Phantosmia during proton radiation and differences in frequency of phantosmia rates based on proton craniospinal irradiation technique for pediatric brain tumor patients

BACKGROUND

Unusual olfactory perception, often referred to as "phantosmia" or "cacosmia" has been reported during brain radiotherapy (RT), but is infrequent and does not typically interfere with the ability to deliver treatment. We seek to determine the rate of phantosmia for patients treated with proton craniospinal irradiation (CSI) and identify any potential clinical or treatment-related associations.

METHODS

We performed a retrospective review of 127 pediatric patients treated with CSI, followed by a boost to the brain for primary brain tumors in a single institution between 2016 and 2021. Proton CSI was delivered with passive scattering (PS) proton technique (n = 53) or pencil beam scanning technique (PBS) (n = 74). Within the PBS group, treatment delivery to the CSI utilized a single posterior (PA) field (n = 24) or two posterior oblique fields (n = 50). We collected data on phantom smell, nausea/vomiting, and the use of medical intervention.

RESULTS

Our cohort included 80 males and 47 females. The median age of patients was 10 years (range: 3-21). Seventy-one patients (56%) received concurrent chemotherapy. During RT, 104 patients (82%) developed worsening nausea, while 63 patients (50%) reported episodes of emesis. Of those patients who were awake during CSI (n = 59), 17 (29%) reported phantosmia. In the non-sedated group, we found a higher rate of phantosmia in patients treated with PBS (n = 16, 42%) than PS (n = 1, 4.7%) (p = .002). Seventy-eight patients (61%) required medical intervention after developing nausea/vomiting or phantosmia during RT. Two patients required sedation due to the malodorous smell during CSI. We did not find any significant difference in nausea/vomiting based on treatment technique.

CONCLUSION

Proton technique significantly influenced olfactory perception with greater rates of phantosmia with PBS compared to PS. Prospective studies should be performed to determine the cause of these findings and determine techniques to minimize phantosmia during radiation therapy.

The effect of electron backscatter and charge build up in media on beam current transformer signal for ultra-high dose rate (FLASH) electron beam monitoring

OBJECTIVE

Beam current transformers (BCT) are promising detectors for real-time beam monitoring in ultra-high dose rate (UHDR) electron radiotherapy. However, previous studies have reported a significant sensitivity of the BCT signal to changes in source-to-surface distance (SSD), field size, and phantom material which have until now been attributed to the fluctuating levels of electrons backscattered within the BCT. The purpose of this study is to evaluate this hypothesis, with the goal of understanding and mitigating the variations in BCT signal due to changes in irradiation Approach: Monte Carlo simulations and experimental measurements were conducted with a UHDR-capable intra-operative electron linear accelerator to analyze the impact of backscattered electrons on BCT signal. The potential influence of charge accumulation in media as a mechanism affecting BCT signal perturbation was further investigated by examining the effects phantom conductivity and electrical grounding. Finally, the effectiveness of Faraday shielding to mitigate BCT signal variations is evaluated. Main Results: Monte Carlo simulations indicated that the fraction of electrons backscattered in water and on the collimator plastic at 6 and 9 MeV is lower than 1%, suggesting that backscattered electrons alone cannot account for the observed BCT signal variations. However, our experimental measurements confirmed previous findings of BCT response variation up to 15% for different field diameters. A significant impact of phantom type on BCT response was also observed, with variations in BCT signal as high as 14.1% when comparing measurements in water and solid water. The introduction of a Faraday shield to our applicators effectively mitigated the dependencies of BCT signal on SSD, field size, and phantom material. Significance: Our results indicate that variations in BCT signal as a function of SSD, field size, and phantom material are likely driven by an electric field originating in dielectric materials exposed to the UHDR electron beam. Strategies such as Faraday shielding were shown to effectively prevent these electric fields from affecting BCT signal, enabling reliable BCT-based electron UHDR beam monitoring.

