A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer’s disease

Background The three core pathologies of Alzheimer’s disease (AD) are amyloid pathology, tau pathology, and neurodegeneration. Biomarkers exist for each. Neurodegeneration is often detected by neuroimaging, and we hypothesized that a voxel-based deep learning approach using structural MRI might outperform other neuroimaging methods. Methods First, we implement an MRI-based deep learning model, trained with a data augmentation strategy, which classifies Alzheimer’s dementia and generates class activation maps. Next, we tested the model in prodromal AD and compared its performance to other biomarkers of amyloid pathology, tau pathology, and neuroimaging biomarkers of neurodegeneration. Results The model distinguished between controls and AD with high accuracy (AUROC = 0.973) with class activation maps that localized to the hippocampal formation. As hypothesized, the model also outperformed other neuroimaging biomarkers of neurodegeneration in prodromal AD (AUROC = 0.788) but also outperformed biomarkers of amyloid (CSF Aβ = 0.702) or tau pathology (CSF tau = 0.682), and the findings are interpreted in the context of AD’s known anatomical biology. Conclusions The advantages of using deep learning to extract biomarker information from conventional MRIs extend practically, potentially reducing patient burden, risk, and cost

Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community

Background: New-onset Alzheimer disease (AD) is often attributed to degenerative changes in the hippocampus. However, the contribution of regionally distributed small vessel cerebrovascular disease, visualized as white matter hyperintensities (WMHs) on magnetic resonance imaging, remains unclear. Objective: To determine whether regional WMHs and hippocampal volume predict incident AD in an epidemiological study. Design: A longitudinal community-based epidemiological study of older adults from northern Manhattan, New York. Setting: The Washington Heights/Inwood Columbia Aging Project. Participants: Between 2005 and 2007, 717 participants without dementia received magnetic resonance imaging scans. A mean (SD) of 40.28 (9.77) months later, 503 returned for follow-up clinical examination and 46 met criteria for incident dementia (45 with AD). Regional WMHs and relative hippocampal volumes were derived. Three Cox proportional hazards models were run to predict incident dementia, controlling for relevant variables. The first included all WMH measurements; the second included relative hippocampal volume; and the third combined the 2 measurements. Main Outcome: Measure Incident AD. Results: White matter hyperintensity volume in the parietal lobe predicted time to incident dementia (hazard ratio [HR] = 1.194; P = .03). Relative hippocampal volume did not predict incident dementia when considered alone (HR = 0.419; P = .77) or with the WMH measures included in the model (HR = 0.302; P = .70). Including hippocampal volume in the model did not notably alter the predictive utility of parietal lobe WMHs (HR = 1.197; P = .049). Conclusions: The findings highlight the regional specificity of the association of WMHs with AD. It is not clear whether parietal WMHs solely represent a marker for cerebrovascular burden or point to distinct injury compared with other regions. Future work should elucidate pathogenic mechanisms linking WMHs and AD pathology

Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia

CONTEXT White matter lesions (WML) increase the risk of dementia. The relevance of WML location is less clear. We sought to determine whether a particular WML profile, based on the density and location of lesions, could be associated with an increased risk of mild cognitive impairment (MCI) or dementia over the following 7 years. METHODS In 426 healthy subjects from a cohort of community-dwelling people aged 65 years and over (ESPRIT Project), standardized cognitive and neurological evaluations were repeated after 2, 4 and 7 years. Patterns of WML were computed with a supervised data mining approach (decision trees) using the regional WML volumes (frontal, parietal, temporal, and occipital regions) and the total WML volume estimated at baseline. Cox proportional hazard models were then constructed to study the association between WML patterns and risk of MCI/dementia. RESULTS Total WML volume and percentage of WML in the temporal region proved to be the best predictors of progression to MCI and dementia. Specifically, severe total WML load with a high proportion of lesions in the temporal region was significantly associated with the risk of developing MCI or dementia. CONCLUSIONS Above a certain threshold of damage, a pattern of WML clustering in the temporal region identifies individuals at increased risk of MCI or dementia. As this WML pattern is observed before the onset of clinical symptoms, it may facilitate the detection of patients at risk of MCI/dementia.The ESPRIT Project is financed by the regional government of Languedoc-Roussillon (http://www.laregion.fr), the Agence Nationale de la Recherche (ANR: http://www.agence-nationale-recherche.fr) and an unconditional grant from Novartis (http://www.novartis.fr). This study is also supported by France Alzheimer (http://www.francealzheimer.org/)

Systemic administration of IGF-I enhances healing in collagenous extracellular matrices: evaluation of loaded and unloaded ligaments

