Deep feature based cross-slide registration

Registration of multiple sections in a tissue block is an important pre-requisite task before any cross-slide image analysis. Non-rigid registration methods are capable of finding correspondence by locally transforming a moving image. These methods often rely on an initial guess to roughly align an image pair linearly and globally. This is essential to prevent convergence to a non-optimal minimum. We explore a deep feature based registration (DFBR) method which utilises data-driven descriptors to estimate the global transformation. A multi-stage strategy is adopted for improving the quality of registration. A visualisation tool is developed to view registered pairs of WSIs at different magnifications. With the help of this tool, one can apply a transformation on the fly without the need to generate a transformed moving WSI in a pyramidal form. We compare the performance on our dataset of data-driven descriptors with that of hand-crafted descriptors. Our approach can align the images with only small registration errors. The efficacy of our proposed method is evaluated for a subsequent non-rigid registration step. To this end, the first two steps of the ANHIR winner's framework are replaced with DFBR to register image pairs provided by the challenge. The modified framework produce comparable results to those of the challenge winning team.

P-643 Long-term pregnancy outcomes in women with normogonadotropic anovulation and clomiphene failure: follow-up study of the M-ovin trial

Study question

What are the long-term outcomes after gonadotrophins versus clomiphene citrate (CC) with or without intrauterine insemination (IUI) in women with normogonadotropic anovulation and clomiphene failure?

Summary answer

The long-term cumulative chance for delivering at least one live birth is 78% for continuing CC and 84% for switching to gonadotrophins.

What is known already

CC has long been used as first line treatment for ovulation induction in women with normogonadotropic anovulation, but the best treatment for CC failure was unknown. Between 2009 and 2015, 666 women with normogonadotropic anovulation and CC failure were randomised to gonadotrophins or continued treatment with CC for another six cycles, with or without IUI. Switching to gonadotrophins increased the chance of live birth by 11% over continued treatment with CC after six failed ovulatory cycles, at a cost of €15 258 per additional live birth, while the addition of IUI did not increase live birth rates.

Study design, size, duration

We asked women that had been included in the M-ovin trial 6 to 13 years ago for consent to participate in this follow-up study. In the M-ovin trial, 666 women that failed to conceive over 6 ovulatory cycles had been allocated to switching to gonadotrophins versus continuing treatment with CC.

Participants/materials, setting, methods

The participating women were asked to complete a web-based questionnaire. The primary outcome of this study was cumulative live birth. Secondary outcomes included fertility treatments, clinical pregnancies, multiple pregnancies, miscarriage, stillbirth, ectopic pregnancy, neonatal outcomes and pregnancy complications.

Main results and the role of chance

We managed to contact 570 women of the 666 (85.6%) and retrieved follow-up data for 347 women of whom 176 had been originally allocated to gonadotrophins and 171 to CC. After a median follow-up time of 8 years (range 6-13), 148 women had a live birth (84.1%) in the gonadotrophin group and 133 women had a live birth (77.8%) in the CC group (RR 1.40 95% CI 0.90 – 2.17). A second live birth occurred in 80 of 176 women (45.5%) in the gonadotrophin group and in 77 of 171 women in the CC group (45.0%) (RR 1.01, 95% CI 0.83 – 1.22). A third live birth occurred in 7 of 176 women (4.0%) in the gonadotrophin group and in 11 of 171 women (6.4%) in the CC group. The use of fertility treatments in the follow-up period was comparable between both groups. The number of twin pregnancies were also comparable.

Limitations, reasons for caution

In 10.7% of the women, most having a follow-up period above 10 years, contact details had been lost. Therefore, not all eligible women could be approached to participate in this study. It should be realised that preliminary results are presented.

Wider implications of the findings

In women with normogonadotropic anovulation and CC failure, continuous treatment with CC for another six cycles is an effective alternative in view of the long-term live birth rates, without the extra costs of gonadotrophins.

Trial registration number

This follow-up study was registered in the OSF Register, https://osf.io/pf24m. The original M-ovin trial was registered in the Netherlands Trial Register, number NTR1449.

POS1422 USE OF DISEASE MODIFYING ANTI-RHEUMATIC DRUGS AND RISK OF MULTIPLE MYELOMA IN PERSONS WITH RHEUMATOID ARTHRITIS

Background

Biologic therapies used in the management of rheumatoid arthritis (RA) target several cytokines that have been implicated in the pathogenesis of multiple myeloma (MM). Yet little is known about the association between use of biologic or targeted synthetic disease modifying anti-rheumatic drugs (b or tsDMARDs) in RA and the incidence of MM.

Objectives

Our objective was to estimate the association between b/tsDMARD use and the risk of MM among persons with RA using Veterans Health Administration (VHA) data. We hypothesized that b-/tsDMARD use is associated with a lower incidence of MM compared with conventional synthetic DMARDs (csDMARDs).

