Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer

This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (p = 0.03) and increase in HV-HC (p = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (p = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: p = 0.03), LV-HC (MDA-MB-231: p = 0.04), LV-LC (BT-474: p = 0.04; MDA-MB-231: p < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer.

Measurement of the Lund Jet Plane Using Charged Particles in 13 TeV Proton-Proton Collisions with the ATLAS Detector

The prevalence of hadronic jets at the LHC requires that a deep understanding of jet formation and structure is achieved in order to reach the highest levels of experimental and theoretical precision. There have been many measurements of jet substructure at the LHC and previous colliders, but the targeted observables mix physical effects from various origins. Based on a recent proposal to factorize physical effects, this Letter presents a double-differential cross-section measurement of the Lund jet plane using 139  fb^{-1} of sqrt[s]=13  TeV proton-proton collision data collected with the ATLAS detector using jets with transverse momentum above 675 GeV. The measurement uses charged particles to achieve a fine angular resolution and is corrected for acceptance and detector effects. Several parton shower Monte Carlo models are compared with the data. No single model is found to be in agreement with the measured data across the entire plane.

Measurement of Azimuthal Anisotropy of Muons from Charm and Bottom Hadrons in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

The elliptic flow of muons from the decay of charm and bottom hadrons is measured in pp collisions at sqrt[s]=13  TeV using a data sample with an integrated luminosity of 150  pb^{-1} recorded by the ATLAS detector at the LHC. The muons from heavy-flavor decay are separated from light-hadron decay muons using momentum imbalance between the tracking and muon spectrometers. The heavy-flavor decay muons are further separated into those from charm decay and those from bottom decay using the distance-of-closest-approach to the collision vertex. The measurement is performed for muons in the transverse momentum range 4-7 GeV and pseudorapidity range |η|<2.4. A significant nonzero elliptic anisotropy coefficient v_{2} is observed for muons from charm decays, while the v_{2} value for muons from bottom decays is consistent with zero within uncertainties.

Search for Magnetic Monopoles and Stable High-Electric-Charge Objects in 13 Tev Proton-Proton Collisions with the ATLAS Detector

A search for magnetic monopoles and high-electric-charge objects is presented using 34.4  fb^{-1} of 13 TeV pp collision data collected by the ATLAS detector at the LHC during 2015 and 2016. The considered signature is based upon high ionization in the transition radiation tracker of the inner detector associated with a pencil-shape energy deposit in the electromagnetic calorimeter. The data were collected by a dedicated trigger based on the tracker high-threshold hit capability. The results are interpreted in models of Drell-Yan pair production of stable particles with two spin hypotheses (0 and 1/2) and masses ranging from 200 to 4000 GeV. The search improves by approximately a factor of 5 the constraints on the direct production of magnetic monopoles carrying one or two Dirac magnetic charges and stable objects with electric charge in the range 20≤|z|≤60 and extends the charge range to 60<|z|≤100.

Non-inferiority trials in cardiology: what clinicians need to know

Clinical trials traditionally aim to show a new treatment is superior to placebo or standard treatment, that is, superiority trials. There is an increasing number of trials demonstrating a new treatment is non-inferior to standard treatment. The hypotheses, design and interpretation of non-inferiority trials are different to superiority trials. Non-inferiority trials are designed with the notion that the new treatment offers advantages over standard treatment in certain important aspects. The non-inferior margin is a predetermined margin of difference between the new and standard treatment that is considered acceptable or tolerable for the new treatment to be considered ‘similar’ or ‘not worse’. Both relative difference and absolute difference methods can be used to define the non-inferior margin. Sequential testing for non-inferiority and superiority is often performed. Non-inferiority trials may be necessary in situations where it is no longer ethical to test any new treatment against placebo. There are inherent assumptions in non-inferiority trials which may not be correct and which are not being tested. Successive non-inferiority trials may introduce less and less effective treatments even though these treatments may have been shown to be non-inferior. Furthermore, poor quality trials favour non-inferior results. Intention-to-treat analysis, the preferred way to analyse randomised trials, may favour non-inferiority. Both intention-to-treat and per-protocol analyses should be recommended in non-inferiority trials. Clinicians should be aware of the pitfalls of non-inferiority trials and not accept non-inferiority on face value. The focus should not be on the p values but on the effect size and confidence limits.

Observation of Electroweak Production of a Same-Sign W Boson Pair in Association with Two Jets in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter presents the observation and measurement of electroweak production of a same-sign W boson pair in association with two jets using 36.1  fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of sqrt[s]=13  TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed in the detector fiducial phase-space region, defined by the presence of two same-sign leptons, electron or muon, and at least two jets with a large invariant mass and rapidity difference. A total of 122 candidate events are observed for a background expectation of 69±7 events, corresponding to an observed signal significance of 6.5 standard deviations. The measured fiducial signal cross section is σ^{fid}=2.89_{-0.48}^{+0.51}(stat)_{-0.28}^{+0.29}(syst)  fb.

Predictive shifts in free energy couple mutations to their phenotypic consequences

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.

Observation of Light-by-Light Scattering in Ultraperipheral Pb+Pb Collisions with the ATLAS Detector

This Letter describes the observation of the light-by-light scattering process, γγ→γγ, in Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV. The analysis is conducted using a data sample corresponding to an integrated luminosity of 1.73  nb^{-1}, collected in November 2018 by the ATLAS experiment at the LHC. Light-by-light scattering candidates are selected in events with two photons produced exclusively, each with transverse energy E_{T}^{γ}>3  GeV and pseudorapidity |η_{γ}|<2.4, diphoton invariant mass above 6 GeV, and small diphoton transverse momentum and acoplanarity. After applying all selection criteria, 59 candidate events are observed for a background expectation of 12±3 events. The observed excess of events over the expected background has a significance of 8.2 standard deviations. The measured fiducial cross section is 78±13(stat)±7(syst)±3(lumi)  nb.

Comparison of Fragmentation Functions for Jets Dominated by Light Quarks and Gluons from pp and Pb+Pb Collisions in ATLAS

Charged-particle fragmentation functions for jets azimuthally balanced by a high-transverse-momentum, prompt, isolated photon are measured in 25  pb^{-1} of pp and 0.49  nb^{-1} of Pb+Pb collision data at 5.02 TeV per nucleon pair recorded with the ATLAS detector at the Large Hadron Collider. The measurements are compared to predictions of Monte Carlo generators and to measurements of inclusively selected jets. In pp collisions, a different jet fragmentation function in photon-tagged events from that in inclusive jet events arises from the difference in fragmentation between light quarks and gluons. The ratios of the fragmentation functions in Pb+Pb events to that in pp events are used to explore the parton color-charge dependence of jet quenching in the hot medium. In relatively peripheral collisions, fragmentation functions exhibit a similar modification pattern for photon-tagged and inclusive jets. However, photon-tagged jets are observed to have larger modifications than inclusive jets in central Pb+Pb events.

