Radiology Commons^™

Fully Automated Deep Learning Based Auto-Contouring Of Liver Segments And Spleen On Contrast-Enhanced Ct Images, Aashish C Gupta, Guillaume Cazoulat, Mais Al Taie, Sireesha Yedururi, Bastien Rigaud, Austin Castelo, John Wood, Cenji Yu, Caleb O'Connor, Usama Salem, Jessica Albuquerque Marques Silva, Aaron Kyle Jones, Molly Mcculloch, Bruno C Odisio, Eugene J Koay, Kristy K Brock

Faculty, Staff and Student Publications

Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ([Formula: see text] and 3d full resolution of nnU-Net ([Formula: see text] to determine the best architecture ([Formula: see text]. BA was used with vessels ([Formula: see text] and spleen ([Formula: see text] to assess the impact on segment contouring. Models were trained, validated, and tested on 160 ([Formula: see text]), …

Tumor Treating Fields Increases Blood-Brain Barrier Permeability And Relative Cerebral Blood Volume In Patients With Glioblastoma, Michael Iv, Lewis Naya, Sajal Sanan, Samuel L Van Buskirk, Seema Nagpal, Reena P Thomas, Lawrence D Recht, Chirag B Patel

Faculty, Staff and Student Publications

BACKGROUND AND OBJECTIVE: 200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans.

METHODS: Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (V

RESULTS: Among 13 pMRI datasets …

Ai-Enhanced Detection Of Clinically Relevant Structural And Functional Anomalies In Mri: Traversing The Landscape Of Conventional To Explainable Approaches, Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri

Publications and Research

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of …

Predicting Radiotherapy Patient Outcomes With Real-Time Clinical Data Using Mathematical Modelling, Alexander P Browning, Thomas D Lewin, Ruth E Baker, Philip K Maini, Eduardo G Moros, Jimmy Caudell, Helen M Byrne, Heiko Enderling

Faculty, Staff and Student Publications

Longitudinal tumour volume data from head-and-neck cancer patients show that tumours of comparable pre-treatment size and stage may respond very differently to the same radiotherapy fractionation protocol. Mathematical models are often proposed to predict treatment outcome in this context, and have the potential to guide clinical decision-making and inform personalised fractionation protocols. Hindering effective use of models in this context is the sparsity of clinical measurements juxtaposed with the model complexity required to produce the full range of possible patient responses. In this work, we present a compartment model of tumour volume and tumour composition, which, despite relative simplicity, is …

Comprehensive Analysis Of Craniopharyngioma: Epidemiology, Clinical Characteristics, Management Strategies, And Role Of Radiotherapy, Amir Mushtaq, Mohsin Fayaz, Abdul Rashid Bhat, Abbas F Abdul Hussein, Gianluca Ferini, Giuseppe Emmanuele Umana, Gianluca Scalia, Feroze Ahmad Mir, Aizul Khursheed, Bipin Chaurasia

Faculty, Staff and Student Publications

BACKGROUND/AIM: Craniopharyngiomas pose challenges in diagnosis and management due to their rare occurrence and diverse clinical manifestations. This study aimed to provide a comprehensive analysis of cranio-pharyngioma, including its epidemiological trends, clinical presentations, radiological characteristics, surgical interventions, and the role of radiotherapy.

PATIENTS AND METHODS: A retrospective observational study was conducted on 23 patients diagnosed with craniopharyngioma at our hospital from August 2017 to July 2019. Data regarding demographics, clinical presentation, radiological findings, surgical interventions, and adjuvant therapies were collected and analyzed.

