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    Complete Evaluation of Dementia: PET and MRI Correlation and Diagnosis for the Neuroradiologist
    (American Society of Neuroradiology, 2021) Oldan, J. D.; Jewells, V. L.; Pieper, B.; Wong, T. Z.; Radiology and Imaging Sciences, School of Medicine
    This article will familiarize neuroradiologists with the pathophysiology, clinical findings, and standard MR imaging and PET imaging features of multiple forms of dementia as well as new emerging techniques. Cases were compiled from multiple institutions with the goal of improved diagnostic accuracy and improved patient care as well as information about biomarkers on the horizon. Dementia topics addressed include the following: Alzheimer disease, frontotemporal dementia, cerebral amyloid angiopathy, Lewy body dementia, Parkinson disease and Parkinson disease variants, amyotrophic lateral sclerosis, multisystem atrophy, Huntington disease vascular dementia, and Creutzfeldt-Jakob disease.
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    Associations of circulating saturated long-chain fatty acids with risk of mild cognitive impairment and Alzheimer’s disease in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort
    (Elsevier, 2023) Fan, Lei; Borenstein, Amy R.; Wang, Sophia; Nho, Kwangsik; Zhu, Xiangzhu; Wen, Wanqing; Huang, Xiang; Mortimer, James A.; Shrubsole, Martha J.; Dai, Qi; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Background: No study has examined the associations between peripheral saturated long-chain fatty acids (LCFAs) and conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). This study aimed to examine whether circulating saturated LCFAs are associated with both risks of incident MCI from cognitively normal (CN) participants and incident AD progressed from MCI in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Methods: We conducted analysis of data from older adults aged 55-90 years who were recruited at 63 sites across the USA and Canada. We examined associations between circulating saturated LCFAs (i.e., C14:0, C16:0, C18:0, C20:0) and risk for incident MCI in CN participants, and incident AD progressed from MCI. Findings: 829 participants who were enrolled in ADNI-1 had data on plasma saturated LCFAs, of which 618 AD-free participants were included in our analysis (226 with normal cognition and 392 with MCI; 60.2% were men). Cox proportional-hazards models were used to account for time-to-event/censor with a 48-month follow-up period for the primary analysis. Other than C20:0, saturated LCFAs were associated with an increased risk for AD among participants with MCI at baseline (Hazard ratios (HRs) = 1.3 to 2.2, P = 0.0005 to 0.003 in fully-adjusted models). No association of C20:0 with risk of AD among participants with MCI was observed. No associations were observed between saturated LCFAs and risk for MCI among participants with normal cognition. Interpretation: Saturated LCFAs are associated with increased risk of progressing from MCI to AD. This finding holds the potential to facilitate precision prevention of AD among patients with MCI.
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    Brain-wide genome-wide colocalization study for integrating genetics, transcriptomics and brain morphometry in Alzheimer’s disease
    (Elsevier, 2023) Bao, Jingxuan; Wen, Junhao; Wen, Zixuan; Yang, Shu; Cui, Yuhan; Yang, Zhijian; Erus, Guray; Saykin, Andrew J.; Long, Qi; Davatzikos, Christos; Shen, Li; Radiology and Imaging Sciences, School of Medicine
    Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases. However, the AD mechanism has not yet been fully elucidated to date, hindering the development of effective therapies. In our work, we perform a brain imaging genomics study to link genetics, single-cell gene expression data, tissue-specific gene expression data, brain imaging-derived volumetric endophenotypes, and disease diagnosis to discover potential underlying neurobiological pathways for AD. To do so, we perform brain-wide genome-wide colocalization analyses to integrate multidimensional imaging genomic biobank data. Specifically, we use (1) the individual-level imputed genotyping data and magnetic resonance imaging (MRI) data from the UK Biobank, (2) the summary statistics of the genome-wide association study (GWAS) from multiple European ancestry cohorts, and (3) the tissue-specific cis-expression quantitative trait loci (cis-eQTL) summary statistics from the GTEx project. We apply a Bayes factor colocalization framework and mediation analysis to these multi-modal imaging genomic data. As a result, we derive the brain regional level GWAS summary statistics for 145 brain regions with 482,831 single nucleotide polymorphisms (SNPs) followed by posthoc functional annotations. Our analysis yields the discovery of a potential AD causal pathway from a systems biology perspective: the SNP chr10:124165615:G>A (rs6585827) mutation upregulates the expression of BTBD16 gene in oligodendrocytes, a specialized glial cells, in the brain cortex, leading to a reduced risk of volumetric loss in the entorhinal cortex, resulting in the protective effect on AD. We substantiate our findings with multiple evidence from existing imaging, genetic and genomic studies in AD literature. Our study connects genetics, molecular and cellular signatures, regional brain morphologic endophenotypes, and AD diagnosis, providing new insights into the mechanistic understanding of the disease. Our findings can provide valuable guidance for subsequent therapeutic target identification and drug discovery in AD.
