Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation.

Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm, and its incidence has doubled over the past two decades owing to increasing risk factors. Despite surveillance, most HCC cases are diagnosed at advanced stages and can only be treated using transarterial chemo-embolization (TACE) or systemic therapy. TACE failure may occur with incidence reaching up to 60% of cases, leaving patients with a financial and emotional burden. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from pre-procedural computed tomography (CT) studies. This data report defines the HCC-TACE data collection of confirmed HCC patients who underwent TACE and have pre- and post-procedure CT imaging studies and available treatment outcomes (time-to-progression and overall survival). Clinically curated segmentation of pre-procedural CT studies was done for the purpose of algorithm training for prediction and automatic liver tumor segmentation.

The Exceptional Responders Initiative: Feasibility of a National Cancer Institute Pilot Study.

BACKGROUND: Tumor molecular profiling from patients experiencing exceptional responses to systemic therapy may provide insights into cancer biology and improve treatment tailoring. This pilot study evaluates the feasibility of identifying exceptional responders retrospectively, obtaining pre-exceptional response treatment tumor tissues, and analyzing them with state-of-the-art molecular analysis tools to identify potential molecular explanations for responses. METHODS: Exceptional response was defined as partial (PR) or complete (CR) response to a systemic treatment with population PR or CR rate less than 10% or an unusually long response (eg, duration >3 times published median). Cases proposed by patients' clinicians were reviewed by clinical and translational experts. Tumor and normal tissue (if possible) were profiled with whole exome sequencing and, if possible, targeted deep sequencing, RNA sequencing, methylation arrays, and immunohistochemistry. Potential germline mutations were tracked for relevance to disease. RESULTS: Cases reflected a variety of tumors and standard and investigational treatments. Of 520 cases, 476 (91.5%) were accepted for further review, and 222 of 476 (46.6%) proposed cases met requirements as exceptional responders. Clinical data were obtained from 168 of 222 cases (75.7%). Tumor was provided from 130 of 168 cases (77.4%). Of 117 of the 130 (90.0%) cases with sufficient nucleic acids, 109 (93.2%) were successfully analyzed; 6 patients had potentially actionable germline mutations. CONCLUSION: Exceptional responses occur with standard and investigational treatment. Retrospective identification of exceptional responders, accessioning, and sequencing of pretreatment archived tissue is feasible. Data from molecular analyses of tumors, particularly when combining results from patients who received similar treatments, may elucidate molecular bases for exceptional responses.

Semantic Integration of Multi-Modal Data and Derived Neuroimaging Results Using the Platform for Imaging in Precision Medicine (PRISM) in the Arkansas Imaging Enterprise System (ARIES).

Neuroimaging is among the most active research domains for the creation and management of open-access data repositories. Notably lacking from most data repositories are integrated capabilities for semantic representation. The Arkansas Imaging Enterprise System (ARIES) is a research data management system which features integrated capabilities to support semantic representations of multi-modal data from disparate sources (imaging, behavioral, or cognitive assessments), across common image-processing stages (preprocessing steps, segmentation schemes, analytic pipelines), as well as derived results (publishable findings). These unique capabilities ensure greater reproducibility of scientific findings across large-scale research projects. The current investigation was conducted with three collaborating teams who are using ARIES in a project focusing on neurodegeneration. Datasets included magnetic resonance imaging (MRI) data as well as non-imaging data obtained from a variety of assessments designed to measure neurocognitive functions (performance scores on neuropsychological tests). We integrate and manage these data with semantic representations based on axiomatically rich biomedical ontologies. These instantiate a knowledge graph that combines the data from the study cohorts into a shared semantic representation that explicitly accounts for relations among the entities that the data are about. This knowledge graph is stored in a triple-store database that supports reasoning over and querying these integrated data. Semantic integration of the non-imaging data using background information encoded in biomedical domain ontologies has served as a key feature-engineering step, allowing us to combine disparate data and apply analyses to explore associations, for instance, between hippocampal volumes and measures of cognitive functions derived from various assessment instruments.

