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Atypical sensory processing is common in autism, but how neural coding is disrupted in sensory cortex is unclear. We evaluate whisker touch coding in L2/3 of somatosensory cortex (S1) in Cntnap2-/- mice, which have reduced inhibition. This classically predicts excess pyramidal cell spiking, but this remains controversial, and other deficits may dominate. We find that c-fos expression is elevated in S1 of Cntnap2-/- mice under spontaneous activity conditions but is comparable to that of control mice after whisker stimulation, suggesting normal sensory-evoked spike rates. GCaMP8m imaging from L2/3 pyramidal cells shows no excess whisker responsiveness, but it does show multiple signs of degraded somatotopic coding. This includes broadened whisker-tuning curves, a blurred whisker map, and blunted whisker point representations. These disruptions are greater in noisy than in sparse sensory conditions. Tuning instability across days is also substantially elevated in Cntnap2-/-. Thus, Cntnap2-/- mice show no excess sensory-evoked activity, but a degraded and unstable tactile code in S1.

This manuscript quantitatively investigates remodeling dynamics of the cortical microvascular network (thousands of connected capillaries) following photothrombotic ischemia (cubic millimeter volume, imaged weekly) using a novel in vivo two-photon angiography and high throughput vascular vectorization method. The results suggest distinct temporal patterns of cerebrovascular plasticity, with acute remodeling peaking at one week post-stroke. The network architecture then gradually stabilizes, returning to a new steady state after four weeks. These findings align with previous literature on neuronal plasticity, highlighting the correlation between neuronal and neurovascular remodeling. Quantitative analysis of neurovascular networks using length- and strand-based statistical measures reveals intricate changes in network anatomy and topology. The distance and strand-length statistics show significant alterations, with a peak of plasticity observed at one week post-stroke, followed by a gradual return to baseline. The orientation statistic plasticity peaks at two weeks, gradually approaching the (conserved across subjects) stroke signature. The underlying mechanism of the vascular response (angiogenesis vs. tissue deformation), however, is yet unexplored. Overall, the combination of chronic two-photon angiography, vascular vectorization, reconstruction/visualization, and statistical analysis enables both qualitative and quantitative assessments of neurovascular remodeling dynamics, demonstrating a method for investigating cortical microvascular network disorders and the therapeutic modes of action thereof. [ABSTRACT FROM AUTHOR]

Abstract Early breach of the blood–brain barrier (BBB) and consequently extravasation of blood-borne substances into the brain parenchyma is a common hallmark of ischemic stroke. Although BBB breakdown is associated with an increased risk of cerebral hemorrhage and poor clinical prognosis, the cause and mechanism of this process are largely unknown. The aim of this study was to establish an imaging and analysis protocol which enables investigation of the dynamics of BBB breach in relation to hemodynamic properties along the arteriovenous axis. Using longitudinal intravital two-photon imaging following photothrombotic induction of ischemic stroke through a cranial window, we were able to study the response of the cerebral vasculature to ischemia, from the early critical hours to the days/weeks after the infarct. We demonstrate that disruption of the BBB and hemodynamic parameters, including perturbed blood flow, can be studied at single-vessel resolution in the three-dimensional space as early as 30 min after vessel occlusion. Further, we show that this protocol permits longitudinal studies on the response of individual blood vessels to ischemia over time, thus enabling detection of (maladaptive) vascular remodeling such as intussusception, angiogenic sprouting and entanglement of vessel networks. Taken together, this in vivo two-photon imaging and analysis protocol will be useful in future studies investigating the molecular and cellular mechanisms, and the spatial contribution, of BBB breach to disease progression which might ultimately aid the development of new and more precise treatment strategies for ischemic stroke.

Early breach of the blood–brain barrier (BBB) and consequently extravasation of blood-borne substances into the brain parenchyma is a common hallmark of ischemic stroke. Although BBB breakdown is associated with an increased risk of cerebral hemorrhage and poor clinical prognosis, the cause and mechanism of this process are largely unknown. The aim of this study was to establish an imaging and analysis protocol which enables investigation of the dynamics of BBB breach in relation to hemodynamic properties along the arteriovenous axis. Using longitudinal intravital two-photon imaging following photothrombotic induction of ischemic stroke through a cranial window, we were able to study the response of the cerebral vasculature to ischemia, from the early critical hours to the days/weeks after the infarct. We demonstrate that disruption of the BBB and hemodynamic parameters, including perturbed blood flow, can be studied at single-vessel resolution in the three-dimensional space as early as 30 min after vessel occlusion. Further, we show that this protocol permits longitudinal studies on the response of individual blood vessels to ischemia over time, thus enabling detection of (maladaptive) vascular remodeling such as intussusception, angiogenic sprouting and entanglement of vessel networks. Taken together, this in vivo two-photon imaging and analysis protocol will be useful in future studies investigating the molecular and cellular mechanisms, and the spatial contribution, of BBB breach to disease progression which might ultimately aid the development of new and more precise treatment strategies for ischemic stroke. [ABSTRACT FROM AUTHOR]

Drug-induced interstitial lung disease (ILD) is crucial to detect early to achieve the best treatment outcome. Optimally, non-invasive imaging biomarkers can be used for early detection of disease progression and treatment follow-up. Therefore, reliable in vivo models are warranted in new imaging biomarker development to accelerate better-targeted treatment options. Single-dose bleomycin models have, for a long time, served as a reference model in fibrosis and lung injury research. Here, we aimed to use a clinically more relevant animal model by systemic exposure to bleomycin and assessing disease progression over time by combined magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging.MethodsC57BL/6 mice received bleomycin (i.p. 35iU/kg) or saline as control twice per week for 4 weeks. Mice were monitored until 2 weeks after cessation of bleomycin administration (w4 + 1 and w4 + 2), referred to as the resting period. MRI scans were performed in weeks 3 and 4 and during the resting weeks. [18F]FDG-PET was performed at the last week of dosing (w4) and 2 weeks after the last dosing (w4 + 2). Lung tissue sections were stained with Masson’s trichrome and evaluated by modified Ashcroft scoring. Lung volume and lesion volumes were assessed using MRI, as well as 3D mapping of the central airways.Results and discussionBleomycin-challenged mice showed increased lung weights (p

Complex distortions on calcium imaging often impair image registration accuracy. Here, we developed a registration algorithm, PatchWarp, to robustly correct slow image distortion for calcium imaging data. PatchWarp is a two-step algorithm with rigid and non-rigid image registrations. To correct non-uniform image distortions, it splits the imaging field and estimates the best affine transformation matrix for each of the subfields. The distortion-corrected subfields are stitched together like a patchwork to reconstruct the distortion-corrected imaging field. We show that PatchWarp robustly corrects image distortions of calcium imaging data collected from various cortical areas through glass window or gradient-index (GRIN) lens with a higher accuracy than existing non-rigid algorithms. Furthermore, it provides a fully automated method of registering images from different imaging sessions for longitudinal neural activity analyses. PatchWarp improves the quality of neural activity analyses and is useful as a general approach to correct image distortions in a wide range of disciplines.

