Radiation Medicine Commons^™

From Standard To Stratified: Modeling Ntcp And Ear To Personalize Daily Mv-Cbct In Radiotherapy., Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Duong Tuan Linh, Nguyen Ngoc Anh, Nguyen Quang Hung, Peter Sandwall, Parham Alaei, David Bradley, James C L Chow

Oncology Articles

PURPOSE: To evaluate the cumulative radiobiological impact of daily megavoltage cone-beam computed tomography (MV-CBCT) imaging dose based on normal tissue complication probability (NTCP) and excess absolute risk (EAR) of secondary malignancies among radiotherapy patients treated for breast, pelvic, and head & neck cancers. This study investigated whether MV-CBCT imaging dose warrants protocol personalization according to patient age, anatomical treatment site, and organ-specific radiosensitivity.

METHODS: This retrospective study included cohorts of breast (n = 30), pelvic (n = 17), and head & neck (n = 20) cancer patients undergoing radiotherapy with daily MV-CBCT. Imaging dose distributions employing two common MV-CBCT protocols …

Fast And Accurate Measurement Of Small Field Dosimetry Using A Novel Scintillation Detector, Yiding Han, Jingzhu Xu, Yao Hao, Baozhou Sun

Faculty, Staff and Students Publications

Background: The most used instruments for small-field dosimetry have notable limitations, including the need for correction of output factors, limited scanning speeds, and challenges in alignment for percentage depth dose (PDD) measurements, particularly for extremely small fields. However, plastic scintillation detectors (PSDs) are an attractive alternative for small-field dosimetry due to their correction-free nature, linear dose response, and fast response time.

Purpose: This study evaluates the robustness and accuracy of the dosimetric measurements using a new water-equivalent PSD in small-field dosimetry. The study also aims to report accurate measurements of output factors, profiles, and an indirect method for measuring PDD …

Robust Automated Method Of Spatial Resolution Measurement In Radiotherapy Ct Simulation Images, Pavel Govyadinov, Rick R Layman, Tucker Netherton, Raymond Mumme, Aaron K Jones, Laurence E Court, Moiz Ahmad

Faculty, Staff and Student Publications

Background: Variation in imaging protocol, patient positioning, and the presence of artifacts can vary image quality in CT images used for radiotherapy planning. Automated methods for spatial resolution (SR) estimation exist but require further investigation and validation for wider adoption.

Purpose: To validated previously existing algorithm for SR estimation and introduce improvements that make it robust to patient positioning, CT protocol, site, and artifacts.

Method: A reference algorithm based on the previous gold standard was recreated and modified to improve robustness. The algorithms were tested on three different datasets: (1) a cylindrical ACR CT QC phantom scanned using a Siemens …

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 …

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 …

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 …

Fast Generation Of Lung Sbrt Plans With A Knowledge-Based Planning Model On Ring-Mounted Halcyon Linac, Justin Visak, Aaron Webster, Mark E. Bernard, Mahesh R. Kudrimoti, Marcus E. Randall, Ronald C. Mcgarry, Damodar Pokhrel

Radiation Medicine Faculty Publications

PURPOSE: To demonstrate fast treatment planning feasibility of stereotactic body radiation therapy (SBRT) for centrally located lung tumors on Halcyon Linac via a previously validated knowledge-based planning (KBP) model to support offline adaptive radiotherapy.

MATERIALS/METHODS: Twenty previously treated non-coplanar volumetric-modulated arc therapy (VMAT) lung SBRT plans (c-Truebeam) on SBRT-dedicated C-arm Truebeam Linac were selected. Patients received 50 Gy in five fractions. c-Truebeam plans were re-optimized for Halcyon manually (m-Halcyon) and with KBP model (k-Halcyon). Both m-Halcyon and k-Halcyon plans were normalized for identical or better target coverage than clinical c-Truebeam …

Predicting The Effect Of Indirect Cell Kill In The Treatment Of Multiple Brain Metastases Via Single-Isocenter/Multitarget Volumetric Modulated Arc Therapy Stereotactic Radiosurgery, Allison N. Palmiero, Denise Fabian, Marcus E. Randall, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

