Search

Your search keyword '"MacIntosh, Bradley J"' showing total 899 results
Start Over Author "MacIntosh, Bradley J"
899 results on '"MacIntosh, Bradley J"'

2. Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction

Author

Liu, Qinghui, Fuster-Garcia, Elies, Hovden, Ivar Thokle, Sederevicius, Donatas, Skogen, Karoline, MacIntosh, Bradley J, Grødem, Edvard, Schellhorn, Till, Brandal, Petter, Bjørnerud, Atle, and Emblem, Kyrre Eeg

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The complex interactions between neoplastic cells and normal tissue, as well as the treatment-induced changes often encountered, make glioma tumor growth modeling challenging. In this paper, we present a novel end-to-end network capable of generating future tumor masks and realistic MRIs of how the tumor will look at any future time points for different treatment plans. Our approach is based on cutting-edge diffusion probabilistic models and deep-segmentation neural networks. We included sequential multi-parametric magnetic resonance images (MRI) and treatment information as conditioning inputs to guide the generative diffusion process. This allows for tumor growth estimates at any given time point. We trained the model using real-world postoperative longitudinal MRI data with glioma tumor growth trajectories represented as tumor segmentation maps over time. The model has demonstrated promising performance across a range of tasks, including the generation of high-quality synthetic MRIs with tumor masks, time-series tumor segmentations, and uncertainty estimates. Combined with the treatment-aware generated MRIs, the tumor growth predictions with uncertainty estimates can provide useful information for clinical decision-making., Comment: 13 pages, 10 figures, 2 tables, 2 agls, preprints in the IEEE trans. format for submission to IEEE-TMI

Published
2023

4. Engaging Mood Brain Circuits with Psilocybin (EMBRACE): a study protocol for a randomized, placebo-controlled and delayed-start, neuroimaging trial in depression

Author

Poulin, Joshua M., Bigford, Gregory E., Lanctôt, Krista L., Giacobbe, Peter, Schaffer, Ayal, Sinyor, Mark, Rabin, Jennifer S., Masellis, Mario, Singnurkar, Amit, Pople, Christopher B., Lipsman, Nir, Husain, Muhammad I., Rosenblat, Joshua D., Cao, Xingshan, MacIntosh, Bradley J., and Nestor, Sean M.

Published
2024
Full Text
View/download PDF

6. Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study

Author

Si, Shuqing, Bi, Anbreen, Yu, Zhaoying, See, Cheryl, Kelly, Sinead, Ambrogi, Sonia, Arango, Celso, Baeza, Inmaculada, Banaj, Nerisa, Berk, Michael, Castro-Fornieles, Josefina, Crespo-Facorro, Benedicto, Crouse, Jacob J., Díaz-Caneja, Covadonga M., Fett, Anne-Kathrin, Fortea, Adriana, Frangou, Sophia, Goldstein, Benjamin I., Hickie, Ian B., Janssen, Joost, Kennedy, Kody G., Krabbendam, Lydia, Kyriakopoulos, Marinos, MacIntosh, Bradley J., Morgado, Pedro, Nerland, Stener, Pascual-Diaz, Saül, Picó-Pérez, Maria, Piras, Fabrizio, Rund, Bjørn Rishovd, de la Serna, Elena, Spalletta, Gianfranco, Sugranyes, Gisela, Suo, Chao, Tordesillas-Gutiérrez, Diana, Vecchio, Daniela, Radua, Joaquim, McGuire, Philip, Thomopoulos, Sophia I., Jahanshad, Neda, Thompson, Paul M., Barth, Claudia, Agartz, Ingrid, James, Anthony, and Kempton, Matthew J.

Published
2024
Full Text
View/download PDF

7. The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge

Author

Li, Xiangyu, Luo, Gongning, Wang, Kuanquan, Wang, Hongyu, Liu, Jun, Liang, Xinjie, Jiang, Jie, Song, Zhenghao, Zheng, Chunyue, Chi, Haokai, Xu, Mingwang, He, Yingte, Ma, Xinghua, Guo, Jingwen, Liu, Yifan, Li, Chuanpu, Chen, Zeli, Siddiquee, Md Mahfuzur Rahman, Myronenko, Andriy, Sanner, Antoine P., Mukhopadhyay, Anirban, Othman, Ahmed E., Zhao, Xingyu, Liu, Weiping, Zhang, Jinhuang, Ma, Xiangyuan, Liu, Qinghui, MacIntosh, Bradley J., Liang, Wei, Mazher, Moona, Qayyum, Abdul, Abramova, Valeriia, Lladó, Xavier, and Li, Shuo

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Automatic intracranial hemorrhage segmentation in 3D non-contrast head CT (NCCT) scans is significant in clinical practice. Existing hemorrhage segmentation methods usually ignores the anisotropic nature of the NCCT, and are evaluated on different in-house datasets with distinct metrics, making it highly challenging to improve segmentation performance and perform objective comparisons among different methods. The INSTANCE 2022 was a grand challenge held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). It is intended to resolve the above-mentioned problems and promote the development of both intracranial hemorrhage segmentation and anisotropic data processing. The INSTANCE released a training set of 100 cases with ground-truth and a validation set with 30 cases without ground-truth labels that were available to the participants. A held-out testing set with 70 cases is utilized for the final evaluation and ranking. The methods from different participants are ranked based on four metrics, including Dice Similarity Coefficient (DSC), Hausdorff Distance (HD), Relative Volume Difference (RVD) and Normalized Surface Dice (NSD). A total of 13 teams submitted distinct solutions to resolve the challenges, making several baseline models, pre-processing strategies and anisotropic data processing techniques available to future researchers. The winner method achieved an average DSC of 0.6925, demonstrating a significant growth over our proposed baseline method. To the best of our knowledge, the proposed INSTANCE challenge releases the first intracranial hemorrhage segmentation benchmark, and is also the first challenge that intended to resolve the anisotropic problem in 3D medical image segmentation, which provides new alternatives in these research fields., Comment: Summarized paper for the MICCAI INSTANCE 2022 Challenge

