The authors would like to make the following correction to the published paper [...]

Background and ObjectivesHealth-related quality of life (HR-QoL) is compromised in patients with neuromuscular disorders (NMDs). Disease severity alone does not predict HR-QoL; there are other known predictors including physical, psychological, and social factors. This study aims to provide insight into how mobility, age, and diagnosis may affect HR-QoL in adults with NMD. MethodsThe QoL in Genetic Neuromuscular Disease Questionnaire (QoL-gNMD) was completed by adult patients with NMDs before attending a clinical visit at the John Walton Muscular Dystrophy Research Centre in Newcastle upon Tyne, UK. The Summary of Function Scale was administered during the clinical visit to characterize mobility status. ResultsA total of 580 responses were included in this cross-sectional study. Overall perceived health and HR-QoL were reported poorest by ambulant patients who walked using aids. Items from the QoL-gNMD that were affected the most by NMDs were future planning and the need to rely more on others. A nonlinear trend where patients with "midlevel" mobility (walked with aids or manual wheelchair users) reported the poorest HR-QoL were observed in all 3 HR-QoL domains: Impact of Physical Symptoms (IPSs), Self-Perception (SP), and Activities and Social Participation (ASP). This nonlinear trend between HR-QoL and mobility was observed for younger patients but became more linear in older age groups. In our cohort, patients with "midlevel" mobility were the oldest, and those with the lowest levels of mobility (i.e., powered wheelchair users) were the youngest. Interaction between age and mobility was significant and both affected HR-QoL. There was marked variability in HR-QoL between diagnoses. Diagnosis was a significant factor for IPS (p < 0.01) and SP (p = 0.04) but not for ASP (p = 0.17). DiscussionAge and mobility status affect HR-QoL. Individuals with limited ambulation reported the poorest HR-QoL, which was partially restored in powered wheelchair users, to levels comparable with more ambulant patients. However, the positive effect of wheelchair use became less substantial as patients get older. There was also marked variability in HR-QoL between diagnoses that was unrelated to physical disability. These findings provide evidence to guide care management discussions and highlight the importance of timely introduction of powered mobility.

Liver health issues in X-linked myotubular myopathy and centronuclear myopathies have historically been under-recognized, with liver monitoring not a routine focus of clinical care. Anecdotal case reports and liver-related adverse events in recent clinical trials highlight the growing need to better understand liver involvement in this population. A patient-led initiative brought together a multi-stakeholder expert working group, the 'Myotubular and Centronuclear Myopathy Global Liver Collaborative' who developed a liver health questionnaire to collect longitudinal patient-reported liver health data. Data from 219 participants was analysed and liver abnormalities were found to be most prevalent in myotubular myopathy patients with 36 % of affected males having abnormal liver function tests with liver issues also reported by symptomatic female carriers. Patients with liver abnormalities were also more likely to require invasive ventilation and had poorer motor function, suggesting a link between liver health and overall disease severity. Significant variation in liver monitoring was observed, with 30 % of participants never having undergone liver function blood tests demonstrating the need for routine liver screening to inform standards of care and guide clinical management. The patient-driven Liver Collaborative has been instrumental in raising awareness in liver related issues with clinical and patient communities.

To meet the growing need for strong clinical evidence on a global scale, both publicand private sectors have invested to standardise health data elements and achievegreater connectivity and interoperability of health data systems. This is enabled byFAIRification (making Findable, Accessible, Interoperable, and Reusable) of clinicaltrial data increasingly recognised as a crucial step in enhancing the value and utility ofclinical data across the research community. This is even more relevant in thepaediatric and rare disease field where data remains highly fragmented in terms ofdata collection practices, ontologies, and clinical reporting standards, and often lockedin silos with diverse formats and standards.