RESULTS: Craniopharyngiomas exhibited a bimodal age distribution, with peaks in childhood and late adulthood. Clinical presentations varied between …

A Look-Up-Table Development To Facilitate Ct Simulation Of Mr-Linac Treatment, Neil Hughes, Travis C Salzillo, Sastry Vedam, Tze Yee Lim, Xin Wang, He Wang, Mustefa Mohammedsaid, Clifton D Fuller, Jihong Wang, Jinzhong Yang

Faculty, Staff and Student Publications

While current MR-Linac (MRL) treatment workflows utilize a large table overlay during CT simulation to convert indexing between the two machines, we developed a look-up-table (LUT) as an alternative approach. After populating the LUT, index conversion factors were verified at three separate table locations. The resultant root-mean-square isocenter shifts on the MRL were 0.04/0.08 cm, 0.08/0.07 cm, and 0.09/0.08 cm with/without using the table overlay during simulation in the lateral, longitudinal, and vertical directions, respectively, which is within registration tolerance. Clinical implementation of the LUT has resulted in a more efficient MRL treatment workflow while maintaining accurate patient setup.

Reporting Quality Of Endoscopic Colorectal Cancer Screening Randomized Controlled Trials: Adherence To Recommendations And Interventions, Fouad Jaber, Khalid Ahmed, Osama Hamid, Willie Mohammed Johnson, Saqr Alsakarneh, Abubaker O Abdalla, Yazan Abboud, Mouhand Mohamed, Dushyant Singh Dahiya, Shifa Umar, Mohamed Abdallah, Mohammad Bilal, Aasma Shaukat

Faculty, Staff and Student Publications

BACKGROUND AND AIMS: In 2013, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) steering group published recommendations to standardize reporting quality in randomized controlled trials (RCTs). We aim to assess adherence to SPIRIT reporting guidelines in RCTs on endoscopic colorectal cancer (CRC) screening and participants' adherence to trial protocols.

METHODS: We searched databases for RCTs evaluating flexible sigmoidoscopy or colonoscopy for CRC screening published in English language through September 2023. Each eligible study was evaluated using the 8 core SPIRIT statement areas, totaling 51 points. Each item received 1 point if it met the criteria and 0 points if …

Clinical Acceptability Of Automatically Generated Lymph Node Levels And Structures Of Deglutition And Mastication For Head And Neck Radiation Therapy, Sean Maroongroge, Abdallah Sr Mohamed, Callistus Nguyen, Jean Guma De La Vega, Steven J Frank, Adam S Garden, Brandon G Gunn, Anna Lee, Lauren Mayo, Amy Moreno, William H Morrison, Jack Phan, Michael T Spiotto, Laurence E Court, Clifton D Fuller, David I Rosenthal, Tucker J Netherton

Faculty, Staff and Student Publications

BACKGROUND AND PURPOSE: Auto-contouring of complex anatomy in computed tomography (CT) scans is a highly anticipated solution to many problems in radiotherapy. In this study, artificial intelligence (AI)-based auto-contouring models were clinically validated for lymph node levels and structures of swallowing and chewing in the head and neck.

MATERIALS AND METHODS: CT scans of 145 head and neck radiotherapy patients were retrospectively curated. One cohort (n = 47) was used to analyze seven lymph node levels and the other (n = 98) used to analyze 17 swallowing and chewing structures. Separate nnUnet models were trained and validated using the separate …

Harnessing Uncertainty In Radiotherapy Auto-Segmentation Quality Assurance, Kareem A Wahid, Jaakko Sahlsten, Joel Jaskari, Michael J Dohopolski, Kimmo Kaski, Renjie He, Enrico Glerean, Benjamin H Kann, Antti Mäkitie, Clifton D Fuller, Mohamed A Naser, David Fuentes

Faculty, Staff and Student Publications

One of the key contributions of this study is the reappropriation of standard DL outputs as a quality indicator to identify cases that clinicians should review further. The authors achieve this by applying an empirically derived threshold to the softmax output of their DL network, computing the mean of the thresholded score map (termed the HiS metric), and correlating it with standard geometric quality indices. When juxtaposed with a mean entropy — a commonly used measure of model output uncertainty — HiS consistently demonstrated a stronger correlation with the geometric indices, suggesting its superior ability to stratify cases needing additional …

Expert-Centered Evaluation Of Deep Learning Algorithms For Brain Tumor Segmentation, Katharina V Hoebel, Christopher P Bridge, Sara Ahmed, Oluwatosin Akintola, Caroline Chung, Raymond Y Huang, Jason M Johnson, Albert Kim, K Ina Ly, Ken Chang, Jay Patel, Marco Pinho, Tracy T Batchelor, Bruce R Rosen, Elizabeth R Gerstner, Jayashree Kalpathy-Cramer

