Reconstruction by Pancreaticogastrostomy versus Pancreaticojejunostomy following Pancreaticoduodenectomy: A Meta-Analysis of Randomized Controlled Trials

Objectives. The aim of our study was to evaluate and compare the results of pancreaticogastrostomy (PG) and pancreaticojejunostomy (PJ) after pancreaticoduodenectomy (PD). Methods. Published data of randomized clinical trials (RCTs) comparing the clinically relevant outcomes of PG versus PJ after PD were analyzed. Two reviewers assessed the quality of each trial and collected data independently. The Cochrane Collaboration's RevMan 5.0 software was used for statistical analysis. Proportions were combined, and the odds ratio (OR) with its 95% CI was used as the effect size estimate. Results. Four RCTs published in 1995 or later were included in this meta-analysis, in which 276 patients underwent PG and 277 patients underwent PJ followed PD. In the combined results of PG versus PJ, a significant difference in the morbidity of intra-abdominal complications (OR, 0.34; 95% CI, 0.23–0.49; P < 0.00001) was found, but no significant difference could be found for pancreatic fistula (OR, 0.69; 95% CI, 0.42–1.12 , P = 0.13) mortality (OR, 1.09; 95% CI, 0.42–2.83; P = 0.87), recovery with no complications (OR, 1.26; 95% CI, 0.90–1.78; P = 0.18), biliary fistula (OR, 0.55; 95% CI, 0.22–1.35; P = 0.19), or in delayed gastric emptying (OR, 0.55; 95% CI, 0.33–1.01; P = 0.06). Conclusions. Current RCTs suggest that PG is better than PJ for pancreatic reconstruction after PD

Evaluation of Hybrid Arc and Volumetric-Modulated Arc Therapy Treatment Plans for Fractionated Stereotactic Intracranial Radiotherapy.

PURPOSE: The study was aimed to compare hybrid arc and volumetric-modulated arc therapy treatment plans for fractionated stereotactic radiotherapy of brain tumors. METHODS: Treatment plans of 22 patients were studied. Hybrid arc and volumetric-modulated arc therapy plans were generated using Brainlab iPlanDose and Varian Eclipse treatment planning systems, respectively, with 6 MV photon beams on a Varian TrueBeam STx linear accelerator (Palo Alto, CA). Prescription dose was 54 Gy. The fractionation was 1.8 Gy per fraction and 30 fractions in total, or 2 Gy per fraction and 27 fractions in total. Planning target volume ranged from 2.4 to 28.6 cm RESULTS: Conformity indexes of hybrid arc and volumetric-modulated arc therapy plans are 1.10 ± 0.10 and 1.14 ± 0.07, respectively ( P = .4); gradient indexes are 5.02 ± 1.20 and 5.64 ± 1.28, respectively ( P = .0001); homogeneity indexes are 1.02 ± 0.01 and 1.05 ± 0.01, respectively ( P = .0001); brainstem maximum doses are 53.87 ± 1.63 Gy and 54.06 ± 3.17 Gy, respectively ( P = .1); and optic chiasm maximum doses are 53.86 ± 1.28 Gy and 53.95 ± 1.81, respectively ( P = .4). The monitor unit efficiencies of hybrid arc and volumetric-modulated arc therapy plans are 2.57 ± 0.25 MU/cGy and 2.68 ± 0.24 MU/cGy, respectively ( P = .2). The differences of conformity index, gradient index, and homogeneity index between hybrid arc and volumetric-modulated arc therapy plans are small: 0.08 ± 0.05, 0.65 ± 0.46, and 0.02 ± 0.01, respectively. The maximum doses in organs at risks are similar between hybrid arc and volumetric-modulated arc therapy plans. Hybrid arc and volumetric-modulated arc therapy plans, which have similar monitor unit efficiencies, present similar dosimetric results in the fractionated intracranial radiotherapy

