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Article ; Online: Image harmonization improves consistency of intra-rater delineations of MS lesions in heterogeneous MRI.

Carass, Aaron / Greenman, Danielle / Dewey, Blake E / Calabresi, Peter A / Prince, Jerry L / Pham, Dzung L

Neuroimage. Reports

2024 Volume 4, Issue 1

Abstract: Clinical magnetic resonance images (MRIs) lack a standard intensity scale due to differences in scanner hardware and the pulse sequences used to acquire the images. When MRIs are used for quantification, as in the evaluation of white matter lesions (WMLs) ...

Abstract	Clinical magnetic resonance images (MRIs) lack a standard intensity scale due to differences in scanner hardware and the pulse sequences used to acquire the images. When MRIs are used for quantification, as in the evaluation of white matter lesions (WMLs) in multiple sclerosis, this lack of intensity standardization becomes a critical problem affecting both the staging and tracking of the disease and its treatment. This paper presents a study of harmonization on WML segmentation consistency, which is evaluated using an object detection classification scheme that incorporates manual delineations from both the original and harmonized MRIs. A cohort of ten people scanned on two different imaging platforms was studied. An expert rater, blinded to the image source, manually delineated WMLs on images from both scanners before and after harmonization. It was found that there is closer agreement in both global and per-lesion WML volume and spatial distribution after harmonization, demonstrating the importance of image harmonization prior to the creation of manual delineations. These results could lead to better truth models in both the development and evaluation of automated lesion segmentation algorithms.
Language	English
Publishing date	2024-02-02
Publishing country	Netherlands
Document type	Journal Article
ISSN	2666-9560
ISSN (online)	2666-9560
DOI	10.1016/j.ynirp.2024.100195
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Book ; Online: RAIFLE

Pham, Dzung / Kulkarni, Shreyas / Houmansadr, Amir

Reconstruction Attacks on Interaction-based Federated Learning with Active Data Manipulation

2023

Abstract: Federated learning (FL) has recently emerged as a privacy-preserving approach for machine learning in domains that rely on user interactions, particularly recommender systems (RS) and online learning to rank (OLTR). While there has been substantial ... ...

Abstract	Federated learning (FL) has recently emerged as a privacy-preserving approach for machine learning in domains that rely on user interactions, particularly recommender systems (RS) and online learning to rank (OLTR). While there has been substantial research on the privacy of traditional FL, little attention has been paid to studying the privacy properties of these interaction-based FL (IFL) systems. In this work, we show that IFL can introduce unique challenges concerning user privacy, particularly when the central server has knowledge and control over the items that users interact with. Specifically, we demonstrate the threat of reconstructing user interactions by presenting RAIFLE, a general optimization-based reconstruction attack framework customized for IFL. RAIFLE employs Active Data Manipulation (ADM), a novel attack technique unique to IFL, where the server actively manipulates the training features of the items to induce adversarial behaviors in the local FL updates. We show that RAIFLE is more impactful than existing FL privacy attacks in the IFL context, and describe how it can undermine privacy defenses like secure aggregation and private information retrieval. Based on our findings, we propose and discuss countermeasure guidelines to mitigate our attack in the context of federated RS/OLTR specifically and IFL more broadly.
Keywords	Computer Science - Cryptography and Security ; Computer Science - Machine Learning
Subject code	004
Publishing date	2023-10-29
Publishing country	us
Document type	Book ; Online
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Article ; Online: Simultaneous Acquisition of Diffusion Tensor and Dynamic Diffusion MRI.

Gangolli, Mihika / Wang, Wen-Tung / Gai, Neville D / Pham, Dzung L / Butman, John A

Journal of magnetic resonance imaging : JMRI

2022 Volume 57, Issue 4, Page(s) 1079–1092

Abstract: Background: Dynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application.: Purpose: To determine whether a ... ...

