CUB Domain-Containing Protein 1 (CDCP1) is a rational target for the development of imaging tracers and antibody-drug conjugates for cancer detection and therapy.

Rationale: An antibody-drug conjugate (ADC) is a targeted therapy consisting of a cytotoxic payload that is linked to an antibody which targets a protein enriched on malignant cells. Multiple ADCs are currently used clinically as anti-cancer agents significantly improving patient survival. Herein, we evaluated the rationale of targeting the cell surface oncoreceptor CUB domain-containing protein 1 (CDCP1) using ADCs and assessed the efficacy of CDCP1-directed ADCs against a range of malignant tumors. Methods: CDCP1 mRNA expression was evaluated using large transcriptomic datasets of normal/tumor samples for 23 types of cancer and 15 other normal organs, and CDCP1 protein expression was examined in 34 normal tissues, >300 samples from six types of cancer, and in 49 cancer cell lines. A recombinant human/mouse chimeric anti-CDCP1 antibody (ch10D7) was labelled with 89Zirconium or monomethyl auristatin E (MMAE) and tested in multiple pre-clinical cancer models including 36 cancer cell lines and three mouse xenograft models. Results: Analysis of CDCP1 expression indicates elevated CDCP1 expression in the majority of the cancers and restricted expression in normal human tissues. Antibody ch10D7 demonstrates a high affinity and specificity for CDCP1 inducing cell signalling via Src accompanied by rapid internalization of ch10D7/CDCP1 complexes in cancer cells. 89Zirconium-labelled ch10D7 accumulates in CDCP1 expressing cells enabling detection of pancreatic cancer xenografts in mice by PET imaging. Cytotoxicity of MMAE-labelled ch10D7 against kidney, colorectal, lung, ovarian, pancreatic and prostate cancer cells in vitro, correlates with the level of CDCP1 on the plasma membrane. ch10D7-MMAE displays robust anti-tumor effects against mouse xenograft models of pancreatic, colorectal and ovarian cancer. Conclusion: CDCP1 directed imaging agents will be useful for selecting cancer patients for personalized treatment with cytotoxin-loaded CDCP1 targeting agents including antibody-drug conjugates.

Early clinical and MRI biomarkers of cognitive and motor outcomes in very preterm born infants.

BACKGROUND: This study aimed to identify which MRI and clinical assessments, alone or in combination, from (i) early (32 weeks postmenstrual age, PMA), (ii) term equivalent age (TEA) and (iii) 3 months corrected age (CA) are associated with motor or cognitive outcomes at 2 years CA in infants born <31 weeks gestation. METHODS: Prospective cohort study of 98 infants who underwent early and TEA MRI (n = 59 males; median birth gestational age 28 + 5 weeks). Hammersmith Neonatal Neurological Examination (HNNE), NICU Neonatal Neurobehavioural Scale and General Movements Assessment (GMs) were performed early and at TEA. Premie-Neuro was performed early and GMs, Test of Infant Motor Performance and visual assessment were performed at TEA and 3 months CA. Neurodevelopmental outcomes were determined using Bayley Scales of Infant and Toddler Development 3rd edition. RESULTS: The best combined motor outcome model included 3-month GMs (ß = -11.41; 95% CI = -17.34, -5.49), TEA MRI deep grey matter score (ß = -6.23; 95% CI = -9.47, -2.99) and early HNNE reflexes (ß = 3.51; 95% CI = 0.86, 6.16). Combined cognitive model included 3-month GMs (ß = -10.01; 95% CI = -15.90, -4.12) and TEA HNNE score (ß = 1.33; 95% CI = 0.57, 2.08). CONCLUSION: Early neonatal neurological assessment improves associations with motor outcomes when combined with term MRI and 3-month GMs. Term neurological assessment combined with 3-month GMs improves associations with cognitive outcomes. IMPACT: We present associations between 32- and 40-week MRI, comprehensive clinical assessments and later 2-year motor and cognitive outcomes for children born <31 weeks gestation. MRI and clinical assessment of motor, neurological and neurobehavioural function earlier than term equivalent age in very preterm infants is safe and becoming more available in clinical settings. Most of these children are discharged from hospital before term age and so completing assessments prior to discharge can assist with follow up. MRI and neurological assessment prior to term equivalent age while the child is still in hospital can provide earlier identification of children at highest risk of adverse outcomes and guide follow-up screening and intervention services.

