Citations 125

Using germline variants to estimate glioma and subtype risks

Neuro-Oncology | January 8, 2019 | Volume: 21 | Issue: 4 | Pages: 451-461

10.1093/neuonc/noz009 | PMID 30624711

Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning

Radiology | December 26, 2018 | Volume: 290 | Issue: 3 | Pages: 669-679

10.1148/radiol.2018181432 | PMID 30526356

What Does Deep Learning See? Insights From a Classifier Trained to Predict Contrast Enhancement Phase From CT Images

American Journal of Roentgenology | November 7, 2018 | Volume: 211 | Issue: 6 | Pages: 1184-1193

10.2214/ajr.18.20331 | PMID 30403527

COMP-05. EVALUATION OF A DEEP LEARNING ARCHITECTURE FOR MRI PREDICTION OF IDH, 1p19q AND TERT IN GLIOMA PATIENTS

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi64-vi64

10.1093/neuonc/noy148.260

EPID-12. USING GERMLINE VARIANTS TO PREDICT GLIOMA RISK AND IDENTIFY GLIOMA SUBTYPE PRE-OPERATIVELY

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi82-vi82

10.1093/neuonc/noy148.339

Standardizing total kidney volume measurements for clinical trials of autosomal dominant polycystic kidney disease

Clinical Kidney Journal | July 27, 2018 | Volume: 12 | Issue: 1 | Pages: 71-77

10.1093/ckj/sfy078 | PMID 30746130

Phase 1/2 trial of temsirolimus and sorafenib in the treatment of patients with recurrent glioblastoma: North Central Cancer Treatment Group Study/Alliance N0572

Cancer | January 3, 2018 | Volume: 124 | Issue: 7 | Pages: 1455-1463

10.1002/cncr.31219 | PMID 29313954

BACKGROUNDMitogen‐activated protein kinase (MAPK) activation and mammalian target of rapamycin (mTOR)‐dependent signaling are hallmarks of glioblastoma. In the current study, the authors conducted a phase 1/2 study of sorafenib (an inhibitor of Raf kinase and vascular endothelial growth factor receptor 2 [VEGFR‐2]) and the mTOR inhibitor temsirolimus in patients with recurrent glioblastoma.METHODSPatients with recurrent glioblastoma who developed disease progression after surgery or radiotherapy plus temozolomide and with ≤2 prior chemotherapy regimens were eligible. The phase 1 endpoint was the maximum tolerated dose (MTD), using a cohorts‐of‐3 design. The 2‐stage phase 2 study included separate arms for VEGF inhibitor (VEGFi)–naive patients and patients who progressed after prior VEGFi.RESULTSThe MTD was sorafenib at a dose of 200 mg twice daily and temsirolimus at a dose of 20 mg weekly. In the first 41 evaluable patients who were treated at the phase 2 dose, there were 7 who were free of disease progression at 6 months (progression‐free survival at 6 months [PFS6]) in the VEGFi‐naive group (17.1%); this finding met the prestudy threshold of success. In the prior VEGFi group, only 4 of the first 41 evaluable patients treated at the phase 2 dose achieved PFS6 (9.8%), and this did not meet the prestudy threshold for success. The median PFS for the 2 groups was 2.6 months and 1.9 months, respectively. The median overall survival for the 2 groups was 6.3 months and 3.9 months, respectively. At least 1 adverse event of grade ≥3 was observed in 75.5% of the VEGFi‐naive patients and in 73.9% of the prior VEGFi patients.CONCLUSIONSThe limited activity of sorafenib and temsirolimus at the dose and schedule used in the current study was observed with considerable toxicity of grade ≥3. Significant dose reductions that were required in this treatment combination compared with tolerated single‐agent doses may have contributed to the lack of efficacy. Cancer 2018;124:1455‐63. © 2018 American Cancer Society.
Image Registration Improves Confidence and Accuracy of Image Interpretation

Cancer Informatics | October 4, 2017 | Volume: 4 | Issue: No issue available | Pages: 117693510700400

10.1177/117693510700400004

Imaging in Clinical Trials

Cancer Informatics | October 4, 2017 | Volume: 4 | Issue: No issue available | Pages: 117693510700400

10.1177/117693510700400003

Machine Learning for Medical Imaging

RadioGraphics | February 17, 2017 | Volume: 37 | Issue: 2 | Pages: 505-515

10.1148/rg.2017160130 | PMID 28212054