Purpose: Studying placental development informs when development is abnormal. Most placental MRI studies are cross‐sectional and do not study the extent of individual variability throughout pregnancy. We aimed to explore how diffusion MRI measures of placental function and microstructure vary in individual healthy pregnancies throughout gestation. Methods: Seventy‐nine pregnant, low‐risk participants (17 scanned twice and 62 scanned once) were included. T2‐weighted anatomical imaging and a combined multi‐echo spin‐echo diffusion‐weighted sequence were acquired at 3 T. Combined diffusion–relaxometry models were performed using both a T2*$$ {\mathrm{T}}_2^{\ast } $$‐ADC and a bicompartmental T2*$$ {\mathrm{T}}_2^{\ast } $$‐intravoxel‐incoherent‐motion (T2*IVIM$$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$) model fit. Results: There was a significant decline in placental T2*$$ {\mathrm{T}}_2^{\ast } $$ and ADC (both P < 0.01) over gestation. These declines are consistent in individuals for T2*$$ {\mathrm{T}}_2^{\ast } $$ (covariance = −0.47), but not ADC (covariance = −1.04). The T2*IVIM$$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model identified a consistent decline in individuals over gestation in T2*$$ {\mathrm{T}}_2^{\ast } $$ from both the perfusing and diffusing placental compartments, but not in ADC values from either. The placental perfusing compartment fraction increased over gestation (P = 0.0017), but this increase was not consistent in individuals (covariance = 2.57). Conclusion: Whole placental T2*$$ {\mathrm{T}}_2^{\ast } $$ and ADC values decrease over gestation, although only T2*$$ {\mathrm{T}}_2^{\ast } $$ values showed consistent trends within subjects. There was minimal individual variation in rates of change of T2*$$ {\mathrm{T}}_2^{\ast } $$ values from perfusing and diffusing placental compartments, whereas trends in ADC values from these compartments were less consistent. These findings probably relate to the increased complexity of the bicompartmental T2*IVIM$$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model, and differences in how different placental regions evolve at a microstructural level. These placental MRI metrics from low‐risk pregnancies provide a useful benchmark for clinical cohorts. [ABSTRACT FROM AUTHOR]

Understanding metabolic heterogeneity is critical for optimizing microbial production of valuable chemicals, but requires tools that can quantify metabolites at the single‐cell level over time. Here, longitudinal hyperspectral stimulated Raman scattering (SRS) chemical imaging is developed to directly visualize free fatty acids in engineered Escherichia coli over many cell cycles. Compositional analysis is also developed to estimate the chain length and unsaturation of the fatty acids in living cells. This method reveals substantial heterogeneity in fatty acid production among and within colonies that emerges over the course of many generations. Interestingly, the strains display distinct types of production heterogeneity in an enzyme‐dependent manner. By pairing time‐lapse and SRS imaging, the relationship between growth and production at the single‐cell level are examined. The results demonstrate that cell‐to‐cell production heterogeneity is pervasive and provides a means to link single‐cell and population‐level production. [ABSTRACT FROM AUTHOR]

Longitudinal neuroimaging studies are becoming increasingly prevalent, where brain images are collected on multiple subjects at multiple time points. Analyses of such data are scientifically important, but also challenging. Brain images are in the form of multidimensional arrays, or tensors, which are characterized by both ultrahigh dimensionality and a complex structure. Longitudinally repeated images and induced temporal correlations add a further layer of complexity. Despite some recent efforts, there exist very few solutions for longitudinal imaging analyses. In response to the increasing need to analyze longitudinal imaging data, we propose several tensor generalized estimating equations (GEEs). The proposed GEE approach accounts for intra-subject correlation, and an imposed low-rank structure on the coefficient tensor effectively reduces the dimensionality. We also propose a scalable estimation algorithm, establish the asymptotic properties of the solution to the tensor GEEs, and investigate sparsity regularization for the purpose of region selection. We demonstrate the proposed method using simulations and by analyzing a real data set from the Alzheimer's Disease Neuroimaging Initiative.

Preterm birth results in premature exposure of the brain to the extrauterine environment during a critical period of neurodevelopment. Consequently, infants born preterm are at a heightened risk of adverse behavioural outcomes in later life. We characterise longitudinal development of neonatal regional brain volume and functional connectivity in the first weeks following preterm birth, sociodemographic factors, and their respective relationships to psychomotor outcomes and psychopathology in toddlerhood. We study 121 infants born preterm who underwent magnetic resonance imaging shortly after birth, at term-equivalent age, or both. Longitudinal regional brain volume and functional connectivity were modelled as a function of psychopathology and psychomotor outcomes at 18 months. Better psychomotor functioning in toddlerhood was associated with greater relative right cerebellar volume and a more rapid decrease over time of sensorimotor degree centrality in the neonatal period. In contrast, increased 18-month psychopathology was associated with a more rapid decrease in relative regional subcortical volume. Furthermore, while socio-economic deprivation was related to both psychopathology and psychomotor outcomes, cognitively stimulating parenting predicted psychopathology only. Our study highlights the importance of longitudinal imaging to better predict toddler outcomes following preterm birth, as well as disparate environmental influences on separable facets of behavioural development in this population.