Methods

In this retrospective cohort study, we identified patients >18 years of age diagnosed with RA in any United States VHA facility from 1/1/2002 and 12/31/2018. All patients met the following inclusion criteria: 1) two or more International Classification of Diseases Version 9 or 10 (ICD9 or ICD10) codes for RA at least 7 days apart but no more than 365 days apart 2) a prescription for a csDMARD within 90 days of the first RA diagnosis 3) one inpatient or outpatient visit 30 days to 2 years preceding first RA diagnosis (indicating a regular user of VHA). Medication data was derived from the outpatient prescription fills, bar coded medication administration (BCMA), and intravenous (IV) data domains. The csDMARDs included in these analyses were: methotrexate, sulfasalazine, leflunomide, and hydroxychloroquine. The bDMARDs included were tumor necrosis factor inhibitors (TNFi) and non-TNFi biologics such as tocilizumab, rituximab, abatacept, and biosimilars; tsDMARD was tofacitinib. Patients with MM before the diagnosis of RA were excluded. Incident MM was determined by 1 or more ICD9/10 code or ICD-oncology codes. Multivariable Cox proportional hazards model were performed to estimate the hazard ratio for developing MM among those during and following the use of a b-/tsDMARD relative to b-/tsDMARD-naïve persons adjusting for age, gender, race, and ethnicity.

Results

27,540 veterans with RA met study eligibility criteria, of whom 8,322 (30%) had taken a b-/tsDMARD. Over the study period there were 77 incident MM over a total of 192,000 person years. There were 55 events in users of csDMARDs, an incidence rate (IR) of 0.40 (95% CI 0.30-0.52) per 1000 person-years and 22 in persons currently or formerly using b-/tsDMARDs (IR 0.41, 0.25-0.61 per 1000 person years). The unadjusted hazard ratio for MM following bDMARD use relative to csDMARD only use was 1.04 (0.63, 1.73), which increased to 1.28 (0.76, 2.16) after adjusting for demographic characteristics (Table 1).

Table 1.

Multivariable Cox proportional hazards model for association between use of disease modifying anti-rheumatic drugs and incident multiple myeloma.

Clinical characteristicHazards ratio (95% CI)csDMARDReferenceb-/tsDMARD use1.28 (0.76-2.16)Age*1.04 (1.02-1.07)Female0.58 (0.20-1.62)RaceReferenceWhite2.11 (1.15-3.86)Black0.70 (0.10-5.08)OtherHispanic Ethnicity0.71 (0.17-2.92)

Abbreviations: b-/tsDMARD- biologic or targeted synthetic disease modifying anti-rheumatic drug; CI: confidence interval

*Hazards ratio reflects risk per every 1-year increase in age

Model adjusted for age, gender, race, and ethnicity

Conclusion

In this nationwide VA study, we did not observe an association between bDMARD use and the incidence of MM. Of note, the median interval from initiation of a bDMARD to the end of follow-up was approximately 5.8 years, which does not allow for an examination of a possible longer term influence.

Disclosure of Interests

None declared

POS1434 USE OF BIOLOGIC OR TARGETED SYNTHETIC DISEASE MODIFYING ANTI-RHEUMATIC DRUGS AND THE RISK OF LYMPHOMA IN RHEUMATOID ARTHRITIS

Background

Epidemiologic studies suggest that disease duration and degree of inflammatory activity of rheumatoid arthritis (RA) contribute to lymphoma development (1). Whether the decrease in inflammatory burden seen with use of biologic or targeted synthetic disease modifying anti-rheumatic drugs (bDMARDs or tsDMARDs) translates into a lower risk of lymphoma in RA needs to be studied.

Objectives

The objective of our study was to examine the effect of administration of b/tsDMARDS on the incidence of lymphoma relative to conventional synthetic DMARDs (csDMARDs) in an inception cohort of Veterans with RA.

Methods

We identified patients >18 years of age diagnosed with RA in any US Veterans Affairs (VA) facility from 1/1/2002 and 12/31/2018 using the VA Corporate Data Warehouse (CDW). To be included, each patient was required to meet the following criteria: 2+ RA diagnostic codes at least 7 days apart but no more than 365 days apart; 2) a prescription for a csDMARD within 90 days of the first RA diagnosis; and 3) an inpatient or outpatient visit 30 days to 2 years preceding first RA diagnosis (indicating they are a regular user of the VA). The csDMARDs included in these analyses were: methotrexate, sulfasalazine, leflunomide, and hydroxychloroquine. The bDMARDs included were tumor necrosis factor inhibitors (TNFi) and non-TNFi biologics such as tocilizumab, rituximab, abatacept, and biosimilars; tsDMARD was tofacitinib. Patients with prevalent lymphoma were excluded. Lymphoma diagnoses were identified using International Classification of Diseases Version 9, 10 and Oncology (ICD9, ICD10, ICDO) codes.

We used marginal structural models as described by Hernan et al (2) and time-varying Cox models to control for confounding by indication while evaluating this association. We adjusted for baseline demographics (age, sex, race, ethnicity, year of cohort entry, rheumatology visits), and time-varying CRP and time-varying Rheumatoid Disease Comorbidity Index (RDCI) (3) to control for confounding.

Results

27,421 Veterans with RA met our eligibility criteria. Most of the Veterans (56%) were in the age range 61-80 years old; 89% male, 76% White, 14% African American. 8,225 (30%) patients were treated with a b-/tsDMARD. The crude incidence rates were 1.71 (95% CI 1.5-1.94) per 1000 person-years for those only on csDMARDs and 1.78 (95% CI 1.44-2.18) for patients during or following use of a b/tsDMARDs. After adjustment with both time-fixed and time-varying covariates using marginal structural models, the incidence of lymphoma was not different between patients who did and did not use a b/tsDMARD (hazard ratio=1.06, 95% CI= 0.82-1.37) (Table 1).

Table 1.

