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Contains fulltext : 232917.pdf (Publisher’s version ) (Open Access) Multi-parametric prostate MRI (mpMRI) is a powerful tool to diagnose prostate cancer, though difficult to interpret even for experienced radiologists. A common radiological procedure is to compare a magnetic resonance image with similarly diagnosed cases. To assist the radiological image interpretation process, computerized Content-Based Image Retrieval systems (CBIRs) can therefore be employed to improve the reporting workflow and increase its accuracy. In this article, we propose a new, supervised siamese deep learning architecture able to handle multi-modal and multi-view MR images with similar PIRADS score. An experimental comparison with well-established deep learning-based CBIRs (namely standard siamese networks and autoencoders) showed significantly improved performance with respect to both diagnostic (ROC-AUC), and information retrieval metrics (Precision-Recall, Discounted Cumulative Gain and Mean Average Precision). Finally, the new proposed multi-view siamese network is general in design, facilitating a broad use in diagnostic medical imaging retrieval.

Abstract Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists’ workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis. Key Points • AI systems need to ensure that the benefits of biopsy avoidance are delivered with consistent high specificities, at a range of disease prevalence. • Initial work has focused on developing systems as diagnostic supporting aids for outlining tasks, so they can be integrated into the radiologists’ workflow to support MRI-directed biopsies. • Decision support tools require a larger body of work including multicentric, multivendor studies where the clinical needs, disease prevalence, patient preferences, and clinical setting are additionally defined.

Introduction: Diagnostic evaluation of patients with a bleeding tendency remains challenging, as no disorder is identified in approximately 50% of patients. An impaired interplay of several haemostatic factors might explain bleeding phenotype in these patients. Objective: To investigate whether global haemostasis assays are able to identify haemostatic abnormalities in patients with a bleeding tendency unexplained by current diagnostic laboratory tests. Materials and methods: Patients of ≥12 years with a bleeding tendency were included from a tertiary outpatient clinic. Bleeding phenotype was assessed with the ISTH-BAT. Patients were classified as having bleeding of unknown cause (BUC) or a mild bleeding disorder (MBD) based on abnormalities assessed by routine haemostatic tests. Global haemostasis tests (rotational thromboelastometry (ROTEM), thrombin generation test (TG) and plasma clot lysis time (CLT)) were measured in all patients. The results were compared with 76 controls. Results: One hundred and eighty-one patients were included, and 60% (109/181) was classified as having BUC. BUC patients demonstrated a significantly prolonged lag time in TG (median 7.7 minutes, IQR 6.7-8.7) and a significantly prolonged CLT (median 60.5 minutes, IQR 54.7-66.1) compared to controls. No differences in ROTEM variables were found. Patients with MBD showed an impaired thrombin generation with a significantly decreased ETP (median 1024 nmol/L*min, IQR 776-1355) and peak height (median 95 nmol/L, IQR 76-138), compared to BUC patients and controls. Conclusion: No major differences were found in ROTEM and TG variables in BUC patients compared to controls. BUC patients did have a significantly prolonged clot lysis time. The underlying mechanism for this finding is unknown.

The Platelets for Neonatal Thrombocytopenia (PlaNeT-2) trial reported an unexpected overall benefit of a prophylactic platelet transfusion threshold of 25 × 109/L compared with 50 × 109/L for major bleeding and/or mortality in preterm neonates (7% absolute-risk reduction). However, some neonates in the trial may have experienced little benefit or even harm from the 25 × 109/L threshold. We wanted to assess this heterogeneity of treatment effect in the PlaNet-2 trial, to investigate whether all preterm neonates benefit from the low threshold. We developed a multivariate logistic regression model in the PlaNet-2 data to predict baseline risk of major bleeding and/or mortality for all 653 neonates. We then ranked the neonates based on their predicted baseline risk and categorized them into 4 risk quartiles. Within these quartiles, we assessed absolute-risk difference between the 50 × 109/L- and 25 × 109/L-threshold groups. A total of 146 neonates died or developed major bleeding. The internally validated C-statistic of the model was 0.63 (95% confidence interval, 0.58-0.68). The 25 × 109/L threshold was associated with absolute-risk reduction in all risk groups, varying from 4.9% in the lowest risk group to 12.3% in the highest risk group. These results suggest that a 25 × 109/L prophylactic platelet count threshold can be adopted in all preterm neonates, irrespective of predicted baseline outcome risk. Future studies are needed to improve the predictive accuracy of the baseline risk model. This trial was registered at www.isrctn.com as #ISRCTN87736839.

Simple Summary Early image-based diagnosis is crucial to improve outcomes in pancreatic ductal adenocarcinoma (PDAC) patients, but is challenging even for experienced radiologists. Artificial intelligence has the potential to assist in early diagnosis by leveraging high amounts of data to automatically detect small (

Item does not contain fulltext OBJECTIVE: To describe levels of perceived shared decision making (SDM), decisional conflict (DC), and decision regret (DR) in prenatal counseling by pregnant women, partners, neonatologists, and obstetricians regarding decision-making around imminent extreme premature birth in which a decision about palliative comfort care versus early intensive care had to be made. STUDY DESIGN: Multicenter, cross-sectional study using surveys to determine perceived SDM at imminent extreme premature birth in parents and physicians, and to determine DC and DR in parents. RESULTS: In total, 73 participants from 22 prenatal counseling sessions were included (21 pregnant women, 20 partners, 14 obstetricians, 18 neonatologists). High perceived levels of SDM were found (median 82,2), and low levels of DC (median 23,4) and DR at one month (median 12, 5). CONCLUSIONS: Reported levels of self-perceived SDM in the setting of prenatal counseling in extreme prematurity were high, by both the parents and the physicians. Levels of DC and DR were low.

Background: Many patients with suspected infection are presented to the emergency Department. Several scoring systems have been proposed to identify patients at high risk of adverse outcomes. Methods: We compared generic early warning scores (MEWS and NEWS) to the (SIRS) criteria and quick Sequential Organ Failure Assessement (qSOFA), for early risk stratification in 1400 patients with suspected infection in the ED. The primary study end point was 30-day mortality. Results: The AUROC of the NEWS score for predicting 30-day mortality was 0.740 (95% Confidence Interval 0.682-0.798), higher than qSOFA (AUROC of 0.689, 95% CI 0.615- 0.763), MEWS (AUROC 0.643 (95% CI 0.583-0.702) and SIRS (AUROC 0.586, 95%CI 0.521 – 0.651). The sensitivity was also highest for NEWS≥ 5 (sensitivity 75,8% specificity of 67,4%). Conclusion: Among patients presenting to the ED with suspected infection, early risk stratification with NEWS (cut-off of ≥5) is more sensitive for prediction of mortality than qSOFA, MEWS or SIRS, with adequate specificity.

Over 75% of severely thrombocytopenic preterm neonates receive platelet transfusions to prevent bleeding, but transfusion guidelines are based mainly on expert opinion. The aim of this review was to investigate whether platelet counts, platelet transfusions or platelet indices are associated with major bleeding in preterm neonates. We performed a systematic search of the EMBASE and MEDLINE databases until December 2017. We included randomized trials, cohort and case control studies. (Prospero: CRD42015013399). We screened 8734 abstracts and 1225 fulltexts, identifying 36 eligible studies. In 30, timing of the platelet counts or transfusions in relation to the bleeding was unclear. Of the remaining six studies, two showed that thrombocytopenia was associated with increased risk of bleeding, two showed no such assocation, and three showed lack of an association between platelet transfusions and bleeding risk. No studies assessing platelet indices were found. The study results suggest that prophylactic platelet transfusions may not reduce bleeding risk in preterm neonates.