Voxel-wise dose rate calculation in clinical pencil beam scanning proton therapy

OBJECTIVE

Clinical outcomes after proton therapy have shown some variability that is not fully understood. Different approaches have been suggested to explain the biological outcome, but none has yet provided a comprehensive and satisfactory rationale for observed toxicities. The relatively recent transition from passive scattering (PS) to pencil beam scanning (PBS) treatments has significantly increased the voxel-wise dose rate in proton therapy. In addition, the dose rate distribution is no longer uniform along the cross section of the target but rather highly heterogeneous, following the spot placement. We suggest investigating dose rate as potential contributor to a more complex proton RBE model. Approach. Due to the time structure of the PBS beam delivery the instantaneous dose rate is highly variable voxel by voxel. Several possible parameters to represent voxel-wise dose rate for a given clinical PBS treatment plan are detailed. These quantities were implemented in the scripting environment of our treatment planning system, and computations experimentally verified. Sample applications to treated patient plans are shown. Main Results. Computed dose rates we experimentally confirmed. Dose rate maps vary depending on which method is used to represent them. Mainly, the underlying time and dose intervals chosen determine the topography of the resultant distributions. The maximum dose rates experienced by any target voxel in a given PBS treatment plan in our system range from ~100 to ~450 Gy(RBE)/min, a factor of 10 - 100 increase compared to PS. These dose rate distributions are very heterogeneous, with distinct hot spots. Significance. Voxel-wise dose rates for current clinical PBS treatment plans vary greatly from clinically established practice with PS. The exploration of different dose rate measures to evaluate potential correlations with observed clinical outcomes is suggested, potentially adding a missing component in the understanding of proton RBE.

Dynamic Prediction of Toxicities in Head and Neck Cancer Radiotherapy by 3D Convolutional Neural Network Using Daily Cone-Beam CTs

PURPOSE/OBJECTIVE(S)

Radiotherapy (RT) is essential in head and neck cancer (HNC) treatments, but often causes significant toxicity. Different machine learning models have shown promise in predicting RT-induced toxicity, but none have yet integrated the fluctuating anatomical changes. By integrating daily cone-beam CTs (CBCT) allowing sequential anatomical views, our aim is to build a dynamic predictive model for three major HNC RT toxicities: reactive feeding tube placement, hospitalization and radionecrosis (RN).

MATERIALS/METHODS

292 HNC cases treated with curative RT between 2017 and 2019 at our institution were retrospectively analyzed for clinical and radiological data. VoxelMorph, a deep deformable registration model, integrated the daily anatomical deformations between each CBCT and the planning CT, then converted them to Jacobian determinant matrix (Jf). Resnet, a convolutional neural network with multiple layers was trained using a 5-fold cross validation to integrate both radiological and clinical data. Each toxicity was classified as a binary decision using the cross-entropy loss to account for a class imbalance. Its predictive performance was compared to the baseline model using only clinical data.

RESULTS

The cohort included 78% men and 22% women, with a median age of 63 years (range 35-84). Primary cancer sites were 46% oropharynx, 19% larynx, 14% oral cavity, 7.5% nasopharynx, 5% hypopharynx, 4% unknown primary and 5% others; and stage ranged between Tx-4b N0 and 3b M0 (AJCC 8th Ed). Induction chemotherapy, concurrent chemotherapy, and adjuvant RT was used in 9%, 57% and 20% of patients, respectively. The incidence of feeding tube, hospitalization and RN was 19.9%, 7.2%, and 3.8%, respectively. Integrating Jf from the 10th RT CBCT showed better accuracy for each toxicity prediction: feeding tube (69.1% > 57.2%), hospitalization (75.3% > 63.1%) and RN (85.8% > 75.7%). Integrating both the raw CBCT and Jf improved hospitalization prediction (79.0% > 73.6%). Substituting Jf for the raw CBCT improved the prediction for RN (79.7% > 74.7%) and hospitalization (73.6% > 64.4%). For feeding tube, predictive performance of the Jf model trained against deformations showed a positive correlation between its performance and the RT received (r2 > 0.9) with increasing RT fractions, with a maximum accuracy of 83.1% at the 25th fraction. No such correlation was found for RN or hospitalization prediction.

CONCLUSION

To our knowledge, this is the first study showing promising results to predict HNC RT toxicities using daily per-treatment CBCT. Next steps involve integrating both the radiomic and the dosimetric inputs to build a more powerful model. This could expand to predict therapeutic outcomes and, ultimately, could guide decisions in individualized RT.

