Beam Position Projection Algorithms in Proton Pencil Beam Scanning.

Beam position uncertainties along the beam trajectory arise from the accelerator, beamline, and scanning magnets (SMs). They can be monitored in real time, e.g., through strip ionization chambers (ICs), and treatments can be paused if needed. Delivery is more reliable and accurate if the beam position is projected from monitored nozzle parameters to the isocenter, allowing for accurate online corrections to be performed. Beam position projection algorithms are also used in post-delivery log file analyses. In this paper, we investigate the four potential algorithms that can be applied to all pencil beam scanning (PBS) nozzles. For some combinations of nozzle configurations and algorithms, however, the projection uses beam properties determined offline (e.g., through beam tuning or technical commissioning). The best algorithm minimizes either the total uncertainty (i.e., offline and online) or the total offline uncertainty in the projection. Four beam position algorithms are analyzed (A1-A4). Two nozzle lengths are used as examples: a large nozzle (1.5 m length) and a small nozzle (0.4 m length). Three nozzle configurations are considered: IC after SM, IC before SM, and ICs on both sides. Default uncertainties are selected for ion chamber measurements, nozzle entrance beam position and angle, and scanning magnet angle. The results for other uncertainties can be determined by scaling these results or repeating the error propagation. We show the propagation of errors from two locations and the SM angle to the isocenter for all the algorithms. The best choice of algorithm depends on the nozzle length and is A1 and A3 for the large and small nozzles, respectively. If the total offline uncertainty is to be minimized (a better choice if the offline uncertainty is not stable), the best choice of algorithm changes to A1 for the small nozzle for some hardware configurations. Reducing the nozzle length can help to reduce the gantry size and make proton therapy more accessible. This work is important for designing smaller nozzles and, consequently, smaller gantries. This work is also important for log file analyses.

Accuracy of Repetitive Ocular Vestibular-Evoked Myogenic Potentials to Diagnose Myasthenia Gravis in Patients With Ptosis or Diplopia.

BACKGROUND AND OBJECTIVES: We developed repetitive ocular vestibular-evoked myogenic potentials (roVEMP) as an electrophysiologic test that allows us to elicit the characteristic decrement of extraocular muscles in patients with ocular myasthenia gravis (OMG). Case-control studies demonstrated that roVEMP reliably differentiates patients with OMG from healthy controls. We now aimed to evaluate the diagnostic accuracy of roVEMP for OMG diagnosis in patients with ptosis and/or diplopia. METHODS: In this blinded prospective diagnostic accuracy trial, we compared roVEMP in 89 consecutive patients presenting with ptosis and/or diplopia suspicious of OMG with a multimodal diagnostic approach, including clinical examination, antibodies, edrophonium testing, repetitive nerve stimulation of accessory and facial nerves, and single-fiber EMG (SFEMG). We calculated the roVEMP decrement as the ratio between the mean of the first 2 responses compared with the mean of the sixth-ninth responses in the train and used cutoff of >9% (unilateral decrement) in a 30 Hz stimulation paradigm. RESULTS: Following a complete diagnostic work-up, 39 patients (44%) were diagnosed with ocular MG, while 50 patients (56%) had various other neuro-ophthalmologic conditions, but not MG (non-MG). roVEMP yielded 88.2% sensitivity, 30.2% specificity, 50% positive predictive value (PPV), and 76.5% negative predictive value (NPV). For comparison, SFEMG resulted in 75% sensitivity, 56% specificity, 55.1% PPV, and 75.7% NPV. All other diagnostic tests (except for the ice pack test) also yielded significantly higher positive results in patients with MG compared with non-MG. DISCUSSION: The study revealed a high sensitivity of 88.2% for roVEMP in OMG, but specificity and PPV were too low to allow for the OMG diagnosis as a single test. Thus, differentiating ocular MG from other neuro-ophthalmologic conditions remains challenging, and the highest diagnostic accuracy is still obtained by a multimodal approach. In this study, roVEMP can complement the diagnostic armamentarium for the diagnosis of MG. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in patients with diplopia and ptosis, roVEMP alone does not accurately distinguish MG from non-MG disorders. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov: NCT03049956.

Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies.