Simple Summary: Machine learning based radiomics models for prediction of loco-regional recurrence today mostly rely on features extracted from pre-treatment imaging data. In this work, we investigate the predictive ability of such models when imaging data obtained during the course of treatment are used. This is achieved by extracting features from pre-treatment CT and FDG-PET images as well as from images obtained two (only CT) and three weeks after start of radiochemotherapy. Models comprised of combined features from both modalities and multiple timepoints are evaluated. We confirm that predictive model performance is improved when features from in-treatment imaging are used, finding that CT-based features allow for more accurate risk prediction, while FDG-PET based models are able to stratify patients into low- and high-risk groups more reliably. Radiomics analysis provides a promising avenue towards the enabling of personalized radiotherapy. Most frequently, prognostic radiomics models are based on features extracted from medical images that are acquired before treatment. Here, we investigate whether combining data from multiple timepoints during treatment and from multiple imaging modalities can improve the predictive ability of radiomics models. We extracted radiomics features from computed tomography (CT) images acquired before treatment as well as two and three weeks after the start of radiochemotherapy for 55 patients with locally advanced head and neck squamous cell carcinoma (HNSCC). Additionally, we obtained features from FDG-PET images taken before treatment and three weeks after the start of therapy. Cox proportional hazards models were then built based on features of the different image modalities, treatment timepoints, and combinations thereof using two different feature selection methods in a five-fold cross-validation approach. Based on the cross-validation results, feature signatures were derived and their performance was independently validated. Discrimination regarding loco-regional control was assessed by the concordance index (C-index) and log-rank tests were performed to assess risk stratification. The best prognostic performance was obtained for timepoints during treatment for all modalities. Overall, CT was the best discriminating modality with an independent validation C-index of 0.78 for week two and weeks two and three combined. However, none of these models achieved statistically significant patient stratification. Models based on FDG-PET features from week three provided both satisfactory discrimination (C-index = 0.61 and 0.64) and statistically significant stratification ( p = 0.044 and p < 0.001 ), but produced highly imbalanced risk groups. After independent validation on larger datasets, the value of (multimodal) radiomics models combining several imaging timepoints should be prospectively assessed for personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Manganese‐enhanced magnetic resonance imaging (MEMRI) holds exceptional promise for preclinical studies of brain‐wide physiology in awake‐behaving animals. The objectives of this review are to update the current information regarding MEMRI and to inform new investigators as to its potential. Mn(II) is a powerful contrast agent for two main reasons: (1) high signal intensity at low doses; and (2) biological interactions, such as projection tracing and neural activity mapping via entry into electrically active neurons in the living brain. High‐spin Mn(II) reduces the relaxation time of water protons: at Mn(II) concentrations typically encountered in MEMRI, robust hyperintensity is obtained without adverse effects. By selectively entering neurons through voltage‐gated calcium channels, Mn(II) highlights active neurons. Safe doses may be repeated over weeks to allow for longitudinal imaging of brain‐wide dynamics in the same individual across time. When delivered by stereotactic intracerebral injection, Mn(II) enters active neurons at the injection site and then travels inside axons for long distances, tracing neuronal projection anatomy. Rates of axonal transport within the brain were measured for the first time in "time‐lapse" MEMRI. When delivered systemically, Mn(II) enters active neurons throughout the brain via voltage‐sensitive calcium channels and clears slowly. Thus behavior can be monitored during Mn(II) uptake and hyperintense signals due to Mn(II) uptake captured retrospectively, allowing pairing of behavior with neural activity maps for the first time. Here we review critical information gained from MEMRI projection mapping about human neuropsychological disorders. We then discuss results from neural activity mapping from systemic Mn(II) imaged longitudinally that have illuminated development of the tonotopic map in the inferior colliculus as well as brain‐wide responses to acute threat and how it evolves over time. MEMRI posed specific challenges for image data analysis that have recently been transcended. We predict a bright future for longitudinal MEMRI in pursuit of solutions to the brain‐behavior mystery. [ABSTRACT FROM AUTHOR]

Skull bone development is a dynamic and well‐coordinated process playing a key role in maturation and maintenance of the bone marrow (BM), fracture healing, and progression of diseases such as osteoarthritis or osteoporosis. At present, dynamic transformation of the growing bone (osteogenesis) as well as its vascularization (angiogenesis) remain largely unexplored due to the lack of suitable in vivo imaging techniques capable of noninvasive visualization of the whole developing calvaria at capillary‐level resolution. We present a longitudinal study on skull bone development using ultrasound‐aided large‐scale optoacoustic microscopy (U‐LSOM). Skull bone morphogenesis and microvascular growth patterns were monitored in three common mouse strains (C57BL/6J, CD‐1, and Athymic Nude‐Foxn1nu) at the whole‐calvaria scale over a 3‐month period. Strain‐specific differences in skull development were revealed by quantitative analysis of bone and vessel parameters, indicating the coupling between angiogenesis and osteogenesis during skull bone growth in a minimally invasive and label‐free manner. The method further enabled identifying BM‐specific sinusoidal vessels, and superficial skull vessels penetrating into BM compartments. Our approach furnishes a new high‐throughput longitudinal in vivo imaging platform to study morphological and vascular skull alterations in health and disease, shedding light on the critical links between blood vessel formation, skull growth, and regeneration. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR). [ABSTRACT FROM AUTHOR]

Alterations in white matter (WM) development are associated with many neuropsychiatric and neurodevelopmental disorders. Most MRI studies examining WM development employ diffusion tensor imaging (DTI), which relies on estimating diffusion patterns of water molecules as a reflection of WM microstructure. Quantitative relaxometry, an alternative method for characterizing WM microstructural changes, is based on molecular interactions associated with the magnetic relaxation of protons. In a longitudinal study of 34 infant non-human primates (NHP) (Macaca mulatta) across the first year of life, we implement a novel, high-resolution, T1-weighted MPnRAGE sequence to examine WM trajectories of the longitudinal relaxation rate (qR1) in relation to DTI metrics and gestational age at scan. To the best of our knowledge, this is the first study to assess developmental WM trajectories in NHPs using quantitative relaxometry and the first to directly compare DTI and relaxometry metrics during infancy. We demonstrate that qR1 exhibits robust logarithmic growth, unfolding in a posterior-anterior and medial-lateral fashion, similar to DTI metrics. On a within-subject level, DTI metrics and qR1 are highly correlated, but are largely unrelated on a between-subject level. Unlike DTI metrics, gestational age at birth (time in utero) is a strong predictor of early postnatal qR1 levels. Whereas individual differences in DTI metrics are maintained across the first year of life, this is not the case for qR1. These results point to the similarities and differences in using quantitative relaxometry and DTI in developmental studies, providing a basis for future studies to characterize the unique processes that these measures reflect at the cellular and molecular level.

Background: To address the need for more objective and quantitative measures of tendon healing in research studies, we intend to use computed tomography (CT) with implanted radiopaque markers on the repaired tendon to measure tendon retraction following rotator cuff repair. In our small prior study, retraction at 1-year follow-up averaged 16.1± 5.3 mm and exceeded 10.0 mm in 12 of 13 patients, and thus tendon retraction appears to be a common clinical phenomenon. This study's objectives were to assess, using 5 longitudinal CT scans obtained over 1 year following rotator cuff repair, the variability in glenohumeral positioning because of pragmatic variations in achieving perfect arm repositioning and to estimate the associated measurement variability in bone-to-tendon marker length measurements. Methods: Forty-eight patients underwent rotator cuff repair with intraoperative placement of radiopaque tendon markers at the repair site. All patients had a CT scan with their arms at the side on the day of surgery and at 3, 12, 26, and 52 weeks postoperatively. Glenohumeral position (defined by the orientation and distance of the humerus with respect to the scapula) and bone-to-tendon marker lengths were measured from each scan. Within-patient variation in glenohumeral position measurements was described by their pooled within-patient standard deviations (SDs), and variation in bone-to-tendon marker lengths by their standard errors of measurement (SEMs) and 95% confidence level minimally detectable distances (MDD95) and changes (MDC95). Results: The mean glenohumeral orientation from the 5 longitudinal CT scans averaged across the 48 patients was 12.6° abduction, 0.4° flexion, and –0.1° internal rotation. Within-patient SDs (95% confidence intervals) of glenohumeral orientation were 3.0° (2.7°-3.4°) in extension/flexion, 5.2° (4.6°-5.8°) in abduction/adduction, and 8.2° (7.3°-9.2°) in internal/external rotation. The SDs of glenohumeral distances were less than 1 mm in any direction. The estimated SEMs of bone-to-tendon lengths were consistent with a common value of 2.4 mm for any of the tendon markers placed across the repair, with MDD95 of 4.7 mm and MDC95 of 6.7 mm. Conclusion: Apparent tendon retraction of 5 mm or more, when measured as the distance from a tendon marker's day of surgery location to its new location on a volumetrically registered longitudinal CT scan, may be considered above the usual range of measurement variation. Tendon retraction measured using implanted radiopaque tendon markers offers an objective and sufficiently reliable means for quantifying the commonly expected changes in structural healing following rotator cuff repair.