Estimates of Effect of bDMARD or tsDMARD use on Lymphoma relative to use of csDMARDs

Marginal Structural Models; adjusted for:@Demographics1.04(0.80, 1.34)#Demographics + CRP1.06(0.82, 1.37)

* per 1000 person-years

@Demographics = age, gender, race, ethnicity, rheumatology visits, and year of cohort entry

#Adjusts for CRP, baseline rheumatology visits (yes/no) and RDCI.

CRP = C-Reactive Protein, RDCI = Rhematic Disease Comorbidity Index, CI = Confidence Interval, b/tsDMARD = biologic or targeted synthetic DMARD, csDMARD = conventional synthetic DMARD

Conclusion

In this large study using the nationwide VA data, we did not observe an association between the use of b/ts DMARDs and an increased risk of lymphoma.

References

[1]Baecklund E, Iliadou A, Askling J, Ekbom A, Backlin C, Granath F, et al. Association of chronic inflammation, not its treatment, with increased lymphoma risk in rheumatoid arthritis. Arthritis Rheum. 2006;54(3):692-701.

[2]Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11(5):550-60.

[3]England BR, Sayles H, Mikuls TR, Johnson DS, Michaud K. Validation of the rheumatic disease comorbidity index. Arthritis care & research. 2015;67(6):865-72.

Disclosure of Interests

None declared

Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue

Many physiological processes and pathological phenomena in the liver tissue are spatially heterogeneous. At a local scale, biomarkers can be quantified along the axis of the blood flow, from portal fields (PFs) to central veins (CVs), i.e., in zonated form. This requires detecting PFs and CVs. However, manually annotating these structures in multiple whole-slide images is a tedious task. We describe and evaluate a fully automated method, based on a convolutional neural network, for simultaneously detecting PFs and CVs in a single stained section. Trained on scans of hematoxylin and eosin-stained liver tissue, the detector performed well with an F1 score of 0.81 compared to annotation by a human expert. It does, however, not generalize well to previously unseen scans of steatotic liver tissue with an F1 score of 0.59. Automated PF and CV detection eliminates the bottleneck of manual annotation for subsequent automated analyses, as illustrated by two proof-of-concept applications: We computed lobulus sizes based on the detected PF and CV positions, where results agreed with published lobulus sizes. Moreover, we demonstrate the feasibility of zonated quantification of biomarkers detected in different stainings based on lobuli and zones obtained from the detected PF and CV positions. A negative control (hematoxylin and eosin) showed the expected homogeneity, a positive control (glutamine synthetase) was quantified to be strictly pericentral, and a plausible zonation for a heterogeneous F4/80 staining was obtained. Automated detection of PFs and CVs is one building block for automatically quantifying physiologically relevant heterogeneity of liver tissue biomarkers. Perspectively, a more robust and automated assessment of zonation from whole-slide images will be valuable for parameterizing spatially resolved models of liver metabolism and to provide diagnostic information.

EMPAIA App Interface: An open and vendor-neutral interface for AI applications in pathology

BACKGROUND AND OBJECTIVE

Artificial intelligence (AI) apps hold great potential to make pathological diagnoses more accurate and time efficient. Widespread use of AI in pathology is hampered by interface incompatibilities between pathology software. We studied the existing interfaces in order to develop the EMPAIA App Interface, an open standard for the integration of pathology AI apps.

METHODS

The EMPAIA App Interface relies on widely-used web communication protocols and containerization. It consists of three parts: A standardized format to describe the semantics of an app, a mechanism to deploy and execute apps in computing environments, and a web API through which apps can exchange data with a host application.

RESULTS

Five commercial AI app manufacturers successfully adapted their products to the EMPAIA App Interface and helped improve it with their feedback. Open source tools facilitate the adoption of the interface by providing reusable data access and scheduling functionality and enabling automatic validation of app compliance.

CONCLUSIONS

Existing AI apps and pathology software can be adapted to the EMPAIA App Interface with little effort. It is a viable alternative to the proprietary interfaces of current software. If enough vendors join in, the EMPAIA App Interface can help to advance the use of AI in pathology.

Toxic-metabolic encephalopathy in adults: Critical discussion and pragmatical diagnostic approach

Toxic-metabolic encephalopathy (TME) results from an acute cerebral dysfunction due to different metabolic disturbances including medications or illicit-drugs. It can lead to altered consciousness, going from delirium to coma, which may require intensive care and invasive mechanical ventilation. Even if it is a life-threatening condition, TME might have an excellent prognosis if its etiology is rapidly identified and treated adequately. This review summarizes the main etiologies, their differential diagnosis, and diagnostic strategy and management of TME with a critical discussion on the definition of TME.

Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis

In the glomerulus, Bowman's space is formed by a continuum of glomerular epithelial cells. In focal segmental glomerulosclerosis (FSGS), glomeruli show segmental scarring, a result of activated parietal epithelial cells (PECs) invading the glomerular tuft. The segmental scars interrupt the epithelial continuum. However, non-sclerotic segments seem to be preserved even in glomeruli with advanced lesions. We studied the histology of the segmental pattern in Munich Wistar Frömter rats, a model for secondary FSGS. Our results showed that matrix layers lined with PECs cover the sclerotic lesions. These PECs formed contacts with podocytes of the uninvolved tuft segments, restoring the epithelial continuum. Formed Bowman's spaces were still connected to the tubular system. In biopsies of patients with secondary FSGS, we also detected matrix layers formed by PECs, separating the uninvolved from the sclerotic glomerular segments. PECs have a major role in the formation of glomerulosclerosis; we show here that in FSGS they also restore the glomerular epithelial cell continuum that surrounds Bowman's space. This process may be beneficial and indispensable for glomerular filtration in the uninvolved segments of sclerotic glomeruli.