OBJECTIVES: To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS). METHODS: This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics. RESULTS: A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001). CONCLUSION: Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers. CLINICAL RELEVANCE STATEMENT: Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers. KEY POINTS: • Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Downstream network transformations dissociate neural activity from causal functional contributions.

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neural networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.

The prognostic value of the post-treatment serum CA 125 level in patients with advanced endometrial cancer.

OBJECTIVES: The goal of this analysis was to assess the prognostic value of the post-treatment serum CA 125 level in each member of a group of advanced endometrial cancer (aEC) patients in comparison to other clinical and pathological parameters. MATERIAL AND METHODS: Records of 266 patients treated at the Maria Sklodowska-Curie Memorial Cancer Centre and Institute of Oncology, Cracow Branch between the years 2006 and 2018 were included in the study. Follow-up ranged from 1 to 138 months. Progression free survival (PFS) and overall survival (OS) were set as the endpoints. The tests chi-squared, Fisher, log-rank, Mann-Whitney, Kruskal-Wallis and Cox proportional hazard ratio were used for statistical analyses. RESULTS: In the analysed group, there was a significant association between an elevated serum CA 125 level following adjuvant treatment and shorter PFS and OS. After setting a cut-off value for CA 125 there was a statistically significant correlation between the marker and PFS and OS. Multivariate analysis indicated that the post-treatment serum CA 125 level is an independent prognostic factor of the course of aEC. CONCLUSIONS: The post-treatment serum CA 125 level correlates significantly with both PFS and OS in each patient with aEC. The marker is an independent prognostic factor in this group. A low post-treatment level of the marker is a strong indicator of good 5-year survival, with 82% of patients reaching 5-year OS.

Using Smartphone Exophthalmometry to Measure Eyeball Protrusion.

Importance: The current clinical criterion standard for measuring abnormal eyeball protrusion is still the historic Hertel exophthalmometer, which is prone to reading errors. Therefore, a smartphone application has been developed to measure exophthalmos. Objective: To evaluate a relatively simple noninvasive measurement method for exophthalmos using a smartphone. Design, Setting, and Participants: This cross-sectional study compared smartphone exophthalmometry with the existing reference standard, the Hertel exophthalmometer, or a professional high-resolution 3-dimensional scanner. Participants were patients with exophthalmos due to Graves orbitopathy and other intraorbital conditions and healthy volunteers who were recruited between June 2019 and January 2022 from the Department of Ophthalmology, University Hospital Zurich. Interventions: All participants were examined twice by 3 different operators using 3 different methods (smartphone, high-resolution scanner, or Hertel exophthalmometer) at an interval of a minimum of 2 weeks or after exophthalmos-changing treatment. Main Outcome Measures: Accuracy and precision, test-retest reliability, and interoperator reliability of eyeball protrusion measurements obtained with the smartphone compared to the Hertel exophthalmometer and the high-resolution face scanner. Results: Of 39 participants, 23 patients (median [IQR] age, 54 [44-59] years; 15 [65%] female and 8 [35%] male) showed a mean difference in eyeball protrusion of 3.3 mm and 16 healthy volunteers (median [IQR] age, 32 [30-37] years; 11 [69%] female and 5 [31%] male) of 0.8 mm without any significant difference between the 3 methods. Accuracy and precision agreement between exophthalmos measures with the smartphone and the Hertel exophthalmometer showed an intraclass correlation coefficient (ICC) of 0.89 (95% CI, 0.80-0.94) and 0.93 (95% CI, 0.83-0.97) for the high-resolution scanner. Interoperator agreement was highest for the high-resolution scanner (ICC, 0.99 [95% CI, 0.98-0.99]), followed by the smartphone (ICC, 0.95 [95% CI, 0.92-0.97]) and the Hertel exophthalmometer (ICC, 0.91 [95% CI, 0.85-0.95]). Test retest reliability was similarly high for the smartphone (ICC, 0.93 [95% CI, 0.82-0.95]), the Hertel exophthalmometer (ICC, 0.92 [95% CI, 0.83-0.96]), and the high-resolution scanner (ICC, 0.95 [95% CI, 0.89-0.97]). Conclusions and Relevance: The findings of this study demonstrate relatively high accuracy and precision, interoperator reliability, and test-retest reliability for smartphone exophthalmometry. These data support the use of a smartphone in place of a Hertel exophthalmometer for measuring exophthalmos in the future.

