Automatic segmentation of the spinal cord nerve rootlets
Jan Valošek
Theo Mathieu
Raphaëlle Schlienger
Olivia S. Kowalczyk
Abstract Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the … (voir plus)spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.
Automatic segmentation of the spinal cord nerve rootlets
Jan Valošek
Theo Mathieu
Raphaëlle Schlienger
Olivia S. Kowalczyk
Abstract Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the … (voir plus)spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.
Co-developing The Canadian MPS Registry: A longitudinal rare disease patient registry
John J. Mitchell
Michal Inbar-Feigenberg
Kim Angel
Pranesh Chakraborty
Monica Lamoureux
John Adams
Beth K. Potter
Sylvia Stockler-Ipsirolgu
Alison H. Howie
Alex Pace
Nancy J. Butcher
Cheryl Greenberg
Robin Hayeems
Anne-Marie Laberge
Jeff Round
Martin Offringa
Maryam Oskoui
Chelsea Ruth
Andreas Schulze
Kathy N. Speechley … (voir 4 de plus)
Kednapa Thavorn
Kumanan Wilson
Thierry Lacaze
Data science opportunities of large language models for neuroscience and biomedicine
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Data science opportunities of large language models for neuroscience and biomedicine
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Data science opportunities of large language models for neuroscience and biomedicine
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Data science opportunities of large language models for neuroscience and biomedicine
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
A database of the healthy human spinal cord morphometry in the PAM50 template space
Jan Valošek
Sandrine Bédard
Miloš Keřkovský
Tomáš Rohan
Abstract Measures of spinal cord morphometry computed from magnetic resonance images serve as relevant prognostic biomarkers for a range of … (voir plus)spinal cord pathologies, including traumatic and non-traumatic spinal cord injury and neurodegenerative diseases. However, interpreting these imaging biomarkers is difficult due to considerable intra- and inter-subject variability. Yet, there is no clear consensus on a normalization method that would help reduce this variability and more insights into the distribution of these morphometrics are needed. In this study, we computed a database of normative values for six commonly used measures of spinal cord morphometry: cross-sectional area, anteroposterior diameter, transverse diameter, compression ratio, eccentricity, and solidity. Normative values were computed from a large open-access dataset of healthy adult volunteers (N = 203) and were brought to the common space of the PAM50 spinal cord template using a newly proposed normalization method based on linear interpolation. Compared to traditional image-based registration, the proposed normalization approach does not involve image transformations and, therefore, does not introduce distortions of spinal cord anatomy. This is a crucial consideration in preserving the integrity of the spinal cord anatomy in conditions such as spinal cord injury. This new morphometric database allows researchers to normalize based on sex and age, thereby minimizing inter-subject variability associated with demographic and biological factors. The proposed methodology is open-source and accessible through the Spinal Cord Toolbox (SCT) v6.0 and higher.
A database of the healthy human spinal cord morphometry in the PAM50 template space
Jan Valošek
Sandrine Bédard
Miloš Keřkovský
Tomáš Rohan
Abstract Measures of spinal cord morphometry computed from magnetic resonance images serve as relevant prognostic biomarkers for a range of … (voir plus)spinal cord pathologies, including traumatic and non-traumatic spinal cord injury and neurodegenerative diseases. However, interpreting these imaging biomarkers is difficult due to considerable intra- and inter-subject variability. Yet, there is no clear consensus on a normalization method that would help reduce this variability and more insights into the distribution of these morphometrics are needed. In this study, we computed a database of normative values for six commonly used measures of spinal cord morphometry: cross-sectional area, anteroposterior diameter, transverse diameter, compression ratio, eccentricity, and solidity. Normative values were computed from a large open-access dataset of healthy adult volunteers (N = 203) and were brought to the common space of the PAM50 spinal cord template using a newly proposed normalization method based on linear interpolation. Compared to traditional image-based registration, the proposed normalization approach does not involve image transformations and, therefore, does not introduce distortions of spinal cord anatomy. This is a crucial consideration in preserving the integrity of the spinal cord anatomy in conditions such as spinal cord injury. This new morphometric database allows researchers to normalize based on sex and age, thereby minimizing inter-subject variability associated with demographic and biological factors. The proposed methodology is open-source and accessible through the Spinal Cord Toolbox (SCT) v6.0 and higher.
