Revealing Hidden Potentials of the q-Space Signal in Breast Cancer

Mammography screening for early detection of breast lesions currently suffers from high amounts of false positive findings, which result in unnecessary invasive biopsies. Diffusion-weighted MR images (DWI) can help to reduce many of these false-positive findings prior to biopsy. Current approaches estimate tissue properties by means of quantitative parameters taken from generative, biophysical models fit to the q-space encoded signal under certain assumptions regarding noise and spatial homogeneity. This process is prone to fitting instability and partial information loss due to model simplicity. We reveal unexplored potentials of the signal by integrating all data processing components into a convolutional neural network (CNN) architecture that is designed to propagate clinical target information down to the raw input images. This approach enables simultaneous and target-specific optimization of image normalization, signal exploitation, global representation learning and classification. Using a multicentric data set of 222 patients, we demonstrate that our approach significantly improves clinical decision making with respect to the current state of the art.Comment: Accepted conference paper at MICCAI 201

Prognostic significance of tumor burden assessed by whole-body magnetic resonance imaging in multiple myeloma patients treated with allogeneic stem cell transplantation

Allogeneic stem cell transplantation is a therapeutic option under dispute but nonetheless chosen with increasing frequency for patients suffering from multiple myeloma in Europe. To study possible predictors of survival, 79 patients were investigated using whole-body magnetic resonance imaging to assess the visible tumor burden before and after allogeneic stem cell transplantation. Statistical analysis of clinical and imaging parameters included Cox regression models and distribution of survival time estimates (Kaplan-Meier method). Log rank test was used to determine the prognostic impact of the presence of focal lesions on survival. A higher tumor burden according to the lesion count was associated with a shorter overall survival (univariable/multivariable Cox regression: 1st magnetic resonance imaging P=0.028/P=0.048; 2nd magnetic resonance imaging P=0.008/P=0.024). Focal infiltration pattern itself seemed to be an additional adverse prognostic factor for overall survival (2nd MRI P=0.048), although no definite cut-off could be defined. Kaplan-Meier estimates at 60 months of follow up show a significant difference (Log rank P=0.04) for overall survival rates between patients with focal infiltration (32%) and those without (75%). Since this subgroup of patients may benefit from maintenance therapy, adoptive immunotherapy, or local interventions, whole-body imaging is an appropriate and highly recommendable diagnostic approach for detection of prognostically relevant lesions before and after treatment

Detecting and characterizing close-in exoplanets with vortex fiber nulling

Vortex Fiber Nulling (VFN) is an interferometric method for suppressing starlight to detect and spectroscopically characterize exoplanets. It relies on a vortex phase mask and single-mode fiber to reject starlight while simultaneously coupling up to 20% of the planet light at separations of ≾ 1λ/D, thereby enabling spectroscopic characterization of a large population of RV and transit-detected planets, among others, that are inaccessible to conventional coronagraphs. VFN has been demonstrated in the lab at visible wavelengths and here we present the latest results of these experiments. This includes polychromatic nulls of 5 10⁻⁴ in 10% bandwidth light centered around 790 nm. An upgraded testbed has been designed and is being built in the lab now; we also present a status update on that work here. Finally, we present preliminary K-band (2 micron) fiber nulling results with the infrared mask that will be used on-sky as part of a VFN mode for the Keck Planet Imager and Characterizer Instrument in 2021

A phase II study for metabolic in vivo response monitoring with sequential 18FDG-PET-CT during treatment with the EGFR-monoclonal-antibody cetuximab in metastatic colorectal cancer: the Heidelberg REMOTUX trial

BACKGROUND: The epidermal growth factor receptor monoclonal antibody cetuximab has proven activity in metastatic colorectal cancer. To date, the mechanisms of action are not completely understood. Especially the impact on tumor glucose metabolism, or tumor vascularization remains largely unclear. The understanding of mechanisms such as early changes in tumor metabolism is of clinical importance since there may be a substantial influence on choice and sequence of drug combinations. Early signals of response to cetuximab may prove useful to identify patients having a relevant clinical treatment benefit. The objective of this trial is to evaluate the predictive relevance of the relative change in (18 )F-Fluorodeoxyglucose tumor uptake for early clinical response during short-term single agent treatment with cetuximab. Early clinical response will be routinely measured according to the response evaluation criteria in solid tumors. Accompanying research includes cytokine immune monitoring and analysis of tumor proteins and tumor genes. METHODS/DESIGN: The REMOTUX trial is an investigator-initiated, prospective, open-label, single-arm, single-center early exploratory predictive study. The first (18 )F-FDG PET-CT is conducted at baseline followed by the run-in phase with cetuximab at days 1 and 8. At day 14, the second (18 )F-FDG PET-CT is performed. Subsequently, patients are treated according to the Folfiri-cetuximab regimen as an active and approved first-line regimen for metastatic colorectal carcinoma. At day 56, clinical response is evaluated with a CT-scan compared to the baseline analysis. Tracer uptake is assessed using standardized uptake values (SUVs). The main hypothesis to be tested in the primary analysis is whether or not the relative change in the SUV from baseline to day 14 has any predictive relevance for early clinical response determined at day 56. Patients are followed until death from any cause or until 24 months after the last patient has ended trial treatment. DISCUSSION: The aim of this trial is to evaluate metabolic changes in metastatic colorectal cancer during short-term single agent treatment with cetuximab and to analyse their potential of predicting early clinical response. This could be helpful to answer the question if early identification of patients not responding to cetuximab is possible. TRIAL REGISTRATION: ClinicalTrials.gov NCT200811021020; EudraCT 20090132792