Clinical and research applications of neuromuscular ultrasound in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder characterized by dysfunction at multiple levels of the neuraxis. It remains a clinical diagnosis without a definitive diagnostic investigation. Electrodiagnostic testing provides supportive information and, along with imaging and biochemical markers, can help exclude mimicking conditions. Neuromuscular ultrasound has a valuable role in the diagnosis and monitoring of ALS and provides complementary information to clinical assessment and electrodiagnostic testing as well as insights into the underlying pathophysiology of this disease. This review highlights the evidence for ultrasound in the evaluation of bulbar, limb and respiratory musculature and peripheral nerves in ALS. Further research in this evolving area is required.

040 Acute cerebellar ataxia following epstein-barr virus infection

Introduction

Infectious aetiologies such as acute Epstein-Barr virus (EBV) infection are in the differential diagnosis for acute cerebellar ataxia (ACA). This syndrome remains exceptionally rare and not well characterised in adults.e.g. 1 2

Methods

A retrospective case review of a patient diagnosed with ACA following EBV infection with implications for pathogenesis and treatment.

Results

A 29-year-old Caucasian male presented with a three day history of ACA. Seven days prior he was diagnosed with infectious mononucleosis; bloodwork was consistent with acute EBV infection. These symptoms improved rapidly with oral prednisolone. He took no regular medications, drank alcohol moderately and had no significant family history.

On examination, he was afebrile, ataxic and mildly dysarthric. Sensory examination was normal, particularly proprioception. Romberg’s test was negative. Remaining neurological and general examination was normal.

Bloodwork showed mild liver dysfunction and positive ANA (titre 1/320, homogenous and speckled patterns). Immune screen was otherwise negative. Antineuronal antibody panel was negative in serum and CSF. CSF glucose was 3.1 mmol/L, protein 751 mg/L, albumin 523 mg/L, neopterin 24 nmol/L and B2 microglobulin 1.1 mg/L. The sample was acellular with negative EBV PCR (<500 copies/mL). Other infective serology and PCRs were also negative. MRI brain with gadolinium showed no abnormality.

The patient received supportive care and was neurologically normal within three months.

Conclusions

ACA related to EBV is rare in adults. This report is important because it documents an adult case, other ACA causes have been rigorously excluded, resolution without antiviral therapy is detailed, and investigations support an immune-mediated pathogenesis.

References

McCarthy CL, McColgan P, Martin P. Acute cerebellar ataxia due to Epstein-Barr virus. Pract Neurol 2012;12:238–240.

Lascelles RG, Longson M, Johnson PJ, Chiang A. Infectious mononucleosis presenting as acute cerebellar syndrome. Lancet 1973;2:707.

Combination of Searches for Invisible Higgs Boson Decays with the ATLAS Experiment

Dark matter particles, if sufficiently light, may be produced in decays of the Higgs boson. This Letter presents a statistical combination of searches for H→invisible decays where H is produced according to the standard model via vector boson fusion, Z(ℓℓ)H, and W/Z(had)H, all performed with the ATLAS detector using 36.1  fb^{-1} of pp collisions at a center-of-mass energy of sqrt[s]=13  TeV at the LHC. In combination with the results at sqrt[s]=7 and 8 TeV, an exclusion limit on the H→invisible branching ratio of 0.26(0.17_{-0.05}^{+0.07}) at 95% confidence level is observed (expected).

Search for the Production of a Long-Lived Neutral Particle Decaying within the ATLAS Hadronic Calorimeter in Association with a Z Boson from pp Collisions at sqrt[s]=13 TeV

This Letter presents a search for the production of a long-lived neutral particle (Z_{d}) decaying within the ATLAS hadronic calorimeter, in association with a standard model (SM) Z boson produced via an intermediate scalar boson, where Z→ℓ^{+}ℓ^{-} (ℓ=e, μ). The data used were collected by the ATLAS detector during 2015 and 2016 pp collisions with a center-of-mass energy of sqrt[s]=13  TeV at the Large Hadron Collider and correspond to an integrated luminosity of 36.1±0.8  fb^{-1}. No significant excess of events is observed above the expected background. Limits on the production cross section of the scalar boson times its decay branching fraction into the long-lived neutral particle are derived as a function of the mass of the intermediate scalar boson, the mass of the long-lived neutral particle, and its cτ from a few centimeters to one hundred meters. In the case that the intermediate scalar boson is the SM Higgs boson, its decay branching fraction to a long-lived neutral particle with a cτ approximately between 0.1 and 7 m is excluded with a 95% confidence level up to 10% for m_{Z_{d}} between 5 and 15 GeV.

Abstract P1-01-02: Quantitative breast MRI to predict response to neoadjuvant therapy in community imaging centers: Preliminary results

Introduction: Early response assessment to neoadjuvant therapy (NAT) for locally advanced breast cancer would allow for more accurate prognosis and provide the opportunity to replace an ineffective treatment with an alternative regimen. This could potentially increase systemic treatment efficacy and avoid unnecessary side effects from ineffective therapies. Quantitative MRI has been shown to be beneficial in predicting breast tumor response to treatment early during the course of NAT within many academic environments. Importantly, integrating quantitative imaging techniques into the community-based setting has the potential to reach a large percentage of breast cancer patients, as most patients receive their care at private practice or community hospitals. This study evaluated the ability to implement quantitative dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) data in the community setting to predict the eventual response of breast tumors to NAT.

Experimental Design: Women undergoing NAT for breast cancer (N=16) were scanned with DCE-MRI and DW-MRI at baseline (prior to beginning therapy, t1) and three longitudinal time points during the course of NAT to evaluate early response to therapy (t2, t3, t4). MRI was performed at two community imaging centers using a 3T Siemens Skyra scanners equipped with 8- or 16-channel breast coils. DW-MRI was acquired with a spin echo sequence with TR/TE = 3000/52 ms, b-values of 200, 800 s/mm2 and used to compute the apparent diffusion coefficient (ADC) values for every voxel. DCE-MRI data was collected (following a pre-contrast T1 map) with TR/TE/α = 7.02 ms/4.60 ms/6o, and a temporal resolution of 7.27 sec for eight minutes. A catheter placed within an antecubital vein delivered gadolinium-based contrast agent (0.1 mmol/kg of Multihance or 10 mL of Gadovist) at 2 mL/sec via a power injector after the acquisition of the first minute of dynamic scans (baseline).Quantitative measures of ADC (evaluating cellularity from DW-MRI) and Ktrans(evaluating vascular perfusion and permeability from DCE-MRI) were calculated for the segmented tumor volume. Imaging was compared to pathology reports at the conclusion of NAT.

Results:The patients (n = 6) achieving a pathological complete response (pCR) revealed a 12.9% ± 19.1% increase in the mean ADC values of the tumor from t1 and t2. Conversely, patients (n = 10) that had residual disease burden after NAT (i.e., a non-pCR) had a decreased ADC, revealing a -8.0% ± 19.2% change between t1 and t2 (p = 0.06). The mean Ktrans values of the tumor decreased showing a change of -61.4% ± 18.2% from t1 to t2 in the pCR patients. Conversely, non-pCR patients had a 10.2% ± 80.4% increase in Ktrans between t1 and t2 (p = 0.14)

Conclusion:Preliminary evidence reveals that quantitative DCE-MRI and DW-MRI can be implemented in community-based imaging settings to predict the response of breast tumors to NAT. Thus, our results provide evidence that quantitative DW-MRI and DCE-MRI can be disseminated across community imaging facilities, thereby dramatically increasing the patient population for which these techniques can serve.