BACKGROUND: Insulin-like growth factor-I (IGF-I) plays a crucial role in wound healing and tissue repair. We tested the hypotheses that systemic administration of IGF-I, or growth hormone (GH), or both (GH+IGF-I) would improve healing in collagenous connective tissue, such as ligament. These hypotheses were examined in rats that were allowed unrestricted activity after injury and in animals that were subjected to hindlimb disuse. Male rats were assigned to three groups: ambulatory sham-control, ambulatory-healing, and hindlimb unloaded-healing. Ambulatory and hindlimb unloaded animals underwent surgical disruption of their knee medial collateral ligaments (MCLs), while sham surgeries were performed on control animals. Healing animals subcutaneously received systemic doses of either saline, GH, IGF-I, or GH+IGF-I. After 3 weeks, mechanical properties, cell and matrix morphology, and biochemical composition were examined in control and healing ligaments. RESULTS: Tissues from ambulatory animals receiving only saline had significantly greater strength than tissue from saline receiving hindlimb unloaded animals. Addition of IGF-I significantly improved maximum force and ultimate stress in tissues from both ambulatory and hindlimb unloaded animals with significant increases in matrix organization and type-I collagen expression. Addition of GH alone did not have a significant effect on either group, while addition of GH+IGF-I significantly improved force, stress, and modulus values in MCLs from hindlimb unloaded animals. Force, stress, and modulus values in tissues from hindlimb unloaded animals receiving IGF-I or GH+IGF-I exceeded (or were equivalent to) values in tissues from ambulatory animals receiving only saline with greatly improved structural organization and significantly increased type-I collagen expression. Furthermore, levels of IGF-receptor were significantly increased in tissues from hindlimb unloaded animals treated with IGF-I. CONCLUSION: These results support two of our hypotheses that systemic administration of IGF-I or GH+IGF-I improve healing in collagenous tissue. Systemic administration of IGF-I improves healing in collagenous extracellular matrices from loaded and unloaded tissues. Growth hormone alone did not result in any significant improvement contrary to our hypothesis, while GH + IGF-I produced remarkable improvement in hindlimb unloaded animals

Spatial Registration Evaluation of [18F]-MK6240 PET

Image registration is an important preprocessing step in neuroimaging which allows for the matching of anatomical and functional information between modalities and subjects. This can be challenging if there are gross differences in image geometry or in signal intensity, such as in the case of some molecular PET radioligands, where control subjects display relative lack of signal relative to noise within intracranial regions, and may have off target binding that may be confused as other regions, and may vary depending on subject. The use of intermediary images or volumes have been shown to aide registration in such cases. To account for this phenomena within our own longitudinal aging cohort, we generated a population specific MRI and PET template from a broad distribution of 30 amyloid negative subjects. We then registered the PET image of each of these subjects, as well as a holdout set of thirty 'template-naive' subjects to their corresponding MRI images using the template image as an intermediate using three different sets of registration parameters and procedures. To evaluate the performance of both conventional registration and our method, we compared these to the registration of the attenuation CT (acquired at time of PET acquisition) to MRI as the reference. We then used our template to directly derive SUVR values without the use of MRI. We found that conventional registration was comparable to an existing CT based standard, and there was no significant difference in errors collectively amongst all methods tested. In addition, there were no significant differences between existing and MR-less tau PET quantification methods. We conclude that a template-based method is a feasible alternative to, or salvage for, direct registration and MR-less quantification; and, may be preferred in cases where there is doubt about the similarity between two image modalities

Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study

It is not clear whether high mammographic density (MD) is equally associated with all subtypes of breast cancer (BC). We investigated the association between MD and subsequent BC, considering invasiveness, means of detection, pathologic subtype, and the time elapsed since mammographic exploration and BC diagnosis. METHODS: BC cases occurring in the population of women who attended screening from 1997 through 2004 in Navarre, a Spanish region with a fully consolidated screening program, were identified via record linkage with the Navarre Cancer Registry (n = 1,172). Information was extracted from the records of their first attendance at screening in that period. For each case, we randomly selected four controls, matched by screening round, year of birth, and place of residence. Cases were classified according to invasiveness (ductal carcinoma in situ (DCIS) versus invasive tumors), pathologic subtype (considering hormonal receptors and HER2), and type of diagnosis (screen-detected versus interval cases). MD was evaluated by a single, experienced radiologist by using a semiquantitative scale. Data on BC risk factors were obtained by the screening program in the corresponding round. The association between MD and tumor subtype was assessed by using conditional logistic regression. RESULTS: MD was clearly associated with subsequent BC. The odds ratio (OR) for the highest MD category (MD >75%) compared with the reference category (MD <10%) was similar for DCIS (OR = 3.47; 95% CI = 1.46 to 8.27) and invasive tumors (OR = 2.95; 95% CI = 2.01 to 4.35). The excess risk was particularly high for interval cases (OR = 7.72; 95% CI = 4.02 to 14.81) in comparison with screened detected tumors (OR = 2.17; 95% CI = 1.40 to 3.36). Sensitivity analyses excluding interval cases diagnosed in the first year after MD assessment or immediately after an early recall to screening yielded similar results. No differences were seen regarding pathologic subtypes. The excess risk associated with MD persisted for at least 7 to 8 years after mammographic exploration. CONCLUSIONS: Our results confirm that MD is an important risk factor for all types of breast cancer. High breast density strongly increases the risk of developing an interval tumor, and this excess risk is not completely explained by a possible masking effect.This work was supported by research grants from Eli Lilly and Company (EV1 1082/08); and the Spanish Federation of Breast Cancer Patients (Federación Española de Cáncer de Mama) (FECMA 485 EPY 1170-10).S