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
Lingkai Kong
Yuanqi Du
Wenhao Mu
Valentin De Bortol
Haorui Wang
Dongxia Wu
Aaron Ferber
Yi-An Ma
Carla P. Gomes
Chao Zhang
Addressing real-world optimization problems becomes particularly challenging when analytic objective functions or constraints are unavailabl… (voir plus)e. While numerous studies have addressed the issue of unknown objectives, limited research has focused on scenarios where feasibility constraints are not given explicitly. Overlooking these constraints can lead to spurious solutions that are unrealistic in practice. To deal with such unknown constraints, we propose to perform optimization within the data manifold using diffusion models. To constrain the optimization process to the data manifold, we reformulate the original optimization problem as a sampling problem from the product of the Boltzmann distribution defined by the objective function and the data distribution learned by the diffusion model. Depending on the differentiability of the objective function, we propose two different sampling methods. For differentiable objectives, we propose a two-stage framework that begins with a guided diffusion process for warm-up, followed by a Langevin dynamics stage for further correction. For non-differentiable objectives, we propose an iterative importance sampling strategy using the diffusion model as the proposal distribution. Comprehensive experiments on a synthetic dataset, six real-world black-box optimization datasets, and a multi-objective molecule optimization dataset show that our method achieves better or comparable performance with previous state-of-the-art baselines.
Family‐centred care interventions for children with chronic conditions: A scoping review
Andrea J. Chow
Ammar Saad
Zobaida Al‐Baldawi
Ryan Iverson
Becky Skidmore
Isabel Jordan
Nicole Pallone
Maureen Smith
Pranesh Chakraborty
Jamie Brehaut
Eyal Cohen
Sarah Dyack
Jane Gillis
Sharan Goobie
Cheryl Greenberg
Robin Hayeems
Brian Hutton
Michal Inbar-Feigenberg
Shailly Jain-Ghai
Sara Khangura … (voir 18 de plus)
Jennifer MacKenzie
John J. Mitchell
Zeinab Moazin
Stuart G. Nicholls
Amy Pender
Chitra Prasad
Andreas Schulze
Komudi Siriwardena
Rebecca N. Sparkes
Kathy N. Speechley
Sylvia Stockler
Monica Taljaard
Mari Teitelbaum
Clara Van Karnebeek
Jagdeep S. Walia
Kumanan Wilson
Beth K. Potter
Children with chronic conditions have greater health care needs than the general paediatric population but may not receive care that centres… (voir plus) their needs and preferences as identified by their families. Clinicians and researchers are interested in developing interventions to improve family‐centred care need information about the characteristics of existing interventions, their development and the domains of family‐centred care that they address. We conducted a scoping review that aimed to identify and characterize recent family‐centred interventions designed to improve experiences with care for children with chronic conditions.
Family‐centred care interventions for children with chronic conditions: A scoping review
Andrea J. Chow
Ammar Saad
Zobaida Al‐Baldawi
Ryan Iverson
Becky Skidmore
Isabel Jordan
Nicole Pallone
Maureen Smith
Pranesh Chakraborty
Jamie Brehaut
Eyal Cohen
Sarah Dyack
Jane Gillis
Sharan Goobie
Cheryl Greenberg
Robin Hayeems
Brian Hutton
Michal Inbar-Feigenberg
Shailly Jain-Ghai
Sara Khangura … (voir 18 de plus)
Jennifer MacKenzie
John J. Mitchell
Zeinab Moazin
Stuart G. Nicholls
Amy Pender
Chitra Prasad
Andreas Schulze
Komudi Siriwardena
Rebecca N. Sparkes
Kathy N. Speechley
Sylvia Stockler
Monica Taljaard
Mari Teitelbaum
Clara Van Karnebeek
Jagdeep S. Walia
Kumanan Wilson
Beth K. Potter
Children with chronic conditions have greater health care needs than the general paediatric population but may not receive care that centres… (voir plus) their needs and preferences as identified by their families. Clinicians and researchers are interested in developing interventions to improve family‐centred care need information about the characteristics of existing interventions, their development and the domains of family‐centred care that they address. We conducted a scoping review that aimed to identify and characterize recent family‐centred interventions designed to improve experiences with care for children with chronic conditions.