Contains fulltext : 235582.pdf (Publisher’s version ) (Open Access) Due to the upfront role of magnetic resonance imaging (MRI) for prostate cancer (PCa) diagnosis, a multitude of artificial intelligence (AI) applications have been suggested to aid in the diagnosis and detection of PCa. In this review, we provide an overview of the current field, including studies between 2018 and February 2021, describing AI algorithms for (1) lesion classification and (2) lesion detection for PCa. Our evaluation of 59 included studies showed that most research has been conducted for the task of PCa lesion classification (66%) followed by PCa lesion detection (34%). Studies showed large heterogeneity in cohort sizes, ranging between 18 to 499 patients (median = 162) combined with different approaches for performance validation. Furthermore, 85% of the studies reported on the stand-alone diagnostic accuracy, whereas 15% demonstrated the impact of AI on diagnostic thinking efficacy, indicating limited proof for the clinical utility of PCa AI applications. In order to introduce AI within the clinical workflow of PCa assessment, robustness and generalizability of AI applications need to be further validated utilizing external validation and clinical workflow experiments.

Bleeding is frequently seen in critically ill children and is associated with increased morbidity and mortality. Fibrinogen is an essential coagulation factor for hemostasis and hypofibrinogenemia is an important risk factor for bleeding in pediatric and adult settings. Cryoprecipitate and fibrinogen concentrate are often given to critically ill children to prevent bleeding and improve fibrinogen levels, especially in the setting of surgery, trauma, leukemia, disseminated intravascular coagulopathy, and liver failure. The theoretical benefit of fibrinogen supplementation to treat hypofibrinogenemia appears obvious, yet the evidence to support fibrinogen supplementation in children is sparce and clinical indications are poorly defined. In addition, it is unknown what the optimal fibrinogen replacement product is in children and neonates or what the targets of treatment should be. As a result, there is considerable variability in practice. In this article we will review the current pediatric and applicable adult literature with regard to the use of fibrinogen replacement in different pediatric critical care contexts. We will discuss the clinical indications for fibrinogen supplementation in critically ill children and the evidence to support their use. We summarize by highlighting current knowledge gaps and areas for future research.

Background The most optimal management for patients with bleeding of unknown cause (BUC) is unknown, as limited data are available. Objective Evaluate management and outcome of surgical procedures and deliveries in patients with BUC. Materials and Methods All patients ≥12 years of age, referred to a tertiary center for a bleeding tendency, were included. Bleeding phenotype was assessed and hemostatic laboratory work-up was performed. Patients were diagnosed with BUC or an established bleeding disorder (BD). Data on bleeding and treatment during surgical procedures and delivery following diagnosis were collected. Results Of 380 included patients, 228 (60%) were diagnosed with BUC and 152 (40%) with an established BD. In 14/72 (19%) surgical procedures major bleeding occurred and 14/41 (34%) deliveries were complicated by major postpartum hemorrhage (PPH). More specifically, 29/53 (55%) of the BUC patients who underwent surgery received prophylactic treatment to support hemostasis. Despite these precautions, 4/29 (14%) experienced major bleeding. Of BUC patients not treated prophylactically, bleeding occurred in 6/24 (25%). Of pregnant women with BUC, 2/26 (8%) received prophylactic treatment during delivery, one women with and 11 (46%) women without treatment developed major PPH. Conclusion Bleeding complications are frequent in BUC patients, irrespective of pre- or perioperative hemostatic treatment. We recommend a low-threshold approach toward administration of hemostatic treatment in BUC patients, especially during delivery.

AimsPatients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality.Method and resultsWe used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existent heart disease and in-hospital mortality. 16,511 patients with COVID-19 were included (21.1% aged 66 – 75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male and often had other comorbid conditions when compared to those without. Mortality was higher in patients with cardiac disease (29.7%; n=1545 versus 15.9%; n=1797). However, following multivariable adjustment this difference was not significant (adjusted risk ratio (aRR) 1.08 [95% CI 1.02 – 1.15; p-value 0.12 (corrected for multiple testing)]). Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure aRR (1.19 [1.10 – 1.30]; p-value ConclusionConsiderable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare.

Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assistance when results from definitive viral testing are delayed. Purpose To develop and validate an artificial intelligence (AI) system to score the likelihood and extent of pulmonary COVID-19 on chest CT scans using the COVID-19 Reporting and Data System (CO-RADS) and CT severity scoring systems. Materials and Methods The CO-RADS AI system consists of three deep-learning algorithms that automatically segment the five pulmonary lobes, assign a CO-RADS score for the suspicion of COVID-19, and assign a CT severity score for the degree of parenchymal involvement per lobe. This study retrospectively included patients who underwent a nonenhanced chest CT examination because of clinical suspicion of COVID-19 at two medical centers. The system was trained, validated, and tested with data from one of the centers. Data from the second center served as an external test set. Diagnostic performance and agreement with scores assigned by eight independent observers were measured using receiver operating characteristic analysis, linearly weighted κ values, and classification accuracy. Results A total of 105 patients (mean age, 62 years ± 16 [standard deviation]; 61 men) and 262 patients (mean age, 64 years ± 16; 154 men) were evaluated in the internal and external test sets, respectively. The system discriminated between patients with COVID-19 and those without COVID-19, with areas under the receiver operating characteristic curve of 0.95 (95% CI: 0.91, 0.98) and 0.88 (95% CI: 0.84, 0.93), for the internal and external test sets, respectively. Agreement with the eight human observers was moderate to substantial, with mean linearly weighted κ values of 0.60 ± 0.01 for CO-RADS scores and 0.54 ± 0.01 for CT severity scores. Conclusion With high diagnostic performance, the CO-RADS AI system correctly identified patients with COVID-19 using chest CT scans and assigned standardized CO-RADS and CT severity scores that demonstrated good agreement with findings from eight independent observers and generalized well to external data. © RSNA, 2020 Supplemental material is available for this article.

OBJECTIVE The aim of this study was to evaluate the effect of a deep learning based computer-aided diagnosis (DL-CAD) system on radiologists' interpretation accuracy and efficiency in reading biparametric prostate magnetic resonance imaging scans. MATERIALS AND METHODS We selected 100 consecutive prostate magnetic resonance imaging cases from a publicly available data set (PROSTATEx Challenge) with and without histopathologically confirmed prostate cancer. Seven board-certified radiologists were tasked to read each case twice in 2 reading blocks (with and without the assistance of a DL-CAD), with a separation between the 2 reading sessions of at least 2 weeks. Reading tasks were to localize and classify lesions according to Prostate Imaging Reporting and Data System (PI-RADS) v2.0 and to assign a radiologist's level of suspicion score (scale from 1-5 in 0.5 increments; 1, benign; 5, malignant). Ground truth was established by consensus readings of 3 experienced radiologists. The detection performance (receiver operating characteristic curves), variability (Fleiss κ), and average reading time without DL-CAD assistance were evaluated. RESULTS The average accuracy of radiologists in terms of area under the curve in detecting clinically significant cases (PI-RADS ≥4) was 0.84 (95% confidence interval [CI], 0.79-0.89), whereas the same using DL-CAD was 0.88 (95% CI, 0.83-0.94) with an improvement of 4.4% (95% CI, 1.1%-7.7%; P = 0.010). Interreader concordance (in terms of Fleiss κ) increased from 0.22 to 0.36 (P = 0.003). Accuracy of radiologists in detecting cases with PI-RADS ≥3 was improved by 2.9% (P = 0.10). The median reading time in the unaided/aided scenario was reduced by 21% from 103 to 81 seconds (P < 0.001). CONCLUSIONS Using a DL-CAD system increased the diagnostic accuracy in detecting highly suspicious prostate lesions and reduced both the interreader variability and the reading time.