Summary: Histological analysis of rat and human kidneys reveals a novel role for parietal epithelial cells (PECs) in glomerulosclerosis. PECs seem to restore the glomerular epithelial continuum, which may avert further loss of glomerular function.

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

OBJECTIVES

To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.

METHODS

CTA exams of the aorta of 191 patients (68.1 ± 14 years, 128 male), performed between 2015 and 2018, were retrospectively identified from our imaging archive and manually segmented by two investigators. A 3D U-Net model was trained on the data, which was divided into a training, a validation, and a test group at a ratio of 7:1:2. Cases in the test group (n = 41) were evaluated to compare manual and automatic segmentations. Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff surface distance (HSD) were extracted. Maximum diameter, effective diameter, and area were quantified and compared between both segmentations at eight anatomical landmarks, and at the maximum area of an aneurysms if present (n = 14). Statistics included error calculation, intraclass correlation coefficient, and Bland-Altman analysis.

RESULTS

A DSC of 0.95 [0.94; 0.95] and an MSD of 0.76 [0.06; 0.99] indicated close agreement between segmentations. HSD was 8.00 [4.47; 10.00]. The largest absolute errors were found in the ascending aorta with 0.8 ± 1.5 mm for maximum diameter and at the coeliac trunk with - 30.0 ± 81.6 mm² for area. Results for absolute errors in aneurysms were - 0.5 ± 2.3 mm for maximum diameter, 0.3 ± 1.6 mm for effective diameter, and 64.9 ± 114.9 mm² for area. ICC showed excellent agreement (> 0.9; p < 0.05) between quantitative measurements.

CONCLUSIONS

Automated segmentation of the aorta on CTA data using a deep learning algorithm is feasible and allows for accurate quantification of the aortic lumen even if the vascular architecture is altered by disease.

KEY POINTS

• A deep learning-based algorithm can automatically segment the aorta, mostly within acceptable margins of error, even if the vascular architecture is altered by disease. • Quantifications performed in the segmentations were mostly within clinically acceptable limits, even in pathologically altered segments of the aorta.

POS0287 USE OF BIOLOGIC DISEASE MODIFYING ANTI-RHEUMATIC DRUGS IN RELATION TO THE RISK OF LYMPHOMA: A COHORT STUDY OF US VETERANS WITH RHEUMATOID ARTHRITIS

Background:

Epidemiologic studies suggest that disease duration and degree of inflammatory activity of rheumatoid arthritis (RA) contribute to lymphoma development. However, the association of the use of biologic disease modifying anti-rheumatic drugs (bDMARDs) in patients with RA on lymphoma risk needs further evaluation.

Objectives:

Examine the effect of administration of bDMARDS on the incidence of lymphoma in an inception cohort of RA.

Methods:

We identified patients diagnosed with RA in any US Veterans Affairs (VA) facility from 1/1/2002 and 12/31/2018 using the Veteran’s Health Administration (VHA) databases. To be included, each patient was required to meet the following criteria: 1) 2+ RA diagnostic codes at least 7 days apart but no more than 365 days apart 2) a prescription for a conventional synthetic DMARD (csDMARD) within 90 days of the first RA diagnosis 3) One inpatient or outpatient visit 30 days to 2 years preceding first RA diagnosis (indicating they are a regular user of the VHA). We excluded patients for any of the following if they preceded the first RA diagnosis: 1) a prior single RA diagnostic code 2) a prescription for any DMARD medication 3) a concomitant diagnosis of another inflammatory arthritis (e.g. psoriatic arthropathy) 4) a diagnosis of lymphoma. Index date for the study is the date of the first qualifying RA diagnosis. Lymphoma diagnoses were identified through VHA records using the International Classification of Diseases-Oncology codes.

Results:

We identified 27,536 veterans with RA in the study period meeting the inclusion and exclusion criteria. Of these, 53% (n=14,705) were in the age range 60 to 80 years. The cohort was 89% male, 75.5% White, 13.7% African American. Over the study period, 1.2% (n=332) of the study population developed a lymphoma.

Conclusion:

Using the nationwide VHA we have identified a large inception cohort of patients with RA of whom 1.2% developed lymphoma over study follow-up. This data will be used in future analyses to produce estimates of the effect of biologic medications on lymphoma risk, adjusting for confounding by indication and other variables.

Table 1.

Baseline characteristics of the cohort based on bDMARD exposure status

CharacteristicbDMARD-naive (n= 19,095)bDMARD-exposed (n=8,441)Overall Lymphomas Age (years)171161 18-4046 40-606378 60-8010074 >8043 Males17,206 (90%)7,270 (86%)Race White14,150 (74%)6,627 (76%) Black2,674 (14%)1,090 (13%) Asian96 (0.5%)46 (0.5%) Native American or Pacific Islander371 (2%)187 (2.2%) Missing1,804 (9%)491 (6%)

Acknowledgements:

The work in this abstract is supported by Investigator Award from the Rheumatology Research Foundation to Dr Singh.

