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Total ankle arthroplasty has gained popularity as advancing technology has resulted in higher survivorship and lower complication rates. In the past, total ankle replacement candidates have been reserved for patients greater than 50 years old with low physical demands and minimal deformity. However, with newer designs, surgeons have begun to expand their patient inclusion criteria. The purpose of this study was to analyze current literature comparing patient outcomes among total ankle replacement patients over and under age 50. A systematic review of the literature was performed comparing the impact of age to total ankle replacement outcomes. 159 articles were reviewed. Seven studies met our inclusion criteria and therefore were included in the synthesis. No statistically significant difference in outcomes was determined for the younger and older age groups in regard to reoperation, complications, and implant survivorship (p = .412, .955, .155, respectively). However, the statistical model is underpowered given the limited number of studies. While the findings of this study infer that total ankle replacement outcomes are not significantly different among older and younger age groups, further research in this area is needed.
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We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.
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Linfócitos T CD4-Positivos , Linfócitos T CD8-Positivos , Neoplasias , Humanos , Linfócitos T CD8-Positivos/metabolismo , Linfócitos T CD4-Positivos/metabolismo , Neoplasias/genética , Neoplasias/imunologia , Neoplasias/patologia , Perfilação da Expressão Gênica/métodos , Transcriptoma , Aprendizado Profundo , Biologia Computacional/métodos , Linfócitos do Interstício Tumoral/imunologia , Regulação Neoplásica da Expressão GênicaRESUMO
Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of >1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of >1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories.
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Aprendizado Profundo , Neoplasias , Humanos , Animais , Camundongos , Neoplasias/genética , Neoplasias/patologia , Neoplasias/diagnóstico por imagem , Genômica/métodos , Xenoenxertos , Ensaios Antitumorais Modelo de Xenoenxerto , Transtornos Linfoproliferativos/genética , Transtornos Linfoproliferativos/patologia , Processamento de Imagem Assistida por Computador/métodosRESUMO
BACKGROUND: Patients with unbalanced common atrioventricular canal can be difficult to manage. Surgical planning often depends on pre-operative echocardiographic measurements. We aimed to determine the added utility of cardiac MRI in predicting successful biventricular repair in common atrioventricular canal. METHODS: We conducted a retrospective cohort study of children with common atrioventricular canal who underwent MRI prior to repair. Associations between MRI and echocardiographic measures and surgical outcome were tested using logistic regression, and models were compared using area under the receiver operator characteristic curve. RESULTS: We included 28 patients (median age at MRI: 5.2 months). The optimal MRI model included the novel end-diastolic volume index (using the ratio of left ventricular end-diastolic volume to total end-diastolic volume) and the left ventricle-right ventricle angle in diastole (area under the curve 0.83, p = 0.041). End-diastolic volume index ≤ 0.18 and left ventricle-right ventricle angle in diastole ≤ 72° yield a sensitivity of 83% and specificity of 81% for successful biventricular repair. The optimal multimodality model included the end-diastolic volume index and the echocardiographic atrioventricular valve index with an area under the curve of 0.87 (p = 0.026). CONCLUSIONS: Cardiac MRI can successfully predict successful biventricular repair in patients with unbalanced common atrioventricular canal utilising the end-diastolic volume index alone or in combination with the MRI left ventricle-right ventricle angle in diastole or the echocardiographic atrioventricular valve index. A prospective cardiac MRI study is warranted to better define the multimodality characteristic predictive of successful biventricular surgery.