Ranking-Based Differential Evolution for Large-Scale Continuous Optimization

Large-scale continuous optimization has gained considerable attention in recent years. Differential evolution (DE) is a simple yet efficient global numerical optimization algorithm, which has been successfully used in diverse fields. Generally, the vectors in the DE mutation operators are chosen randomly from the population. In this paper, we employ the ranking-based mutation operators for the DE algorithm to improve DE's performance. In the ranking-based mutation operators, the vectors are selected according to their rankings in the current population. The ranking-based mutation operators are general, and they are integrated into the original DE algorithm, GODE, and GaDE to verify the enhanced performance. Experiments have been conducted on the large-scale continuous optimization problems. The results indicate that the ranking-based mutation operators are able to enhance the overall performance of DE, GODE, and GaDE in the large-scale continuous optimization problems

Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

INTRODUCTION In 2017, it is estimated that 26,070 patients will be diagnosed with a malignant primary brain tumor in the United States, with more than half having the diagnosis of glioblas- toma (GBM).1 Magnetic resonance imaging (MRI) is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma; standard modalities available from any clinical MRI scanner, including T1, T2, T2-FLAIR, and T1-contrast-enhanced (T1CE) sequences, provide critical clinical information. In the last decade, advanced imaging modalities are increasingly utilized to further charac- terize glioblastomas. These include multi-parametric MRI sequences, such as dynamic contrast enhancement (DCE), dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), functional imaging, and spectroscopy (MRS), to further characterize glioblastomas, and significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. A contemporary review of standard and advanced MR imaging in clinical neuro-oncologic practice is presented

From survival to survivorship: late side effects become an issue in high-grade glioma.

“For many patients, controlling neurological symptoms, preventing cognitive dysfunction and maintaining functional independence are just as important as prolonging survival.

Stereotactic Radiosurgery Practice Patterns for Brain Metastases in the United States: A National Survey

Background: Stereotactic radiosurgery (SRS) has emerged as an important modality for the treatment of intracranial metastases. There are currently few established guidelines delineating indications for SRS use and fewer still regarding plan evaluation in the treat- ment of multiple brain metastases. Methods: An 18 question electronic survey was distributed to radiation oncologists at National Cancer Institute (NCI) designated cancer centers in the US (60). Centers without radiation oncologists were excluded. Physicians who indicated that they do not prescribe SRS were excluded from the remaining survey questions. Sign test and Chi-square test were used to determine if responses differed significantly from random distribution. Results: 116 of the 697 radiation oncologists surveyed completed the questionnaire, representing 51 institutions. 62% reported treating patients with brain metastases using SRS. Radiation oncologists prescribing SRS most commonly treat CNS (66.2%) and lung (49.3%) malignancies. SRS was used more frequently for \u3c10 brain metastases (73.7%; p\u3c.0001) and whole brain radiation therapy (WBRT) for \u3e10 brain metastases (82.5%; p\u3c.0001). The maximum number of lesions physicians were willing to treat with SRS without WBRT was 1-4 (40.4%) and 5-10 (42.4%) (p\u3c.0001 compared to 11-15, 16-20 and no limit). The most important criteria for choosing SRS or WBRT were number of lesions (p\u3c.0001) and performance status (p=.016). The most common margin for SRS was 0 mm (49.1%; p=.0021). The most common dose constraints other than critical structure was conformity index (84.2%) and brain V12 (61.4%). The LINAC was the most common treatment modality (54.4%) and mono-isocenter technique for multiple brain metastases was commonly used (43.9%; p=.23). Most departments do not have a policy for brain metastases treatment (64.9%; p=.024). Conclusions: This is one of the first national surveys assessing the use of SRS for brain metastases in clinical practice. These data highlight some clinical considerations for physicians treating brain metastases with SRS. Summary: This is among the first national surveys to assess the use of SRS for brain metastases in clinical practice. Specifically, radiation oncologist reported increasingly using SRS instead of WBRT for treating \u3c10 metastases, with the LINAC being the most common modality. Further, treatment parameters considered the most important included 0 mm margins, conformity index, brain V12, and mono- isocenter technique for multiple brain metastases. These results may provide context regarding the use of SRS for brain metastases in clinical practice

