A molecular biology and phase II trial of lapatinib in children with refractory CNS malignancies: a pediatric brain tumor consortium study.

High expression of ERBB2 has been reported in medulloblastoma and ependymoma; EGFR is amplified and over-expressed in brainstem glioma suggesting these proteins as potential therapeutic targets. We conducted a molecular biology (MB) and phase II study to estimate inhibition of tumor ERBB signaling and sustained responses by lapatinib in children with recurrent CNS malignancies. In the MB study, patients with recurrent medulloblastoma, ependymoma, and high-grade glioma (HGG) undergoing resection were stratified and randomized to pre-resection treatment with lapatinib 900 mg/m(2) dose bid for 7-14 days or no treatment. Western blot analysis of ERBB expression and pathway activity in fresh tumor obtained at surgery estimated ERBB receptor signaling inhibition in vivo. Drug concentration was simultaneously assessed in tumor and plasma. In the phase II study, patients, stratified by histology, received lapatinib continuously, to assess sustained response. Eight patients, on the MB trial (four medulloblastomas, four ependymomas), received a median of two courses (range 1-6+). No intratumoral target inhibition by lapatinib was noted in any patient. Tumor-to-plasma ratios of lapatinib were 10-20 %. In the 34 patients (14 MB, 10 HGG, 10 ependymoma) in the phase II study, lapatinib was well-tolerated at 900 mg/m(2) dose bid. The median number of courses in the phase II trial was two (range 1-12). Seven patients (three medulloblastoma, four ependymoma) remained on therapy for at least four courses range (4-26). Lapatinib was well-tolerated in children with recurrent or CNS malignancies, but did not inhibit target in tumor and had little single agent activity.Fil: Fouladi, Maryam. St. Jude Children’s Research Hospital; Estados UnidosFil: Stewart, Clinton F.. St. Jude Children’s Research Hospital; Estados UnidosFil: Blaney, Susan M.. Baylor College of Medicine. Texas Children’s Cancer Center; Estados UnidosFil: Onar Thomas, Arzu. St. Jude Children’s Research Hospital; Estados UnidosFil: Schaiquevich, Paula Susana. St. Jude Children’s Research Hospital; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Packer, Roger J.. Children’s National Medical Center; Estados UnidosFil: Goldman, Stewart. Anne and Robert H. Lurie Children’s Hospital of Chicago; Estados UnidosFil: Geyer, J. Rusell. Children’s Hospital and Regional Medical Center; Estados UnidosFil: Gajjar, Amar. St. Jude Children’s Research Hospital; Estados UnidosFil: Kun, Larry E.. St. Jude Children’s Research Hospital; Estados UnidosFil: Boyett, James M.. St. Jude Children’s Research Hospital; Estados UnidosFil: Gilbertson, Richard J.. St. Jude Children’s Research Hospital; Estados Unido

A knowledge-guided active model method of skull segmentation on T1-weighted MR images

Skull is the anatomic landmark for patient set up of head radiation therapy. Skull is generally segmented from CT images because CT provides better definition of skull than MR imaging. In the mean time, radiation therapy is planned on MR images for soft tissue information. This study utilized a knowledge-guided active model (KAM) method to segmented skull on MR images in order to enable radiation therapy planning with MR images as the primary planning dataset. KAM utilized age-specific skull mesh models that segmented from CT images using a conditional region growing algorithm. Skull models were transformed to given MR images using an affine registration algorithm based on normalized mutual information. The transformed mesh models actively located skull boundaries by minimizing their total energy. The preliminary validation was performed on MR and CT images from five patients. The KAM segmented skulls were compared with those segmented from CT images. The average image similarity (kappa index) was 0.57. The initial validation showed that it was promising to segment skulls directly on MR images using KAM

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

A Knowledge-guided Active Model Method of Skull Segmentation on T1-weighted MR images

ABSTRACT Skull is the anatomic landmark for patient set up of head radiation therapy. Skull is generally segmented from CT images because CT provides better definition of skull than MR imaging. In the mean time, radiation therapy is planned on MR images for soft tissue information. This study utilized a knowledge-guided active model (KAM) method to segmented skull on MR images in order to enable radiation therapy planning with MR images as the primary planning dataset. KAM utilized age-specific skull mesh models that segmented from CT images using a conditional region growing algorithm. Skull models were transformed to given MR images using an affine registration algorithm based on normalized mutual information. The transformed mesh models actively located skull boundaries by minimizing their total energy. The preliminary validation was performed on MR and CT images from five patients. The KAM segmented skulls were compared with those segmented from CT images. The average image similarity (kappa index) was 0.57. The initial validation showed that it was promising to segment skulls directly on MR images using KAM