PURPOSE: Due to spatial uncertainty, patient setup errors are of major concern for radiosurgery of multiple brain metastases (m-bm) when using single-isocenter/multitarget (SIMT) volumetric modulated arc therapy (VMAT) techniques. However, recent clinical outcome studies show high rates of tumor local control for SIMT-VMAT. In addition to direct cell kill (DCK), another possible explanation includes the effects of indirect cell kill (ICK) via devascularization for a single dose of 15 Gy or more and by inducing a radiation immune intratumor response. This study quantifies the role of indirect cell death in dosimetric errors as a function of spatial patient setup uncertainty …

Computer Automation For Physics Chart Check Should Be Adopted In Clinic To Replace Manual Chart Checking For Radiotherapy, Edward L. Clouser, Quan Chen, Yi Rong

Radiation Medicine Faculty Publications

No abstract provided.

An Analytical Expression For R50% Dependent On Ptv Surface Area And Volume: A Cranial Srs Comparison, Dharmin D. Desai, Ellis Lee Johnson, Ivan L. Cordrey

Radiation Medicine Faculty Publications

The intermediate dose spill for a stereotactic radiosurgery (SRS) plan can be quantified with the metric R50%, defined as the 50% isodose cloud volume (V_IDC50%) divided by the volume of the planning target volume (PTV). By coupling sound physical principles with the basic definition of R50%, we derive an analytical expression for R50% for a spherical PTV. Our analytical expression depends on three quantities: the surface area of PTV (SA_PTV), the volume of PTV (V_PTV), and the distance of dose drop-off to 50% (Δr). The value of ∆r was obtained from a simple set …

Targeting Accuracy Considerations For Simultaneous Tumor Treating Fields Antimitotic Therapy During Robotic Hypofractionated Radiation Therapy., Sharmi Biswas, Irina Kapitanova, Sabrina Divekar, Jimm Grimm, Ian J Butterwick, Daniel Garren, Lawrence R Kleinberg, Kristin J Redmond, Michel Lacroix, Anand Mahadevan, Kenneth M Forster

College of Health Professions Faculty Papers

Purpose: Tumor treating fields (TTFields) is a novel antimitotic treatment that was first proven effective for glioblastoma multiforme, now with trials for several extracranial indications underway. Several studies focused on concurrent TTFields therapy with radiation in the same time period, but were not given simultaneously. This study evaluates the targeting accuracy of simultaneous radiation therapy while TTFields arrays are in place and powered on, ensuring that radiation does not interfere with TTFields and TTFields does not interfere with radiation. This is one of several options to enable TTFields to begin several weeks sooner, and opens potential for synergistic effects of …

A Novel And Clinically Useful Dynamic Conformal Arc (Dca)-Based Vmat Planning Technique For Lung Sbrt, Damodar Pokhrel, Justin Visak, Lana Sanford

Radiation Medicine Faculty Publications

PURPOSE: Volumetric modulated arc therapy (VMAT) is gaining popularity for stereotactic treatment of lung lesions for medically inoperable patients. Due to multiple beamlets in delivery of highly modulated VMAT plans, there are dose delivery uncertainties associated with small-field dosimetry error and interplay effects with small lesions. We describe and compare a clinically useful dynamic conformal arc (DCA)-based VMAT (d-VMAT) technique for lung SBRT using flattening filter free (FFF) beams to minimize these effects.

MATERIALS AND METHODS: Ten solitary early-stage I-II non-small-cell lung cancer (NSCLC) patients were treated with a single dose of 30 Gy using 3-6 non-coplanar VMAT arcs (clinical …

Outlier Identification In Radiation Therapy Knowledge-Based Planning: A Study Of Pelvic Cases., Yang Sheng, Yaorong Ge, Lulin Yuan, Taoran Li, Fang-Fang Yin, Qingrong Jackie Wu

Department of Radiation Oncology Faculty Papers

PURPOSE: The purpose of this study was to apply statistical metrics to identify outliers and to investigate the impact of outliers on knowledge-based planning in radiation therapy of pelvic cases. We also aimed to develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers.

METHODS: Four groups (G1-G4) of pelvic plans were sampled in this study. These include the following three groups of clinical IMRT cases: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases) and G3 (37 prostate bed cases). Cases in G4 were planned in accordance with dynamic-arc radiation therapy procedure and include 10 …