BackgroundPediatric clinical research, especially in rare diseases, faces persistent challenges including the identification and recruitment of eligible patients, assessing protocol feasibility, and ensuring efficient trial execution. These issues are compounded by small, age-stratified populations and fragmented clinical data. Real-world data (RWD), especially when drawn from electronic health records (EHRs), present an opportunity to support innovative trial designs, such as real-world comparator arms and postmarketing surveillance. However, realizing this potential depends on the routine availability of structured, reusable clinical data. ObjectiveThis proof-of-concept study aimed to assess the availability and structure of routine clinical data in European pediatric hospitals, focusing on data elements relevant for use in comparator arms and postmarketing surveillance studies. The study focused on 2 disease areas—neurofibromatosis (NF) and atopic dermatitis (AD)—as examples of rare and common conditions in children, respectively. MethodsAn inventory of 113 high-value clinical data items was developed based on expert analysis of clinical protocols for NF, AD, and safety studies. These items were included in a structured web-based survey disseminated through the connect4children (c4c) National Hub network, reaching sites across. Europe. Respondents were asked to indicate how each data item is collected and stored: in structured/coded EHR fields, as free text, in external systems, or on paper. ResultsSurvey responses from 24 hospitals across 11 European countries revealed considerable variability in how data are captured and stored. While many general clinical and drug safety data elements—such as demographics, vital signs, and medication use—were often collected in structured formats, disease-specific and contextual variables were frequently captured as free text or not documented in a standardized way. For example, structured data capture was more prevalent for basic demographic and safety-related variables, whereas only a minority of sites recorded key disease-specific clinical details in a structured form. Lifestyle and family history data were among the least consistently documented. These gaps in structured data entry reduce the immediate reusability of EHR data for secondary research purposes. ConclusionsThis study highlights gaps in the structured documentation of pediatric clinical data across European sites. While the routine collection of many variables is promising, the lack of structured and coded formats poses a barrier to reusing these data for observational studies or comparator arms. As a first step toward the broader integration of RWD into pediatric research, this study demonstrates the feasibility of assessing EHR data availability and sets the stage for future scaling across more diseases and sites.

OBJECTIVES:Determine the utility of low-flip angle "black bone" magnetic resonance imaging (MRI) for cortical mandibular bone assessment compared to computed tomography (CT). METHODS:Quantification of cortical mandibular bone width was performed per Hamada et al. at 15 cross-sectional interdentium locations on pretreatment black bone MRI and CT for 15 oropharyngeal cancer patients, with interobserver analyses on a subset of three patients by 11 observers. CT and MRI measurements were compared using Bland-Altman analysis, Lin's concordance, and Deming regression; interobserver variability was assessed with absolute variance and intraclass correlation coefficient (ICC). RESULTS:Bland Altman and Deming regression analyses showed CT and black bone MRI measurements were comparable within ±0.85mm limits of agreement, and systematically smaller for MRI. ICC (0.60[0.52;0.67]) showed moderate equivalence between modalities. The average absolute variance between the observers was similar on CT (1.13±0.06mm) and MRI (1.15±0.06mm). ICC analysis showed that measurement consistency was significantly higher (p<0.001) for black bone MRI (0.43[0.32;0.56]) than CT (0.22[0.13;0.35]); nonetheless, ICC was poor for both modalities. CONCLUSION:Black bone MRI is a viable alternative to CT for assessing mandibular cortical bone and early detection of anatomical changes like osteoradionecrosis. Both modalities showed similar interobserver variability, which may be reduced through (semi)automated measurement.

The conect4children (c4c) initiative was established to facilitate the development of new drugs and other therapies for paediatric patients. It is widely recognised that there are not enough medicines tested for all relevant ages of the paediatric population. To overcome this, it is imperative that clinical data from different sources are interoperable and can be pooled for larger post hoc studies. c4c has collaborated with the Clinical Data Interchange Standards Consortium (CDISC) to develop cross-cutting data resources that build on existing CDISC standards in an effort to standardise paediatric data. The natural next step was an extension to disease-specific data items. c4c brought together several existing initiatives and resources relevant to disease-specific data and analysed their use for standardising disease-specific data in clinical trials. Several case studies that combined disease-specific data from multiple trials have demonstrated the need for disease-specific data standardisation. We identified three relevant initiatives. These include European Reference Networks, European Joint Programme on Rare Diseases, and Pistoia Alliance. Other resources reviewed were National Cancer Institute Enterprise Vocabulary Services, CDISC standards, pharmaceutical company-specific data dictionaries, Human Phenotype Ontology, Phenopackets, Unified Registry for Inherited Metabolic Disorders, Orphacodes, Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP), and Observational Medical Outcomes Partnership. The collaborative partners associated with these resources were also reviewed briefly. A plan of action focussed on collaboration was generated for standardising disease-specific paediatric clinical trial data. A paediatric data standards multistakeholder and multi-project user group was established to guide the remaining actions—FAIRification of metadata, a Phenopackets pilot with RDCA-DAP, applying Orphacodes to case report forms of clinical trials, introducing CDISC standards into European Reference Networks, testing of the CDISC Pediatric User Guide using data from the mentioned resources and organisation of further workshops and educational materials.

