Kevin Albuquerque

ORCID: 0000-0003-4067-6518
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About
Contact & Profiles
Research Areas
  • Endometrial and Cervical Cancer Treatments
  • Advanced Radiotherapy Techniques
  • Radiomics and Machine Learning in Medical Imaging
  • Ovarian cancer diagnosis and treatment
  • Management of metastatic bone disease
  • Breast Cancer Treatment Studies
  • Advances in Oncology and Radiotherapy
  • Cervical Cancer and HPV Research
  • Uterine Myomas and Treatments
  • Colorectal and Anal Carcinomas
  • MRI in cancer diagnosis
  • Medical Imaging Techniques and Applications
  • Endometriosis Research and Treatment
  • Medical Imaging and Analysis
  • Radiation Dose and Imaging
  • Lung Cancer Diagnosis and Treatment
  • Head and Neck Cancer Studies
  • Effects of Radiation Exposure
  • Cancer Diagnosis and Treatment
  • Breast Lesions and Carcinomas
  • Breast Implant and Reconstruction
  • Prostate Cancer Diagnosis and Treatment
  • Gastric Cancer Management and Outcomes
  • Advanced X-ray and CT Imaging
  • Electronic Health Records Systems

The University of Texas Southwestern Medical Center
2016-2025

Southwestern Medical Center
2015-2024

UPMC Hillman Cancer Center
2023

Harold C. Simmons Comprehensive Cancer Center
2020-2021

Texas Oncology
2021

American College of Radiology
2018-2020

Duke Medical Center
2020

Radiation Oncology Associates
2013-2018

University of California Davis Medical Center
2016

University of North Texas at Dallas
2015

Better understanding of the dose-toxicity relationship is critical for safe dose escalation to improve local control in late-stage cervical cancer radiotherapy. In this study, we introduced a convolutional neural network (CNN) model analyze rectum distribution and predict toxicity. Forty-two patients treated with combined external beam radiotherapy (EBRT) brachytherapy (BT) were retrospectively collected, including twelve toxicity thirty non-toxicity patients. We adopted transfer learning...

10.1088/1361-6560/aa8d09 article EN Physics in Medicine and Biology 2017-09-15

In order to survive, cells have evolved highly effective repair mechanisms deal with the potentially lethal DNA damage produced by exposure endogenous as well exogenous agents. Ionizing radiation induces damage, especially double-strand breaks (DSBs), that is sensed cellular machinery and then subsequently repaired either of two different DSB mechanisms: (1) non-homologous end joining, which re-ligates broken ends (2) homologous recombination, employs an undamaged identical sequence a...

10.3389/fonc.2012.00214 article EN cc-by Frontiers in Oncology 2013-01-01

To evaluate the tolerability of a dose-escalated 5-fraction stereotactic body radiation therapy for partial-breast irradiation (S-PBI) in treating early-stage breast cancer after partial mastectomy; primary objective was to escalate dose utilizing robotic system lumpectomy cavity without exceeding maximum tolerated dose.Eligible patients included those with ductal carcinoma situ or invasive nonlobular epithelial histologies and stage 0, I, II, tumor size <3 cm. Patients physicians completed...

10.1016/j.ijrobp.2017.01.020 article EN cc-by-nc-nd International Journal of Radiation Oncology*Biology*Physics 2017-01-12

Distant failure is the main cause of human cancer-related mortalities. To develop a model for predicting distant in non-small cell lung cancer (NSCLC) and cervix (CC) patients, shell feature, consisting outer voxels around tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy 52 CC underwent external beam concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy....

10.1088/1361-6560/aabb5e article EN Physics in Medicine and Biology 2018-04-04

The role of stereotactic ablative radiotherapy (SABR) for gynecologic malignant tumors has yet to be clearly defined despite recent clinical uptake.

10.1001/jamaoncol.2024.1796 article EN JAMA Oncology 2024-06-13

Cervical tumor segmentation on 3D 18FDG PET images is a challenging task because of the proximity between cervix and bladder, both which can uptake tracers. This problem makes traditional based intensity variation methods ineffective reduces overall accuracy. Based anatomy knowledge, including 'roundness' cervical relative positioning bladder cervix, we propose supervised machine learning method that integrates convolutional neural network (CNN) with this prior information to segment tumors....

10.1088/1361-6560/ab0b64 article EN Physics in Medicine and Biology 2019-02-28

Integration of hypofractionated body radiotherapy (H-RT) into immune checkpoint inhibitor (ICI) therapy may be a promising strategy to improve the outcomes ICIs, although sufficient data is lacking regarding safety and efficacy this regimen. We, hereby, reviewed combination in 59 patients treated with H-RT during or within 8 weeks ICI infusion compared results historical reports treatment alone. Most had RCC melanoma. Median follow-up was 11 months. received either Nivolumab alone...

10.1080/2162402x.2018.1440168 article EN OncoImmunology 2018-02-13

Aim/Objectives/Background: The American College of Radiology (ACR) and the Society for Radiation Oncology (ASTRO) have jointly developed following practice parameter image-guided radiation therapy (IGRT). IGRT is that employs imaging to maximize accuracy precision throughout entire process treatment delivery with goal optimizing reliability target, while minimizing dose normal tissues. Methods: ACR–ASTRO Practice Parameter was revised according described on ACR website (“The Process...

10.1097/coc.0000000000000697 article EN American Journal of Clinical Oncology 2020-05-22

OBJECTIVE. The purpose of this study is to evaluate the prognostic value quantitative metabolic parameters from pretreatment PET/CT scans patients with squamous cell cervical cancer. MATERIALS AND METHODS. This retrospective included 120 biopsy-proven carcinoma cervix who underwent FDG for initial tumor staging. primary maximum standardized uptake (SUVmax) and mean (SUVmean), glycolytic activity, volume (MTV), intratumoral heterogeneity index (calculated as AUC cumulative [SUV]-volume...

10.2214/ajr.19.21604 article EN American Journal of Roentgenology 2020-02-18

Abstract Objective. Predicting the probability of having plan approved by physician is important for automatic treatment planning. Driven mathematical foundation deep learning that can use a neural network to represent functions accurately and flexibly, we developed deep-learning framework learns approval cervical cancer high-dose-rate brachytherapy (HDRBT). Approach. The system consisted dose prediction (DPN) plan-approval (PPN). DPN predicts organs at risk (OAR) D 2 cc CTV 90% current...

10.1088/1361-6560/ad3880 article EN cc-by Physics in Medicine and Biology 2024-03-27

This pilot study used a prospective longitudinal design to compare the effect of adjuvant whole breast radiation therapy (WBRT) versus partial (PBRT) on fatigue, perceived stress, quality life and natural killer cell activity (NKCA) in women receiving after cancer surgery. Women (N = 30) with early-stage received either PBRT, Mammosite brachytherapy at dose 34 Gy 10 fractions/5 days, 15) or WBRT, 3-D conformal techniques 50 +10 Boost/30 fractions, 15). Treatment was determined by attending...

10.1186/1471-2407-12-251 article EN cc-by BMC Cancer 2012-06-18

Better knowledge of the dose-toxicity relationship is essential for safe dose escalation to improve local control in cervical cancer radiotherapy. The conventional model based on volume histogram, which parameter lacking spatial information. To overcome this limit, we explore a comprehensive rectal both histogram and map features accurate radiation toxicity prediction. Forty-two patients treated with combined external beam radiotherapy (EBRT) brachytherapy (BT) were retrospectively studied,...

10.1186/s13014-018-1068-0 article EN cc-by Radiation Oncology 2018-07-06

Digitization of interstitial needles is a complicated and tedious process for the treatment planning 3D CT image based high dose-rate brachytherapy (HDRBT) gynecological cancer. We developed deep-learning assisted auto-digitization method needles. The digitization consisted two steps. first step used deep neural network with U-net structure to segment all from images. second simultaneously clustered segmented voxels into different needle groups generated central trajectories by solving an...

10.1088/1361-6560/ab3fcb article EN Physics in Medicine and Biology 2019-08-30
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