Published
2023

8. Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CT

Author

Liu, Qinghui, MacIntosh, Bradley J, Schellhorn, Till, Skogen, Karoline, Emblem, KyrreEeg, and Bjørnerud, Atle

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a novel and flexible attention based U-Net architecture referred to as "Voxels-Intersecting Along Orthogonal Levels Attention U-Net" (viola-Unet), for intracranial hemorrhage (ICH) segmentation task in the INSTANCE 2022 Data Challenge on non-contrast computed tomography (CT). The performance of ICH segmentation was improved by efficiently incorporating fused spatially orthogonal and cross-channel features via our proposed Viola attention plugged into the U-Net decoding branches. The viola-Unet outperformed the strong baseline nnU-Net models during both 5-fold cross validation and online validation. Our solution was the winner of the challenge validation phase in terms of all four performance metrics (i.e., DSC, HD, NSD, and RVD). The code base, pretrained weights, and docker image of the viola-Unet AI tool are publicly available at \url{https://github.com/samleoqh/Viola-Unet}., Comment: Accepted by ISBI2023, 5 pages, 4 figures, 4 tables

Published
2022

10. Cytochrome P450-soluble epoxide hydrolase oxylipins, depression and cognition in type 2 diabetes

Author

Anita, Natasha Z., Herrmann, Nathan, Ryoo, Si Won, Major-Orfao, Chelsi, Lin, William Z., Kwan, Felicia, Noor, Shiropa, Rabin, Jennifer S., Marzolini, Susan, Nestor, Sean, Ruthirakuhan, Myuri T., MacIntosh, Bradley J., Goubran, Maged, Yang, Pearl, Cogo-Moreira, Hugo, Rapoport, Mark, Gallagher, Damien, Black, Sandra E., Goldstein, Benjamin I., Lanctôt, Krista L., Oh, Paul I., Taha, Ameer Y., and Swardfager, Walter

Published
2024
Full Text
View/download PDF

13. Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Author

Zavaliangos‐Petropulu, Artemis, Lo, Bethany, Donnelly, Miranda R, Schweighofer, Nicolas, Lohse, Keith, Jahanshad, Neda, Barisano, Giuseppe, Banaj, Nerisa, Borich, Michael R, Boyd, Lara A, Buetefisch, Cathrin M, Byblow, Winston D, Cassidy, Jessica M, Charalambous, Charalambos C, Conforto, Adriana B, DiCarlo, Julie A, Dula, Adrienne N, Egorova‐Brumley, Natalia, Etherton, Mark R, Feng, Wuwei, Fercho, Kelene A, Geranmayeh, Fatemeh, Hanlon, Colleen A, Hayward, Kathryn S, Hordacre, Brenton, Kautz, Steven A, Khlif, Mohamed Salah, Kim, Hosung, Kuceyeski, Amy, Lin, David J, Liu, Jingchun, Lotze, Martin, MacIntosh, Bradley J, Margetis, John L, Mohamed, Feroze B, Piras, Fabrizio, Ramos‐Murguialday, Ander, Revill, Kate P, Roberts, Pamela S, Robertson, Andrew D, Schambra, Heidi M, Seo, Na Jin, Shiroishi, Mark S, Stinear, Cathy M, Soekadar, Surjo R, Spalletta, Gianfranco, Taga, Myriam, Tang, Wai Kwong, Thielman, Gregory T, Vecchio, Daniela, Ward, Nick S, Westlye, Lars T, Werden, Emilio, Winstein, Carolee, Wittenberg, George F, Wolf, Steven L, Wong, Kristin A, Yu, Chunshui, Brodtmann, Amy, Cramer, Steven C, Thompson, Paul M, and Liew, Sook‐Lei

Subjects
Neurosciences, Stroke, Aging, Brain Disorders, Cross-Sectional Studies, Female, Hippocampus, Humans, Male, Quality of Life, Recovery of Function, Stroke Rehabilitation, Upper Extremity, hippocampus, MRI, sensorimotor impairment, stroke, Cardiorespiratory Medicine and Haematology
Abstract

Background Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper-limb sensorimotor impairment. We investigated associations between non-lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results Cross-sectional T1-weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta-Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA-UE (Fugl-Meyer Assessment of Upper Extremity). Robust mixed-effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni-corrected, P

Published
2022

17. Classifying youth with bipolar disorder versus healthy youth using cerebral blood flow patterns

Author

Luciw, Nicholas J., Grigorian, Anahit, Dimick, Mikaela K., Jiang, Guocheng, Chen, J. Jean, Graham, Simon J., Goldstein, Benjamin I., and MacIntosh, Bradley J.