Brain microstructure and morphology of very preterm-born infants at term equivalent age: Associations with motor and cognitive outcomes at 1 and 2 years.

Very preterm-born infants are at risk of adverse neurodevelopmental outcomes. Brain magnetic resonance imaging (MRI) at term equivalent age (TEA) can probe tissue microstructure and morphology, and demonstrates potential in the early prediction of outcomes. In this study, we use the recently introduced fixel-based analysis method for diffusion MRI to investigate the association between microstructure and morphology at TEA, and motor and cognitive development at 1 and 2 years corrected age (CA). Eighty infants born <31 weeks' gestation successfully underwent diffusion MRI (3T; 64 directions; b â€‹= â€‹2000s/mm2) at term equivalent age, and had neurodevelopmental follow-up using the Bayley-III motor and cognitive assessments at 1 year (n â€‹= â€‹78) and/or 2 years (n â€‹= â€‹76) CA. Diffusion MRI data were processed using constrained spherical deconvolution (CSD) and aligned to a study-specific fibre orientation distribution template, yielding measures of fibre density (FD), fibre-bundle cross-section (FC), and fibre density and bundle cross-section (FDC). The association between FD, FC, and FDC at TEA, and motor and cognitive composite scores at 1 and 2 years CA, and change in composite scores from 1 to 2 years, was assessed using whole-brain fixel-based analysis. Additionally, the association between diffusion tensor imaging (DTI) metrics (fractional anisotropy FA, mean diffusivity MD, axial diffusivity AD, radial diffusivity RD) and outcomes was investigated. Motor function at 1 and 2 years CA was associated with CSD-based measures of the bilateral corticospinal tracts and corpus callosum. Cognitive function was associated with CSD-based measures of the midbody (1-year outcomes only) and splenium of the corpus callosum, as well as the bilateral corticospinal tracts. The change in motor/cognitive outcomes from 1 to 2 years was associated with CSD-based measures of the splenium of the corpus callosum. Analysis of DTI-based measures showed overall less extensive associations. Post-hoc analysis showed that associations were weaker for 2-year outcomes than they were for 1-year outcomes. Infants with better neurodevelopmental outcomes demonstrated higher FD, FC, and FDC at TEA, indicating better information transfer capacity which may be related to increased number of neurons, increased myelination, thicker bundles, and/or combinations thereof. The fibre bundles identified here may serve as the basis for future studies investigating the predictive ability of these metrics.

Prediction of childhood brain outcomes in infants born preterm using neonatal MRI and concurrent clinical biomarkers (PREBO-6): study protocol for a prospective cohort study.