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Defeitos dos Septos Cardíacos , Criança , Humanos , Lactente , Estudos Retrospectivos , Defeitos dos Septos Cardíacos/cirurgia , Ventrículos do Coração/diagnóstico por imagem , Ventrículos do Coração/cirurgia , Imageamento por Ressonância Magnética , Espectroscopia de Ressonância MagnéticaRESUMO
Background: Infants with complex congenital heart disease (CHD) require life-saving corrective/palliative heart surgery in the first weeks of life. These infants are at risk for brain injury and poor neurodevelopmental outcomes. Cerebral microhemorrhages (CMH) are frequently seen after neonatal bypass heart surgery, but it remains unknown if CMH are a benign finding or constitute injury. Herein, we investigate the risk factors for developing CMH and their clinical significance. Methods: 192 infants with CHD undergoing corrective cardiac surgery with cardiopulmonary bypass (CPB) at a single institution were prospectively evaluated with pre-(n = 183) and/or postoperative (n = 162) brain magnetic resonance imaging (MRI). CMH severity was scored based on total number of microhemorrhages. Antenatal, perioperative, and postoperative candidate risk factors for CMH and neurodevelopmental (ND) outcomes were analyzed. Eighteen-month neurodevelopmental outcomes were assessed using the Bayley-III Scales of Infants and Toddler Development in a subset of patients (n = 82). Linear regression was used to analyze associations between risk factors or ND outcomes and presence/number of CMH. Results: The most common CHD subtypes were hypoplastic left heart syndrome (HLHS) (37%) and transposition of the great arteries (TGA) (33%). Forty-two infants (23%) had CMH present on MRI before surgery and 137 infants (85%) post-surgery. No parameters evaluated were significant risk factors for preoperative CMH. In multivariate analysis, cardiopulmonary bypass (CPB) duration (p < 0.0001), use of extracorporeal membrane oxygenation (ECMO) support (p < 0.0005), postoperative seizure(s) (p < 0.03), and lower birth weight (p < 0.03) were associated with new or worsened CMH postoperatively. Higher CMH number was associated with lower scores on motor (p < 0.03) testing at 18 months. Conclusion: CMH is a common imaging finding in infants with CHD with increased prevalence and severity after CPB and adverse impact on neurodevelopmental outcomes starting at a young age. Longer duration of CPB and need for postoperative ECMO were the most significant risk factors for developing CMH. However, presence of CMH on preoperative scans indicates non-surgical risk factors that are yet to be identified. Neuroprotective strategies to mitigate risk factors for CMH may improve neurodevelopmental outcomes in this vulnerable population.
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Cardiopulmonary bypass (CPB) provides cerebral oxygenation and blood flow (CBF) during neonatal congenital heart surgery, but the impacts of CPB on brain oxygen supply and metabolic demands are generally unknown. To elucidate this physiology, we used diffuse correlation spectroscopy and frequency-domain diffuse optical spectroscopy to continuously measure CBF, oxygen extraction fraction (OEF), and oxygen metabolism (CMRO2) in 27 neonatal swine before, during, and up to 24 h after CPB. Concurrently, we sampled cerebral microdialysis biomarkers of metabolic distress (lactate-pyruvate ratio) and injury (glycerol). We applied a novel theoretical approach to correct for hematocrit variation during optical quantification of CBF in vivo. Without correction, a mean (95% CI) +53% (42, 63) increase in hematocrit resulted in a physiologically improbable +58% (27, 90) increase in CMRO2 relative to baseline at CPB initiation; following correction, CMRO2 did not differ from baseline at this timepoint. After CPB initiation, OEF increased but CBF and CMRO2 decreased with CPB time; these temporal trends persisted for 0-8 h following CPB and coincided with a 48% (7, 90) elevation of glycerol. The temporal trends and glycerol elevation resolved by 8-24 h. The hematocrit correction improved quantification of cerebral physiologic trends that precede and coincide with neurological injury following CPB.