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    Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data
    (Elsevier, 2023) Jo, Taeho; Kim, Junpyo; Bice, Paula; Huynh, Kevin; Wang, Tingting; Arnold, Matthias; Meikle, Peter J.; Giles, Corey; Kaddurah-Daouk, Rima; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Metabolomics Consortium (ADMC); Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Background: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics. Methods: The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification. Findings: The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6). Interpretation: Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation.
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    Anti-Amyloid Therapy, AD, and ARIA: Untangling the Role of CAA
    (MDPI, 2023-10-27) Sin, Mo-Kyung; Zamrini, Edward; Ahmed, Ali; Nho, Kwangsik; Hajjar, Ihab; Radiology and Imaging Sciences, School of Medicine
    Anti-amyloid therapies (AATs), such as anti-amyloid monoclonal antibodies, are emerging treatments for people with early Alzheimer’s disease (AD). AATs target amyloid β plaques in the brain. Amyloid-related imaging abnormalities (ARIA), abnormal signals seen on magnetic resonance imaging (MRI) of the brain in patients with AD, may occur spontaneously but occur more frequently as side effects of AATs. Cerebral amyloid angiopathy (CAA) is a major risk factor for ARIA. Amyloid β plays a key role in the pathogenesis of AD and of CAA. Amyloid β accumulation in the brain parenchyma as plaques is a pathological hallmark of AD, whereas amyloid β accumulation in cerebral vessels leads to CAA. A better understanding of the pathophysiology of ARIA is necessary for early detection of those at highest risk. This could lead to improved risk stratification and the ultimate reduction of symptomatic ARIA. Histopathological confirmation of CAA by brain biopsy or autopsy is the gold standard but is not clinically feasible. MRI is an available in vivo tool for detecting CAA. Cerebrospinal fluid amyloid β level testing and amyloid PET imaging are available but do not offer specificity for CAA vs amyloid plaques in AD. Thus, developing and testing biomarkers as reliable and sensitive screening tools for the presence and severity of CAA is a priority to minimize ARIA complications.
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    Effects of acute alcohol exposure and chronic alcohol use on neurite orientation dispersion and density imaging (NODDI) parameters
    (Springer, 2023) Yoder, Karmen K.; Chumin, Evgeny J.; Mustafi, Sourajit M.; Kolleck, Kelly A.; Halcomb, Meredith E.; Hile, Karen L.; Plawecki, Martin H.; O’Connor, Sean J.; Dzemidzic, Mario; Wu, Yu‑Chien; Radiology and Imaging Sciences, School of Medicine
    Rationale: Little is known about how acute and chronic alcohol exposure may alter the in vivo membrane properties of neurons. Objectives: We employed neurite orientation dispersion and density imaging (NODDI) to examine acute and chronic effects of alcohol exposure on neurite density. Methods: Twenty-one healthy social drinkers (CON) and thirteen nontreatment-seeking individuals with alcohol use disorder (AUD) underwent a baseline multi-shell diffusion magnetic resonance imaging (dMRI) scan. A subset (10 CON, 5 AUD) received dMRI during intravenous infusions of saline and alcohol during dMRI. NODDI parametric images included orientation dispersion (OD), isotropic volume fraction (ISOVF), and corrected intracellular volume fraction (cICVF). Diffusion tensor imaging metrics of fractional anisotropy and mean, axial, and radial diffusivity (FA, MD, AD, RD) were also computed. Average parameter values were extracted from white matter (WM) tracts defined by the Johns Hopkins University atlas. Results: There were group differences in FA, RD, MD, OD, and cICVF, primarily in the corpus callosum. Both saline and alcohol had effects on AD and cICVF in WM tracts proximal to the striatum, cingulate, and thalamus. This is the first work to indicate that acute fluid infusions may alter WM properties, which are conventionally believed to be insensitive to acute pharmacological challenges. It also suggests that the NODDI approach may be sensitive to transient changes in WM. The next steps should include determining if the effect on neurite density differs with solute or osmolality, or both, and translational studies to assess how alcohol and osmolality affect the efficiency of neurotransmission.