Subjects
Bipolar disorder, Medical research, Medicine, Experimental, Teenagers, Youth, Blood flow, Health, Psychology and mental health
Abstract

Background: Clinical neuroimaging studies often investigate group differences between patients and controls, yet multivariate imaging features may enable individual-level classification. This study aims to classify youth with bipolar disorder (BD) versus healthy youth using grey matter cerebral blood flow (CBF) data analyzed with logistic regressions. Methods: Using a 3 Tesla magnetic resonance imaging (MRI) system, we collected pseudo-continuous, arterial spin-labelling, resting-state functional MRI (rfMRI) and Trweighted images from youth with BD and healthy controls. We used 3 logistic regression models to classify youth with BD versus controls, controlling for age and sex, using mean grey matter CBF as a single explanatory variable, quantitative CBF features based on principal component analysis (PCA) or relative (intensity-normalized) CBF features based on PCA. We also carried out a comparison analysis using rfMRI data. Results: The study included 46 patients with BD (mean age 17 yr, standard deviation [SD] 1 yr; 25 females) and 49 healthy controls (mean age 16 yr, SD 2 yr; 24 females). Global mean CBF and multivariate quantitative CBF offered similar classification performance that was above chance. The association between CBF images and the feature map was not significantly different between groups (p = 0.13); however, the multivariate classifier identified regions with lower CBF among patients with BD ([DELTA]CBF = -2.94 mL/100 g/min; permutation test p = 0047). Classification performance decreased when considering rfMRI data. Limitations: We cannot comment on which CBF principal component is most relevant to the classification. Participants may have had various mood states, comorbidities, demographics and medication records. Conclusion: Brain CBF features can classify youth with BD versus healthy controls with above-chance accuracy using logistic regression. A global CBF feature may offer similar classification performance to distinct multivariate CBF features., Introduction Bipolar disorder (BD) is a severe psychiatric condition defined by recurrent episodes of elevated and depressed mood. The onset of BD most commonly occurs during adolescence. (1) Diagnosis of [...]

Published
2023
Full Text
View/download PDF

18. An empirical analysis of structural neuroimaging profiles in a staging model of depression

Author

Nogovitsyn, Nikita, Ballester, Pedro, Lasby, Mike, Dunlop, Katharine, Ceniti, Amanda K., Squires, Scott, Rowe, Jessie, Ho, Keith, Suh, JeeSu, Hassel, Stefanie, Souza, Roberto, Casseb, Raphael F., Harris, Jacqueline K., Zamyadi, Mojdeh, Arnott, Stephen R., Strother, Stephen C., Hall, Geoffrey, Lam, Raymond W., Poppenk, Jordan, Lebel, Catherine, Bray, Signe, Metzak, Paul, MacIntosh, Bradley J., Goldstein, Benjamin I., Wang, JianLi, Rizvi, Sakina J., MacQueen, Glenda, Addington, Jean, Harkness, Kate L., Rotzinger, Susan, Kennedy, Sidney H., and Frey, Benicio N.

Published
2024
Full Text
View/download PDF

19. Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data

Author

Aitken, Madison, Ameis, Stephanie H., Andrade, Brendan F., Battaglia, Marco, Boileau, Isabelle, Cleverley, Kristin, Courtney, Darren B., Diaconescu, Andreea O., Dickie, Erin W., Felsky, Daniel, Foussias, George, Goldstein, Benjamin I., Gonçalves, Vanessa, Hamilton, Hayley, Griffiths, John D., Haltigan, John D., Hawke, Lisa D., Hill, Sean, Husain, Muhammad Omair, Jani, Melanie, Kidd, Sean A., Kozloff, Nicole, Kurdyak, Paul, Lai, Meng-Chuan, Lewis, Stephen P., Levitan, Robert D., Lin, Hsiang-Yuan, Lunsky, Yona, Mohan, Akshay, Nikolova, Yuliya S., Osman, Sam, Pascoe, Shannon, Polillo, Alexia, Putterman, Connie, Rotenberg, Martin, Quilty, Lena C., Sivakumar, Harijah, Szatmari, Peter, Tempelaar, Wanda, Vasdev, Neil, Wang, Wei, Wheeler, Anne L., van der Miesen, Anna I.R., Vieira, Erica L., Voineskos, Aristotle N., Husain, Muhammad O., Rubin-Kahana, Dafna S., Iftikhar, Myera, MacIntosh, Bradley J., Vieira, Erica, Ahmadzadeh, Ghazaleh, Heyland, Lindsay, Ogunsanya, Feyi, Oliver, Lindsay D., Zhu, Cherrie, Wong, Jimmy K.Y., Charlton, Colleen, Truong, Jennifer, Yu, Lujia, and Kelly, Rachel

