Understanding quantitative DCE-MRI of the breast : towards meaningful clinical application

In most industrialized countries breast cancer will affect one out of eight women during her lifetime. In the USA, after continuously increasing for more than two decades, incidence rates are slowly decreasing since 2001. Since 1990, death rates from breast cancer have steadily decreased in women, which is attributed to both earlier detection and improved treatment. Still, it is second only to lung cancer as a cause of cancer death in women. In this work we set out to improve early detection of breast cancer via quantitative analysis of magnetic resonance images (MRI). Screening and diagnosis of breast cancer are generally performed using X-ray mammography, possibly in conjunction with ultrasonography. However, MRI is becoming an important modality for screening of women at high-risk due to for instance hereditary gene mutations, as a problem-solving tool in case of indecisive mammographic and / or ultrasonic imaging, and for anti-cancer therapy assessment. In this work, we focused on MR imaging of the breast. More specifically, the dynamic contrast-enhanced (DCE) part of the protocol was highlighted, as well as radiological assessment of DCE-MRI data. The T_1-weighted (T_1: longitudinal relaxation time, a tissue property) signal-versus-time curve that can be extracted from the DCE-MRI series that is acquired at the time of and after injection of a T_1-shortening (shorter T_1 results in higher signal) contrast agent, is usually visually assessed by the radiologist. For example, a fast initial rise to the peak (1-2 minutes post injection) followed by loss of signal within a time frame of about 5-6 minutes is a sign for malignancy, whereas a curve showing persistent (slow) uptake within the same time frame is a sign for benignity. This difference in contrast agent uptake pattern is related to physiological changes in tumorous tissue that for instance result in a stronger uptake of the contrast agent. However, this descriptive way of curve type classification is based on clinical statistics, not on knowledge about tumor physiology. We investigated pharmacokinetic modeling as a quantitative image analysis tool. Pharmacokinetics describes what happens to a substance (e.g. drug or contrast agent) after it has been administered to a living organism. This includes the mechanisms of absorption and distribution. The terms in which these mechanisms are described are physiological and can therefore provide parameters describing the functioning of the tissue. This physiological aspect makes it an attractive approach to investigate (aberrant) tissue functioning. In addition, this type of analysis excludes confounding factors due to inter- and intra-patient differences in the systemic blood circulation, as well as differences in the injection protocol. In this work, we discussed the physiological basis and details of different types of pharmacokinetic models, with the focus on compartmental models. Practical implications such as obtaining an arterial input function and model parameter estimation were taken into account as well. A simulation study of the data-imposed limitations – in terms of temporal resolution and noise properties – on the complexity of pharmacokinetic models led to the insight that only one of the tested models, the basic Tofts model, is applicable to DCE-MRI data of the breast. For the basic Tofts model we further investigated the aspect of temporal resolution, because a typical diagnostic DCE-MRI scan of the breast is acquired at a rate of about 1 image volume every minute; whereas pharmacokinetic modeling usually requires a sampling time of less than 10 s. For this experiment we developed a new downsampling method using high-temporal-resolution raw k-space data to simulate what uptake curves would have looked like if they were acquired at lower temporal resolutions. We made use of preclinical animal data. With this data we demonstrated that the limit of 10 s can be stretched to about 1 min if the arterial input function (AIF, the input to the pharmacokinetic model) is inversely derived from a healthy reference tissue, instead of measured in an artery or taken from the literature. An important precondition for the application of pharmacokinetic modeling is knowledge of the relationship between the acquired DCE-MRI signal and the actual concentration of the contrast agent in the tissue. This relationship is not trivial because with MRI we measure the indirect effect of the contrast agent on water protons. To establish this relationship via calculation of T_1 (t), we investigated both a theoretical and an empirical approach, making use of an in-house (University of Chicago) developed reference object that is scanned concurrently with the patient. The use of the calibration object can shorten the scan duration (an empirical approach requires less additional scans than an approach using a model of the acquisition technique), and can demonstrate if theoretical approaches are valid. Moreover we produced concentration images and estimated tissue proton density, also making use of the calibration object. Finally, via pharmacokinetic modeling and other MRI-derived measures we partly revealed the actions of a novel therapeutic in a preclinical study. In particular, the anti-tumor activity of a single dose of liposomal prednisolone phosphate was investigated, which is an anti-inflammatory drug that has demonstrated tumor growth inhibition. The work presented in this thesis contributes to a meaningful clinical application and interpretation of quantitative DCE-MRI of the breast