We acknowledge the support of CPRIT RR160005.

Citation Format: Sorace AG, Virostko J, Wu C, Jarrett AM, Barnes SL, Ekrut D, Patt D, Goodgame B, Avery S, Yankeelov TE. Quantitative breast MRI to predict response to neoadjuvant therapy in community imaging centers: Preliminary results [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-01-02.

Mapping DNA sequence to transcription factor binding energy in vivo

Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site’s DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 k_BT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor’s sequence specificity.

It has been said that we live in the “genomic era,” a time where we can readily sequence full genomes at will. However, it remains difficult to interpret much of the information within a genome. This is especially true of non-coding sequences such as promoters, which contain a number of features such as transcription factor binding sites that determine how genes are regulated. There is no straightforward regulatory “code” that tells us how transcription factor binding sites are organized within a promoter. In this work we examine how DNA sequence determines one of the most important features of a promoter, the strength with which a transcription factor binds to its DNA binding site. We discuss an approach to modeling DNA sequence-specific transcription factor binding energies in vivo using a massively parellel reporter assay. We develop models that allow us to predict the binding energy between a transcription factor and a mutated version of its binding site. We then show that this modeling technique can be used to address a number of scientific and design questions, such as engineering the behavior of genetic circuit elements or examining how transcription factors and their binding sites co-evolve.

Combination of the Searches for Pair-Produced Vectorlike Partners of the Third-Generation Quarks at sqrt[s]=13 TeV with the ATLAS Detector

A combination of the searches for pair-produced vectorlike partners of the top and bottom quarks in various decay channels (T→Zt/Wb/Ht, B→Zb/Wt/Hb) is performed using 36.1  fb^{-1} of pp collision data at sqrt[s]=13  TeV with the ATLAS detector at the Large Hadron Collider. The observed data are found to be in good agreement with the standard model background prediction in all individual searches. Therefore, combined 95% confidence-level upper limits are set on the production cross section for a range of vectorlike quark scenarios, significantly improving upon the reach of the individual searches. Model-independent limits are set assuming the vectorlike quarks decay to standard model particles. A singlet T is excluded for masses below 1.31 TeV and a singlet B is excluded for masses below 1.22 TeV. Assuming a weak isospin (T,B) doublet and |V_{Tb}|≪|V_{tB}|, T and B masses below 1.37 TeV are excluded.

Observation of Centrality-Dependent Acoplanarity for Muon Pairs Produced via Two-Photon Scattering in Pb+Pb Collisions at sqrt[s_{NN}]=5.02 TeV with the ATLAS Detector

This Letter presents a measurement of γγ→μ^{+}μ^{-} production in Pb+Pb collisions recorded by the ATLAS detector at the Large Hadron Collider at sqrt[s_{NN}]=5.02  TeV with an integrated luminosity of 0.49  nb^{-1}. The azimuthal angle and transverse momentum correlations between the muons are measured as a function of collision centrality. The muon pairs are produced from γγ through the interaction of the large electromagnetic fields of the nuclei. The contribution from background sources of muon pairs is removed using a template fit method. In peripheral collisions, the muons exhibit a strong back-to-back correlation consistent with previous measurements of muon pair production in ultraperipheral collisions. The angular correlations are observed to broaden significantly in central collisions. The modifications are qualitatively consistent with rescattering of the muons while passing through the hot matter produced in the collision.

Search for Resonant and Nonresonant Higgs Boson Pair Production in the bb[over ¯]τ^{+}τ^{-} Decay Channel in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

A search for resonant and nonresonant pair production of Higgs bosons in the bb[over ¯]τ^{+}τ^{-} final state is presented. The search uses 36.1  fb^{-1} of pp collision data with sqrt[s]=13  TeV recorded by the ATLAS experiment at the LHC in 2015 and 2016. Decays of the τ-lepton pairs with at least one τ lepton decaying to final states with hadrons and a neutrino are considered. No significant excess above the expected background is observed in the data. The cross-section times branching ratio for nonresonant Higgs boson pair production is constrained to be less than 30.9 fb, 12.7 times the standard model expectation, at 95% confidence level. The data are also analyzed to probe resonant Higgs boson pair production, constraining a model with an extended Higgs sector based on two doublets and a Randall-Sundrum bulk graviton model. Upper limits are placed on the resonant Higgs boson pair production cross-section times branching ratio, excluding resonances X in the mass range 305  GeV<m_{X}<402  GeV in the simplified hMSSM minimal supersymmetric model for tanβ=2 and excluding bulk Randall-Sundrum gravitons G_{KK} in the mass range 325  GeV<m_{G_{KK}}<885  GeV for k/M[over ¯]_{Pl}=1.

Probing the Quantum Interference between Singly and Doubly Resonant Top-Quark Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

This Letter presents a normalized differential cross-section measurement in a fiducial phase-space region where interference effects between top-quark pair production and associated production of a single top quark with a W boson and a b-quark are significant. Events with exactly two leptons (ee, μμ, or eμ) and two b-tagged jets that satisfy a multiparticle invariant mass requirement are selected from 36.1  fb^{-1} of proton-proton collision data taken at sqrt[s]=13  TeV with the ATLAS detector at the LHC in 2015 and 2016. The results are compared with predictions from simulations using various strategies for the interference. The standard prescriptions for interference modeling are significantly different from each other but are within 2σ of the data. State-of-the-art predictions that naturally incorporate interference effects provide the best description of the data in the measured region of phase space most sensitive to these effects. These results provide an important constraint on interference models and will guide future model development and tuning.

Measurement of the Soft-Drop Jet Mass in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

Jet substructure observables have significantly extended the search program for physics beyond the standard model at the Large Hadron Collider. The state-of-the-art tools have been motivated by theoretical calculations, but there has never been a direct comparison between data and calculations of jet substructure observables that are accurate beyond leading-logarithm approximation. Such observables are significant not only for probing the collinear regime of QCD that is largely unexplored at a hadron collider, but also for improving the understanding of jet substructure properties that are used in many studies at the Large Hadron Collider. This Letter documents a measurement of the first jet substructure quantity at a hadron collider to be calculated at next-to-next-to-leading-logarithm accuracy. The normalized, differential cross section is measured as a function of log_{10}ρ^{2}, where ρ is the ratio of the soft-drop mass to the ungroomed jet transverse momentum. This quantity is measured in dijet events from 32.9  fb^{-1} of sqrt[s]=13  TeV proton-proton collisions recorded by the ATLAS detector. The data are unfolded to correct for detector effects and compared to precise QCD calculations and leading-logarithm particle-level Monte Carlo simulations.