INTRODUCTION: Infants born very preterm are at risk of adverse neurodevelopmental outcomes, including cognitive deficits, motor impairments and cerebral palsy. Earlier identification enables targeted early interventions to be implemented with the aim of improving outcomes. METHODS AND ANALYSIS: Protocol for 6-year follow-up of two cohorts of infants born <31 weeks gestational age (PPREMO: Prediction of Preterm Motor Outcomes; PREBO: Prediction of Preterm Brain Outcomes) and a small term-born reference sample in Brisbane, Australia. Both preterm cohorts underwent very early MRI and concurrent clinical assessment at 32 and 40 weeks postmenstrual age (PMA) and were followed up at 3, 12 and 24 months corrected age (CA). This study will perform MRI and electroencephalography (EEG). Primary outcomes include the Movement Assessment Battery for Children second edition and Full-Scale IQ score from the Wechsler Intelligence Scale for Children fifth edition (WISC-V). Secondary outcomes include the Gross Motor Function Classification System for children with cerebral palsy; executive function (Behavior Rating Inventory of Executive Function second edition, WISC-V Digit Span and Picture Span, Wisconsin Card Sorting Test 64 Card Version); attention (Test of Everyday Attention for Children second edition); language (Clinical Evaluation of Language Fundamentals fifth edition), academic achievement (Woodcock Johnson IV Tests of Achievement); mental health and quality of life (Development and Well-Being Assessment, Autism Spectrum Quotient-10 Items Child version and Child Health Utility-9D). AIMS: Examine the ability of early neonatal MRI, EEG and concurrent clinical measures at 32 weeks PMA to predict motor, cognitive, language, academic achievement and mental health outcomes at 6 years CA.Determine if early brain abnormalities persist and are evident on brain MRI at 6 years CA and the relationship to EEG and concurrent motor, cognitive, language, academic achievement and mental health outcomes. ETHICS AND DISSEMINATION: Ethical approval has been obtained from Human Research Ethics Committees at Children's Health Queensland (HREC/19/QCHQ/49800) and The University of Queensland (2019000426). Study findings will be presented at national and international conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ACTRN12619000155190p. WEB ADDRESS OF TRIAL: http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12619000155190p.

PET Imaging Quantifying 68Ga-PSMA-11 Uptake in Metastatic Colorectal Cancer.

At diagnosis, 22% of colorectal cancer (CRC) patients have metastases, and 50% later develop metastasis. Peptide receptor radionuclide therapy (PRRT), such as 177Lu-PSMA-617, is used to treat metastatic prostate cancer. 177Lu-PSMA-617 targets prostate-specific membrane antigen (PSMA), a cell-surface protein enriched in prostate cancer and the neovasculature of other solid tumors, including CRC. We performed 68Ga-PSMA-11 PET/CT imaging of 10 patients with metastatic CRC to assess metastasis avidity. Eight patients had lesions lacking avidity, and 2 had solitary metastases exhibiting very low avidity. Despite expression of PSMA in CRC neovasculature, none of the patients exhibited tumor avidity sufficient to be considered for 177Lu-PSMA-617 PRRT.

Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model.

BACKGROUND AND AIMS: Preterm birth imposes a high risk for developing neuromotor delay. Earlier prediction of adverse outcome in preterm infants is crucial for referral to earlier intervention. This study aimed to predict abnormal motor outcome at 2 years from early brain diffusion magnetic resonance imaging (MRI) acquired between 29 and 35 weeks postmenstrual age (PMA) using a deep learning convolutional neural network (CNN) model. METHODS: Seventy-seven very preterm infants (born <31 weeks gestational age (GA)) in a prospective longitudinal cohort underwent diffusion MR imaging (3T Siemens Trio; 64 directions, b â€‹= â€‹2000 â€‹s/mm2). Motor outcome at 2 years corrected age (CA) was measured by Neuro-Sensory Motor Developmental Assessment (NSMDA). Scores were dichotomised into normal (functional score: 0, normal; n â€‹= â€‹48) and abnormal scores (functional score: 1-5, mild-profound; n â€‹= â€‹29). MRIs were pre-processed to reduce artefacts, upsampled to 1.25 â€‹mm isotropic resolution and maps of fractional anisotropy (FA) were estimated. Patches extracted from each image were used as inputs to train a CNN, wherein each image patch predicted either normal or abnormal outcome. In a postprocessing step, an image was classified as predicting abnormal outcome if at least 27% (determined by a grid search to maximise the model performance) of its patches predicted abnormal outcome. Otherwise, it was considered as normal. Ten-fold cross-validation was used to estimate performance. Finally, heatmaps of model predictions for patches in abnormal scans were generated to explore the locations associated with abnormal outcome. RESULTS: For the identification of infants with abnormal motor outcome based on the FA data from early MRI, we achieved mean sensitivity 70% (standard deviation SD 19%), mean specificity 74% (SD 39%), mean AUC (area under the receiver operating characteristic curve) 72% (SD 14%), mean F1 score of 68% (SD 13%) and mean accuracy 73% (SD 19%) on an unseen test data set. Patch-based prediction heatmaps showed that the patches around the motor cortex and somatosensory regions were most frequently identified by the model with high precision (74%) as a location associated with abnormal outcome. Part of the cerebellum, and occipital and frontal lobes were also highly associated with abnormal NSMDA/motor outcome. DISCUSSION/CONCLUSION: This study established the potential of an early brain MRI-based deep learning CNN model to identify preterm infants at risk of a later motor impairment and to identify brain regions predictive of adverse outcome. Results suggest that predictions can be made from FA maps of diffusion MRIs well before term equivalent age (TEA) without any prior knowledge of which MRI features to extract and associated feature extraction steps. This method, therefore, is suitable for any case of brain condition/abnormality. Future studies should be conducted on a larger cohort to re-validate the robustness and effectiveness of these models.

