Leveraging the Apple Ecosystem: Easy Viewing and Sharing of Three-dimensional Perforator Visualizations via iPad/iPhone-based Augmented Reality.

We introduce a novel technique using augmented reality (AR) on smartphones and tablets, making it possible for surgeons to review perforator anatomy in three dimensions on the go. Autologous breast reconstruction with abdominal flaps remains challenging due to the highly variable anatomy of the deep inferior epigastric artery. Computed tomography angiography has mitigated some but not all challenges. Previously, volume rendering and different headsets were used to enable better three-dimensional (3D) review for surgeons. However, surgeons have been dependent on others to provide 3D imaging data. Leveraging the ubiquity of Apple devices, our approach permits surgeons to review 3D models of deep inferior epigastric artery anatomy segmented from abdominal computed tomography angiography directly on their iPhone/iPad. Segmentation can be performed in common radiology software. The models are converted to the universal scene description zipped format, which allows immediate use on Apple devices without third-party software. They can be easily shared using secure, Health Insurance Portability and Accountability Act-compliant sharing services already provided by most hospitals. Surgeons can simply open the file on their mobile device to explore the images in 3D using "object mode" natively without additional applications or can switch to AR mode to pin the model in their real-world surroundings for intuitive exploration. We believe patient-specific 3D anatomy models are a powerful tool for intuitive understanding and communication of complex perforator anatomy and would be a valuable addition in routine clinical practice and education. Using this one-click solution on existing devices that is simple to implement, we hope to streamline the adoption of AR models by plastic surgeons.

The Reconstructive Metaverse - Collaboration in Real-Time Shared Mixed Reality Environments for Microsurgical Reconstruction.

Plastic surgeons routinely use 3D-models in their clinical practice, from 3D-photography and surface imaging to 3D-segmentations from radiological scans. However, these models continue to be viewed on flattened 2D screens that do not enable an intuitive understanding of 3D-relationships and cause challenges regarding collaboration with colleagues. The Metaverse has been proposed as a new age of applications building on modern Mixed Reality headset technology that allows remote collaboration on virtual 3D-models in a shared physical-virtual space in real-time. We demonstrate the first use of the Metaverse in the context of reconstructive surgery, focusing on preoperative planning discussions and trainee education. Using a HoloLens headset with the Microsoft Mesh application, we performed planning sessions for 4 DIEP-flaps in our reconstructive metaverse on virtual patient-models segmented from routine CT angiography. In these sessions, surgeons discuss perforator anatomy and perforator selection strategies whilst comprehensively assessing the respective models. We demonstrate the workflow for a one-on-one interaction between an attending surgeon and a trainee in a video featuring both viewpoints as seen through the headset. We believe the Metaverse will provide novel opportunities to use the 3D-models that are already created in everyday plastic surgery practice in a more collaborative, immersive, accessible, and educational manner.

Suture Packaging as a Marker for Intraoperative Image Alignment in Augmented Reality on Mobile Devices.

Preoperative vascular imaging has become standard practice in the planning of microsurgical breast reconstruction. Currently, translating perforator locations from radiological findings to a patient's abdomen is often not easy or intuitive. Techniques using three-dimensional printing or patient-specific guides have been introduced to superimpose anatomy onto the abdomen for reference. Augmented and mixed reality is currently actively investigated for perforator mapping by superimposing virtual models directly onto the patient. Most techniques have found only limited adoption due to complexity and price. Additionally, a critical step is aligning virtual models to patients. We propose repurposing suture packaging as an image tracking marker. Tracking markers allow quick and easy alignment of virtual models to the individual patient's anatomy. Current techniques are often complicated or expensive and limit intraoperative use of augmented reality models. Suture packs are sterile, readily available, and can be used to align abdominal models on the patients. Using an iPad, the augmented reality models automatically align in the correct position by using a suture pack as a tracking marker. Given the ubiquity of iPads, the combination of these devices with readily available suture packs will predictably lower the barrier to entry and utilization of this technology. Here, our workflow is presented along with its intraoperative utilization. Additionally, we investigated the accuracy of this technology.