Search for Low-Mass Dijet Resonances Using Trigger-Level Jets with the ATLAS Detector in pp Collisions at sqrt[s]=13 TeV

Searches for dijet resonances with sub-TeV masses using the ATLAS detector at the Large Hadron Collider can be statistically limited by the bandwidth available to inclusive single-jet triggers, whose data-collection rates at low transverse momentum are much lower than the rate from standard model multijet production. This Letter describes a new search for dijet resonances where this limitation is overcome by recording only the event information calculated by the jet trigger algorithms, thereby allowing much higher event rates with reduced storage needs. The search targets low-mass dijet resonances in the range 450-1800 GeV. The analyzed data set has an integrated luminosity of up to 29.3  fb^{-1} and was recorded at a center-of-mass energy of 13 TeV. No excesses are found; limits are set on Gaussian-shaped contributions to the dijet mass distribution from new particles and on a model of dark-matter particles with axial-vector couplings to quarks.

Abstract 3043: Quantitative MRI during neoadjuvant therapy for predicting breast cancer response in the community setting

Purpose: Quantification of accurate and early response to neoadjuvant therapy (NAT) provides the opportunity to replace an ineffective treatment with an alternative regimen, thereby potentially avoiding ineffective systemic therapy. Quantitative magnetic resonance imaging (MRI) has been shown to predict breast cancer response to treatment early during the course of NAT within academic medical centers. Integrating quantitative imaging techniques into community-based medical practices has the potential to reach a larger percentage of breast cancer patients, and allow more community center participation in clinical trials that require quantitative imaging. This study evaluated the reproducibility and accuracy of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in the community setting and the ability to implement these techniques to predict the eventual response of breast tumors to NAT.

Experiment Procedure: MRI was performed at two community imaging centers and one academic research facility using a 3T Siemens Skyra scanners equipped with a breast coil. To assess reproducibility across sites, normal subjects (N=3) were scanned at three imaging centers. Quantitative T1 (required for pharmacokinetic modeling of DCE-MRI) and apparent diffusion coefficient (ADC) maps were calculated of normal fibroglandular breast tissue. Accuracy was tested through evaluation of T1 and DW-MRI in phantoms. Women undergoing NAT for breast cancer (N=10) were scanned with DCE-MRI and DW-MRI at baseline (prior to beginning therapy) and three longitudinal time points during the course of NAT to evaluate early prediction of response to therapy. Quantitative measures of ADC (evaluating cellularity from DW-MRI) and Ktrans (evaluating vascular perfusion and permeability from DCE-MRI) were calculated for the segmented tumor volume. Imaging was compared to pathology reports at the conclusion of NAT.

Results: Reproducibility scans of normal breast fibroglandular tissue yielded an average difference of 8.4% and 7.0% in T1 and ADC measurements, respectively, across sites. Phantom studies revealed accurate measurements of T1 mapping and ADC, with reproducibility measurements showing a difference of 2.8% and 1.6%, respectively. Patients achieving a pathological complete response (pCR) revealed a 13.8% ± 19.0% increase in the mean ADC values of the tumor from t1 (baseline, prior to beginning NAT) and t2 (following one round of NAT) and a 15.4% ± 40.9% decrease in mean Ktrans. Conversely, patients that did not achieve non-pCR had little change in ADC (-0.9% ± 12.6% change between t1 and t2) and a 15.3% ± 42.8% increase in Ktrans.

Conclusions: Quantitative MRI has been shown to be accurate and reproducible across community medical centers. Furthermore, the preliminary results discussed above parallel those previously reported in the academic research setting.

Citation Format: Anna Sorace, Jack Virostko, Chengyue Wu, Angela M. Jarrett, Stephanie L. Barnes, Debra Patt, Boone Goodgame, Sarah Avery, Thomas E. Yankeelov. Quantitative MRI during neoadjuvant therapy for predicting breast cancer response in the community setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3043.

The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains

PURPOSE

Quantitative evaluation of dynamic contrast enhanced MRI (DCE-MRI) allows for estimating perfusion, vessel permeability, and tissue volume fractions by fitting signal intensity curves to pharmacokinetic models. These compart mental models assume rapid equilibration of contrast agent within each voxel. However, there is increasing evidence that this assumption is violated for small molecular weight gadolinium chelates. To evaluate the error introduced by this invalid assumption, we simulated DCE-MRI experiments with volume fractions computed from entire histological tumor cross-sections obtained from murine studies.

METHODS

A 2D finite element model of a diffusion-compensated Tofts-Kety model was developed to simulate dynamic T₁ signal intensity data. Digitized histology slices were segmented into vascular (v_p ), cellular and extravascular extracellular (v_e ) volume fractions. Within this domain, K^trans (the volume transfer constant) was assigned values from 0 to 0.5 min^-1 . A representative signal enhancement curve was then calculated for each imaging voxel and the resulting simulated DCE-MRI data analyzed by the extended Tofts-Kety model.

RESULTS

Results indicated parameterization errors of -19.1% ± 10.6% in K^trans , -4.92% ± 3.86% in v_e , and 79.5% ± 16.8% in v_p for use of Gd-DTPA over 4 tumor domains.

CONCLUSION

These results indicate a need for revising the standard model of DCE-MRI to incorporate a correction for slow diffusion of contrast agent. Magn Reson Med 80:330-340, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Search for the Decay of the Higgs Boson to Charm Quarks with the ATLAS Experiment

A direct search for the standard model Higgs boson decaying to a pair of charm quarks is presented. Associated production of the Higgs and Z bosons, in the decay mode ZH→ℓ^{+}ℓ^{-}cc[over ¯] is studied. A data set with an integrated luminosity of 36.1  fb^{-1} of pp collisions at sqrt[s]=13TeV recorded by the ATLAS experiment at the LHC is used. The H→cc[over ¯] signature is identified using charm-tagging algorithms. The observed (expected) upper limit on σ(pp→ZH)×B(H→cc[over ¯]) is 2.7 (3.9_{-1.1}^{+2.1}) pb at the 95% confidence level for a Higgs boson mass of 125 GeV, while the standard model value is 26 fb.

Search for a Structure in the B_{s}^{0}π^{±} Invariant Mass Spectrum with the ATLAS Experiment

A search for the narrow structure, X(5568), reported by the D0 Collaboration in the decay sequence X→B_{s}^{0}π^{±}, B_{s}^{0}→J/ψϕ, is presented. The analysis is based on a data sample recorded with the ATLAS detector at the LHC corresponding to 4.9  fb^{-1} of pp collisions at 7 TeV and 19.5  fb^{-1} at 8 TeV. No significant signal was found. Upper limits on the number of signal events, with properties corresponding to those reported by D0, and on the X production rate relative to B_{s}^{0} mesons, ρ_{X}, were determined at 95% confidence level. The results are N(X)<382 and ρ_{X}<0.015 for B_{s}^{0} mesons with transverse momenta above 10 GeV, and N(X)<356 and ρ_{X}<0.016 for transverse momenta above 15 GeV. Limits are also set for potential B_{s}^{0}π^{±} resonances in the mass range 5550 to 5700 MeV.

