Towards Prediction of Radiation Pneumonitis Arising from Lung Cancer Patients Using Machine Learning Approaches

Radiation pneumonitis (RP) is a potentially fatal side effect arising in lung cancer patients who receive radiotherapy as part of their treatment. For the modeling of RP outcomes data, several predictive models based on traditional statistical methods and machine learning techniques have been reported. However, no guidance to variation in performance has been provided to date. In this study, we explore several machine learning algorithms for classification of RP data. The performance of these classification algorithms is investigated in conjunction with several feature selection strategies and the impact of the feature selection strategy on performance is further evaluated. The extracted features include patients demographic, clinical and pathological variables, treatment techniques, and dose-volume metrics. In conjunction, we have been developing an in-house Matlab-based open source software tool, called DREES, customized for modeling and exploring dose response in radiation oncology. This software has been upgraded with a popular classification algorithm called support vector machine (SVM), which seems to provide improved performance in our exploration analysis and has strong potential to strengthen the ability of radiotherapy modelers in analyzing radiotherapy outcomes data

A Graphical Tool and Methods for Assessing Margin Definition From Daily Image Deformations

Estimating the proper margins for the planning target volume (PTV) could be a challenging task in cases where the organ undergoes significant changes during the course of radiotherapy treatment. Developments in image-guidance and the presence of onboard imaging technologies facilitate the process of correcting setup errors. However, estimation of errors to organ motions remain an open question due to the lack of proper software tools to accompany these imaging technological advances. Therefore, we have developed a new tool for visualization and quantification of deformations from daily images. The tool allows for estimation of tumor coverage and normal tissue exposure as a function of selected margin (isotropic or anisotropic). Moreover, the software allows estimation of the optimal margin based on the probability of an organ being present at a particular location. Methods based on swarm intelligence, specifically Ant Colony Optimization (ACO) are used to provide an efficient estimate of the optimal margin extent in each direction. ACO can provide global optimal solutions in highly nonlinear problems such as margin estimation. The proposed method is demonstrated using cases from gastric lymphoma with daily TomoTherapy megavoltage CT (MVCT) contours. Preliminary results using Dice similarity index are promising and it is expected that the proposed tool will be very helpful and have significant impact for guiding future margin definition protocols

Selective cognitive and psychiatric manifestations in Wolfram Syndrome

BACKGROUND: Wolfram Syndrome (WFS) is known to involve diabetes mellitus, diabetes insipidus, optic nerve atrophy, vision loss, hearing impairment, motor abnormalities, and neurodegeneration, but has been less clearly linked to cognitive, sleep, and psychiatric abnormalities. We sought to determine whether these abnormalities are present in children, adolescents, and young adults with WFS compared to age- and gender-matched individuals with and without type 1 diabetes using standardized measures. METHODS: Individuals with genetically-confirmed WFS (n = 19, ages 7–27) were compared to age- and gender- equivalent groups of individuals with type 1 diabetes (T1DM; n = 25), and non-diabetic healthy controls (HC: n = 25). Cognitive performance across multiple domains (verbal intelligence, spatial reasoning, memory, attention, smell identification) was assessed using standardized tests. Standardized self- and parent-report questionnaires on psychiatric symptoms and sleep disturbances were acquired from all groups and an unstructured psychiatric interview was performed within only the WFS group. RESULTS: The three groups were similar demographically (age, gender, ethnicity, parental IQ). WFS and T1DM had similar duration of diabetes but T1DM had higher Hb(A1C) levels than WFS and as expected both groups had higher levels than HC. The WFS group was impaired on smell identification and reported sleep quality, but was not impaired in any other cognitive or self-reported psychiatric domain. In fact, the WFS group performed better than the other two groups on selected memory and attention tasks. However, based upon a clinical evaluation of only WFS patients, we found that psychiatric and behavioral problems were present and consisted primarily of anxiety and hypersomnolence. CONCLUSIONS: This study found that cognitive performance and psychological health were relatively preserved WFS patients, while smell and sleep abnormalities manifested in many of the WFS patients. These findings contradict past case and retrospective reports indicating significant cognitive and psychiatric impairment in WFS. While many of these patients were diagnosed with anxiety and hypersomnolence, self-reported measures of psychiatric symptoms indicated that the symptoms were not of grave concern to the patients. It may be that cognitive and psychiatric issues become more prominent later in life and/or in later stages of the disease, but this requires standardized assessment and larger samples to determine. In the relatively early stages of WFS, smell and sleep-related symptoms may be useful biomarkers of disease and should be monitored longitudinally to determine if they are good markers of progression as well. TRIAL REGISTRATION: Current Clinicaltrials.gov Trial NCT02455414