Feasibility of 3 Tesla MRI for the assessment of mid-palatal suture maturation: a retrospective pilot study.

The maxilla occupies a key position in dentofacial orthopaedics, since its transversal development can be directly influenced by orthodontic therapy. The maturation stages of the mid-palatal suture, which are obtained from cone-beam computed tomography images (CBCT), present an addition to clinical decision-making in transversal discrepancies of the upper jaw. In an endeavour to reduce ionizing radiation in adolescents and young adults, who are particularly susceptible to long term stochastic irradiation effects, we investigated the feasibility of 3 Tesla (3T) MRI in detecting the maturation stages of the mid-palatal suture. A collective of 30 patients aged 24-93 years with routine neck MRI at 3T, underwent an additional three-dimensional isotropic T1 weighted study sequence of the midface. Image evaluation was performed on axial, multi-planar formatted reconstructions of the dataset aligned to the midline axis of the palate, and curved reconstructions aligned to the concavity of the palate. Inverted images helped to achieve an image impression similar to the well-known CBCT appearance. All datasets were reviewed by three readers and mid-palatal maturation was scored twice according to Angelieri et al. Intra- and inter-rater agreement were evaluated to measure the robustness of the images for clinical evaluation. 3T MRI deemed reliable for the assessment of mid-palatal suture maturation and hence for the appraisal of the hard palate and its adjacent sutures. The data of this pilot study display the feasibility of non-ionizing cross-sectional MRI for the determination of sutural maturation stages. These findings underline the potential of MRI for orthodontic treatment planning, further contributing to the avoidance of unnecessary radiation doses.

Relative biological effectiveness of oxygen ion beams in the rat spinal cord: Dependence on linear energy transfer and dose and comparison with model predictions.

Background and purpose: Ion beams exhibit an increased relative biological effectiveness (RBE) with respect to photons. This study determined the RBE of oxygen ion beams as a function of linear energy transfer (LET) and dose in the rat spinal cord. Materials and methods: The spinal cord of rats was irradiated at four different positions of a 6 cm spread-out Bragg-peak (LET: 26, 66, 98 and 141 keV/µm) using increasing levels of single and split oxygen ion doses. Dose-response curves were established for the endpoint paresis grade II and based on ED50 (dose at 50 % effect probability), the RBE was determined and compared to model predictions. Results: When LET increased from 26 to 98 keV/µm, ED50 decreased from 17.2 ± 0.3 Gy to 13.5 ± 0.4 Gy for single and from 21.7 ± 0.4 Gy to 15.5 ± 0.5 Gy for split doses, however, at 141 keV/µm, ED50 rose again to 15.8 ± 0.4 Gy and 17.2 ± 0.4 Gy, respectively. As a result, the RBE increased from 1.43 ± 0.05 to 1.82 ± 0.08 (single dose) and from 1.58 ± 0.04 to 2.21 ± 0.08 (split dose), respectively, before declining again to 1.56 ± 0.06 for single and 1.99 ± 0.06 for split doses at the highest LET. Deviations from RBE-predictions were model-dependent. Conclusion: This study established first RBE data for the late reacting central nervous system after single and split doses of oxygen ions. The data was used to validate the RBE-dependence on LET and dose of three RBE-models. This study extends the existing data base for protons, helium and carbon ions and provides important information for future patient treatments with oxygen ions.

Newborn screening in metachromatic leukodystrophy - European consensus-based recommendations on clinical management.