A role for cortical interneurons as adversarial discriminators.

The brain learns representations of sensory information from experience, but the algorithms by which it does so remain unknown. One popular theory formalizes representations as inferred factors in a generative model of sensory stimuli, meaning that learning must improve this generative model and inference procedure. This framework underlies many classic computational theories of sensory learning, such as Boltzmann machines, the Wake/Sleep algorithm, and a more recent proposal that the brain learns with an adversarial algorithm that compares waking and dreaming activity. However, in order for such theories to provide insights into the cellular mechanisms of sensory learning, they must be first linked to the cell types in the brain that mediate them. In this study, we examine whether a subtype of cortical interneurons might mediate sensory learning by serving as discriminators, a crucial component in an adversarial algorithm for representation learning. We describe how such interneurons would be characterized by a plasticity rule that switches from Hebbian plasticity during waking states to anti-Hebbian plasticity in dreaming states. Evaluating the computational advantages and disadvantages of this algorithm, we find that it excels at learning representations in networks with recurrent connections but scales poorly with network size. This limitation can be partially addressed if the network also oscillates between evoked activity and generative samples on faster timescales. Consequently, we propose that an adversarial algorithm with interneurons as discriminators is a plausible and testable strategy for sensory learning in biological systems.

Metadata-independent classification of MRI sequences using convolutional neural networks: Successful application to prostate MRI.

PURPOSE: The ever-increasing volume of medical imaging data and interest in Big Data research brings challenges to data organization, categorization, and retrieval. Although the radiological value chain is almost entirely digital, data structuring has been widely performed pragmatically, but with insufficient naming and metadata standards for the stringent needs of image analysis. To enable automated data management independent of naming and metadata, this study focused on developing a convolutional neural network (CNN) that classifies medical images based solely on voxel data. METHOD: A 3D CNN (3D-ResNet18) was trained using a dataset of 31,602 prostate MRI volumes with 10 different sequence types of 1243 patients. A five-fold cross-validation approach with patient-based splits was chosen for training and testing. Training was repeated with a gradual reduction in training data assessing classification accuracies to determine the minimum training data required for sufficient performance. The trained model and developed method were tested on three external datasets. RESULTS: The model achieved an overall accuracy of 99.88 % ± 0.13 % in classifying typical prostate MRI sequence types. When being trained with approximately 10 % of the original cohort (112 patients), the CNN still achieved an accuracy of 97.43 % ± 2.10 %. In external testing the model achieved sensitivities of > 90 % for 10/15 tested sequence types. CONCLUSIONS: The herein developed CNN enabled automatic and reliable sequence identification in prostate MRI. Ultimately, such CNN models for voxel-based sequence identification could substantially enhance the management of medical imaging data, improve workflow efficiency and data quality, and allow for robust clinical AI workflows.

When Neural Activity Fails to Reveal Causal Contributions.

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neuronal networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.

Reducing psychiatric illness in the perinatal period: A review and commentary.

This brief overview highlights the global crisis of perinatal psychiatric illness (PPI). PPI is a major contributor to many adverse pregnancy, childbirth, and childhood development outcomes. It contributes to billions of dollars in spending worldwide each year and has a significant impact on the individual, their family, and their community. It is also highly preventable. Current recommendations for intervention and management of PPI are limited and vary considerably from country to country. Furthermore, there are several significant challenges asso-ciated with implementation of these recommendations. These challenges are magnified in number and consequence among women of color and/or minority populations, who experience persistent and negative health disparities during pregnancy and the postpartum period. This paper aims to provide a broad overview of the current state of recommendations and implementation challenges for PPI and layout a framework for overcoming these challenges. An equity-informed model of care that provides universal intervention for pregnant women may be one solution to address the preventable consequences of PPI on child and maternal health. Uniquely, this model emphasizes the importance of managing and eliminating known barriers to traditional health care models. Culturally and contextually specific challenges must be overcome to fully realize the impact of improved management of PPI.

The neuroconnectionist research programme.

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.

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.