Molecular Features of Cancers Exhibiting Exceptional Responses to Treatment.

A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories-DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis-with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.

Chest imaging representing a COVID-19 positive rural U.S. population.

As the COVID-19 pandemic unfolds, radiology imaging is playing an increasingly vital role in determining therapeutic options, patient management, and research directions. Publicly available data are essential to drive new research into disease etiology, early detection, and response to therapy. In response to the COVID-19 crisis, the National Cancer Institute (NCI) has extended the Cancer Imaging Archive (TCIA) to include COVID-19 related images. Rural populations are one population at risk for underrepresentation in such public repositories. We have published in TCIA a collection of radiographic and CT imaging studies for patients who tested positive for COVID-19 in the state of Arkansas. A set of clinical data describes each patient including demographics, comorbidities, selected lab data and key radiology findings. These data are cross-linked to SARS-COV-2 cDNA sequence data extracted from clinical isolates from the same population, uploaded to the GenBank repository. We believe this collection will help to address population imbalance in COVID-19 data by providing samples from this normally underrepresented population.

Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data.

The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.

Author Correction: Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy.

In the original version of the Data Descriptor the surname of author Hesham Elhalawani was misspelled. This has now been corrected in the HTML and PDF versions.

Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy.

Cross sectional imaging is essential for the patient-specific planning and delivery of radiotherapy, a primary determinant of head and neck cancer outcomes. Due to challenges ensuring data quality and patient de-identification, publicly available datasets including diagnostic and radiation treatment planning imaging are scarce. In this data descriptor, we detail the collection and processing of computed tomography based imaging in 215 patients with head and neck squamous cell carcinoma that were treated with radiotherapy. Using cross sectional imaging, we calculated total body skeletal muscle and adipose content before and after treatment. We detail techniques for validating the high quality of these data and describe the processes of data de-identification and transfer. All imaging data are subject- and date-matched to clinical data from each patient, including demographics, risk factors, grade, stage, recurrence, and survival. These data are a valuable resource for studying the association between patient-specific anatomic and metabolic features, treatment planning, and oncologic outcomes, and the first that allows for the integration of body composition as a risk factor or study outcome.

Reengineering Workflow for Curation of DICOM Datasets.

Reusable, publicly available data is a pillar of open science and rapid advancement of cancer imaging research. Sharing data from completed research studies not only saves research dollars required to collect data, but also helps insure that studies are both replicable and reproducible. The Cancer Imaging Archive (TCIA) is a global shared repository for imaging data related to cancer. Insuring the consistency, scientific utility, and anonymity of data stored in TCIA is of utmost importance. As the rate of submission to TCIA has been increasing, both in volume and complexity of DICOM objects stored, the process of curation of collections has become a bottleneck in acquisition of data. In order to increase the rate of curation of image sets, improve the quality of the curation, and better track the provenance of changes made to submitted DICOM image sets, a custom set of tools was developed, using novel methods for the analysis of DICOM data sets. These tools are written in the programming language perl, use the open-source database PostgreSQL, make use of the perl DICOM routines in the open-source package Posda, and incorporate DICOM diagnostic tools from other open-source packages, such as dicom3tools. These tools are referred to as the "Posda Tools." The Posda Tools are open source and available via git at https://github.com/UAMS-DBMI/PosdaTools . In this paper, we briefly describe the Posda Tools and discuss the novel methods employed by these tools to facilitate rapid analysis of DICOM data, including the following: (1) use a database schema which is more permissive, and differently normalized from traditional DICOM databases; (2) perform integrity checks automatically on a bulk basis; (3) apply revisions to DICOM datasets on an bulk basis, either through a web-based interface or via command line executable perl scripts; (4) all such edits are tracked in a revision tracker and may be rolled back; (5) a UI is provided to inspect the results of such edits, to verify that they are what was intended; (6) identification of DICOM Studies, Series, and SOP instances using "nicknames" which are persistent and have well-defined scope to make expression of reported DICOM errors easier to manage; and (7) rapidly identify potential duplicate DICOM datasets by pixel data is provided; this can be used, e.g., to identify submission subjects which may relate to the same individual, without identifying the individual.

