Learning Amyloid Pathology Progression from Longitudinal PIB-PET Images in Preclinical Alzheimer's Disease

Wei, Hao; Vogt, N.; Meng, Zihang; Hwang, Seong Jae; Koscik, Rebecca L.; Johnson, Sterling C.; Bendlin, Barbara B.; Singh, Vikas

doi:10.1109/isbi45749.2020.9098571

Cited by 2 publications

(2 citation statements)

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“…We are hopeful that both the neuroanatomical and model-based approach and the empirical results from this study can support future work on ERI and generalize to other research domains that seek to integrate the transdiagnostic study of psychopathology at two crucial levels of analysis, psychiatry, and neuroscience. To expedite this goal, tools are actively being developed to leverage deep learning algorithms as a guide to semi-automate the definition of neuroanatomical structures such as the small and variable tertiary sulci explored here (71,72). Such tools will be sure to increase the sample size, which is a main limitation of the present study, as well as shed further light on the relationship between tertiary sulci and psychopathology.…”

Section: Discussionmentioning

confidence: 99%

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Hastings,

Willbrand,

Elliott

et al. 2024

Preprint

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BackgroundEmotion-related impulsivity (ERI) describes the trait-like tendency toward poor self-control when experiencing strong emotions. ERI has been shown to be elevated across psychiatric disorders and predictive of the onset and worsening of psychiatric syndromes. Recent work has correlated ERI scores with the neuroanatomy of the orbitofrontal cortex (OFC). Informed by a growing body of research indicating that the morphology of cortical folds (sulci) can produce insights into behavioral outcomes, the present study modeled the association between ERI and the sulcal morphology of OFC at a finer scale than previously conducted.MethodsAnalyses were conducted in a transdiagnostic sample of 118 individuals with a broad range of psychiatric syndromes. We first manually defined over 2000 sulci across the 118 participants. We then implemented a model-based LASSO regression to relate OFC sulcal morphology to ERI and test whether effects were specific to ERI as compared to non-emotion-related impulsivity.ResultsThe LASSO regression revealed bilateral associations of ERI with the depth of eight OFC sulci. These effects were specific to ERI and were not observed in non-emotion-related impulsivity. In addition, we identified a new transverse component of the olfactory sulcus in every hemisphere that is dissociable from the longitudinal component based on anatomical features and correlation with behavior, which could serve as a new transdiagnostic biomarker.ConclusionsThe results of this data-driven investigation provide greater neuroanatomical and neurodevelopmental specificity on how OFC is related to ERI. As such, findings link neuroanatomical characteristics to a trait that is highly predictive of psychopathology.

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Section: Discussionmentioning

confidence: 99%

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Hastings,

Willbrand,

Elliott

et al. 2024

Preprint

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“…Hao et al [78] aim to utilize NODE to infer the propagation dynamics of amyloid pathology, which is considered the primary pathological event in AD. The method involves constructing a brain network graph where each node represents a cortical or subcortical gray matter region, and edges denote connectivity strength.…”

Section: Applications In Disease Predictionmentioning

confidence: 99%

On the Applications of Neural Ordinary Differential Equations in Medical Image Analysis

Niu,

Zhou,

Yan

et al. 2024

Preprint

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Medical image analysis tasks are characterized by high-noise, volumetric, and multi-modality, posing challenges for the model that attempts to learn robust features from the input images. Over the last decade, deep neural networks (DNNs) have achieved enormous success in medical image analysis tasks, which can be attributed to their powerful feature representation capability. Despite the promising results reported in numerous literature, DNNs are also criticized for several pivotal limits, with one of the limitations is lack of safety. Safety plays an important role in the applications of DNNs during clinical practice, helping the model defend against potential attacks and preventing the model from silent failure prediction. The recently proposed Neural Ordinary Differential Equation (NODE), a continuous model bridging the gap between DNNs and ODE, provides a significant advantage in ensuring the model's safety. Among the variants of NODE, the neural memory ordinary differential equation (nmODE) owns the global attractor theoretically, exhibiting superiority in prompting the model's performance and robustness during applications. While NODE and its variants have been widely used in medical image analysis tasks, there is a lack of a comprehensive review of their applications, hindering the in-depth understanding of NODE's working principle and its potential applications. To mitigate this limitation, this paper thoroughly reviews the literature on the applications of NODE in medical image analysis from the following five aspects: segmentation, reconstruction, registration, disease prediction, and data generation. We also summarize both the strengths and downsides of the applications of NODE, followed by the possible research directions. To the best of our knowledge, this is the first review regards the applications of NODE in the field of medical image analysis. We hope this review can draw the researchers' attention to the great potential of NODE and its variants in medical image analysis.

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Learning Amyloid Pathology Progression from Longitudinal PIB-PET Images in Preclinical Alzheimer's Disease

Cited by 2 publications

References 11 publications

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

On the Applications of Neural Ordinary Differential Equations in Medical Image Analysis

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