Faculty, Staff and Student Publications

Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts' evaluation of …

Image-Guided Deployment And Monitoring Of A Novel Tungsten Nanoparticle-Infused Radiopaque Absorbable Inferior Vena Cava Filter In A Swine Model, Erin Marie San Valentin, Jossana A Damasco, Marvin Bernardino, Karem A Court, Biana Godin, Gino Martin Canlas, Adam Melancon, Gouthami Chintalapani, Megan C Jacobsen, William Norton, Rick R Layman, Natalie Fowlkes, Stephen R Chen, Steven Y Huang, Marites P Melancon

Faculty, Staff and Student Publications

PURPOSE: To improve radiopacity of radiolucent absorbable poly-p-dioxanone (PPDO) inferior vena cava filters (IVCFs) and demostrate their effectiveness in clot-trapping ability.

MATERIALS AND METHODS: Tungsten nanoparticles (WNPs) were incorporated along with polyhydroxybutyrate (PHB), polycaprolactone (PCL), and polyvinylpyrrolidone (PVP) polymers to increase the surface adsorption of WNPs. The physicochemical and in vitro and in vivo imaging properties of PPDO IVCFs with WNPs with single-polymer PHB (W-P) were compared with those of WNPs with polymer blends consisting of PHB, PCL, and PVP (W-PB).

RESULTS: In vitro analyses using PPDO sutures showed enhanced radiopacity with either W-P or W-PB coating, without compromising the …

Siglec15, Negatively Correlated With Pd-L1 In Hcc, Could Induce Cd8+ T Cell Apoptosis To Promote Immune Evasion, Zheng Chen, Mincheng Yu, Bo Zhang, Lei Jin, Qiang Yu, Shuang Liu, Binghai Zhou, Jiuliang Yan, Wentao Zhang, Xiaoqiang Li, Yongfeng Xu, Yongsheng Xiao, Jian Zhou, Jia Fan, Mien-Chie Hung, Qinghai Ye, Hui Li, Lei Guo

Faculty, Staff and Student Publications

Functional roles of SIGLEC15 in hepatocellular carcinoma (HCC) were not clear, which was recently found to be an immune inhibitor with similar structure of inhibitory B7 family members. SIGLEC15 expression in HCC was explored in public databases and further examined by PCR analysis. SIGLEC15 and PD-L1 expression patterns were examined in HCC samples through immunohistochemistry. SIGLEC15 expression was knocked-down or over-expressed in HCC cell lines, and CCK8 tests were used to examine cell proliferative ability in vitro. Influences of SIGLEC15 expression on tumor growth were examined in immune deficient and immunocompetent mice respectively. Co-culture system of HCC cell lines and …

Improving Radiotherapy In Immunosuppressive Microenvironments By Targeting Complement Receptor C5ar1, Callum Beach, David Maclean, Dominika Majorova, Stavros Melemenidis, Dhanya K Nambiar, Ryan K Kim, Gabriel N Valbuena, Silvia Guglietta, Carsten Krieg, Mahnaz Darvish-Damavandi, Tatsuya Suwa, Alistair Easton, Lily Vs Hillson, Ashley K Mcculloch, Ross K Mcmahon, Kathryn Pennel, Joanne Edwards, Sean M O'Cathail, Campbell S Roxburgh, Enric Domingo, Eui Jung Moon, Dadi Jiang, Yanyan Jiang, Qingyang Zhang, Albert C Koong, Trent M Woodruff, Edward E Graves, Tim Maughan, Simon Ja Buczacki, Manuel Stucki, Quynh-Thu Le, Simon J Leedham, Amato J Giaccia, Monica M Olcina

