoxia, anemia, or hypo- and hyper-capnic CBF variations. The simulations revealed that, to maintain CMRO2 constant, a variation in CBF and Hb required active change in EOD. In contrast, unless the EOD change took place, the brain allowed small but significant nonlinear change in CMRO2 directly dependent upon oxygen delivery. Application of the present model to quantitative neuroimaging of CBF and CMRO2 enables us to evaluate the biologic response at capillary level other than Hb- and flow-dependent properties of oxygen transport and may give us another insight regarding the physiologic control of oxygen delivery in the human brain.

scholarly journals Quantitative neuroimaging in mucolipidosis type IV

2014 ◽  
Vol 111 (2) ◽  
pp. 147-151 ◽  
Author(s):  
Raphael Schiffmann ◽  
Joan Mayfield ◽  
Caren Swift ◽  
Igor Nestrasil
Keyword(s):  
Mucolipidosis Type Iv ◽  
Type Iv ◽  
Quantitative Neuroimaging ◽  
Mucolipidosis Type

scholarly journals Radiation sparing of cerebral cortex in brain tumor patients using quantitative neuroimaging

2016 ◽  
Vol 118 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Roshan A. Karunamuni ◽  
Kevin L. Moore ◽  
Tyler M. Seibert ◽  
Nan Li ◽  
Nathan S. White ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Brain Tumor ◽  
Tumor Patients ◽  
Quantitative Neuroimaging

scholarly journals Prospective Trial of Quantitative Neuroimaging Correlates of Verbal and Nonverbal Memory Decline

2017 ◽  
Vol 99 (2) ◽  
pp. S101
Author(s):  
K.R. Tringale ◽  
R. Karunamuni ◽  
T. Nguyen ◽  
T.M. Seibert ◽  
K. Leyden ◽  
...  
Keyword(s):  
Prospective Trial ◽  
Memory Decline ◽  
Nonverbal Memory ◽  
Quantitative Neuroimaging

scholarly journals Prospective Quantitative Neuroimaging Analysis of Putative Temporal Lobe Epilepsy

2021 ◽  
Vol 12 ◽  
Author(s):  
Kost Elisevich ◽  
Esmaeil Davoodi-Bojd ◽  
John G. Heredia ◽  
Hamid Soltanian-Zadeh
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Prediction Models ◽  
Quantitative Imaging ◽  
Hippocampal Volume ◽  
Mesial Temporal Lobe Epilepsy ◽  
Nuclear Medicine Imaging ◽  
Class 1 ◽  
A Prospective Study ◽  
Quantitative Neuroimaging

Purpose: A prospective study of individual and combined quantitative imaging applications for lateralizing epileptogenicity was performed in a cohort of consecutive patients with a putative diagnosis of mesial temporal lobe epilepsy (mTLE).Methods: Quantitative metrics were applied to MRI and nuclear medicine imaging studies as part of a comprehensive presurgical investigation. The neuroimaging analytics were conducted remotely to remove bias. All quantitative lateralizing tools were trained using a separate dataset. Outcomes were determined after 2 years. Of those treated, some underwent resection, and others were implanted with a responsive neurostimulation (RNS) device.Results: Forty-eight consecutive cases underwent evaluation using nine attributes of individual or combinations of neuroimaging modalities: 1) hippocampal volume, 2) FLAIR signal, 3) PET profile, 4) multistructural analysis (MSA), 5) multimodal model analysis (MMM), 6) DTI uncertainty analysis, 7) DTI connectivity, and 9) fMRI connectivity. Of the 24 patients undergoing resection, MSA, MMM, and PET proved most effective in predicting an Engel class 1 outcome (>80% accuracy). Both hippocampal volume and FLAIR signal analysis showed 76% and 69% concordance with an Engel class 1 outcome, respectively.Conclusion: Quantitative multimodal neuroimaging in the context of a putative mTLE aids in declaring laterality. The degree to which there is disagreement among the various quantitative neuroimaging metrics will judge whether epileptogenicity can be confined sufficiently to a particular temporal lobe to warrant further study and choice of therapy. Prediction models will improve with continued exploration of combined optimal neuroimaging metrics.

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