Disclosure of Interests:

None declared

Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics

The tumour microenvironment has been shown to be a valuable source of prognostic information for different cancer types. This holds in particular for triple negative breast cancer (TNBC), a breast cancer subtype for which currently no prognostic biomarkers are established. Although different methods to assess tumour infiltrating lymphocytes (TILs) have been published, it remains unclear which method (marker, region) yields the most optimal prognostic information. In addition, to date, no objective TILs assessment methods are available. For this proof of concept study, a subset of our previously described TNBC cohort (n = 94) was stained for CD3, CD8 and FOXP3 using multiplex immunohistochemistry and subsequently imaged by a multispectral imaging system. Advanced whole-slide image analysis algorithms, including convolutional neural networks (CNN) were used to register unmixed multispectral images and corresponding H&E sections, to segment the different tissue compartments (tumour, stroma) and to detect all individual positive lymphocytes. Densities of positive lymphocytes were analysed in different regions within the tumour and its neighbouring environment and correlated to relapse free survival (RFS) and overall survival (OS). We found that for all TILs markers the presence of a high density of positive cells correlated with an improved survival. None of the TILs markers was superior to the others. The results of TILs assessment in the various regions did not show marked differences between each other. The negative correlation between TILs and survival in our cohort are in line with previous studies. Our results provide directions for optimizing TILs assessment methodology.

Artificial Intelligence in Pathology: From Prototype to Product

Modern image analysis techniques based on artificial intelligence (AI) have great potential to improve the quality and efficiency of diagnostic procedures in pathology and to detect novel biomarkers. Despite thousands of published research papers on applications of AI in pathology, hardly any research implementations have matured into commercial products for routine use. Bringing an AI solution for pathology to market poses significant technological, business, and regulatory challenges. In this paper, we provide a comprehensive overview and advice on how to meet these challenges. We outline how research prototypes can be turned into a product-ready state and integrated into the IT infrastructure of clinical laboratories. We also discuss business models for profitable AI solutions and reimbursement options for computer assistance in pathology. Moreover, we explain how to obtain regulatory approval so that AI solutions can be launched as in vitro diagnostic medical devices. Thus, this paper offers computer scientists, software companies, and pathologists a road map for transforming prototypes of AI solutions into commercial products.

Do European patients with peripeheral arterial disease receive optimal lipid lowering therapy and achieve LDL-C goals? Results from the DA VINCI study

Background

2016 and 2019 EAS/ESC dyslipidemia guidelines recommend lipid lowering therapy (LLT) to reduce LDL-C in patients with peripheral arterial disease (PAD) with or without established cardiovascular (CV) disease, and recommend target LDL-C goals based on individual CV risk. Data regarding the implementation of these guidelines in clinical practice across Europe is currently lacking.

Purpose

Describe LLT and achievement of the target LDL-C goals recommended in EAS/ESC dyslipidemia guidelines in patients with PAD.

Methods

The cross-sectional Da Vinci study enrolled consenting adults who had received LLT in the 12 months prior to the study visit and had at least one LDL-C measurement in the 14 months prior to the study visit, seen in a primary or secondary care setting across 18 European countries. Patients with coronary, peripheral and cerebral disease were enrolled at a ratio of 1:2:2. FH patients with prior CV events were excluded. Data were collected from medical records at a single visit between Jun '17–Nov '18, including LLT and most recent LDL-C. Primary outcome was LDL-C goal attainment ≥28 days after starting most recent LLT (treatment-stabilised LLT).

Results

Of 5888 patients enrolled, 2794 met our definition of atherosclerotic cardiovascular disease (ASCVD). Of these ASCVD patients, 1036 (37%) had PAD. 31% (323/1036) of PAD patients were female and mean (SD) age was 69 (9.4) years. Concomitant CV risk factors included diabetes mellitus (473/1036 patients [46%]), hypertension (809/1036 [78%]) and smoking (794/1036 [77%]). 26% (271/1036) of patients with PAD also had coronary vascular disease and 12% (122/1036) also had cerebrovascular disease. At the visit date, approximately half (497/1036 [48%]) of all PAD patients were receiving moderate intensity statins and 41% (421/1036) were receiving high intensity statins. 818 (73%) of the PAD patients had a treatment-stabilised LDL-C measurement (median, 2.20 mmol/L), of whom 40% (326/818) achieved the 2016 EAS/ESC LDL-C goal of 1.8 mmol/L and only 19% (159/818) achieved the 2019 goal of 1.4mmol/L.

Conclusions

European patients with PAD are not treated as per EAS/ESC recommendations, with a large proportion receiving suboptimal LLT and fewer than half achieving target LDL-C levels.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Amgen

ANHIR: Automatic Non-Rigid Histological Image Registration Challenge

Automatic Non-rigid Histological Image Registration (ANHIR) challenge was organized to compare the performance of image registration algorithms on several kinds of microscopy histology images in a fair and independent manner. We have assembled 8 datasets, containing 355 images with 18 different stains, resulting in 481 image pairs to be registered. Registration accuracy was evaluated using manually placed landmarks. In total, 256 teams registered for the challenge, 10 submitted the results, and 6 participated in the workshop. Here, we present the results of 7 well-performing methods from the challenge together with 6 well-known existing methods. The best methods used coarse but robust initial alignment, followed by non-rigid registration, used multiresolution, and were carefully tuned for the data at hand. They outperformed off-the-shelf methods, mostly by being more robust. The best methods could successfully register over 98% of all landmarks and their mean landmark registration accuracy (TRE) was 0.44% of the image diagonal. The challenge remains open to submissions and all images are available for download.