Multi-parametric photoacoustic microscopy (PAM) has emerged as a promising new technique for high-resolution quantification of hemodynamics and oxygen metabolism in the mouse brain. In this work, we have extended the scope of multi-parametric PAM to longitudinal, cortex-wide, awake-brain imaging with the use of a long-lifetime (24 weeks), wide-field (5 × 7 mm2), light-weight (2 g), dual-transparency (i.e., light and ultrasound) cranial window. Cerebrovascular responses to the window installation were examined in vivo, showing a complete recovery in 18 days. In the 22-week monitoring after the recovery, no dura thickening, skull regrowth, or changes in cerebrovascular structure and function were observed. The promise of this technique was demonstrated by monitoring vascular and metabolic responses of the awake mouse brain to ischemic stroke throughout the acute, subacute, and chronic stages. Side-by-side comparison of the responses in the ipsilateral (injury) and contralateral (control) cortices shows that despite an early recovery of cerebral blood flow and an increase in microvessel density, a long-lasting deficit in cerebral oxygen metabolism was observed throughout the chronic stage in the injured cortex, part of which proceeded to infarction. This longitudinal, functional-metabolic imaging technique opens new opportunities to study the chronic progression and therapeutic responses of neurovascular diseases. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) is standard of care for rotator cuff evaluation, with clinical interpretation usually limited to qualitative judgments. The reliability of MRI-based measurements and scoring systems has been evaluated only preoperatively or ≥6 months following rotator cuff repair, when repairs are in the later stages of healing. This study describes the MRI assessments and inter-rater agreement of various rotator cuff tendon and muscle parameters evaluated preoperatively and 4 times during the first postoperative year. Two musculoskeletal radiologists independently assessed MRI scans of 42 patients preoperatively and 3, 12, 26, and 52 weeks after rotator cuff repair. Using standardized reading rules, readers assessed tendon integrity (5-point Sugaya classification), tear dimensions, muscle fat (5-point Goutallier classification) and atrophy (4-point Warner classification), muscle cross-sectional areas, and myotendinous junction distance. Raw exact agreement proportions, κ statistics, and correlation coefficients were used to quantify inter-rater agreement. Readers showed moderate to substantial above-chance agreement in scoring rotator cuff tendon integrity and supraspinatus muscle atrophy and good to excellent agreement on tear dimensions and muscle cross-sectional areas but only fair to moderate agreement for fatty infiltration and myotendinous junction distance. Only fatty infiltration grades evidenced observer bias. Inter-rater agreement did not appear time dependent. By use of defined reading rules in a research setting, MRI evaluations of rotator cuff tendon integrity, tear dimensions, muscle atrophy, and cross-sectional areas have reasonable reliability at all time points in the first postoperative year. However, the presence of clinically significant disagreements, even in such favorable circumstances, indicates the need for improved imaging tools for precise rotator cuff evaluation. [ABSTRACT FROM AUTHOR]

Osteoporosis is one of the most common skeletal diseases, but current therapies are limited to generalized antiresorptive or anabolic interventions, which do not target regions that would benefit from improvements to skeletal health. To improve the evaluation of treatment plans, we used a spatio-temporal multiscale approach that combines longitudinal in vivo micro-computed tomography (micro-CT) and in silico subject-specific finite element modeling to quantitatively map bone adaptation changes due to disease and treatment at high resolution. Our findings show time and region-dependent modifications in bone remodelling following one and two sets of mechanical loading and/or pharmacological interventions. The multiscale results highlighted that the distal section was unaffected by mechanical loading alone but the proximal tibia had the greatest gain from positive interactions of combined therapies. Mechanical loading abated the catabolic effect of PTH, but the main benefit of combined treatments occurred from the additive interactions of the two therapies in periosteal apposition. These results provide detailed insight into the efficacy of combined treatments, facilitating the optimisation of dosage and treatment duration in preclinical mouse studies, and the development of novel interventions for skeletal diseases. Combined mechanical loading and pharmacotherapy have the potential to slow osteoporosis-induced bone loss but current therapies do not target the regions in need of strengthening. We show for the first time spatial region-dependant interactions between PTH and mechanical loading treatment in OVX mouse tibiae, highlighting local regions in the tibia that benefitted from separate and combined treatments. Combined experimental-computational analysis also detailed the lasting period of each treatment per location in the tibia, the extent of positive (or negative) interactions of the combined therapies, and the impact of each treatment on the regulation of bone adaptation spatio-temporally. This approach can be used to create hypothesis about the interactions of different treatments to optimise the design of biomaterials and medical interventions. [Display omitted] [ABSTRACT FROM AUTHOR]

Substance use disorder (SUD) is comorbid with devastating health issues, social withdrawal, and isolation. Successful clinical treatments for SUD have used social interventions. Neurons can encode drug cues, and drug cues can trigger relapse. It is important to study how the activity in circuits and embedded cell types that encode drug cues develop in SUD. Exploring shared neurobiology between social interaction (SI) and SUD may explain why humans with access to social treatments still experience relapse. However, circuitry remains poorly characterized due to technical challenges in studying the complicated nature of SI and SUD. To understand the neural correlates of SI and SUD, it is important to: (1) identify cell types and circuits associated with SI and SUD, (2) record and manipulate neural activity encoding drug and social rewards over time, (3) monitor unrestrained animal behavior that allows reliable drug self-administration (SA) and SI. Miniaturized fluorescence microscopes (miniscopes) are ideally suited to meet these requirements. They can be used with gradient index (GRIN) lenses to image from deep brain structures implicated in SUD. Miniscopes can be combined with genetically encoded reporters to extract cell-type specific information. In this mini-review, we explore how miniscopes can be leveraged to uncover neural components of SI and SUD and advance potential therapeutic interventions. [ABSTRACT FROM AUTHOR]

