Radiation Medicine Commons^™

Intralabyrinthine Mri Flair As A Predictive Marker For Hearing Loss In Vestibular Schwannomas In Neurofibromatosis Type 2, Robert L. Walker, Maxwell T. Laws, H. Jeffrey Kim, Christopher Zalewski, Ashok Asthagiri, Sruthi Ranganathan, Christina Hayes, John D. Heiss, John A. Butman, Prashant Chittiboina

Department of Radiation Oncology Faculty Papers

BACKGROUND AND OBJECTIVES: The onset of hearing loss due to vestibular schwannomas (VS) is inevitable but does not correlate with the size of the tumor. In patients with Neurofibromatosis Type 2 (NF2) and VS, we previously found an association between pre-contrast fluid-attenuated inversion recovery magnetic resonance imaging (FLAIR MRI) signal in the labyrinth and hearing loss. Here, we asked whether FLAIR hyper-intensity could serve as a predictive biomarker for hearing loss in NF2 patients with VS.

METHODS: A prospective longitudinal study (NCT00598351) of NF2 enrolled 168 subjects between 2008 and 2013. This study included 34 patients with small VS (total …

Aggressive Natural Killer Cell Leukemia: A Rare And Rapidly Progressive Hematologic Malignancy—Case Report And Literature Review, Jennifer Priessnitz, Ali Hariri, Yuliya Levkiavska, Kyle E. Bonner, Stephan I. Fisher, Joshua M. Sill

Department of Medicine Faculty Publications

Aggressive natural killer cell leukemia (ANKL) is a rare, fulminant hematologic malignancy characterized by neoplastic proliferation of mature NK cells. It is frequently associated with Epstein-Barr virus (EBV) infection, although EBV-negative cases have also been reported. While typically observed in young to middle-aged adults of East Asian descent, increasing recognition has led to identification of ANKL across diverse age groups and ethnicities. The disease is defined by a rapid clinical course and poor prognosis, underscoring the importance of early diagnosis and effective treatment. We present a case of a 71-year-old Caucasian male who developed fever, altered mental status, hepatosplenomegaly, pancytopenia, …

Investigating The Necessity Of Adaptive Radiotherapy In Tomotherapy Of Head And Neck Cancer Patients, Ali Chaparian, Mahsa Kianinia, Mahnaz Roayaei, Nadia Najafizade, Abolfazl Kanani, Leili Mahani, Hamidreza Nourzadeh

Department of Radiation Oncology Faculty Papers

BACKGROUND: Anatomical variations that occur during radiation therapy in head and neck cancer (HNC) patients can lead to significant dosimetric changes. The purpose of this study is to evaluate dosimetric and volume changes in key anatomical structures for different treatment sites in HNC patients, and to determine the percentage of patients who need adaptive radiotherapy (ART) per treatment site.

METHODS: A total of 1,740 megavoltage computed tomography (MVCT) images from 58 HNC patients treated with helical tomotherapy (HT) were exported to the PreciseART™ (Accuray) software. Volume changes in the planning target volume (PTV) and the organs at risk (OARs) in …

Desmoplastic Small Round Cell Tumor: An Update Of Current Management Practices, Ahmed Gawash, Alexa Simonetti, Brandon J Goodwin, Alissa Brotman O'Neill

Rowan-Virtua School of Osteopathic Medicine Departmental Research

BACKGROUND: Desmoplastic small round cell tumor (DSRCT) poses a diagnostic challenge, initiating with imaging techniques like ultrasound, CT, MRI, and PET scans, with CT being the primary choice for abdominal tumor visualization. Despite advances, the absence of a standardized staging system complicates the diagnostic process.

METHODS: A comprehensive literature review and search strategy, encompassing databases like PubMed and Cochrane was performed.