Abstract	Background: Dynamic diffusion magnetic resonance imaging (ddMRI) metrics can assess transient microstructural alterations in tissue diffusivity but requires additional scan time hindering its clinical application. Purpose: To determine whether a diffusion gradient table can simultaneously acquire data to estimate dynamic and diffusion tensor imaging (DTI) metrics. Study type: Prospective. Subjects: Seven healthy subjects, 39 epilepsy patients (15 female, 31 male, age ± 15). Field strength/sequence: Two-dimensional diffusion MRI (b = 1000 s/mm Assessment: Fifteen direction DTI was repeated twice for within-session test-retest measurements in healthy subjects. Bland-Altman analysis computed bias and limits of agreement for DTI metrics using test-retest scans and standard 15 direction vs. 5 nested cubes scans. Intraclass correlation (ICC) analysis compared tensor metrics between 15 direction DTI scans (standard vs. 5 nested cubes) and the coefficients of variation (CoV) of trace and apparent diffusion coefficient (ADC) between 30 direction ddMRI scans (standard vs. 10 nested cubes). Statistical tests: Bland-Altman and ICC analysis using a P-value of 0.05 for statistical significance. Results: Correlations of mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were strong and significant in gray (ICC > 0.95) and white matter (ICC > 0.95) between standard vs. nested cubes DTI acquisitions. Correlation of white matter fractional anisotropy was also strong (ICC > 0.95) and significant. ICCs of the CoV of dynamic ADC measured using repeated cubes and nested cubes acquisitions were modest (ICC >0.60), but significant in gray matter. Conclusion: A nested cubes diffusion gradient table produces tensor-based and dynamic diffusion measurements in a single acquisition. Level of evidence: 2 TECHNICAL EFFICACY: Stage 1.
MeSH term(s)	Humans ; Male ; Female ; Adolescent ; Diffusion Tensor Imaging/methods ; Prospective Studies ; Diffusion Magnetic Resonance Imaging ; White Matter/pathology ; Epilepsy/pathology ; Anisotropy
Language	English
Publishing date	2022-09-03
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Intramural
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.28407
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Article: Automated Classification of Resting-State fMRI ICA Components Using a Deep Siamese Network.

Chou, Yiyu / Chang, Catie / Remedios, Samuel W / Butman, John A / Chan, Leighton / Pham, Dzung L

Frontiers in neuroscience

2022 Volume 16, Page(s) 768634

Abstract: Manual classification of functional resting state networks (RSNs) derived from Independent Component Analysis (ICA) decomposition can be labor intensive and requires expertise, particularly in large multi-subject analyses. Hence, a fully automatic ... ...

Abstract	Manual classification of functional resting state networks (RSNs) derived from Independent Component Analysis (ICA) decomposition can be labor intensive and requires expertise, particularly in large multi-subject analyses. Hence, a fully automatic algorithm that can reliably classify these RSNs is desirable. In this paper, we present a deep learning approach based on a Siamese Network to learn a discriminative feature representation for single-subject ICA component classification. Advantages of this supervised framework are that it requires relatively few training data examples and it does not require the number of ICA components to be specified. In addition, our approach permits one-shot learning, which allows generalization to new classes not seen in the training set with only one example of each new class. The proposed method is shown to out-perform traditional convolutional neural network (CNN) and template matching methods in identifying eleven subject-specific RSNs, achieving 100% accuracy on a holdout data set and over 99% accuracy on an outside data set. We also demonstrate that the method is robust to scan-rescan variation. Finally, we show that the functional connectivity of default mode and salience networks identified by the proposed technique is altered in a group analysis of mild traumatic brain injury (TBI), severe TBI, and healthy subjects.
Language	English
Publishing date	2022-03-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2411902-7
ISSN	1662-453X ; 1662-4548
ISSN (online)	1662-453X
ISSN	1662-4548
DOI	10.3389/fnins.2022.768634
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Article ; Online: Segmented 3D Echo Planar Acquisition for Rapid Susceptibility-Weighted Imaging: Application to Microhemorrhage Detection in Traumatic Brain Injury.

Wang, Wen-Tung / Li, Ningzhi / Papageorgiou, Ioannis / Chan, Leighton / Pham, Dzung L / Butman, John A

Journal of magnetic resonance imaging : JMRI

2022 Volume 56, Issue 5, Page(s) 1529–1535

Abstract: Background: Susceptibility-weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three-dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time.: Purpose: To evaluate ... ...

