Radiation Medicine Commons^™

Comparison Of Reconstructed Prompt Gamma Emissions Using Maximum Likelihood Estimation And Origin Ensemble Algorithms For A Compton Camera System Tailored To Proton Range Monitoring, Ingrid Valencia Lozano, George Dedes, Steve Peterson, Dennis Mackin, Andreas Zoglauer, Sam Beddar, Stephen Avery, Jerimy Polf, Katia Parodi

Faculty, Staff and Student Publications

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit …

Midterm Outcomes Of Aortic Root Surgery In Patients With Marfan Syndrome: A Prospective, Multicenter, Comparative Study, Joseph S Coselli, Irina V Volguina, Scott A Lemaire, Heidi M Connolly, Thoralf M Sundt, Dianna M Milewicz, Harry C Dietz, Hiruni S Amarasekara, Susan Y Green, Qianzi Zhang, Hartzell V Schaff, D Craig Miller

Faculty, Staff and Students Publications

Objective: The objective of this study was to compare midterm outcomes of aortic valve-replacing root replacement (AVR) and aortic valve-sparing root replacement (AVS) operations in patients with Marfan syndrome.

Methods: Patients who met strict Ghent diagnostic criteria for Marfan syndrome and who underwent either AVR or AVS between March 1, 2005 and December 31, 2010 were enrolled in a 3-year follow-up prospective, multicenter, international registry study; the study was subsequently amended to include 20-year follow-up. Enrollees were followed clinically and echocardiographically.

Results: Of the 316 patients enrolled, 77 underwent AVR and 239 underwent AVS; 214 gave reconsent for 20-year follow-up. …

Characterizing The Interplay Of Treatment Parameters And Complexity And Their Impact On Performance On An Iroc Imrt Phantom Using Machine Learning, Hunter Mehrens, Andrea Molineu, Nadia Hernandez, Laurence Court, Rebecca Howell, David Jaffray, Christine B Peterson, Julianne Pollard-Larkin, Stephen F Kry

Faculty, Staff and Student Publications

AIM OF THE STUDY: To elucidate the important factors and their interplay that drive performance on IMRT phantoms from the Imaging and Radiation Oncology Core (IROC).

METHODS: IROC's IMRT head and neck phantom contains two targets and an organ at risk. Point and 2D dose are measured by TLDs and film, respectively. 1,542 irradiations between 2012-2020 were retrospectively analyzed based on output parameters, complexity metrics, and treatment parameters. Univariate analysis compared parameters based on pass/fail, and random forest modeling was used to predict output parameters and determine the underlying importance of the variables.

RESULTS: The average phantom pass rate was …

Applicability And Usage Of Dose Mapping/Accumulation In Radiotherapy, Martina Murr, Kristy K Brock, Marco Fusella, Nicholas Hardcastle, Mohammad Hussein, Michael G Jameson, Isak Wahlstedt, Johnson Yuen, Jamie R Mcclelland, Eliana Vasquez Osorio

Faculty, Staff and Student Publications

Dose mapping/accumulation (DMA) is a topic in radiotherapy (RT) for years, but has not yet found its widespread way into clinical RT routine. During the ESTRO Physics workshop 2021 on "commissioning and quality assurance of deformable image registration (DIR) for current and future RT applications", we built a working group on DMA from which we present the results of our discussions in this article. Our aim in this manuscript is to shed light on the current situation of DMA in RT and to highlight the issues that hinder consciously integrating it into clinical RT routine. As a first outcome of …

Modelling Radiation Cancer Treatment With A Death-Rate Term In Ordinary And Fractional Differential Equations, Nicole Wilson, Corina S Drapaca, Heiko Enderling, Jimmy J Caudell, Kathleen P Wilkie

Faculty, Staff and Student Publications

Fractional calculus has recently been applied to the mathematical modelling of tumour growth, but its use introduces complexities that may not be warranted. Mathematical modelling with differential equations is a standard approach to study and predict treatment outcomes for population-level and patient-specific responses. Here, we use patient data of radiation-treated tumours to discuss the benefits and limitations of introducing fractional derivatives into three standard models of tumour growth. The fractional derivative introduces a history-dependence into the growth function, which requires a continuous death-rate term for radiation treatment. This newly proposed radiation-induced death-rate term improves computational efficiency in both ordinary and …

Commentary: There Is More Than One Way To Skin A Cat, Joseph S Coselli, Jonathan C Hong

Faculty, Staff and Students Publications

No abstract provided.