Published
2024
Full Text
View/download PDF

20. A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms

Author

Liew, Sook-Lei, Lo, Bethany P, Donnelly, Miranda R, Zavaliangos-Petropulu, Artemis, Jeong, Jessica N, Barisano, Giuseppe, Hutton, Alexandre, Simon, Julia P, Juliano, Julia M, Suri, Anisha, Wang, Zhizhuo, Abdullah, Aisha, Kim, Jun, Ard, Tyler, Banaj, Nerisa, Borich, Michael R, Boyd, Lara A, Brodtmann, Amy, Buetefisch, Cathrin M, Cao, Lei, Cassidy, Jessica M, Ciullo, Valentina, Conforto, Adriana B, Cramer, Steven C, Dacosta-Aguayo, Rosalia, de la Rosa, Ezequiel, Domin, Martin, Dula, Adrienne N, Feng, Wuwei, Franco, Alexandre R, Geranmayeh, Fatemeh, Gramfort, Alexandre, Gregory, Chris M, Hanlon, Colleen A, Hordacre, Brenton G, Kautz, Steven A, Khlif, Mohamed Salah, Kim, Hosung, Kirschke, Jan S, Liu, Jingchun, Lotze, Martin, MacIntosh, Bradley J, Mataró, Maria, Mohamed, Feroze B, Nordvik, Jan E, Park, Gilsoon, Pienta, Amy, Piras, Fabrizio, Redman, Shane M, Revill, Kate P, Reyes, Mauricio, Robertson, Andrew D, Seo, Na Jin, Soekadar, Surjo R, Spalletta, Gianfranco, Sweet, Alison, Telenczuk, Maria, Thielman, Gregory, Westlye, Lars T, Winstein, Carolee J, Wittenberg, George F, Wong, Kristin A, and Yu, Chunshui

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Physical Sciences, Stroke, Neurosciences, Bioengineering, Networking and Information Technology R&D (NITRD), Algorithms, Brain, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neuroimaging
Abstract

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.

Published
2022

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

Author

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

Subjects
Stroke, Brain Disorders, Biomedical Imaging, Neurosciences, Behavioral and Social Science, Humans, Magnetic Resonance Imaging, Multicenter Studies as Topic, Neuroimaging, Stroke Rehabilitation, big data, lesions, MRI, neuroinformatics, stroke, Cognitive Sciences, Experimental Psychology
Abstract

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Published
2022

22. What we learn about bipolar disorder from large‐scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author

Ching, Christopher RK, Hibar, Derrek P, Gurholt, Tiril P, Nunes, Abraham, Thomopoulos, Sophia I, Abé, Christoph, Agartz, Ingrid, Brouwer, Rachel M, Cannon, Dara M, Zwarte, Sonja MC, Eyler, Lisa T, Favre, Pauline, Hajek, Tomas, Haukvik, Unn K, Houenou, Josselin, Landén, Mikael, Lett, Tristram A, McDonald, Colm, Nabulsi, Leila, Patel, Yash, Pauling, Melissa E, Paus, Tomas, Radua, Joaquim, Soeiro‐de‐Souza, Marcio G, Tronchin, Giulia, Haren, Neeltje EM, Vieta, Eduard, Walter, Henrik, Zeng, Ling‐Li, Alda, Martin, Almeida, Jorge, Alnæs, Dag, Alonso‐Lana, Silvia, Altimus, Cara, Bauer, Michael, Baune, Bernhard T, Bearden, Carrie E, Bellani, Marcella, Benedetti, Francesco, Berk, Michael, Bilderbeck, Amy C, Blumberg, Hilary P, Bøen, Erlend, Bollettini, Irene, Bonnin, Caterina Mar, Brambilla, Paolo, Canales‐Rodríguez, Erick J, Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Díaz‐Zuluaga, Ana M, Dima, Danai, Duchesnay, Édouard, Elvsåshagen, Torbjørn, Fears, Scott C, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Green, Melissa J, Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus CM, Henry, Chantal, Howells, Fleur M, Ives‐Deliperi, Victoria, Jansen, Andreas, Kircher, Tilo TJ, Knöchel, Christian, Kramer, Bernd, Lafer, Beny, López‐Jaramillo, Carlos, Machado‐Vieira, Rodrigo, MacIntosh, Bradley J, Melloni, Elisa MT, Mitchell, Philip B, Nenadic, Igor, Nery, Fabiano, Nugent, Allison C, Oertel, Viola, Ophoff, Roel A, Ota, Miho, Overs, Bronwyn J, Pham, Daniel L, Phillips, Mary L, Pineda‐Zapata, Julian A, Poletti, Sara, Polosan, Mircea, Pomarol‐Clotet, Edith, Pouchon, Arnaud, Quidé, Yann, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Schene, Aart H, and Sim, Kang

Subjects
Serious Mental Illness, Brain Disorders, Biomedical Imaging, Bipolar Disorder, Clinical Research, Behavioral and Social Science, Mental Health, Neurosciences, Mental health, Neurological, Good Health and Well Being, Cerebral Cortex, Humans, Magnetic Resonance Imaging, Meta-Analysis as Topic, Multicenter Studies as Topic, Neuroimaging, bipolar disorder, cortical surface area, cortical thickness, ENIGMA, mega-analysis, meta-analysis, MRI, neuroimaging, psychiatry, volume, ENIGMA Bipolar Disorder Working Group, Cognitive Sciences, Experimental Psychology
Abstract

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Published
2022

23. Intracranial and subcortical volumes in adolescents with early-onset psychosis: A multisite mega-analysis from the ENIGMA consortium.