Search for High-Mass Resonances Decaying to τν in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

A search for high-mass resonances decaying to τν using proton-proton collisions at sqrt[s]=13  TeV produced by the Large Hadron Collider is presented. Only τ-lepton decays with hadrons in the final state are considered. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1  fb^{-1}. No statistically significant excess above the standard model expectation is observed; model-independent upper limits are set on the visible τν production cross section. Heavy W^{'} bosons with masses less than 3.7 TeV in the sequential standard model and masses less than 2.2-3.8 TeV depending on the coupling in the nonuniversal G(221) model are excluded at the 95% credibility level.

Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer

PURPOSE

To develop and investigate a set of biophysical models based on a mechanically coupled reaction-diffusion model of the spatiotemporal evolution of tumor growth after radiation therapy.

METHODS AND MATERIALS

Post-radiation therapy response is modeled using a cell death model (Md), a reduced proliferation rate model (Mp), and cell death and reduced proliferation model (Mdp). To evaluate each model, rats (n = 12) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging (MRI) and contrast-enhanced MRI at 7 time points over 2 weeks. Rats received either 20 or 40 Gy between the third and fourth imaging time point. Diffusion-weighted MRI was used to estimate tumor cell number within enhancing regions in contrast-enhanced MRI data. Each model was fit to the spatiotemporal evolution of tumor cell number from time point 1 to time point 5 to estimate model parameters. The estimated model parameters were then used to predict tumor growth at the final 2 imaging time points. The model prediction was evaluated by calculating the error in tumor volume estimates, average surface distance, and voxel-based cell number.

RESULTS

For both the rats treated with either 20 or 40 Gy, significantly lower error in tumor volume, average surface distance, and voxel-based cell number was observed for the Mdp and Mp models compared with the Md model. The Mdp model fit, however, had significantly lower sum squared error compared with the Mp and Md models.

CONCLUSIONS

The results of this study indicate that for both doses, the Mp and Mdp models result in accurate predictions of tumor growth, whereas the Md model poorly describes response to radiation therapy.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting

BACKGROUND

Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer.

PURPOSE/HYPOTHESIS

To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices.

STUDY TYPE

Prospective.

SUBJECTS/PHANTOM

Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability.

FIELD STRENGTH/SEQUENCE

3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping.

ASSESSMENT

Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast.

STATISTICAL TESTS

Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility.

RESULTS

ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively).

DATA CONCLUSION

Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial

Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and K^trans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis

This meta-analysis assesses the prognostic value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) performed during neoadjuvant therapy (NAT) of locally advanced breast cancer. A systematic literature search was conducted to identify studies of quantitative DCE-MRI and DW-MRI performed during breast cancer NAT that report the sensitivity and specificity for predicting pathological complete response (pCR). Details of the study population and imaging parameters were extracted from each study for subsequent meta-analysis. Metaregression analysis, subgroup analysis, study heterogeneity, and publication bias were assessed. Across 10 studies that met the stringent inclusion criteria for this meta-analysis (out of 325 initially identified studies), we find that MRI had a pooled sensitivity of 0.91 [95% confidence interval (CI), 0.80 to 0.96] and specificity of 0.81(95% CI, 0.68 to 0.89) when adjusted for covariates. Quantitative DCE-MRI exhibits greater specificity for predicting pCR than semiquantitative DCE-MRI (p<0.001). Quantitative DCE-MRI and DW-MRI are able to predict, early in the course of NAT, the eventual response of breast tumors, with a high level of specificity and sensitivity. However, there is a high degree of heterogeneity in published studies highlighting the lack of standardization in the field.

Search for Heavy Higgs Bosons A/H Decaying to a Top Quark Pair in pp Collisions at sqrt[s]=8 TeV with the ATLAS Detector

A search for heavy pseudoscalar (A) and scalar (H) Higgs bosons decaying into a top quark pair (tt[over ¯]) has been performed with 20.3  fb^{-1} of proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider at a center-of-mass energy sqrt[s]=8  TeV. Interference effects between the signal process and standard model tt[over ¯] production, which are expected to distort the signal shape from a single peak to a peak-dip structure, are taken into account. No significant deviation from the standard model prediction is observed in the tt[over ¯] invariant mass spectrum in final states with an electron or muon, large missing transverse momentum, and at least four jets. The results are interpreted within the context of a type-II two-Higgs-doublet model. Exclusion limits on the signal strength are derived as a function of the mass m_{A/H} and the ratio of the vacuum expectation values of the two Higgs fields, tanβ, for m_{A/H}>500  GeV.

Search for Dark Matter Produced in Association with a Higgs Boson Decaying to bb[over ¯] Using 36 fb^{-1} of pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

Several extensions of the standard model predict associated production of dark-matter particles with a Higgs boson. Such processes are searched for in final states with missing transverse momentum and a Higgs boson decaying to a bb[over ¯] pair with the ATLAS detector using 36.1  fb^{-1} of pp collisions at a center-of-mass energy of 13 TeV at the LHC. The observed data are in agreement with the standard model predictions and limits are placed on the associated production of dark-matter particles and a Higgs boson.

DCE- and DW-MRI as early imaging biomarkers of treatment response in a preclinical model of triple negative breast cancer

This work evaluates quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) parameters as early biomarkers of response in a preclinical model of triple negative breast cancer (TNBC). The standard Tofts' model of DCE-MRI returns estimates of the volume transfer constant (K^trans ) and the extravascular extracellular volume fraction (v_e ). DW-MRI returns estimates of the apparent diffusion coefficient (ADC). Mice (n = 38) were injected subcutaneously with MDA-MB-231. Tumors were grown to approximately 275 mm³ and sorted into the following groups: saline controls, low-dose Abraxane (15 mg/kg) and high-dose Abraxane (25 mg/kg). Animals were imaged at days zero, one and three. On day three, tumors were extracted for immunohistochemistry. The positive percentage change in ADC on day one was significantly higher in both treatment groups relative to the control group (p < 0.05). In addition, the positive percentage change in K^trans was significantly higher than controls (p < 0.05) on day one for the high-dose group and on days one and three for the low-dose group. The percentage change in tumor volume was significantly different between the high-dose and control groups on day three (p = 0.006). Histology confirmed differences at day three through reduced numbers of proliferating cells (Ki67 staining) in the high-dose group (p = 0.03) and low-dose group (p = 0.052) compared with the control group. Co-immunofluorescent staining of vascular maturity [using von Willebrand Factor (vWF) and α-smooth muscle actin (α-SMA)] indicated significantly higher vascular maturation in the low-dose group compared with the controls on day three (p = 0.03), and trending towards significance in the high-dose group compared with controls on day three (p = 0.052). These results from quantitative imaging with histological validation indicate that ADC and K^trans have the potential to serve as early biomarkers of treatment response in murine studies of TNBC.

A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict in vivo glioma growth

While gliomas have been extensively modelled with a reaction-diffusion (RD) type equation it is most likely an oversimplification. In this study, three mathematical models of glioma growth are developed and systematically investigated to establish a framework for accurate prediction of changes in tumour volume as well as intra-tumoural heterogeneity. Tumour cell movement was described by coupling movement to tissue stress, leading to a mechanically coupled (MC) RD model. Intra-tumour heterogeneity was described by including a voxel-specific carrying capacity (CC) to the RD model. The MC and CC models were also combined in a third model. To evaluate these models, rats (n = 14) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging over 10 days to estimate tumour cellularity. Model parameters were estimated from the first three imaging time points and then used to predict tumour growth at the remaining time points which were then directly compared to experimental data. The results in this work demonstrate that mechanical-biological effects are a necessary component of brain tissue tumour modelling efforts. The results are suggestive that a variable tissue carrying capacity is a needed model component to capture tumour heterogeneity. Lastly, the results advocate the need for additional effort towards capturing tumour-to-tissue infiltration.