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies.

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Innovative Therapeutic Strategies for Effective Treatment of Brain Metastases.

Brain metastases are the most prevalent of intracranial malignancies. They are associated with a very poor prognosis and near 100% mortality. This has been the case for decades, largely because we lack effective therapeutics to augment surgery and radiotherapy. Notwithstanding improvements in the precision and efficacy of these life-prolonging treatments, with no reliable options for adjunct systemic therapy, brain recurrences are virtually inevitable. The factors limiting intracranial efficacy of existing agents are both physiological and molecular in nature. For example, heterogeneous permeability, abnormal perfusion and high interstitial pressure oppose the conventional convective delivery of circulating drugs, thus new delivery strategies are needed to achieve uniform drug uptake at therapeutic concentrations. Brain metastases are also highly adapted to their microenvironment, with complex cross-talk between the tumor, the stroma and the neural compartments driving speciation and drug resistance. New strategies must account for resistance mechanisms that are frequently engaged in this milieu, such as HER3 and other receptor tyrosine kinases that become induced and activated in the brain microenvironment. Here, we discuss molecular and physiological factors that contribute to the recalcitrance of these tumors, and review emerging therapeutic strategies, including agents targeting the PI3K axis, immunotherapies, nanomedicines and MRI-guided focused ultrasound for externally controlling drug delivery.

A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective.

Autism Spectrum Disorder (ASD) affects approximately 1% of the population and leads to impairments in social interaction, communication and restricted, repetitive behaviours. Establishing robust neuroimaging biomarkers of ASD using structural magnetic resonance imaging (MRI) is an important step for diagnosing and tailoring treatment, particularly early in life when interventions can have the greatest effect. However currently, there is mixed findings on the structural brain changes associated with autism. Therefore in this systematic review, recent (post-2007), high-resolution (3 T) MRI studies investigating brain morphology associated with ASD have been collated to identify robust neuroimaging biomarkers of ASD. A systematic search was conducted on three databases; PubMed, Web of Science and Scopus, resulting in 123 reviewed articles. Patients with ASD were observed to have increased whole brain volume, particularly under 6 years of age. Other consistent changes observed in ASD patients include increased volume in the frontal and temporal lobes, increased cortical thickness in the frontal lobe, increased surface area and cortical gyrification, and increased cerebrospinal fluid volume, as well as reduced cerebellum volume and reduced corpus callosum volume, compared to typically developing controls. Findings were inconsistent regarding the developmental trajectory of brain volume and cortical thinning with age in ASD, as well as potential volume differences in the white matter, hippocampus, amygdala, thalamus and basal ganglia. To elucidate these inconsistencies, future studies should look towards aggregating MRI data from multiple sites or available repositories to avoid underpowered studies, as well as utilising methods which quantify larger-scale image features to reduce the number of statistical tests performed, and hence risk of false positive findings. Additionally, studies should look to perform a thorough validation strategy, to ensure generalisability of study findings, as well as look to leverage the improved image resolution of 3 T scanning to identify subtle brain changes related to ASD.