EEG-BIDS, an extension to the brain imaging data structure for electroencephalography

The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard

Hierarchical Event Descriptor library schema for EEG data annotation

Standardizing terminology to describe electrophysiological events can improve both clinical care and computational research. Sharing data enriched by such standardized terminology can support advances in neuroscientific data exploration, from single-subject to mega-analysis. Machine readability of electrophysiological event annotations is essential for performing such analyses efficiently across software tools and packages. Hierarchical Event Descriptors (HED) provide a framework for describing events in neuroscience experiments. HED library schemas extend the standard HED schema vocabulary to include specialized vocabularies, such as standardized clinical terms for electrophysiological events. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for annotating EEG events, including artifacts. This study makes SCORE machine-readable by incorporating it into a HED library schema. We demonstrate the use of the HED-SCORE library schema to annotate events in example EEG data stored in Brain Imaging Data Structure (BIDS) format. Clinicians and researchers worldwide can now use the HED-SCORE library schema to annotate and then compute on electrophysiological data obtained from the human brain.Comment: 22 pages, 5 figure

Analyzing Longitudinal wb-MRI Data and Clinical Course in a Cohort of Former Smoldering Multiple Myeloma Patients: Connections between MRI Findings and Clinical Progression Patterns

The purpose of this study was to analyze size and growth dynamics of focal lesions (FL) as well as to quantify diffuse infiltration (DI) in untreated smoldering multiple myeloma (SMM) patients and correlate those MRI features with timepoint and cause of progression. We investigated 199 whole-body magnetic resonance imaging (wb-MRI) scans originating from longitudinal imaging of 60 SMM patients and 39 computed tomography (CT) scans for corresponding osteolytic lesions (OL) in 17 patients. All FLs >5 mm were manually segmented to quantify volume and growth dynamics, and DI was scored, rating four compartments separately in T1- and fat-saturated T2-weighted images. The majority of patients with at least two FLs showed substantial spatial heterogeneity in growth dynamics. The volume of the largest FL (p = 0.001, c-index 0.72), the speed of growth of the fastest growing FL (p = 0.003, c-index 0.75), the DI score (DIS, p = 0.014, c-index 0.67), and its dynamic over time (DIS dynamic, p < 0.001, c-index 0.67) all significantly correlated with the time to progression. Size and growth dynamics of FLs correlated significantly with presence/appearance of OL in CT within 2 years after the respective MRI assessment (p = 0.016 and p = 0.022). DIS correlated with decrease of hemoglobin (p < 0.001). In conclusion, size and growth dynamics of FLs correlate with prognosis and local bone destruction. Connections between MRI findings and progression patterns (fast growing FL—OL; DIS—hemoglobin decrease) might enable more precise diagnostic and therapeutic approaches for SMM patients in the future

Calendar age and puberty-related development of regional gray matter volume and white matter tracts during adolescence

Background Adolescence is a critical time for brain development. Findings from previous studies have been inconsistent, failing to distinguish the influence of pubertal status and aging on brain maturation. The current study sought to address these inconsistencies, addressing the trajectories of pubertal development and aging by longitudinally tracking structural brain development during adolescence. Methods Two cohorts of healthy children were recruited (cohort 1: 9–10 years old; cohort 2: 12–13 years old at baseline). MRI data were acquired for gray matter volume and white matter tract measures. To determine whether age, pubertal status, both or their interaction best modelled longitudinal data, we compared four multi-level linear regression models to the null model (general brain growth indexed by total segmented volume) using Bayesian model selection. Results Data were collected at baseline (n = 116), 12 months (n = 97) and 24 months (n = 84) after baseline. Findings demonstrated that the development of most regional gray matter volume, and white matter tract measures, were best modelled by age. Interestingly, precentral and paracentral regions of the cortex, as well as the accumbens demonstrated significant preference for the pubertal status model. None of the white matter tract measures were better modelled by pubertal status. Limitations: The major limitation of this study is the two-cohort recruitment. Although this allowed a faster coverage of the age span, a complete per person trajectory over 6 years of development (9–15 years) could not be investigated. Conclusions Comparing the impact of age and pubertal status on regional gray matter volume and white matter tract measures, we found age to best predict longitudinal changes. Further longitudinal studies investigating the differential influence of puberty status and age on brain development in more diverse samples are needed to replicate the present results and address mechanisms underlying norm-variants in brain development