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

Objective. To evaluate the impact of setup uncertainty reduction (SUR) and adaptation to geometrical changes (AGC) on normal tissue complication probability (NTCP) when using online adaptive head and neck intensity modulated proton therapy (IMPT).Approach.A cohort of ten retrospective head and neck cancer patients with daily scatter corrected cone-beam CT (CBCT) was studied. For each patient, two IMPT treatment plans were created: one with a 3 mm setup uncertainty robustness setting and one with no explicit setup robustness. Both plans were recalculated on the daily CBCT considering three scenarios: the robust plan without adaptation, the non-robust plan without adaptation and the non-robust plan with daily online adaptation. Online-adaptation was simulated using an in-house developed workflow based on GPU-accelerated Monte Carlo dose calculation and partial spot-intensity re-optimization. Dose distributions associated with each scenario were accumulated on the planning CT, where NTCP models for six toxicities were applied. NTCP values from each scenario were intercompared to quantify the reduction in toxicity risk induced by SUR alone, AGC alone and SUR and AGC combined. Finally, a decision tree was implemented to assess the clinical significance of the toxicity reduction associated with each mechanism.Main results. For most patients, clinically meaningful NTCP reductions were only achieved when SUR and AGC were performed together. In these conditions, total reductions in NTCP of up to 30.48 pp were obtained, with noticeable NTCP reductions for aspiration, dysphagia and xerostomia (mean reductions of 8.25, 5.42 and 5.12 pp respectively). While SUR had a generally larger impact than AGC on NTCP reductions, SUR alone did not induce clinically meaningful toxicity reductions in any patient, compared to only one for AGC alone.SignificanceOnline adaptive head and neck proton therapy can only yield clinically significant reductions in the risk of long-term side effects when combining the benefits of SUR and AGC.

Large anatomical changes in head-and-neck cancers – a dosimetric comparison of online and offline adaptive proton therapy

Purpose

This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes.

Methods

IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT.

Results

Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D₉₈ degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands.

Conclusion

Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Artificial intelligence to predict outcomes of head and neck radiotherapy

Head and neck radiotherapy induces important toxicity, and its efficacy and tolerance vary widely across patients. Advancements in radiotherapy delivery techniques, along with the increased quality and frequency of image guidance, offer a unique opportunity to individualize radiotherapy based on imaging biomarkers, with the aim of improving radiation efficacy while reducing its toxicity. Various artificial intelligence models integrating clinical data and radiomics have shown encouraging results for toxicity and cancer control outcomes prediction in head and neck cancer radiotherapy. Clinical implementation of these models could lead to individualized risk-based therapeutic decision making, but the reliability of the current studies is limited. Understanding, validating and expanding these models to larger multi-institutional data sets and testing them in the context of clinical trials is needed to ensure safe clinical implementation. This review summarizes the current state of the art of machine learning models for prediction of head and neck cancer radiotherapy outcomes.

Tattoo-Free Setup for Patients With Breast Cancer Receiving Regional Nodal Irradiation

PURPOSE

Patients undergoing regional nodal irradiation (RNI) with either 3-dimensional conformal radiation therapy (3DCRT) planning or volumetric modulated arc therapy (VMAT) receive permanent tattoos to assist with daily setup alignment and verification. With the advent of surface imaging, tattoos may not be necessary to ensure setup accuracy. We compared the accuracy of conventional tattoo-based setups to those without reference to tattoos.

METHODS AND MATERIALS

Forty-eight patients receiving RNI at our institution from July 2019 to December 2020 were identified. All patients received tattoos per standard of care. Twenty-four patients underwent setup using tattoos for initial positioning followed by surface and x-ray imaging. A subsequent 24 patients underwent positioning using surface imaging followed by x-ray imaging without reference to tattoos. Patient cohorts were balanced by treatment technique and use of deep inspiration breath hold. Treatment (including setup and delivery) time and x-ray-based shifts after surface imaging were recorded.

RESULTS

Among patients in the tattoo group receiving 3DCRT RNI, the average treatment time per fraction was 21.35 versus 19.75 minutes in the 3DCRT RNI no-tattoo cohort (P = .03). Mean 3D vector shifts for patients in the tattoo cohort were 5.6 versus 4.4 mm in the no-tattoo cohort. The average treatment time per fraction for the tattoo VMAT RNI cohort was 23.16 versus 20.82 minutes in the no-tattoo VMAT RNI cohort (P = .08). Mean 3D vector shifts for the patients in the tattoo VMAT cohort were 5.5 versus 7.1 mm in the no-tattoo VMAT cohort. Breath hold technique and body mass index did not affect accuracy in a consistent or clinically relevant way.