Abstract	Background: Susceptibility-weighted imaging (SWI) provides superior image contrast of cerebral microhemorrhages (CMBs). It is based on a three-dimensional (3D) gradient echo (GRE) sequence with a relatively long imaging time. Purpose: To evaluate whether an accelerated 3D segmented echo planar imaging SWI is comparable to GRE SWI in detecting CMBs in traumatic brain injury (TBI). Study type: Prospective. Subjects: Four healthy volunteers and 46 consecutive subjects (38.0 ± 14.4 years, 16 females; 12 mild, 13 moderate, and 7 severe TBI). Field strength/sequence: A 3 T scanner/3D gradient echo and 3D segmented echo planar imaging (segEPI). Assessment: Brain images were acquired using GRE and segEPI in a single session (imaging time = 9 minutes 47 seconds and 1 minute 30 seconds, respectively). The signal-to-noise ratio (SNR) calculated from healthy volunteer thalamus and centrum semiovale were compared. CMBs were counted by three raters blinded to diagnostic information. Statistical tests: A t-test was used to assess SNR difference. Pearson correlation and Wilcoxon signed-rank test were performed using CMB counts. The intermethod agreement was evaluated using Bland-Altman method. Intermethod and interrater reliabilities of image-based diffuse axonal injury (DAI) diagnoses were evaluated using Cohen's kappa and percent agreement. P ≤ 0.05 was considered statistically significant. Results: Thalamus SNRs were 16.9 ± 2.2 and 16.5 ± 3 for GRE and segEPI (P = 0.84), respectively. Centrum semiovale SNRs were 25.8 ± 4.6 and 21.1 ± 2.7 (P = 0.13). The correlation coefficient of CMBs was 0.93, and differences were not significant (P = 0.56-0.85). For DAI diagnoses, Cohen's kappa was 0.62-0.84 and percent agreement was 85%-94%. Data conclusion: CMB counts on segEPI and GRE were highly correlated, and DAI diagnosis was made equally effectively. segEPI SWI can potentially replace GRE SWI in detecting TBI CMBs, especially when time constraints are critical. Evidence level: 1 TECHNICAL EFFICACY: Stage 2.
MeSH term(s)	Brain Injuries, Traumatic/complications ; Brain Injuries, Traumatic/diagnostic imaging ; Diffuse Axonal Injury ; Echo-Planar Imaging/methods ; Female ; Humans ; Magnetic Resonance Imaging/methods ; Prospective Studies
Language	English
Publishing date	2022-07-19
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Intramural ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.28326
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Article ; Online: Associations between white matter integrity and postural control in adults with traumatic brain injury.

Zampieri, Cris / Leary, Jacob B / Shahim, Pashtun / Damiano, Diane / Ho, Pei-Shu / Pham, Dzung L / Chan, Leighton

PloS one

2023 Volume 18, Issue 11, Page(s) e0288727

Abstract: Abnormalities of postural sway have been extensively reported in traumatic brain injury (TBI). However, the underlying neural correlates of balance disturbances in TBI remain to be elucidated. Studies in children with TBI have reported associations ... ...

Abstract	Abnormalities of postural sway have been extensively reported in traumatic brain injury (TBI). However, the underlying neural correlates of balance disturbances in TBI remain to be elucidated. Studies in children with TBI have reported associations between the Sensory Organization Test (SOT) and measures of white matter (WM) integrity with diffusion tensor imaging (DTI) in brain areas responsible for multisensory integration. This study seeks to replicate those associations in adults as well as explore relationships between DTI and the Limits of Stability (LOS) Test. Fifty-six participants (43±17 years old) with a history of TBI were tested 30 days to 5 years post-TBI. This study confirmed results in children for associations between the SOT and the medial lemniscus as well as middle cerebellar peduncle, and revealed additional associations with the posterior thalamic radiation. Additionally, this study found significant correlations between abnormal LOS scores and impaired WM integrity in the cingulum, corpus callosum, corticopontine and corticospinal tracts, fronto-occipital fasciculi, longitudinal fasciculi, medial lemniscus, optic tracts and thalamic radiations. Our findings indicate the involvement of a broad range of WM tracts in the control of posture, and demonstrate the impact of TBI on balance via disruptions to WM integrity.
MeSH term(s)	Child ; Humans ; Adult ; Middle Aged ; White Matter/diagnostic imaging ; Diffusion Tensor Imaging/methods ; Brain/diagnostic imaging ; Brain Injuries, Traumatic/diagnostic imaging ; Postural Balance
Language	English
Publishing date	2023-11-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0288727
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Article ; Online: Comparison of Deformation Patterns Excited in the Human Brain In Vivo by Harmonic and Impulsive Skull Motion.

Escarcega, Jordan D / Knutsen, Andrew K / Alshareef, Ahmed A / Johnson, Curtis L / Okamoto, Ruth J / Pham, Dzung L / Bayly, Philip V

Journal of biomechanical engineering

2023 Volume 145, Issue 8

Abstract: Noninvasive measurements of brain deformation in human participants in vivo are needed to develop models of brain biomechanics and understand traumatic brain injury (TBI). Tagged magnetic resonance imaging (tagged MRI) and magnetic resonance elastography ...

