Utilization of Texture Analysis in Differentiating Benign and Malignant Breast Masses: Comparison of Grayscale Ultrasound, Shear Wave Elastography, and Radiomic Features.

OBJECTIVE: This study aims to determine which qualitative and quantitative US features are independently associated with malignancy, including those derived from grayscale imaging morphology, shear wave elastography (SWE), and texture analysis. METHODS: This single-center retrospective study was approved by the institutional research ethics board. Consecutive breast US studies performed between January and December 2020 were included. Images were acquired using a Canon Aplio i800 US unit (Canon Medical Systems, Inc., CA) and i18LX5 wideband linear matrix transducer. Grayscale US features, SWE mean, and median elasticity were obtained. Single representative grayscale images were analyzed using dedicated software (LIFEx, version 6.30). First-order and gray-level co-occurrence matrix second-order texture features were extracted. Multivariate logistic regression was performed to assess for predictors of malignancy (STATA v16.1). RESULTS: One hundred forty-seven cases with complete SWE data were selected for analysis (mean age 54.3, range 21-92). The following variables were found to be independently associated with malignancy: age (P <.001), family history (P = .013), irregular mass shape (P = .024), and stiffness on SWE (mean SWE ≥40 kPa; P <.001). Remaining variables (including texture features) were not found to be independently associated with malignancy (P >.05). CONCLUSION: US texture analysis features were not associated with malignancy independent of other qualitative and quantitative US characteristics currently utilized in clinical practice. This suggests texture analysis may not be warranted when differentiating benign and malignant breast masses on US. In contrast, irregular mass shape on grayscale imaging and increased stiffness on SWE were found to be independent predictors of malignancy.

Redox signalling regulates breast cancer metastasis via phenotypic and metabolic reprogramming due to p63 activation by HIF1α.

BACKGROUND: Redox signaling caused by knockdown (KD) of Glutathione Peroxidase 2 (GPx2) in the PyMT mammary tumour model promotes metastasis via phenotypic and metabolic reprogramming. However, the tumour cell subpopulations and transcriptional regulators governing these processes remained unknown. METHODS: We used single-cell transcriptomics to decipher the tumour cell subpopulations stimulated by GPx2 KD in the PyMT mammary tumour and paired pulmonary metastases. We analyzed the EMT spectrum across the various tumour cell clusters using pseudotime trajectory analysis and elucidated the transcriptional and metabolic regulation of the hybrid EMT state. RESULTS: Integration of single-cell transcriptomics between the PyMT/GPx2 KD primary tumour and paired lung metastases unraveled a basal/mesenchymal-like cluster and several luminal-like clusters spanning an EMT spectrum. Interestingly, the luminal clusters at the primary tumour gained mesenchymal gene expression, resulting in epithelial/mesenchymal subpopulations fueled by oxidative phosphorylation (OXPHOS) and glycolysis. By contrast, at distant metastasis, the basal/mesenchymal-like cluster gained luminal and mesenchymal gene expression, resulting in a hybrid subpopulation using OXPHOS, supporting adaptive plasticity. Furthermore, p63 was dramatically upregulated in all hybrid clusters, implying a role in regulating partial EMT and MET at primary and distant sites, respectively. Importantly, these effects were reversed by HIF1α loss or GPx2 gain of function, resulting in metastasis suppression. CONCLUSIONS: Collectively, these results underscored a dramatic effect of redox signaling on p63 activation by HIF1α, underlying phenotypic and metabolic plasticity leading to mammary tumour metastasis.

Functional characterization of a single nucleotide polymorphism associated with Alzheimer's disease in a hiPSC-based neuron model.

