Generalized Born implicit solvent models for small molecule hydration free energies.

Hydration free energy estimation of small molecules from all-atom simulations was widely investigated in recent years, as it provides an essential test of molecular force fields and our understanding of solvation effects. While explicit solvent representations result in highly accurate models, they also require extensive sampling due to the high number of solvent degrees of freedom. Implicit solvent models, such as those based on the generalized Born model for electrostatic solvation effects and a solvent accessible surface area term for nonpolar contributions (GBSA), significantly reduce the number of degrees of freedom and the computational cost to estimate hydration free energies. However, a recent survey revealed a gap in the accuracy between explicit TIP3P solvent estimates and those computed with many common GBSA models. Here we address this shortcoming by providing a thorough comparison of the performance of three implicit solvent models with different nonpolar contributions and a generalized Born term to estimate experimental hydration free energies. Starting with a minimal set of only ten atom types, we demonstrate that a nonpolar term with atom type dependent surface tension coefficients in combination with an accurate generalized Born term and fully optimized parameters performs best in estimating hydration free energies, even yielding comparable results to the explicit TIP3P water model. Analysis of our results provides evidence that the asymmetric behavior of water around oppositely charged atoms is one of the main sources of error for two of the three implicit solvent models. Explicitly accounting for this effect in the parameterization reduces the corresponding errors, suggesting this as a general strategy for improving implicit solvent models. The findings presented here will help to improve the existing generalized Born based implicit solvent models implemented in state-of-the-art molecular simulation packages.

Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics.

OBJECTIVES: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation. MATERIALS AND METHODS: The consensus was achieved by a multi-stage process. Stage 1 comprised a definition screening, a retrospective analysis with semantic mapping of terms found in 22 workflow definitions, and the compilation of an initial baseline definition. Stages 2 and 3 consisted of a Delphi process with over 45 experts hailing from sites participating in the German Research Foundation (DFG) Priority Program 2177. Stage 2 aimed to achieve a broad consensus for a definition proposal, while stage 3 identified the importance of translational challenges. RESULTS: Workflow definitions from 22 publications (published 2012-2020) were analyzed. Sixty-nine definition terms were extracted, mapped, and semantic ambiguities (e.g., homonymous and synonymous terms) were identified and resolved. The consensus definition was developed via a Delphi process. The final definition comprising seven phases and 37 aspects reached a high overall consensus (> 89% of experts "agree" or "strongly agree"). Two aspects reached no strong consensus. In addition, the Delphi process identified and characterized from the participating experts' perspective the ten most important challenges in radiomics workflows. CONCLUSION: To overcome semantic inconsistencies between existing definitions and offer a well-defined, broad, referenceable terminology, a consensus workflow definition for radiomics-based setups and a terms mapping to existing literature was compiled. Moreover, the most relevant challenges towards clinical application were characterized. CRITICAL RELEVANCE STATEMENT: Lack of standardization represents one major obstacle to successful clinical translation of radiomics. Here, we report a consensus workflow definition on different aspects of radiomics studies and highlight important challenges to advance the clinical adoption of radiomics. KEY POINTS: Published radiomics workflow terminologies are inconsistent, hindering standardization and translation. A consensus radiomics workflow definition proposal with high agreement was developed. Publicly available result resources for further exploitation by the scientific community.

Are We There Yet? The Value of Deep Learning in a Multicenter Setting for Response Prediction of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy.

This retrospective study aims to evaluate the generalizability of a promising state-of-the-art multitask deep learning (DL) model for predicting the response of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (nCRT) using a multicenter dataset. To this end, we retrained and validated a Siamese network with two U-Nets joined at multiple layers using pre- and post-therapeutic T2-weighted (T2w), diffusion-weighted (DW) images and apparent diffusion coefficient (ADC) maps of 83 LARC patients acquired under study conditions at four different medical centers. To assess the predictive performance of the model, the trained network was then applied to an external clinical routine dataset of 46 LARC patients imaged without study conditions. The training and test datasets differed significantly in terms of their composition, e.g., T-/N-staging, the time interval between initial staging/nCRT/re-staging and surgery, as well as with respect to acquisition parameters, such as resolution, echo/repetition time, flip angle and field strength. We found that even after dedicated data pre-processing, the predictive performance dropped significantly in this multicenter setting compared to a previously published single- or two-center setting. Testing the network on the external clinical routine dataset yielded an area under the receiver operating characteristic curve of 0.54 (95% confidence interval [CI]: 0.41, 0.65), when using only pre- and post-therapeutic T2w images as input, and 0.60 (95% CI: 0.48, 0.71), when using the combination of pre- and post-therapeutic T2w, DW images, and ADC maps as input. Our study highlights the importance of data quality and harmonization in clinical trials using machine learning. Only in a joint, cross-center effort, involving a multidisciplinary team can we generate large enough curated and annotated datasets and develop the necessary pre-processing pipelines for data harmonization to successfully apply DL models clinically.

Towards customizable thin-panel low-Z detector arrays: electrode design for increased spatial resolution ion chamber arrays.