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    American Society of Emergency Radiology Multicenter Blunt Splenic Trauma Study: CT and Clinical Findings
    (Radiological Society of North America, 2021) Lee, James T.; Slade, Emily; Uyeda, Jennifer; Steenburg, Scott D.; Chong, Suzanne T.; Tsai, Richard; Raptis, Demetrios; Linnau, Ken F.; Chinapuvvula, Naga R.; Dattwyler, Matthew P.; Dugan, Adam; Baghdanian, Arthur; Flink, Carl; Baghdanian, Armonde; LeBedis, Christina A.; Radiology and Imaging Sciences, School of Medicine
    Background: Treatment of blunt splenic trauma (BST) continues to evolve with improved imaging for detection of splenic vascular injuries. Purpose: To report on treatments for BST from 11 trauma centers, the frequency and clinical impact of splenic vascular injuries, and factors influencing treatment. Materials and Methods: Patients were retrospectively identified as having BST between January 2011 and December 2018, and clinical, imaging, and outcome data were recorded. Patient data were summarized descriptively, both overall and stratified by initial treatment received (nonoperative management [NOM], angiography, or surgery). Regression analyses were used to examine the primary outcomes of interest, which were initial treatment received and length of stay (LOS). Results: This study evaluated 1373 patients (mean age, 42 years ± 18; 845 men). Initial treatments included NOM in 849 patients, interventional radiology (IR) in 240 patients, and surgery in 284 patients. Rates from CT reporting were 22% (304 of 1373) for active splenic hemorrhage (ASH) and 20% (276 of 1373) for contained vascular injury (CVI). IR management of high-grade injuries increased 15.6%, from 28.6% (eight of 28) to 44.2% (57 of 129) (2011–2012 vs 2017–2018). Patients who were treated invasively had a higher injury severity score (odds ratio [OR], 1.04; 95% CI: 1.02, 1.05; P < .001), lower temperature (OR, 0.97; 95% CI: 0.97, 1.00; P = .03), and a lower hematocrit (OR, 0.96; 95% CI: 0.93, 0.99; P = .003) and were more likely to show ASH (OR, 8.05; 95% CI: 5.35, 12.26; P < .001) or CVI (OR, 2.70; 95% CI: 1.64, 4.44; P < .001) on CT images, have spleen-only injures (OR, 2.35; 95% CI: 1.45, 3.8; P < .001), and have been administered blood product for fewer than 24 hours (OR, 2.35; 95% CI: 1.58, 3.51; P < .001) compared with those chosen for NOM, after adjusting for key demographic and clinical variables. After adjustment, factors associated with a shorter LOS were female sex (OR, 0.84; 95% CI: 0.73, 0.96; P = .009), spleen-only injury (OR, 0.72; 95% CI: 0.6, 0.86; P < .001), higher admission hematocrit (OR, 0.98; 95% CI: 0.6, 0.86; P < .001), and presence of ASH at CT (OR, 0.74; 95% CI: 0.62, 0.88; P < .001). Conclusion: Contained vascular injury and active splenic hemorrhage (ASH) were frequently reported, and rates of interventional radiologic management increased during the study period. ASH was associated with a shorter length of stay, and patients with ASH had eight times the odds of undergoing invasive treatment compared with undergoing nonoperative management.
