Imaging Brain Diseases A Neuroradiology, Nuclear Medicine, Neurosurgery, Neuropathology and Molecular Biology-based Approach

Imaging Brain Diseases A Neuroradiology, Nuclear Medicine, Neurosurgery, Neuropathology and Molecular Biology-based Approach

by Serge Weis (Author), Michael Sonnberger (Author), Andreas Dunzinger (Author), Eva Voglmayr (Author), Martin Aichholzer (Author), Raimund Kleiser (Author), Peter Strasser (Author)

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This book illustrates in a unique way the most common diseases affecting the human nervous system using different imaging modalities derived from radiology, nuclear medicine, and neuropathology. The features of the diseases are visualized on computerized tomography (CT)-scans, magnetic resonance imaging (MRI)-scans, nuclear medicine scans, surgical intraoperative as well as gross-anatomy and histology preparations. For each disease entity, the structural changes are illustrated in a correlative comparative way based on the various imaging techniques. The brain diseases are presented in a systematic way allowing the reader to easily find the topics in which she or he is particularly interested. In Part 1 of the book, the imaging techniques are described in a practical, straightforward way. The morphological built-up of the normal human brain and its vascular supply are presented in Part 2. The chapters of the subsequent Parts 3 to 10 deal with the following diseases involving the nervous system including: hemodynamic, vascular, infectious, neurodegenerative, demyelination, epilepsy, trauma and intoxication, and tumors.

The authors incite the clinician to see the cell, the tissue, the organ, the disorder by enabling him to recognize brain lesions or interpreting histologic findings and to correlate this knowledge with molecular biologic concepts. Thus, this book bridges the gap between neuro-clinicians, neuro-imagers and neuro-pathologists. The information provided will facilitate the understanding of the disease processes in the daily routine work of neurologists, neuroradiologists, neurosurgeons, neuropathologists, and all allied clinical disciplines.

Imaging in Neurovascular Disease A Case-Based Approach

Imaging in Neurovascular Disease A Case-Based Approach

by Waleed Brinjikji (Author), Timo Krings (Author)

List Price: $149.99

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Unique case-based reference presents high-yield images and expertise focused on vascular neuroradiology

Imaging in Neurovascular Disease: A Case-Based Approach by Waleed Brinjikji and Timo Krings is unique in its approach, detailing diagnostic and interventional neuroradiology cases based on radiologic findings. The book explores the key role vascular imaging can play in treatment decision making, prognostication, and improving the understanding of the pathophysiology of neurovascular diseases.

Spread over 11 chapters, this book covers a full spectrum of neurovascular diseases spanning the age continuum, starting with acute ischemic stroke, concluding with spinal vascular disease. All vascular neuroradiology cases follow a consistent format. After a succinct introduction describing the clinical scenario with relevant case images, the authors present key facts about the disease and the integral role of different neurovascular imaging procedures in disease management. Imaging findings are discussed in depth, with insightful clinical pearls on image-guided procedures and tips on managing potential pitfalls.

Key Highlights

About 600 high-quality noninvasive images, such as MR angiography/MR imaging, CT angiography/CT perfusion, with angiography where applicable, elucidate a spectrum of findings Analysis of the imaging appearance of a diverse array of common to rare neurovascular diseases provides diagnostic and treatment insights Each case concludes with the most important points clinicians need to know, high-yield facts about a specific cerebrovascular disease, and suggested readings for further exploration This unique case-based book is essential reading for radiology, neurology and neurosurgery residents. It will greatly benefit neurovascular disease specialists including radiologists, neurosurgeons and neurologists as well as interested in furthering their knowledge on the use of neuroimaging to guide neurointerventional and neurosurgical procedures to treat cerebrovascular disease.

This book includes complimentary access to a digital copy on https://medone.thieme.com.

Neuromelanin magnetic resonance imaging

Neuromelanin magnetic resonance imaging

Neuromelanin-sensitive MRI (NM-MRI) purports to detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). Interindividual variability in dopamine function may result in varying levels of NM accumulation in the SN; however, the ability of NM-MRI to measure dopamine function in nonneurodegenerative conditions has not been established.


Neuromelanin sensitive MRI may be the method of choice for the follow-up of meningeal melanocytoma 1).


Cassidy et al. validated that NM-MRI signal intensity in postmortem midbrain specimens correlated with regional NM concentration even in the absence of neurodegeneration, a prerequisite for its use as a proxy for dopamine function. They then validated a voxelwise NM-MRI approach with sufficient anatomical sensitivity to resolve SN subregions. Using this approach and a multimodal dataset of molecular PET and fMRI data, they further showed the NM-MRI signal was related to both dopamine release in the dorsal striatum and resting blood flow within the SN. These results suggest that NM-MRI signal in the SN is a proxy for function of dopamine neurons in the nigrostriatal pathway. As a proof of concept for its clinical utility, we show that the NM-MRI signal correlated to severity of psychosis in schizophrenia and individuals at risk for schizophrenia, consistent with the well-established dysfunction of the nigrostriatal pathway in psychosis. The results indicate that noninvasive NM-MRI is a promising tool that could have diverse research and clinical applications to investigate in vivo the role of dopamine in neuropsychiatric illness 2).


A study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson’s disease diagnosis.

NM-MRI datasets from two different 3T-scanners were used: a “principal dataset” with 122 participants and an “external validation dataset” with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined.

For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets.

U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method 3)

References

1)

Matsuno H, Takasu S, Seki Y. Usefulness of Neuromelanin Sensitive MRI for En Plaque Meningeal Melanocytoma Involving the Cavernous Sinus: A Case Report. NMC Case Rep J. 2019 Mar 21;6(2):43-46. doi: 10.2176/nmccrj.cr.2018-0211. eCollection 2019 Apr. PubMed PMID: 31016099; PubMed Central PMCID: PMC6476814.
2)

Cassidy CM, Zucca FA, Girgis RR, Baker SC, Weinstein JJ, Sharp ME, Bellei C, Valmadre A, Vanegas N, Kegeles LS, Brucato G, Jung Kang U, Sulzer D, Zecca L, Abi-Dargham A, Horga G. Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain. Proc Natl Acad Sci U S A. 2019 Mar 12;116(11):5108-5117. doi: 10.1073/pnas.1807983116. Epub 2019 Feb 22. PubMed PMID: 30796187; PubMed Central PMCID: PMC6421437.
3)

Le Berre A, Kamagata K, Otsuka Y, Andica C, Hatano T, Saccenti L, Ogawa T, Takeshige-Amano H, Wada A, Suzuki M, Hagiwara A, Irie R, Hori M, Oyama G, Shimo Y, Umemura A, Hattori N, Aoki S. Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI. Neuroradiology. 2019 Aug 10. doi: 10.1007/s00234-019-02279-w. [Epub ahead of print] PubMed PMID: 31401723.
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