Neurodegenerative diseases encompass a group of debilitating conditions resulting from progressive nerve cell death. Of these, Alzheimer's disease (AD) occurs most frequently, but is currently incurable and has limited treatment success. Late onset AD, the most common form, is highly heritable but is caused by a combination of non-genetic risk factors and many low-effect genetic variants whose disease-causing mechanisms remain unclear. By mining the FinnGen study database of phenome-wide association studies, we identified a rare variant, rs148726219, enriched in the Finnish population that is associated with AD risk and dementia, and appears to have arisen on a common haplotype with older AD-associated variants such as rs429358. The rs148726219 variant lies in an overlapping intron of the FosB proto-oncogene (FOSB) and ERCC excision repair 1 (ERCC1) genes. To understand the impact of this SNP on disease phenotypes, we performed CRISPR/Cas9 editing in a human induced pluripotent stem cell (hiPSC) line to generate isogenic clones harboring heterozygous and homozygous alleles of rs148726219. hiPSC clones differentiated into induced excitatory neurons (iNs) did not exhibit detectable molecular or morphological variation in differentiation potential compared to isogenic controls. However, global transcriptome analysis showed differential regulation of nearby genes and upregulation of several biological pathways related to neuronal function, particularly synaptogenesis and calcium signaling, specifically in mature iNs harboring rs148726219 homozygous and heterozygous alleles. Functional differences in iN circuit maturation as measured by calcium imaging were observed across genotypes. Edited mature iNs also displayed downregulation of unfolded protein response and cell death pathways. This study implicates a phenotypic impact of rs148726219 in the context of mature neurons, consistent with its identification in late onset AD, and underscores a hiPSC-based experimental model to functionalize GWAS-identified variants.

A scoping review of natural language processing of radiology reports in breast cancer.

Various natural language processing (NLP) algorithms have been applied in the literature to analyze radiology reports pertaining to the diagnosis and subsequent care of cancer patients. Applications of this technology include cohort selection for clinical trials, population of large-scale data registries, and quality improvement in radiology workflows including mammography screening. This scoping review is the first to examine such applications in the specific context of breast cancer. Out of 210 identified articles initially, 44 met our inclusion criteria for this review. Extracted data elements included both clinical and technical details of studies that developed or evaluated NLP algorithms applied to free-text radiology reports of breast cancer. Our review illustrates an emphasis on applications in diagnostic and screening processes over treatment or therapeutic applications and describes growth in deep learning and transfer learning approaches in recent years, although rule-based approaches continue to be useful. Furthermore, we observe increased efforts in code and software sharing but not with data sharing.

Sequential transcatheter aortic and pulmonic valve replacement in bioprosthetic valve dysfunction: a case report.

Background: Transcatheter valve replacement is a less invasive alternative to surgical valve replacement and has become increasingly popular. It is often the preferred approach for patients with high surgical risk. In patients with multiple prior sternotomies and multi-valvular failure, sequential transcatheter valve replacements may be a viable option. Case summary: We present the case of a 61-year-old-man with two prior sternotomies who underwent sequential transcatheter replacements of the aortic and pulmonic valves for symptomatic aortic and pulmonary stenosis. He was deemed high risk for a repeat sternotomy. The decision to perform sequential transcatheter aortic valve replacement (TAVR) and transcatheter pulmonic valve replacement (TPVR) a month apart was made. Patient underwent valve-in-valve TAVR in a stentless bioprosthetic valve with 29-mm Edwards Sapien 3 followed by TPVR with 26-mm Edwards Sapien 3. He tolerated both procedures well and was asymptomatic at 1-month follow up. Discussion: To our knowledge, this is the first reported successful case of sequential TAVR and TPVR with right ventricular outflow tract stenting in a patient with both aortic and pulmonic bioprosthetic valve dysfunction. Our case demonstrates that transcatheter approach to multi-valvular replacements may be a viable option for high-risk surgical patients.

MRI vs. CT for pancreatic adenocarcinoma vascular invasion: comparative diagnostic test accuracy systematic review and meta-analysis.