Commentary: Through Thick And Thin, Jonathan C Hong, Joseph S Coselli

Faculty, Staff and Students Publications

No abstract provided.

Pocketnet: A Smaller Neural Network For Medical Image Analysis, Adrian Celaya, Jonas A Actor, Rajarajesawari Muthusivarajan, Evan Gates, Caroline Chung, Dawid Schellingerhout, Beatrice Riviere, David Fuentes

Faculty, Staff and Student Publications

Medical imaging deep learning models are often large and complex, requiring specialized hardware to train and evaluate these models. To address such issues, we propose the PocketNet paradigm to reduce the size of deep learning models by throttling the growth of the number of channels in convolutional neural networks. We demonstrate that, for a range of segmentation and classification tasks, PocketNet architectures produce results comparable to that of conventional neural networks while reducing the number of parameters by multiple orders of magnitude, using up to 90% less GPU memory, and speeding up training times by up to 40%, thereby allowing …

An Untrained Deep Learning Method For Reconstructing Dynamic Mr Images From Accelerated Model-Based Data, Kalina P Slavkova, Julie C Dicarlo, Viraj Wadhwa, Sidharth Kumar, Chengyue Wu, John Virostko, Thomas E Yankeelov, Jonathan I Tamir

Faculty, Staff and Student Publications

PURPOSE: To implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerated data.

METHODS: The ConvDecoder (CD) neural network was trained with a physics-based regularization term incorporating the spoiled gradient echo equation that describes variable-flip angle data. Fully-sampled variable-flip angle k-space data were retrospectively accelerated by factors of R = {8, 12, 18, 36} and reconstructed with CD, CD with the proposed regularization (CD + r), locally low-rank (LR) reconstruction, and compressed sensing with L1-wavelet regularization (L1). Final images from CD + r training were evaluated at the "argmin" of …

Safety Of Nivolumab Added To Chemoradiation Therapy Platforms For Intermediate And High-Risk Locoregionally Advanced Head And Neck Squamous Cell Carcinoma: Rtog Foundation 3504, Maura L Gillison, Robert L Ferris, Jonathan Harris, A Dimitrios Colevas, Loren K Mell, Christina Kong, Richard C Jordan, Kevin L Moore, Minh-Tam Truong, Claudia Kirsch, Arnab Chakravarti, Dukagjin M Blakaj, David A Clump, James P Ohr, John F Deeken, Michael F Gensheimer, Nabil F Saba, Jennifer A Dorth, David I Rosenthal, Rom S Leidner, Randall J Kimple, Mitchell Machtay, Walter J Curran, Pedro Torres-Saavedra, Quynh Thu Le

Faculty, Staff and Student Publications

PURPOSE: Programmed death-1 immune checkpoint blockade improves survival of patients with recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but the benefits of addition to (chemo)radiation for newly diagnosed patients with HNSCC remain unknown.

METHODS AND MATERIALS: We evaluated the safety of nivolumab concomitant with 70 Gy intensity modulated radiation therapy and weekly cisplatin (arm 1), every 3-week cisplatin (arm 2), cetuximab (arm 3), or alone for platinum-ineligible patients (arm 4) in newly diagnosed intermediate- or high-risk locoregionally advanced HNSCC. Patients received nivolumab from 2 weeks prior to radiation therapy until 3 months post-radiation therapy. The primary endpoint was dose-limiting …

Commentary: A Little Help From The Bench To Cut Risk Of Paraplegia?, Monika Halas, Joseph S Coselli

Faculty, Staff and Students Publications

No abstract provided.

Commentary: Is The Glass Half Full Or Half Empty?, Monika Halas, Joseph S Coselli

Faculty, Staff and Students Publications

No abstract provided.

Vidutolimod In Combination With Atezolizumab With And Without Radiation Therapy In Patients With Programmed Cell Death Protein 1 Or Programmed Death-Ligand 1 Blockade-Resistant Advanced Nsclc, Marcelo V Negrao, Vassiliki A Papadimitrakopoulou, Andrew C Price, Alda L Tam, Muhammad Furqan, Sandeep T Laroia, Erminia Massarelli, Jose Pacheco, John V Heymach, Anne S Tsao, Gary V Walker, Lalit Vora, David Mauro, Heather Kelley, James E Wooldridge, Arthur M Krieg, Jiaxin Niu

Faculty, Staff and Student Publications

INTRODUCTION: Vidutolimod, a CpG-A TLR9 agonist, was investigated in a phase 1b study (CMP-001-003; ClinicalTrials.gov, NCT03438318) in combination with atezolizumab with and without radiation therapy (RT) in patients with advanced NSCLC.