Fixel-based analysis reveals alterations is brain microstructure and macrostructure of preterm-born infants at term equivalent age.

Preterm birth causes significant disruption in ongoing brain development, frequently resulting in adverse neurodevelopmental outcomes. Brain imaging using diffusion MRI may provide valuable insight into microstructural properties of the developing brain. The aim of this study was to establish whether the recently introduced fixel-based analysis method, with its associated measures of fibre density (FD), fibre bundle cross-section (FC), and fibre density and bundle cross-section (FDC), is suitable for the investigation of the preterm infant brain at term equivalent age. High-angular resolution diffusion weighted images (HARDI) of 55 preterm-born infants and 20 term-born infants, scanned around term-equivalent age, were included in this study (3 T, 64 directions, b = 2000 s/mm2). Postmenstrual age at the time of MRI, and intracranial volume (FC and FDC only), were identified as confounding variables. Gestational age at birth was correlated with all fixel measures in the splenium of the corpus callosum. Compared to term-born infants, preterm infants showed reduced FD, FC, and FDC in a number of regions, including the corpus callosum, anterior commissure, cortico-spinal tract, optic radiations, and cingulum. Preterm infants with minimal macroscopic brain abnormality showed more extensive reductions than preterm infants without any macroscopic brain abnormality; however, little differences were observed between preterm infants with no and with minimal brain abnormality. FC showed significant reductions in preterm versus term infants outside regions identified with FD and FDC, highlighting the complementary role of these measures. Fixel-based analysis identified both microstructural and macrostructural abnormalities in preterm born infants, providing a more complete picture of early brain development than previous diffusion tensor imaging (DTI) based approaches.

Relationship between very early brain structure and neuromotor, neurological and neurobehavioral function in infants born <31 weeks gestational age.

AIM: This study aimed to examine associations between structural MRI and concurrent motor, neurological and neurobehavioral measures at 30-32 weeks postmenstrual age (PMA; 'Early'), and at term equivalent age ('Term'). METHOD: In this prospective cohort study, infants underwent Early MRI (n = 119; 73 male; median 32 weeks 1 day PMA) and Term MRI (n = 102; 61 male; median 40 weeks 4 days PMA) at 3 T. Structural images were scored generating white matter (WM), cortical gray matter, deep gray matter, cerebellar and global brain abnormality scores. Clinical measures were General Movements Assessment (GMs), Hammersmith Neonatal Neurological Examination (HNNE) and NICU Neonatal Neurobehavioral Scale (NNNS). The Premie-Neuro was administered Early and the Test of Infant Motor Performance (TIMP) and a visual assessment at Term. RESULTS: Early MRI cerebellar scores were strongly associated with neurological components of HNNE (reflexes), NNNS (Hypertonicity), the Premie-Neuro neurological subscale (regression coefficient ß = -0.06; 95% confidence interval CI = -0.09, -0.04; p < .001) and cramped-synchronized GMs (ß = 1.10; 95%CI = 0.57, 1.63; p < .001). Term MRI WM and global scores were strongly associated with the TIMP (WM ß = -1.02; 95%CI = -1.67, -0.36; p = .002; global ß = -1.59; 95%CI = -2.62, -0.56; p = .001). INTERPRETATION: Brain structure on Early and Term MRI was associated with concurrent motor, neurological and neurobehavioral function in very preterm infants.

Diagnostic accuracy of early magnetic resonance imaging to determine motor outcomes in infants born preterm: a systematic review and meta-analysis.