Background and ObjectiveNon-participation in colorectal cancer (CRC) screening needs to be decreased to achieve its full potential as a public health strategy. To facilitate successful implementation of CRC screening towards unscreened individuals, this study aimed to quantify the impact of screening and individual characteristics on non-participation in CRC screening.MethodsAn online discrete choice experiment partly based on qualitative research was used among 406 representatives of the Dutch general population aged 55–75 years. In the discrete choice experiment, respondents were offered a series of choices between CRC screening scenarios that differed on five characteristics: effectiveness of the faecal immunochemical screening test, risk of a false-negative outcome, test frequency, waiting time for faecal immunochemical screening test results and waiting time for a colonoscopy follow-up test. The discrete choice experiment data were analysed in a systematic manner using random-utility-maximisation choice processes with scale and/or preference heterogeneity (based on 15 individual characteristics) and/or random intercepts.ResultsScreening characteristics proved to influence non-participation in CRC screening (21.7–28.0% non-participation rate), but an individual’s characteristics had an even higher impact on CRC screening non-participation (8.4–75.5% non-participation rate); particularly the individual’s attitude towards CRC screening followed by whether the individual had participated in a cancer screening programme before, the decision style of the individual and the educational level of the individual. Our findings provided a high degree of confidence in the internal–external validity.ConclusionsThis study showed that although screening characteristics proved to influence non-participation in CRC screening, a respondent’s characteristics had a much higher impact on CRC screening non-participation. Policy makers and physicians can use our study insights to improve and tailor their communication plans regarding (CRC) screening for unscreened individuals.

Fibrinogen is a key coagulation protein, playing a critical role in hemostasis. It is the first factor to decrease to critical levels during bleeding. Hypofibrinogenemia is an important risk factor for bleeding in clinical settings, including pediatric surgery. Yet, the optimal measurement of fibrinogen levels is subject to debate, as is the critical threshold for intervention. Fibrinogen replacement may be provided by cryoprecipitate and fibrinogen concentrate. Whilst both products contain fibrinogen, they are not equivalent, each has its own advantages and disadvantages, especially for pediatric use. Unfortunately, medical literature to support fibrinogen replacement in children is limited. In this article we review the current diagnostic tools to measure fibrinogen, with respect to their use in the pediatric critical care setting. Secondly, we evaluate the different fibrinogen replacement therapies, focusing on cryoprecipitate and fibrinogen concentrate and examine their individual product characteristics, associated risks and benefits, different dosing strategies and specific pitfalls for use in children. We summarize by highlighting current knowledge gaps and areas for future research.

BACKGROUND: Surgical craniosynostosis repair in children is associated with massive blood loss and significant transfusion of blood products. Fibrinogen concentrate is claimed to be useful in reducing blood loss and transfusion requirements. OBJECTIVE: We investigated whether prophylactic administration of fibrinogen concentrate will reduce blood loss and transfusion requirements during paediatric craniofacial surgery. DESIGN: Randomised, placebo-controlled, double-blind clinical trial. SETTING: University medical centre. PATIENTS: A total of 114 infants and children up to 25 months of age (median age 10 months). INTERVENTION: Surgical craniosynostosis repair by calvarial remodelling was performed in each patient. Patients were randomised to receive prophylactic fibrinogen concentrate (Haemocomplettan P) at a mean dose of 79 mg kg-1 body weight or placebo. MAIN OUTCOME MEASURES: Primary outcome was the volume of transfused blood products. Secondary outcomes were peri-operative blood loss, duration of surgery, length of stay in the paediatric ICU, length of hospital stay, postoperative complications and adverse effects of fibrinogen concentrate infusion. RESULTS: No significant differences (P

In women at risk of developing preeclampsia, we evaluated the use of a digital health platform for telemonitoring blood pressure and symptoms combined with a minimal antenatal visit schedule.A case-control study for women with chronic hypertension, history of preeclampsia, or maternal cardiac or kidney disease. A care path was designed with reduced visits enhanced with a digital platform (SAFE@HOME) for daily blood pressure and symptom monitoring starting from 16 weeks of gestation. Home-measurements were monitored in-hospital by obstetric professionals, taking actions upon alarming results. This prospective SAFE@HOME group was compared to a retrospective control group managed without self-monitoring.Primary: healthcare consumption (number of antenatal visits, ultrasounds, admissions and diagnostics), user experiences of the platform. Secondary: maternal and perinatal outcomes.Baseline characteristics of the SAFE@HOME (n = 103) and control group (n = 133) were comparable. In the SAFE@HOME group, antenatal visits (mean 13.7 vs 16.0, p 0.001) and ultrasounds (6.3 vs 7.4, p = 0.005) were lower compared to the control group. Admissions for hypertension or suspected preeclampsia were significantly fewer in the SAFE@HOME group (2.9% versus 13.5%, p = 0.004). Telemonitoring participants were highly satisfied using the platform. No differences were observed for maternal and perinatal outcomes.Our care path including blood pressure telemonitoring for women at risk of preeclampsia allows fewer antenatal visits, ultrasounds and hypertension-related admissions. We observed no differences in perinatal outcomes. These results suggest that telemonitoring of blood pressure is feasible in a high-risk pregnant population and has the potential to profoundly change antenatal care.

Prostate cancer (PCa) is the most prevalent and one of the leading causes of cancer death among men. Multi-parametric MRI (mp-MRI) is a prominent diagnostic scan, which could help in avoiding unnecessary biopsies for men screened for PCa. Artificial intelligence (AI) systems could help radiologists to be more accurate and consistent in diagnosing clinically significant cancer from mp-MRI scans. Lack of specificity has been identified recently as one of weak points of such assistance systems. In this paper, we propose a novel false positive reduction network to be added to the overall detection system to further analyze lesion candidates. The new network utilizes multiscale 2D image stacks of these candidates to discriminate between true and false positive detections. We trained and validated our network on a dataset with 2170 cases from seven different institutions and tested it on a separate independent dataset with 243 cases. With the proposed model, we achieved area under curve (AUC) of 0.876 on discriminating between true and false positive detected lesions and improved the AUC from 0.825 to 0.867 on overall identification of clinically significant cases.

The increasing incidence of pancreatic cancer will make it the second deadliest cancer in 2030. Imaging based early diagnosis and image guided treatment are emerging potential solutions. Artificial intelligence (AI) can help provide and improve widespread diagnostic expertise and accurate interventional image interpretation. Accurate segmentation of the pancreas is essential to create annotated data sets to train AI, and for computer assisted interventional guidance. Automated deep learning segmentation performance in pancreas computed tomography (CT) imaging is low due to poor grey value contrast and complex anatomy. A good solution seemed a recent interactive deep learning segmentation framework for brain CT that helped strongly improve initial automated segmentation with minimal user input. This method yielded no satisfactory results for pancreas CT, possibly due to a sub-optimal neural network architecture. We hypothesize that a state-of-the-art U-net neural network architecture is better because it can produce a better initial segmentation and is likely to be extended to work in a similar interactive approach. We implemented the existing interactive method, iFCN, and developed an interactive version of U-net method we call iUnet. The iUnet is fully trained to produce the best possible initial segmentation. In interactive mode it is additionally trained on a partial set of layers on user generated scribbles. We compare initial segmentation performance of iFCN and iUnet on a 100CT dataset using dice similarity coefficient analysis. Secondly, we assessed the performance gain in interactive use with three observers on segmentation quality and time. Average automated baseline performance was 78% (iUnet) versus 72% (FCN). Manual and semi-automatic segmentation performance was: 87% in 15 min. for manual, and 86% in 8 min. for iUNet. We conclude that iUnet provides a better baseline than iFCN and can reach expert manual performance significantly faster than manual segmentation in case of pancreas CT. Our novel iUnet architecture is modality and organ agnostic and can be a potential novel solution for semi-automatic medical imaging segmentation in general.