Author

Gurholt, Tiril P, Lonning, Vera, Nerland, Stener, Jørgensen, Kjetil N, Haukvik, Unn K, Alloza, Clara, Arango, Celso, Barth, Claudia, Bearden, Carrie E, Berk, Michael, Bohman, Hannes, Dandash, Orwa, Díaz-Caneja, Covadonga M, Edbom, Carl T, van Erp, Theo GM, Fett, Anne-Kathrin J, Frangou, Sophia, Goldstein, Benjamin I, Grigorian, Anahit, Jahanshad, Neda, James, Anthony C, Janssen, Joost, Johannessen, Cecilie, Karlsgodt, Katherine H, Kempton, Matthew J, Kochunov, Peter, Krabbendam, Lydia, Kyriakopoulos, Marinos, Lundberg, Mathias, MacIntosh, Bradley J, Rund, Bjørn Rishovd, Smelror, Runar E, Sultan, Alysha, Tamnes, Christian K, Thomopoulos, Sophia I, Vajdi, Ariana, Wedervang-Resell, Kirsten, Myhre, Anne M, Andreassen, Ole A, Thompson, Paul M, Agartz, Ingrid, and ENIGMA-EOP Working Group

Subjects
ENIGMA-EOP Working Group, Brain, Hippocampus, Globus Pallidus, Humans, Magnetic Resonance Imaging, Adolescent Development, Affective Disorders, Psychotic, Psychotic Disorders, Schizophrenia, Age of Onset, Adolescent, adolescence, antipsychotics, brain structure, early-onset, intracranial volume, psychosis spectrum, Mental Health, Clinical Research, Serious Mental Illness, Biomedical Imaging, Brain Disorders, Pediatric, Pediatric Research Initiative, Neurosciences, Mental health, Good Health and Well Being, Cognitive Sciences, Experimental Psychology
Abstract

Early-onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early-onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early-onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early-onset schizophrenia (n = 183), affective psychosis (n = 39), or other psychotic disorders (n = 41). We used linear mixed-effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d = -0.39) and hippocampal (d = -0.25) volumes, and higher caudate (d = 0.25) and pallidum (d = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early-onset schizophrenia (d = -0.34) and affective psychosis (d = -0.42), and early-onset schizophrenia showed lower hippocampal (d = -0.24) and higher pallidum (d = 0.29) volumes. Patients who were currently treated with antipsychotic medication (n = 193) had significantly lower intracranial volume (d = -0.42). The findings demonstrate a similar pattern of brain alterations in early-onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early-onset psychosis.

Published
2022

24. Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide

Author

Liew, Sook-Lei, Zavaliangos-Petropulu, Artemis, Schweighofer, Nicolas, Jahanshad, Neda, Lang, Catherine E, Lohse, Keith R, Banaj, Nerisa, Barisano, Giuseppe, Baugh, Lee A, Bhattacharya, Anup K, Bigjahan, Bavrina, Borich, Michael R, Boyd, Lara A, Brodtmann, Amy, Buetefisch, Cathrin M, Byblow, Winston D, Cassidy, Jessica M, Charalambous, Charalambos C, Ciullo, Valentina, Conforto, Adriana B, Craddock, Richard C, Dula, Adrienne N, Egorova, Natalia, Feng, Wuwei, Fercho, Kelene A, Gregory, Chris M, Hanlon, Colleen A, Hayward, Kathryn S, Holguin, Jess A, Hordacre, Brenton, Hwang, Darryl H, Kautz, Steven A, Khlif, Mohamed Salah, Kim, Bokkyu, Kim, Hosung, Kuceyeski, Amy, Lo, Bethany, Liu, Jingchun, Lin, David, Lotze, Martin, MacIntosh, Bradley J, Margetis, John L, Mohamed, Feroze B, Nordvik, Jan Egil, Petoe, Matthew A, Piras, Fabrizio, Raju, Sharmila, Ramos-Murguialday, Ander, Revill, Kate P, Roberts, Pamela, Robertson, Andrew D, Schambra, Heidi M, Seo, Na Jin, Shiroishi, Mark S, Soekadar, Surjo R, Spalletta, Gianfranco, Stinear, Cathy M, Suri, Anisha, Tang, Wai Kwong, Thielman, Gregory T, Thijs, Vincent N, Vecchio, Daniela, Ward, Nick S, Westlye, Lars T, Winstein, Carolee J, Wittenberg, George F, Wong, Kristin A, Yu, Chunshui, Wolf, Steven L, Cramer, Steven C, Thompson, Paul M, Baugh, Lee, Gallaguet, Adrià Bermudo, Bhattacharya, Anup, Borich, Michael, Boyd, Lara, Brown, Truman, Buetefisch, Cathrin, Byblow, Winston, Cassidy, Jessica, Charalambous, Charalambos, Cloutier, Alison, Cole, James, Conforto, Adriana, Craddock, Richard, Cramer, Steven, Aguayo, Rosalia Dacosta, DiCarlo, Julie, Dimyan, Michael, Domin, Martin, Donnellly, Miranda, Dula, Adrienne, Edwardson, Matthew, and Ermer, Elsa

Subjects
Biological Psychology, Psychology, Rehabilitation, Stroke, Brain Disorders, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, stroke, rehabilitation, sensorimotor behaviour, MRI, subcortical volumes, ENIGMA Stroke Recovery Working Group, Clinical sciences, Biological psychology
Abstract