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Glioblastoma (GBM) is an aggressive brain cancer with a median survival time of 14.6 months after diagnosis. GBM cells have altered metabolism and exhibit the Warburg effect, preferentially producing lactate under aerobic conditions. After standard-of-care treatment for GBM, there is an almost 100% recurrence rate. Hypoxia-adapted, treatment-resistant GBM stem-like cells are thought to drive this high recurrence rate. We used human T98G GBM cells as a model to identify differential gene expression induced by hypoxia and to search for potential therapeutic targets of hypoxia adapted GBM cells. RNA sequencing (RNAseq) and bioinformatics were used to identify differentially expressed genes (DEGs) and cellular pathways affected by hypoxia. We also examined expression of lactate dehydrogenase (LDH) genes using qRT-PCR and zymography as LDH dysregulation is a feature of many cancers. We found 2630 DEGs significantly altered by hypoxia (p < 0.05), 1241 upregulated in hypoxia and 1389 upregulated in normoxia. Hypoxia DEGs were highest in pathways related to glycolysis, hypoxia response, cell adhesion and notably the endoplasmic reticulum, including the inositol-requiring enzyme 1 (IRE1)-mediated unfolded protein response (UPR). These results, paired with numerous published preclinical data, provide additional evidence that inhibition of the IRE1-mediated UPR may have therapeutic potential in treating GBM. We propose a possible drug repurposing strategy to simultaneously target IRE1 and the spleen tyrosine kinase (SYK) in patients with GBM.
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Glioblastoma , Humanos , Glioblastoma/tratamento farmacológico , Glioblastoma/genética , Glioblastoma/metabolismo , Linhagem Celular Tumoral , Proteínas Serina-Treonina Quinases/genética , Proteínas Serina-Treonina Quinases/metabolismo , Análise de Sequência de RNA , Hipóxia/genéticaRESUMO
Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response.
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Antineoplásicos , Leucemia Mielogênica Crônica BCR-ABL Positiva , Leucemia Mieloide de Fase Crônica , Humanos , Antineoplásicos/farmacologia , Proteínas de Fusão bcr-abl/genética , Inibidores de Proteínas Quinases/efeitos adversos , Leucemia Mielogênica Crônica BCR-ABL Positiva/diagnóstico , Leucemia Mielogênica Crônica BCR-ABL Positiva/tratamento farmacológico , Leucemia Mielogênica Crônica BCR-ABL Positiva/genética , Resultado do TratamentoRESUMO
PURPOSE: To validate an arthroscopic approach for performing significant acetabular rim correction and circumferential labral reconstruction required to treat severe pincer-type femoroacetabular impingement. METHODS: Using a minimum of 2-year follow-up, data from 48 hips, including 47 patients (11 male, 36 female; mean age of 42 years) having undergone significant arthroscopic acetabuloplasty for severe pincer impingement (center edge angle >45°) with concomitant circumferential allograft labral reconstruction were analyzed to determine improvements in patient-reported outcomes and degree of radiographic correction. RESULTS: Findings demonstrated a 98% success rate, including substantial improvements on all radiographic measurements and patient-reported outcomes. Minimal clinically important differences were met with extremely strong measures of effect. The mean center edge angle improved from 49° to 36° (MΔ = 13.96, P ≤ .001, standard deviation [SD] = 55.97, confidence interval [CI] 12.17- 15.62, d = 2.33) and the mean Tönnis angle improved from -6° to 0° (MΔ = 6.2, P ≤ .001, SD = 2.76 CI -7.1 to -5.39, d = 2.29). Modified Hip Harris Scores improved by a mean of 34.45 points (P ≤ .001, SD = 20.64, 95% CI 28.45-40.44, d = 1.66). Lower extremity functional scale scores improved by a mean of 27.35 points (P ≤ .001, SD = 18.37, 95% CI 22.02-32.69, d =1.48). No complications were reported. One case converted to a total hip arthroplasty (2%). CONCLUSIONS: Findings validated that the significant acetabular rim correction required to treat severe pincer morphology is safe and feasible via an arthroscopic approach. This, in addition to concomitant circumferential allograft labral reconstruction, resulted in improvement in patient-reported outcomes and radiographic measurements. LEVEL OF EVIDENCE: Level IV, therapeutic case-series.