CONCLUSIONS

Using a combination of surface and x-ray imaging, without reference to tattoos, provides excellent accuracy in alignment and setup verification among patients receiving RNI for breast cancer, regardless of treatment technique and with reduced treatment time. Skin-based tattoos are no longer warranted for patients receiving supine RNI.

Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers

PURPOSE

To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients.

METHODS

We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDI_vol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference.

RESULTS

The maximum differences in D₉₈ between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%.

CONCLUSION

The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.

Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans

Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1-5 repeated images during treatment: 'reference adaptation', with structures drawn by a physician; 'single-DIR adaptation', using a single set of deformably propagated structures; 'multi-DIR adaptation', using robust planning with multiple deformed structure sets; 'conservative adaptation', using the intersection and union of all deformed structures; 'probabilistic adaptation', using the probability of a voxel belonging to the structure in the optimization weight; and 'no adaptation'. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast 'plausibility check', and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.

Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation

BACKGROUND/PURPOSE

Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT.

MATERIALS/METHODS

A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only.

RESULTS

The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage.

CONCLUSION

Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy

The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether plan adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OA_W), and daily online adaptation (OA_D). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo (MC) dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OA_Dmitigated random delivery errors more effectively than OA_Won a fraction per fraction basis, both OA_Wand OA_Dachieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values of D_98%ranged between 97.15% and 99.73% of the prescription dose for OA_D, with a median of 98.07%. For OA_W, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OA_Wcould be used as an alternative approach to OA_Dfor most patients in order to reduce the clinical workload.

Parametrization of multi-energy CT projection data with eigentissue decomposition

The purpose of this work is, firstly, to propose an optimized parametrization of the attenuation coefficient to describe human tissues in the context of projection-based material characterization with multi-energy CT. The approach is based on eigentissue decomposition (ETD). Secondly, to evaluate its benefits in terms of accuracy and precision of radiotherapy-related parameters against established parametrizations. The attenuation coefficient is parametrized as a linear combination of virtual materials, eigentissues, obtained by performing principal component analysis on a set of reference tissues in order to optimally represent human tissue composition. Two implementations of ETD are compared with other pre-reconstruction formalisms established for dual-energy and photon-counting CT in a simulation framework. The first implementation uses a single set of eigentissues to describe all human tissues, while the second uses different sets of eigentissues to characterize soft tissues and bones, and includes a post-reconstruction classification step. The simulation framework evaluates the reconstruction accuracy of various radiotherapy-related quantities over a range of 71 human tissues for various noise levels. Compared to conventional parametrizations, the first implementation of ETD reduces the mean error and root-mean-square error (RMSE) in two radiotherapy-related quantities (the proton stopping power and the mass energy absorption coefficient of 21 keV photons from ¹⁰³Pd seeds used in brachytherapy) for all noise levels and modalities investigated. This illustrates that a decomposition basis selected with principal component analysis is superior to an arbitrary pair of materials to describe human tissues. The mean error on radiotherapy-related parameters can be further reduced with the classification-based approach. In the context of pre-reconstruction material characterization with multi-energy CT, parametrizing the attenuation coefficient with eigentissues provides a more accurate and precise evaluation of human tissues properties for radiotherapy. Accurate quantification can thus be achieved without the need to parametrize tissues using unphysical parameters, such as the energy-dependent effective atomic number.

Influence of intravenous contrast agent on dose calculation in proton therapy using dual energy CT

The purpose of this study is to evaluate the effect of an intravenous (IV) contrast agent on proton therapy dose calculation using dual-energy computed tomography (DECT). Two DECT methods are considered. The first one, [Formula: see text], attempts to accurately predict the proton stopping powers relative to water (SPR) of contrast enhanced (CE) DECT images, while the second generates a virtual non-contrast (VNC) volume that can be processed as a native non-contrast (NC) one. Both methods are compared against single-energy computed tomography (SECT). The accuracy of SPR predicted for different concentrations of IV contrast diluted in water is first evaluated using simulated data. Results then are validated in an experimental set-up comparing SPR predictions for both NC and CE images to measurements made with a multi-layer ionisation chamber (MLIC). Finally, the impact of IV contrast on dose calculation using both SECT and DECT is evaluated for one liver and one head and neck patient. Using simulated data, DECT is shown to be less sensitive to the presence of IV contrast than SECT, although the performance of the [Formula: see text] method is sensitive to the level of beam hardening considered. For different concentrations of IV contrast diluted in water, experimental MLIC measurement of SPR agrees with DECT predictions within 3% while SECT introduce errors above 20%. This error in the SPR value results in a range error of up to 3.2 mm (2.6%) for proton beams calculated on SECT CE patient images. The error is reduced below 1 mm using DECT with the [Formula: see text] and VNC methods. Globally, it is observed that the influence of IV contrast on proton therapy dose calculation is mitigated using DECT over SECT. In patient anatomies, the VNC approach provides the best agreement with the reference dose distribution.