Passage of uranium through human cerebral microvascular endothelial cells: influence of time exposure in mono- and co-culture in vitro models

PURPOSE

Depleted uranium (DU) has several civilian and military applications. The effects of this emerging environmental pollutant on human health raise some concerns. Previous experimental studies have shown that uranium (U) exposure can disturb the central nervous system. A small quantity of U reaches the brain via the blood, but the effects on the blood-brain barrier (BBB) remain unclear.

MATERIALS AND METHODS

In the present work, two cell culture models were exposed to DU for different times to study its cytotoxicity, paracellular permeability and extracellular concentration of U. The well-known immortalized human cerebral microvascular endothelial cells, hCMEC/D3, were cultured on the filter in the first model. In the second model, human primary cells of pericytes were cultured under the filter to understand the influence of cell environment after U exposure.

RESULTS

The results show that U is not cytotoxic to hCMEC/D3 cells or pericytes until 500 µM (1.6 Bq.L^-1). In addition, acute or chronic low-dose exposure of U did not disturb permeability and was conserved in both cell culture models. However, U is able to reach the brain compartment. During the first hours of exposure, the passage of U to the abluminal compartment was significantly reduced in the presence of pericytes. Electronic microscopy studies evidenced the formation of needlelike structures, like urchin-shaped precipitates, from 1 h of exposure. Analytical microscopy confirmed the U composition of these precipitates. Interestingly, precipitated U was detected only in endothelial cells and not in pericytes. U was localized in multilamellar or multivesicular bodies along the endo-lysosomal pathway, suggesting the involvement of these traffic vesicles in U sequestration and/or elimination.

CONCLUSIONS

We show for the first time the in vitro passage of U across a human cerebral microvascular endothelial cells, and the intracellular localization of U precipitates without any cytotoxicity or modification of paracellular permeability. The difference between the results obtained with monolayers and co-culture models with pericytes illustrates the need to use complex in vitro models in order to mimic the neurovascular unit. Further in vivo studies should be performed to better understand the passage of U across the blood-brain barrier potentially involved in behavioral consequences.

Atypical Deep Cerebral Vein Thrombosis with Hemorrhagic Venous Infarction in a Patient Positive for COVID-19

There is growing evidence that Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) has a neurotropic and neuroinvasive potential. In particular, neurologic complications associated with the infection by SARS-CoV-2 include strokes that may result from a dysregulated inflammatory response to the infection. We report an atypical deep cerebral vein thrombosis complicated with hemorrhagic venous infarction in a patient positive for SARS-CoV-2 with no risk factors for thrombosis.

Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard

Given the importance of gland morphology in grading prostate cancer (PCa), automatically differentiating between epithelium and other tissues is an important prerequisite for the development of automated methods for detecting PCa. We propose a new deep learning method to segment epithelial tissue in digitised hematoxylin and eosin (H&E) stained prostatectomy slides using immunohistochemistry (IHC) as reference standard. We used IHC to create a precise and objective ground truth compared to manual outlining on H&E slides, especially in areas with high-grade PCa. 102 tissue sections were stained with H&E and subsequently restained with P63 and CK8/18 IHC markers to highlight epithelial structures. Afterwards each pair was co-registered. First, we trained a U-Net to segment epithelial structures in IHC using a subset of the IHC slides that were preprocessed with color deconvolution. Second, this network was applied to the remaining slides to create the reference standard used to train a second U-Net on H&E. Our system accurately segmented both intact glands and individual tumour epithelial cells. The generalisation capacity of our system is shown using an independent external dataset from a different centre. We envision this segmentation as the first part of a fully automated prostate cancer grading pipeline.

[Metabolic encephalopathies]

Metabolic encephalopathies (ME) are a common cause of admission to emergency rooms, to hospitalization wards or to intensive care units. They could account for 10 to 20% of causes of comatose states in ICU and could be associated to a poor outcome especially in older patients. Nevertheless, they are often reversible and are associated with a favorable outcome when diagnosed and rapidly treated. They correspond to an altered brain functioning secondary to the deficiency of a substance that is mandatory for the normal brain functioning or to the accumulation of a substance that can be either endogenous or exogenous. It preferably occurs in co-morbid patients, complicating its diagnosis and its management. Altered brain functioning, going from mild neuropsychological impairment to coma, movement disorders especially myoclonus and the absence of any obvious differential diagnosis are highly suggestive of the diagnosis. Whereas some biological samplings and brain MRI are essential to rule out differential diagnosis, some others, such as electroencephalogram, may be able to propose important clues in favor of the diagnosis. Once simple symptomatic measures are introduced, the treatment consists mainly in the correction of the cause. Specific treatment options are only seldom available for ME; this is the case for hepatic encephalopathy and some drug-induced encephalopathies. We will successively describe in this review the main pathophysiological mechanisms, the main causes, favoring circumstances of ME, the differential diagnosis to rule out and the etiological work-up for the diagnosis. Finally, a diagnostic and therapeutic strategy for the care of patients with ME will be proposed.