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Impacto Femoroacetabular , Humanos , Masculino , Feminino , Adulto , Articulação do Quadril/cirurgia , Resultado do Tratamento , Artroscopia/métodos , Medidas de Resultados Relatados pelo Paciente , Estudos Retrospectivos , SeguimentosRESUMO
BACKGROUND AND OBJECTIVES: Deep learning utilizing convolutional neural networks (CNNs) applied to hematoxylin & eosin (H&E)-stained slides numerically encodes histomorphological tumor features. Tumor heterogeneity is an emerging biomarker in colon cancer that is, captured by these features, whereas microsatellite instability (MSI) is an established biomarker traditionally assessed by immunohistochemistry or polymerase chain reaction. METHODS: H&E-stained slides from The Cancer Genome Atlas (TCGA) colon cohort are passed through the CNN. Resulting imaging features are used to cluster morphologically similar slide regions. Tile-level pairwise similarities are calculated and used to generate a tumor heterogeneity score (THS). Patient-level THS is then correlated with TCGA-reported biomarkers, including MSI-status. RESULTS: H&E-stained images from 313 patients generated 534 771 tiles. Deep learning automatically identified and annotated cells by type and clustered morphologically similar slide regions. MSI-high tumors demonstrated significantly higher THS than MSS/MSI-low (p < 0.001). THS was higher in MLH1-silent versus non-silent tumors (p < 0.001). The sequencing derived MSIsensor score also correlated with THS (r = 0.51, p < 0.0001). CONCLUSIONS: Deep learning provides spatially resolved visualization of imaging-derived biomarkers and automated quantification of tumor heterogeneity. Our novel THS correlates with MSI-status, indicating that with expanded training sets, translational tools could be developed that predict MSI-status using H&E-stained images alone.
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Neoplasias do Colo , Neoplasias Colorretais , Aprendizado Profundo , Humanos , Instabilidade de Microssatélites , Repetições de Microssatélites , Neoplasias do Colo/diagnóstico por imagem , Neoplasias do Colo/genética , Neoplasias do Colo/patologia , Neoplasias Colorretais/patologiaRESUMO
Neonates undergoing cardiac surgery involving aortic arch reconstruction are at an increased risk for hypoxic-ischemic brain injury. Deep hypothermia is utilized to help mitigate this risk when periods of circulatory arrest are needed for surgical repair. Here, we investigate correlations between non-invasive optical neuromonitoring of cerebral hemodynamics, which has recently shown promise for the prediction of postoperative white matter injury in this patient population, and invasive cerebral microdialysis biomarkers. We compared cerebral tissue oxygen saturation (StO2), relative total hemoglobin concentration (rTHC), and relative cerebral blood flow (rCBF) measured by optics against the microdialysis biomarkers of metabolic stress and injury (lactate-pyruvate ratio (LPR) and glycerol) in neonatal swine models of deep hypothermic cardiopulmonary bypass (DHCPB), selective antegrade cerebral perfusion (SACP), and deep hypothermic circulatory arrest (DHCA). All three optical parameters were negatively correlated with LPR and glycerol in DHCA animals. Elevation of LPR was found to precede the elevation of glycerol by 30-60 min. From these data, thresholds for the detection of hypoxic-ischemia-associated cerebral metabolic distress and neurological injury are suggested. In total, this work provides insight into the timing and mechanisms of neurological injury following hypoxic-ischemia and reports a quantitative relationship between hypoxic-ischemia severity and neurological injury that may inform DHCA management.