The purpose of the present development is to employ 3D printing to prototype an ion chamber array with a scalable design potentially allowing increased spatial resolution and a larger active area. An additional goal is to design and fabricate a custom size thin-panel detector array with low-Z components. As a proof of principle demonstration, a medium size detector array with 30 × 30 air-vented ion chambers was 3D-printed using PLA as frame for the electrodes. The active-area is 122 mm × 120 mm with 4 × 4 mm2 spatial resolution. External electrodes are cylindrical and made from conductive PLA. Internal electrodes are made from microwire. The array is symmetric with respect to the central plane and its thickness is 10 mm including build-up/-down plates of 2.5 mm thickness. Data acquisition is realized by biasing only selected chamber rows and reading only 30 chambers at a time. To test the device for potential clinical applications, 1D dose profiles and 2D dose maps with various square and irregular fields were measured. The overall agreement with the reference doses (film and treatment planning system) was satisfactory, but the measured dose differs in the penumbra region and in the field size dependence. Both of these features are related to the thin walls between neighboring ion chambers and different lateral phantom scatter in the detector panel vs homogeneous material. We demonstrated feasibility of radiation detector arrays with minimal number of readout channels and low-cost electronics. The acquisition scheme based on selected row or column 'activation' by bias voltage is not practical for 2D dosimetry but it allows for rapid turn-around when testing of custom arrays with the aid of multiple 1D dose profiles. Future progress in this area includes overcoming the limitations due high chamber packing ratio, which leads to the lateral scattering effects.

3D printing for rapid prototyping of low-Z/density ionization chamber arrays.

PURPOSE: To explore 3D printing for rapid development of prototype thin slab low-Z/density ionization chamber arrays viable for custom needs in radiotherapy dosimetry and quality assurance (QA). MATERIALS AND METHODS: We designed and fabricated parallel plate ionization chambers and ionization chamber arrays using an off-the-shelf 3D printing equipment. Conductive components of the detectors were made of conductive polylactic acid (cPLA) and insulating components were made of acrylonitrile butadiene styrene (ABS). We characterized the detector responses using a Varian TrueBeam linac at 95 cm SSD in slab solid water phantom at 5 cm depth. We measured the current-voltage (IV) curves, the response to different energy beam lines (2.5 MV, 6 MV, 6 MV FFF) for various dose rates and compared them to responses of a commercial Exradin A12 ionization chamber. We measured off-axis ratio (OAR) for several small field static multi-leaf collimators field sizes (0.5-3 cm) and compared them to OAR data obtained for commissioning of stereotactic radiotherapy. RESULTS: We identified the printing capability and the limitations of a low-cost off-the-shelf 3D printer for rapid prototyping of detector arrays. The design of the array with sub-millimeter size features conformed to the 3D printing capabilities. IV-curve for the array showed a strong polarity effect (8%) due to the design. Results for the parallel plate and the array compared well with A12 chamber: monitor unit (MU) dependence for the array was within a few % and the response to different energy beam lines was within 1%. Off-axis dose profiles measured with the array were comparable to dose profiles obtained in water tank and stereotactic diode after accounting for the size of the chambers. Dose error was within 2% at the center of the profile and slightly larger at the penumbra. CONCLUSIONS: Rapid prototyping of ion chambers by means of low-cost 3D printing is feasible with certain limitations in the design and spatial accuracy of the printed details.

Self-powered nano-porous aerogel x-ray sensor employing fast electron current.

PURPOSE: We developed a new class of aerogel-based thin-film self-powered radiation sensors employing high-energy electron current (HEC) in periodic multilayer (high-Z | polyimide aerogel (PA) | low-Z) electrode microstructures. MATERIALS: Low-Z (Al) and high-Z (Ta) electrodes were deposited on 50 µm-thick PA films to obtain sensors with Al-PA-Ta-PA-Al structures. Sensors were tested with x rays in the 40-120 kVp range and with 2.5 MV, 6 MV, and 6 MV-FFF linac beams (TrueBeam, Varian). Performance of PA-HEC sensors was compared to commercial A12 Farmer ionization chamber as well as to radiation transport simulations using CEPXS/ONEDANT with nanometer-to-micrometer spatial resolution. The computations included periodic and single-element structures N x (Al-PA-Ta-PA-Al) with variable layer thicknesses. RESULTS: Signal from PA-HEC sensors was proportional to the simulated net leakage electron current (averaged over the PA thickness). Experimental response was linear with dose and independent of dose rate. Detector responses to different x-ray sources show higher signals for kVp photon energies, as expected, though a strong signal was obtained for MV energies as well. The signal scaled with total effective area inside the multielemental structures; for example, the yield of a multielement sensor made with 20 Ta layers compared to a single-element structure with 1 Ta layer of the same total thickness of Ta was 10 times greater for 6 MV beam and 23 times greater for 120 kVp. Beam attenuation per element in the detector was 0.5%, 1%, 3%, and 46%, respectively for 6 MV, 6 MV FFF, 2.5 MV, and 120 kVp. CONCLUSION: We demonstrated the feasibility of aerogel-based multilayer HEC radiation detector and its application for flux/dose monitoring of kVp and radiotherapy MV beams with small beam attenuation.