AIM: To examine the diagnostic ability of early magnetic resonance imaging (MRI; <36wks postmenstrual age) to detect later adverse motor outcomes or cerebral palsy (CP) in infants born preterm. METHOD: Studies of infants born preterm with MRI earlier than 36 weeks postmenstrual age and quantitative motor data or a diagnosis of CP at or beyond 1 year corrected age were identified. Study details were extracted and meta-analyses performed where possible. Quality of included studies was evaluated with the QUADAS-2 (a revised tool for the quality assessment of diagnostic accuracy studies). RESULTS: Thirty-one articles met the inclusion criteria, five of which reported diagnostic accuracy and five reported data sufficient for calculation of diagnostic accuracy. Early structural MRI global scores detected a later diagnosis of CP with a pooled sensitivity of 100% (95% confidence interval [CI] 86-100) and a specificity of 93% (95% CI 59-100). Global structural MRI scores determined adverse motor outcomes with a pooled sensitivity of 89% (95% CI 44-100) and a specificity of 98% (95% CI 90-100). White matter scores determined adverse motor outcomes with a pooled sensitivity of 33% (95% CI 20-48) and a specificity of 83% (95% CI 78-88). INTERPRETATION: Early structural MRI has reasonable sensitivity and specificity to determine adverse motor outcomes and CP in infants born preterm. Greater reporting of diagnostic accuracy in studies examining relationships with motor outcomes and CP is required to facilitate clinical utility of early MRI. WHAT THIS PAPER ADDS: Early magnetic resonance imaging (MRI) has reasonable sensitivity and specificity to determine later adverse motor outcomes and cerebral palsy (CP). Detection of infants who progressed to CP was stronger than motor outcomes. Global MRI scores determined adverse motor outcomes more accurately than white matter scores. Few studies report diagnostic accuracy of early MRI findings. Diagnostic accuracy is required to draw clinically meaningful conclusions from early MRI studies.

Brain changes following four weeks of unimanual motor training: Evidence from fMRI-guided diffusion MRI tractography.

We have reported reliable changes in behavior, brain structure, and function in 24 healthy right-handed adults who practiced a finger-thumb opposition sequence task with their left hand for 10 min daily, over 4 weeks. Here, we extend these findings by using diffusion MRI to investigate white-matter changes in the corticospinal tract, basal-ganglia, and connections of the dorsolateral prefrontal cortex. Twenty-three participant datasets were available with pre-training and post-training scans. Task performance improved in all participants (mean: 52.8%, SD: 20.0%; group P < 0.01 FWE) and widespread microstructural changes were detected across the motor system of the "trained" hemisphere. Specifically, region-of-interest-based analyses of diffusion MRI (n = 22) revealed significantly increased fractional anisotropy (FA) in the right caudate nucleus (4.9%; P < 0.05 FWE), and decreased mean diffusivity in the left nucleus accumbens (-1.3%; P < 0.05 FWE). Diffusion MRI tractography (n = 22), seeded by sensorimotor cortex fMRI activation, also revealed increased FA in the right corticospinal tract (mean 3.28%; P < 0.05 FWE) predominantly reflecting decreased radial diffusivity. These changes were consistent throughout the entire length of the tract. The left corticospinal tract did not show any changes. FA also increased in white matter connections between the right middle frontal gyrus and both right caudate nucleus (17/22 participants; P < 0.05 FWE) and right supplementary motor area (18/22 participants; P < 0.05 FWE). Equivalent changes in FA were not seen in the left (non-trained) hemisphere. In combination with our functional and structural findings, this study provides detailed, multifocal evidence for widespread neuroplastic changes in the human brain resulting from motor training. Hum Brain Mapp 38:4302-4312, 2017. © 2017 Wiley Periodicals, Inc.

Brain changes following four weeks of unimanual motor training: Evidence from behavior, neural stimulation, cortical thickness, and functional MRI.