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BACKGROUND: Obstructed total anomalous pulmonary venous connection (TAPVC) is a form of critical congenital heart disease that usually requires urgent postnatal intervention. Knowing which patients have severe obstruction can aid delivery planning. The authors previously developed a novel quantitative metric of pulmonary venous flow, the pulmonary venous variability index (PVVI). The aim of this study was to test the hypothesis that fetal PVVI and vertical vein Doppler velocities are associated with severe pulmonary vein obstruction postnatally. METHODS: A retrospective cohort study of neonates with prenatally diagnosed TAPVC was performed. Patients who underwent fetal echocardiography at the Children's Hospital of Philadelphia with Doppler interrogation of the vertical vein were included for analysis. Twenty-nine patients met criteria (21 with heterotaxy, 18 with supracardiac TAPVC). The latest gestation fetal echocardiogram was used. Severe pulmonary vein obstruction was defined as preoperative death or urgent surgery or catheter-based intervention (first day of life). Measurements of PVVI, defined as (maximum velocity - minimum velocity)/mean velocity, were made offline. Wilcoxon rank sum models were used to assess the associations of severe obstruction and PVVI and maximum, mean, and minimum velocities. RESULTS: The mean gestational age at the latest fetal echocardiographic examination was 35 weeks (range, 30-39 weeks). Twelve of the 29 patients (41%) met criteria for severe pulmonary vein obstruction. Lower PVVI was associated with greater risk for severe pulmonary venous obstruction (P = .008). The maximum, mean, and minimum velocities in the vertical vein were all significantly associated with severe pulmonary venous obstruction (P = .03, P = .03, and P = .007, respectively). Qualitative assessment of obstruction was not significantly associated with the outcome. Interobserver reliability for all vertical vein Doppler metrics was high (intraclass correlation coefficient > 0.9). CONCLUSIONS: Fetal PVVI and maximum, mean, and minimum velocities are associated with severe postnatal pulmonary vein obstruction in TAPVC. Accurate prediction of obstructed TAPVC could allow safer delivery planning. Further research with larger sample sizes is needed to identify the ideal cutoff values for these Doppler measures.
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Cardiopatias Congênitas , Veias Pulmonares , Síndrome de Cimitarra , Recém-Nascido , Criança , Humanos , Gravidez , Lactente , Feminino , Estudos Retrospectivos , Reprodutibilidade dos Testes , Cardiopatias Congênitas/complicações , Cardiopatias Congênitas/diagnóstico , Cardiopatias Congênitas/cirurgia , Síndrome de Cimitarra/diagnóstico , Síndrome de Cimitarra/diagnóstico por imagem , Veias Pulmonares/diagnóstico por imagem , EcocardiografiaRESUMO
Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture). While many studies have incorporated CNN features into predictive models, there has been little empirical study of their properties. We show such features can be construed as abstract morphological genes ("mones") with strong independent associations to biological phenotypes. Many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC = [Formula: see text] for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC = [Formula: see text]). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values. Our work also demonstrates mones can be interpreted without using a classifier as a proxy.
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Adenocarcinoma , Neoplasias do Colo , Aprendizado Profundo , Neoplasias do Colo/genética , Humanos , Aprendizado de Máquina , Redes Neurais de ComputaçãoRESUMO
We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.
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Helicobacter pylori is a common gastric pathogen associated with multiple clinical syndromes, including cancer. Eradication rates of H. pylori remain suboptimal despite the progress made in the past few decades in improving treatment strategies. The low eradication rates are mainly driven by antibiotic resistance of H. pylori. Non-invasive molecular testing to identify patients with antibiotic-resistant H. pylori represents a promising therapeutic avenue, however this technology currently remains limited by availability, costs, and lack of robust validation. Moreover, there is insufficient evidence to demonstrate that resistance-testing-based treatment approaches are superior to appropriately designed empiric strategies. Consensus guidelines recommend use of proven locally effective regimens; however, eradication data are inconsistently generated in several regions of the world. In this review, we describe several clinical factors associated with increased rates of antibiotic resistant H. pylori, including history of previous antibiotic exposure, increasing age, female gender, ethnicity/race, extent of alcohol use, and non-ulcer dyspepsia. Assessment of these factors may aid the clinician in choosing the most appropriate empiric treatment strategy for each patient. Future study should aim to identify locally effective therapies and further explore the clinical factors associated with antibiotic resistance.
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Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. As such, our Image Analysis Working Group (IAWG), composed of researchers in the Cancer Systems Biology Consortium (CSBC) and the Physical Sciences - Oncology Network (PS-ON), convened a workshop on "Computational Challenges Shared by Diverse Imaging Platforms" to characterize these common issues and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).