Search for the Dimuon Decay of the Higgs Boson in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

A search for the dimuon decay of the Higgs boson was performed using data corresponding to an integrated luminosity of 36.1  fb^{-1} collected with the ATLAS detector in pp collisions at sqrt[s]=13  TeV at the Large Hadron Collider. No significant excess is observed above the expected background. The observed (expected) upper limit on the cross section times branching ratio is 3.0 (3.1) times the Standard Model prediction at the 95% confidence level for a Higgs boson mass of 125 GeV. When combined with the pp collision data at sqrt[s]=7  TeV and sqrt[s]=8  TeV, the observed (expected) upper limit is 2.8 (2.9) times the Standard Model prediction.

A Predictive Mathematical Modeling Approach for the Study of Doxorubicin Treatment in Triple Negative Breast Cancer

Doxorubicin forms the basis of chemotherapy regimens for several malignancies, including triple negative breast cancer (TNBC). Here, we present a coupled experimental/modeling approach to establish an in vitro pharmacokinetic/pharmacodynamic model to describe how the concentration and duration of doxorubicin therapy shape subsequent cell population dynamics. This work features a series of longitudinal fluorescence microscopy experiments that characterize (1) doxorubicin uptake dynamics in a panel of TNBC cell lines, and (2) cell population response to doxorubicin over 30 days. We propose a treatment response model, fully parameterized with experimental imaging data, to describe doxorubicin uptake and predict subsequent population dynamics. We found that a three compartment model can describe doxorubicin pharmacokinetics, and pharmacokinetic parameters vary significantly among the cell lines investigated. The proposed model effectively captures population dynamics and translates well to a predictive framework. In a representative cell line (SUM-149PT) treated for 12 hours with doxorubicin, the mean percent errors of the best-fit and predicted models were 14% (±10%) and 16% (±12%), which are notable considering these statistics represent errors over 30 days following treatment. More generally, this work provides both a template for studies quantitatively investigating treatment response and a scalable approach toward predictions of tumor response in vivo.

Deconstructing the relative benefits of a universal glove and gown intervention on MRSA acquisition

BACKGROUND

The 20-site Benefits of Universal Glove and Gown (BUGG) study found that wearing gloves and gowns for all patient contacts in the intensive care unit (ICU) reduced acquisition rates of meticillin-resistant Staphylococcus aureus (MRSA). The relative importance of gloves and gowns as a barrier, improved hand hygiene, and reduced healthcare worker (HCW)-patient contact rates is unknown.

AIM

To determine what proportion of the reduction in acquisition rates observed in the BUGG study was due to improved hand hygiene, reduced contact rates, and universal glove and gown use using agent-based simulation modelling.

METHODS

An existing agent-based model to simulate MRSA transmission dynamics in an ICU was modified, and the model was calibrated using site-specific data. Model validation was completed using data collected in the BUGG study. A full 2^k factorial design was conducted to quantify the relative benefits of improving each of the aforementioned factors with respect to MRSA acquisition rates.

FINDINGS

Across 40 simulated replications for each factorial design point and intervention site, approximately 44% of the decrease in MRSA acquisition rates was due to universal glove and gown use, 38.1% of the decrease was due to improvement in hand hygiene compliance on exiting patient rooms, and 14.5% of the decrease was due to the reduction in HCW-patient contact rates.

CONCLUSION

Using mathematical modelling, the decrease in MRSA acquisition in the BUGG study was found to be due primarily to the barrier effects of gowns and gloves, followed by improved hand hygiene and lower HCW-patient contact rates.

Abstract P4-02-02: Increased tumor perfusion following treatment with trastuzumab as measured by contrast-enhanced ultrasound

Introduction: The primary purpose of this study is to determine if the order of dosing in standard-of-care (SOC) combination therapy for HER2+ breast cancer has an effect on the perfusion characteristics within the tumor. Improving the intratumoral delivery of cytotoxic systemic therapy is a significant challenge in advancing cancer treatment. Knowledge of the vascular changes following SOC treatments could enable optimizing their order and timing, potentially leading to significantly improved response. Currently, one SOC regimen for HER2+ breast cancer treatment is doxorubicin administered for 3-4 cycles prior to trastuzumab. Our goal is to quantitatively map the changes in perfusion in response to different combinations of trastuzumab plus doxorubicin treatment through imaging in a murine model of HER2+ breast cancer.

Experimental Design: BT474 breast cancer cells (1×107) were subcutaneously implanted into mice (n = 12) and randomly assigned into three treatment groups: two doses of trastuzumab (10 mg/kg) followed by doxorubicin (1.5 mg/kg), doxorubicin prior to trastuzumab (same total drug dosage as group 1), and saline. After tumors reached ~225 mm3, animals were imaged with contrast-enhanced ultrasound (CEUS) (VisualSonics Vevo 770, Definity microbubbles) before treatment (day 0), and on days 1, 3, 4, and 7. Treatment occurred on days 0, 3 and 4. Percent change (from baseline, day 0 scans) of the CEUS signal intensity quantified from the functional vasculature (surrogate for vessel perfusion) following contrast injection were measured for each animal for each day. Tumors were extracted on day 7, and sectioned, paraffin-embedded, and stained with CD31, alpha-SMA and H&E.

Results: Tumors treated with trastuzumab initially exhibited a significant increase in CEUS signal intensity (from the functional vasculature) on day 1 compared to tumors initially treated with doxorubicin (p &lt; 0.01). Additionally, compared to the control tumors, tumors treated with trastuzumab prior to doxorubicin revealed a significant increase in perfusion (change in signal intensity of functional vasculature) of contrast agent on days 3 (p = 0.01), 4 (p = 0.001) and day 7 (p &lt; 0.01). There were no significant differences in the doxorubicin treated first group and the controls on any of the days (p &gt; 0.25). Qualitative differences were noted between control and treated groups for alpha-SMA, no apparent differences were noted in microvessel density.

Conclusion: Trastuzumab significantly improves a tumor's vascular perfusion in this HER2+ breast cancer model. Doxorubicin dosing prior to treatment with trastuzumab may potentially be hindering the intratumoral delivery of the subsequently delivered, targeted therapy. Improving the tumor's functional vasculature by altering the order of dosing of these combination therapies by giving trastuzumab prior to cytotoxic therapy has potential to enhance both the delivery and the effectiveness of these combination therapies. These data indicate a potential pathway to optimize therapeutic efficacy for individual HER2+ breast cancer patients.

Citation Format: Sorace AG, Barnes SL, Quarles CC, McIntyre JO, Yankeelov TE. Increased tumor perfusion following treatment with trastuzumab as measured by contrast-enhanced ultrasound [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-02-02.