Patients' understanding of cellulitis and views about how best to prevent recurrent episodes: mixed-methods study in primary and secondary care

BACKGROUND

Cellulitis is a common painful infection of the skin and underlying tissues that recurs in approximately one-third of cases. The only proven strategy to reduce the risk of recurrence is long-term, low-dose antibiotics. Given current concerns about antibiotic resistance and the pressure to reduce antibiotic prescribing, other prevention strategies are needed.

OBJECTIVES

To explore patients' views about cellulitis and different ways of preventing recurrent episodes.

METHODS

Adults aged ≥ 18 years with a history of first-episode or recurrent cellulitis were invited through primary care, hospitals and advertising to complete a survey, take part in an interview or both.

RESULTS

Thirty interviews were conducted between August 2016 and July 2017. Two hundred and forty surveys were completed (response rate 17%). Triangulation of quantitative and qualitative data showed that people who have had cellulitis have wide-ranging beliefs about what can cause cellulitis and are often unaware of risk of recurrence or potential strategies to prevent recurrence. Enhanced foot hygiene, applying emollients daily, exercise and losing weight were more popular potential strategies than the use of compression stockings or long-term antibiotics. Participants expressed caution about long-term oral antibiotics, particularly those who had experienced only one episode of cellulitis.

CONCLUSIONS

People who have had cellulitis are keen to know about possible ways to prevent further episodes. Enhanced foot hygiene, applying emollients daily, exercise and losing weight were generally viewed to be more acceptable, feasible strategies than compression or antibiotics, but further research is needed to explore uptake and effectiveness in practice.

Optimized I-values for use with the Bragg additivity rule and their impact on proton stopping power and range uncertainty

Novel imaging modalities can improve the estimation of patient elemental compositions for particle treatment planning. The mean excitation energy (I-value) is a main contributor to the proton range uncertainty. To minimize their impact on beam range errors and quantify their uncertainties, the currently used I-values proposed in 1982 are revisited. The study aims at proposing a new set of optimized elemental I-values for use with the Bragg additivity rule (BAR) and establishing uncertainties on the optimized I-values and the BAR. We optimize elemental I-values for the use in compounds based on measured material I-values. We gain a new set of elemental I-values and corresponding uncertainties, based on the experimental uncertainties and our uncertainty model. We evaluate uncertainties on I-values and relative stopping powers (RSP) of 70 human tissues, taking into account statistical correlations between tissues and water. The effect of new I-values on proton beam ranges is quantified using Monte Carlo simulations. Our elemental I-values describe measured material I-values with higher accuracy than ICRU-recommended I-values (RMSE: 6.17% (ICRU), 5.19% (this work)). Our uncertainty model estimates an uncertainty component from the BAR to 4.42%. Using our elemental I-values, we calculate the I-value of water as 78.73  ±  2.89 eV, being consistent with ICRU 90 (78  ±  2 eV). We observe uncertainties on tissue I-values between 1.82-3.38 eV, and RSP uncertainties between 0.002%-0.44%. With transport simulations of a proton beam in human tissues, we observe range uncertainties between 0.31% and 0.47%, as compared to current estimates of 1.5%. We propose a set of elemental I-values well suited for human tissues in combination with the BAR. Our model establishes uncertainties on elemental I-values and the BAR, enabling to quantify uncertainties on tissue I-values, RSP as well as particle range. This work is particularly relevant for Monte Carlo simulations where the interaction probabilities are reconstructed from elemental compositions.

