Neuroimaging

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Review Neurosciences

ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

Peter Kochunov, L. Elliot Hong, Emily L. Dennis, Rajendra A. Morey, David F. Tate, Elisabeth A. Wilde, Mark Logue, Sinead Kelly, Gary Donohoe, Pauline Favre, Josselin Houenou, Christopher R. K. Ching, Laurena Holleran, Ole A. Andreassen, Laura S. van Velzen, Lianne Schmaal, Julio E. Villalon-Reina, Carrie E. Bearden, Fabrizio Piras, Gianfranco Spalletta, Odile A. van den Heuvel, Dick J. Veltman, Dan J. Stein, Meghann C. Ryan, Yunlong Tan, Theo G. M. van Erp, Jessica A. Turner, Liz Haddad, Talia M. Nir, David C. Glahn, Paul M. Thompson, Neda Jahanshad

Summary: The ENIGMA-DTI workgroup investigates the effects of psychiatric, neurological, and developmental disorders on white matter pathways in the human brain. They have identified patterns of white matter deficits in various disorders and demonstrated their reproducibility across different cohorts. Applying the regional vulnerability index (RVI) to individual subjects, they have shown the similarity of deficit patterns among different disorders and discussed the differences between idiopathic schizophrenia and 22q11 deletion syndrome. These findings emphasize the importance of collaborative large-scale research in understanding individual vulnerability and cross-diagnosis features.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD

Kanhao Zhao, Boris Duka, Hua Xie, Desmond J. Oathes, Vince Calhoun, Yu Zhang

Summary: The dynamic graph convolutional network (dGCN) improves the diagnostic performance of Attention Deficit Hyperactivity Disorder (ADHD) by learning informative features in brain functional connectome. Visualization of functional abnormal regions and connectivity reveals important brain areas related to ADHD and a positive correlation with symptom severity. The proposed dGCN model shows great potential for precision diagnosis of ADHD and broader applications in studying mental disorders based on brain connectome.

NEUROIMAGE (2022)

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Article Neurosciences

Connectomics of human electrophysiology

Sepideh Sadaghiani, Matthew J. Brookes, Sylvain Baillet

Summary: The paper presents a scientific overview and conceptual positions on the challenges and benefits of electrophysiological measurements in understanding the human connectome. It emphasizes the importance of electrophysiological signals, current data modalities, and analytical methods. Furthermore, it encourages the field to embrace the complexity of electrophysiological signals and develop testable mechanistic models for information integration in hierarchical brain networks.

NEUROIMAGE (2022)

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Review Neurosciences

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

Sook-Lei Liew, Artemis Zavaliangos-Petropulu, Neda Jahanshad, Catherine E. Lang, Kathryn S. Hayward, Keith R. Lohse, Julia M. Juliano, Francesca Assogna, Lee A. Baugh, Anup K. Bhattacharya, Bavrina Bigjahan, Michael R. Borich, Lara A. Boyd, Amy Brodtmann, Cathrin M. Buetefisch, Winston D. Byblow, Jessica M. Cassidy, Adriana B. Conforto, R. Cameron Craddock, Michael A. Dimyan, Adrienne N. Dula, Elsa Ermer, Mark R. Etherton, Kelene A. Fercho, Chris M. Gregory, Shahram Hadidchi, Jess A. Holguin, Darryl H. Hwang, Simon Jung, Steven A. Kautz, Mohamed Salah Khlif, Nima Khoshab, Bokkyu Kim, Hosung Kim, Amy Kuceyeski, Martin Lotze, Bradley J. MacIntosh, John L. Margetis, Feroze B. Mohamed, Fabrizio Piras, Ander Ramos-Murguialday, Genevieve Richard, Pamela Roberts, Andrew D. Robertson, Jane M. Rondina, Natalia S. Rost, Nerses Sanossian, Nicolas Schweighofer, Na Jin Seo, Mark S. Shiroishi, Surjo R. Soekadar, Gianfranco Spalletta, Cathy M. Stinear, Anisha Suri, Wai Kwong W. Tang, Gregory T. Thielman, Daniela Vecchio, Arno Villringer, Nick S. Ward, Emilio Werden, Lars T. Westlye, Carolee Winstein, George F. Wittenberg, Kristin A. Wong, Chunshui Yu, Steven C. Cramer, Paul M. Thompson

Summary: The ENIGMA Stroke Recovery working group aims to understand the relationship between brain and behavior using meta- and mega-analytic approaches. They have developed neuroinformatics protocols and methods to manage large-scale data from over 2,100 stroke patients. The challenges and recommendations for data harmonization in stroke research are discussed.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group