Diagnosis and management of basal cell carcinoma: interdisciplinary consensus statements of Jose R. Reyes Memorial Medical Center, a Department of Health Tertiary Hospital in Manila, Philippines.

BACKGROUND: Basal cell carcinoma (BCC) is the most common cutaneous malignancy. Multiple risk factors are associated in the development of BCC, with ultraviolet light and genetics playing major roles. AIMS: The departments of dermatology, medical oncology, ophthalmology, otorhinolaryngology, head and neck surgery, plastic surgery, and radiation oncology of the Jose R. Reyes Memorial Medical Center, Manila, Philippines, have convened and formulated consensus statements on the diagnosis and management of BCC patients seen in the institution. CONCLUSION: The summary of the recommendations is: (1) Surgery is the treatment of choice for BCC. The range of margins (2-4 mm) depends on the type of BCC. (2) Mohs micrographic surgery (MMS) is indicated for high risk BCC. (3) Topical treatment with imiquimod or 5-flourouracil (5-FU) may be used for superficial BCC. (4) Destructive methods (cryotherapy, curettage and electrodessication, photodynamic therapy) may be used for low risk BCC. (5) Medical and/or radiation therapy is advised for cases where surgery is contraindicated or tumor is not amenable to surgery. Metastasis of this malignancy is rare. Follow-up, which may continue up until 2 years, is recommended for high risk BCC.

Lesion follows function: video-oculography compared with MRI to diagnose internuclear ophthalmoplegia in patients with multiple sclerosis.

BACKGROUND: Video-oculography (VOG) is used to quantify functional deficits in internuclear ophthalmoplegia (INO), whereas MRI can detect the corresponding structural lesions in the medial longitudinal fasciculus (MLF). This study investigates the diagnostic agreement of MRI compared to VOG measurements. METHODS: We prospectively compared structural MRI findings and functional VOG measures of 63 MS patients to assess their diagnostic agreement for INO. RESULTS: MRI detected 12 true-positive and 92 true-negative MLF lesions for INO compared to VOG (12 true-positive and 38 true-negative patients) but identified one-third of the MLF lesions on the wrong side. MRI ratings were specific (92.0%) to detect MLF lesions but not sensitive (46.2%) for diagnosing INO (86.4% and 63.2% by patient). Accordingly, MRI has a high positive likelihood ratio of 5.77 but a modest negative likelihood ratio of 0.59 for the probability of INO (4.63 and 0.43) with an accuracy of 82.5% (79.4%). CONCLUSION: MRI assessments are highly specific but not sensitive for detecting INO compared to VOG. While MRI identifies MLF lesions in INO, VOG quantifies the deficit. As a simple, quick, and non-invasive test for diagnosing and tracking functional INO deficits, it will hopefully find its place in the diagnostic and therapeutic pathways of MS.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow.

Purpose: To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods: A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results: The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion: The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

Efficient neural codes naturally emerge through gradient descent learning.

Human sensory systems are more sensitive to common features in the environment than uncommon features. For example, small deviations from the more frequently encountered horizontal orientations can be more easily detected than small deviations from the less frequent diagonal ones. Here we find that artificial neural networks trained to recognize objects also have patterns of sensitivity that match the statistics of features in images. To interpret these findings, we show mathematically that learning with gradient descent in neural networks preferentially creates representations that are more sensitive to common features, a hallmark of efficient coding. This effect occurs in systems with otherwise unconstrained coding resources, and additionally when learning towards both supervised and unsupervised objectives. This result demonstrates that efficient codes can naturally emerge from gradient-like learning.

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 CTDIvol 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.

Three aspects of representation in neuroscience.

Neuroscientists often describe neural activity as a representation of something, or claim to have found evidence for a neural representation, but there is considerable ambiguity about what such claims entail. Here we develop a thorough account of what 'representation' does and should do for neuroscientists in terms of three key aspects of representation. (i) Correlation: a neural representation correlates to its represented content; (ii) causal role: the representation has a characteristic effect on behavior; and (iii) teleology: a goal or purpose served by the behavior and thus the representation. We draw broadly on literature in both neuroscience and philosophy to show how these three aspects are rooted in common approaches to understanding the brain and mind. We first describe different contexts that 'representation' has been closely linked to in neuroscience, then discuss each of the three aspects in detail.