OBJECTIVES: To perform a systematic review comparing the diagnostic accuracy of MRI vs. CT for assessing pancreatic ductal adenocarcinoma (PDAC) vascular invasion. METHODS: MEDLINE, EMBASE, Cochrane Central, and Scopus were searched until December 2021 for diagnostic accuracy studies comparing MRI vs. CT to evaluate vascular invasion of pathologically confirmed PDAC in the same patients. Findings on resection or exploratory laparotomy were the preferred reference standard. Data extraction, risk of bias, and applicability assessment were performed by two authors using the Quality Assessment of Diagnostic Accuracy Studies-Comparative Tool. Bivariate random-effects meta-analysis and meta-regression were performed with 95% confidence intervals (95% CI). RESULTS: Three studies were included assessing 474 vessels without vascular invasion and 65 with vascular invasion in 107 patients. All patients were imaged using MRI at ≥ 1.5 T and a pancreatic protocol CT. No difference was shown between MRI and CT for diagnosing PDAC vascular invasion: MRI/CT sensitivity (95% CI) were 71% (47-87%)/74% (56-86%), and specificity were 97% (94-99%)/97% (94-98%). Sources of bias included selection bias from only a subset of CT patients undergoing MRI and verification bias from patients with unresectable disease not confirmed on surgery. No patients received neoadjuvant therapy prior to staging. CONCLUSIONS: Based on limited data, no difference was observed between MRI and pancreatic protocol CT for PDAC vascular invasion assessment. MRI may be an adequate substitute for pancreatic protocol CT in some patients, particularly those who have already had a single-phase CT. Larger and more recent cohort studies at low risk of bias, including patients who have received neoadjuvant therapy, are needed. CLINICAL RELEVANCE STATEMENT: Abdominal MRI performed similarly to pancreatic protocol CT at assessing pancreatic ductal adenocarcinoma vascular invasion, suggesting local staging is adequate in some patients using MRI. More data are needed using larger, more recent cohorts including patients with neoadjuvant treatment. KEY POINTS: • Based on limited data, no difference was found between MRI and pancreatic protocol CT sensitivity and specificity for diagnosing PDAC vascular invasion (p = 0.81, 0.73 respectively). • Risk of bias could be reduced in future PDAC MRI vs CT comparative diagnostic test accuracy research by ensuring all enrolled patients undergo both imaging modalities being compared in random order and regardless of the findings on either modality. • More studies are needed that directly compare the diagnostic performance of MRI and CT for PDAC staging after neoadjuvant therapy.

Pancreatic Cystic Lesions on MRI: What Is The Likelihood of a Present or Future Diagnosis of Pancreatic Carcinoma?

BACKGROUND: Pancreatic cystic lesions (PCLs) are followed for years due to older and likely biased works demonstrating a strong association with pancreatic carcinoma; more recent data are needed clarifying this relationship. PURPOSE: To determine the association between PCLs on MRI and a synchronous or future diagnosis of pancreatic carcinoma. STUDY TYPE: Single-center retrospective cohort. POPULATION: A total of 192 patients (111 female, 58%) with median age 66 years (range 26-87 years) with PCLs on abdominal MRI from 2011 to 2016. FIELD STRENGTH/SEQUENCES: 1.5 T and 3 T, including T2 WI, T1 WI, diffusion weighted imaging and contrast-enhanced T1 WI. ASSESSMENT: Each PCL was reviewed independently by 2 of 10 fellowship-trained abdominal radiologists. Fukuoka guideline worrisome features and high-risk stigmata were evaluated. Follow-up imaging and clinical notes were reviewed within a system that captures pancreatic carcinoma for the region, for a median follow-up of 67 months (interquartile range: 43-88 months). STATISTICAL TESTS: Pancreatic carcinoma prevalence and incidence rate for future carcinoma with 95% confidence intervals (95% CI). Fisher exact test, logistic regression with odds ratios (OR) and the Wilcoxon rank-sum test were used to assess PCL morphologic features with the Kolmogorov-Smirnov test used to assess for normality. P < 0.05 defined statistical significance. RESULTS: The prevalence of pancreatic carcinoma on initial MRI showing a PCL was 2.4% (95% CI: 0.9%, 5.2%). Thickened/enhancing cyst wall was associated with pancreatic carcinoma, OR 52 (95% CI: 4.5, 1203). Of 189 patients with a PCL but without pancreatic carcinoma at the time of initial MRI, one developed high-grade dysplasia and none developed invasive carcinoma for an incidence rate of 0.97 (95% CI: 0.02, 5.43) and 0 (95% CI: 0, 3.59) cases per 1000 person-years, respectively. DATA CONCLUSION: A low percentage of patients with a PCL on MRI had a pancreatic carcinoma at the time of initial evaluation and none developed carcinoma over a median 67 months of follow-up. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: 5.

Geroscience-guided repurposing of FDA-approved drugs to target aging: A proposed process and prioritization.

