Kristy K. Brock's research while affiliated with University of Texas MD Anderson Cancer Center and other places

Publications (343)

Article
PurposeThe aim of this study was to analyze the impact of using intra-procedural pre-ablation contrast-enhanced CT prior to percutaneous thermal ablation (pre-ablation CECT) of colorectal liver metastases (CLM) on local outcomes.Materials and Methods This retrospective analysis of a prospectively collected liver ablation registry included 144 conse...
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Objectives: Cancer patients have worse outcomes from the COVID-19 infection and greater need for ventilator support and elevated mortality rates than the general population. However, previous artificial intelligence (AI) studies focused on patients without cancer to develop diagnosis and severity prediction models. Little is known about how the AI...
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Image-guided percutaneous ablation techniques represent an attractive local therapy for the treatment of colorectal liver metastases (CLM) given its low risk of severe complications, which allows for early initiation of adjuvant therapies and spare functional liver parenchyma, allowing repeated treatments at the time of recurrence. However, ablatio...
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Image fusion of CT, MRI, and PET with endoscopic ultrasound and transabdominal ultrasound can be promising for GI malignancies as it has the potential to allow for a more precise lesion characterization with higher accuracy in tumor detection, staging, and interventional/image guidance. We conducted a literature review to identify the current possi...
Article
Purpose Deep learning (DL) techniques have been successful in disease prediction tasks and could improve the prediction of mandible osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiation therapy. In this study, we retrospectively compared the performance of DL algorithms and traditional machine learning (ML) techniques to pred...
Article
Purpose/Objective(s) To test the hypothesis that deep learning (DL) techniques, using full dose distributions, can outperform machine learning (ML) methods, using dose summary statistics, in the prediction of osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiotherapy (RT). Materials/Methods 1259 subjects from a single institut...
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Purpose Discrepancies between planned and delivered dose to GI structures during radiation therapy (RT) of liver cancer may hamper the prediction of treatment outcomes. The purpose of this study is to develop a streamlined workflow for dose accumulation in a treatment planning system (TPS) during liver image-guided RT and to assess its accuracy whe...
Article
Purpose/Objective(s) To test the hypothesis that radiation damage measured via lung image density change is a function of variable RBE for protons with a coefficient of determination (R²) greater than 0.8. Materials/Methods Data from 61 NSCLC patients previously treated on a prospective clinical trial with PSPT (N = 24) or IMRT (N = 37) to 74 Gy(R...
Article
Background: Percutaneous thermal ablation is a curative-intent locoregional therapy (LRT) for selected patients with unresectable colorectal liver metastasis (CLM). Several factors have been identified that contribute to local tumour control after ablation. However, factors contributing to disease progression outside the ablation zone after ablati...
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Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investig...
Preprint
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Although generative adversarial networks (GANs) have shown promise in medical imaging, they have four main limitations that impeded their utility: computational cost, data requirements, reliable evaluation measures, and training complexity. Our work investigates each of these obstacles in a novel application of StyleGAN2-ADA to high-resolution medi...
Chapter
Although generative adversarial networks (GANs) have shown promise in medical imaging, they have four main limitations that impede their utility: computational cost, data requirements, reliable evaluation measures, and training complexity. Our work investigates each of these obstacles in a novel application of StyleGAN2-ADA to high-resolution medic...
Article
Purpose The purposes of this study were to develop and integrate a colorectal model that incorporates anatomical variations of pediatric patients into the age-scalable in-house computational phantom, and validate the model for pediatric radiation therapy (RT) dose reconstructions. Methods Colorectal contours were manually derived from whole-body n...
Article
PurposeThis study aims to evaluate the intra-procedural use of a novel ablation confirmation (AC) method, consisting of biomechanical deformable image registration incorporating AI-based auto-segmentation, and its impact on tumor coverage by quantitative three-dimensional minimal ablative margin (MAM) CT-generated assessment.Materials and methodsTh...
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Objectives Colorectal cancer (CRC), the third most common cancer in the USA, is a leading cause of cancer-related death worldwide. Up to 60% of patients develop liver metastasis (CRLM). Treatments like radiation and ablation therapies require disease segmentation for planning and therapy delivery. For ablation, ablation-zone segmentation is require...
Article
Background: Successful generation of biomechanical model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor intensive and hinder DIR efficiency and clinical workflow. Purpose: To identify optimal parameters...
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Purpose: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours. Methods: A reference autocontouring system (primary system to create clinical contours) and a verification autocontouring system (secondary system to test the primary contours) were used to generate a pair of 6 f...
Article
Purpose/Objective(s) Current GI toxicity models are limited by the uncertainty in the estimated delivered dose used to develop the models. The purpose of this study is to assess the benefit of harnessing deep learning and biomechanical models to improve the understanding of the dose-toxicity relationship. Materials/Methods Retrospective dose accum...
Preprint
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Purpose: In order to accurately accumulate delivered dose for head and neck cancer patients treated with the Adapt to Position workflow on the 1.5T magnetic resonance imaging (MRI)-linear accelerator (MR-linac), the low-resolution T2-weighted MRIs used for daily setup must be segmented to enable reconstruction of the delivered dose at each fraction...
Article
Despite tremendous advancements in in vivo imaging modalities, there remains substantial uncertainty with respect to tumor delineation on in these images. Histopathology remains the gold standard for determining the extent of malignancy, with in vivo imaging to histopathologic correlation enabling spatial comparisons. In this review, the steps nece...
Article
Brain-shift during neurosurgery compromises the accuracy of tracking the boundaries of the tumor to be resected. Although several studies have used various finite element models (FEMs) to predict inward brain-shift, evaluation of their accuracy and efficiency based on public benchmark data has been limited. This study evaluates several FEMs propose...
Article
Purpose: Precise correlation between 3D imaging and histology can aid biomechanical modeling of the breast. We develop a framework to register ex vivo images to histology using a novel cryo-fluorescence tomography (CFT) device. Methods: A formalin-fixed cadaveric breast specimen, including chest wall, was subjected to high-resolution magnetic re...
Article
Purpose: Objective assessment of deformable image registration (DIR) accuracy often relies on the identification of anatomical landmarks in image pairs, a manual process known to be extremely time-expensive. The goal of this study is to propose a method to automatically detect vessel bifurcations in images and assess their use for the computation...
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Image-guided ablation can provide effective local tumor control in selected patients with CLM. A randomized controlled trial suggested that radiofrequency ablation combined with systemic chemotherapy resulted in a survival benefit for patients with unresectable CLM, compared to systemic chemotherapy alone. For small tumors, ablation with adequate m...
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Purpose: Colorectal cancer is the third most common form of cancer in the United States, and up to 60% of these patients develop liver metastasis. While hepatic resection is the curative treatment of choice, only 20% of patients are candidates at the time of diagnosis. While percutaneous thermal ablation (PTA) has demonstrated 24-51% overall 5-yea...
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Purpose: Re-planning for four-dimensional computed tomography (4DCT)-based lung adaptive radiotherapy commonly requires deformable dose mapping between the planning average-intensity image (AVG) and the newly acquired AVG. However, such AVG-AVG deformable image registration (DIR) lacks accuracy assessment. The current work quantified and compared...
Presentation
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Purpose: To develop, validate and integrate into an age-scalable computational phantom an “average” colorectal model that incorporates anatomical variations of pediatric patients. Methods: Whole-body non-contrast CT scans of fifty-five male pediatric patients (age range: 2.1-21.6years) were retrospectively selected. Manual colorectal contours were...
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Objectives Stereotactic radiosurgery (SRS) is a common treatment for brain metastases and is typically planned on MR imaging. However, the MR acquisition parameters used for patient selection and treatment planning for SRS can vary within and across institutions. In this work, we investigate the effect of MRI slice thickness on the detection and co...
Article
Deep learning is becoming increasingly popular and available to new users, particularly in the medical field. Deep learning image segmentation, outcome analysis, and generators rely on presentation of Digital Imaging and Communications in Medicine (DICOM) images, and often radiation therapy (RT) structures as masks. While the technology to convert...
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Purpose: Abdominal compression can minimize breathing motion in stereotactic radiotherapy, though it may impact the positioning of dose-limiting normal tissues. This study quantified the reproducibility of abdominal normal tissues and respiratory motion with the use of an abdominal compression device using MR imaging. Methods: Twenty healthy vol...
Article
Purpose: Most existing computed tomography (CT)-ventilation imaging techniques are based on deformable image registration (DIR) of different respiratory phases of a four-dimensonal CT (4DCT) scan of the lung, followed by the quantification of local breathing-induced changes in Hounsfield Units (HU) or volume. To date, only moderate correlations ha...
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Purpose: This study investigated deep learning models for automatic segmentation to support the development of daily online dose optimization strategies, eliminating the need for ITV expansions and thereby reducing toxicity events of IMRT for cervical cancer. Methods and Materials: The cervix-uterus, vagina, parametrium, bladder, rectum, sigmoid,...
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Purpose: To develop a tool for the automatic contouring of clinical treatment volumes (CTVs) and normal tissues for radiotherapy treatment planning in cervical cancer patients. Methods: An auto-contouring tool based on convolutional neural networks (CNN) was developed to delineate 3 cervical CTVs and 11 normal structures (7 OARs, 4 bony structur...
Article
During minimally invasive surgery (MIS) for lung tumor resection, the localization of tumors or nodules relies on visual inspection of the deflated lung on intra-procedural video. For patients with tumors or nodules located deeper in the lung, this localization is not possible without prior invasive marking techniques. In efforts to avoid the incre...
Preprint
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Objectives To determine the utility of low-flip angle black bone magnetic resonance imaging (MRI) for cortical mandibular bone assessment by comparing interdentium cortical measurements and inter-observer morphometric variability in relation to computed tomography (CT). Methods Quantification of cortical mandible bone width was performed as per Ham...
Article
Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and...
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Purpose: Prior in silico simulations propose that Temporally Feathered Radiation Therapy (TFRT) may reduce toxicity related to head and neck radiation therapy. In this study we demonstrate a step-by-step guide to TFRT planning with modern treatment planning systems. Methods: One patient with oropharyngeal cancer planned for definitive radiation...
Article
Purpose On June 13-14, 2019, the American Society for Radiation Oncology (ASTRO) and the Radiological Society of North America (RSNA) convened a workshop on the Treatment of Oligometastatic Disease in Washington, DC. The workshop was initiated because of several reasons. First, oligometastatic (OM) disease is of increasing academic and community in...
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The deformable nature of the liver can make focal treatment challenging and is not adequately addressed with simple rigid registration techniques. While more advanced registration techniques can take deformations into account (biomechanical modeling), they require segmentations of the whole liver for each scan, a time intensive process. We hypothes...
Article
Purpose: Early animal studies suggest that parotid gland (PG) toxicity prediction could be improved by an accurate estimation of the radiation dose to sub-regions of the PG. Translation to clinical investigation requires voxel-level dose accumulation in this organ that responds volumetrically throughout treatment. To date, deformable image registr...
Article
Purpose To develop robust normal tissue complication probability (NTCP) models for hepatocellular carcinoma (HCC) patients treated with radiation therapy (RT) using Child-Pugh (CP) score and Albumin-Bilirubin (ALBI) grade increase as endpoints for hepatic toxicity. Methods and Materials Data from 108 HCC patients treated with RT between 2008 and 2...
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Glioblastoma is an aggressive brain tumor with a propensity for intracranial recurrence. We hypothesized that tumors can be visualized with diffusion tensor imaging (DTI) before they are detected on anatomical magnetic resonance (MR) images. We retrospectively analyzed serial MR images from 30 patients, including the DTI and T1-weighted images at r...
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Purpose: In this study, we investigated registration methods for estimating the large interfractional sigmoid deformations that occur between external beam radiation therapy (EBRT) and brachytherapy (BT) for cervical cancer. Methods and materials: Sixty-three patients were retrospectively analyzed. The sigmoid colon was delineated on 2 computed...
Article
Purpose: Response assessment of radiotherapy for the treatment of intrahepatic cholangiocarcinoma (IHCC) across longitudinal images is challenging due to anatomical changes. Advanced deformable image registration (DIR) techniques are required to correlate corresponding tissues across time. In this study, the accuracy of five commercially available...