Introduction The conect4children (c4c) project aims to facilitate efficient planning and delivery of paediatric clinical trials. One objective of c4c is data standardization and reuse. Interoperability and reusability of paediatric clinical trial data is challenging due to a lack of standardization. The Clinical Data Interchange Standards Consortium (CDISC) standards that are required or recommended for regulatory submissions in several countries lack paediatric specificity with limited awareness within academic institutions. To address this, c4c and CDISC collaborated to develop the Pediatrics User Guide (PUG) consisting of cross-cutting data items that are routinely collected in paediatric clinical trials, factoring in all paediatric age ranges.Methods and Results The development of the PUG consisted of six stages. During the scoping phase, subtopics (each containing several clinically relevant concepts) were suggested and debated for inclusion in the PUG. Ninety concepts were selected for the modelling phase. Concept maps describing the Research Topic and representation procedure were developed for the 19 concepts that had no (or partial) previous modelling in CDISC. Next, metadata and implementation examples were developed for concepts. This was followed by a CDISC internal review and a public review. For both these review stages, the feedback comments were either implemented or rejected based on budget, timelines, expert review, and scope. The PUG was published on the CDISC website on February 23, 2023.Discussion The PUG is a first step in bridging the lack of child specific CDISC standards, particularly within academia. Several academic and industrial partners were involved in the development of the PUG, and c4c has undertaken multiple steps to publicize the PUG within its academic partner organizations - in particular, the European Reference Networks (ERNs) that are developing registries and dictionaries in 24 disease areas. In the long term, continued use of the PUG in paediatric clinical trials will enable the pooling of data from multiple trials, which is particularly important for medical domains with small populations.

The reuse of paediatric individual patient data (IPD) from clinical trials (CTs) is essential to overcome specific ethical, regulatory, methodological, and economic issues that hinder the progress of paediatric research. Sharing data through repositories enables the aggregation and dissemination of clinical information, fosters collaboration between researchers, and promotes transparency. This work aims to identify and describe existing data-sharing repositories (DSRs) developed to store, share, and reuse paediatric IPD from CTs. A rapid review of platforms providing access to electronic DSRs was conducted. A two-stage process was used to characterize DSRs: a first step of identification, followed by a second step of analysis using a set of eight purpose-built indicators. From an initial set of forty-five publicly available DSRs, twenty-one DSRs were identified as meeting the eligibility criteria. Only two DSRs were found to be totally focused on the paediatric population. Despite an increased awareness of the importance of data sharing, the results of this study show that paediatrics remains an area in which targeted efforts are still needed. Promoting initiatives to raise awareness of these DSRs and creating ad hoc measures and common standards for the sharing of paediatric CT data could help to bridge this gap in paediatric research.

There has been immense progress in medical image analysis over the past decade [...]

Over the past 50 years, the advancements in medical and health research have radically changed the epidemiology of health conditions in neonates, children, and adolescents; and clinical research has on the whole, moved forward. However, large sections of the pediatric community remain vulnerable and underserved, by clinical research. One reason for this is the fact that most pediatric diseases are also rare diseases (i.e., they fit the EU definition of a rare condition, by affecting no more than 5 in 10,000 individuals), and indeed the majority of conditions under this umbrella heading are in fact much rarer, affecting fewer than 1 in 100,000. Rare pediatric diseases incur particular challenges, both in terms of actually conducting clinical trials but also planning trials (and indeed, stimulating the preclinical research and knowledge generation necessary to embark on clinical trials in the first place). The pediatric regulation and orphan regulation (covering rare diseases) were introduced to address the complexities in research and development of medicines specifically for children and for people living with a rare disease, respectively. The regulations have been reasonably effective, particularly in areas where adult and pediatric diseases overlap, driving the development of more pediatric medicines; however, challenges still remain, often exacerbated by the rarity of the diseases. These include issues around trial planning, the need for more innovative methodologies in smaller populations, significant delays in trial start up and recruitment, recruitment issues (due to small populations and the nature of the conditions), lack of endpoints, and scarce data. This chapter will discuss some of the major challenges in delivering trials in pediatric rare diseases while also assessing current and future solutions to address these.