The public cancer radiology imaging collections of The Cancer Imaging Archive.

The Cancer Imaging Archive (TCIA) is the U.S. National Cancer Institute's repository for cancer imaging and related information. TCIA contains 30.9 million radiology images representing data collected from approximately 37,568 subjects. This data is organized into collections by tumor-type with many collections also including analytic results or clinical data. TCIA staff carefully de-identify and curate all incoming collections prior to making the information available via web browser or programmatic interfaces. Each published collection within TCIA is assigned a Digital Object Identifier that references the collection. Additionally, researchers who use TCIA data may publish the subset of information used in their analysis by requesting a TCIA generated Digital Object Identifier. This data descriptor is a review of a selected subset of existing publicly available TCIA collections. It outlines the curation and publication methods employed by TCIA and makes available 15 collections of cancer imaging data.

Using a Checklist to Improve Family Communication in Trauma Care.

Modern concepts of patient-centered care emphasize effective communication with patients and families, an essential requirement in acute trauma settings. We hypothesized that using a checklist to guide the initial family conversation would improve the family's perception of the interaction. Institutional Review Board-approved, prospective pre/post study involving families of trauma patients admitted to our Level I trauma center for >24 hours. In the control group, families received information according to existing practices. In the study group, residents gave patient information to a first-degree family member using a checklist that guided the interaction. The checklist included a physician introduction, patient condition, list of known injuries, admission unit or intensive care unit, any consultants involved, plans for additional studies or operations, and opportunity for family to ask questions. An 11-item survey was administered 24 to 48 hours after admission to each group that evaluated the trauma team's communication in the areas of physician introduction, patient condition, ongoing treatment, and family perception of the interaction. Responses were on a Likert scale and analyzed using the Wilcoxon-Mann-Whitney test. There were 130 patients in each group. The study group had significantly (P < 0.05) better responses in 8 of 11 items surveyed: physician spoke to family, physician introduction, understanding of their relative's injuries, admitting unit, consultants involved, urgent surgical procedures required, ongoing diagnostic studies, and understanding of the treatment plan. In conclusion, using a checklist improves the perception of the initial communication between the trauma team and family members of trauma patients, especially their understanding of the treatment plan.

Quality and extent of locum tenens coverage in pediatric surgical practices.

The prevalence and quality of locum tenens coverage in pediatric surgery have not been determined. An Internet-based survey of American Pediatric Surgical Association members was conducted: 1) practice description; 2) use and frequency of locum tenens coverage; 4) whether the surgeon provided such coverage; and 5) Likert scale responses (strongly disagree, disagree, neutral, agree, strongly agree) to statements addressing its acceptability and quality (two × five contingency table and χ(2) analyses, significance at P < 0.05). Three hundred sixteen of 1163 members (27.2% response rate) responded. One-fourth (24.1%) used a locum tenens regularly. Reasons were long-term inability to recruit a full-time surgeon (35.2%) and short-term vacancies (32.4%). One-fifth (20.4%) did locum tenens work; one-fourth (27.0%) plan to do so in the future. Two-thirds (64.2%) believe that surgical care in a locum tenens situation does not provide the same level of care as a full-time community-based surgeon. Most support locum tenens for short-term coverage (87.3%) and recruitment problems (72.1%), but not long-term vacancies (38.8%; P < 0.001) or permanent coverage (27.0%; P < 0.001). locum tenens coverage is an established feature of pediatric surgery. Most view it as a stopgap solution to the surgical workforce shortage.

Allodynia and descending pain modulation in migraine: a resting state functional connectivity analysis.