Data-Driven Discovery of Immune Contexture Biomarkers

Background: Features characterizing the immune contexture (IC) in the tumor microenvironment can be prognostic and predictive biomarkers. Identifying novel biomarkers can be challenging due to complex interactions between immune and tumor cells and the abundance of possible features. Methods: We describe an approach for the data-driven identification of IC biomarkers. For this purpose, we provide mathematical definitions of different feature classes, based on cell densities, cell-to-cell distances, and spatial heterogeneity thereof. Candidate biomarkers are ranked according to their potential for the predictive stratification of patients. Results: We evaluated the approach on a dataset of colorectal cancer patients with variable amounts of microsatellite instability. The most promising features that can be explored as biomarkers were based on cell-to-cell distances and spatial heterogeneity. Both the tumor and non-tumor compartments yielded features that were potentially predictive for therapy response and point in direction of further exploration. Conclusion: The data-driven approach simplifies the identification of promising IC biomarker candidates. Researchers can take guidance from the described approach to accelerate their biomarker research.

Deep learning nuclei detection: A simple approach can deliver state-of-the-art results

BACKGROUND

Deep convolutional neural networks have become a widespread tool for the detection of nuclei in histopathology images. Many implementations share a basic approach that includes generation of an intermediate map indicating the presence of a nucleus center, which we refer to as PMap. Nevertheless, these implementations often still differ in several parameters, resulting in different detection qualities.

METHODS

We identified several essential parameters and configured the basic PMap approach using combinations of them. We thoroughly evaluated and compared various configurations on multiple datasets with respect to detection quality, efficiency and training effort.

RESULTS

Post-processing of the PMap was found to have the largest impact on detection quality. Also, two different network architectures were identified that improve either detection quality or runtime performance. The best-performing configuration yields f1-measures of 0.816 on H&E stained images of colorectal adenocarcinomas and 0.819 on Ki-67 stained images of breast tumor tissue. On average, it was fully trained in less than 15,000 iterations and processed 4.15 megapixels per second at prediction time.

CONCLUSIONS

The basic PMap approach is greatly affected by certain parameters. Our evaluation provides guidance on their impact and best settings. When configured properly, this simple and efficient approach can yield equal detection quality as more complex and time-consuming state-of-the-art approaches.

Automated quantification of steatosis: agreement with stereological point counting

BACKGROUND

Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist.

METHODS

The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability.

RESULTS

The new method showed the strongest agreement with the expert. At 20× resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10× resolution, it was more accurate than and twice as fast as all other methods at 20× resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer.

CONCLUSIONS

The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers.

An Assessment of the Primary Payer Variable among Breast and Colorectal Cancer Cases in the Massachusetts Cancer Registry, 2005-2009

The Massachusetts Cancer Registry (MCR) reviewed the medical charts of 5,348 randomly selected breast and colorectal cancer cases diagnosed from 2005 to 2009. The purpose of this study was to assess the reliability of primary payer at diagnosis in the MCR database and to examine primary payer and the first course of treatment of individual cancer patients. For the first period (2005-2006), private insurance (72.6% agreement) and Medicare (84.3% agreement) indicated strong agreement with kappa values of 0.62 and 0.72, respectively. Agreement for the later period was again stronger in the private insurance and Medicare categories (kappa= 0.63 and 0.74, respectively).

Factors Associated With Nutritional Risk Among Homebound Older Adults With Depressive Symptoms

OBJECTIVES

This study used the Evans model of public health determinants to identify factors associated with nutritional risk in older adults.

DESIGN

The Evans model domains (physical and mental well-being, social/environmental statuses, individual choice, and economic security) were measured in a sample of homebound older adults. Regularized logistic regression analysis with LASSO penalty function was used to determine the strongest domain of the Evans model. Using traditional logistic regression, individual variables across all domains were compared to identify the significant predictors.

SETTING

Older adults receiving home meal services were referred to the study by community program staff.

PARTICIPANTS

Participants included 164 homebound older adults (age > 60) who endorsed at least one gateway symptom of depression.

MEASUREMENTS

Measurements: Nutritional risk was determined using the Mini Nutritional Assessment. Domains of the Evans model were measured using the MAI Medical Condition Checklist, items from the IADL scale, the Structured Clinical Interview for DSM-IV Axis I Disorders, the Duke Social Support Index, living arrangements, marital status, the Alcohol Use Disorders Identification Test, items from the SCID Screening Module, and a self-report of perceived financial security.

RESULTS

Poor mental well-being, defined by a diagnosis of major depressive disorder, was identified as the strongest Evans model domain in the prediction of nutritional risk. When each variable was independently evaluated across domains, instrumental support (Wald’s Z=-2.24, p=0.03) and a history of drug use (Wald’s Z=-2.40, p=0.02) were significant predictors.

CONCLUSIONS

The Evans model is a useful conceptual framework for understanding nutritional health, with the mental domain found to be the strongest domain predictor of nutritional risk. Among individual variables across domains, having someone to help with shopping and food preparation and a history of drug use were associated with lower nutritional risk. These analyses highlight potential targets of intervention for nutritional risk among older adults.

[Two forms of familial hypercholesterolemia: differences in cardiovascular risk factors, cardiac and extracardiac atherosclerosis]

BACKGROUND AND AIM

The monogenetic hypercholesterolemias (HC) are associated with a very high risk of premature coronary heart disease (CHD). We sought to assess the influence of the genetic defect and the cardiovascular risk factors on the manifestation of atherosclerotic complications in two forms of genetic HC.