The Myotubular and Centronuclear Myopathy Registry is an international research database containing key longitudinal data on a diverse and growing cohort of individuals affected by this group of rare and ultra-rare neuromuscular conditions. It can inform and support all areas of translational research including epidemiological and natural history studies, clinical trial feasibility planning, recruitment for clinical trials or other research studies, stand-alone clinical studies, standards of care development, and provision of real-world evidence data. For ten years, it has also served as a valuable communications tool and provided a link between the scientific and patient communities. With the anticipated advent of disease-modifying therapies for these conditions, the registry is a key resource for the generation of post-authorisation data for regulatory decision-making, real world evidence, and patient-reported outcome measures. In this paper we present some key data from the current 444 registered individuals with the following genotype split: MTM1 n=270, DNM2 n=42, BIN1 n=4, TTN n=4, RYR1 n=12, other n=4, unknown n=108. The data presented are consistent with the current literature and the common understanding of a strong genotype/phenotype correlations in CNM, most notably the data supports the current knowledge that XLMTM is typically the most severe form of CNM. Additionally, we outline the ways in which the registry supports research, and, more generally, the importance of continuous investment and development to maintain the relevance of registries for all stakeholders. Further information on the registry and contact details are available on the registry website at www.mtmcnmregistry.org.

Standardization of data items collected in paediatric clinical trials is an important but challenging issue. The Clinical Data Interchange Standards Consortium (CDISC) data standards are well understood by the pharmaceutical industry but lack the implementation of some paediatric specific concepts. When a paediatric concept is absent within CDISC standards, companies and research institutions take multiple approaches in the collection of paediatric data, leading to different implementations of standards and potentially limited utility for reuse. To overcome these challenges, the conect4children consortium has developed a cross-cutting paediatric data dictionary (CCPDD). The dictionary was built over three phases - scoping (including a survey sent out to ten industrial and 34 academic partners to gauge interest), creation of a longlist and consensus building for the final set of terms. The dictionary was finalized during a workshop with attendees from academia, hospitals, industry and CDISC. The attendees held detailed discussions on each data item and participated in the final vote on the inclusion of the item in the CCPDD. Nine industrial and 34 academic partners responded to the survey, which showed overall interest in the development of the CCPDD. Following the final vote on 27 data items, three were rejected, six were deferred to the next version and a final opinion was sought from CDISC. The first version of the CCPDD with 25 data items was released in August 2019. The continued use of the dictionary has the potential to ensure the collection of standardized data that is interoperable and can later be pooled and reused for other applications. The dictionary is already being used for case report form creation in three clinical trials. The CCPDD will also serve as one of the inputs to the Paediatric User Guide, which is being developed by CDISC.

Data dictionaries for clinical trials are often created manually, with data structures and controlled vocabularies specific for a trial or family of trials within a sponsor’s portfolio. Microsoft Excel is commonly used to capture the representation of data dictionary items but has limited functionality for this purpose. The conect4children (c4c) network is piloting the Direcht clinical data modelling tool to model their Cross Cutting Paediatric Data Dictionary (CCPDD) in a more formalised way. The first pilot had the key objective of testing whether a clinical data modelling tool could be used to represent data items from the CCPDD. The key objective of the second pilot is to establish whether a small team with little or no experience of clinical data modelling can use Direcht to expand the CCPDD. Clinical modelling is the process of structuring clinical data so it can be understood by computer systems and humans. The model contains all of the elements that are needed to define the data item. Results from the pilots show that Direcht creates a structured environment to build data items into models that fit into the larger CCPDD. Models can be represented as an HTML document, mind map, or exported in various formats for import into a computer system. Challenges identified over the course of both pilots are being addressed with c4c partners and external stakeholders.

INTRODUCTION The conect4children (c4c) consortium was setup to facilitate the development of new drugs and therapies for paediatric populations and address key challenges associated with paediatric clinical trials. Two of the major adopting principles for c4c were academia-industry partnership and data harmonisation and interoperability through common eCRF definitions. To understand the challenges arising out of these principles, the c4c team at Newcastle University conducted semi-structured interviews with four c4c industry partners. METHODS Each partner was asked 10 questions about the data standards used in their company, management and maintenance of data dictionaries, how they dealt with paediatric-specific issues, major knowledge gaps and how academia could aid in bridging these gaps. Thematic analysis was performed to identify patterns in their answers. RESULTS All companies use the Clinical Data Interchange Standards Consortium (CDISC) standards but face problems when certain terminology is not included in CDISC (e.g., paediatric-specific terminologies). All companies were committed to interoperability and had strict policies about how additional terminology could be added to their dictionaries. Three of the four companies maintained a single dictionary but also had lighter versions for specific usage. The two major knowledge gaps identified from the interviews were handling of non-CDISC terminology and maintenance of normal lab ranges in dictionaries. DISCUSSION To address these gaps, c4c has been working on a four-point plan including the development of a cross-cutting paediatric dictionary and a paediatric user guide in collaboration with CDISC.