Emotional eating phenotype is associated with central dopamine D2 receptor binding independent of body mass index

PET studies have provided mixed evidence regarding central D2/D3 dopamine receptor binding and its relationship with obesity as measured by body mass index (BMI). Other aspects of obesity may be more tightly coupled to the dopaminergic system. We characterized obesity-associated behaviors and determined if these related to central D2 receptor (D2R) specific binding independent of BMI. Twenty-two obese and 17 normal-weight participants completed eating- and reward-related questionnaires and underwent PET scans using the D2R-selective and nondisplaceable radioligand (N-[(11)C]methyl)benperidol. Questionnaires were grouped by domain (eating related to emotion, eating related to reward, non-eating behavior motivated by reward or sensitivity to punishment). Normalized, summed scores for each domain were compared between obese and normal-weight groups and correlated with striatal and midbrain D2R binding. Compared to normal-weight individuals, the obese group self-reported higher rates of eating related to both emotion and reward (p < 0.001), greater sensitivity to punishment (p = 0.06), and lower non-food reward behavior (p < 0.01). Across normal-weight and obese participants, self-reported emotional eating and non-food reward behavior positively correlated with striatal (p < 0.05) and midbrain (p < 0.05) D2R binding, respectively. In conclusion, an emotional eating phenotype may reflect altered central D2R function better than other commonly used obesity-related measures such as BMI

Novel mutations expand the clinical spectrum of DYNC1H1-associated spinal muscular atrophy

OBJECTIVE To expand the clinical phenotype of autosomal dominant congenital spinal muscular atrophy with lower extremity predominance (SMA-LED) due to mutations in the dynein, cytoplasmic 1, heavy chain 1 (DYNC1H1) gene. METHODS Patients with a phenotype suggestive of a motor, non-length-dependent neuronopathy predominantly affecting the lower limbs were identified at participating neuromuscular centers and referred for targeted sequencing of DYNC1H1. RESULTS We report a cohort of 30 cases of SMA-LED from 16 families, carrying mutations in the tail and motor domains of DYNC1H1, including 10 novel mutations. These patients are characterized by congenital or childhood-onset lower limb wasting and weakness frequently associated with cognitive impairment. The clinical severity is variable, ranging from generalized arthrogryposis and inability to ambulate to exclusive and mild lower limb weakness. In many individuals with cognitive impairment (9/30 had cognitive impairment) who underwent brain MRI, there was an underlying structural malformation resulting in polymicrogyric appearance. The lower limb muscle MRI shows a distinctive pattern suggestive of denervation characterized by sparing and relative hypertrophy of the adductor longus and semitendinosus muscles at the thigh level, and diffuse involvement with relative sparing of the anterior-medial muscles at the calf level. Proximal muscle histopathology did not always show classic neurogenic features. CONCLUSION Our report expands the clinical spectrum of DYNC1H1-related SMA-LED to include generalized arthrogryposis. In addition, we report that the neurogenic peripheral pathology and the CNS neuronal migration defects are often associated, reinforcing the importance of DYNC1H1 in both central and peripheral neuronal functions