PATIENTS AND METHODS

Data of patients with genetically defined HC (54 LDL-receptor defective familial hypercholesterolemia (FH) and 54 familial defective apolipoprotein B (FDB)) were analysed retrospectively for cardiac and extracardiac atherosclerosis.

RESULTS

Total and LDL-cholesterol were significantly higher in FH men than in FDB men, but not so in women. 41.8% of FH patients had CHD (mean age 41 years), 5.6% of FDB (mean age 52 years). Stenoses (>50% narrowing) of the internal carotid artery were verified in 15% of FH and 4% of FDB patients. Peripheral arterial disease was found in 3 FH and 2 FDB patients. Hypertension and active smoking were allotted almost equally, body weight was normal in most of the patients (BMI ≤ 25 kg/m(2)). Conlusion: Patients with genetic HC suffer from early manifestation of cardiac disease. Patients with FH seem to be affected more often than patients with FDB. Early diagnosis and early and lifelong treatment are essential and, according to the literature, lead to a delay of disease manifestation.

[Endovascular treatment of thoracic aneurisms: indications, techniques and results]

CLINICAL ISSUE OF THORACIC ANEURYSMS: Aneurysms are among the most common diseases affecting the thoracic aorta, with a continuous increase in incidence over the recent decades. The main cause of thoracic aneurysms is atherosclerosis, which, due to the frequent lack of major symptoms and the potentially lethal complications such as ruptured aortic aneurysm, remains a challenge in clinical practice.

STANDARD RADIOLOGICAL METHODS

CT angiography remains the imaging method of choice for acute aortic aneurysms, with MR angiography being increasingly used for follow-up imaging. THRESHOLD FOR TREATMENT: In the ascending aorta a diameter larger than 5-5.5 cm (descending aorta 6.5 cm) is regarded as the threshold for treatment. THORACIC ENDOVASCULAR AORTIC REPAIR: The continuous evolution of aortic stent grafting (i.e., thoracic endovascular aortic repair [TEVAR]) since Parodi, Palmaz and Dake has led to a steep rise in stent grafting procedures in recent years.

PRACTICAL RECOMMENDATIONS

Particularly in elderly patients with multiple comorbidities, TEVAR is a valuable, less invasive option compared to open surgical repair.

Monitoring of gadolinium-BOPTA uptake into the vessel wall during magnetic resonance (MR)-guided angioplasty of the peripheral arteries with a paclitaxel/gadolinium-BOPTA-coated balloon: an experimental study at 3 Tesla

PURPOSE

The success of paclitaxel distribution within the vessel wall during paclitaxel-coated balloon angioplasty to prevent restenosis cannot be monitored under X-ray guidance. The aim of this pilot study was to demonstrate the feasibility of monitoring Gadolinium-BOPTA delivery within the vessel wall during magnetic resonance (MR)-guided paclitaxel/Gadolinium-BOPTA-coated balloon angioplasty of the peripheral arteries.

MATERIALS AND METHODS

6 pigs (47 ± 2 kg) were investigated. All experiments were performed using a 3 Tesla MR scanner. MR-guided bilateral angioplasty of the iliac arteries was performed using a paclitaxel/MR contrast agent-coated balloon catheter. The feasibility of monitoring the delivery of Gadolinium-BOPTA to the vessel wall was assessed in 4 animals. In two additional animals, bilateral stenosis was surgically induced in the iliac arteries. Delivery of paclitaxel to the vessel wall was monitored using a 3 D T1-weighted gradient echo (GE) sequence for delineation of the vessel wall. Normalized signal intensity (SI) of the vessel wall was measured before and repeatedly after the intervention for 45 min. in all animals.

RESULTS

Paclitaxel/gadolinium-BOPTA-coated balloon angioplasty was successfully accomplished in all iliac arteries (n = 12). In animals with stenosis MR-angiography demonstrated successful dilatation (n = 4). The normalized SI of the vessel wall on T1-weighted GE images significantly increased after the intervention in all animals with and without stenosis for more than 45 min. (p < 0.001).

CONCLUSION

Monitoring of Gadolinium-BOPTA into the vessel wall during MR-guided coated balloon angioplasty is feasible. This is a first step towards providing a tool for the online control of homogenous drug delivery after paclitaxel-coated balloon angioplasty.

KEY POINTS

• Monitoring of gadolinium-BOPTA uptake into the vessel wall during MR-guided coated balloon angioplasty is feasible.• Endovascular MR-guided interventions on a 3 Tesla MR scanner are feasible.• This is a first step towards providing a tool for online control of homogenous drug delivery after paclitaxel-coated balloon angioplasty.

[Update carotid artery stenosis]

Stenosis of the extracranial carotid artery is a treatable cause of ischemic stroke and can reliably be detected and graded by vascular ultrasound. The differentiation between symptomatic and asymptomatic stenosis, the perioperative risk and the estimated life expectancy of the patient guide the therapy. Therapy is based on an optimal treatment of cardiovascular risk factors and antiplatelet drugs. Revascularization using surgical carotid endarterectomy is efficient for the prevention of stroke in patients with a high grade symptomatic stenosis. Endovascular therapy using stent-protected angioplasty of the carotid artery is an alternative in patients with a higher surgical risk with low complication rates when performed in experienced centres. Patients with asymptomatic carotid artery stenosis are primarily treated conservatively and revascularization is indicated in patients with a low surgical and global cardiovascular risk.