Improvements in behavior are known to be accompanied by both structural and functional changes in the brain. However, whether those changes lead to more general improvements, beyond the behavior being trained, remains a contentious issue. We investigated whether training on one of two cognitive tasks would lead to either near transfer (that is, improvements on a quantifiably similar task) or far transfer (that is, improvements on a quantifiably different task), and furthermore, if such changes did occur, what the underlying neural mechanisms might be. Healthy adults (n = 16, 15 females) trained on either a verbal inhibitory control task or a visuospatial working memory task for 4 weeks, over the course of which they received five diffusion tensor imaging scans. Two additional tasks served as measures of near and far transfer. Behaviorally, participants improved on the task that they trained on, but did not improve on cognitively similar tests (near transfer), nor cognitively dissimilar tests (far transfer). Extensive changes to white matter microstructure were observed, with verbal inhibitory control training leading to changes in a left‐lateralized network of frontotemporal and occipitofrontal tracts, and visuospatial working memory training leading to changes in right‐lateralized frontoparietal tracts. Very little overlap was observed in changes between the two training groups. On the basis of these results, we suggest that near and far transfer were not observed because the changes in white matter tracts associated with training on each task are almost entirely nonoverlapping with, and therefore afford no advantages for, the untrained tasks. [ABSTRACT FROM AUTHOR]

Substance use disorder (SUD) is comorbid with devastating health issues, social withdrawal, and isolation. Successful clinical treatments for SUD have used social interventions. Neurons can encode drug cues, and drug cues can trigger relapse. It is important to study how the activity in circuits and embedded cell types that encode drug cues develop in SUD. Exploring shared neurobiology between social interaction (SI) and SUD may explain why humans with access to social treatments still experience relapse. However, circuitry remains poorly characterized due to technical challenges in studying the complicated nature of SI and SUD. To understand the neural correlates of SI and SUD, it is important to: (1) identify cell types and circuits associated with SI and SUD, (2) record and manipulate neural activity encoding drug and social rewards over time, (3) monitor unrestrained animal behavior that allows reliable drug self-administration (SA) and SI. Miniaturized fluorescence microscopes (miniscopes) are ideally suited to meet these requirements. They can be used with gradient index (GRIN) lenses to image from deep brain structures implicated in SUD. Miniscopes can be combined with genetically encoded reporters to extract cell-type specific information. In this mini-review, we explore how miniscopes can be leveraged to uncover neural components of SI and SUD and advance potential therapeutic interventions.

Decades of research have confirmed the beneficial and advantageous use of zebrafish (Danio rerio) as a model of human disease in biomedical studies. Not only are 71% of human genes shared with the zebrafish many of these genes are linked to human diseases. Currently, numerous transgenic and mutant genetic zebrafish lines are now widely available for use in research. Furthermore, zebrafish are relatively inexpensive to maintain compared to rodents. However, a limiting factor to fully utilising adult zebrafish in research is not the fish but the technological imaging tools available. In order to increase the utilisation of adult zebrafish, which are not naturally transparent, requires new imaging approaches. Therefore, this feasibility study: (1) presents an innovative designed PET/CT adult zebrafish imaging platform, capable of maintaining normal aquatic physiology during scanning; (2) assesses the practical aspects of adult zebrafish imaging; and (3) set basic procedural guidelines for zebrafish imaging during a PET/CT acquisition.Methods: With computer aided design (CAD) software an imaging platform was developed for 3D printing. A 3D printed zebrafish model was created from a CT acquisition of a zebrafish using the CAD software. This model and subsequently euthanised zebrafish were imaged post-injection using different concentrations of the radiotracer [18F]FDG with CT contrast.Results: PET/CT imaging was successful, revealing levels as low as 0.01 MBq could be detected in the fish. In the zebrafish imaging post-injection distribution of the radiotracer was observed away from the injection site as well as tissue uptake. Potential preliminary husbandry and welfare guidelines for the fish during and after PET/CT imaging were determined.Conclusion: Using PET/CT for adult zebrafish imaging as a viable non-invasive technological tool is feasible. Adult zebrafish PET/CT imaging has the potential to be a key imaging technique offering the possibilities of enhanced biomedical understanding and new translational data sets.

The first 1000 days from conception to two-years of age are a critical period in brain development, and there is an increasing drive for developing technologies to help advance our understanding of neurodevelopmental processes during this time. Functional near-infrared spectroscopy (fNIRS) has enabled longitudinal infant brain function to be studied in a multitude of settings. Conventional fNIRS analyses tend to occur in the channel-space, where data from equivalent channels across individuals are combined, which implicitly assumes that head size and source-detector positions (i.e. array position) on the scalp are constant across individuals. The validity of such assumptions in longitudinal infant fNIRS analyses, where head growth is most rapid, has not previously been investigated. We employed an image reconstruction approach to analyse fNIRS data collected from a longitudinal cohort of infants in The Gambia aged 5- to 12-months. This enabled us to investigate the effect of variability in both head size and array position on the anatomical and statistical inferences drawn from the data at both the group- and the individual-level. We also sought to investigate the impact of group size on inferences drawn from the data. We found that variability in array position was the driving factor between differing inferences drawn from the data at both the individual- and group-level, but its effect was weakened as group size increased towards the full cohort size (N = 53 at 5-months, N = 40 at 8-months and N = 45 at 12-months). We conclude that, at the group sizes in our dataset, group-level channel-space analysis of longitudinal infant fNIRS data is robust to assumptions about head size and array position given the variability in these parameters in our dataset. These findings support a more widespread use of image reconstruction techniques in longitudinal infant fNIRS studies.

[Display omitted] • Despite similar language symptoms at onset, nfvPPA and lvPPA show divergent disease trajectories. • NfvPPA show early emotion recognition impairments and progressive bilateral frontal atrophy. • LvPPA show rapid cognitive changes and progressive right temporal atrophy. • LvPPA also develop emotion recognition impairments later in the disease course. To examine the clinical trajectories and neural correlates of cognitive and emotion processing changes in the non-fluent/agrammatic (nfvPPA) and the logopenic (lvPPA) variants of primary progressive aphasia (PPA). Observational case-control longitudinal cohort study. Research clinic of frontotemporal dementia. This study recruited 29 non-semantic PPA patients (15 nfvPPA and 14 lvPPA) and compared them with 15 Alzheimer's disease (AD) patients and 14 healthy controls. Participants completed an annual assessment (median = 2 years; range = 1–5 years) of general cognition, emotion processing and structural MRI. Linear mixed effects models investigated clinical and imaging trajectories between groups. Over time, lvPPA showed the greatest cognitive deterioration. In contrast, nfvPPA showed significant decline in emotion recognition, whereas AD showed preserved emotion recognition, even with disease progression. Importantly, lvPPA also developed emotion processing impairments, with disease progression. Both nfvPPA and lvPPA showed continuing cortical atrophy in hallmark language-processing regions associated with these syndromes, together with progressive involvement of the right hemisphere regions, mirroring left hemisphere atrophy patterns at presentation. Decline in emotion processing was associated with bilateral frontal atrophy in nfvPPA and right temporal atrophy in lvPPA. Our results show divergent clinical courses in nfvPPA and lvPPA, with rapid cognitive and neural deterioration in lvPPA and emotion processing decline in both groups and support the concurrent assessment of cognition and emotion processing in the clinic to inform diagnosis and monitoring in the non-semantic variants of PPA. [ABSTRACT FROM AUTHOR]