Integrated Detector Control and Calibration Processing at the European XFEL

The European X-ray Free Electron Laser is a high-intensity X-ray light source currently being constructed in the area of Hamburg, that will provide spatially coherent X-rays in the energy range between $0.25\,\mathrm{keV}$ and $25\,\mathrm{keV}$. The machine will deliver $10\,\mathrm{trains/s}$, consisting of up to $2700\,\mathrm{pulses}$, with a $4.5\,\mathrm{MHz}$ repetition rate. The LPD, DSSC and AGIPD detectors are being developed to provide high dynamic-range Mpixel imaging capabilities at the mentioned repetition rates. A consequence of these detector characteristics is that they generate raw data volumes of up to $15\,\mathrm{Gbyte/s}$. In addition the detector's on-sensor memory-cell and multi-/non-linear gain architectures pose unique challenges in data correction and calibration, requiring online access to operating conditions and control settings. We present how these challenges are addressed within XFEL's control and analysis framework Karabo, which integrates access to hardware conditions, acquisition settings (also using macros) and distributed computing. Implementation of control and calibration software is mainly in Python, using self-optimizing (py) CUDA code, numpy and iPython parallels to achieve near-real time performance for calibration application.Comment: Proceeding ICALEPS 201

Real‐world treatment patterns and outcomes using terlipressin in 203 patients with the hepatorenal syndrome

Background: Hepatorenal syndrome and acute kidney injury are common complications of decompensated cirrhosis, and terlipressin is recommended as first‐line vasoconstrictor therapy. However, data on its use outside of clinical trials are lacking. / Aims: To assess practice patterns and outcomes around vasoconstrictor use for hepatorenal syndrome in UK hospitals. / Methods: This was a multicentre chart review study. Data were extracted from medical records of patients diagnosed with hepatorenal syndrome and treated by vasoconstrictor drugs between January 2013 and December 2017 at 26 hospitals in the United Kingdom. The primary outcome was improvement of kidney function, defined as complete response (serum creatinine improved to ≤1.5 mg/dL), partial response (serum creatinine reduction of ≥20% but >1.5 mg/dL) and overall response (complete or partial response). Other outcomes included need for dialysis, mortality, liver transplantation and adverse events. / Results: Of the 225 patients included in the analysis, 203 (90%) were treated with terlipressin (median duration, 6 days; range: 2‐24 days). Mean (±standard deviation) serum creatinine at vasopressor initiation was 3.25 ± 1.64 mg/dL. Terlipressin overall response rate was 73%. Overall response was higher in patients with mild acute kidney injury (baseline serum creatinine <2.25 mg/dL), compared to those with moderate (serum creatinine ≥2.25 mg/dL and <3.5 mg/dL) or severe (serum creatinine ≥3.5 mg/dL). Ninety‐day survival was 86% for all patients (93% for overall responders vs 66% for treatment nonresponders, P < 0.0001). / Conclusion: Terlipressin is the most commonly prescribed vasoconstrictor for patients with hepatorenal syndrome in the United Kingdom. Treatment with terlipressin in patients with less severe acute kidney injury (serum creatinine <2.25 mg/dL) was associated with higher treatment responses, and 90‐day survival

Health state utilities of patients with heart failure: a systematic literature review

Background and Objectives New treatments and interventions are in development to address clinical needs in heart failure. To support decision making on reimbursement, cost-effectiveness analyses are frequently required. A systematic literature review was conducted to identify and summarize heart failure utility values for use in economic evaluations. Methods Databases were searched for articles published until June 2019 that reported health utility values for patients with heart failure. Publications were reviewed with specific attention to study design; reported values were categorized according to the health states, ‘chronic heart failure’, ‘hospitalized’, and ‘other acute heart failure’. Interquartile limits (25th percentile ‘Q1’, 75th percentile ‘Q3’) were calculated for health states and heart failure subgroups where there were sufficient data. Results The systematic literature review identified 161 publications based on data from 142 studies. Utility values for chronic heart failure were reported by 128 publications; 39 publications published values for hospitalized and three for other acute heart failure. There was substantial heterogeneity in the specifics of the study populations, methods of elicitation, and summary statistics, which is reflected in the wide range of utility values reported. EQ-5D was the most used instrument; the interquartile limit for mean EQ-5D values for chronic heart failure was 0.64–0.72. Conclusions There is a wealth of published utility values for heart failure to support economic evaluations. Data are heterogenous owing to specificities of the study population and methodology of utility value elicitation and analysis. Choice of value(s) to support economic models must be carefully justified to ensure a robust economic analysis

Multi-parametric assessment of the anti-angiogenic effects of liposomal glucocorticoids