Faculty, Staff and Student Publications

An immunosuppressive microenvironment causes poor tumor T cell infiltration and is associated with reduced patient overall survival in colorectal cancer. How to improve treatment responses in these tumors is still a challenge. Using an integrated screening approach to identify cancer-specific vulnerabilities, we identified complement receptor C5aR1 as a druggable target, which when inhibited improved radiotherapy, even in tumors displaying immunosuppressive features and poor CD8+ T cell infiltration. While C5aR1 is well-known for its role in the immune compartment, we found that C5aR1 is also robustly expressed on malignant epithelial cells, highlighting potential tumor cell-specific functions. C5aR1 targeting resulted in increased …

Identifying The Optimal Deep Learning Architecture And Parameters For Automatic Beam Aperture Definition In 3d Radiotherapy, Skylar S Gay, Kelly D Kisling, Brian M Anderson, Lifei Zhang, Dong Joo Rhee, Callistus Nguyen, Tucker Netherton, Jinzhong Yang, Kristy Brock, Anuja Jhingran, Hannah Simonds, Ann Klopp, Beth M Beadle, Laurence E Court, Carlos E Cardenas

Faculty, Staff and Student Publications

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation.

METHODS: Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer …

Operational Ontology For Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical And Research Use Of Real-World Data From Patients Treated For Cancer, Charles S Mayo, Mary U Feng, Kristy K Brock, Randi Kudner, Peter Balter, Jeffrey C Buchsbaum, Amanda Caissie, Elizabeth Covington, Emily C Daugherty, Andre L Dekker, Clifton D Fuller, Anneka L Hallstrom, David S Hong, Julian C Hong, Sophia C Kamran, Eva Katsoulakis, John Kildea, Andra V Krauze, Jon J Kruse, Tod Mcnutt, Michelle Mierzwa, Amy Moreno, Jatinder R Palta, Richard Popple, Thomas G Purdie, Susan Richardson, Gregory C Sharp, Shiraishi Satomi, Lawrence R Tarbox, Aradhana M Venkatesan, Alon Witztum, Kelly E Woods, Yuan Yao, Keyvan Farahani, Sanjay Aneja, Peter E Gabriel, Lubomire Hadjiiski, Dan Ruan, Jeffrey H Siewerdsen, Steven Bratt, Michelle Casagni, Su Chen, John C Christodouleas, Anthony Didonato, James Hayman, Rishhab Kapoor, Saul Kravitz, Sharon Sebastian, Martin Von Siebenthal, Walter Bosch, Coen Hurkmans, Sue S Yom, Ying Xiao

Faculty, Staff and Student Publications

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships.

METHODS AND MATERIALS: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- …

Systematic Review Of Genetic Polymorphisms Associated With Acute Pain Induced By Radiotherapy For Head And Neck Cancers, Vivian Salama, Yimin Geng, Jillian Rigert, Clifton D Fuller, Sanjay Shete, Amy C Moreno

Faculty, Staff and Student Publications

BACKGROUND/OBJECTIVE: Pain is the most common acute symptom following radiation therapy (RT) for head and neck cancer (HNC). The multifactorial origin of RT-induced pain makes it highly challenging to manage. Multiple studies were conducted to identify genetic variants associated with cancer pain, however few of them focused on RT-induced acute pain. In this review, we summarize the potential mechanisms of acute pain after RT in HNC and identify genetic variants associated with RT-induced acute pain and relevant acute toxicities.

METHODS: A comprehensive search of Ovid Medline, EMBASE and Web of Science databases using terms including "Variants", "Polymorphisms", "Radiotherapy", "Acute pain", …

Primary Tumor Site For Localized Merkel Cell Carcinoma Drives Different Management Strategies Without Impacting Oncologic Outcomes, Samuel Cass, Brandon Cope, Andrew J Bishop, Yi-Ju Chiang, B Ashleigh Guadagnolo, Ahsan Farooqi, William Morrison, Russell G Witt, Riyad N H Seervai, Adam S Garden, Clifton D Fuller, Ryan P Goepfert, Merrick Ross, Jeffrey E Gershenwald, Michael Wong, Phyu P Aung, Emily Z Keung, Devarati Mitra

Faculty, Staff and Student Publications

BACKGROUND AND PURPOSE: Clinically localized Merkel cell carcinoma (MCC) has been associated with high rates of disease relapse. This study examines how primary tumor anatomic site drives patterns of care and outcomes in a large cohort treated in the contemporary era.