INTRODUCTION: Metachromatic leukodystrophy (MLD) is a rare autosomal recessive lysosomal storage disorder resulting from arylsulfatase A enzyme deficiency, leading to toxic sulfatide accumulation. As a result affected individuals exhibit progressive neurodegeneration. Treatments such as hematopoietic stem cell transplantation (HSCT) and gene therapy are effective when administered pre-symptomatically. Newborn screening (NBS) for MLD has recently been shown to be technically feasible and is indicated because of available treatment options. However, there is a lack of guidance on how to monitor and manage identified cases. This study aims to establish consensus among international experts in MLD and patient advocates on clinical management for NBS-identified MLD cases. METHODS: A real-time Delphi procedure using eDELPHI software with 22 experts in MLD was performed. Questions, based on a literature review and workshops, were answered during a seven-week period. Three levels of consensus were defined: A) 100%, B) 75-99%, and C) 50-74% or >75% but >25% neutral votes. Recommendations were categorized by agreement level, from strongly recommended to suggested. Patient advocates participated in discussions and were involved in the final consensus. RESULTS: The study presents 57 statements guiding clinical management of NBS-identified MLD patients. Key recommendations include timely communication by MLD experts with identified families, treating early-onset MLD with gene therapy and late-onset MLD with HSCT, as well as pre-treatment monitoring schemes. Specific knowledge gaps were identified, urging prioritized research for future evidence-based guidelines. DISCUSSION: Consensus-based recommendations for NBS in MLD will enhance harmonized management and facilitate integration in national screening programs. Structured data collection and monitoring of screening programs are crucial for evidence generation and future guideline development. Involving patient representatives in the development of recommendations seems essential for NBS programs.

Increasing DIEA Perforator Detail in Three-Dimensional Photorealistic Volume-Rendering Visualizations.

SUMMARY: Preoperative computed tomographic angiography is increasingly performed before perforator flap-based reconstruction. However, radiologic two-dimensional thin slices do not allow for intuitive interpretation and translation to intraoperative findings. Three-dimensional volume rendering has been used to alleviate the need for mental two-dimensional to three-dimensional abstraction. Even though volume rendering allows for a much easier understanding of anatomy, it currently has limited utility, as the skin obstructs the view of critical structures. Using free, open-source software, the authors introduce a new skin-masking technique that allows surgeons to easily create a segmentation mask of the skin that can later be used to toggle the skin on and off. In addition, the mask can be used in other rendering applications. The authors use Cinematic Anatomy for photorealistic volume rendering and interactive exploration of computed tomographic angiography with and without skin. The authors present results from using this technique to investigate perforator anatomy in deep inferior epigastric perforator flaps and demonstrate that the skin-masking workflow is performed in less than 5 minutes. In Cinematic Anatomy, the view onto the abdominal wall and especially onto perforators becomes significantly sharper and more detailed when no longer obstructed by the skin. The authors perform a virtual, partial muscle dissection to show the intramuscular and submuscular course of the perforators. The skin-masking workflow allows surgeons to improve arterial and perforator detail in volume renderings easily and quickly by removing skin and could alternatively be performed solely using open-source and free software. The workflow can be easily expanded to other perforator flaps without the need for modification.

Carbon Ion and Photon Radiation Therapy Show Enhanced Antitumoral Therapeutic Efficacy With Neoantigen RNA-LPX Vaccines in Preclinical Colon Carcinoma Models.

PURPOSE: Personalized liposome-formulated mRNA vaccines (RNA-LPX) are a powerful new tool in cancer immunotherapy. In preclinical tumor models, RNA-LPX vaccines are known to achieve potent results when combined with conventional X-ray radiation therapy (XRT). Densely ionizing radiation used in carbon ion radiation therapy (CIRT) may induce distinct effects in combination with immunotherapy compared with sparsely ionizing X-rays. METHODS AND MATERIALS: Within this study, we investigate the potential of CIRT and isoeffective doses of XRT to mediate tumor growth inhibition and survival in murine colon adenocarcinoma models in conjunction with neoantigen (neoAg)-specific RNA-LPX vaccines encoding both major histocompatibility complex (MHC) class I- and class II-restricted tumor-specific neoantigens. We characterize tumor immune infiltrates and antigen-specific T cell responses by flow cytometry and interferon-γ enzyme-linked immunosorbent spot (ELISpot) analyses, respectively. RESULTS: NeoAg RNA-LPX vaccines significantly potentiate radiation therapy-mediated tumor growth inhibition. CIRT and XRT alone marginally prime neoAg-specific T cell responses detected in the tumors but not in the blood or spleens of mice. Infiltration and cytotoxicity of neoAg-specific T cells is strongly driven by RNA-LPX vaccines and is accompanied by reduced expression of the inhibitory markers PD-1 and Tim-3 on these cells. The neoAg RNA-LPX vaccine shows similar overall therapeutic efficacy in combination with both CIRT and XRT, even if the physical radiation dose is lower for carbon ions than for X-rays. CONCLUSIONS: We hence conclude that the combination of CIRT and neoAg RNA-LPX vaccines is a promising strategy for the treatment of radioresistant tumors.