A weighted biobjective transformation technique for locating multiple optimal solutions of nonlinear equation systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Due to the fact that a nonlinear equation system may contain multiple optimal solutions, solving nonlinear equation systems is one of the most important challenges in numerical computation. When applying evolutionary algorithms to solve nonlinear equation systems, two issues should be considered: i) how to transform a nonlinear equation system into a kind of optimization problem, and ii) how to develop an optimization algorithm to solve the transformed optimization problem. In this paper, we tackle the first issue by transforming a nonlinear equation system into a weighted biobjective optimization problem. By the above transformation, not only do all the optimal solutions of an original nonlinear equation system become the Pareto optimal solutions of the transformed biobjective optimization problem, but also their images are different points on a linear Pareto front in the objective space. In addition, we suggest an adaptive multiobjective differential evolution, the goal of which is to effectively locate the Pareto optimal solutions of the transformed biobjective optimization problem. Once these solutions are found, the optimal solutions of the original nonlinear equation system can also be obtained correspondingly. By combining the weighted biobjective transformation technique with the adaptive multiobjective differential evolution, we propose a generic framework for the simultaneous locating of multiple optimal solutions of nonlinear equation systems. Comprehensive experiments on 38 nonlinear equation systems with various features have demonstrated that our framework provides very competitive overall performance compared with several state-of-the-art methods

Anveshak - A Groundtruth Generation Tool for Foreground Regions of Document Images

We propose a graphical user interface based groundtruth generation tool in this paper. Here, annotation of an input document image is done based on the foreground pixels. Foreground pixels are grouped together with user interaction to form labeling units. These units are then labeled by the user with the user defined labels. The output produced by the tool is an image with an XML file containing its metadata information. This annotated data can be further used in different applications of document image analysis.Comment: Accepted in DAR 201

Comparison of Online 6 Degree-of-Freedom Image Registration of Varian TrueBeam Cone-Beam CT and BrainLab ExacTrac X-Ray for Intracranial Radiosurgery.

PURPOSE: The study was aimed to compare online 6 degree-of-freedom image registrations of TrueBeam cone-beam computed tomography and BrainLab ExacTrac X-ray imaging systems for intracranial radiosurgery. METHODS: Phantom and patient studies were performed on a Varian TrueBeam STx linear accelerator (version 2.5), which is integrated with a BrainLab ExacTrac imaging system (version 6.1.1). The phantom study was based on a Rando head phantom and was designed to evaluate isocenter location dependence of the image registrations. Ten isocenters at various locations representing clinical treatment sites were selected in the phantom. Cone-beam computed tomography and ExacTrac X-ray images were taken when the phantom was located at each isocenter. The patient study included 34 patients. Cone-beam computed tomography and ExacTrac X-ray images were taken at each patient\u27s treatment position. The 6 degree-of-freedom image registrations were performed on cone-beam computed tomography and ExacTrac, and residual errors calculated from cone-beam computed tomography and ExacTrac were compared. RESULTS: In the phantom study, the average residual error differences (absolute values) between cone-beam computed tomography and ExacTrac image registrations were 0.17 ± 0.11 mm, 0.36 ± 0.20 mm, and 0.25 ± 0.11 mm in the vertical, longitudinal, and lateral directions, respectively. The average residual error differences in the rotation, roll, and pitch were 0.34° ± 0.08°, 0.13° ± 0.09°, and 0.12° ± 0.10°, respectively. In the patient study, the average residual error differences in the vertical, longitudinal, and lateral directions were 0.20 ± 0.16 mm, 0.30 ± 0.18 mm, 0.21 ± 0.18 mm, respectively. The average residual error differences in the rotation, roll, and pitch were 0.40°± 0.16°, 0.17° ± 0.13°, and 0.20° ± 0.14°, respectively. Overall, the average residual error differences wer