METHODS: Patients with progressive disease after anti-programmed cell death protein 1 or programmed death-ligand 1 therapy received either vidutolimod and atezolizumab (part A) or vidutolimod, atezolizumab, and RT (part B). The primary objective was to evaluate the safety of vidutolimod and atezolizumab with and without RT. Key secondary end point was best objective response rate per Response Evaluation Criteria in Solid Tumors, version 1.1.

RESULTS: Between March 28, 2018, …

Circulating Neutrophils And Tumor-Associated Myeloid Cells Function As A Powerful Biomarker For Response To Chemoradiation In Locally Advanced Cervical Cancer, Olsi Gjyshi, Adam Grippin, Lauren Andring, Anuja Jhingran, Lilie L Lin, Julianna Bronk, Patricia J Eifel, Melissa M Joyner, Jagannadha K Sastry, Kyoko Yoshida-Court, Travis N Solley, Tatiana Cisneros Napravnik, Madison P O'Hara, Venkatesh L Hegde, Lauren E Colbert, Ann H Klopp

Faculty, Staff and Student Publications

PURPOSE: The immune system's role in mediating the cytotoxic effects of chemoradiotherapy remains not completely understood. The integration of immunotherapies into treatment will require insight into features and timing of the immune microenvironment associated with treatment response. Here, we investigated the role of circulating neutrophils and tumor-associated myeloid cells (TSAMs) as potential agents and biomarkers for disease-related outcomes in locally advanced cervical cancer (LACC).

MATERIAL AND METHODS: Hematologic parameters for two LACC patient cohorts, a retrospective clinical and a prospective translational cohort, were obtained at baseline, weekly during chemoradiotherapy for the retrospective cohort, biweekly during chemoradiotherapy for the prospective cohort, …

Physician Perspectives On Telemedicine In Radiation Oncology, Sean Maroongroge, Brian De, Kristina D Woodhouse, Roland L Bassett, Percy Lee, Elizabeth S Bloom, Grace L Smith, Steven J Frank, Jing Li, George Perkins, Prajnan Das, Albert C Koong, Benjamin D Smith, Chenyang Wang

Faculty, Staff and Student Publications

PURPOSE: Telemedicine enthusiasm and uptake in radiation oncology rapidly increased during the COVID-19 pandemic, but it is unclear if and how telemedicine should be used after the COVID-19 public health emergency ends is unclear. Herein, we report on our institution's provider experience after the mature adoption of telemedicine.

METHODS AND MATERIALS: We distributed a survey to all radiation oncology attending physicians at our institution in October 2021 to assess satisfaction, facilitators, and barriers to telemedicine implementation. We performed quantitative and qualitative analyses to characterize satisfaction and identify influencing factors whether telemedicine is employed. We calculated the average proportion of visits …

Carbon Fiber-Reinforced Polyetheretherketone Spinal Implants For Treatment Of Spinal Tumors: Perceived Advantages And Limitations, Christopher Alvarez-Breckenridge, Romulo De Almeida, Ali Haider, Matthew Muir, Justin Bird, Robert North, Laurence Rhines, Claudio Tatsui

Faculty, Staff and Student Publications

PURPOSE: Carbon-fiber reinforced polyetheretherketone (CFRP)-based spinal implants are an alternative to titanium, offering less image artifact as their metallic counterparts while maintaining similar biomechanical and biocompatibility properties. Its use in the management of spinal tumors has been reported, however the perceived advantages related to improved imaging quality, radiation treatment planning, and detection of tumor recurrence have not been fully assessed.

METHODS: We performed a retrospective review of medical records amongst oncologic patients treated at MD Anderson Cancer Center with CFRP implants. Histology, tumor location, construct features, time of follow-up, adjuvant radiation, recurrences, overall survival, and hardware-related complications were recorded.