Modeling secondary cancer risk ratios for proton versus carbon ion beam therapy: A comparative study based on the local effect model.

BACKGROUND: Ion beam therapy allows for substantial sparing of normal tissues. Besides deterministic normal-tissue complications, stochastic long-term effects like secondary cancer (SC) induction are of importance when comparing different treatment modalities. PURPOSE: To develop a modeling approach for comparison of SC risk in proton and carbon ion therapy. METHODS AND MATERIALS: The local effect model (LEM) is used to predict the relative biological effectiveness (RBE) of SC induction after particle therapy. A key feature of the new approach is the double use of the LEM, reflecting the competition between the two processes of mutation induction (leading to cancer development) and cell inactivation (leading to suppression of cancer development). Based on previous investigations, treatment plans were in this work analyzed for an idealized geometry in order to assess the underlying systematic dependencies of cancer induction. In a further step, relative SC risks were predicted for proton and carbon ion treatment plans prepared for 10 prostate cancer patients. RESULTS: We investigated the impact of factors such as treatment plan geometry, fractionation scheme, and tissue radiosensitivity to photon irradiation on the ion beam SC risk. Our model studies do not result in a clear preference for either protons or carbon ions, but rather indicate a complex interplay of different aspects. Reduced lateral scattering leads to a lower SC risk for carbon ions compared to protons at the lateral field margins in the entrance channel, while an increased risk was found closely behind the tumor due to projectile fragmentation. The fractionation scheme had little impact on the expected risk ratio. With respect to sensitivity parameters, those characterizing RBE for cell killing of potentially cancerous cells as well as of the primary tumor had the most significant impact. The observed general systematic dependencies are in agreement with results from previous model studies. The prostate patient study reveals reduced SC risks predictions for skin and bones for carbon ions as compared to protons, but higher mean risks for bladder and rectum. CONCLUSION: The methods established in this work provide a basis for further investigating treatment optimizing strategies for ion beam therapy with regard to SC risk comparisons.

A Predictive Biophysical Model of the Combined Action of Radiation Therapy and Immunotherapy of Cancer.

PURPOSE: Immunotherapy with checkpoint inhibitors has an enormous potential in therapy of metastatic cancers. Immunotherapy is generally combined with local treatments, such as radiation therapy. The time schedule of drug-radiation combination is largely based on empirical observations, and a comprehensive predictive model would be needed to optimize treatments. We present a biophysical model predicting the combined interaction and apply it to describe preclinical experimental data. METHODS AND MATERIALS: The model considers the dependences of primary and distal tumor masses, immune cell kinetics targeting tumor cells, and signals causing immune cell replenishment after radiation mechanistic interpretation of the low frequency of abscopal responses. It is benchmarked against 16 experiments with synthetic tumors in murine models. RESULTS: The model predicts that immune response is stronger for checkpoint inhibitor administration at the time of irradiation or shortly after. The model discriminates correctly between tumor remission and continued growth in all considered experimental cases, including radiation and checkpoint delivery alone or in combination. It identifies a radiation dose window maximizing immune response and avoiding on one side the understimulation of the immune system and radiation-induced depletion of the immune cell pool on the other. Consequently, abscopal effects can be established in certain circumstances only. CONCLUSIONS: The model allows a quantitative mechanistic interpretation of the interaction of radiation with checkpoint blockers and will be helpful for optimizing clinical trials.

Relative biological effectiveness of single and split helium ion doses in the rat spinal cord increases strongly with linear energy transfer.