RESULTS: Systemic chemotherapy, notably the P6 regimen, is the cornerstone of DSRCT treatment, while other options, including CDK4/6 inhibitors, antibody-drug conjugates, and anlotinib present varying efficacy. A novel chemotherapeutic agent, ONC-201, exhibits promise, inhibiting tumor growth in preclinical models. …

3d-Printed Organ-Realistic Phantoms To Verify Quantitative Spect/Ct Accuracy For 177lu-Psma-617 Treatment Planning, Lydia J. Wilson, Sara Belko, Eric L. Gingold, Shuying Wan, Rachel Monane, Robert S. Pugliese, Firas Mourtada

Department of Radiation Oncology Faculty Papers

Background/Objectives: Accurate patient-specific dosimetry is essential for optimizing radiopharmaceutical therapy (RPT), but current tools lack validation in clinically realistic conditions. This work aimed to develop a workflow for designing and fabricating patient-derived, organ-realistic RPT phantoms and evaluate their feasibility for commissioning patient-specific RPT radioactivity quantification. Methods: We used computed tomographic (CT) and magnetic resonance (MR) imaging of representative patients, computer-aided design, and in-house 3D printing technology to design and fabricate anthropomorphic kidney and parotid phantoms with realistic organ spacing, anatomically correct orientation, and surrounding tissue heterogeneities. We evaluated the fabrication process via geometric verification (i.e., volume comparisons) and leak testing …

Evaluating Artifact-Free Four-Dimensional Computer Tomography With 16 Cm Detector Array, Inhwan Yeo, Wei Nie, Jiajin Fan, Mindy Joo, Michael Correa, Qianyi Xu

Department of Radiation Oncology Faculty Papers

PURPOSE: To evaluate a 16 cm-array axial four-dimensional computer tomography (4DCT) in comparison with a 4 cm-array 4DCT in the presence of respiration irregularity.

METHOD: Ten traces of lung tumor motion from CyberKnife treatments were imported to move the lung cylinder, containing a spherical target, of a phantom. Images were acquired for the lung that moved to each of the 10-positions/phases (1) step-wisely by nominal helical scan at each movement (ground truth), (2) continuously by 4D scan with the 16 cm array, and (3) the same with the 4 cm array, involving table shift. Irregularities, consisting of baseline shift and/or …

Patient-Reported Outcomes: Comparing Functional Avoidance And Standard Thoracic Radiation Therapy In Lung Cancer, Spencer Poiset, Joseph Lombardo, Edward Castillo, Richard Castillo, Bernard Jones, Moyed Miften, Brian Kavanagh, Adam Dicker, Cullen Boyle, Nicole Simone, Benjamin Movsas, Inga Grills, Chad Rusthoven, Yevgeniy Vinogradskiy, Lydia Wilson

Department of Radiation Oncology Faculty Papers

PURPOSE: Novel methods generate functional images using image processing techniques combined with four-dimensional computed tomography (4DCT) data (4DCT-ventilation). 4DCT-ventilation was implemented in a phase II, multicenter functional avoidance clinical trial. The work compares functional avoidance patient-reported outcomes (PROs) against historical standards.

METHODS: Patients with locally advanced lung cancer undergoing curative-intent chemoradiation were accrued. 4DCT-ventilation imaging was generated and functional avoidance treatment plans created reduced dose to functional lung. PRO instruments included Functional Assessment of Cancer Therapy Lung questionnaire and accompanying subscales (including the Trial Outcome Index [TOI]), EuroQol-5 Dimension (EQ-5D), and EQ-Visual Analog Scale (EQ-VAS). The average change from baseline …

Atypical Presentation Of Non-Small Cell Lung Carcinoma With Metastasis To Breast Tissue, Tylar P. Seckman, Diane Krutzler-Berry, Mohamed Ashal, Waqas Mahmud, Krista L. Denning, Logan M. Lawrence

Marshall Journal of Medicine

Malignant neoplasms of the lung commonly metastasize to lymph nodes, bone, brain, and liver via hematogenous and lymphatic routes. Much less commonly, metastasis occurs in the breast. Secondary metastatic disease of the breast is very rare, with a reported incidence ranging from 0.4-1.3%­­—with primary lung cancer being one of the most anomalous sources. This case details non-small cell lung cancer metastasis to the breast with proven primary contralateral lung origination. This atypical finding prompts medical professionals to consider these malignant cells' immunologic, histologic, and pathologic makeup to understand further and treat the neoplasm.