Contains fulltext : 195587.pdf (Publisher’s version ) (Open Access) CONTEXT: The main difference between the available magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion platforms for prostate biopsy is the method of image registration being either rigid or elastic. As elastic registration compensates for possible deformation caused by the introduction of an ultrasound probe for example, it is expected that it would perform better than rigid registration. OBJECTIVE: The aim of this meta-analysis is to compare rigid with elastic registration by calculating the detection odds ratio (OR) for both subgroups. The detection OR is defined as the ratio of the odds of detecting clinically significant prostate cancer (csPCa) by MRI-TRUS fusion biopsy compared with systematic TRUS biopsy. Secondary objectives were the OR for any PCa and the OR after pooling both registration techniques. EVIDENCE ACQUISITION: The electronic databases PubMed, Embase, and Cochrane were systematically searched for relevant studies according to the Preferred Reporting Items for Systematic Review and Meta-analysis Statement. Studies comparing MRI-TRUS fusion and systematic TRUS-guided biopsies in the same patient were included. The quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies version 2. EVIDENCE SYNTHESIS: Eleven papers describing elastic and 10 describing rigid registration were included. Meta-analysis showed an OR of csPCa for elastic and rigid registration of 1.45 (95% confidence interval [CI]: 1.21-1.73, p

Introduction: Diamond Blackfan anemia (DBA) is an inherited bone marrow failure syndrome (IBMFS) characterized by hypoplastic anemia, congenital malformations and an increased risk to develop malignancies.Until now, treatment of DBA consists of red blood cell (RBC) transfusions, glucocorticoids (GC) and allogeneic hematopoietic stem cell transplantation in a selection of patients. Whereas RBC transfusions are the main cause of IO, elevated iron parameters have also been reported in non-transfusion-dependent DBA patients. Here we investigated the incidence and severity of IO in a well-described cohort of transfusion-dependent and non-transfusion-dependent DBA patients in order to gain more insight in the regulation of iron metabolism in DBA, and to provide clinical guiding to improve the diagnosis and management of IO in DBA. Methods: In this retrospective, observational study we have included twenty-nine pediatric and adult DBA patients for whom at least one serum ferritin level and/or MRI result was available. Ten patients (34%) were classified as transfusion-dependent (TD) (ten or more transfusions during the twelve months prior to evaluation). Non-transfusion-dependent (NTD) patients (66%) were treated with either GC, incidental transfusions or received no treatment. Transfusion burden (transfusion history) was assessed via medical records. Serum ferritin levels ≥250 ng/mL in males and ≥150 ng/mL in females were considered to be elevated. Results of MRI were expressed as liver iron content (LIC) and as cardiac T2* in milliseconds (ms). LIC ≥3 mg/g indicates significant hepatic IO, and LIC ≥7 mg/g is associated with clinical morbidity. Cardiac T2* ≤20 ms indicates significant cardiac IO. Results: In 15/29 (52%) MRI analysis of IO was performed. Hepatic IO (LIC >3 mg/g) was present in 9/29 (31%) of DBA patients, of which 8/9 (89%) had moderate to severe IO (LIC>7mg/g), despite the fact that all but one were treated with chelation therapy. Overall serum ferritin levels and LIC correlated significantly (r=0.7907, p1000 ng/mL (Figure 1A). Interestingly, in the NTD group, hepatic IO was present in 2/7 patients (29%), who both only had mildly elevated serum ferritin levels (263 ng/mL and 277 ng/mL) and were not treated with iron chelation therapy. Based on total transfusion burden since birth, patients were classified in distinct groups: nine patients who received ³10 transfusions during life (9/10) were diagnosed with hepatic IO, whilst none of the patients who received Discussion: We demonstrate that IO is common in DBA yet can be easily overlooked in NTD patients that were treated with transfusions in the past. While serum ferritin levels significantly correlated with LIC values, this parameter cannot be used exclusively to screen for IO or titrate iron chelation therapy. We conclude that in clinical practice, biochemical parameters in combination with transfusion history justify a low-threshold to perform an MRI-based evaluation of IO, and to start adequate chelation therapy. Figure 1 Figure 1. Disclosures Van Beers: Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Novartis: Research Funding; RR Mechatronics: Research Funding. Wijk: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Axcella health: Research Funding; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Purpose To compare clinically significant prostate cancer (csPCa) detection rates between magnetic resonance imaging (MRI)–transrectal ultrasound (TRUS) fusion-guided prostate biopsy (FGB) and direct in-bore MRI-guided biopsy (MRGB). Methods We performed a comparison of csPCa detection rates between FGB and MRGB. Included patients had (1) at least one prior negative TRUS biopsy; (2) a Prostate Imaging Reporting and Data System (PI-RADS) 4 or 5 lesion and (3) a lesion size of ≥8 mm measured in at least one direction. We considered a Gleason score ≥7 being csPCa. Descriptive statistics with 95% confidence intervals (CI) were used to determine any differences. Results We included 51 patients with FGB (59 PI-RADS 4 and 41% PI-RADS 5) and 227 patients with MRGB (34 PI-RADS 4 and 66% PI-RADS 5). Included patients had a median age of 69 years (IQR, 65–72) and a median PSA level of 11.0 ng/ml (IQR, 7.4–15.1) and a median age of 67 years (IQR, 61–70), the median PSA 12.8 ng/ml (IQR, 9.1–19.0) within the FGB and the MRGB group, respectively. Detection rates of csPCA did not differ significantly between FGB and MRGB, 49 vs. 61%, respectively. Conclusion We did not detect significant differences between FGB and MRGB in the detection of csPCa. The differences in detection ratios between both biopsy techniques are narrow with an increasing lesion size. This study warrants further studies to optimize selection of best biopsy modality.

Purpose To investigate whether multi-view convolutional neural networks can improve a fully automated lymph node detection system for pelvic MR Lymphography (MRL) images of patients with prostate cancer. Methods A fully automated computer-aided detection (CAD) system had been previously developed to detect lymph nodes in MRL studies. The CAD system was extended with three types of 2D multi-view convolutional neural networks (CNN) aiming to reduce false positives (FP). A 2D multi-view CNN is an efficient approximation of a 3D CNN, and three types were evaluated: a 1-view, 3-view, and 9-view 2D CNN. The three deep learning CNN architectures were trained and configured on retrospective data of 240 prostate cancer patients that received MRL images as the standard of care between January 2008 and April 2010. The MRL used ferumoxtran-10 as a contrast agent and comprised at least two imaging sequences: a 3D T1-weighted and a 3D T2*-weighted sequence. A total of 5089 lymph nodes were annotated by two expert readers, reading in consensus. A first experiment compared the performance with and without CNNs and a second experiment compared the individual contribution of the 1-view, 3-view, or 9-view architecture to the performance. The performances were visually compared using free-receiver operating characteristic (FROC) analysis and statistically compared using partial area under the FROC curve analysis. Training and analysis were performed using bootstrapped FROC and 5-fold cross-validation. Results Adding multi-view CNNs significantly (p p Conclusion Multi-view convolutional neural networks significantly reduce false positives in a lymph node detection system for MRL images, and three orthogonal views are sufficient. At the achieved level of performance, CAD for MRL may help speed up finding lymph nodes and assessing them for potential metastatic involvement.

A 66-year-old man with indolent systemic mastocytosis presented with a plaque-like cutaneous lesion at his right inguinal region. He had travelled to various African countries in the years before. Pathological examination revealed a granulomatous infiltrate surrounding eggs of Schistosoma haematobium. Ectopic cutaneous schistosomiasis was therefore diagnosed, for which he was treated with Praziquantel.