OBJECTIVE: Most migraineurs develop cutaneous allodynia during migraines, and many have cutaneous sensitization between attacks. Atypical pain modulation via the descending pain system may contribute to this sensitization and allodynia. The objective of this study was to test the hypothesis that compared with non-allodynic migraineurs, allodynic migraineurs have atypical periaqueductal gray (PAG) and nucleus cuneiformis (NCF) resting-state functional connectivity (rs-fc) with other pain processing regions. DESIGN: Ten minutes resting-state blood-oxygen-level-dependent data were collected from 38 adult migraineurs and 20 controls. Seed-based analyses compared whole-brain rs-fc with PAG and with NCF in migraineurs with severe ictal allodynia (N = 8) to migraineurs with no ictal allodynia (N = 8). Correlations between the strength of functional connections that differed between severely allodynic and non-allodynic migraineurs with allodynia severity were determined for all migraineurs (N = 38). PAG and NCF rs-fc in all migraineurs was compared with rs-fc in controls. RESULTS: Migraineurs with severe allodynia had stronger PAG and NCF rs-fc to other brainstem, thalamic, insula and cerebellar regions that participate in discriminative pain processing, as well as to frontal and temporal regions implicated in higher order pain modulation. Evidence that these rs-fc differences were specific for allodynia included: 1) strong correlations between some rs-fc strengths and allodynia severity among all migraineurs; and 2) absence of overlap when comparing rs-fc differences in severely allodynic vs non-allodynic migraineurs with those in all migraineurs vs controls. CONCLUSION: Atypical rs-fc of brainstem descending modulatory pain regions with other brainstem and higher order pain-modulating regions is associated with migraine-related allodynia.

Automated measurement of skull circumference, cranial index, and braincase volume from pediatric computed tomography.

Normative values of pediatric skull circumference, cranial index, and braincase volume would inform multiple disciplines including neurosurgery, plastic surgery and anthropology. Semi-automated methods exist for obtaining these data but are time consuming and require expertise. We report on a new method for automated extraction of in vivo measures of pediatric crania based on x-ray computed tomography scans (CT). Data were obtained from a clinical image repository for pediatric populations in whom no pathology was noted. The automated process showed good agreement with semi-automated measures, although there was a small bias for both braincase volume and circumference. We developed an open source program to automatically extract measures of skull circumference, cranial index, and braincase volume that are likely to prove useful in multiple disciplines.

Sigmoid volvulus in 16-year-old boy with an associated anomalous congenital band.

Sigmoid volvulus, a condition generally seen in debilitated elderly patients, is extremely rare in the pediatric age group. Frequent predisposing conditions that accompany pediatric sigmoid volvulus include intestinal malrotation, omphalomesenteric abnormalities, Hirschsprung's disease, imperforate anus and chronic constipation. A 16-year-old previously healthy African American male presented with a 12 hour history of sudden onset abdominal pain and intractable vomiting. CT was consistent with sigmoid volvulus. A contrast enema did not reduce the volvulus, but it was colonoscopically reduced. Patient condition initially improved after colonoscopy, but he again became distended with abdominal pain, so he was taken to the operating room. On exploratory laparotomy, a band was discovered where the mesenteries of the sigmoid and small bowel adhered and created a narrow fixation point around which the sigmoid twisted. A sigmoidectomy with primary anastomosis was performed. The diagnosis of sigmoid volvulus may be more difficult in children, with barium enema being the most consistently helpful. Seventy percent of cases do not involve an associated congenital problem, suggesting that some pediatric patients may have congenital redundancy of the sigmoid colon and elongation of its mesentery. The congenital band found in our patient was another potential anatomic factor that led to sigmoid volvulus. Pediatric surgeons, accustomed to unusual problems in children, may thus encounter a condition generally found in the debilitated elderly patient.

Atypical resting-state functional connectivity of affective pain regions in chronic migraine.

