Prediction of Normal Tissue Complication Probability (NTCP) After Radiation Therapy Using Imaging and Molecular Biomarkers and Multivariate Modelling.

The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma.

Evaluation of the sleepy patient.

BACKGROUND: Inefficient sleep leading to excessive daytime sleepiness is a common complaint encountered by GPs and sleep physicians. Common causes of excessive daytime sleepiness include circadian rhythm disorder/shiftwork, sleep apnoea syndrome, psychiatric disorders, restless leg syndrome, medication effect, narcolepsy and idiopathic hypersomnia. OBJECTIVE: This short review discusses the available objective and subjective testing measures in office evaluation of sleepy patients, predominantly in the primary care setting. DISCUSSION: Beyond affecting patients' quality of life, mood and functionality, excessive sleepiness can become a public health concern when affecting critical job holders. Therefore, a clear understanding of its importance and applying current standards in evaluating patients with such a complaint are of great necessity. Apart from the clinical assessments, including a thorough history taking and physical examination, measures to assess sleepiness and ability to maintain wakefulness are available.

Etiopathophysiological assessment of cases with chronic daily headache: A functional magnetic resonance imaging included investigation.

BACKGROUND: Chronic daily headache (CDH) has gained little attention in functional neuro-imaging. When no structural abnormality is found in CDH, defining functional correlates between activated brain regions during headache bouts may provide unique insights towards understanding the pathophysiology of this type of headache. METHODS: We recruited four CDH cases for comprehensive assessments, including history taking, physical examinations and neuropsychological evaluations (The Addenbrooke's Cognitive Evaluation, Beck's Anxiety and Depression Inventories, Pittsburg Sleep Quality Index and Epworth Sleepiness Scale). Visual analogue scale (VAS) was used to self-rate the intensity of headache. Patients then underwent electroencephalography (EEG), transcranial Doppler (TCD) and functional magnetic resonance imaging (fMRI) evaluations during maximal (VAS = 8-10/10) and off-headache (VAS = 0-3/10) conditions. Data were used to compare in both conditions. We also used BOLD (blood oxygen level dependent) -group level activation map fMRI to possibly locate headache-related activated brain regions. RESULTS: General and neurological examinations as well as conventional MRIs were unremarkable. Neuropsychological assessments showed moderate anxiety and depression in one patient and minimal in others. Unlike three patients, maximal and off-headache TCD evaluation in one revealed increased middle cerebral artery blood flow velocity, at the maximal pain area. Although with no seizure history, the same patient's EEG showed paroxysmal epileptic discharges during maximal headache intensity, respectively. Group level activation map fMRI showed activated classical pain matrix regions upon headache bouts (periaqueductal grey, substantia nigra and raphe nucleus), and markedly bilateral occipital lobes activation. CONCLUSION: The EEG changes were of note. Furthermore, the increased BOLD signals in areas outside the classical pain matrix (i.e. occipital lobes) during maximal headaches may suggest that activation of these areas can be linked to the increased neural activity or visual cortex hyperexcitability in response to visual stimuli. These findings can introduce new perspective towards more in-depth functional imaging studies in headaches of poorly understood pathophysiology.