Contains fulltext : 209081.pdf (Publisher’s version ) (Open Access)

Purpose: To investigate whether atlas-based anatomical information can improve a fully automated lymph node detection system for pelvic MR lymphography (MRL) images of patients with prostate cancer. Methods: Their data set contained MRL images of 240 prostate cancer patients who had an MRL as part of their clinical work-up between January 2008 and April 2010, with ferumoxtran-10 as contrast agent. Each MRL consisted of at least a 3D T1-weighted sequence, a 3D T2*-weighted sequence, and a FLASH-3D sequence. The reference standard was created by two expert readers, reading in consensus, who annotated and interactively segmented the lymph nodes in all MRL studies. A total of 5089 lymph nodes were annotated. A fully automated computer-aided detection (CAD) system was developed to find lymph nodes in the MRL studies. The system incorporates voxel features based on image intensities, the Hessian matrix, and spatial position. After feature calculation, a GentleBoost-classifier in combination with local maxima detection was used to identify lymph node candidates. Multiatlas based anatomical information was added to the CAD system to assess whether this could improve performance. Using histogram analysis and free-receiver operating characteristic analysis, this was compared to a strategy where relative position features were used to encode anatomical information. Results: Adding atlas-based anatomical information to the CAD system reduced false positive detections both visually and quantitatively. Median likelihood values of false positives decreased significantly in all annotated anatomical structures. The sensitivity increased from 53% to 70% at 10 false positives per lymph node. Conclusions: Adding anatomical information through atlas registration significantly improves an automated lymph node detection system for MRL images.

Item does not contain fulltext BACKGROUND AND OBJECTIVE: Deterioration of nutritional status during PEG-interferon containing therapy for chronic hepatitis C can be ameliorated by preventive nutritional support. We aimed to explore whether such support also affects paid labour productivity, physical exercise and performance status. METHODS: In this prospective randomized controlled trial (J Hepatol 2012;57:1069-75), 53 patients with chronic hepatitis C had been allocated to "on demand" support (n=26: nutritional intervention if weight loss>5%) or preventive support (n=27: regular dietary advice plus energy- and protein-rich evening snack) during PEG-interferon-containing therapy. Paid labour productivity, physical exercise and performance status were evaluated at baseline, after 24 and (if applicable) after 48weeks of treatment. RESULTS: At baseline, 46% of patients performed paid labour and 62% performed some kind of physical exercise. Furthermore, most patients were able to carry out normal activity with only minor symptoms of disease (mean Karnofsky performance score: 94). Decreases of paid labour productivity (-21% vs. -70%, P=0.003), physical exercise activity (-43% vs. -87%, P=0.005) and Karnofsky performance scores (-12% vs. -24%, P

Contains fulltext : 170913.pdf (Publisher’s version ) (Open Access) PURPOSE: To evaluate MR-targeted TRUS prostate biopsy using a novel local reference augmentation method. PATIENTS AND METHODS: Tracker-based MR-TRUS fusion was applied using local reference augmentation. In contrast to conventional whole gland fusion, local reference augmentation focuses the highest registration accuracy to the region surrounding the lesion to be biopsied. Pre-acquired multi-parametric MR images (mpMRI) were evaluated using PIRADS classification. T2-weighted MR images were imported on an ultrasound machine to allow for MR-TRUS fusion. Biopsies were targeted to the most suspicious lesion area identified on mpMRI. Each target was biopsied 1-5 times. For each biopsied lesion the diameter, PIRADS and Gleason scores, visibility during fusion, and representativeness were recorded. RESULTS: Included were 23 consecutive patients with 25 MR suspicious lesions, of which 11 patients had a previous negative TRUS-guided biopsy and 12 were biopsy naive. The cancer detection rate was 64 % (Gleason score >/=6). Biopsy was negative (i.e., no Gleason score) in seven patients confirmed by follow-up in all of them (up to 18 months). After MR-TRUS fusion, 88 % of the lesions could be visualized on TRUS. The cancer detection rate increases with increasing lesion size, being 73 % for lesions larger than 10 mm. CONCLUSION: Tracker-based MR-TRUS fusion biopsy with local reference augmentation is feasible, especially for lesions with an MR maximum diameter of at least 10 mm or PIRADS 5 lesions. If this is not the case, we recommend in-bore MR-guided biopsy.

Contains fulltext : 188598.pdf (Publisher’s version ) (Open Access) Objectives: To improve information for patients and to facilitate a vaccination coverage that is in line with the EU and World Health Organization goals, we aimed to quantify how vaccination and patient characteristics impact on influenza vaccination uptake of elderly people. Methods: An online discrete choice experiment (DCE) was conducted among 1261 representatives of the Dutch general population aged 60 years or older. In the DCE, we used influenza vaccination scenarios based on five vaccination characteristics: effectiveness, risk of severe side effects, risk of mild side effects, protection duration, and absorption time. A heteroscedastic multinomial logit model was used, taking scale and preference heterogeneity (based on 19 patient characteristics) into account. Results: Vaccination and patient characteristics both contributed to explain influenza vaccination uptake. Assuming a base case respondent and a realistic vaccination scenario, the predicted uptake was 58%. One-way changes in vaccination characteristics and patient characteristics changed this uptake from 46% up to 61% and from 37% up to 95%, respectively. The strongest impact on vaccination uptake was whether the patient had been vaccinated last year, whether s/he had experienced vaccination side effects, and the patient’s general attitude towards vaccination. Conclusions: Although vaccination characteristics proved to influence influenza vaccination uptake, certain patient characteristics had an even higher impact on influenza vaccination uptake. Policy makers and general practitioners can use these insights to improve their communication plans and information regarding influenza vaccination for individuals aged 60 years or older. For instance, physicians should focus more on patients who had experienced side effects due to vaccination in the past, and policy makers should tailor the standard information folder to patients who had been vaccinated last year and to patient who had not. 10 p.

Grand challenges stimulate advances within the medical imaging research community; within a competitive yet friendly environment, they allow for a direct comparison of algorithms through a well-defined, centralized infrastructure. The tasks of the two-part PROSTATEx Challenges (the PROSTATEx Challenge and the PROSTATEx-2 Challenge) are (1) the computerized classification of clinically significant prostate lesions and (2) the computerized determination of Gleason Grade Group in prostate cancer, both based on multiparametric magnetic resonance images. The challenges incorporate well-vetted cases for training and testing, a centralized performance assessment process to evaluate results, and an established infrastructure for case dissemination, communication, and result submission. In the PROSTATEx Challenge, 32 groups apply their computerized methods (71 methods total) to 208 prostate lesions in the test set. The area under the receiver operating characteristic curve for these methods in the task of differentiating between lesions that are and are not clinically significant ranged from 0.45 to 0.87; statistically significant differences in performance among the top-performing methods, however, are not observed. In the PROSTATEx-2 Challenge, 21 groups apply their computerized methods (43 methods total) to 70 prostate lesions in the test set. When compared with the reference standard, the quadratic-weighted kappa values for these methods in the task of assigning a five-point Gleason Grade Group to each lesion range from [Formula: see text] to 0.27; superiority to random guessing can be established for only two methods. When approached with a sense of commitment and scientific rigor, challenges foster interest in the designated task and encourage innovation in the field.

The risk for type 2 diabetes (T2D) in ethnic minorities in Europe is higher in comparison with their European host populations. The western dietary pattern, characterized by high amounts of sugar and saturated fat (HSHF dietary pattern), has been associated with a higher risk for T2D. Information on this association in minority populations is scarce. Therefore, we aimed to investigate the HSHF dietary pattern and its role in the unequal burden of T2D prevalence in a multi-ethnic population in The Netherlands. We included 4694 participants aged 18-70 years of Dutch, South-Asian Surinamese, African Surinamese, Turkish, and Moroccan origin from the HELIUS study. Dutch participants scored the highest on the HSHF dietary pattern, followed by the Turkish, Moroccan, African Surinamese, and South-Asian Surinamese participants. Prevalence ratios (PR) for T2D were then calculated using multivariate cox regression analyses, adjusted for sociodemographic, anthropometric, and lifestyle factors. Higher adherence to an HSHF diet was not significantly related to T2D prevalence in the total study sample (PR 1.04 high versus low adherence, 95% CI: 0.80-1.35). In line, adjustment for HSHF diet score did not explain the ethnic differences in T2D. For instance, the PR of the South-Asian Surinamese vs. Dutch changed from 2.76 (95% CI: 2.05-3.72) to 2.90 (95% CI: 2.11-3.98) after adjustment for HSHF. To conclude, a western dietary pattern high in sugar and saturated fat was not associated with T2D, and did not explain the unequal burden in prevalence of T2D across the ethnic groups.