MATERIALS AND METHODS: Patterns of care and associated outcomes were evaluated for clinically Stage I-II MCC patients treated at our institution with adjuvant radiation therapy (RT) to the primary site and/or regional nodal basin as a component of their curative intent therapy between 2014-2021.

RESULTS: Of 80 patients who met inclusion criteria, the primary tumor anatomic site was head …

Quantitative Longitudinal Mapping Of Radiation-Treated Prostate Cancer Using Mr Fingerprinting With Radial Acquisition And Subspace Reconstruction, Victoria Y Yu, Ricardo Otazo, Can Wu, Ergys Subashi, Manuel Baumann, Peter Koken, Mariya Doneva, Peter Mazurkewitz, Daniel Shasha, Michael Zelefsky, Laura Cervino, Ouri Cohen

Faculty, Staff and Student Publications

MR fingerprinting (MRF) enables fast multiparametric quantitative imaging with a single acquisition and has been shown to improve diagnosis of prostate cancer. However, most prostate MRF studies were performed with spiral acquisitions that are sensitive to B0 inhomogeneities and consequent blurring. In this work, a radial MRF acquisition with a novel subspace reconstruction technique was developed to enable fast T1/T2 mapping in the prostate in under 4 min. The subspace reconstruction exploits the extensive temporal correlations in the MRF dictionary to pre-compute a low dimensional space for the solution and thus reduce the number of radial spokes to accelerate the …

Immunotherapy Targeting Different Immune Compartments In Combination With Radiation Therapy Induces Regression Of Resistant Tumors, Nils-Petter Rudqvist, Maud Charpentier, Claire Lhuillier, Erik Wennerberg, Sheila Spada, Caroline Sheridan, Xi Kathy Zhou, Tuo Zhang, Silvia C Formenti, Jennifer S Sims, Alicia Alonso, Sandra Demaria

Faculty, Staff and Student Publications

Radiation therapy (RT) increases tumor response to CTLA-4 inhibition (CTLA4i) in mice and in some patients, yet deep responses are rare. To identify rational combinations of immunotherapy to improve responses we use models of triple negative breast cancer highly resistant to immunotherapy in female mice. We find that CTLA4i promotes the expansion of CD4+ T helper cells, whereas RT enhances T cell clonality and enriches for CD8+ T cells with an exhausted phenotype. Combination therapy decreases regulatory CD4+ T cells and increases effector memory, early activation and precursor exhausted CD8+ T cells. A combined gene signature comprising these three CD8+ …

Advances In The Radiological Evaluation Of And Theranostics For Glioblastoma, Grayson W Hooper, Shehbaz Ansari, Jason M Johnson, Daniel T Ginat

Faculty, Staff and Student Publications

Imaging is essential for evaluating patients with glioblastoma. Traditionally a multimodality undertaking, CT, including CT cerebral blood profusion, PET/CT with traditional fluorine-18 fluorodeoxyglucose (18F-FDG), and MRI have been the mainstays for diagnosis and post-therapeutic assessment. However, recent advances in these modalities, in league with the emerging fields of radiomics and theranostics, may prove helpful in improving diagnostic accuracy and treating the disease.

Multi-Parametric Mri For Radiotherapy Simulation, Tian Li, Jihong Wang, Yingli Yang, Carri K Glide-Hurst, Ning Wen, Jing Cai

Faculty, Staff and Student Publications

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Predicting Severity Of Radiation Induced Lymphopenia In Individual Proton Therapy Patients For Varying Dose Rate And Fractionation Using Dynamic 4-Dimensional Blood Flow Simulations, Lucas Mccullum, Jungwook Shin, Stella Xing, Chris Beekman, Jan Schuemann, Theodore Hong, Dan Duda, Radhe Mohan, Steven H Lin, Camilo M Correa-Alfonso, Sean Domal, Julia Withrow, Wesley Bolch, Harald Paganetti, Clemens Grassberger

Faculty, Staff and Student Publications

PURPOSE: Radiation-induced lymphopenia has gained attention recently as the result of its correlation with survival in a range of indications, particularly when combining radiation therapy (RT) with immunotherapy. The purpose of this study is to use a dynamic blood circulation model combined with observed lymphocyte depletion in patients to derive the in vivo radiosensitivity of circulating lymphocytes and study the effect of RT delivery parameters.