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    Effects of home-based leg heat therapy on walking performance in patients with symptomatic peripheral artery disease: a pilot randomized trial
    (American Physiological Society, 2022) Monroe, Jacob C.; Pae, Byung Joon; Kargl, Christopher; Gavin, Timothy P.; Parker, Jason; Perkins, Susan M.; Han, Yan; Klein, Janet; Motaganahalli, Raghu L.; Roseguini, Bruno T.; Radiology and Imaging Sciences, School of Medicine
    Few noninvasive therapies currently exist to improve functional capacity in people with lower extremity peripheral artery disease (PAD). The goal of the present study was to test the hypothesis that unsupervised, home-based leg heat therapy (HT) using water-circulating trousers perfused with warm water would improve walking performance in patients with PAD. Patients with symptomatic PAD were randomized into either leg HT (n = 18) or a sham treatment (n = 16). Patients were provided with water-circulating trousers and a portable pump and were asked to apply the therapy daily (7 days/wk, 90 min/session) for 8 wk. The primary study outcome was the change from baseline in 6-min walk distance at 8-wk follow-up. Secondary outcomes included the claudication onset-time, peak walking time, peak pulmonary oxygen consumption and peak blood pressure during a graded treadmill test, resting blood pressure, the ankle-brachial index, postocclusive reactive hyperemia in the calf, cutaneous microvascular reactivity, and perceived quality of life. Of the 34 participants randomized, 29 completed the 8-wk follow-up. The change in 6-min walk distance at the 8-wk follow-up was significantly higher (P = 0.029) in the group exposed to HT than in the sham-treated group (Sham: median: -0.9; 25%, 75% percentiles: -5.8, 14.3; HT: median: 21.3; 25%, 75% percentiles: 10.1, 42.4, P = 0.029). There were no significant differences in secondary outcomes between the HT and sham group at 8-wk follow-up. The results of this pilot study indicate that unsupervised, home-based leg HT is safe, well-tolerated, and elicits a clinically meaningful improvement in walking tolerance in patients with symptomatic PAD. NEW & NOTEWORTHY: This is the first sham-controlled trial to examine the effects of home-based leg heat therapy (HT) on walking performance in patients with peripheral artery disease (PAD). We demonstrate that unsupervised HT using water-circulating trousers is safe, well-tolerated, and elicits meaningful changes in walking ability in patients with symptomatic PAD. This home-based treatment option is practical, painless, and may be a feasible adjunctive therapy to counteract the decline in lower extremity physical function in patients with PAD.
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    PET imaging with [68Ga]-labeled TGFβ-targeting peptide in a mouse PANC-1 tumor model
    (Frontiers Media, 2023-09-15) Li, Yong; Zhao, Hong; Hu, Shan; Zhang, Xichen; Chen, Haojian; Zheng, Qihuang; Radiology and Imaging Sciences, School of Medicine
    Purpose: Transforming growth factor β (TGFβ) is upregulated in many types of tumors and plays important roles in tumor microenvironment construction, immune escape, invasion, and metastasis. The therapeutic effect of antibodies and nuclide-conjugated drugs targeting TGFβ has not been ideal. Targeting TGFβ with small-molecule or peptide carriers labeled with diagnostic/therapeutic nuclides is a new development direction. This study aimed to explore and confirm the imaging diagnostic efficiency of TGFβ-targeting peptide P144 coupled with [68Ga] in a PANC-1 tumor model. Procedures: TGFβ-targeting inhibitory peptide P144 with stable activity was prepared through peptide synthesis and screening, and P144 was coupled with biological chelator DOTA and labeled with radionuclide [68Ga] to achieve a stable TGFβ-targeting tracer [68Ga]Ga-P144. This tracer was first used for positron emission tomography (PET) molecular imaging study of pancreatic cancer in a mouse PANC-1 tumor model. Results: [68Ga]Ga-P144 had a high targeted uptake and relatively long uptake retention time in tumors and lower uptakes in non-target organs and backgrounds. Target pre-blocking experiment with the cold drug P144-DOTA demonstrated that the radioactive uptake with [68Ga]Ga-P144 PET in vivo, especially in tumor tissue, had a high TGFβ-targeting specificity. [68Ga]Ga-P144 PET had ideal imaging efficiency in PANC-1 tumor-bearing mice, with high specificity in vivo and good tumor-targeting effect. Conclusion: [68Ga]Ga-P144 has relatively high specificity and tumor-targeted uptake and may be developed as a promising diagnostic tool for TGFβ-positive malignancies.
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    MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study
    (Oxford University Press, 2021-03-05) Tam, Lydia T.; Yeom, Kristen W.; Wright, Jason N.; Jaju, Alok; Radmanesh, Alireza; Han, Michelle; Toescu, Sebastian; Maleki, Maryam; Chen, Eric; Campion, Andrew; Lai, Hollie A.; Eghbal, Azam A.; Oztekin, Ozgur; Mankad, Kshitij; Hargrave, Darren; Jacques, Thomas S.; Goetti, Robert; Lober, Robert M.; Cheshier, Samuel H.; Napel, Sandy; Said, Mourad; Aquilina, Kristian; Ho, Chang Y.; Monje, Michelle; Vitanza, Nicholas A.; Mattonen, Sarah A.; Radiology and Imaging Sciences, School of Medicine
    Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance.