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Angel I. Blanco

Bio: Angel I. Blanco is an academic researcher from University of Texas Health Science Center at Houston. The author has contributed to research in topics: Radiation therapy & Radiosurgery. The author has an hindex of 18, co-authored 47 publications receiving 2257 citations. Previous affiliations of Angel I. Blanco include Houston Methodist Hospital & Memorial Hermann Healthcare System.


Papers
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Journal ArticleDOI
TL;DR: CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.
Abstract: A software environment is described, called the computational environment for radiotherapy research (CERR, pronounced "sir"). CERR partially addresses four broad needs in treatment planning research: (a) it provides a convenient and powerful software environment to develop and prototype treatment planning concepts, (b) it serves as a software integration environment to combine treatment planning software written in multiple languages (MATLAB, FORTRAN, C/C++, JAVA, etc.), together with treatment plan information (computed tomography scans, outlined structures, dose distributions, digital films, etc.), (c) it provides the ability to extract treatment plans from disparate planning systems using the widely available AAPM/RTOG archiving mechanism, and (d) it provides a convenient and powerful tool for sharing and reproducing treatment planning research results. The functional components currently being distributed, including source code, include: (1) an import program which converts the widely available AAPM/RTOG treatment planning format into a MATLAB cell-array data object, facilitating manipulation; (2) viewers which display axial, coronal, and sagittal computed tomography images, structure contours, digital films, and isodose lines or dose colorwash, (3) a suite of contouring tools to edit and/or create anatomical structures, (4) dose-volume and dose-surface histogram calculation and display tools, and (5) various predefined commands. CERR allows the user to retrieve any AAPM/RTOG key word information about the treatment plan archive. The code is relatively self-describing, because it relies on MATLAB structure field name definitions based on the AAPM/RTOG standard. New structure field names can be added dynamically or permanently. New components of arbitrary data type can be stored and accessed without disturbing system operation. CERR has been applied to aid research in dose-volume-outcome modeling, Monte Carlo dose calculation, and treatment planning optimization. In summary, CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.

856 citations

Journal ArticleDOI
TL;DR: The factors that affect salivary function after head-and-neck radiotherapy (RT), including parotid gland dose-volume effects, potential compensation by less-irradiated gland tissue, and functional recovery over time are investigated.
Abstract: Purpose: We investigated the factors that affect salivary function after head-and-neck radiotherapy (RT), including parotid gland dose-volume effects, potential compensation by less-irradiated gland tissue, and functional recovery over time. Methods and Materials: Sixty-five patients with head-and-neck tumors were enrolled in a prospective salivary function study. RT was delivered using intensity-modulated RT ( n = 45), forward-planning three-dimensional conformal RT ( n = 14), or three-dimensional conformal RT with an intensity-modulated RT boost ( n = 6). Whole salivary flow was measured before therapy and at 6 months ( n = 61) and 12 months ( n = 31) after RT. A wide variety of dose-volume models to predict post-RT salivary function were tested. Xerostomia was defined according to the subjective, objective, management, analytic (SOMA) criteria as occurring when posttreatment salivary function was Results: A significant correlation was observed between the relative quality-of-life scores and relative stimulated saliva values at 6 months after RT (Spearman's correlation coefficient [R s ] = 0.46, p (−A × mean gland dose), with A equal to 0.054/Gy (68% confidence interval 0.052–0.059), provided a good representation of the data and was incorporated into our multimetric analysis. Using that model, we estimated that a mean parotid dose of 25.8 Gy, on average, was likely to reduce a single parotid gland's flow to 25% of its pretreatment value, regardless of the treatment delivery method. Significant correlations were observed between a logistic multivariate model (incorporating the mean dose-exponential equation, gender, and Karnofsky performance status) and stimulated saliva flow at 6 months (R s = 0.73), stimulated saliva flow at 12 months (R s = 0.54), and quality-of-life score at 6 months (R s = 0.35) after RT. Conclusion: Stimulated parotid salivary gland dose-volume models strongly correlated with both stimulated salivary function and quality-of-life scores at 6 months after RT. The mean stimulated saliva flow rates improved from 6 to 12 months after RT. Salivary function, in each gland, appeared to be lost exponentially at a rate of approximately 5%/1 Gy of mean dose. Additional research is necessary to distinguish among the models for use in treatment planning. The incidence of xerostomia was significantly decreased when the mean dose of at least one parotid gland was kept to