METHODS AND MATERIALS: We assembled a cohort of 17 patients with hepatocellular carcinoma treated with proton RT alone in 15 fractions (fx) using conventional dose rates (beam-on time [BOT], 120 seconds) for whom weekly absolute …

Longitudinal Diffusion And Volumetric Kinetics Of Head And Neck Cancer Magnetic Resonance On A 15 T Mr-Linear Accelerator Hybrid System: A Prospective R-Ideal Stage 2a Imaging Biomarker Characterization/Pre-Qualification Study, Joint Head And Neck Radiation Therapy-Mri Development Cooperative, Mr-Linac Consortium Head And Neck Tumor Site Group

Faculty, Staff and Student Publications

Objectives: We aim to characterize the serial quantitative apparent diffusion coefficient (ADC) changes of the target disease volume using diffusion-weighted imaging (DWI) acquired weekly during radiation therapy (RT) on a 1.5 T MR-Linac and correlate these changes with tumor response and oncologic outcomes for head and neck squamous cell carcinoma (HNSCC) patients as part of a programmatic R-IDEAL biomarker characterization effort.

Methods:Thirty patients with HNSCC who received curative-intent RT at MD Anderson Cancer Center, were included. Baseline and weekly MRI were obtained, and various ADC parameters were extracted from the regions of interest (ROIs). Baseline and weekly ADC parameters were …

Analysis Of Performance And Failure Modes Of The Iroc Proton Liver Phantom, Hunter Mehrens, Paige Taylor, Paola Alvarez, Stephen Kry

Faculty, Staff and Student Publications

Purpose: To analyze trends in institutional performance and failure modes for the Imaging and Radiation Oncology Core’s (IROC’s) proton liver phantom.

Materials and Methods: Results of 66 phantom irradiations from 28 institutions between 2015 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom results. Phantom results included pass/fail classification, average thermoluminescent dosimeter (TLD) ratio of both targets, and percentage of pixels passing gamma of both targets. The following categories were evaluated in terms of how they predicted these outcomes: irradiation year, treatment planning system (TPS), TPS algorithm, treatment machine, number …

Imaging In Interventional Radiology: 2043 And Beyond, Kristy K Brock, Stephen R Chen, Rahul A Sheth, Jeffrey H Siewerdsen

Faculty, Staff and Student Publications

Since its inception in the early 20th century, interventional radiology (IR) has evolved tremendously and is now a distinct clinical discipline with its own training pathway. The arsenal of modalities at work in IR includes x-ray radiography and fluoroscopy, CT, MRI, US, and molecular and multimodality imaging within hybrid interventional environments. This article briefly reviews the major developments in imaging technology in IR over the past century, summarizes technologies now representative of the standard of care, and reflects on emerging advances in imaging technology that could shape the field in the century ahead. The role of emergent imaging technologies in …

Addressing The Global Expertise Gap In Radiation Oncology: The Radiation Planning Assistant, Laurence Court, Ajay Aggarwal, Hester Burger, Carlos Cardenas, Christine Chung, Raphael Douglas, Monique Du Toit, David Jaffray, Anuja Jhingran, Michael Mejia, Raymond Mumme, Sikudhani Muya, Komeela Naidoo, Jerry Ndumbalo, Kelly Nealon, Tucker Netherton, Callistus Nguyen, Niki Olanrewaju, Jeannette Parkes, Willie Shaw, Christoph Trauernicht, Melody Xu, Jinzhong Yang, Lifei Zhang, Hannah Simonds, Beth M Beadle