Unn K. Haukvik, Tiril P. Gurholt, Stener Nerland, Torbjorn Elvsashagen, Theophilus N. Akudjedu, Martin Alda, Dag Alnaes, Silvia Alonso-Lana, Jochen Bauer, Bernhard T. Baune, Francesco Benedetti, Michael Berk, Francesco Bettella, Erlend Boen, Caterina M. Bonnin, Paolo Brambilla, Erick J. Canales-Rodriguez, Dara M. Cannon, Xavier Caseras, Orwa Dandash, Udo Dannlowski, Giuseppe Delvecchio, Ana M. Diaz-Zuluaga, Theo G. M. Erp, Mar Fatjo-Vilas, Sonya F. Foley, Katharina Foerster, Janice M. Fullerton, Jose M. Goikolea, Dominik Grotegerd, Oliver Gruber, Bartholomeus C. M. Haarman, Beathe Haatveit, Tomas Hajek, Brian Hallahan, Mathew Harris, Emma L. Hawkins, Fleur M. Howells, Carina Huelsmann, Neda Jahanshad, Kjetil N. Jorgensen, Tilo Kircher, Bernd Kraemer, Axel Krug, Rayus Kuplicki, Trine Lagerberg, Thomas M. Lancaster, Rhoshel K. Lenroot, Vera Lonning, Carlos Lopez-Jaramillo, Ulrik F. Malt, Colm McDonald, Andrew M. McIntosh, Genevieve McPhilemy, Dennis Meer, Ingrid Melle, Elisa M. T. Melloni, Philip B. Mitchell, Leila Nabulsi, Igor Nenadic, Viola Oertel, Lucio Oldani, Nils Opel, Maria C. G. Otaduy, Bronwyn J. Overs, Julian A. Pineda-Zapata, Edith Pomarol-Clotet, Joaquim Radua, Lisa Rauer, Ronny Redlich, Jonathan Repple, Maria M. Rive, Gloria Roberts, Henricus G. Ruhe, Lauren E. Salminen, Raymond Salvador, Salvador Sarro, Jonathan Savitz, Aart H. Schene, Kang Sim, Marcio G. Soeiro-de-Souza, Michael Staeblein, Dan J. Stein, Frederike Stein, Christian K. Tamnes, Henk S. Temmingh, Sophia Thomopoulos, Dick J. Veltman, Eduard Vieta, Lena Waltemate, Lars T. Westlye, Heather C. Whalley, Philipp G. Saemann, Paul M. Thompson, Christopher R. K. Ching, Ole A. Andreassen, Ingrid Agartz

Summary: By studying the volume of hippocampal subfields in individuals with bipolar disorder, this research found that there are widespread reductions in several subfields in bipolar disorder, compared to healthy controls. The use of medication, particularly lithium, may have a protective effect in bipolar disorder.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

Cross-Axis projection error in optically pumped magnetometers and its implication for magnetoencephalography systems

Amir Borna, Joonas Iivanainen, Tony R. Carter, Jim McKay, Samu Taulu, Julia Stephen, Peter D. D. Schwindt

Summary: The study demonstrates that significant cross-axis projection errors can be introduced into the output signal of optically pumped magnetometers, leading to a degradation in localization and calibration accuracy of the system.

NEUROIMAGE (2022)

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Article Neurosciences

Mitigating site effects in covariance for machine learning in neuroimaging data

Andrew A. Chen, Joanne C. Beer, Nicholas J. Tustison, Philip A. Cook, Russell T. Shinohara, Haochang Shou

Summary: In order to address discrepancies in neuroimaging data acquired from different research sites, efforts have been made to harmonize the data by removing site-related effects in the mean and variance. Additionally, the utilization of machine learning in neuroimaging has become increasingly popular, providing improved sensitivity and specificity due to modeling the joint relationship across brain measurements. Researchers have proposed a novel method called Correcting Covariance Batch Effects (CovBat) that removes site effects in mean, variance, and covariance, demonstrating successful harmonization of within-site correlation matrices and accurate disease group prediction after harmonization.

HUMAN BRAIN MAPPING (2022)

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Article Neuroimaging

Clinical and imaging outcomes of cerebrospinal fluid-venous fistula embolization

Waleed Brinjikji, Ivan Garza, Mark Whealy, Narayan Kissoon, John L. D. Atkinson, Luis Savastano, Ajay Madhavan, Jeremy Cutsforth-Gregory

Summary: This study evaluated the clinical outcomes of transvenous embolization in patients with spontaneous intracranial hypotension (SIH). The results showed that using Onyx for the embolization of cerebrospinal fluid-venous fistulas (CSFVFs) is safe and effective, resulting in significant improvement in headache and overall clinical outcomes.