BACKGROUND AND PURPOSE: Determination of the relative biological effectiveness (RBE) of helium ions as a function of linear energy transfer (LET) for single and split doses using the rat cervical spinal cord as model system for late-responding normal tissue. MATERIAL AND METHODS: The rat cervical spinal cord was irradiated at four different positions within a 6 cm spread-out Bragg-peak (SOBP) (LET 2.9, 9.4, 14.4 and 20.7 keV/µm) using increasing levels of single or split doses of helium ions. Dose-response curves were determined and based on TD50-values (dose at 50% effect probability using paresis II as endpoint), RBE-values were derived for the endpoint of radiation-induced myelopathy. RESULTS: With increasing LET, RBE-values increased from 1.13 ± 0.04 to 1.42 ± 0.05 (single dose) and 1.12 ± 0.03 to 1.50 ± 0.04 (split doses) as TD50-values decreased from 21.7 ± 0.3 Gy to 17.3 ± 0.3 Gy (single dose) and 30.6 ± 0.3 Gy to 22.9 ± 0.3 Gy (split doses), respectively. RBE-models (LEM I and IV, mMKM) deviated differently for single and split doses but described the RBE variation in the high-LET region sufficiently accurate. CONCLUSION: This study established the LET-dependence of the RBE for late effects in the central nervous system after single and split doses of helium ions. The results extend the existing database for protons and carbon ions and allow systematic testing of RBE-models. While the RBE-values of helium were generally lower than for carbon ions, the increase at the distal edge of the Bragg-peak was larger than for protons, making detailed RBE-modeling necessary.

The Chromatin Architectural Protein CTCF Is Critical for Cell Survival upon Irradiation-Induced DNA Damage.

CTCF is a nuclear protein initially discovered for its role in enhancer-promoter insulation. It has been shown to play a role in genome architecture and in fact, its DNA binding sites are enriched at the borders of chromatin domains. Recently, we showed that depletion of CTCF impairs the DNA damage response to ionizing radiation. To investigate the relationship between chromatin domains and DNA damage repair, we present here clonogenic survival assays in different cell lines upon CTCF knockdown and ionizing irradiation. The application of a wide range of ionizing irradiation doses (0-10 Gy) allowed us to investigate the survival response through a biophysical model that accounts for the double-strand breaks' probability distribution onto chromatin domains. We demonstrate that the radiosensitivity of different cell lines is increased upon lowering the amount of the architectural protein. Our model shows that the deficiency in the DNA repair ability is related to the changes in the size of chromatin domains that occur when different amounts of CTCF are present in the nucleus.

Comprehensive comparison of local effect model IV predictions with the particle irradiation data ensemble.

PURPOSE: The increased relative biological effectiveness (RBE) of ions is one of the key benefits of ion radiotherapy compared to conventional radiotherapy with photons. To account for the increased RBE of ions during the process of ion radiotherapy treatment planning, a robust model for RBE predictions is indispensable. Currently, at several ion therapy centers the local effect model I (LEM I) is applied to predict the RBE, which varies with biological and physical impacting factors. After the introduction of LEM I, several model improvements were implemented, leading to the current version, LEM IV, which is systematically tested in this study. METHODS: As a comprehensive RBE model should give consistent results for a large variety of ion species and energies, the particle irradiation data ensemble (PIDE) is used to systematically validate the LEM IV. The database covers over 1100 photon and ion survival experiments in form of their linear-quadratic parameters for a wide range of ion types and energies. This makes the database an optimal tool to challenge the systematic dependencies of the RBE model. After appropriate filtering of the database, 571 experiments were identified and used as test data. RESULTS: The study confirms that the LEM IV reflects the RBE systematics observed in measurements well. It is able to reproduce the dependence of RBE on the linear energy transfer (LET) as well as on the αγ /ßγ ratio for several ion species in a wide energy range. Additionally, the systematic quantitative analysis revealed precision capabilities and limits of the model. At lower LET values, the LEM IV tends to underestimate the RBE with an increasing underestimation with increasing atomic number of the ion. At higher LET values, the LEM IV overestimates the RBE for protons or helium ions, whereas the predictions for heavier ions match experimental data well. CONCLUSIONS: The LEM IV is able to predict general RBE characteristics for several ion species in a broad energy range. The accuracy of the predictions is reasonable considering the small number of input parameters needed by the model. The detailed quantification of possible systematic deviations, however, enables to identify not only strengths but also limitations of the model. The gained knowledge can be used to develop model adjustments to further improve the model accuracy, which is on the way.