Up to two-thirds of stroke survivors experience persistent sensorimotor impairments. Recovery relies on the integrity of spared brain areas to compensate for damaged tissue. Deep grey matter structures play a critical role in the control and regulation of sensorimotor circuits. The goal of this work is to identify associations between volumes of spared subcortical nuclei and sensorimotor behaviour at different timepoints after stroke. We pooled high-resolution T1-weighted MRI brain scans and behavioural data in 828 individuals with unilateral stroke from 28 cohorts worldwide. Cross-sectional analyses using linear mixed-effects models related post-stroke sensorimotor behaviour to non-lesioned subcortical volumes (Bonferroni-corrected, P

Published
2021

28. Perivascular spaces mediate a relationship between diabetes and other cerebral small vessel disease markers in cerebrovascular and neurodegenerative diseases

Author

Zebarth, Julia, Kamal, Radia, Perlman, George, Ouk, Michael, Xiong, Lisa Y., Yu, Di, Lin, William Z., Ramirez, Joel, Masellis, Mario, Goubran, Maged, MacIntosh, Bradley J., Black, Sandra E., Cogo-Moreira, Hugo, Scott, Christopher J.M., Bartha, Robert, Symons, Sean, Haddad, Seyyed M.H., Ozzoude, Miracle, Nanayakkara, Nuwan, Beaton, Derek, Arnott, Stephen, Dowlatshahi, Dariush, Swartz, Richard H., Saposnik, Gustavo, Grimes, David, Lang, Anthony, Fischer, Corinne E., Frank, Andrew, Kumar, Sanjeev, Pollock, Bruce G., Tang-Wai, David, Finger, Elizabeth, Rabin, Jennifer S., and Swardfager, Walter

Published
2023
Full Text
View/download PDF

29. Neuroimaging standards for research into small vessel disease—advances since 2013

Author

Duering, Marco, Biessels, Geert Jan, Brodtmann, Amy, Chen, Christopher, Cordonnier, Charlotte, de Leeuw, Frank-Erik, Debette, Stéphanie, Frayne, Richard, Jouvent, Eric, Rost, Natalia S, ter Telgte, Annemieke, Al-Shahi Salman, Rustam, Backes, Walter H, Bae, Hee-Joon, Brown, Rosalind, Chabriat, Hugues, De Luca, Alberto, deCarli, Charles, Dewenter, Anna, Doubal, Fergus N, Ewers, Michael, Field, Thalia S, Ganesh, Aravind, Greenberg, Steven, Helmer, Karl G, Hilal, Saima, Jochems, Angela C C, Jokinen, Hanna, Kuijf, Hugo, Lam, Bonnie Y K, Lebenberg, Jessica, MacIntosh, Bradley J, Maillard, Pauline, Mok, Vincent C T, Pantoni, Leonardo, Rudilosso, Salvatore, Satizabal, Claudia L, Schirmer, Markus D, Schmidt, Reinhold, Smith, Colin, Staals, Julie, Thrippleton, Michael J, van Veluw, Susanne J, Vemuri, Prashanthi, Wang, Yilong, Werring, David, Zedde, Marialuisa, Akinyemi, Rufus O, Del Brutto, Oscar H, Markus, Hugh S, Zhu, Yi-Cheng, Smith, Eric E, Dichgans, Martin, and Wardlaw, Joanna M

Published
2023
Full Text
View/download PDF

31. Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration

Author

Smith, Eric E, Biessels, Geert Jan, De Guio, François, de Leeuw, Frank Erik, Duchesne, Simon, Düring, Marco, Frayne, Richard, Ikram, M Arfan, Jouvent, Eric, MacIntosh, Bradley J, Thrippleton, Michael J, Vernooij, Meike W, Adams, Hieab, Backes, Walter H, Ballerini, Lucia, Black, Sandra E, Chen, Christopher, Corriveau, Rod, DeCarli, Charles, Greenberg, Steven M, Gurol, M Edip, Ingrisch, Michael, Job, Dominic, Lam, Bonnie YK, Launer, Lenore J, Linn, Jennifer, McCreary, Cheryl R, Mok, Vincent CT, Pantoni, Leonardo, Pike, G Bruce, Ramirez, Joel, Reijmer, Yael D, Romero, Jose Rafael, Ropele, Stefan, Rost, Natalia S, Sachdev, Perminder S, Scott, Christopher JM, Seshadri, Sudha, Sharma, Mukul, Sourbron, Steven, Steketee, Rebecca ME, Swartz, Richard H, van Oostenbrugge, Robert, van Osch, Matthias, van Rooden, Sanneke, Viswanathan, Anand, Werring, David, Dichgans, Martin, and Wardlaw, Joanna M

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Neurodegenerative, Biomedical Imaging, Brain Disorders, Neurosciences, Neurological, Cerebrovascular disease, Stroke, Dementia, Magnetic resonance imaging, Radiology, Genetics, Biological psychology
Abstract

IntroductionMany consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.MethodsSurveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.ResultsA framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.ConclusionsThe HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Published
2019

35. Standardized evaluation of the extent of resection in glioblastoma with automated early post-operative segmentation

Author

Luque, Lidia, primary, Skogen, Karoline, additional, MacIntosh, Bradley J., additional, Emblem, Kyrre E., additional, Larsson, Christopher, additional, Bouget, David, additional, Helland, Ragnhild Holden, additional, Reinertsen, Ingerid, additional, Solheim, Ole, additional, Schellhorn, Till, additional, Vardal, Jonas, additional, Mireles, Eduardo E. M., additional, Vik-Mo, Einar O., additional, and Bjørnerud, Atle, additional

Published
2024
Full Text
View/download PDF

42. Correction: Virtual Arm Boot Camp (V-ABC): study protocol for a mixed-methods study to increase upper limb recovery after stroke with an intensive program coupled with a grasp count device

Author

Simpson, Lisa A., Barclay, Ruth, Bayley, Mark T., Dukelow, Sean P., MacIntosh, Bradley J., MacKay-Lyons, Marilyn, Menon, Carlo, Mortenson, W. Ben, Peng, Tzu-Hsuan, Pollock, Courtney L., Pooyania, Sepideh, Teasell, Robert, Yang, Chieh-ling, Yao, Jennifer, and Eng, Janice J.