OBJECTIVE: Chronic migraineurs (CM) have painful intolerances to somatosensory, visual, olfactory, and auditory stimuli during and between migraine attacks. These intolerances are suggestive of atypical affective responses to potentially noxious stimuli. We hypothesized that atypical resting-state functional connectivity (rs-fc) of affective pain-processing brain regions may associate with these intolerances. This study compared rs-fc of affective pain-processing regions in CM with controls. METHODS: Twelve minutes of resting-state blood oxygenation level-dependent data were collected from 20 interictal adult CM and 20 controls. Rs-fc between 5 affective regions (anterior cingulate cortex, right/left anterior insula, and right/left amygdala) with the rest of the brain was determined. Functional connections consistently differing between CM and controls were identified using summary analyses. Correlations between number of migraine years and the strengths of functional connections that consistently differed between CM and controls were calculated. RESULTS: Functional connections with affective pain regions that differed in CM and controls included regions in anterior insula, amygdala, pulvinar, mediodorsal thalamus, middle temporal cortex, and periaqueductal gray. There were significant correlations between the number of years with CM and functional connectivity strength between the anterior insula with mediodorsal thalamus and anterior insula with periaqueductal gray. CONCLUSION: CM is associated with interictal atypical rs-fc of affective pain regions with pain-facilitating and pain-inhibiting regions that participate in sensory-discriminative, cognitive, and integrative domains of the pain experience. Atypical rs-fc with affective pain regions may relate to aberrant affective pain processing and atypical affective responses to painful stimuli characteristic of CM.

Traumatic disruption of the abdominal wall: lap-belt injuries in children.

Traumatic abdominal wall hernia (TAWH) from high speed mechanism is a unique finding in adult trauma, and exceedingly rare in pediatrics. The majority of reports are of low-speed "handlebar" hernias associated with direct injury by bicycle handlebars. We report a series of three pediatric patients in motor vehicle collisions (MVC) who experienced TAWH by lap-belt and associated intra-abdominal injuries necessitating immediate operative intervention. Different operative approaches were used in each case to manage the varying types of disruptions. This adds to the pediatric literature the largest series of its kind.

Characterization of scale-free properties of human electrocorticography in awake and slow wave sleep States.

Like many complex dynamic systems, the brain exhibits scale-free dynamics that follow power-law scaling. Broadband power spectral density (PSD) of brain electrical activity exhibits state-dependent power-law scaling with a log frequency exponent that varies across frequency ranges. Widely divergent naturally occurring neural states, awake and slow wave sleep (SWS), were used to evaluate the nature of changes in scale-free indices of brain electrical activity. We demonstrate two analytic approaches to characterizing electrocorticographic (ECoG) data obtained during awake and SWS states. A data-driven approach was used, characterizing all available frequency ranges. Using an equal error state discriminator (EESD), a single frequency range did not best characterize state across data from all six subjects, though the ability to distinguish awake and SWS ECoG data in individual subjects was excellent. Multi-segment piecewise linear fits were used to characterize scale-free slopes across the entire frequency range (0.2-200 Hz). These scale-free slopes differed between awake and SWS states across subjects, particularly at frequencies below 10 Hz and showed little difference at frequencies above 70 Hz. A multivariate maximum likelihood analysis (MMLA) method using the multi-segment slope indices successfully categorized ECoG data in most subjects, though individual variation was seen. In exploring the differences between awake and SWS ECoG data, these analytic techniques show that no change in a single frequency range best characterizes differences between these two divergent biological states. With increasing computational tractability, the use of scale-free slope values to characterize ECoG and EEG data will have practical value in clinical and research studies.

Determination of neural state classification metrics from the power spectrum of human ECoG.

Brain electrical activity exhibits scale-free dynamics that follow power law scaling. Previous works have shown that broadband spectral power exhibits state-dependent scaling with a log frequency exponent that systematically varies with neural state. However, the frequency ranges which best characterize biological state are not consistent across brain location or subject. An adaptive piecewise linear fitting solution was developed to extract features for classification of brain state. Performance was evaluated by comparison to an a posteriori based feature search method. This analysis, using the 1/ƒ characteristics of the human ECoG signal, demonstrates utility in advancing the ability to perform automated brain state discrimination.