RESULTS: …

Radiation Therapy For Retroperitoneal Sarcomas: A Strass-Ful Situation, Ahsan S Farooqi, B Ashleigh Guadagnolo, Devarati Mitra, Andrew J Bishop

Faculty, Staff and Student Publications

Locoregional recurrence (LRR) is the predominant pattern of relapse and often the cause of death in patients with retroperitoneal sarcomas (RPS). As a result, reducing LRR is a critical objective for RPS patients. However, unlike soft tissue sarcomas (STS) of the superficial trunk and extremity where the benefits of radiation therapy (RT) are well-established, the role of RT in the retroperitoneum remains controversial. Historically, preoperative or postoperative RT, either alone or in combination with intraoperative radiation (IORT), was commonly justified for RPS based on extrapolation from the superficial trunk and extremity STS literature. However, long-awaited results were recently published from …

A Learning Health System For Radiation Oncology, Rishabh Kapoor

Theses and Dissertations

The proposed research aims to address the challenges faced by clinical data science researchers in radiation oncology accessing, integrating, and analyzing heterogeneous data from various sources. The research presents a scalable intelligent infrastructure, called the Health Information Gateway and Exchange (HINGE), which captures and structures data from multiple sources into a knowledge base with semantically interlinked entities. This infrastructure enables researchers to mine novel associations and gather relevant knowledge for personalized clinical outcomes.

The dissertation discusses the design framework and implementation of HINGE, which abstracts structured data from treatment planning systems, treatment management systems, and electronic health records. It utilizes …

Characterization And Investigation Of Cold Atmospheric Plasma And Its Effects On Cancer Cell Biology, Thomas M. Ritrosky

Theses and Dissertations

Modern cancer treatment uses radiation therapy in over 50% of patient cases. It is an e↵ective way of treating tumors because the mechanisms of cell killing are well known through the damage that ionizing radiation does to DNA. The amount of radiation can be tracked through measuring the dose of the clinical photon or electron beam used. However, there are limitations in the usage of radiation therapy, for example, a tumor can create hypoxic areas that become radioresistant leading to complete ine↵ectiveness of further radiation treatment. This project looks into the application of cold atmospheric plasma as an adjuvant therapy …

Safety Of Concurrent Radiation Therapy With Brentuximab Vedotin In The Treatment Of Lymphoma, Susan Y Wu, Penny Q Fang, Ethan B Wang, Sairah Ahmed, Madeleine Duvic, Preetesh Jain, Luis E Malpica Castillo, Ranjit Nair, Raphael E Steiner, Paolo Strati, Auris O Huen, Swaminathan P Iyer, Chelsea C Pinnix, Bouthaina S Dabaja, Jillian R Gunther

Faculty, Staff and Student Publications

PURPOSE: Purpose: Radiation therapy (RT) and the antibody-drug conjugate brentuximab vedotin (BV) are standard-of-care treatment options for patients with certain B and T-cell lymphomas; however, there are limited data exploring the safety of concurrent BV and RT (BVRT).

METHODS AND MATERIALS: We performed a single institutional retrospective review of 44 patients who received BVRT.

RESULTS: Twenty percent of patients (9/44) developed new grade 2 or higher (G2+) hematologic toxicity (HT) after BVRT, which was associated with radiation dose (median dose of 35 Gy in those with new G2+ HT compared with 15 Gy in those without;

CONCLUSIONS: Our analysis demonstrates …

Deep Learning-Based Dose Prediction For Automated, Individualized Quality Assurance Of Head And Neck Radiation Therapy Plans, Mary P Gronberg, Beth M Beadle, Adam S Garden, Heath Skinner, Skylar Gay, Tucker Netherton, Wenhua Cao, Carlos E Cardenas, Christine Chung, David T Fuentes, Clifton D Fuller, Rebecca M Howell, Anuja Jhingran, Tze Yee Lim, Barbara Marquez, Raymond Mumme, Adenike M Olanrewaju, Christine B Peterson, Ivan Vazquez, Thomas J Whitaker, Zachary Wooten, Ming Yang, Laurence E Court

Faculty, Staff and Student Publications

PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.