Purpose: Adding magnetic resonance (MR)-derived information to standard transrectal ultrasound (TRUS) images for guiding prostate biopsy is of substantial clinical interest. A tumor visible on MR images can be projected on ultrasound (US) by using MR-US registration. A common approach is to use surface-based registration. The authors hypothesize that biomechanical modeling will better control deformation inside the prostate than a regular nonrigid surface-based registration method. The authors developed a novel method by extending a nonrigid surface-based registration algorithm with biomechanical finite element (FE) modeling to better predict internal deformations of the prostate. Methods: Data were collected from ten patients and the MR and TRUS images were rigidly registered to anatomically align prostate orientations. The prostate was manually segmented in both images and corresponding surface meshes were generated. Next, a tetrahedral volume mesh was generated from the MR image. Prostate deformations due to the TRUS probe were simulated using the surface displacements as the boundary condition. A three-dimensional thin-plate spline deformation field was calculated by registering the mesh vertices. The target registration errors (TREs) of 35 reference landmarks determined by surface and volume mesh registrations were compared. Results: The median TRE of a surface-based registration with biomechanical regularization was 2.76 (0.81–7.96) mm. This was significantly different than the median TRE of 3.47 (1.05–7.80) mm for regular surface-based registration without biomechanical regularization. Conclusions: Biomechanical FE modeling has the potential to improve the accuracy of multimodal prostate registration when comparing it to a regular nonrigid surface-based registration algorithm and can help to improve the effectiveness of MR guided TRUS biopsy procedures.

Red blood cell (RBC) clearance is known to occur primarily in the spleen, and is presumed to be executed by red pulp macrophages. Erythrophagocytosis in the spleen takes place as part of the homeostatic turnover of RBCs to remove old RBCs. It can be strongly promoted by immunoglobulin G (IgG) opsonization of RBCs, a condition that can occur as a consequence of autoantibody or alloantibody formation. The purpose of our study was to investigate which phagocytes are involved in IgG-mediated RBC clearance in the human spleen. We developed a highly specific in vitro assay to monitor RBC phagocytosis in total human splenocytes. Surprisingly, we have found that whereas homeostatic clearance of RBCs is primarily a task for splenic macrophages, neutrophils and, to a lesser extent, also monocytes can be a major factor in clearance of IgG-opsonized RBCs. Erythrophagocytosis by neutrophils is strongly dependent on the degree of opsonization of the RBCs. Additionally, the process is enhanced after blocking the "do not eat me" signal CD47 on the opsonized RBCs, which binds signal regulatory protein α, a myeloid inhibitory receptor that restricts phagocytosis. Moreover, RBCs isolated from autoimmune hemolytic anemia patients, opsonized by auto-IgGs, were shown to be readily phagocytosed by neutrophils. Finally, priming of neutrophils by inflammatory mediators such as tumor necrosis factor α and lipopolysaccharide further increases the magnitude of erythrophagocytosis. Collectively, our data suggest that neutrophils contribute significantly to the phagocytosis of antibody-opsonized RBCs, especially under inflammatory conditions. This indicates a hereto unanticipated contribution of neutrophils in RBC phagocytosis, especially under pathological conditions such as alloimmunization or autoimmunization.

Contains fulltext : 137700.pdf (Publisher’s version ) (Open Access) OBJECTIVES: To correlate pharmacokinetic parameters of 3-T dynamic contrast-enhanced (DCE-)MRI with histopathologic microvascular and lymphatic parameters in organ-confined prostate cancer. METHODS: In 18 patients with unilateral peripheral zone (pT2a) tumours who underwent DCE-MRI prior to radical prostatectomy (RP), the following pharmacokinetic parameters were assessed: permeability surface area volume transfer constant (K (trans)), extravascular extracellular volume (Ve) and rate constant (K ep). In the RP sections blood and lymph vessels were visualised immunohistochemically and automatically examined and analysed. Parameters assessed included microvessel density (MVD), area (MVA) and perimeter (MVP) as well as lymph vessel density (LVD), area (LVA) and perimeter (LVP). RESULTS: A negative correlation was found between age and K (trans) and K ep for tumour (r = -0.60, p = 0.009; r = -0.67, p = 0.002) and normal (r = -0.54, p = 0.021; r = -0.46, p = 0.055) tissue. No correlation existed between absolute values of microvascular parameters from histopathology and DCE-MRI. In contrast, the ratio between tumour and normal tissue (correcting for individual microvascularity variations) significantly correlated between K ep and MVD (r = 0.61, p = 0.007) and MVP (r = 0.54, p = 0.022). The lymphovascular parameters showed only a correlation between LVA and K ep (r = -0.66, p = 0.003). CONCLUSIONS: Significant correlations between DCE-MRI and histopathologic parameters were found when correcting for interpatient variations in microvascularity. KEY POINTS: * Normal prostate tissue shows strong heterogeneity in microvascularity. * Peripheral zone prostate cancer shows increased and less heterogeneous microvascularity. * Normal and tumour tissue shows considerable variation in microvascularity between patients. * DCE-MRI should take into account the interprostatic heterogeneity of microvasculature between patients.

Contains fulltext : 117989.pdf (Publisher’s version ) (Open Access) BACKGROUND: A challenge in the diagnosis of prostate cancer (PCa) is the accurate assessment of aggressiveness. OBJECTIVE: To validate the performance of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate at 3 tesla (T) for the assessment of PCa aggressiveness, with prostatectomy specimens as the reference standard. DESIGN, SETTINGS, AND PARTICIPANTS: A total of 45 patients with PCa scheduled for prostatectomy were included. This study was approved by the institutional review board; the need for informed consent was waived. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Subjects underwent a clinical MRI protocol including DCE-MRI. Blinded to DCE-images, PCa was indicated on T2-weighted images based on histopathology results from prostatectomy specimens with the use of anatomical landmarks for the precise localization of the tumor. PCa was classified as low-, intermediate-, or high-grade, according to Gleason score. DCE-images were used as an overlay on T2-weighted images; mean and quartile values from semi-quantitative and pharmacokinetic model parameters were extracted per tumor region. Statistical analysis included Spearman's ρ, the Kruskal-Wallis test, and a receiver operating characteristics (ROC) analysis. RESULTS AND LIMITATIONS: Significant differences were seen for the mean and 75th percentile (p75) values of wash-in (p = 0.024 and p = 0.017, respectively), mean wash-out (p = 0.044), and p75 of transfer constant (K(trans)) (p = 0.035), all between low-grade and high-grade PCa in the peripheral zone. ROC analysis revealed the best discriminating performance between low-grade versus intermediate-grade plus high-grade PCa in the peripheral zone for p75 of wash-in, K(trans), and rate constant (Kep) (area under the curve: 0.72). Due to a limited number of tumors in the transition zone, a definitive conclusion for this region of the prostate could not be drawn. CONCLUSIONS: Quantitative parameters (K(trans) and Kep) and semi-quantitative parameters (wash-in and wash-out) derived from DCE-MRI at 3 T have the potential to assess the aggressiveness of PCa in the peripheral zone. P75 of wash-in, K(trans), and Kep offer the best possibility to discriminate low-grade from intermediate-grade plus high-grade PCa. Copyright © 2013 European Association of Urology. Published by Elsevier B.V. All rights reserved. KEYWORDS: Dynamic contrast-enhanced MRI, Pharmacokinetic modeling, Prostate cancer, Prostate cancer aggressiveness, Validation study

Contains fulltext : 122874.pdf (Publisher’s version ) (Open Access) In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59±3.08 mm.