Although different aspects of neuroplasticity can be quantified with behavioral probes, brain stimulation, and brain imaging assessments, no study to date has combined all these approaches into one comprehensive assessment of brain plasticity. Here, 24 healthy right-handed participants practiced a sequence of finger-thumb opposition movements for 10 min each day with their left hand. After 4 weeks, performance for the practiced sequence improved significantly (P < 0.05 FWE) relative to a matched control sequence, with both the left (mean increase: 53.0% practiced, 6.5% control) and right (21.0%; 15.8%) hands. Training also induced significant (cluster p-FWE < 0.001) reductions in functional MRI activation for execution of the trained sequence, relative to the control sequence. These changes were observed as clusters in the premotor and supplementary motor cortices (right hemisphere, 301 voxel cluster; left hemisphere 700 voxel cluster), and sensorimotor cortices and superior parietal lobules (right hemisphere 864 voxel cluster; left hemisphere, 1947 voxel cluster). Transcranial magnetic stimulation over the right ("trained") primary motor cortex yielded a 58.6% mean increase in a measure of motor evoked potential amplitude, as recorded at the left abductor pollicis brevis muscle. Cortical thickness analyses based on structural MRI suggested changes in the right precentral gyrus, right post central gyrus, right dorsolateral prefrontal cortex, and potentially the right supplementary motor area. Such findings are consistent with LTP-like neuroplastic changes in areas that were already responsible for finger sequence execution, rather than improved recruitment of previously nonutilized tissue. Hum Brain Mapp 38:4773-4787, 2017. © 2017 Wiley Periodicals, Inc.

Measuring neuroplasticity associated with cerebral palsy rehabilitation: An MRI based power analysis.

Researchers in the field of child neurology are increasingly looking to supplement clinical trials of motor rehabilitation with neuroimaging in order to better understand the relationship between behavioural training, brain changes, and clinical improvements. Randomised controlled trials are typically accompanied by sample size calculations to detect clinical improvements but, despite the large cost of neuroimaging, not equivalent calculations for concurrently acquired imaging neuroimaging measures of changes in response to intervention. To aid in this regard, a power analysis was conducted for two measures of brain changes that may be indexed in a trial of rehabilitative therapy for cerebral palsy: cortical thickness of the impaired primary sensorimotor cortex, and fractional anisotropy of the impaired, delineated corticospinal tract. Power for measuring fractional anisotropy was assessed for both region-of-interest-seeded and fMRI-seeded diffusion tractography. Taking into account practical limitations, as well as data loss due to behavioural and image-processing issues, estimated required participant numbers were 101, 128 and 59 for cortical thickness, region-of-interest-based tractography, and fMRI-seeded tractography, respectively. These numbers are not adjusted for study attrition. Although these participant numbers may be out of reach of many trials, several options are available to improve statistical power, including careful preparation of participants for scanning using mock simulators, careful consideration of image processing options, and enrolment of as homogeneous a cohort as possible. This work suggests that smaller and moderate sized studies give genuine consideration to harmonising scanning protocols between groups to allow the pooling of data.

Neuroanatomical correlates of childhood apraxia of speech: A connectomic approach.

Childhood apraxia of speech (CAS) is a paediatric speech sound disorder in which precision and consistency of speech movements are impaired. Most children with idiopathic CAS have normal structural brain MRI. We hypothesize that children with CAS have altered structural connectivity in speech/language networks compared to controls and that these altered connections are related to functional speech/language measures. Whole brain probabilistic tractography, using constrained spherical deconvolution, was performed for connectome generation in 17 children with CAS and 10 age-matched controls. Fractional anisotropy (FA) was used as a measure of connectivity and the connections with altered FA between CAS and controls were identified. Further, the relationship between altered FA and speech/language scores was determined. Three intra-hemispheric/interhemispheric subnetworks showed reduction of FA in CAS compared to controls, including left inferior (opercular part) and superior (dorsolateral, medial and orbital part) frontal gyrus, left superior and middle temporal gyrus and left post-central gyrus (subnetwork 1); right supplementary motor area, left middle and inferior (orbital part) frontal gyrus, left precuneus and cuneus, right superior occipital gyrus and right cerebellum (subnetwork 2); right angular gyrus, right superior temporal gyrus and right inferior occipital gyrus (subnetwork 3). Reduced FA of some connections correlated with diadochokinesis, oromotor skills, expressive grammar and poor lexical production in CAS. These findings provide evidence of structural connectivity anomalies in children with CAS across specific brain regions involved in speech/language function. We propose altered connectivity as a possible epiphenomenon of complex pathogenic mechanisms in CAS which need further investigation.

