Undoubtedly unaware of homonymous hemianopia: The contribution of overconfidence to anosognosia of hemianopia.

A new functional deficit caused by a stroke can be understood as a situation of uncertainty that has to prompt deficit discovery and subsequent incorporation into an altered self-perception. Anosognosia for visual field deficits is frequent after stroke. For hemiplegia, patients' performance in a riddle test provided evidence that the inability to generate and adjust beliefs in face of uncertainty contributes to anosognosia for hemiplegia. In this prospective study, the same riddles are used in patients with homonymous hemianopia due to a first-ever stroke in the posterior cerebral artery territory and in an age-matched control cohort. The riddles create a situation of uncertainty that is resolved with five successive clues which progressively delimit the target word. After each clue, patients have to guess the target word and rate their confidence in the answer's correctness. Patients were tested once during the hospital stay. According to the Bisiach score for anosognosia, 12 out of 29 patients were unaware of their visual field deficits. All patients with anosognosia for hemianopia had right hemisphere lesions. Patients with and without anosognosia did not differ significantly in global cognitive impairment, mental flexibility or memory function. Importantly, patients with anosognosia showed higher confidence ratings than patients without anosognosia and controls in the first two clues (situations of uncertainty). This was demonstrated by a significant interaction effect in a mixed ANOVA with the factors group (anosognosia, nosognosia, controls) and riddle clues. An exploratory lesion subtraction analysis showed a high proportion of deficit unawareness in patients with lesions in the right fusiform and (para)hippocampal gyri. Our findings suggest that overconfidence in situations of uncertainty might contribute to the appearance of anosognosia for hemianopia. Because this has been demonstrated before in anosognosia for hemiplegia, we suggest that overconfidence is a supra-modal contributor to deficit unawareness.

Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description.

PURPOSE: Developing automated methods to identify task-driven quality assurance (QA) procedures is key toward increasing safety, efficacy, and efficiency. We investigate the use of machine learning (ML) methods for possible visualization, automation, and targeting of QA, and assess its performance using multi-institutional data. METHODS: To enable automated analysis of QA data given its higher dimensional nature, we used nonlinear kernel mapping with support vector data description (SVDD) driven approaches. Instead of using labeled data as in typical support vector machine (SVM) applications, which requires exhaustive annotation, we applied a clustering extension of SVDD, which identifies the minimal enclosing hypersphere in the feature space defined by a kernel function separating normal operations from possible failures (i.e., outliers). In our case, QA test data are mapped by a Gaussian kernel to a higher dimensional feature space and then the minimal enclosing sphere was identified. This sphere, when mapped back to the input data space along the principal components, can separate the data into several components, each enclosing a separate cluster of QA points that could be used to evaluate tolerance boundaries and test reliability. We evaluated this approach for gantry sag, radiation field shift, and [multileaf collimator (MLC)] offset data acquired using electronic portal imaging devices (EPID), as representative examples. RESULTS: Data from eight LINACS and seven institutions (n = 119) were collected. A standardized EPID image of a phantom with fiducials provided deviation estimates between the radiation field and phantom center at four cardinal gantry angles. Deviation measurements in the horizontal direction (0°, 180°) were used to determine the gantry sag and deviations in the vertical direction (90°, 270°) were used to determine the field shift. These measurements were fed into the SVDD clustering algorithm with varying hypersphere radii (Gaussian widths). For gantry sag analysis, two clusters were identified one of which contained 2.5% of the outliers and also exceeded the 1 mm tolerance set by TG-142. In the case of field shifts, SVM clustering identified two distinct classes of measurements primarily driven by variations in the second principal component at 270°. Results from MLC analysis identified one outlier cluster (0.34%) along Leaf offset Constancy (LoC) axis that coincided with TG-142 limits. CONCLUSION: Machine learning methods based on SVDD clustering are promising for developing automated QA tools and providing insights into their reliability and reproducibility.

The American Society for Radiation Oncology's 2015 Core Physics Curriculum for Radiation Oncology Residents.