To the Editor: Hemodialysis patients are exposed to high amounts of phosphate and citrate, causing hypocalcaemia and hyperparathyroidism (1). These perturbations have a substantial role in extravascular calcifications causing cardiovascular disease and bone abnormalities. The Kidney Disease: Improving Global Outcomes (KDIGO)1 work group developed a clinical practice guideline on mineral and bone disorders and have advised frequent measurement of calcium, phosphorus, and parathyroid hormone (PTH) (1). Ideally, ionized calcium is measured, but for practical reasons adjusted calcium formulas are broadly used in the clinic. Therapeutic decisions depend on calcium status, in addition to PTH concentrations and clinical aspects (1). Until now, the adequacy of only a few formulas for calculating calcium values in hemodialysis patients has been evaluated. Here, results of the 3 best-performing formulas and the classic modified Orrell from a comprehensive evaluation of 24 formulas are presented. Medline was searched using search terms related to formulas for calculating calcium. Ninety-one blood samples for routine control laboratory measurement from 56 hemodialysis patients were collected. The inclusion criterion was the availability of control panel samples for hemodialysis. Exclusion criteria were interference due to hemolysis, icteria …

Contains fulltext : 172198.pdf (Publisher’s version ) (Open Access) Purpose To determine the best features to discriminate prostate cancer from benign disease and its relationship to benign disease class and cancer grade. Materials and Methods The institutional review board approved this study and waived the need for informed consent. A retrospective cohort of 70 patients (age range, 48-70 years; median, 62 years), all of whom were scheduled to undergo radical prostatectomy and underwent preoperative 3-T multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced imaging, were included. The digitized prostatectomy slides were annotated for cancer and noncancerous disease and coregistered to MR imaging with an interactive deformable coregistration scheme. Computer-identified features for each of the noncancerous disease categories (eg, benign prostatic hyperplasia [BPH], prostatic intraepithelial neoplasia [PIN], inflammation, and atrophy) and prostate cancer were extracted. Feature selection was performed to identify the features with the highest discriminatory power. The performance of these five features was evaluated by using the area under the receiver operating characteristic curve (AUC). Results High-b-value diffusion-weighted images were more discriminative in distinguishing BPH from prostate cancer than apparent diffusion coefficient, which was most suitable for distinguishing PIN from prostate cancer. The focal appearance of lesions on dynamic contrast-enhanced images may help discriminate atrophy and inflammation from cancer. Which imaging features are discriminative for different benign lesions is influenced by cancer grade. The apparent diffusion coefficient appeared to be the most discriminative feature in identifying high-grade cancer. Classification results showed increased performance by taking into account specific benign types (AUC = 0.70) compared with grouping all noncancerous findings together (AUC = 0.62). Conclusion The best features with which to discriminate prostate cancer from noncancerous benign disease depend on the type of benign disease and cancer grade. Use of the best features may result in better diagnostic performance. (c) RSNA, 2015 Online supplemental material is available for this article.

ObjectivesThe key to MR lymphography is suppression of T2* MR signal in normal lymph nodes, while retaining high signal in metastatic nodes. Our objective is to quantitatively compare the ability of ferumoxtran-10 and ferumoxytol to suppress the MR signal in normal pelvic lymph nodes.MethodsIn 2010, a set of consecutive patients who underwent intravenous MR Lymphography (MRL) were included. Signal suppression in normal lymph nodes in T2*-weighted images due to uptake of USPIO (Ultra-Small Superparamagnetic Particles of Iron Oxide) was quantified. Signal suppression by two USPIO contrast agents, ferumoxtran-10 and ferumoxytol was compared using Wilcoxon’s signed rank test.ResultsForty-four patients were included, of which all 44 had a ferumoxtran-10 MRL and 4 had additionally a ferumoxytol MRL. A total of 684 lymph nodes were identified in the images, of which 174 had been diagnosed as metastatic. USPIO-induced signal suppression in normal lymph nodes was significantly stronger in ferumoxtran-10 MRL than in ferumoxytol MRL (p ConclusionsT2* signal suppression in normal pelvic lymph nodes is significantly stronger with ferumoxtran-10 than with ferumoxytol, which may affect diagnostic accuracy.

textabstractBackground Cirrhotic patients are at considerable risk for bacterial infections, possibly through increased intestinal permeability and bacterial overgrowth. Proton pump inhibitors (PPIs) may increase infection risk. We aimed to explore the potential association between PPI use and bacterial infection risk in cirrhotic patients and potential underlying mechanisms in complementary patient and animal models. Materials and methods Bacterial overgrowth was determined in jejunum of 30 rats randomly allocated to 6-week PPI treatment, gastrectomy or no treatment. In 84 consecutive cirrhotic patients, bacterial infection risk was prospectively assessed and related to PPI use. Intestinal permeability was determined by polyethylene glycol (PEG) test in nine healthy individuals and 12 cirrhotic patients. Results Bacterial overgrowth was much more common in jejunum of rats treated with PPI or gastrectomy compared with nontreated rats. Twenty-four patients (29%) developed a bacterial infection during a median follow-up of 28months. Although PPI users tended to experience infection more often than patients without PPI therapy, PPI use was not an independent predictor of bacterial infection (HR 1·2, 95% CI 0·5-3·0, P=0·72), after correction for Child-Pugh class (HR 3·6, 95% CI 1·5-8·7, P=0·004) and age (HR 1·05, 95%CI 1·01-1·09, P=0·02). In cirrhotic patients, 24-h urinary recovery of PEGs 1500 and 3350 was significantly higher compared with healthy controls. Conclusions Although in our animal model PPIs induced intestinal overgrowth, stage of liver disease rather than PPI use was the predominant factor determining infection risk in cirrhotic patients. Increased intestinal permeability may be a factor contributing to infection risk.

Contains fulltext : 108408.pdf (Publisher’s version ) (Open Access) Purpose: To determine the interpatient variability of prostate peripheral zone (PZ) apparent diffusion coefficient (ADC) and its effect on the assessment of prostate cancer aggressiveness. Materials and Methods: The requirement for institutional review board approval was waived. Intra- and interpatient variation of PZ ADCs was determined by means of repeated measurements of normal ADCs at three magnetic resonance (MR) examinations in a retrospective cohort of 10 consecutive patients who had high prostate-specific antigen levels and negative findings at transrectal ultrasonographically-guided biopsy. In these patients, no signs of PZ cancer were found at all three MR imaging sessions. The effect of interpatient variation on the assessment of prostate cancer aggressiveness was examined in a second retrospective cohort of 51 patients with PZ prostate cancer. Whole-mount step-section pathologic evaluation served as reference standard for placement of regions of interest on tumors and normal PZ. Repeated-measures analysis of variance was used to determine the significance of the interpatient variations in ADCs. Linear logistic regression was used to assess whether incorporating normal PZ ADCs improves the prediction of cancer aggressiveness. Results: Analysis of variance revealed that interpatient variability (1.2-2.0 x 10(-3) mm(2)/sec) was significantly larger than measurement variability (0.068 x 10(-3) mm(2)/sec +/- 0.027 [standard deviation]) (P = .0058). Stand-alone tumor ADCs showed an area under the receiver operating characteristic curve (AUC) of 0.91 for discriminating low-grade versus high-grade tumors. Incorporating normal PZ ADC significantly improved the AUC to 0.96 (P = .0401). Conclusion: PZ ADCs show significant interpatient variation, which has a substantial effect on the prediction of prostate cancer aggressiveness. Correcting this effect results in a significant increase in diagnostic accuracy. (c) RSNA, 2012.