Published
2022
Full Text
View/download PDF

43. Virtual Arm Boot Camp (V-ABC): study protocol for a mixed-methods study to increase upper limb recovery after stroke with an intensive program coupled with a grasp count device

Author

Simpson, Lisa A., Barclay, Ruth, Bayley, Mark T., Dukelow, Sean P., MacIntosh, Bradley J., McKay-Lyons, Marilyn, Menon, Carlo, Mortenson, W. Ben, Peng, Tzu-Hsuan, Pollock, Courtney L., Pooyania, Sepideh, Teasell, Robert, Yang, Chieh-ling, Yao, Jennifer, and Eng, Janice J.

Published
2022
Full Text
View/download PDF

44. Perivascular Spaces Segmentation in Brain MRI Using Optimal 3D Filtering

Author

Ballerini, Lucia, Lovreglio, Ruggiero, Valdes-Hernandez, Maria del C., Ramirez, Joel, MacIntosh, Bradley J., Black, Sandra E., and Wardlaw, Joanna M.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Perivascular Spaces (PVS) are a recently recognised feature of Small Vessel Disease (SVD), also indicating neuroinflammation, and are an important part of the brain's circulation and glymphatic drainage system. Quantitative analysis of PVS on Magnetic Resonance Images (MRI) is important for understanding their relationship with neurological diseases. In this work, we propose a segmentation technique based on the 3D Frangi filtering for extraction of PVS from MRI. Based on prior knowledge from neuroradiological ratings of PVS, we used ordered logit models to optimise Frangi filter parameters in response to the variability in the scanner's parameters and study protocols. We optimized and validated our proposed models on two independent cohorts, a dementia sample (N=20) and patients who previously had mild to moderate stroke (N=48). Results demonstrate the robustness and generalisability of our segmentation method. Segmentation-based PVS burden estimates correlated with neuroradiological assessments (Spearman's $\rho$ = 0.74, p $<$ 0.001), suggesting the great potential of our proposed method

Published
2017
Full Text
View/download PDF

45. Effects of post-acute COVID-19 syndrome on cerebral white matter and emotional health among non-hospitalized individuals.

Author

Churchill, Nathan W., Roudaia, Eugenie, Chen, J. Jean, Sekuler, Allison, Fuqiang Gao, Masellis, Mario, Lam, Benjamin, Cheng, Ivy, Heyn, Chris, Black, Sandra E., MacIntosh, Bradley J., Graham, Simon J., and Schweizer, Tom A.

Subjects
POST-acute COVID-19 syndrome, DIFFUSION magnetic resonance imaging, WHITE matter (Nerve tissue), AFFECT (Psychology), VIRUS diseases
Abstract

Introduction: Post-acute COVID syndrome (PACS) is a growing concern, given its impact on mental health and quality of life. However, its effects on cerebral white matter remain poorly understood, particularly in non-hospitalized cohorts. The goals of this cross-sectional, observational study were to examine (1) whether PACS was associated with distinct alterations in white matter microstructure, compared to symptom-matched non-COVID viral infection; and (2) whether microstructural alterations correlated with indices of post-COVID emotional health. Methods: Data were collected for 54 symptomatic individuals who tested positive for COVID-19 (mean age 41 ± 12 yrs., 36 female) and 14 controls who tested negative for COVID-19 (mean age 41 ± 14 yrs., 8 female), with both groups assessed an average of 4-5 months after COVID testing. Diffusion magnetic resonance imaging data were collected, and emotional health was assessed via the NIH emotion toolbox, with summary scores indexing social satisfaction, well-being and negative affect. Results: Despite similar symptoms, the COVID-19 group had reduced mean and axial diffusivity, along with increased mean kurtosis and neurite dispersion, in deep white matter. After adjusting for social satisfaction, higher levels of negative affect in the COVID-19 group were also correlated with increased mean kurtosis and reduced free water in white matter. Discussion: These results provide preliminary evidence that indices of white matter microstructure distinguish PACS from symptomatic non-COVID infection. Moreover, white matter effects seen in PACS correlate with the severity of emotional sequelae, providing novel insights into this highly prevalent disorder. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

46. Recommendations for quantitative cerebral perfusion MRI using multi‐timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Author

Woods, Joseph G., Achten, Eric, Asllani, Iris, Bolar, Divya S., Dai, Weiying, Detre, John A., Fan, Audrey P., Fernández‐Seara, María A., Golay, Xavier, Günther, Matthias, Guo, Jia, Hernandez‐Garcia, Luis, Ho, Mai‐Lan, Juttukonda, Meher R., Lu, Hanzhang, MacIntosh, Bradley J., Madhuranthakam, Ananth J., Mutsaerts, Henk‐Jan, Okell, Thomas W., and Parkes, Laura M.