Unsupervised classification of tissues composition for Monte Carlo dose calculation

The purpose of this study is to investigate the potential of k-means clustering to efficiently reduce the variety of materials needed in Monte Carlo (MC) dose calculation. A numerical phantom with 31 human tissues surrounded by water is created. K-means clustering is used to group the tissues in clusters of constant elemental composition. Four different distance measures are used to perform the clustering technique: Euclidean, Standardized Euclidean, Chi-Squared and Cityblock. Dose distributions are calculated with MC simulations for both low-kV photons and MeV protons using the clustered and reference elemental composition. Comparison between the dose distributions in the clustered and non-clustered phantom are made to assess the impact of clustering with each distance measure. The statistical significance of the differences observed between the four different metrics is determined by comparing the accuracy of energy absorption coefficients (EAC) of low-kV photons and proton stopping powers relative to water (SPR) for repeated clustering procedures. The performance of the proposed approach for a larger number of original materials is evaluated similarly by using a population of 62 000 statistically generated materials grouped into classes defined with supervised and unsupervised classification. In the phantom geometry, the Chi-Squared distance is the one introducing the smallest error on dose distribution and significant differences are observed between the EAC and SPR values predicted by each distance metric. The proposed approach is also shown to be equivalent to a state-of-the-art supervised classification method for proton therapy, but beneficial for low-kV photons applications. In conclusion, k-means clustering successfully reduces the variety of materials needed for accurate MC dose calculation. Based on the performance of four distance measures, we conclude that k-means clustering using the Chi-Squared distance introduces the smallest errors on dose distribution. The method is shown to yield similar or improved accuracy on key physical parameters compared to supervised classification.

Dosimetric impact of dual-energy CT tissue segmentation for low-energy prostate brachytherapy: a Monte Carlo study

The purpose of this study is to evaluate the impact of a novel tissue characterization method using dual-energy over single-energy computed tomography (DECT and SECT) on Monte Carlo (MC) dose calculations for low-dose rate (LDR) prostate brachytherapy performed in a patient like geometry. A virtual patient geometry is created using contours from a real patient pelvis CT scan, where known elemental compositions and varying densities are overwritten in each voxel. A second phantom is made with additional calcifications. Both phantoms are the ground truth with which all results are compared. Simulated CT images are generated from them using attenuation coefficients taken from the XCOM database with a 100 kVp spectrum for SECT and 80 and 140Sn kVp for DECT. Tissue segmentation for Monte Carlo dose calculation is made using a stoichiometric calibration method for the simulated SECT images. For the DECT images, Bayesian eigentissue decomposition is used. A LDR prostate brachytherapy plan is defined with ¹²⁵I sources and then calculated using the EGSnrc user-code Brachydose for each case. Dose distributions and dose-volume histograms (DVH) are compared to ground truth to assess the accuracy of tissue segmentation. For noiseless images, DECT-based tissue segmentation outperforms the SECT procedure with a root mean square error (RMS) on relative errors on dose distributions respectively of 2.39% versus 7.77%, and provides DVHs closest to the reference DVHs for all tissues. For a medium level of CT noise, Bayesian eigentissue decomposition still performs better on the overall dose calculation as the RMS error is found to be of 7.83% compared to 9.15% for SECT. Both methods give a similar DVH for the prostate while the DECT segmentation remains more accurate for organs at risk and in presence of calcifications, with less than 5% of RMS errors within the calcifications versus up to 154% for SECT. In a patient-like geometry, DECT-based tissue segmentation provides dose distributions with the highest accuracy and the least bias compared to SECT. When imaging noise is considered, benefits of DECT are noticeable if important calcifications are found within the prostate.

Experimental validation of two dual-energy CT methods for proton therapy using heterogeneous tissue samples

PURPOSE

The purpose of this work is to evaluate the performance of dual-energy CT (DECT) for determining proton stopping power ratios (SPRs) in an experimental environment and to demonstrate its potential advantages over conventional single-energy CT (SECT) in clinical conditions.

METHODS

Water equivalent range (WER) measurements of 12 tissue-equivalent plastic materials and 12 fresh animal tissue samples are performed in a 195 MeV broad proton beam using the dose extinction method. SECT and DECT scans of the samples are performed with a dual-source CT scanner (Siemens SOMATOM Definition Flash). The methods of Schneider et al. (1996), Bourque et al. (2014), and Lalonde et al. (2017) are used to predict proton SPR on SECT and DECT images. From predicted SPR values, the WER of the proton beam through the sample is predicted for SECT and DECT using Monte Carlo simulations and compared to the measured WER.