Biological Impact of Target Fragments on Proton Treatment Plans: An Analysis Based on the Current Cross-Section Data and a Full Mixed Field Approach.

Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic fragments, secondary protons and fragments, is in fact challenging due to their very short range. However, considering their low residual energy and therefore high LET, the possible contribution of such heavy particles to the overall biological effect could be not negligible. In this context, we performed a systematic analysis aimed at an explicit assessment of the RBE (relative biological effectiveness, i.e., the ratio of photon to proton physical dose needed to achieve the same biological effect) contribution of target fragments in the biological dose calculations of proton fields. The TOPAS Monte Carlo code has been used to characterize the radiation field, i.e., for the scoring of primary protons and fragments in an exemplary water target. TRiP98, in combination with LEM IV RBE tables, was then employed to evaluate the RBE with a mixed field approach accounting for fragments' contributions. The results were compared with that obtained by considering only primary protons for the pristine beam and spread out Bragg peak (SOBP) irradiations, in order to estimate the relative weight of target fragments to the overall RBE. A sensitivity analysis of the secondary particles production cross-sections to the biological dose has been also carried out in this study. Finally, our modeling approach was applied to the analysis of a selection of cell survival and RBE data extracted from published in vitro studies. Our results indicate that, for high energy proton beams, the main contribution to the biological effect due to the secondary particles can be attributed to secondary protons, while the contribution of heavier fragments is mainly due to helium. The impact of target fragments on the biological dose is maximized in the entrance channels and for small α/ß values. When applied to the description of survival data, model predictions including all fragments allowed better agreement to experimental data at high energies, while a minor effect was observed in the peak region. An improved description was also obtained when including the fragments' contribution to describe RBE data. Overall, this analysis indicates that a minor contribution can be expected to the overall RBE resulting from target fragments. However, considering the fragmentation effects can improve the agreement with experimental data for high energy proton beams.

Strong Shift to ATR-Dependent Regulation of the G2-Checkpoint after Exposure to High-LET Radiation.

The utilization of high linear-energy-transfer (LET) ionizing radiation (IR) modalities is rapidly growing worldwide, causing excitement but also raising concerns, because our understanding of their biological effects is incomplete. Charged particles such as protons and heavy ions have increasing potential in cancer therapy, due to their advantageous physical properties over X-rays (photons), but are also present in the space environment, adding to the health risks of space missions. Therapy improvements and the protection of humans during space travel will benefit from a better understanding of the mechanisms underpinning the biological effects of high-LET IR. There is evidence that high-LET IR induces DNA double-strand breaks (DSBs) of increasing complexity, causing enhanced cell killing, owing, at least partly, to the frequent engagement of a low-fidelity DSB-repair pathway: alternative end-joining (alt-EJ), which is known to frequently induce severe structural chromosomal abnormalities (SCAs). Here, we evaluate the radiosensitivity of A549 lung adenocarcinoma cells to X-rays, α-particles and 56Fe ions, as well as of HCT116 colorectal cancer cells to X-rays and α-particles. We observe the expected increase in cell killing following high-LET irradiation that correlates with the increased formation of SCAs as detected by mFISH. Furthermore, we report that cells exposed to low doses of α-particles and 56Fe ions show an enhanced G2-checkpoint response which is mainly regulated by ATR, rather than the coordinated ATM/ATR-dependent regulation observed after exposure to low doses of X-rays. These observations advance our understanding of the mechanisms underpinning high-LET IR effects, and suggest the potential utility for ATR inhibitors in high-LET radiation therapy.

Modeling Radiation-Induced Neoplastic Cell Transformation In Vitro and Tumor Induction In Vivo with the Local Effect Model.

