Clinically established thermal therapies like thermo ablative approaches or adjuvant hyperthermia treatment rely on accurate thermal dose information for the evaluation and adaptation of the thermal therapy. Intratumoral temperature measurements have been correlated successfully with clinical endpoints. Magnetic resonance imaging is the most suitable technique for non-invasive thermometry avoiding complications related to invasive temperature measurements. Since the advent of MR thermometry two decades ago, numerous MR thermometry techniques have been developed continuously increasing accuracy and robustness for in vivo applications. While this progress was primarily focused on relative temperature mapping, current and future efforts will likely close the gap towards quantitative temperature readings. These efforts are essential to benchmark thermal therapy efficiency, understand temperature related biophysical and physiological processes and to use these insights to set new landmarks for diagnostic and therapeutic applications. With that in mind, this review summarizes and discusses advances in MR thermometry providing practical considerations, pitfalls and technical obstacles constraining temperature measurement accuracy, spatial and temporal resolution in vivo. Established approaches and current trends in thermal therapy hardware are surveyed with respect to potential benefits for MR thermometry.3

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Objective In Berlin, the first public SARS-CoV-2 testing site started one day after the first case in the city occured. We describe epidemiological and clinical characteristics and aim at identifying risk factors for SARS-CoV-2 detection during the first six weeks of operation. Methods Testing followed national recommendations, but was also based on the physician´s discretion. We related patient characteristics to SARS-CoV-2 test positivity for exploratory analyses using a cross-sectional, observational study design. Results Between March 3 and April 13, 2020, 5179 patients attended the site (median age 34 years; IQR 26-47 years). The median time since disease onset was 4 days (IQR 2-7 days). Among 4333 patients tested, 333 (7.7%) were positive. Test positivity increased up to 10.3% (96/929) during the first three weeks and then declined, paralleling Germany’s lock-down and the course of the epidemic in Berlin. Strict adherence to testing guidelines resulted in 10.4% (262/2530) test positivity, compared to 3.9% (71/1803) among patients tested for other indications. A nightclub was a transmission hotspot; 27.7% (26/94) of one night’s visitors were found positive. Smell and/or taste dysfunction indicated COVID-19 with 85.6% specificity (95%CI 82.1-88.1%). Some 4% (14/333) of those infected were asymptomatic. Risk factors for detection of SARS-CoV-2 infection were recent contact to a positive case (second week after contact, OR 3.42; 95%CI 2.48-4.71), travel to regions of high pandemic activity (e.g. Austria, OR 4.16; 95%CI 2.48-6.99), recent onset of symptoms (second week, OR 3.61; 95%CI 1.87-6.98), and an impaired sense of smell/taste (4.08; 95%CI 2.36-7.03). Conclusions In this young population, early-onset presentation of COVID-19 resembled flu-like symptoms, except for smell and/or taste dysfunction. Risk factors for SARS-CoV-2 detection were return from regions with high incidence and contact to confirmed SARS-CoV-2 cases, particularly when tests were administered within the first two weeks after contact and/or onset of symptoms.

The main findings were that the clinical impact of GTV changes during definitive radiotherapy is still unclear due to heterogeneous study designs with varying quality. Several potential confounding variables were found and need to be considered for future studies to evaluate GTV changes during definitive radiotherapy with respect to treatment outcome.

Lung cancer is the most common fatal malignancy in adults worldwide, and non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer diagnoses. Computed tomography (CT) is routinely used in clinical practice to determine lung cancer treatment and assess prognosis. Here, we developed LungNet, a shallow convolutional neural network for predicting outcomes of NSCLC patients. We trained and evaluated LungNet on four independent cohorts of NSCLC patients from four medical centers: Stanford Hospital (n = 129), H. Lee Moffitt Cancer Center and Research Institute (n = 185), MAASTRO Clinic (n = 311) and Charité – Universitätsmedizin (n=84). We show that outcomes from LungNet are predictive of overall survival in all four independent survival cohorts as measured by concordance indices of 0.62, 0.62, 0.62 and 0.58 on cohorts 1, 2, 3, and 4, respectively. Further, the survival model can be used, via transfer learning, for classifying benign vs malignant nodules on the Lung Image Database Consortium (n = 1010), with improved performance (AUC=0.85) versus training from scratch (AUC=0.82). LungNet can be used as a noninvasive predictor for prognosis in NSCLC patients and can facilitate interpretation of CT images for lung cancer stratification and prognostication.

We have measured the stray fields of thin permalloy (Ni 83 Fe 17 ) microstructures with different geometries and several thicknesses by magnetic-force microscopy ͑MFM͒. The MFM images are compared to corresponding images calculated from micromagnetic simulations. In particular, the type of 180°domain walls is discussed. We observe a transition from cross-tie to asymmetric Bloch walls between 70 and 100 nm film thickness. Good agreement between measurement and simulation is obtained.

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Over the last months, cases of SARS-CoV-2 surged repeatedly in many countries but could often be controlled with nonpharmaceutical interventions including social distancing. We analyzed deidentified Global Positioning System (GPS) tracking data from 1.15 to 1.4 million cell phones in Germany per day between March and November 2020 to identify encounters between individuals and statistically evaluate contact behavior. Using graph sampling theory, we estimated the contact index (CX), a metric for number and heterogeneity of contacts. We found that CX, and not the total number of contacts, is an accurate predictor for the effective reproduction number R derived from case numbers. A high correlation between CX and R recorded more than 2 wk later allows assessment of social behavior well before changes in case numbers become detectable. By construction, the CX quantifies the role of superspreading and permits assigning risks to specific contact behavior. We provide a critical CX value beyond which R is expected to rise above 1 and propose to use that value to leverage the social-distancing interventions for the coming months.