METHODS AND MATERIALS: A total of 245 volumetric modulated arc therapy HN plans were created using RapidPlan knowledge-based planning (KBP). A subset of 112 high-quality plans was selected under the supervision of an HN radiation oncologist. We trained a 3D Dense Dilated U-Net architecture to predict 3-dimensional dose distributions using 3-fold cross-validation on 90 plans. Model inputs included computed tomography images, target prescriptions, and contours for targets and organs at risk (OARs). The model's performance was assessed on …

Validation Of An Automated Contouring And Treatment Planning Tool For Pediatric Craniospinal Radiation Therapy, Soleil Hernandez, Hester Burger, Callistus Nguyen, Arnold C Paulino, John T Lucas, Austin M Faught, Jack Duryea, Tucker Netherton, Dong Joo Rhee, Carlos Cardenas, Rebecca Howell, David Fuentes, Julianne Pollard-Larkin, Laurence Court, Jeannette Parkes

Faculty, Staff and Student Publications

PURPOSE: Treatment planning for craniospinal irradiation (CSI) is complex and time-consuming, especially for resource-constrained centers. To alleviate demanding workflows, we successfully automated the pediatric CSI planning pipeline in previous work. In this work, we validated our CSI autosegmentation and autoplanning tool on a large dataset from St. Jude Children's Research Hospital.

METHODS: Sixty-three CSI patient CT scans were involved in the study. Pre-planning scripts were used to automatically verify anatomical compatibility with the autoplanning tool. The autoplanning pipeline generated 15 contours and a composite CSI treatment plan for each of the compatible test patients (n=51). Plan quality was evaluated quantitatively …

Head And Neck Radiation Therapy Patterns Of Practice Variability Identified As A Challenge To Real-World Big Data: Results From The Learning From Analysis Of Multicentre Big Data Aggregation (Lambda) Consortium, Amanda Caissie, Michelle Mierzwa, Clifton David Fuller, Murali Rajaraman, Alex Lin, Andrew Macdonald, Richard Popple, Ying Xiao, Lisanne Vandijk, Peter Balter, Helen Fong, Heping Xu, Matthew Kovoor, Joonsang Lee, Arvind Rao, Mary Martel, Reid Thompson, Brandon Merz, John Yao, Charles Mayo

Faculty, Staff and Student Publications

PURPOSE: Outside of randomized clinical trials, it is difficult to develop clinically relevant evidence-based recommendations for radiation therapy (RT) practice guidelines owing to lack of comprehensive real-world data. To address this knowledge gap, we formed the Learning from Analysis of Multicenter Big Data Aggregation consortium to cooperatively implement RT data standardization, develop software solutions for data analysis, and recommend clinical practice change based on real-world data analyzed. The first phase of this "Big Data" study aimed at characterizing variability in clinical practice patterns of dosimetric data for organs at risk (OARs) that would undermine subsequent use of large-scale, electronically aggregated …

Dose Escalation For Pancreas Sbrt: Potential And Limitations Of Using Daily Online Adaptive Radiation Therapy And An Iterative Isotoxicity Automated Planning Approach, Dong Joo Rhee, Sam Beddar, Joseph Abi Jaoude, Gabriel Sawakuchi, Rachael Martin, Luis Perles, Cenji Yu, Yulun He, Laurence E Court, Ethan B Ludmir, Albert C Koong, Prajnan Das, Eugene J Koay, Cullen Taniguichi, Joshua S Niedzielski

Faculty, Staff and Student Publications

PURPOSE: To determine the dosimetric limitations of daily online adaptive pancreas stereotactic body radiation treatment by using an automated dose escalation approach.

METHODS AND MATERIALS: We collected 108 planning and daily computed tomography (CT) scans from 18 patients (18 patients × 6 CT scans) who received 5-fraction pancreas stereotactic body radiation treatment at MD Anderson Cancer Center. Dose metrics from the original non-dose-escalated clinical plan (non-DE), the dose-escalated plan created on the original planning CT (DE-ORI), and the dose-escalated plan created on daily adaptive radiation therapy CT (DE-ART) were analyzed. We developed a dose-escalation planning algorithm within the radiation treatment …

Stereotactic Body Proton Therapy For Early Stage Non-Small Cell Lung Cancer – Technical Challenges And Solutions: The Md Anderson Experience, X Ronald Zhu, Yuting Li, Ming Yang, Thomas J Whitaker, Paige A Taylor, Xiaodong Zhang, Falk Poenisch, Narayan Sahoo, Zhongxing Liao, Joe Y Chang

Faculty, Staff and Student Publications

Our randomized clinical study comparing stereotactic body radiotherapy (SBRT) and stereotactic body proton therapy (SBPT) for early stage non-small cell lung cancer (NSCLC) was closed prematurely owing to poor enrollment, largely because of lack of volumetric imaging and difficulty in obtaining insurance coverage for the SBPT group. In this article, we describe technology improvements in our new proton therapy center, particularly in image guidance with cone beam CT (CBCT) and CT on rail (CTOR), as well as motion management with real-time gated proton therapy (RGPT) and optical surface imaging. In addition, we have a treatment planning system that provides better …