Common chronic diseases represent the greatest driver of rising healthcare costs, as well as declining function, independence, and quality of life. Geroscience-guided approaches seek to delay the onset and progression of multiple chronic conditions by targeting fundamental biological pathways of aging. This approach is more likely to improve overall health and function in old age than treating individual diseases, by addressing aging the largest and mostly ignored risk factor for the leading causes of morbidity in older adults. Nevertheless, challenges in repurposing existing and moving newly discovered interventions from the bench to clinical care have impeded the progress of this potentially transformational paradigm shift. In this article, we propose the creation of a standardized process for evaluating FDA-approved medications for their geroscience potential. Criteria for systematically evaluating the existing literature that spans from animal models to human studies will permit the prioritization of efforts and financial investments for translating geroscience and allow immediate progress on the design of the next Targeting Aging with MEtformin (TAME)-like study involving such candidate gerotherapeutics.

Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer.

In search of redox mechanisms in breast cancer, we uncovered a striking role for glutathione peroxidase 2 (GPx2) in oncogenic signaling and patient survival. GPx2 loss stimulates malignant progression due to reactive oxygen species/hypoxia inducible factor-α (HIF1α)/VEGFA (vascular endothelial growth factor A) signaling, causing poor perfusion and hypoxia, which were reversed by GPx2 reexpression or HIF1α inhibition. Ingenuity Pathway Analysis revealed a link between GPx2 loss, tumor angiogenesis, metabolic modulation, and HIF1α signaling. Single-cell RNA analysis and bioenergetic profiling revealed that GPx2 loss stimulated the Warburg effect in most tumor cell subpopulations, except for one cluster, which was capable of oxidative phosphorylation and glycolysis, as confirmed by coexpression of phosphorylated-AMPK and GLUT1. These findings underscore a unique role for redox signaling by GPx2 dysregulation in breast cancer, underlying tumor heterogeneity, leading to metabolic plasticity and malignant progression.

scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) methods have been advantageous for quantifying cell-to-cell variation by profiling the transcriptomes of individual cells. For scRNA-seq data, variability in gene expression reflects the degree of variation in gene expression from one cell to another. Analyses that focus on cell-cell variability therefore are useful for going beyond changes based on average expression and, instead, identifying genes with homogeneous expression versus those that vary widely from cell to cell. RESULTS: We present a novel statistical framework, scShapes, for identifying differential distributions in single-cell RNA-sequencing data using generalized linear models. Most approaches for differential gene expression detect shifts in the mean value. However, as single-cell data are driven by overdispersion and dropouts, moving beyond means and using distributions that can handle excess zeros is critical. scShapes quantifies gene-specific cell-to-cell variability by testing for differences in the expression distribution while flexibly adjusting for covariates if required. We demonstrate that scShapes identifies subtle variations that are independent of altered mean expression and detects biologically relevant genes that were not discovered through standard approaches. CONCLUSIONS: This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html).

Muscle fibrosis and maladaptation occur progressively in CKD and are rescued by dialysis.

BACKGROUNDSkeletal muscle maladaptation accompanies chronic kidney disease (CKD) and negatively affects physical function. Emphasis in CKD has historically been placed on muscle fiber-intrinsic deficits, such as altered protein metabolism and atrophy. However, targeted treatment of fiber-intrinsic dysfunction has produced limited improvement, whereas alterations within the fiber-extrinsic environment have scarcely been examined.METHODSWe investigated alterations to the skeletal muscle interstitial environment with deep cellular phenotyping of biopsies from patients with CKD and age-matched controls and performed transcriptome profiling to define the molecular underpinnings of CKD-associated muscle impairments. We examined changes in muscle maladaptation following initiation of dialysis therapy for kidney failure.RESULTSPatients with CKD exhibited a progressive fibrotic muscle phenotype, which was associated with impaired regenerative capacity and lower vascular density. The severity of these deficits was strongly associated with the degree of kidney dysfunction. Consistent with these profound deficits, CKD was associated with broad alterations to the muscle transcriptome, including altered ECM organization, downregulated angiogenesis, and altered expression of pathways related to stem cell self-renewal. Remarkably, despite the seemingly advanced nature of this fibrotic transformation, dialysis treatment rescued these deficits, restoring a healthier muscle phenotype. Furthermore, after accounting for muscle atrophy, strength and endurance improved after dialysis initiation.CONCLUSIONThese data identify a dialysis-responsive muscle fibrotic phenotype in CKD and suggest the early dialysis window presents a unique opportunity of improved muscle regenerative capacity during which targeted interventions may achieve maximal impact.TRIAL REGISTRATIONNCT01452412FUNDINGNIH, NIH Clinical and Translational Science Awards (CTSA), and Einstein-Mount Sinai Diabetes Research Center.