Ionizing radiation induces DNA damage to cycling cells which, if left unrepaired or misrepaired, can cause cell inactivation or heritable, viable mutations. The latter can lead to cell transformation, which is thought to be an initial step of cancer formation. Consequently, the study of radiation-induced cell transformation promises to offer insights into the general properties of radiation carcinogenesis. As for other end points, the effectiveness in inducing cell transformation is elevated for radiation qualities with high linear energy transfer (LET), and the same is true for cancer induction. In considering DNA damage as a common cause of both cell death and transformations, a worthwhile approach is to apply mathematical models for the relative biological effectiveness (RBE) of cell killing to also assess the carcinogenic potential of high-LET radiation. In this work we used an established RBE model for cell survival and clinical end points, the local effect model (LEM), to estimate the transformation probability and the carcinogenic potential of ion radiation. The provided method consists of accounting for the competing processes of cell inactivation and induction of transformations or carcinogenic events after radiation exposure by a dual use of the LEM. Correlations between both processes inferred by the number of particle impacts to individual cells were considered by summing over the distribution of hits that individual cells receive. RBE values for cell transformation in vitro were simulated for three independent data sets, which were also used to gauge the approach. The simulations reflect the general RBE systematics both in magnitude and in energy and LET dependence. To challenge the developed method, in vivo carcinogenesis was investigated using the same concepts, where the probability for cancer induction within an irradiated organ was derived from the probability of finding carcinogenic events in individual cells. The predictions were compared with experimental data of carcinogenesis in Harderian glands of mice. Again, the developed method shows the same characteristics as the experimental data. We conclude that the presented method is helpful to predictively assess RBE for both neoplastic cell transformation and tumor induction after ion exposure within a wide range of LET values. The theoretical concept requires a non-linear component in the photon dose response for carcinogenic end points as a precondition for the observed enhanced effects after ion exposure, thus contributing to a long debate in epidemiology. Future work will use the method for assessing cancer induction in radiation therapy and exposure scenarios frequently discussed in radiation protection.

Electronic Spectrum of the Tropylium Cation in the Gas Phase.

The structure and properties of the tropylium cation (C7H7+) have enthralled chemists since the prediction by Hückel in 1931 of the remarkable stability for cyclic, aromatic molecules containing six π-electrons. However, probing and understanding the excited electronic states of the isolated tropylium cation have proved challenging, as the accessible electronic transitions are weak, and there are difficulties in creating appreciable populations of the tropylium cation in the gas phase. Here, we present the first gas-phase S1 ←S0 electronic spectrum of the tropylium cation, recorded by resonance-enhanced photodissociation of weakly bound tropylium-Ar complexes. We demonstrate that the intensity of the symmetry-forbidden S1 ←S0 transition arises from Herzberg-Teller vibronic coupling between the S1 and S2 electronic states mediated by vibrational modes of e2' and e3' symmetry. The main geometry change upon excitation involves elongation of the C-C bonds. Multiconfigurational ab initio calculations predict that the S1 excited state is affected by the dynamical Jahn-Teller effect, which should lead to the appearance of additional weak bands that may be apparent in higher-resolution electronic spectra.

Same same but different: A Web-based deep learning application revealed classifying features for the histopathologic distinction of cortical malformations.

OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex remains challenging. Both entities are distinct subtypes of human malformations of cortical development that share histopathological features consisting of neuronal dyslamination with dysmorphic neurons and balloon cells. We trained a convolutional neural network (CNN) to classify both entities and visualize the results. Additionally, we propose a new Web-based deep learning application as proof of concept of how deep learning could enter the pathologic routine. METHODS: A digital processing pipeline was developed for a series of 56 cases of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex to obtain 4000 regions of interest and 200 000 subsamples with different zoom and rotation angles to train a neural network. Guided gradient-weighted class activation maps (Guided Grad-CAMs) were generated to visualize morphological features used by the CNN to distinguish both entities. RESULTS: Our best-performing network achieved 91% accuracy and 0.88 area under the receiver operating characteristic curve at the tile level for an unseen test set. Novel histopathologic patterns were found through the visualized Guided Grad-CAMs. These patterns were assembled into a classification score to augment decision-making in routine histopathology workup. This score was successfully validated by 11 expert neuropathologists and 12 nonexperts, boosting nonexperts to expert level performance. SIGNIFICANCE: Our newly developed Web application combines the visualization of whole slide images with the possibility of deep learning-aided classification between focal cortical dysplasia IIb and tuberous sclerosis complex. This approach will help to introduce deep learning applications and visualization for the histopathologic diagnosis of rare and difficult-to-classify brain lesions.

