Hypothalamic hamartomas and gelastic seizures are often associated with cognitive deterioration, behavioral problems, and poor response to anticonvulsant treatment or cortical resections. The origin and pathophysiology of the epileptic attacks are obscure. We investigated 3 patients with this syndrome and frequent gelastic seizures. Ictal single-photon emission computed tomography performed during typical gelastic seizures demonstrated hyperperfusion in the hamartomas, hypothalamic region, and thalamus without cortical or cerebellar hyperperfusion. Electroencephalographic recordings with depth electrodes implanted in the hamartoma demonstrated focal seizure origin from the hamartoma in 1 patient. Electrical stimulation studies reproduced the typical gelastic events. Stereotactic radiofrequency lesioning of the hamartoma resulted in seizure remission without complications 20 months after surgery. The functional imaging findings, electrophysiological data, and results of radiofrequency surgery indicate that epileptic seizures in this syndrome originate and propagate from the hypothalamic hamartoma and adjacent structures.

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This phase I study evaluated the safety, tolerability, and pharmacokinetics of copanlisib, an intravenously administered pan-phosphatidylinositol 3-kinase inhibitor in patients with advanced solid tumors or non-Hodgkin's lymphoma. Copanlisib was well tolerated with a manageable safety profile, with anti-tumor activity in both advanced solid tumors and hematological malignancies.

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Pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) time-course data allows estimation of quantitative parameters such as K (trans) (rate constant for plasma/interstitium contrast agent transfer), v e (extravascular extracellular volume fraction), and v p (plasma volume fraction). A plethora of factors in DCE-MRI data acquisition and analysis can affect accuracy and precision of these parameters and, consequently, the utility of quantitative DCE-MRI for assessing therapy response. In this multicenter data analysis challenge, DCE-MRI data acquired at one center from 10 patients with breast cancer before and after the first cycle of neoadjuvant chemotherapy were shared and processed with 12 software tools based on the Tofts model (TM), extended TM, and Shutter-Speed model. Inputs of tumor region of interest definition, pre-contrast T1, and arterial input function were controlled to focus on the variations in parameter value and response prediction capability caused by differences in models and associated algorithms. Considerable parameter variations were observed with the within-subject coefficient of variation (wCV) values for K (trans) and v p being as high as 0.59 and 0.82, respectively. Parameter agreement improved when only algorithms based on the same model were compared, e.g., the K (trans) intraclass correlation coefficient increased to as high as 0.84. Agreement in parameter percentage change was much better than that in absolute parameter value, e.g., the pairwise concordance correlation coefficient improved from 0.047 (for K (trans)) to 0.92 (for K (trans) percentage change) in comparing two TM algorithms. Nearly all algorithms provided good to excellent (univariate logistic regression c-statistic value ranging from 0.8 to 1.0) early prediction of therapy response using the metrics of mean tumor K (trans) and k ep (=K (trans)/v e, intravasation rate constant) after the first therapy cycle and the corresponding percentage changes. The results suggest that the interalgorithm parameter variations are largely systematic, which are not likely to significantly affect the utility of DCE-MRI for assessment of therapy response.