JOURNAL OF NEUROINTERVENTIONAL SURGERY (2022)

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Review Clinical Neurology

The 2021 World Health Organization Classification of Tumors of the Central Nervous System: What Neuroradiologists Need to Know

A. G. Osborn, D. N. Louis, T. Y. Poussaint, L. L. Linscott, K. L. Salzman

Summary: Neuroradiologists play a crucial role in the diagnosis and treatment of brain tumors, and it is important for them to stay updated with the latest classification systems and diagnostic markers to provide optimal patient care.

AMERICAN JOURNAL OF NEURORADIOLOGY (2022)

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Article Clinical Neurology

A New Frontier in Temporal Bone Imaging: Photon-Counting Detector CT Demonstrates Superior Visualization of Critical Anatomic Structures at Reduced Radiation Dose

J. C. Benson, K. Rajendran, J. I. Lane, F. E. Diehn, N. M. Weber, J. E. Thorne, N. B. Larson, J. G. Fletcher, C. H. McCollough, S. Leng

Summary: This study aimed to compare the clinical impact of photon-counting detector CT and conventional energy-integrating detector CT in temporal bone imaging. The results showed that photon-counting detector CT images had superior spatial resolution and better critical structure visualization, even with a substantial dose reduction.

AMERICAN JOURNAL OF NEURORADIOLOGY (2022)

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Article Neurosciences

Cardiometabolic risk factors associated with brain age and accelerate brain ageing

Dani Beck, Ann-Marie G. de Lange, Mads L. Pedersen, Dag Alnaes, Ivan I. Maximov, Irene Voldsbekk, Genevieve Richard, Anne-Marthe Sanders, Kristine M. Ulrichsen, Erlend S. Dorum, Knut K. Kolskar, Einar A. Hogestol, Nils Eiel Steen, Srdjan Djurovic, Ole A. Andreassen, Jan E. Nordvik, Tobias Kaufmann, Lars T. Westlye

Summary: The study found a link between cardiometabolic risk factors and brain ageing, with factors like smoking and high blood pressure potentially leading to older-appearing brains. Data also showed that cardiometabolic risk factors were associated with accelerated brain ageing.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

Mind the gap: Performance metric evaluation in brain-age prediction

Ann-Marie G. de Lange, Melis Anaturk, Jaroslav Rokicki, Laura K. M. Han, Katja Franke, Dag Alnaes, Klaus P. Ebmeier, Bogdan Draganski, Tobias Kaufmann, Lars T. Westlye, Tim Hahn, James H. Cole

Summary: Estimating age based on neuroimaging-derived data is a popular approach, but there is significant variation in model accuracy across studies. This study found that performance metrics for age prediction models depend on cohort and study-specific data characteristics. Age range, sample size, and age-bias correction all have an impact on the accuracy of the models. Furthermore, evaluating prediction variance and age-bias provides important information about underlying model attributes.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

Olfactory loss and brain connectivity after COVID-19

Fabrizio Esposito, Mario Cirillo, Rosa De Micco, Giuseppina Caiazzo, Mattia Siciliano, Andrea Gerardo Russo, Caterina Monari, Nicola Coppola, Gioacchino Tedeschi, Alessandro Tessitore

Summary: This study analyzed the neural connectivity in the central olfactory system of individuals with persisting olfactory impairment due to COVID-19. The results showed that both the structural and functional connectivity were significantly increased in previously infected subjects compared to the control group. Greater residual olfactory impairment was associated with more segregated processing within certain regions. These findings suggest a characteristic brain connectivity response to residual hyposmia related to COVID-19.

HUMAN BRAIN MAPPING (2022)

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Article Neurosciences

A unified view on beamformers for M/EEG source reconstruction

Britta U. Westner, Sarang S. Dalal, Alexandre Gramfort, Vladimir Litvak, John C. Mosher, Robert Oostenveld, Jan-Mathijs Schoffelen

Summary: This paper provides a unified documentation of the mathematical background and terminology for beamforming, compares beamformer implementations across different toolboxes, and discusses pitfalls and solutions in beamforming analysis.