Histopathology is the accepted gold standard for identifying cancerous tissues. Validation of in vivo imaging signals with precisely correlated histopathology can potentially improve the delineation of tumors in medical images for focal therapy planning, guidance, and assessment. Registration of histopathology with other imaging modalities is challenging due to soft tissue deformations that occur between imaging and histological processing of tissue. In this paper, a framework for precise registration of medical images and pathology using white-light images (photographs) is presented. A euthanized normal mouse was imaged using four imaging modalities: CBCT, PET-CT, MRI and micro CT. The mouse was then fixed in an embedding medium, optical cutting temperature (OCT) compound, with co-registration markers and sliced at 50 m intervals in a cryostatmicrotome. The device automatically photographed each slice with a mounted camera and reconstructed the 3D white-light image of the mouse through co-registering of consecutive slices. The white-light image was registered to the four imaging modalities based on the external contours of the mouse. Six organs (brain, liver, stomach, pancreas, kidneys and bladder) were contoured on the MR image while the skeletal structure and lungs were segmented on the CBCT image. The contours of these structures were propagated to the additional imaging modalities based on the registrations to the white-light image and were analyzed qualitatively by developing an anatomical atlas of normal mouse defined using three imaging modalities. This work will serve as the foundation to include histopathology through the transfer of the imaged slice onto tape for histological processing.

Purpose Precise correlation between three-dimensional (3D) imaging and histology can aid biomechanical modeling of the breast. We develop a framework to register ex vivo images to histology using a novel cryo-fluorescence tomography (CFT) device. Methods A formalin-fixed cadaveric breast specimen, including chest wall, was subjected to high-resolution magnetic resonance (MR) imaging. The specimen was then frozen and embedded in an optimal cutting temperature (OCT) compound. The OCT block was placed in a CFT device with an overhead camera and 50 mu m thick slices were successively shaved off the block. After each shaving, the block-face was photographed. At select locations including connective/adipose tissue, muscle, skin, and fibroglandular tissue, 20 mu m sections were transferred onto cryogenic tape for manual hematoxylin and eosin staining, histological assessment, and image capture. A 3D white-light image was automatically reconstructed from the photographs by aligning fiducial markers embedded in the OCT block. The 3D MR image, 3D white-light image, and photomicrographs were rigidly registered. Target registration errors (TREs) were computed based on 10 pairs of points marked at fibroglandular intersections. The overall MR-histology registration was used to compare the MR intensities at tissue extraction sites with a one-way analysis of variance. Results The MR image to CFT-captured white-light image registration achieved a mean TRE of 0.73 +/- 0.25 mm (less than the 1 mm MR slice resolution). The block-face white-light image and block-face photomicrograph registration showed visually indistinguishable alignment of anatomical structures and tissue boundaries. The MR intensities at the four tissue sites identified from histology differed significantly (p < 0.01). Each tissue pair, except the skin-connective/adipose tissue pair, also had significantly different MR intensities (p < 0.01). Conclusions Fine sectioning in a highly controlled imaging/sectioning environment enables accurate registration between the MR image and histology. Statistically significant differences in MR signal intensities between histological tissues are indicators for the specificity of correlation between MRI and histology.

Brain-shift during neurosurgery compromises the accuracy of tracking the boundaries of the tumor to be resected. Although several studies have used various finite element models (FEMs) to predict inward brain-shift, evaluation of their accuracy and efficiency based on public benchmark data has been limited. This study evaluates several FEMs proposed in the literature (various boundary conditions, mesh sizes, and material properties) by using intraoperative imaging data (the public REtroSpective Evaluation of Cerebral Tumors [RESECT] database). Four patients with low-grade gliomas were identified as having inward brain-shifts. We computed the accuracy (using target registration error) of several FEM-based brain-shift predictions and compared our findings. Since information on head orientation during craniotomy is not included in this database, we tested various plausible angles of head rotation. We analyzed the effects of brain tissue viscoelastic properties, mesh size, craniotomy position, CSF drainage level, and rigidity of meninges and then quantitatively evaluated the trade-off between accuracy and central processing unit time in predicting inward brain-shift across all models with second-order tetrahedral FEMs. The mean initial target registration error (TRE) was 5.78 ± 3.78 mm with rigid registration. FEM prediction (edge-length, 5 mm) with non-rigid meninges led to a mean TRE correction of 1.84 ± 0.83 mm assuming heterogeneous material. Results show that, for the low-grade glioma patients in the study, including non-rigid modeling of the meninges was significant statistically. In contrast including heterogeneity was not significant. To estimate the optimal head orientation and CSF drainage, an angle step of 5° and an CSF height step of 5 mm were enough leading to <0.26 mm TRE fluctuation.