Correction: Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy.

[This corrects the article DOI: 10.1371/journal.pone.0159540.].

PREMM: preterm early massage by the mother: protocol of a randomised controlled trial of massage therapy in very preterm infants.

BACKGROUND: Preterm infants follow an altered neurodevelopmental trajectory compared to their term born peers as a result of the influence of early birth, and the altered environment. Infant massage in the preterm infant has shown positive effects on weight gain and reduced length of hospital stay. There is however, limited current evidence of improved neurodevelopment or improved attachment, maternal mood or anxiety. The aim of this study is to investigate the effects of infant massage performed by the mother in very preterm (VPT) infants. Effects on the infant will be assessed at the electrophysiological, neuroradiological and clinical levels.  Effects on maternal mood, anxiety and mother-infant attachment will also be measured. METHODS/DESIGN: A randomised controlled trial to investigate the effect of massage therapy in VPT infants. Sixty VPT infants, born at 28 to 32 weeks and 6 days gestational age, who are stable, off supplemental oxygen therapy and have normal cranial ultrasounds will be recruited and randomised to an intervention (infant massage) group or a control (standard care) group. Ten healthy term born infants will be recruited as a reference comparison group. The intervention group will receive standardised massage therapy administered by the mother from recruitment, until term equivalent age (TEA). The control group will receive care as usual (CAU). Infants and their mothers will be assessed at baseline, TEA, 12 months and 24 months corrected age (CA), with a battery of clinical, neuroimaging and electrophysiological measures, as well as structured questionnaires, psychoanalytic observations and neurodevelopmental assessments. DISCUSSION: Optimising preterm infant neurodevelopment is a key aim of neonatal research, which could substantially improve long-term outcomes and reduce the socio-economic impact of VPT birth. This study has the potential to give insights into the mother-baby relationship and any positive effects of infant massage on neurodevelopment. An early intervention such as massage that is relatively easy to administer and could alter the trajectory of preterm infant brain development, holds potential to improve neurodevelopmental outcomes in this vulnerable population. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12612000335897 . Date registered: 22/3/2012.

Surface-Based fMRI-Driven Diffusion Tractography in the Presence of Significant Brain Pathology: A Study Linking Structure and Function in Cerebral Palsy.

Diffusion MRI (dMRI) tractography analyses are difficult to perform in the presence of brain pathology. Automated methods that rely on cortical parcellation for structural connectivity studies often fail, while manually defining regions is extremely time consuming and can introduce human error. Both methods also make assumptions about structure-function relationships that may not hold after cortical reorganisation. Seeding tractography with functional-MRI (fMRI) activation is an emerging method that reduces these confounds, but inherent smoothing of fMRI signal may result in the inclusion of irrelevant pathways. This paper describes a novel fMRI-seeded dMRI-analysis pipeline based on surface-meshes that reduces these issues and utilises machine-learning to generate task specific white matter pathways, minimising the requirement for manually-drawn ROIs. We directly compared this new strategy to a standard voxelwise fMRI-dMRI approach, by investigating correlations between clinical scores and dMRI metrics of thalamocortical and corticomotor tracts in 31 children with unilateral cerebral palsy. The surface-based approach successfully processed more participants (87%) than the voxel-based approach (65%), and provided significantly more-coherent tractography. Significant correlations between dMRI metrics and five clinical scores of function were found for the more superior regions of these tracts. These significant correlations were stronger and more frequently found with the surface-based method (15/20 investigated were significant; R2 = 0.43-0.73) than the voxelwise analysis (2 sig. correlations; 0.38 & 0.49). More restricted fMRI signal, better-constrained tractography, and the novel track-classification method all appeared to contribute toward these differences.