Abstract A14: Predicting the response of triple negative breast cancer to doxorubicin

Introduction: The goal of this study is to establish a data-driven model of cytotoxic therapy that predicts in vitro cell population dynamics in response to a single doxorubicin dose. Whereas traditional therapy response assays are evaluated at a single timepoint following constant exposure to drug, this abstract focuses on a series of fluorescence microscopy experiments that characterize the temporal dynamics of SUM-149PT cell populations, a model of triple negative breast cancer, in response to time-resolved doxorubicin treatments. These data are then used to train a model to predict population dynamics following exposure to doxorubicin.

Experimental Design: SUM-149PT cells, labeled with a nuclear fluorescent marker, were seeded in microtiter plates and allowed to reach a steady proliferation rate. Doxorubicin was then introduced at concentrations ranging from 10 nM to 2.5 μM and subsequently removed via media replacement after 6, 12, or 24 hours. These cells were imaged daily via fluorescent microscopy for 25 days following application of doxorubicin. Nuclei were segmented and counted to quantify cell population. Six replicates of each of the 28 treatment conditions were collected. A logistic growth model modified by a set of time-dependent growth functions was employed for this study. Briefly, two piecewise growth functions were implemented: a constant function and a monoexponential function. The constant function assumed an immediate transition from the pre-treatment growth rate to a stable, post-treatment rate following doxorubicin exposure. The monoexponential function allowed for a smooth induction of drug effect, while ultimately allowing for recovery of the cell population. Both models were fit to each treatment condition independently using MATLAB (Natick, MA). The area under the concentration of drug versus time curve (AUC) was used to summarize each treatment condition, allowing for comparison of data from all exposure times. The ability of the model to predict population changes following treatment at new concentrations and exposure times was then evaluated. A leave-one-out approach was employed for these predictions. For each treatment condition in the test set, the Akaike information criterion (AIC) was used to select the appropriate growth model, and the appropriate parameters were learned from the training data. The average percent error of both the best fit and predicted models are reported.

Results: SUM-149PT cellular response to doxorubicin was tightly linked to both drug concentration and exposure time. Higher doses (&gt;1 μM) induced rapid cell death. Smaller doses (&lt;1 μM) induced a concentration-dependent nonlinear response defined by an initial increase in population size that, depending on exposure time, was followed by a protracted decrease in cell number and subsequent regrowth of the population. The half-maximal effect of doxorubicin was observed at an AUC of 1136 (±151) nM hr. The constant model was selected at both AUC extremes (AUC &lt; 250 and AUC &gt; 15000 nM–hr). The monoexponential model was selected at intermediate AUC's. The mean percent error of the AIC-selected models across all treatment conditions was 12.4 (±11.0) while the mean percent error of the predicted models was 14.9 (±13.0).

Conclusion: These time-resolved treatment protocols replicate the clinically observed pharmacokinetics of cytotoxic therapies more closely than the constant concentrations in previous dose-response assays. With this data-rich approach, the in vitro response of a triple negative breast cancer cell line to doxorubicin can be predicted. Of note, different models are selected over the range of AUC's to reflect the various drug mechanisms of action. This approach should allow for predictions of tumor response in animal models and, eventually, personalized, computationally-optimized treatment regimens that maximize tumor control with doxorubicin.

Citation Format: Matthew T. McKenna, Stephanie L. Barnes, Jared A. Weis, Abigail M. Searfoss, Darren R. Tyson, Erin C. Rericha, Michael I. Miga, Vito Quaranta, Thomas E. Yankeelov. Predicting the response of triple negative breast cancer to doxorubicin. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A14.

Search for triboson [Formula: see text] production in pp collisions at [Formula: see text] [Formula: see text] with the ATLAS detector

This paper reports a search for triboson [Formula: see text] production in two decay channels ([Formula: see text] and [Formula: see text] with [Formula: see text]) in proton-proton collision data corresponding to an integrated luminosity of 20.3 [Formula: see text] at a centre-of-mass energy of 8 [Formula: see text] with the ATLAS detector at the Large Hadron Collider. Events with exactly three charged leptons, or two leptons with the same electric charge in association with two jets, are selected. The total number of events observed in data is consistent with the Standard Model (SM) predictions. The observed 95% confidence level upper limit on the SM [Formula: see text] production cross section is found to be 730 fb with an expected limit of 560 fb in the absence of SM [Formula: see text] production. Limits are also set on WWWW anomalous quartic gauge couplings.

Measurement of the Inelastic Proton-Proton Cross Section at sqrt[s]=13 TeV with the ATLAS Detector at the LHC

This Letter presents a measurement of the inelastic proton-proton cross section using 60  μb^{-1} of pp collisions at a center-of-mass energy sqrt[s] of 13 TeV with the ATLAS detector at the LHC. Inelastic interactions are selected using rings of plastic scintillators in the forward region (2.07<|η|<3.86) of the detector. A cross section of 68.1±1.4  mb is measured in the fiducial region ξ=M_{X}^{2}/s>10^{-6}, where M_{X} is the larger invariant mass of the two hadronic systems separated by the largest rapidity gap in the event. In this ξ range the scintillators are highly efficient. For diffractive events this corresponds to cases where at least one proton dissociates to a system with M_{X}>13  GeV. The measured cross section is compared with a range of theoretical predictions. When extrapolated to the full phase space, a cross section of 78.1±2.9  mb is measured, consistent with the inelastic cross section increasing with center-of-mass energy.

Search for Higgs and Z Boson Decays to ϕγ with the ATLAS Detector

A search for the decays of the Higgs and Z bosons to a ϕ meson and a photon is performed with a pp collision data sample corresponding to an integrated luminosity of 2.7  fb^{-1} collected at sqrt[s]=13  TeV with the ATLAS detector at the LHC. No significant excess of events is observed above the background, and 95% confidence level upper limits on the branching fractions of the Higgs and Z boson decays to ϕγ of 1.4×10^{-3} and 8.3×10^{-6}, respectively, are obtained.

Abstract 776: Multiscale treatment response model for triple-negative breast cancer linking drug pharmacokinetics to tumor cell population dynamics

Introduction

The goal of this study is to establish a predictive model of cytotoxic therapy that incorporates in vitro drug pharmacokinetics and cell-scale therapy response data, on a cell-line specific basis. We report on a series of time-resolved fluorescence microscopy experiments to characterize the uptake of doxorubicin and its effect on the population dynamics of MDA-MB-231 cells, a model of triple negative breast cancer.

Experimental Design

We leveraged the intrinsic fluorescence of doxorubicin to measure its uptake by MDA-MB-231 cells. Cells, labeled with a fluorescent nuclear marker, were seeded in microtiter plates and incubated with doxorubicin concentrations ranging from 10 nM to 10 μM for 6, 12, or 24 hours. These plates were imaged daily via bright field and fluorescent microscopy after addition of doxorubicin. Nuclei were segmented and automatically counted to quantify cell population size. Counts were normalized to population size at time of treatment and converted to population doublings. On a separate channel, extracellular, cytoplasmic, and nuclear doxorubicin fluorescence were quantified. A compartment model describing the movement of doxorubicin from the extracellular space into cells was fit to these data. We then constructed a cell treatment response model and fit it, coupled with the compartment model, to the population data using MATLAB.