Imaging breast cancer using hyperpolarized carbon-13 MRI.

Our purpose is to investigate the feasibility of imaging tumor metabolism in breast cancer patients using 13C magnetic resonance spectroscopic imaging (MRSI) of hyperpolarized 13C label exchange between injected [1-13C]pyruvate and the endogenous tumor lactate pool. Treatment-naïve breast cancer patients were recruited: four triple-negative grade 3 cancers; two invasive ductal carcinomas that were estrogen and progesterone receptor-positive (ER/PR+) and HER2/neu-negative (HER2-), one grade 2 and one grade 3; and one grade 2 ER/PR+ HER2- invasive lobular carcinoma (ILC). Dynamic 13C MRSI was performed following injection of hyperpolarized [1-13C]pyruvate. Expression of lactate dehydrogenase A (LDHA), which catalyzes 13C label exchange between pyruvate and lactate, hypoxia-inducible factor-1 (HIF1α), and the monocarboxylate transporters MCT1 and MCT4 were quantified using immunohistochemistry and RNA sequencing. We have demonstrated the feasibility and safety of hyperpolarized 13C MRI in early breast cancer. Both intertumoral and intratumoral heterogeneity of the hyperpolarized pyruvate and lactate signals were observed. The lactate-to-pyruvate signal ratio (LAC/PYR) ranged from 0.021 to 0.473 across the tumor subtypes (mean ± SD: 0.145 ± 0.164), and a lactate signal was observed in all of the grade 3 tumors. The LAC/PYR was significantly correlated with tumor volume (R = 0.903, P = 0.005) and MCT 1 (R = 0.85, P = 0.032) and HIF1α expression (R = 0.83, P = 0.043). Imaging of hyperpolarized [1-13C]pyruvate metabolism in breast cancer is feasible and demonstrated significant intertumoral and intratumoral metabolic heterogeneity, where lactate labeling correlated with MCT1 expression and hypoxia

White Matter Hyperintensity Burden on Magnetic Resonance Imaging in Essential Tremor

Background: Whereas structural abnormalities in the cerebellum have been associated with essential tremor (ET), the contribution of vascular disease via white matter hyperintensities (WMHs) and strokes has not been examined. In this study, we explored these potential associations and hypothesized that ET would be associated with greater overall WMH volume, greater cerebellar WMH volume and greater infarct presence.Methods: In a cross-sectional magnetic resonance imaging (MRI) study of 540 community-dwelling elderly persons in northern Manhattan, New York, brain measures of total WMH volume and regional WMH volume were derived from T2-weighted FLAIR-weighted MR images. Presence of cerebral infarcts on MRI was determined as well.Results: Total WMH volume was greater among 33 ET cases than 507 controls in both univariate (OR=1.41, p=0.038) and fully adjusted analyses (OR=1.44, p=0.03). Cerebellar WMH volume was associated with marginally increased odds of ET in a univariate model (OR=1.52, p=0.11) and significantly increased odds in a fully adjusted multivariate model (OR=1.74, p=0.049). Temporal lobe WMH volume was associated with significantly increased odds of ET in both univariate (OR=3.36, p&lt;0.001) and fully adjusted models (OR=3.73, p&lt;0.001). Large strokes were significantly more common in cases than controls in unadjusted analyses (OR=3.04, p=0.02) and marginally in adjusted analyses (OR=2.56 - 2.57, p=0.045 - 0.056). The distribution of strokes did not differ by diagnosis.Discussion: MRI data in this study indicated that ET was associated with greater total WMH volume, greater cerebellar WMH volume and possibly more strokes. Cerebrovascular disease could play a role in the development of ET