Subjects
SPIN labels, PERFUSION, CLINICAL medicine, PERFUSION imaging, MAGNETIC resonance imaging
Abstract

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision‐making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi‐timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post‐labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi‐timepoint data can be acquired in the same scan time as single‐PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single‐PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi‐timepoint ASL and provides robust recommendations for acquiring high‐quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi‐timepoint ASL data. Furthermore, we review the potential clinical applications where multi‐timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

48. Neuroimaging and Biosample Collection in the Toronto Adolescent and Youth Cohort Study: Rationale, Methods, and Early Data

Author

Dickie, Erin W., primary, Ameis, Stephanie H., additional, Boileau, Isabelle, additional, Diaconescu, Andreea O., additional, Felsky, Daniel, additional, Goldstein, Benjamin I., additional, Gonçalves, Vanessa, additional, Griffiths, John D., additional, Haltigan, John D., additional, Husain, Muhammad O., additional, Rubin-Kahana, Dafna S., additional, Iftikhar, Myera, additional, Jani, Melanie, additional, Lai, Meng-Chuan, additional, Lin, Hsiang-Yuan, additional, MacIntosh, Bradley J., additional, Wheeler, Anne L., additional, Vasdev, Neil, additional, Vieira, Erica, additional, Ahmadzadeh, Ghazaleh, additional, Heyland, Lindsay, additional, Mohan, Akshay, additional, Ogunsanya, Feyi, additional, Oliver, Lindsay D., additional, Zhu, Cherrie, additional, Wong, Jimmy K.Y., additional, Charlton, Colleen, additional, Truong, Jennifer, additional, Yu, Lujia, additional, Kelly, Rachel, additional, Cleverley, Kristin, additional, Courtney, Darren B., additional, Foussias, George, additional, Hawke, Lisa D., additional, Hill, Sean, additional, Kozloff, Nicole, additional, Polillo, Alexia, additional, Rotenberg, Martin, additional, Quilty, Lena C., additional, Tempelaar, Wanda, additional, Wang, Wei, additional, Nikolova, Yuliya S., additional, Voineskos, Aristotle N., additional, Aitken, Madison, additional, Andrade, Brendan F., additional, Battaglia, Marco, additional, Dickie, Erin W., additional, Hamilton, Hayley, additional, Husain, Muhammad Omair, additional, Kidd, Sean A., additional, Kurdyak, Paul, additional, Lewis, Stephen P., additional, Levitan, Robert D., additional, Lunsky, Yona, additional, Osman, Sam, additional, Pascoe, Shannon, additional, Putterman, Connie, additional, Sivakumar, Harijah, additional, Szatmari, Peter, additional, van der Miesen, Anna I.R., additional, and Vieira, Erica L., additional

Published
2024
Full Text
View/download PDF

50. Cannabis use and resting state functional connectivity in adolescent bipolar disorder

Author

Sultan, Alysha A., Hird, Megan A., Dimick, Mikaela K., MacIntosh, Bradley J., and Goldstein, Benjamin I.

Subjects
Bipolar disorder -- Development and progression, Brain -- Health aspects, Neural circuitry -- Health aspects, Child psychopathology -- Development and progression, Marijuana -- Psychological aspects -- Health aspects -- Demographic aspects, Health, Psychology and mental health
Abstract

Background: Adolescents with bipolar disorder have high rates of cannabis use, and cannabis use is associated with increased symptom severity and treatment resistance in bipolar disorder. Studies have identified anomalous resting-state functional connectivity among reward networks in bipolar disorder and cannabis use independently, but have yet to examine their convergence. Methods: Participants included 134 adolescents, aged 13 to 20 years: 40 with bipolar disorder and lifetime cannabis use, 31 with bipolar disorder and no history of cannabis use, and 63 healthy controls without lifetime cannabis use. We used a seed-to-voxel analysis to assess the restingstate functional connectivity of the amygdala, the nucleus accumbens and the orbitofrontal cortex, regions implicated in bipolar disorder and cannabis use. We used a generalized linear model to explore bivariate correlations for each seed, controlling for age and sex. Results: We found 3 significant clusters. Resting-state functional connectivity between the left nucleus accumbens seed and the left superior parietal lobe was negative in adolescents with bipolar disorder and no history of cannabis use, and positive in healthy controls. Resting-state functional connectivity between the right orbitofrontal cortex seed and the right lateral occipital cortex was positive in adolescents with bipolar disorder and lifetime cannabis use, and negative in healthy controls and adolescents with bipolar disorder and no history of cannabis use. Resting-state functional connectivity between the right orbitofrontal cortex seed and right occipital pole was positive in adolescents with bipolar disorder and lifetime cannabis use, and negative in adolescents with bipolar disorder and no history of cannabis use. Limitations: The study did not include a cannabis-using control group. Conclusion: This study provides preliminary evidence of cannabis-related differences in functional reward circuits in adolescents with bipolar disorder. Further studies are necessary to evaluate whether the present findings reflect consequences of or predisposition to cannabis use., Introduction Bipolar disorder affects approximately 2% to 5% of adolescents worldwide, and is characterized by recurrent mood episodes, including depression and mania or hypomania. (1,2) Bipolar disorder is associated with [...]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results