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Processamento de Imagem Assistida por Computador , Neoplasias , Diagnóstico por Imagem , Humanos , Processamento de Imagem Assistida por Computador/métodos , Neoplasias/diagnóstico por imagem , Software , Microambiente TumoralRESUMO
BACKGROUND: The increasing incidence of obesity has led to a rise in bariatric surgeries. Obesity can be associated with various gastrointestinal symptoms as well as abnormal findings on high-resolution esophageal manometry (HRM). Bariatric procedures have variable effects on esophageal function and may contribute to postoperative symptoms. Preoperative HRM is not performed routinely on patients undergoing bariatric surgery but may identify patients likely to experience postoperative esophageal symptoms via delineation of structural or functional abnormalities. OBJECTIVES: To evaluate whether prebariatric surgery HRM could predict persistent or de novo postoperative esophageal symptoms. SETTING: Academic tertiary care hospital, United States. METHODS: Retrospective data were collected for 20 patients undergoing HRM and 100 controls 18 years and older from May 2012 to May 2015. Propensity score matching was performed to adjust for baseline differences between the 2 groups. Preoperative and postoperative esophageal symptoms (reflux, dysphagia, nausea/vomiting, bloating, fullness, early satiety, pain, and intolerance) were compared between HRM and control patients, and associations among HRM findings, Chicago Classification, and symptoms were analyzed. All included patients had follow-up beyond 3 months postoperatively. Data were analyzed with 2-tailed Fisher's exact test, Wilcoxon rank-sum test, and odds ratio. RESULTS: Compared to controls, patients undergoing preoperative HRM had a higher rate of postoperative chronic intolerance (25% versus 8%, P = .041). This difference was not observed in propensity score matching analysis. Identification of elevated integrated relaxation pressure and esophagogastric junction outflow obstruction predicted chronic intolerance (odds ratio = 21.0; 95% confidence interval: 1.40-314; P = .027 for each). CONCLUSIONS: Preoperative HRM abnormalities were associated with postoperative symptoms in patients undergoing bariatric surgery. HRM can identify patients who are more likely to experience postoperative esophageal symptoms and may aid in discussion of suitability for surgery and selection of bariatric intervention.
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Cirurgia Bariátrica , Transtornos da Motilidade Esofágica , Transtornos da Motilidade Esofágica/complicações , Transtornos da Motilidade Esofágica/etiologia , Junção Esofagogástrica , Humanos , Manometria/métodos , Estudos RetrospectivosRESUMO
BACKGROUND: Cerebral autoregulation mechanisms help maintain adequate cerebral blood flow (CBF) despite changes in cerebral perfusion pressure. Impairment of cerebral autoregulation, during and after cardiopulmonary bypass (CPB), may increase risk of neurologic injury in neonates undergoing surgery. In this study, alterations of cerebral autoregulation were assessed in a neonatal swine model probing four perfusion strategies. METHODS: Neonatal swine (n = 25) were randomized to continuous deep hypothermic cardiopulmonary bypass (DH-CPB, n = 7), deep hypothermic circulatory arrest (DHCA, n = 7), selective cerebral perfusion (SCP, n = 7) at deep hypothermia, or normothermic cardiopulmonary bypass (control, n = 4). The correlation coefficient (LDx) between laser Doppler measurements of CBF and mean arterial blood pressure was computed at initiation and conclusion of CPB. Alterations in cerebral autoregulation were assessed by the change between initial and final LDx measurements. RESULTS: Cerebral autoregulation became more impaired (LDx increased) in piglets that underwent DH-CPB (initial LDx: median 0.15, IQR [0.03, 0.26]; final: 0.45, [0.27, 0.74]; p = 0.02). LDx was not altered in those undergoing DHCA (p > 0.99) or SCP (p = 0.13). These differences were not explained by other risk factors. CONCLUSIONS: In a validated swine model of cardiac surgery, DH-CPB had a significant effect on cerebral autoregulation, whereas DHCA and SCP did not. IMPACT: Approximately half of the patients who survive neonatal heart surgery with cardiopulmonary bypass (CPB) experience neurodevelopmental delays. This preclinical investigation takes steps to elucidate and isolate potential perioperative risk factors of neurologic injury, such as impairment of cerebral autoregulation, associated with cardiac surgical procedures involving CPB. We demonstrate a method to characterize cerebral autoregulation during CPB pump flow changes in a neonatal swine model of cardiac surgery. Cerebral autoregulation was not altered in piglets that underwent deep hypothermic circulatory arrest (DHCA) or selective cerebral perfusion (SCP), but it was altered in piglets that underwent deep hypothermic CBP.