Faculty, Staff and Student Publications

PURPOSE: Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

DESIGN: In this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and …

Prospective Validation Of Diffusion-Weighted Mri As A Biomarker Of Tumor Response And Oncologic Outcomes In Head And Neck Cancer: Results From An Observational Biomarker Pre-Qualification Study, Abdallah S R Mohamed, Abdelrahman Abusaif, Renjie He, Kareem A Wahid, Vivian Salama, Sara Youssef, Brigid A Mcdonald, Mohamed Naser, Yao Ding, Travis C Salzillo, Moamen A Abobakr, Jihong Wang, Stephen Y Lai, Clifton D Fuller

Faculty, Staff and Student Publications

PURPOSE: To determine DWI parameters associated with tumor response and oncologic outcomes in head and neck (HNC) patients treated with radiotherapy (RT).

METHODS: HNC patients in a prospective study were included. Patients had MRIs pre-, mid-, and post-RT completion. We used T2-weighted sequences for tumor segmentation which were co-registered to respective DWIs for extraction of apparent diffusion coefficient (ADC) measurements. Treatment response was assessed at mid- and post-RT and was defined as: complete response (CR) vs. non-complete response (non-CR). The Mann-Whitney U test was used to compare ADC between CR and non-CR. Recursive partitioning analysis (RPA) was performed to identify …

Single-Compartment Dose Prescriptions For Ablative 90y-Radioembolization Segmentectomy, Srinivas Cheenu Kappadath, Benjamin P Lopez

Faculty, Staff and Student Publications

BACKGROUND: Yttrium-90 (90Y) radioembolization is increasingly being utilized with curative intent. While single-compartment doses with respect to the perfused volume for the complete pathologic necrosis (CPN) of tumors have been reported, the actual doses delivered to the tumor and at-risk margins that leads to CPN have hitherto not been estimated. We present an ablative dosimetry model that calculates the dose distribution for tumors and at-risk margins based on numerical mm-scale dose modeling and the available clinical CPN evidence and report on the necessary dose metrics needed to achieve CPN following 90Y-radioembolization.

METHODS: Three-dimensional (3D) activity distributions (MBq/voxel) simulating spherical tumors …

Clinical Outcomes Of Immunotherapy Continued Beyond Radiographic Disease Progression In Older Adult Patients With Advanced Non-Small Cell Lung Cancer, Eric K Singhi, Frank Mott, Michelle Worst, Cheuk Hong Leung, J Jack Lee, Brett Carter, Carolyn J Presley, John V Heymach, Mehmet Altan

Faculty, Staff and Student Publications

Immunotherapy is an effective and generally well-tolerated treatment strategy for older adult patients (aged ≥70 years) with advanced non-small cell lung cancer (NSCLC). Unfortunately, most patients who receive immunotherapy eventually exhibit disease progression during treatment. The present study reports on a subset of older adult patients with advanced NSCLC who could effectively continue immunotherapy beyond radiographic disease progression due to perceived clinical benefit. Local consolidative radiotherapy may be used in select older adult patients to prolong the duration of immunotherapy they receive, with a particular consideration of their preexisting co-morbidities, performance status and tolerance of potential toxicities associated with combined …

Cone-Beam Ct Sampling Incompleteness: Analytical And Empirical Studies Of Emerging Systems And Source-Detector Orbits, Pengwei Wu, Aina Tersol, Rolf Clackdoyle, John M Boone, Jeffrey H Siewerdsen

Faculty, Staff and Student Publications

PURPOSE: Motivated by emerging cone-beam computed tomography (CBCT) systems and scan orbits, we aim to quantitatively assess the completeness of data for 3D image reconstruction-in turn, related to "cone-beam artifacts." Fundamental principles of cone-beam sampling incompleteness are considered with respect to an analytical figure-of-merit [FOM, denoted

APPROACH:A previously proposed analytical FOM [tan ( ψmin ) , defined as the minimum angle between a point in the 3D image reconstruction and the x-ray source over the scan orbit] was analyzed for a variety of CBCT geometries. A physical test phantom was configured with parallel disk pairs (perpendicular to the z-axis) …