245 citations

Journal ArticleDOI
TL;DR: Multivariate analysis showed that GTV and nGTV were independent risk factors determining locoregional control and disease-free survival for definitive oropharyngeal IMRT patients and are the most important factors predictive of therapeutic outcome.
Abstract: Purpose To assess the therapeutic outcomes in oropharyngeal cancer patients treated with intensity-modulated radiotherapy (IMRT) and analyze the impact of primary gross tumor volume (GTV) and nodal GTV (nGTV) on survival and locoregional control rates. Methods and materials Between February 1997 and September 2001, 74 patients with squamous cell carcinoma of the oropharynx were treated with IMRT. Thirty-one patients received definitive IMRT; 17 also received platinum-based chemotherapy. Forty-three patients received combined surgery and postoperative IMRT. The median follow-up for all patients was 33 months (range, 9–60 months). Fifty-two patients (70.3%) had Stage IV disease, 17 patients (23%) had Stage III, 3 patients (4.1%) had Stage II, and 2 patients (2.7%) had Stage I tumors. The mean prescription dose was 70 and 66 Gy, respectively, for the definitive and postoperative cohorts. The daily fraction dose was either 1.9 or 2 Gy, five times weekly. The GTV and/or nGTV were determined and derived using the Computational Environment for Radiotherapy Research, a free software package developed at Washington University. The mean GTV was 30.5 ± 22.3 cm 3 , and the mean nGTV was 23.2 ± 20.6 cm 3 . Results Ten locoregional failures were observed. Six patients died of disease and three died of concurrent disease. Distant metastasis developed in 6 patients. The 4-year estimate of overall survival was 87%, and the 4-year estimate of disease-free survival was 81% (66% in the definitive vs. 92% in the postoperative RT group). The 4-year estimate of locoregional control was 87% (78% in the definitive vs. 95% in the postoperative RT group); the 4-year estimate of distant metastasis-free survival was 90% (84% in the definitive vs. 94% in the postoperative group). Multivariate analysis showed that GTV and nGTV were independent risk factors determining locoregional control and disease-free survival for definitive oropharyngeal IMRT patients. The worst late toxicities documented were as follows: 32 patients with Grade 1 and 9 with Grade 2 xerostomia; 2 with Grade 1 and 1 with Grade 2 skin toxicity; 3 with Grade 1 late mucositis; and 3 with Grade 1 trismus. Seventeen patients required gastrostomy tube placement. Conclusion IMRT is an effective treatment modality for locally advanced oropharyngeal carcinoma. The GTV and nGTV are the most important factors predictive of therapeutic outcome.

222 citations

Journal ArticleDOI
TL;DR: Intensity‐modulated radiation therapy (IMRT), an advent of three‐dimensional conformal radiotherapy (3D CRT), has excited the profession of radiation oncology more than any other new invention since the introduction of the linear accelerator.
Abstract: Intensity-modulated radiation therapy (IMRT), an advent of three-dimensional conformal radiotherapy (3D CRT), has excited the profession of radiation oncology more than any other new invention since the introduction of the linear accelerator Approximately 1000 articles have been published on this topic to date, more than 200 of which focus on head and neck cancer IMRT is based on computer-optimized treatment planning and a computer-controlled treatment delivery system The computer-driven technology generates dose distributions that sharply conform to the tumor target while minimizing the dose delivered to the surrounding normal tissues The high dose volume that tailors to the 3D configuration of the tumor along with the ability to spare the nearby normal tissues allows the option of tumor dose escalation The head and neck region is an ideal target for this new technology for several reasons First, IMRT offers the potential for improved tumor control through delivery of high doses to the target volume Second, because of sharp dose gradients, IMRT results in the relative sparing of normal structures, such as the parotid glands, in the head and neck region Third, organ motion is virtually absent in the head and neck region so, with proper immobilization, treatment can be accurately delivered Although this is a relatively new technology, single-institution retrospective studies show better dosimetric profiles compared with conventional radiation techniques, as well as excellent clinical results Salivary gland sparing using IMRT has also resulted in reduced incidence and severity of xerostomia, and this has been tested in a randomized trial against conventional radiotherapy for early-stage nasopharyngeal cancer The results do confirm that IMRT does decrease xerostomia compared with conventional radiotherapy

204 citations

Journal ArticleDOI
TL;DR: Bootstrap variable selection techniques improve model building by reducing sample size effects and unveiling variable cross correlations, and statistical inference methods combined with Spearman's coefficient provide an efficient approach to estimating optimal model order.
Abstract: Purpose: The probability of a specific radiotherapy outcome is typically a complex, unknown function of dosimetric and clinical factors. Current models are usually oversimplified. We describe alternative methods for building multivariable dose–response models. Methods: Representative data sets of esophagitis and xerostomia are used. We use a logistic regression framework to approximate the treatment–response function. Bootstrap replications are performed to explore variable selection stability. To guard against under/overfitting, we compare several analytical and data-driven methods for model-order estimation. Spearman’s coefficient is used to evaluate performance robustness. Novel graphical displays of variable cross correlations and bootstrap selection are demonstrated. Results: Bootstrap variable selection techniques improve model building by reducing sample size effects and unveiling variable cross correlations. Inference by resampling and Bayesian approaches produced generally consistent guidance for model order estimation. The optimal esophagitis model consisted of 5 dosimetric/clinical variables. Although the xerostomia model could be improved by combining clinical and dose–volume factors, the improvement would be small. Conclusions: Prediction of treatment response can be improved by mixing clinical and dose–volume factors. Graphical tools can mitigate the inherent complexity of multivariable modeling. Bootstrap-based variable selection analysis increases the reliability of reported models. Statistical inference methods combined with Spearman’s coefficient provide an efficient approach to estimating optimal model order.