White matter (WM) development early in life is a critical component of brain development that facilitates the coordinated function of neuronal pathways. Additionally, alterations in WM have been implicated in various neurodevelopmental disorders, including psychiatric disorders. Because of the need to understand WM development in the weeks immediately following birth, we characterized changes in WM microstructure throughout the postnatal macaque brain during the first year of life. This is a period in primates during which genetic, developmental, and environmental factors may have long-lasting impacts on WM microstructure. Studies in nonhuman primates (NHPs) are particularly valuable as a model for understanding human brain development because of their evolutionary relatedness to humans. Here, 34 rhesus monkeys (23 females, 11 males) were imaged longitudinally at 3, 7, 13, 25, and 53 weeks of age with T1-weighted (MPnRAGE) and diffusion tensor imaging (DTI). With linear mixed-effects (LME) modeling, we demonstrated robust logarithmic growth in FA, MD, and RD trajectories extracted from 18 WM tracts across the brain. Estimated rate of change curves for FA, MD, and RD exhibited an initial 10-week period of exceedingly rapid WM development, followed by a precipitous decline in growth rates. K-means clustering of raw DTI trajectories and rank ordering of LME model parameters revealed distinct posterior-to-anterior and medial-to-lateral gradients in WM maturation. Finally, we found that individual differences in WM microstructure assessed at 3 weeks of age were significantly related to those at 1 year of age. This study provides a quantitative characterization of very early WM growth in NHPs and lays the foundation for future work focused on the impact of alterations in early WM developmental trajectories in relation to human psychopathology.

Introduction: Micro-computed tomography with nanoparticle contrast agents may be a suitable tool for monitoring the time course of the development and progression of tumors. Here, we suggest a practical and convenient experimental method for generating and longitudinally imaging murine liver cancer models. Methods: Liver cancer was induced in 6 experimental mice by injecting clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeats-associated protein 9 plasmids causing mutations in genes expressed by hepatocytes. Nanoparticle agents are captured by Kupffer cells and detected by micro-computed tomography, thereby enabling longitudinal imaging. A total of 9 mice were used for the experiment. Six mice were injected with both plasmids and contrast, 2 injected with contrast alone, and one not injected with either agent. Micro-computed tomography images were acquired every 2- up to 14-weeks after cancer induction. Results: Liver cancer was first detected by micro-computed tomography at 8 weeks. The mean value of hepatic parenchymal attenuation remained almost unchanged over time, although the standard deviation of attenuation, reflecting heterogeneous contrast enhancement of the hepatic parenchyma, increased slowly over time in all mice. Histopathologically, heterogeneous distribution and aggregation of Kupffer cells was more prominent in the experimental group than in the control group. Heterogeneous enhancement of hepatic parenchyma, which could cause image quality deterioration and image misinterpretation, was observed and could be due to variation in Kupffer cells distribution. Conclusion: Micro-computed tomography with nanoparticle contrast is useful in evaluating the induction and characteristics of liver cancer, determining appropriate size of liver cancer for testing, and confirming therapeutic response. [ABSTRACT FROM AUTHOR]

Drug-induced interstitial lung disease (ILD) is crucial to detect early to achieve the best treatment outcome. Optimally, non-invasive imaging biomarkers can be used for early detection of disease progression and treatment follow-up. Therefore, reliable in vivo models are warranted in new imaging biomarker development to accelerate better-targeted treatment options. Single-dose bleomycin models have, for a long time, served as a reference model in fibrosis and lung injury research. Here, we aimed to use a clinically more relevant animal model by systemic exposure to bleomycin and assessing disease progression over time by combined magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging., Methods: C57BL/6 mice received bleomycin (i.p. 35iU/kg) or saline as control twice per week for 4 weeks. Mice were monitored until 2 weeks after cessation of bleomycin administration (w4 + 1 and w4 + 2), referred to as the resting period. MRI scans were performed in weeks 3 and 4 and during the resting weeks. [ 18 F]FDG-PET was performed at the last week of dosing (w4) and 2 weeks after the last dosing (w4 + 2). Lung tissue sections were stained with Masson's trichrome and evaluated by modified Ashcroft scoring. Lung volume and lesion volumes were assessed using MRI, as well as 3D mapping of the central airways., Results and Discussion: Bleomycin-challenged mice showed increased lung weights ( p  < 0.05), while total lung volume was unchanged (w4 and onward). Histology analysis demonstrated fibrotic lesions emanating from the distal parts of the lung. Fibrosis progression was visualized by MRI with significantly increased high signal in bleomycin-exposed lungs compared to controls ( p  < 0.05). In addition, a significant increase in central airway diameter ( p  < 0.01) was displayed in bleomycin-exposed animals compared to controls and further continued to dilate as the disease progressed, comparing the bleomycin groups over time ( p  < 0.05-0.001). Lung [ 18 F]FDG uptake was significantly elevated in bleomycin-exposed mice compared to controls ( p  < 0.05)., Conclusion: Non-invasive imaging displayed progressing lesions in the lungs of bleomycin-exposed mice, using two distinct MRI sequences and [ 18 F]FDG-PET. With observed fibrosis progression emanating from distal lung areas, dilation of the central airways was evident. Taken together, this chronic bleomycin-exposure model is translationally more relevant for studying lung injury in ILD and particularly in the context of DIILD., Competing Interests: Truly Labs—CRO performing in vivo model development. KW was the CEO of Truly Labs and NF, JL, and CC were employed at Truly Labs at the time when studies were conducted. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Mahmutovic Persson, Fransén Petterson, Liu, in 't Zandt, Carvalho, Örbom, Olsson and von Wachenfeldt.)