RESULTS

For homogeneous tissue-equivalent plastic materials, results with DECT are consistent with experimental measurements and show a systematic reduction of SPR uncertainty compared to SECT, with root-mean-square errors of 1.59% versus 0.61% for SECT and DECT, respectively. Measurements with heterogeneous animal samples show a clear reduction of the bias on range predictions in the presence of bones, with -0.88% for SECT versus -0.58% and -0.14% for both DECT methods. An uncertainty budget allows isolating the effect of CT number conversion to SPR and predicts improvements by DECT over SECT consistently with theoretical predictions, with 0.34% and 0.31% for soft tissues and bones in the experimental setup compared to 0.34% and 1.14% with the theoretical method.

CONCLUSIONS

The present work uses experimental measurements in a realistic clinical environment to show potential benefits of DECT for proton therapy treatment planning. Our results show clear improvements over SECT in tissue-equivalent plastic materials and animal tissues. Further work towards using Monte Carlo simulations for treatment planning with DECT data and a more detailed investigation of the uncertainties on I-value and limitations on the Bragg additivity rule could potentially further enhance the benefits of this imaging technology for proton therapy.

The potential of dual-energy CT to reduce proton beam range uncertainties

PURPOSE

Dual-energy CT (DECT) promises improvements in estimating stopping power ratios (SPRs) for proton therapy treatment planning. Although several comparable mathematical formalisms have been proposed in literature, the optimal techniques to characterize human tissue SPRs with DECT in a clinical environment are not fully established. The aim of this work is to compare the most robust DECT methods against conventional single-energy CT (SECT) in conditions reproducing a clinical environment, where CT artifacts and noise play a major role on the accuracy of these techniques.

METHODS

Available DECT tissue characterization methods are investigated and their ability to predict SPRs is compared in three contexts: (a) a theoretical environment using the XCOM cross section database; (b) experimental data using a dual-source CT scanner on a calibration phantom; (c) simulations of a virtual humanoid phantom with the ImaSim software. The latter comparison accounts for uncertainties caused by CT artifacts and noise, but leaves aside other sources of uncertainties such as CT grid size and the I-values. To evaluate the clinical impact, a beam range calculation model is used to predict errors from the probability distribution functions determined with ImaSim simulations. Range errors caused by SPR errors in soft tissues and bones are investigated.

RESULTS

Range error estimations demonstrate that DECT has the potential of reducing proton beam range uncertainties by 0.4% in soft tissues using low noise levels of 12 and 8 HU in DECT, corresponding to 7 HU in SECT. For range uncertainties caused by the transport of protons through bones, the reduction in range uncertainties for the same levels of noise is found to be up to 0.6 to 1.1 mm for bone thicknesses ranging from 1 to 5 cm, respectively. We also show that for double the amount noise, i.e., 14 HU in SECT and 24 and 16 HU for DECT, the advantages of DECT in soft tissues are lost over SECT. In bones however, the reduction in range uncertainties is found to be between 0.5 and 0.9 mm for bone thicknesses ranging from 1 to 5 cm, respectively.

CONCLUSION

DECT has a clear potential to improve proton beam range predictions over SECT in proton therapy. However, in the current state high levels of noise remain problematic for DECT characterization methods and do not allow getting the full benefits of this technology. Future work should focus on adapting DECT methods to noise and investigate methods based on raw-data to reduce CT artifacts.

102 INCLUSION OF A RECOMBINANT BOVINE TRYPSIN INTO THE IETS SANITARY PROTOCOL FOR DISINFECTION OF BOVINE EMBRYOS TO PREVENT BOVINE HERPESVIRUS 1 (BHV 1) TRANSMISSION VIA EMBRYO TRANSFER TO RECIPIENTS AND CALVES

This study dealt with the potential for introduction of infectious agents through the use of animal-derived products. The efficacy of a recombinant bovine trypsin (RBTr) as a replacement for porcine pancreatic trypsin as a disinfectant for bovine herpesvirus-1 (BHV-1)-infected embryos was investigated according to the sanitary guidelines of the IETS. Treatment of in vivo-fertilised embryos (n = 147) contaminated with BHV-1 [105 50% tissue culture infectious dose (TCID50)/mL] in the presence of RBTr (525 U mL–1) for 120 s effectively removed the infectious virus (100%) compared with untreated and washed embryos [9/55 (16%); P < 0.05]. Transfer of in vivo-fertilised and disinfected embryos to BHV-1 seronegative recipients (n = 24) resulted in 14 pregnancies and 11 calves born free of BHV-1. In contrast, transfer of unwashed/undisinfected embryos to 4 recipients resulted in seroconversion and no pregnancies at term. The same treatment applied to in vivo-fertilised contaminated embryos removed the infectious virus from all but 1 [1/100 (99%)] compared with untreated and unwashed embryos [16/28 (57%); P < 0.05]. It was concluded that the use of RBTr can be considered as an alternative method of rendering embryos free of bovine herpesvirus and thus reduce the potential risk of disease transmission to embryo recipients and offspring.