PURPOSE: The American Society for Radiation Oncology (ASTRO) Physics Core Curriculum Subcommittee (PCCSC) has updated the recommended physics curriculum for radiation oncology resident education to improve consistency in teaching, intensity, and subject matter. METHODS AND MATERIALS: The ASTRO PCCSC is composed of physicists and physicians involved in radiation oncology residency education. The PCCSC updated existing sections within the curriculum, created new sections, and attempted to provide additional clinical context to the curricular material through creation of practical clinical experiences. Finally, we reviewed the American Board of Radiology (ABR) blueprint of examination topics for correlation with this curriculum. RESULTS: The new curriculum represents 56 hours of resident physics didactic education, including a 4-hour initial orientation. The committee recommends completion of this curriculum at least twice to assure both timely presentation of material and re-emphasis after clinical experience. In addition, practical clinical physics and treatment planning modules were created as a supplement to the didactic training. Major changes to the curriculum include addition of Fundamental Physics, Stereotactic Radiosurgery/Stereotactic Body Radiation Therapy, and Safety and Incidents sections, and elimination of the Radiopharmaceutical Physics and Dosimetry and Hyperthermia sections. Simulation and Treatment Verification and optional Research and Development in Radiation Oncology sections were also added. A feedback loop was established with the ABR to help assure that the physics component of the ABR radiation oncology initial certification examination remains consistent with this curriculum. CONCLUSIONS: The ASTRO physics core curriculum for radiation oncology residents has been updated in an effort to identify the most important physics topics for preparing residents for careers in radiation oncology, to reflect changes in technology and practice since the publication of previous recommended curricula, and to provide practical training modules in clinical radiation oncology physics and treatment planning. The PCCSC is committed to keeping the curriculum current and consistent with the ABR examination blueprint.

Age and comorbid illness are associated with late rectal toxicity following dose-escalated radiation therapy for prostate cancer.

PURPOSE: To assess the impacts of patient age and comorbid illness on rectal toxicity following external beam radiation therapy (EBRT) for prostate cancer and to assess the Qualitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) normal tissue complication probability (NTCP) model in this context. METHODS AND MATERIALS: Rectal toxicity was analyzed in 718 men previously treated for prostate cancer with EBRT (≥75 Gy). Comorbid illness was scored using the Charlson Comorbidity Index (CCMI), and the NTCP was evaluated with the QUANTEC model. The influence of clinical and treatment-related parameters on rectal toxicity was assessed by Kaplan-Meier and Cox proportional hazards models. RESULTS: The cumulative incidence of rectal toxicity grade ≥2 was 9.5% and 11.6% at 3 and 5 years and 3.3% and 3.9% at 3 and 5 years for grade ≥3 toxicity, respectively. Each year of age predicted an increasing relative risk of grade ≥2 (P<.03; hazard ratio [HR], 1.04 [95% confidence interval {CI}, 1.01-1.06]) and ≥3 rectal toxicity (P<.0001; HR, 1.14 [95% CI,1.07-1.22]). Increasing CCMI predicted rectal toxicity where a history of either myocardial infarction (MI) (P<.0001; HR, 5.1 [95% CI, 1.9-13.7]) or congestive heart failure (CHF) (P<.0006; HR, 5.4 [95% CI, 0.6-47.5]) predicted grade ≥3 rectal toxicity, with lesser correlation with grade ≥2 toxicity (P<.02 for MI, and P<.09 for CHF). An age comorbidity model to predict rectal toxicity was developed and confirmed in a validation cohort. The use of anticoagulants increased toxicity independent of age and comorbidity. NTCP was prognostic for grade ≥3 (P=.015) but not grade ≥2 (P=.49) toxicity. On multivariate analysis, age, MI, CHF, and an NTCP >20% all correlated with late rectal toxicity. CONCLUSIONS: Patient age and a history of MI or CHF significantly impact rectal toxicity following EBRT for the treatment of prostate cancer, even after controlling for NTCP.