MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

The Microwave Emission Model of Layered Snowpacks (MEMLS) was originally developed for microwave emissions of snowpacks in the frequency range 5–100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like- and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS) is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment) campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/projects/snowtools/memls.html.

Guidance of treatment decisions in risk-adapted primary radiotherapy for prostate cancer using multiparametric magnetic resonance imaging: a single center experience.

BACKGROUND Magnetic resonance imaging (MRI) of the prostate is considered to be the most precise noninvasive staging modality for localized prostate cancer. Multiparametric MRI (mpMRI) dynamic sequences have recently been shown to further increase the accuracy of staging relative to morphological imaging alone. Correct radiological staging, particularly the detection of extraprostatic disease extension, is of paramount importance for target volume definition and dose prescription in highly-conformal curative radiotherapy (RT); in addition, it may affect the risk-adapted duration of additional antihormonal therapy. The purpose of our study was to analyze the impact of mpMRI-based tumor staging in patients undergoing primary RT for prostate cancer. METHODS A total of 122 patients admitted for primary RT for prostate cancer were retrospectively analyzed regarding initial clinical and computed tomography-based staging in comparison with mpMRI staging. Both tumor stage shifts and overall risk group shifts, including prostate-specific antigen (PSA) level and the Gleason score, were assessed. Potential risk factors for upstaging were tested in a multivariate analysis. Finally, the impact of mpMRI-based staging shift on prostate RT and antihormonal therapy was evaluated. RESULTS Overall, tumor stage shift occurred in 55.7% of patients after mpMRI. Upstaging was most prominent in patients showing high-risk serum PSA levels (73%), but was also substantial in patients presenting with low-risk PSA levels (50%) and low-risk Gleason scores (45.2%). Risk group changes occurred in 28.7% of the patients with consequent treatment adaptations regarding target volume delineation and duration of androgen deprivation therapy. High PSA levels were found to be a significant risk factor for tumor upstaging and newly diagnosed seminal vesicle infiltration assessed using mpMRI. CONCLUSIONS Our findings suggest that mpMRI of the prostate leads to substantial tumor upstaging, and can considerably affect treatment decisions in all patient groups undergoing risk-adapted curative RT for prostate cancer.