Nontransmission of porcine circovirus 2 (PCV2) by embryo transfer

Two experiments were conducted to determine the association of porcine circovirus type 2 (PCV2) with embryos and the risk of viral transmission by embryo transfer. In the first experiment, 240 embryos from uninfected donors were exposed to PCV2a 10(4)TCID50/mL in vitro before transfer to seronegative recipients; in the second experiment, 384 embryos recovered from infected donors, 10 days after donor inoculation with PCV2, were transferred to seronegative recipients. In total, 1120 embryos and/or ova were collected from 37 viral-free donors (experiment 1) and 1019 from 59 PCV2-infected donors (experiment 2) (P < 0.01). The washing and/or disinfection procedure recommended by the International Embryo Transfer Society was applied to embryos in both experiments. Transfer of embryos experimentally exposed in vitro to high titers of virus caused seroconversion of recipients (58%; N = 7/12) and their piglets (81%; N = 13/16). Postmortem, PCV2 DNA was detected in various organs of embryo transfer recipients and their embryo transfer-derived piglets. In contrast, the transfer of embryos recovered from infectious PCV2 donors did not result in the seroconversion of embryo recipients (N = 24) or their embryo transfer-derived piglets (N = 76). Neither PCV2 DNA nor infectious virus was detected in the tissues of either recipients or embryo transfer-derived piglets collected postmortem in the second experiment. The results obtained in this study indicate that the transmission of PCV2 from infected donors by embryo transfer is unlikely if the sanitary recommendations of the International Embryo Transfer Society are followed. In practical terms, this means that embryo transfer can be successfully used for the intentional elimination of PCV2 and to create virus-free offspring for the safe exchange of swine genetic materials.

186 TRANSMISSION OF NONCYTOPATHIC BOVINE DIARRHEA VIRUS BY INFECTED SEMEN TO EMBRYO DONORS AND BY EMBRYOS TO EMBRYO TRANSFER RECIPIENTS AND OFFSPRING

Bovine diarrhea virus (BVDV) causes a variety of economically important enteric and infertility problems. For that reason, several countries have eradicated the disease and some others have schemes in progress to achieve freedom from it. Although there is a considerable amount of information about the risk of BVDV transmission through contaminated semen used for AI, there is no available evidence to indicate whether the resulting embryos, when used for embryo transfer (ET), can lead to the transmission of BVDV to recipients and offspring. For this experiment, semen from a bull persistently infected with BVDV (105 TCID50/mL of NY strain) was used for insemination (2 times at estrus) of BVDV-seronegative, superovulated heifers (n = 27).All heifers seroconverted to BVDV within 10 days post-insemination. Embryos and unfertilized oocytes were collected nonsurgically (n = 92) or postmortem (n = 52) 7 days post-insemination and were either washed according to IETS recommendations (without trypsin treatment) or left unwashed. In total, out of 144 unfertilized oocytes and embryos collected, 23 (16%) were of ET quality. Most of the embryos were degenerated or unfertilized. On 17 occasions, 1 or 2 washed embryos were transferred to BVDV-seronegative recipients. After ET, all pregnant and nonpregnant recipients remained free of BVDV and antibodies. In total, 6 heifers became pregnant and 5 calves free of BVDV and BVDV antibodies, including 2 sets of twins, have been born to date. Post-insemination, BVDV was detected in 29% (12/41) of unwashed and 10% (4/40) of washed embryos, 100% (4/4) of follicular fluid samples, oviductal epithelial cells, endometrium, and corpora lutea tissues as determined by the virus isolation test. Results herein suggest that BVDV can be transmitted by AI, resulting in the production of some proportion of contaminated embryos. However, it appears that such embryos, when washed according to the IETS guidelines, do not cause BVDV transmission to recipients or their offspring.