Contains fulltext : 109206.pdf (Publisher’s version ) (Open Access) BACKGROUND: Accurate pretreatment assessment of prostate cancer (PCa) aggressiveness is important in decision making. Gleason grade is a critical predictor of the aggressiveness of PCa. Transrectal ultrasound-guided biopsies (TRUSBxs) show substantial undergrading of Gleason grades found after radical prostatectomy (RP). Diffusion-weighted magnetic resonance imaging (MRI) has been shown to be a biomarker of tumour aggressiveness. OBJECTIVE: To improve pretreatment assessment of PCa aggressiveness, this study prospectively evaluated MRI-guided prostate biopsies (MR-GBs) of abnormalities determined on diffusion-weighted imaging (DWI) apparent diffusion coefficient (ADC) maps. The results were compared with a 10-core TRUSBx cohort. RP findings served as the gold standard. DESIGN, SETTING, AND PARTICIPANTS: A 10-core TRUSBx (n=64) or MR-GB (n=34) was used for PCa diagnosis before RP in 98 patients. MEASUREMENTS: Using multiparametric 3-T MRI: T2-weighted, dynamic contrast-enhanced imaging, and DWI were performed to identify tumour-suspicious regions in patients with a negative TRUSBx. The regions with the highest restriction on ADC maps within the suspicions regions were used to direct MR-GB. A 10-core TRUSBx was used in a matched cohort. Following RP, the highest Gleason grades (HGGs) in biopsies and RP specimens were identified. Biopsy and RP Gleason grade results were evaluated using chi-square analysis. RESULTS AND LIMITATIONS: No significant differences on RP were observed for proportions of patients having a HGG of 3 (35% vs 28%; p=0.50), 4 (32% vs 41%; p=0.51), and 5 (32% vs 31%; p=0.61) for the MR-GB and TRUSBx cohort, respectively. MR-GB showed an exact performance with RP for overall HGG: 88% (30 of 34); for TRUS-GB it was 55% (35 of 64; p=0.001). In the MR-GB cohort, an exact performance with HGG 3 was 100% (12 of 12); for HGG 4, 91% (10 of 11); and for HGG 5, 73% (8 of 11). The corresponding performance rates for TRUSBx were 94% (17 of 18; p=0.41), 46% (12 of 26; p=0.02), and 30% (6 of 20; p=0.01), respectively. CONCLUSIONS: This study shows prospectively that DWI-directed MR-GBs significantly improve pretreatment risk stratification by obtaining biopsies that are representative of true Gleason grade. 01 januari 2012

Contains fulltext : 110666.pdf (Publisher’s version ) (Open Access) PURPOSE: To evaluate automatic characterization of a breast MR lesion by its spatially coherent region of interest (ROI). MATERIALS AND METHODS: The method delineated 247 enhancing lesions using Otsu thresholding after manually placing a sphere. Mean Shift Clustering subdivided each volume, based on features including pharmacokinetic parameters. An iteratively trained classifier to predict the most suspicious ROI (IsR) was used, to predict the malignancy likelihood of each lesion. Performance was evaluated using receiver operator characteristic (ROC) analysis, and compared with a previous prototype. IsR was compared with noniterative training. The effect of adding BI-RADS� morphology (from a radiologist) to the classifier was investigated. RESULTS: The area under the ROC curve (AUC) was 0.83 (95\% confidence interval [CI] of 0.77-0.88), and was 0.75 (95\%CI = 0.68-0.81; P = 0.029) without pharmacokinetic features. IsR performed better than conventional selection, based on one feature (AUC 0.75, 95\%CI = 0.68-0.81; P = 0.035). With morphology, the AUC was 0.84 (95\%CI = 0.78-0.88) versus 0.82 without (P = 0.40). CONCLUSION: Breast lesions can be characterized by their most suspicious, contiguous ROI using multi-feature clustering and iterative training. Characterization was improved by including pharmacokinetic modeling, while in our experiments, including morphology did not improve characterization. J. Magn. Reson. Imaging 2012;. � 2012 Wiley Periodicals, Inc.

Contains fulltext : 108597.pdf (Publisher’s version ) (Open Access) X-ray mammography is routinely used in national screening programmes and as a clinical diagnostic tool. Magnetic Resonance Imaging (MRI) is commonly used as a complementary modality, providing functional information about the breast and a 3D image that can overcome ambiguities caused by the superimposition of fibro-glandular structures associated with X-ray imaging. Relating findings between these modalities is a challenging task however, due to the different imaging processes involved and the large deformation that the breast undergoes. In this work we present a registration method to determine spatial correspondence between pairs of MR and X-ray images of the breast, that is targeted for clinical use. We propose a generic registration framework which incorporates a volume-preserving affine transformation model and validate its performance using routinely acquired clinical data. Experiments on simulated mammograms from 8 volunteers produced a mean registration error of 3.8+/-1.6mm for a mean of 12 manually identified landmarks per volume. When validated using 57 lesions identified on routine clinical CC and MLO mammograms (n=113 registration tasks) from 49 subjects the median registration error was 13.1mm. When applied to the registration of an MR image to CC and MLO mammograms of a patient with a localisation clip, the mean error was 8.9mm. The results indicate that an intensity based registration algorithm, using a relatively simple transformation model, can provide radiologists with a clinically useful tool for breast cancer diagnosis. 01 juli 2012

Contains fulltext : 107793.pdf (Publisher’s version ) (Open Access) OBJECTIVES: To evaluate the accuracy and speed of a novel robotic technique as an aid to perform magnetic resonance image (MRI)-guided prostate biopsies on patients with cancer suspicious regions. METHODS: A pneumatic controlled MR-compatible manipulator with 5 degrees of freedom was developed in-house to guide biopsies under real-time imaging. From 13 consecutive biopsy procedures, the targeting error, biopsy error and target displacement were calculated to evaluate the accuracy. The time was recorded to evaluate manipulation and procedure time. RESULTS: The robotic and manual techniques demonstrated comparable results regarding mean targeting error (5.7 vs 5.8 mm, respectively) and mean target displacement (6.6 vs 6.0 mm, respectively). The mean biopsy error was larger (6.5 vs 4.4 mm) when using the robotic technique, although not significant. Mean procedure and manipulation time were 76 min and 6 min, respectively using the robotic technique and 61 and 8 min with the manual technique. CONCLUSIONS: Although comparable results regarding accuracy and speed were found, the extended technical effort of the robotic technique make the manual technique - currently - more suitable to perform MRI-guided biopsies. Furthermore, this study provided a better insight in displacement of the target during in vivo biopsy procedures. 01 februari 2012

Contains fulltext : 110343.pdf (Publisher’s version ) (Open Access) In this paper, a fully automatic computer-aided detection (CAD) method is proposed for the detection of prostate cancer. The CAD method consists of multiple sequential steps in order to detect locations that are suspicious for prostate cancer. In the initial stage, a voxel classification is performed using a Hessian-based blob detection algorithm at multiple scales on an apparent diffusion coefficient map. Next, a parametric multi-object segmentation method is applied and the resulting segmentation is used as a mask to restrict the candidate detection to the prostate. The remaining candidates are characterized by performing histogram analysis on multiparametric MR images. The resulting feature set is summarized into a malignancy likelihood by a supervised classifier in a two-stage classification approach. The detection performance for prostate cancer was tested on a screening population of 200 consecutive patients and evaluated using the free response operating characteristic methodology. The results show that the CAD method obtained sensitivities of 0.41, 0.65 and 0.74 at false positive (FP) levels of 1, 3 and 5 per patient, respectively. In conclusion, this study showed that it is feasible to automatically detect prostate cancer at a FP rate lower than systematic biopsy. The CAD method may assist the radiologist to detect prostate cancer locations and could potentially guide biopsy towards the most aggressive part of the tumour.