Effectiveness Without Efficacy: Cautionary Tale From A Landmark Breast Cancer Randomized Controlled Trial, Yu Shen, Jing Ning, Heather Y Lin, Simona F Shaitelman, Henry M Kuerer, Isabelle Bedrosian

Faculty, Staff and Student Publications

Background: “Old” randomized controlled trials established breast conserving therapy (BCT) and total mastectomy (TM) equivalence for treating early breast cancer, whereas recent literature report improved survival with BCT. To reconcile this, we performed a simulation study and re-analyzed B-06 trial data.

Methods: We estimated the distributions for overall survival (OS), cumulative incidence functions for breast-cancer-specific death (BCSD) and other causes-specific death (OCSD) by BCT and TM. The restricted mean survival time (RMST) difference and hazard ratio between the two arms were estimated. Given the estimated distributions, we simulated cause-specific death times from each arm, evaluating the power to test treatment …

Predictive Digital Twin For Optimizing Patient-Specific Radiotherapy Regimens Under Uncertainty In High-Grade Gliomas, Anirban Chaudhuri, Graham Pash, David A Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto A B F Lima, Thomas E Yankeelov, Karen Willcox

Faculty, Staff and Student Publications

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties in the underlying tumor biology in high-grade gliomas, where heterogeneity in the response to standard-of-care (SOC) radiotherapy contributes to sub-optimal patient outcomes. The digital twin is initialized through prior distributions derived from population-level clinical data in the literature for a mechanistic model's parameters. Then the digital twin is personalized using Bayesian model calibration for assimilating patient-specific magnetic resonance imaging data. The calibrated digital twin is used to propose optimal …

Comparison Of Machine-Learning And Deep-Learning Methods For The Prediction Of Osteoradionecrosis Resulting From Head And Neck Cancer Radiation Therapy, Brandon Reber, Lisanne Van Dijk, Brian Anderson, Abdallah Sherif Radwan Mohamed, Clifton Fuller, Stephen Lai, Kristy Brock

Faculty, Staff and Student Publications

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 predict mandible ORN binary outcome in an extensive cohort of patients with HNC.

METHODS AND MATERIALS: Patients who received HNC radiation therapy at the University of Texas MD Anderson Cancer Center from 2005 to 2015 were identified for the ML (n = 1259) and DL (n = 1236) studies. The subjects were followed for ORN …

Using Patient Flow Analysis With Real-Time Patient Tracking To Optimize Radiation Oncology Consultation Visits, Shane Mesko, Julius Weng, Prajnan Das, Albert C Koong, Joseph M Herman, Dorothy Elrod-Joplin, Ashley Kerr, Thomas Aloia, John Frenzel, Katy E French, Wendi Martinez, Iris Recinos, Abdulaziz Alshaikh, Utpala Daftary, Amy C Moreno, Quynh-Nhu Nguyen

Faculty, Staff and Student Publications

PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic.

METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create process maps and optimize the workflow of consultation visits in a gastrointestinal radiation oncology clinic at a large academic cancer center. Metrics such as cycle times, waiting times, and rooming times were assessed by using a real-time patient status function in the electronic medical record for 556 consults and compared between before vs after …

Quantitative Apparent Diffusion Coefficients From Peritumoral Regions As Early Predictors Of Response To Neoadjuvant Systemic Therapy In Triple-Negative Breast Cancer, Benjamin C Musall, Beatriz E Adrada, Rosalind P Candelaria, Rania M M Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Lumarie Santiago, Gary J Whitman, Tanya W Moseley, Marion E Scoggins, Hagar S Mahmoud, Jason B White, Ken-Pin Hwang, Nabil A Elshafeey, Medine Boge, Shu Zhang, Jennifer K Litton, Vicente Valero, Debu Tripathy, Alastair M Thompson, Clinton Yam, Peng Wei, Stacy L Moulder, Mark D Pagel, Wei T Yang, Jingfei Ma, Gaiane M Rauch

Faculty, Staff and Student Publications

BACKGROUND: Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC.

PURPOSE: To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC.

STUDY TYPE: Prospective.

POPULATION/SUBJECTS: A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020.

FIELD STRENGTH/SEQUENCE: A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI).

ASSESSMENT: Three scans were …