Neovascular age-related macular degeneration (nAMD) is nowadays successfully treated with anti-VEGF substances, but inter-individual treatment requirements are vastly heterogeneous and currently poorly plannable resulting in suboptimal treatment frequency. Optical coherence tomography (OCT) with its 3D high-resolution imaging serves as a companion diagnostic to anti-VEGF therapy. This creates a need for building predictive models using automated image analysis of OCT scans acquired during the treatment initiation phase. We propose such a model based on deep learning (DL) architecture, comprised of a densely connected neural network (DenseNet) and a recurrent neural network (RNN), trainable end-to-end. The method starts by sampling several 2D-images from an OCT volume to obtain a lower-dimensional OCT representation. At the core of the predictive model, the DenseNet learns useful retinal spatial features while the RNN integrates information from different time points. The introduced model was evaluated on the prediction of anti-VEGF treatment requirements in nAMD patients treated under a pro-re-nata (PRN) regimen. The DL model was trained on 281 patients and evaluated on a hold-out test set of 69 patient. The predictive model achieved a concordance index of 0.7 in regressing the number of received treatments, while in a classification task it obtained an 0.85 (0.81) AUC in detecting the patients with low (high) treatment requirements. The proposed model outperformed previous machine learning strategies that relied on a set of spatio-temporal image features, showing that the proposed DL architecture successfully learned to extract the relevant spatio-temporal patterns directly from raw longitudinal OCT images. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Rapid and adequate islet revascularisation and restoration of the islet–extracellular matrix (ECM) interaction are significant factors influencing islet survival and function of the transplanted islets in individuals with type 1 diabetes. Because the ECM encapsulating the islets is degraded during islet isolation, understanding the process of revascularisation and engraftment after transplantation is essential and needs further investigation. Methods: Here we apply a longitudinal and high-resolution imaging approach to investigate the dynamics of the pancreatic islet engraftment process up to 11 months after transplantation. Human and mouse islet grafts were inserted into the anterior chamber of the mouse eye, using a NOD.ROSA-tomato.Rag2−/− or B6.ROSA-tomato host allowing the investigation of the expansion of host vs donor cells and the contribution of host cells to aspects such as promoting the encapsulation and vascularisation of the graft. Results: A fibroblast-like stromal cell population of host origin rapidly migrates to ensheath the transplanted islet and aid in the formation of a basement membrane-like structure. Moreover, we show that the vessel network, while reconstituted by host endothelial cells, still retains the overall architecture of the donor islets. Conclusions/interpretation: In this transplantation situation the fibroblast-like stromal cells appear to take over as main producers of ECM or act as a scaffold for other ECM-producing cells to reconstitute a peri-islet-like basement membrane. This may have implications for our understanding of long-term graft rejection and for the design of novel strategies to interfere with this process. [ABSTRACT FROM AUTHOR]

The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial (11)C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources--ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm(3) by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm(3)/year) < amnestic mild cognitive impairment (2.5 cm(3)/year) < Alzheimer's disease (7.7 cm(3)/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = -0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =-0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =-0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.

Significance: Photoacoustic tomography (PAT) has great potential in monitoring disease progression and treatment response in breast cancer. However, due to variations in breast repositioning, there is a chance of geometric misalignment between images. Further, poor repositioning can affect light fluence distribution and imaging field-of-view, making images different from one another. The net effect is that it becomes challenging to distinguish between image changes due to repositioning effects and those due to true biological variations., Aim: The aim is to develop a three-dimensional image registration framework for geometrically aligning repeated PAT volumetric images, which are potentially affected by repositioning effects such as misalignment, changed radiant exposure conditions, and different fields-of-view., Approach: The proposed framework involves the use of a coordinate-based neural network to represent the displacement field between pairs of PAT volumetric images. A loss function based on normalized cross correlation and Frangi vesselness feature extraction at multiple scales was implemented. We refer to our image registration framework as MUVINN-reg, which stands for multiscale vesselness-based image registration using neural networks. The approach was tested on a longitudinal dataset of healthy volunteer breast PAT images acquired with the hybrid photoacoustic-ultrasound Photoacoustic Mammoscope 3 imaging system. The registration performance was also tested under unfavorable repositioning conditions such as intentional mispositioning, and variation in breast-supporting cup size between measurements., Results: A total of 13 pairs of repeated PAT scans were included in this study. MUVINN-reg showed excellent performance in co-registering each pair of images. The proposed framework was shown to be robust to image intensity shifts and field-of-view changes. Furthermore, MUVINN-reg could align vessels at imaging depths greater than 4 cm., Conclusions: The proposed framework will enable the use of PAT for quantitative and reproducible monitoring of disease progression and treatment response., (© 2024 The Authors.)

Longitudinal neuroimaging studies are becoming increasingly prevalent, where brain images are collected on multiple subjects at multiple time points. Analyses of such data are scientifically important, but also challenging. Brain images are in the form of multidimensional arrays, or tensors, which are characterized by both ultrahigh dimensionality and a complex structure. Longitudinally repeated images and induced temporal correlations add a further layer of complexity. Despite some recent efforts, there exist very few solutions for longitudinal imaging analyses. In response to the increasing need to analyze longitudinal imaging data, we propose several tensor generalized estimating equations (GEEs). The proposed GEE approach accounts for intra-subject correlation, and an imposed low-rank structure on the coefficient tensor effectively reduces the dimensionality. We also propose a scalable estimation algorithm, establish the asymptotic properties of the solution to the tensor GEEs, and investigate sparsity regularization for the purpose of region selection. We demonstrate the proposed method using simulations and by analyzing a real data set from the Alzheimer's Disease Neuroimaging Initiative. [ABSTRACT FROM AUTHOR]

Rodent studies of bone in chronic kidney disease have primarily relied on end-point examinations of bone microarchitecture. This study used longitudinal in vivo microcomputed tomography (in vivo μCT) to characterize the onset and progression of bone loss, specifically cortical porosity, in the Cy/+ rat of model of CKD. Male CKD rats and normal littermates were studied. In vivo μCT scans of the right distal tibia repeated at 25, 30, and 35 weeks were analyzed for longitudinal changes in cortical and trabecular bone morphometry. In vitro μCT scans of the tibia and femur identified spatial patterns of bone loss across distal, midshaft and proximal sites. CKD animals had reduced BV/TV and cortical BV at all time points but developed cortical porosity and thinning between 30 and 35 weeks. Cortical pore formation was localized near the endosteal surface. The severity of bone loss was variable across bone sites, but the distal tibia was representative of both cortical and trabecular changes. The distal tibia was found to be a sensitive suitable site for longitudinal imaging of both cortical and trabecular bone changes in the CKD rat. CKD trabecular bone loss progressed through ~30 weeks followed by a sudden acceleration in cortical bone catabolism. These changes varied in timing and severity across individuals, and cortical bone loss and porosity progressed rapidly once initiated. The inclusion of longitudinal μCT in future studies will be important for both reducing the number of required animals and to track individual responses to treatment. Unlabelled Image • The distal tibia is a sensitive site for longitudinal μCT of cortical and trabecular bone changes in the CKD rat. • CKD trabecular bone loss largely precedes the initial formation of cortical porosity. • CKD cortical porosity formation is initially concentrated near the endosteal surface. • CKD cortical bone loss varies in timing and severity across individuals but porosity progresses rapidly once initiated. [ABSTRACT FROM AUTHOR]