164 citations


Cited by
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01 Jan 2013
TL;DR: In this article, the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs) was described, including several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA.
Abstract: We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

2,616 citations

Journal ArticleDOI
TL;DR: The Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) review summarizes the currently available three-dimensional dose/volume/outcome data to update and refine the normal tissue dose/ volume tolerance guidelines provided by the classic Emami et al. paper published in 1991.
Abstract: The Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) review summarizes the currently available three-dimensional dose/volume/outcome data to update and refine the normal tissue dose/volume tolerance guidelines provided by the classic Emami et al. paper published in 1991. A "clinician's view" on using the QUANTEC information in a responsible manner is presented along with a description of the most commonly used normal tissue complication probability (NTCP) models. A summary of organ-specific dose/volume/outcome data, based on the QUANTEC reviews, is included.

1,399 citations

Journal ArticleDOI
TL;DR: This text is a general introduction to radiation biology and a complete, self-contained course especially for residents in diagnostic radiology and nuclear medicine that follows the Syllabus in Radiation Biology of the RSNA.
Abstract: The text consists of two sections, one for those studying or practicing diagnostic radiology, nuclear medicine and radiation oncology; the other for those engaged in the study or clinical practice of radiation oncology--a new chapter, on radiologic terrorism, is specifically for those in the radiation sciences who would manage exposed individuals in the event of a terrorist event. The 17 chapters in Section I represent a general introduction to radiation biology and a complete, self-contained course especially for residents in diagnostic radiology and nuclear medicine that follows the Syllabus in Radiation Biology of the RSNA. The 11 chapters in Section II address more in-depth topics in radiation oncology, such as cancer biology, retreatment after radiotherapy, chemotherapeutic agents and hyperthermia.

1,359 citations

Journal ArticleDOI
TL;DR: Clinical limitations to the current knowledge base include the need for more data on the effect of patient-related cofactors, interactions between dose distribution and cytotoxic or molecular targeted agents, and theeffect of dose fractions and overall treatment time in relation to nonuniform dose distributions.
Abstract: Advances in dose-volume/outcome (or normal tissue complication probability, NTCP) modeling since the seminal Emami paper from 1991 are reviewed. There has been some progress with an increasing number of studies on large patient samples with three-dimensional dosimetry. Nevertheless, NTCP models are not ideal. Issues related to the grading of side effects, selection of appropriate statistical methods, testing of internal and external model validity, and quantification of predictive power and statistical uncertainty, all limit the usefulness of much of the published literature. Synthesis (meta-analysis) of data from multiple studies is often impossible because of suboptimal primary analysis, insufficient reporting and variations in the models and predictors analyzed. Clinical limitations to the current knowledge base include the need for more data on the effect of patient-related cofactors, interactions between dose distribution and cytotoxic or molecular targeted agents, and the effect of dose fractions and overall treatment time in relation to nonuniform dose distributions. Research priorities for the next 5-10 years are proposed.

919 citations

Journal ArticleDOI
TL;DR: CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.
Abstract: A software environment is described, called the computational environment for radiotherapy research (CERR, pronounced "sir"). CERR partially addresses four broad needs in treatment planning research: (a) it provides a convenient and powerful software environment to develop and prototype treatment planning concepts, (b) it serves as a software integration environment to combine treatment planning software written in multiple languages (MATLAB, FORTRAN, C/C++, JAVA, etc.), together with treatment plan information (computed tomography scans, outlined structures, dose distributions, digital films, etc.), (c) it provides the ability to extract treatment plans from disparate planning systems using the widely available AAPM/RTOG archiving mechanism, and (d) it provides a convenient and powerful tool for sharing and reproducing treatment planning research results. The functional components currently being distributed, including source code, include: (1) an import program which converts the widely available AAPM/RTOG treatment planning format into a MATLAB cell-array data object, facilitating manipulation; (2) viewers which display axial, coronal, and sagittal computed tomography images, structure contours, digital films, and isodose lines or dose colorwash, (3) a suite of contouring tools to edit and/or create anatomical structures, (4) dose-volume and dose-surface histogram calculation and display tools, and (5) various predefined commands. CERR allows the user to retrieve any AAPM/RTOG key word information about the treatment plan archive. The code is relatively self-describing, because it relies on MATLAB structure field name definitions based on the AAPM/RTOG standard. New structure field names can be added dynamically or permanently. New components of arbitrary data type can be stored and accessed without disturbing system operation. CERR has been applied to aid research in dose-volume-outcome modeling, Monte Carlo dose calculation, and treatment planning optimization. In summary, CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.

856 citations