Inflammation plays a prominent role in tumor growth. Anti-inflammatory drugs have therefore been proposed as anti-cancer therapeutics. In this study, we determined the anti-angiogenic activity of a single dose of liposomal prednisolone phosphate (PLP-L), by monitoring tumor vascular function and viability over a period of one week. C57BL/6 mice were inoculated subcutaneously with B16F10 melanoma cells. Six animals were PLP-L-treated and six served as control. Tumor tissue and vascular function were probed using MRI before and at three timepoints after treatment. DCE-MRI was used to determine Ktrans, ve, time-to-peak, initial slope and the fraction of non-enhancing pixels, complemented with immunohistochemistry. The apparent diffusion coefficient (ADC), T2 and tumor size were assessed with MRI as well. PLP-L treatment resulted in smaller tumors and caused a significant drop in Ktrans 48 h post-treatment, which was maintained until one week after drug administration. However, this effect was not sufficient to significantly distinguish treated from non-treated animals. The therapy did not affect tumor tissue viability but did prevent the ADC decrease observed in the control group. No evidence for PLP-L-induced tumor vessel normalization was found on histology. Treatment with PLP-L altered tumor vascular function. This effect did not fully explain the tumor growth inhibition, suggesting a broader spectrum of PLP-L activities

Contribution of NFP LysM Domains to the Recognition of Nod Factors during the Medicago truncatula/Sinorhizobium meliloti Symbiosis

The root nodule nitrogen fixing symbiosis between legume plants and soil bacteria called rhizobia is of great agronomical and ecological interest since it provides the plant with fixed atmospheric nitrogen. The establishment of this symbiosis is mediated by the recognition by the host plant of lipo-chitooligosaccharides called Nod Factors (NFs), produced by the rhizobia. This recognition is highly specific, as precise NF structures are required depending on the host plant. Here, we study the importance of different LysM domains of a LysM-Receptor Like Kinase (LysM-RLK) from Medicago truncatula called Nod factor perception (NFP) in the recognition of different substitutions of NFs produced by its symbiont Sinorhizobium meliloti. These substitutions are a sulphate group at the reducing end, which is essential for host specificity, and a specific acyl chain at the non-reducing end, that is critical for the infection process. The NFP extracellular domain (ECD) contains 3 LysM domains that are predicted to bind NFs. By swapping the whole ECD or individual LysM domains of NFP for those of its orthologous gene from pea, SYM10 (a legume plant that interacts with another strain of rhizobium producing NFs with different substitutions), we showed that NFP is not directly responsible for specific recognition of the sulphate substitution of S. meliloti NFs, but probably interacts with the acyl substitution. Moreover, we have demonstrated the importance of the NFP LysM2 domain for rhizobial infection and we have pinpointed the importance of a single leucine residue of LysM2 in that step of the symbiosis. Together, our data put into new perspective the recognition of NFs in the different steps of symbiosis in M. truncatula, emphasising the probable existence of a missing component for early NF recognition and reinforcing the important role of NFP for NF recognition during rhizobial infection

Pseudo-color visualizations of DCE-MR image series for MR mammography

In recent years, dynamic contrast-enhanced magnetic resonance (DCE-MR) imaging has become a valuable tool for detection, diagnosis and management of breast cancer. Several criteria for describing morphologic and dynamic characteristics of suspiciously enhancing tissue regions have been collected in the ACR BIRADS MRI lexicon. However, evaluation of these criteria is nonetheless a challenging task for human observers due to the huge amount and the multitemporal nature of the image data. Therefore, computer aided diagnosis (CAD) tools based on artificial neural networks (ANN) or pharamcokinetic models receive growing attention from the radiologic community. In DCE-MR imaging, each voxel is associated with a vector s = (s1, . . . , st) reflecting the temporal variation of the local signal intensity after intravenous administration of a contrast agent (Gd-DTPA). Due to changes in their vascular structure, benign and malignant tissue expose characteristic intensity-time curves (ITC). These curves enable radiologists to infer information about the tissue state from the image data, a time-consuming task owing to the heterogeneity of cancerous tissue. To aid evaluation of DCE-MR image series, we propose a pseudo-color visualization of the temporal information based on ANNs. An ANN is trained with labeled ITCs sampled from a number of histologically verified training cases to classify each temporal signal sx,y,z as being indicative for malignant (m), normal (n) or benign (b) tissue according to the returned posteriori probabilities p(m|s_x,y,z), p(n|s_x,y,z) and p(b|s_x,y,z). Pseudo-color visualizations of unseen image series are computed by displaying suspiciously enhancing voxels with RGB colors reflecting the ANN based signal assessment: bright red, green and blue voxels indicate high p(m|s_x,y,z), p(n|s_x,y,z) and p(b|s_x,y,z) values, respectively. Therewith, temporal characteristics of tissue regions are revealed, enabling radiologists to assess the architecture of lesions by means of a single 3D color image

Effects of reference tissue AIF derived from low temporal resolution DCE-MRI data on pharmacokinetic parameter estimation

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