Abstract	Noninvasive measurements of brain deformation in human participants in vivo are needed to develop models of brain biomechanics and understand traumatic brain injury (TBI). Tagged magnetic resonance imaging (tagged MRI) and magnetic resonance elastography (MRE) are two techniques to study human brain deformation; these techniques differ in the type of motion and difficulty of implementation. In this study, oscillatory strain fields in the human brain caused by impulsive head acceleration and measured by tagged MRI were compared quantitatively to strain fields measured by MRE during harmonic head motion at 10 and 50 Hz. Strain fields were compared by registering to a common anatomical template, then computing correlations between the registered strain fields. Correlations were computed between tagged MRI strain fields in six participants and MRE strain fields at 10 Hz and 50 Hz in six different participants. Correlations among strain fields within the same experiment type were compared statistically to correlations from different experiment types. Strain fields from harmonic head motion at 10 Hz imaged by MRE were qualitatively and quantitatively similar to modes excited by impulsive head motion, imaged by tagged MRI. Notably, correlations between strain fields from 10 Hz MRE and tagged MRI did not differ significantly from correlations between strain fields from tagged MRI. These results suggest that low-frequency modes of oscillation dominate the response of the brain during impact. Thus, low-frequency MRE, which is simpler and more widely available than tagged MRI, can be used to illuminate the brain's response to head impact.
MeSH term(s)	Humans ; Brain/diagnostic imaging ; Skull/diagnostic imaging ; Skull/physiology ; Head ; Motion ; Brain Injuries ; Magnetic Resonance Imaging ; Elasticity Imaging Techniques
Language	English
Publishing date	2023-06-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	243094-0
ISSN	1528-8951 ; 0148-0731
ISSN (online)	1528-8951
ISSN	0148-0731
DOI	10.1115/1.4062809
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Article: Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.

Remedios, Samuel W / Butman, John A / Landman, Bennett A / Pham, Dzung L

Lecture notes-monograph series

2020 Volume 12444

Abstract: Multi-site training methods for artificial neural networks are of particular interest to the medical machine learning community primarily due to the difficulty of data sharing between institutions. However, contemporary multi-site techniques such as ... ...

Abstract	Multi-site training methods for artificial neural networks are of particular interest to the medical machine learning community primarily due to the difficulty of data sharing between institutions. However, contemporary multi-site techniques such as weight averaging and cyclic weight transfer make theoretical sacrifices to simplify implementation. In this paper, we implement federated gradient averaging (FGA), a variant of federated learning without data transfer that is mathematically equivalent to single site training with centralized data. We evaluate two scenarios: a simulated multi-site dataset for handwritten digit classification with MNIST and a real multi-site dataset with head CT hemorrhage segmentation. We compare federated gradient averaging to single site training, federated weight averaging (FWA), and cyclic weight transfer. In the MNIST task, we show that training with FGA results in a weight set equivalent to centralized single site training. In the hemorrhage segmentation task, we show that FGA achieves on average superior results to both FWA and cyclic weight transfer due to its ability to leverage momentum-based optimization.
Language	English
Publishing date	2020-09-26
Publishing country	United States
Document type	Journal Article
ISSN	0749-2170
ISSN	0749-2170
DOI	10.1007/978-3-030-60548-3_17
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Article: Joint Image and Label Self-Super-Resolution.

Remedios, Samuel W / Han, Shuo / Dewey, Blake E / Pham, Dzung L / Prince, Jerry L / Carass, Aaron

Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI (Workshop)

2021 Volume 12965, Page(s) 14–23

Abstract: We propose a method to jointly super-resolve an anisotropic image volume along with its corresponding voxel labels without external training data. Our method is inspired by internally trained superresolution, or self-super-resolution (SSR) techniques ... ...

Abstract	We propose a method to jointly super-resolve an anisotropic image volume along with its corresponding voxel labels without external training data. Our method is inspired by internally trained superresolution, or self-super-resolution (SSR) techniques that target anisotropic, low-resolution (LR) magnetic resonance (MR) images. While resulting images from such methods are quite useful, their corresponding LR labels-derived from either automatic algorithms or human raters-are no longer in correspondence with the super-resolved volume. To address this, we develop an SSR deep network that takes both an anisotropic LR MR image and its corresponding LR labels as input and produces both a super-resolved MR image and its super-resolved labels as output. We evaluated our method with 50
Language	English
Publishing date	2021-09-21
Publishing country	Switzerland
Document type	Journal Article
DOI	10.1007/978-3-030-87592-3_2
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Article ; Online: Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis.

Okar, Serhat Vahip / Dieckhaus, Henry / Beck, Erin S / Gaitán, María I / Norato, Gina / Pham, Dzung L / Absinta, Martina / Cortese, Irene Cm / Fletcher, Anita / Jacobson, Steven / Nair, Govind / Reich, Daniel S

Investigative radiology

2023 Volume 59, Issue 3, Page(s) 243–251

Abstract: Background: Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). ... ...

Abstract	Background: Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. Purpose: To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. Materials and methods: We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. Results: We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. Conclusions: Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.
MeSH term(s)	Humans ; Female ; Adult ; Middle Aged ; Multiple Sclerosis/pathology ; Magnetic Resonance Imaging ; Meninges/diagnostic imaging ; Meninges/pathology ; Inflammation/pathology
Language	English
Publishing date	2023-07-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	80345-5
ISSN	1536-0210 ; 0020-9996
ISSN (online)	1536-0210
ISSN	0020-9996
DOI	10.1097/RLI.0000000000001011
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