Pancreas adenocarcinoma CT texture analysis: comparison of 3D and 2D tumor segmentation techniques.

PURPOSE: To determine equivalency of multi-slice 3D CTTA and single slice 2D CTTA of pancreas adenocarcinoma. METHODS: This retrospective study was research ethics board approved. Untreated pancreas adenocarcinomas were segmented on CT in 128 consecutive patients. Tumor segmentation was compared using two techniques: 3D segmentation by contouring all visible tumor in a 3D volume, and 2D segmentation using only a single axial image. First-order CTTA features including mean, minimum, maximum Hounsfield units (HU), standard deviation, skewness, kurtosis, entropy, and second-order gray-level co-occurrence matrix (GLCM) features homogeneity, contrast, correlation, entropy and dissimilarity were extracted. Median values were compared using the Mann-Whitney U test with Holm-Bonferroni correction. Kendall's Rank Correlation Tau assessed for correlation, and agreement was calculated using intraclass correlation coefficients (ICC) using a two-way model with single rating and absolute agreement. Statistical significance defined as P < 0.05. RESULTS: The median values of CTTA features differed significantly between 3 and 2D segmentations for all of the evaluated features except for mean attenuation, standard deviation and skewness (P = 0.2979 each). 3D and 2D segmentations had moderate correlation for mean attenuation (R = 0.69, P < 0.01), while all other features demonstrated poor to fair correlation. Agreement between 3 and 2D segmentations was good for mean attenuation (ICC: 0.87, P < 0.01), moderate for minimum (ICC: 0.65, P < 0.01) and standard deviation (ICC: 0.56, P < 0.01), and poor for all other features. CONCLUSION: While pancreas adenocarcinoma CTTA features obtained using 3D and 2D segmentation have multiple associations with clinically relevant outcomes, these segmentation techniques are likely not interchangeable other than for mean HU.

A geroscience perspective on immune resilience and infectious diseases: a potential case for metformin.

We are in the midst of the global pandemic. Though acute respiratory coronavirus (SARS-COV2) that leads to COVID-19 infects people of all ages, severe symptoms and mortality occur disproportionately in older adults. Geroscience interventions that target biological aging could decrease risk across multiple age-related diseases and improve outcomes in response to infectious disease. This offers hope for a new host-directed therapeutic approach that could (i) improve outcomes following exposure or shorten treatment regimens; (ii) reduce the chronic pathology associated with the infectious disease and subsequent comorbidity, frailty, and disability; and (iii) promote development of immunological memory that protects against relapse or improves response to vaccination. We review the possibility of this approach by examining available evidence in metformin: a generic drug with a proven safety record that will be used in a large-scale multicenter clinical trial. Though rigorous translational research and clinical trials are needed to test this empirically, metformin may improve host immune defenses and confer protection against long-term health consequences of infectious disease, age-related chronic diseases, and geriatric syndromes.

Metformin alters skeletal muscle transcriptome adaptations to resistance training in older adults.

Evidence from clinical trials and observational studies suggests that both progressive resistance exercise training (PRT) and metformin delay a variety of age-related morbidities. Previously, we completed a clinical trial testing the effects of 14 weeks of PRT + metformin (metPRT) compared to PRT with placebo (plaPRT) on muscle hypertrophy in older adults. We found that metformin blunted PRT-induced muscle hypertrophic response. To understand potential mechanisms underlying the inhibitory effect of metformin on PRT, we analyzed the muscle transcriptome in 23 metPRT and 24 plaPRT participants. PRT significantly increased expression of genes involved in extracellular matrix remodeling pathways, and downregulated RNA processing pathways in both groups, however, metformin attenuated the number of differentially expressed genes within these pathways compared to plaPRT. Pathway analysis showed that genes unique to metPRT modulated aging-relevant pathways, such as cellular senescence and autophagy. Differentially expressed genes from baseline biopsies in older adults compared to resting muscle from young volunteers were reduced following PRT in plaPRT and were further reduced in metPRT. We suggest that although metformin may blunt pathways induced by PRT to promote muscle hypertrophy, adjunctive metformin during PRT may have beneficial effects on aging-associated pathways in muscle from older adults.