Deep Learning-Based Auto-Segmentation For Liver Yttrium-90 Selective Internal Radiation Therapy, Jun Li, Wookjin Choi, Rani Anne

Department of Radiation Oncology Faculty Papers

The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segmentation of the liver was tested in CT images of SIRT patients. DL auto-segmented liver contours were evaluated against physician manually-delineated contours. Dice similarity coefficient (DSC) and mean distance to agreement (MDA) were calculated. The DL-model-generated contours were compared with the contours generated using an Atlas-based method. Ratio of volume (RV, the ratio of DL-model auto-segmented liver volume to manually-delineated liver volume), and ratio of activity (RA, …

Validation Of An Artificial Intelligence-Based Prognostic Biomarker In Patients With Oligometastatic Castration-Sensitive Prostate Cancer, Jarey H. Wang, Matthew P. Deek, Adrianna A. Mendes, Yang Song, Amol Shetty, Soha Bazyar, Kim Van Der Eecken, Emmalyn Chen, Timothy N. Showalter, Trevor J. Royce, Tamara Todorovic, Huei-Chung Huang, Scott A. Houck, Rikiya Yamashita, Ana P. Kiess, Daniel Y. Song, Tamara Lotan, Theodore Deweese, Luigi Marchionni, Lei Ren, Amit Sawant, Nicole L. Simone, Alejandro Berlin, Cem Onal, Andre Esteva, Felix Y. Feng, Phuoc T. Tran, Philip Sutera, Piet Ost

Department of Radiation Oncology Faculty Papers

BACKGROUND: There is a need for clinically actionable prognostic and predictive tools to guide the management of oligometastatic castration-sensitive prostate cancer (omCSPC).

METHODS: This is a multicenter retrospective study to assess the prognostic and predictive performance of a multimodal artificial intelligence biomarker (MMAI; the ArteraAI Prostate Test) in men with omCSPC (n = 222). The cohort also included 51 patients from the STOMP and ORIOLE phase 2 clinical trials which randomized patients to observation versus metastasis-directed therapy (MDT). MMAI scores were computed from digitized histopathology slides and clinical variables. Overall survival (OS) and time to castration-resistant prostate cancer (TTCRPC) were …

A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo

Theses and Dissertations

Visualization of liver tumors on simulation CT scans is challenging even with contrast-enhancement, due to the sensitivity of the contrast enhancement to the timing of the CT acquisition. Image registration to magnetic resonance imaging (MRI) can be helpful for delineation, but differences in patient position, liver shape and volume, and the lack of anatomical landmarks between the two image sets makes the task difficult. This study develops a U-Net based neural network for automated liver and tumor segmentation for purposes of radiotherapy treatment planning. Non-contrast simulation based abdominal CT axial scans of 52 patients with primary liver tumors were utilized. …

Scintillation Event Localization In Novel Hemi-Ellipsoid Detector For Spect, Hanif R. Soysal

LSU Master's Theses

A high sensitivity Cardiac SPECT system using hemi-ellipsoid crystals with pinhole collimation was previously proposed by Dey et al. To investigate detector resolution for this design, the scintillation light spread on a monolithic hemi-ellipsoidal CsI crystal was simulated using Geant4 Monte Carlo. The expected distribution of scintillation light on the outer surface of the crystal from photoelectric absorption events was obtained from the simulations for selected points inside the crystal. Two sets of simulations were performed. For the first set, a look-up table (LUT) of 12 points was created and each point mapped to its expected light distribution—four points at …