Results

MDA-MB-231 cellular response to doxorubicin was tightly linked to both drug concentration and exposure time. Higher doses (&gt; 1 μM) invariably induced rapid cell death. Smaller doses (&lt; 1 μM) induced a concentration-dependent nonlinear response defined by an initial increase in population size that, depending on exposure time, was followed by a protracted decrease in cell number. For example, when treated with 156 nM for 6, 12, and 24 hours, we observed, respectively, an average of 2.6, 2.1, and 0.67 population doublings over the first 150 hours after treatment (p &lt; 0.05 among groups). These populations then either held stable or receded out to 400 hours, when we observed net population doublings of 2.6, 1.7, and 0.037, respectively (p &lt; 0.05). Untreated cells followed a logistic growth pattern, with an average total of 4.4 population doublings.

Conclusion

These time-resolved treatment protocols replicate clinically observed pharmacokinetics of cytotoxic therapies more closely than the constant concentrations in previous dose-response assays. By explicitly considering both drug and population dynamics, our mathematical model enables exploration, in silico, of treatment protocols intractable experimentally. Predictions from model simulations can then be tested experimentally, hopefully allowing for computationally-optimized and experimentally validated treatment regimens that maximize cytotoxic effects of doxorubicin.

Citation Format: Matthew T. McKenna, Stephanie L. Barnes, Abigail Searfoss, Darren R. Tyson, Erin Rericha, Vito Quaranta, Thomas E. Yankeelov. Multiscale treatment response model for triple-negative breast cancer linking drug pharmacokinetics to tumor cell population dynamics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 776.

Observation of Long-Range Elliptic Azimuthal Anisotropies in sqrt[s]=13 and 2.76 TeV pp Collisions with the ATLAS Detector

ATLAS has measured two-particle correlations as a function of the relative azimuthal angle, Δϕ, and pseudorapidity, Δη, in sqrt[s]=13 and 2.76 TeV pp collisions at the LHC using charged particles measured in the pseudorapidity interval |η|<2.5. The correlation functions evaluated in different intervals of measured charged-particle multiplicity show a multiplicity-dependent enhancement at Δϕ∼0 that extends over a wide range of Δη, which has been referred to as the "ridge." Per-trigger-particle yields, Y(Δϕ), are measured over 2<|Δη|<5. For both collision energies, the Y(Δϕ) distribution in all multiplicity intervals is found to be consistent with a linear combination of the per-trigger-particle yields measured in collisions with less than 20 reconstructed tracks, and a constant combinatoric contribution modulated by cos(2Δϕ). The fitted Fourier coefficient, v_{2,2}, exhibits factorization, suggesting that the ridge results from per-event cos(2ϕ) modulation of the single-particle distribution with Fourier coefficients v_{2}. The v_{2} values are presented as a function of multiplicity and transverse momentum. They are found to be approximately constant as a function of multiplicity and to have a p_{T} dependence similar to that measured in p+Pb and Pb+Pb collisions. The v_{2} values in the 13 and 2.76 TeV data are consistent within uncertainties. These results suggest that the ridge in pp collisions arises from the same or similar underlying physics as observed in p+Pb collisions, and that the dynamics responsible for the ridge has no strong sqrt[s] dependence.

Measurement of the ZZ Production Cross Section in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector

The ZZ production cross section in proton-proton collisions at 13 TeV center-of-mass energy is measured using 3.2  fb^{-1} of data recorded with the ATLAS detector at the Large Hadron Collider. The considered Z boson candidates decay to an electron or muon pair of mass 66-116 GeV. The cross section is measured in a fiducial phase space reflecting the detector acceptance. It is also extrapolated to a total phase space for Z bosons in the same mass range and of all decay modes, giving 16.7_{-2.0}^{+2.2}(stat)+0.9/-0.7(syst)+1.0/-0.7(lumi)  pb. The results agree with standard model predictions.

Determination of the Ratio of b-Quark Fragmentation Fractions f(s)/f(d) in pp Collisions at √s=7 TeV with the ATLAS Detector

With an integrated luminosity of 2.47  fb(-1) recorded by the ATLAS experiment at the LHC, the exclusive decays B(s)(0)→J/ψϕ and B(d)(0)→J/ψK(*0) of B mesons produced in pp collisions at √s=7  TeV are used to determine the ratio of fragmentation fractions f(s)/f(d). From the observed B(s)(0)→J/ψϕ and B(d)(0)→J/ψK(*0) yields, the quantity (f(s)/f(d))[B(B(s)(0)→J/ψϕ)/B(B(d)(0)→J/ψK(*0))] is measured to be 0.199±0.004(stat)±0.008(syst). Using a recent theory prediction for [B(B(s)(0)→J/ψϕ)/B(B(d)(0)→J/ψK(*0))] yields (f(s)/f(d))=0.240±0.004(stat)±0.010(syst)±0.017(th). This result is based on a new approach that provides a significant improvement of the world average.

Techniques and applications of dynamic contrast enhanced magnetic resonance imaging in cancer

We first discuss several key technical issues associated with quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), and then provide examples of DCE-MRI in oncology. In particular, we examine the importance of both active and passive delivery of the contrast agent to the tissue under investigation, and repeatability/reproducibility in DCE-MRI studies. We then discuss examples of how DCE-MRI can assist in assessing and predicting therapeutic response in the neoadjuvant setting.

Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer

The purpose of this work was to determine the relationship between the apparent diffusion coefficient (ADC, from diffusion-weighted (DW) MRI), the extravascular, extracellular volume fraction (ve , from dynamic contrast-enhanced (DCE) MRI), and histological measurement of the extracellular space fraction. Athymic nude mice were injected with either human epidermal growth factor receptor 2 positive (HER2+) BT474 (n = 15) or triple negative MDA-MB-231 (n = 20) breast cancer cells, treated with either Herceptin (n = 8), Abraxane (low dose n = 7, high dose n = 6), or saline (n = 7 for each cell line), and imaged using DW- and DCE-MRI before, during, and after treatment. After the final imaging acquisition, the tissue was resected and evaluated by histological analysis. H&E-stained central slices were scanned using a digital brightfield microscope and evaluated with thresholding techniques to calculate the extracellular space. For both BT474 and MDA-MB-231, the median ADC of the central slice exhibited a significantly positive correlation with the corresponding central slice extracellular space as measured by H&E (p = 0.03, p < 0.01, respectively). Median ve calculated from the central slice showed differing results between the two cell lines. For BT474, a significant correlation between ve and extracellular space was calculated (p = 0.02), while MDA-MB-231 tumors did not demonstrate a significant correlation (p = 0.64). Additionally, there was no correlation discovered between ADC and ve with either whole tumor analysis or central slice analysis (p > 0.05). While ADC correlates well with the histologically determined fraction of extracellular space, these data add to the growing body of literature that suggests that ve derived from DCE-MRI is not a reliable biomarker of extracellular space for a range of physiological conditions.