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Ponte Cardiopulmonar , Hipotermia Induzida , Animais , Animais Recém-Nascidos , Ponte Cardiopulmonar/efeitos adversos , Circulação Cerebrovascular , Homeostase , SuínosRESUMO
Hyperpolarized 13C-MRI is an emerging tool for probing tissue metabolism by measuring 13C-label exchange between intravenously injected hyperpolarized [1-13C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1H-MRI and hyperpolarized 13C-MRI before and 7-11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5-6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A (LDHA), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential. SIGNIFICANCE: Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7-11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques.
Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias da Mama/patologia , Isótopos de Carbono/análise , Imageamento por Ressonância Magnética/métodos , Terapia Neoadjuvante/métodos , Recidiva Local de Neoplasia/patologia , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/metabolismo , Feminino , Seguimentos , Humanos , Recidiva Local de Neoplasia/tratamento farmacológico , Recidiva Local de Neoplasia/metabolismo , Prognóstico , Taxa de SobrevidaRESUMO
BACKGROUND: Helicobacter pylori (H. pylori), a bacterium that infects approximately half of the world's population, is associated with various gastrointestinal diseases, including peptic ulcers, non-ulcer dyspepsia, gastric adenocarcinoma, and gastric lymphoma. As the burden of antibiotic resistance increases, the need for new adjunct therapies designed to facilitate H. pylori eradication and reduce negative distal outcomes associated with infection has become more pressing. Characterization of the interactions between H. pylori, the fecal microbiome, and fecal fatty acid metabolism, as well as the mechanisms underlying these interactions, may offer new therapeutic approaches. AIM: To characterize the gut microbiome and metabolome in H. pylori patients in a socioeconomically challenged and underprivileged inner-city community. METHODS: Stool samples from 19 H. pylori patients and 16 control subjects were analyzed. 16S rRNA gene sequencing was performed on normalized pooled amplicons using the Illumina MiSeq System using a MiSeq reagent kit v2. Alpha and beta diversity analyses were performed in QIIME 2. Non-targeted fatty acid analysis of the samples was carried out using gas chromatography-mass spectrometry, which measures the total content of 30 fatty acids in stool after conversion into their corresponding fatty acid methyl esters. Multi-dimensional scaling (MDS) was performed on Bray-Curtis distance matrices created from both the metabolomics and microbiome datasets and a Procrustes test was performed on the metabolomics and microbiome MDS coordinates. RESULTS: Fecal microbiome analysis showed that alpha diversity was lowest in H. pylori patients over 40 years of age compared to control subjects of similar age group. Beta diversity analysis of the samples revealed significant differences in microbial community structure between H. pylori patients and control subjects across all ages. Thirty-eight and six taxa had lower and higher relative abundance in H. pylori patients, respectively. Taxa that were enriched in H. pylori patients included Atopobium, Gemellaceae, Micrococcaceae, Gemellales and Rothia (R. mucilaginosa). Notably, relative abundance of the phylum Verrucomicrobia was decreased in H. pylori patients compared to control subjects. Procrustes analysis showed a significant relationship between the microbiome and metabolome datasets. Stool samples from H. pylori patients showed increases in several fatty acids including the polyunsaturated fatty acids (PUFAs) 22:4n6, 22:5n3, 20:3n6 and 22:2n6, while decreases were noted in other fatty acids including the PUFA 18:3n6. The pattern of changes in fatty acid concentration correlated to the Bacteroidetes:Firmicutes ratio determined by 16S rRNA gene analysis. CONCLUSION: This exploratory study demonstrates H. pylori-associated changes to the fecal microbiome and fecal fatty acid metabolism. Such changes may have implications for improving eradication rates and minimizing associated negative distal outcomes.