Article
This work demonstrates the potential for using a deformable mapping method to register lesions between dedicated breast computed tomography (bCT) and both automated breast ultrasound (ABUS) and digital breast tomosynthesis (DBT) images (craniocaudal [CC] and mediolateral oblique [MLO] views). Two multi-modality breast phantoms with external fiducia...
Article
This work investigates the application of a deformable localization/mapping method to register lesions between the digital breast tomosynthesis (DBT) craniocaudal (CC) and mediolateral oblique (MLO) views and automated breast ultrasound (ABUS) images. This method was initially validated using compressible breast phantoms. This methodology was appli...
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Purpose Deformable image registration (DIR) of longitudinal liver cancer computed tomographic (CT) images can be challenging owing to anatomic changes caused by radiation therapy (RT) or disease progression. We propose a workflow for the DIR of longitudinal contrast-enhanced CT scans of liver cancer based on a biomechanical model of the liver drive...
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During head and neck (HN) cancer radiation therapy (RT), dose-response analysis for the parotid glands (PG) relies on accurate alignment of soft tissue between longitudinal images. To isolate the response of the PG to delivered dose, from deformation due to patient position, patient postural changes, mainly due to neck flexion, should be resolved....
Article
Purpose: To evaluate the effect of setup uncertainties including uncertainties between different breath holds (BH) and inter-fractional anatomical changes under CT-guided BH with intensity-modulated proton therapy (IMPT) in patients with liver cancer. Methods and materials: This retrospective study considered 17 patients with liver tumors who un...
Article
Background: Chronic lung allograft dysfunction (CLAD) limits long-term survival following lung transplantation (LTx). Early detection or prediction of CLAD can lead to changes in patient management that, in turn, may improve prognosis. The purpose of this study was to investigate the utility of quantitative computed tomography (CT) lung density an...
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Background: MRI-guided radiotherapy planning (MRIgRT) may be superior to CT-guided planning in some instances owing to its improved soft tissue contrast. However, MR images do not communicate tissue electron density information necessary for dose calculation and therefore must either be co-registered to CT or algorithmically converted to synthetic...
Article
For locally advanced cervical cancer (LACC), anatomy correspondence with and without BT applicator needs to be quantified to merge the delivered doses of external beam radiation therapy (EBRT) and brachytherapy (BT). This study proposed and evaluated different deformable image registration (DIR) methods for this application. Twenty patients who un...
Article
Purpose: This study aimed to improve the understanding of deviations between planned and accumulated doses and to establish metrics to predict clinically significant dosimetric deviations midway through treatment to evaluate the potential need to re-plan during fractionated radiation therapy (RT). Methods and materials: A total of 100 patients w...
Article
Purpose: Research in radiation oncology (RO) is imperative to support the discovery of new uses of radiation and improvement of current approaches to radiation delivery and to foster the continued evolution of our field. Therefore, in 2016, the American Society of Radiation Oncology performed an evaluation of research grant funding for RO. Method...
Article
Purpose: CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present t...
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Background: Current standard radiotherapy for oropharynx cancer (OPC) is associated with high rates of severe toxicities, shown to adversely impact patients' quality of life. Given excellent outcomes of human papilloma virus (HPV)-associated OPC and long-term survival of these typically young patients, treatment de-intensification aimed at improvi...
Article
Purpose: To develop a deformable mapping technique to match corresponding lesions between digital breast tomosynthesis (DBT) and automated breast ultrasound (ABUS) images. Methods: External fiducial markers were attached to the surface of two CIRS multi-modality compressible breast phantoms (A and B) containing multiple simulated lesions. Both p...
Article
Purpose: To determine whether serial cone-beam computed tomography (CBCT) images taken during head and neck radiotherapy (HNR) can improve chronic xerostomia prediction METHODS AND MATERIALS: In a retrospective analysis, parotid glands (PGs) were delineated on daily kV CBCT images using deformable image registration (DIR) for 119 HNR patients (60...
Article
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Purpose: Response assessment of radiotherapy in the treatment of cholangiocarcinomas across longitudinal images is challenging due to liver deformations caused by tumor response and patient positioning. To address this, advanced deformable image registration (DIR) techniques are required. Here we compare four commercially used DIR techniques. Met...