NEUROIMAGE (2022)

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Article Neurosciences

Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Shengwen Deng, Crystal G. Franklin, Michael O'Boyle, Wei Zhang, Betty L. Heyl, Paul A. Jerabek, Hanzhang Lu, Peter T. Fox

Summary: The study aims to quantify spatial correspondences between voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI and PET measurements of cerebral metabolic rate and hemodynamics. The results show significant correspondences between ALFF and blood volume (BV), between fALFF and metabolic rate of glucose (MRGlu), oxygen consumption (MRO2), blood flow (BF) and BV, as well as between ReHo and MRGlu, MRO2, BF, and BV. However, the strength of the PET-BOLD correspondences varies by brain region.

NEUROIMAGE (2022)

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Article Neurosciences

Hyperbolic trade-off : The importance of balancing trial and subject sample sizes in neuroimaging

Gang Chen, Daniel S. Pine, Melissa A. Brotman, Ashley R. Smith, Robert W. Cox, Paul A. Taylor, Simone P. Haller

Summary: Trials play a crucial role in task-based neuroimaging, impacting statistical efficiency and condition-level generalizability. Increasing both trial and subject sample sizes can improve statistical efficiency more effectively than focusing on subjects alone, and trial-level modeling may be necessary for accurately assessing effect estimates with small trial size.

NEUROIMAGE (2022)

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Article Neurosciences

SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI

Qiyuan Tian, Ziyu Li, Qiuyun Fan, Jonathan R. Polimeni, Berkin Bilgic, David H. Salat, Susie Y. Huang

Summary: Diffusion tensor magnetic resonance imaging (DTI) is widely used for mapping brain tissue microstructure and white matter tracts, but the accuracy and precision of DTI parameters are affected by noise in the images. This study presents a self-supervised deep learning-based method (SDnDTI) for denoising DTI data without extra high-SNR data, improving the quality of DTI.

NEUROIMAGE (2022)

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Article Neuroimaging

CLinical Assessment of WEB device in Ruptured aneurYSms (CLARYS): results of 1-month and 1-year assessment of rebleeding protection and clinical safety in a multicenter study

Laurent Spelle, Denis Herbreteau, Jildaz Caroff, Xavier Barreau, Jean-Christophe Ferre, Jens Fiehler, Anne-Christine Januel, Vincent Costalat, Thomas Liebig, Romain Bourcier, Markus Moehlenbruch, Joachim Berkefeld, Werner Weber, Cristian Mihalea, Leon Ikka, Augustin Ozanne, Christophe Cognard, Ana Paula Narata, Richard Edwige Bibi, Jean-Yves Gauvrit, Helene Raoult, Stephane Velasco, Jan-Hendrik Buhk, Vanessa Chalumeau, Maxim Bester, Hubert Desal, Richard du Mesnil de Rochemont, Georg Bohner, Sebastian Fischer, Alessandra Biondi, Lamiae Grimaldi, Jacques Moret, James Byrne, Laurent Pierot

Summary: The CLARYS study demonstrates that the endovascular treatment of ruptured bifurcation aneurysms with the WEB device is safe and effective in preventing rebleeding at 1 month and 1 year postprocedure. The overall rate of intraoperative complications is low, with acceptable mortality and morbidity rates at 1 month and 1 year.

JOURNAL OF NEUROINTERVENTIONAL SURGERY (2022)

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Article Neuroimaging

Predictors of futile recanalization in patients undergoing endovascular treatment in the DIRECT-MT trial

Tengfei Zhou, Tingyu Yi, Tianxiao Li, Liangfu Zhu, Yucheng Li, Zhaoshuo Li, Meiyun Wang, Qiang Li, Yingkun He, Pengfei Yang, Yongwei Zhang, Zifu Li, Yongxin Zhang, Xiaofei Ye, Wenhuo Chen, Shouchun Wang, Jianmin Liu

Summary: Through analyzing the predictors of futile recanalization in AIS patients who received endovascular treatment, it was found that older age, higher baseline systolic blood pressure, incomplete reperfusion defined by eTICI, and larger final infarct volume are independent predictors of futile recanalization.

JOURNAL OF NEUROINTERVENTIONAL SURGERY (2022)

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Article Neurosciences

Connectivity-based parcellation of normal and anatomically distorted human cerebral cortex

Stephane Doyen, Peter Nicholas, Anujan Poologaindran, Lewis Crawford, Isabella M. Young, Rafeael Romero-Garcia, Michael E. Sughrue

Summary: By developing a novel connectivity-based parcellation approach, researchers created a personalized neurosurgical application method that can be applied at the single-subject level, overcoming the impact of pathology and resection on brain structure.

HUMAN BRAIN MAPPING (2022)

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