Benefits of Metformin in Attenuating the Hallmarks of Aging.

Biological aging involves an interplay of conserved and targetable molecular mechanisms, summarized as the hallmarks of aging. Metformin, a biguanide that combats age-related disorders and improves health span, is the first drug to be tested for its age-targeting effects in the large clinical trial-TAME (targeting aging by metformin). This review focuses on metformin's mechanisms in attenuating hallmarks of aging and their interconnectivity, by improving nutrient sensing, enhancing autophagy and intercellular communication, protecting against macromolecular damage, delaying stem cell aging, modulating mitochondrial function, regulating transcription, and lowering telomere attrition and senescence. These characteristics make metformin an attractive gerotherapeutic to translate to human trials.

Diagnostic Accuracy of Single-Phase Computed Tomography Texture Analysis for Prediction of LI-RADS v2018 Category.

OBJECTIVE: The aim of this study was to determine if texture analysis can classify liver observations likely to be hepatocellular carcinoma based on the Liver Imaging Reporting and Data System (LI-RADS) using single portal venous phase computed tomography. METHODS: This research ethics board-approved retrospective cohort study included 64 consecutive LI-RADS observations. Individual observation texture analysis features were compared using Kruskal-Wallis and 2 sample t tests. Logistic regression was used for prediction of LI-RADS group. Diagnostic accuracy was assessed using receiver operating characteristic curves and Youden method. RESULTS: Multiple texture features were associated with LI-RADS including the mean HU (P = 0.003), median (P = 0.002), minimum (P = 0.010), maximum (P = 0.013), standard deviation (P = 0.009), skewness (P = 0.007), and entropy (P < 0.001). On logistic regression, LI-RADS group could be predicted with area under the curve, sensitivity, and specificity of 0.98, 96%, and 100%, respectively. CONCLUSIONS: Texture analysis features on portal venous phase computed tomography can identify liver observations likely to be hepatocellular carcinoma, which may preclude the need to recall some patients for additional multiphase imaging.

Hypovascular pancreas head adenocarcinoma: CT texture analysis for assessment of resection margin status and high-risk features.

OBJECTIVES: To determine if CT texture analysis features are associated with hypovascular pancreas head adenocarcinoma (PHA) postoperative margin status, nodal status, grade, lymphovascular invasion (LVI), and perineural invasion (PNI). METHODS: This Research Ethics Board-approved retrospective cohort study included 131 consecutive patients with resected PHA. Tumors were segmented on preoperative contrast-enhanced CT. Tumor diameter and texture analysis features including mean, minimum and maximum Hounsfield units, standard deviation, skewness, kurtosis, and entropy and gray-level co-occurrence matrix (GLCM) features correlation and dissimilarity were extracted. Two-sample t test and logistic regression were used to compare parameters for prediction of margin status, nodal status, grade, LVI, and PNI. Diagnostic accuracy was assessed using receiver operating characteristic curves and Youden method was used to establish cutpoints. RESULTS: Margin status was associated with GLCM correlation (p = 0.012) and dissimilarity (p = 0.003); nodal status was associated with standard deviation (p = 0.026) and entropy (p = 0.031); grade was associated with kurtosis (p = 0.031); LVI was associated with standard deviation (p = 0.047), entropy (p = 0.026), and GLCM correlation (p = 0.033) and dissimilarity (p = 0.011). No associations were found for PNI (p > 0.05). Logistic regression yielded an area under the curve of 0.70 for nodal disease, 0.70 for LVI, 0.68 for grade, and 0.65 for margin status. Optimal sensitivity/specificity was as follows: nodal disease 73%/72%, LVI 72%/65%, grade 55%/83%, and margin status 63%/66%. CONCLUSIONS: CT texture analysis features demonstrate fair diagnostic accuracy for assessment of hypovascular PHA nodal disease, LVI, grade, and postoperative margin status. Additional research is rapidly needed to identify these high-risk features with better accuracy. KEY POINTS: • CT texture analysis features are associated with pancreas head adenocarcinoma postoperative margin status which may help inform treatment decisions as a negative resection margin is required for cure. • CT texture analysis features are associated with pancreas head adenocarcinoma nodal disease, a poor prognostic feature. • Indicators of more aggressive pancreas head adenocarcinoma biology including tumor grade and LVI can be diagnosed using CT texture analysis with fair accuracy.