Highlights • The human brain has a protracted developmental trajectory and is inherently adaptive. • A dynamic, developmental aspect is largely missing from neurobiological models of psychopathology. • Longitudinal data are key to progress in our understanding of social anxiety disorder. • Analytical recommendations for longitudinal imaging studies are made. Abstract Longitudinal studies offer a unique window into developmental change. Yet, most of what we know about the pathophysiology of psychiatric disorders is based on cross-sectional work. Here, we highlight the importance of adopting a longitudinal approach in order to make progress towards identifying the neurobiological mechanisms of social anxiety disorder (SAD). Using examples, we illustrate how longitudinal data can uniquely inform SAD etiology and timing of interventions. The brain's inherently adaptive quality requires that we model risk correlates of disorders as dynamic in their expression. Developmental theories regarding timing of environmental events, cascading effects and (mal)adaptations of the developing brain will be crucial components of comprehensive, integrative models of SAD. We close by discussing analytical considerations when working with longitudinal, developmental data. [ABSTRACT FROM AUTHOR]

Cerebral hemodynamics are modulated in response to changes in neuronal activity, a process termed neurovascular coupling (NVC), which can be disrupted by neuropsychiatric diseases (e.g., stroke, Alzheimer's disease). Thus, there is growing interest to image long-term NVC dynamics with high spatiotemporal resolutions. Here, by combining the use of a genetically-encoded calcium indicator with optical techniques, we develop a longitudinal multimodal optical imaging platform (MIP) that enabled time-lapse tracking of NVC over a relatively large field of view in the mouse somatosensory cortex at single cell and single vessel resolutions. Specifically, GCaMP6f was used as marker of neuronal activity, which along with MIP allowed us to simultaneously measure the changes in neuronal [Ca 2+ ] i fluorescence, cerebral blood flow velocity (CBFv) and hemodynamics longitudinally for more than eight weeks. We show that [Ca 2+ ] i fluorescence was detectable one week post viral injection and the damage to local microvasculature and perfusion recovered two weeks after injection. By three weeks post viral injection, maximal neuronal and CBFv responses to hindpaw stimulations were observed. Moreover, single neuronal activation in response to hindpaw stimulation was consistently recorded, followed by ∼2 s delayed dilation of contiguous microvessels. Additionally, resting-state spontaneous neuronal and hemodynamic oscillations were detectable throughout the eight weeks of study. Our results demonstrate the capability of MIP for longitudinal investigation of the organization and plasticity of the neurovascular network during resting state and during stimulation-evoked neuronal activation at high spatiotemporal resolutions. [ABSTRACT FROM AUTHOR]

A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-points. This work explores the issues raised in using model-derived metric as predictors for survival analyses. Re-growth rate and time to tumour re-growth were calculated for three large clinical studies by forward and reverse alignment. The latter involves re-aligning patients to their time of progression. Hence, it accounts for the time taken to estimate re-growth rate and time to tumour re-growth but also assesses if these predictors correlate to survival from the time of progression. I found that neither re-growth rate nor time to tumour re-growth correlated to survival using reverse alignment. This suggests that the dynamics of tumours up until disease progression has no relationship to survival post progression. For prediction of a phase III trial I found the metrics performed no better than empirical end-points. These results highlight that care must be taken when relating dynamics of tumour imaging to survival and that bench-marking new approaches to existing ones is essential.

Preclinical animal model studies of brain energy metabolism and neuroinflammation in Alzheimer’s disease have produced conflicting results, hampering both the elucidation of the underlying disease mechanism and the development of effective Alzheimer’s disease therapies. Here, we aimed to quantify the relationship between brain energy metabolism and neuroinflammation in the APP/PS1-21 transgenic mouse model of Alzheimer’s disease using longitudinal in vivo18F-FDG and 18F-DPA-714) PET imaging and ex vivo brain autoradiography. APP/PS1-21 (TG, n = 9) and wild type control mice (WT, n = 9) were studied longitudinally every third month from age 6 to 15 months with 18F-FDG and 18F-DPA-714 with a one-week interval between the scans. Additional TG (n = 52) and WT (n = 29) mice were used for ex vivo studies. In vivo, the 18F-FDG SUVs were lower and the 18F-DPA-714 binding ratios relative to the cerebellum were higher in the TG mouse cortex and hippocampus than in WT mice at age 12 to 15 months (p < 0.05). The ex vivo cerebellum binding ratios supported the results of the in vivo18F-DPA-714 studies but not the 18F-FDG studies. This longitudinal PET study demonstrated decreased energy metabolism and increased inflammation in the brains of APP/PS1-21 mice compared to WT mice. [ABSTRACT FROM AUTHOR]

Background & new method The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer’s Disease Neuroimaging initiative (ADNI). Results and comparison with existing methods While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level. Interestingly, the neurobiological relevance of the relevant parameter at the individual level describes specific differences associated with aging. In addition, our approach highlights white matter areas that reliably discriminate between patients with Alzheimer’s disease and healthy controls with a predictive power of 0.99 and include the hippocampal alveus, the para-hippocampal white matter, the white matter of the posterior cingulate, and optic tracts. In this context, notably the classifier includes a sub-population of patients with minimal cognitive impairment into the pathological domain. Conclusion Our classifier offers promising features for an accessible biomarker that predicts the risk of conversion to Alzheimer’s disease. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu ). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf. Significance statement This study assesses neuro-degenerative processes in the brain’s white matter as revealed by diffusion-weighted imaging, in order to discriminate healthy from pathological aging in a large sample of elderly subjects. The analysis of time-series examinations in a linear mixed effects model allowed the discrimination of population-based aging processes from individual determinants. We demonstrate that a simple classifier based on white matter imaging data is able to predict the conversion to Alzheimer’s disease with a high predictive power [ABSTRACT FROM AUTHOR]

Preterm birth results in premature exposure of the brain to the extrauterine environment during a critical period of neurodevelopment. Consequently, infants born preterm are at a heightened risk of adverse behavioural outcomes in later life. We characterise longitudinal development of neonatal regional brain volume and functional connectivity in the first weeks following preterm birth, sociodemographic factors, and their respective relationships to psychomotor outcomes and psychopathology in toddlerhood. We study 121 infants born preterm who underwent magnetic resonance imaging shortly after birth, at term-equivalent age, or both. Longitudinal regional brain volume and functional connectivity were modelled as a function of psychopathology and psychomotor outcomes at 18 months. Better psychomotor functioning in toddlerhood was associated with greater relative right cerebellar volume and a more rapid decrease over time of sensorimotor degree centrality in the neonatal period. In contrast, increased 18-month psychopathology was associated with a more rapid decrease in relative regional subcortical volume. Furthermore, while socio-economic deprivation was related to both psychopathology and psychomotor outcomes, cognitively stimulating parenting predicted psychopathology only. Our study highlights the importance of longitudinal imaging to better predict toddler outcomes following preterm birth, as well as disparate environmental influences on separable facets of behavioural development in this population. [ABSTRACT FROM AUTHOR]