Fractionated carbon ion irradiations of the rat spinal cord: comparison of the relative biological effectiveness with predictions of the local effect model.

BACKGROUND: To determine the relative biological effectiveness (RBE) and α/ß-values after fractionated carbon ion irradiations of the rat spinal cord with varying linear energy transfer (LET) to benchmark RBE-model calculations. MATERIAL AND METHODS: The rat spinal cord was irradiated with 6 fractions of carbon ions at 6 positions within a 6 cm spread-out Bragg-peak (SOBP, LET: 16-99 keV/µm). TD50-values (dose at 50% complication probability) were determined from dose-response curves for the endpoint radiation induced myelopathy (paresis grade II) within 300 days after irradiation. Based on TD50-values of 15 MV photons, RBE-values were calculated and adding previously published data, the LET and fractional dose-dependence of the RBE was used to benchmark the local effect model (LEM I and IV). RESULTS: At six fractions, TD50-values decreased from 39.1 ± 0.4 Gy at 16 keV/µm to 17.5 ± 0.3 Gy at 99 keV/µm and the RBE increased accordingly from 1.46 ± 0.05 to 3.26 ± 0.13. Experimental α/ß-ratios ranged from 6.9 ± 1.1 Gy to 44.3 ± 7.2 Gy and increased strongly with LET. Including all available data, comparison with model-predictions revealed that (i) LEM IV agrees better in the SOBP, while LEM I fits better in the entrance region, (ii) LEM IV describes the slope of the RBE within the SOBP better than LEM I, and (iii) in contrast to the strong LET-dependence, the RBE-deviations depend only weakly on fractionation within the measured range. CONCLUSIONS: This study extends the available RBE data base to significantly lower fractional doses and performes detailed tests of the RBE-models LEM I and IV. In this comparison, LEM IV agrees better with the experimental data in the SOBP than LEM I. While this could support a model replacement in treatment planning, careful dosimetric analysis is required for the individual patient to evaluate potential clinical consequences.

Prediction of Cell Survival after Exposure to Mixed Radiation Fields with the Local Effect Model.

Mixed radiation fields comprise the most common form of radiation exposure. Given their relevance in radiation protection, cancer radiotherapy and space research, accurate predictions of the corresponding radiation effects are essential. The local effect model (LEM) allows the prediction of cell survival after ion irradiation based on the knowledge of the cells' response to photon radiation. The assumption is made that the same spatial DNA double-strand break (DSB) distributions in the cell nucleus lead to the same effects, independent of the radiation quality that produced the DSBs. This makes the LEM an ideal tool for predictions of cell survival after exposure to any mixed radiation field. In this work, the LEM is applied to calculate cell survival for extreme mixed irradiation scenarios, i.e., high-linear energy transfer (LET) ion radiation combined with low-LET photon radiation, which can be understood as a consistency test for the high-LET model. Available experimental data covering several ion species and energies in combination with photon exposure are predicted with the LEM. Furthermore, the results are compared to the microdosimetric model by Zaider and Rossi and the lesion additivity model by Lam, which allow the prediction of cell survival after exposure to mixed radiation fields based on the knowledge of the survival curves of the two radiation components. Although the LEM uses only photon dose-response data as input, it is able to compete with the empirical radiobiological models that additionally require ion dose-response curves as input. Certain experimental scenarios are presented in which the specific consideration of spatial DSB distributions could be essential for an accurate prediction of the effect of mixed radiation fields.