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759 full-text articles. Page 7 of 35.

Differentiation Stage Predicts Radiosensitivity In Mesenchymal-Like Pancreatic Cancer, Tingshi Su, Xinjian Yu, Mojtaba Hoseini-Ghahfarokhi, David B Flint, Scott J Bright, Joana I D S Antunes, David K J Martinus, Mandira Manandhar, Mariam Ben Kacem, Poliana C Marinello, Eurico J G Pereira, Hua-Sheng Chiu, Uwe Titt, David R Grosshans, Jan Schuemann, Henning Willers, Harald Paganetti, Pavel Sumazin, Gabriel O Sawakuchi 2025 The Texas Medical Center Library

Differentiation Stage Predicts Radiosensitivity In Mesenchymal-Like Pancreatic Cancer, Tingshi Su, Xinjian Yu, Mojtaba Hoseini-Ghahfarokhi, David B Flint, Scott J Bright, Joana I D S Antunes, David K J Martinus, Mandira Manandhar, Mariam Ben Kacem, Poliana C Marinello, Eurico J G Pereira, Hua-Sheng Chiu, Uwe Titt, David R Grosshans, Jan Schuemann, Henning Willers, Harald Paganetti, Pavel Sumazin, Gabriel O Sawakuchi

Faculty, Staff and Student Publications

Purpose: To derive a genomic classifier to predict radiosensitivity of pancreatic cancer cell lines and patients with pancreatic cancer to allow genomic-guided radiation therapy.

Methods and materials: We collected a comprehensive data set of full clonogenic cell survival curves of 45 pancreatic cancer cell lines irradiated with clinical photon and proton beams. We derived classifiers based on data from human embryonic and fetal pancreas single-cell RNA-sequencing to distinguish between epithelial and mesenchymal cells and to predict pancreas cell-line differentiation stage. Independent testing was done with an embryonic mouse pancreas single-cell RNA-sequencing data set. We then used bulk RNA-seq profiles from …


Cost-Effectiveness Of Personalized Policies For Implementing Organ-At-Risk Sparing Adaptive Radiation Therapy In Head And Neck Cancer, Seyedmohammadhossein Hosseinian, Daniel Suarez-Aguirre, Cem Dede, Raul Garcia, Lucas McCullum, Mehdi Hemmati, Aysenur Karagoz, Abdallah S R Mohamed, Stephen Y Lai, Katherine A Hutcheson, Amy C Moreno, Kristy K Brock, Fatemeh Nosrat, Clifton D Fuller, Andrew J Schaefer 2025 The Texas Medical Center Library

Cost-Effectiveness Of Personalized Policies For Implementing Organ-At-Risk Sparing Adaptive Radiation Therapy In Head And Neck Cancer, Seyedmohammadhossein Hosseinian, Daniel Suarez-Aguirre, Cem Dede, Raul Garcia, Lucas Mccullum, Mehdi Hemmati, Aysenur Karagoz, Abdallah S R Mohamed, Stephen Y Lai, Katherine A Hutcheson, Amy C Moreno, Kristy K Brock, Fatemeh Nosrat, Clifton D Fuller, Andrew J Schaefer

Faculty, Staff and Student Publications

Background and purpose: The principle of adaptive radiation therapy (ART) is to adjust radiation plans in response to anatomical changes during treatment. The purpose of this study was to develop a decision-making model for implementation of personalized ART that balances the costs and clinical benefits of radiation plan adaptations in head and neck cancer (HNC).

Materials and methods: Using retrospective imaging data from 52 HNC patients, a Markov decision process (MDP) model was developed to determine optimal timing for plan adaptations based on the difference in normal tissue complication probability (ΔNTCP) between planned and delivered doses to organs-at-risk. To capture …


Enhancing Lymphoma Staging: Unveiling The Potential And Challenges Of Whole-Body Magnetic Resonance Imaging, Mohadese Ahmadzade, Mohammad Ghasemi-Rad 2025 The Texas Medical Center Library

Enhancing Lymphoma Staging: Unveiling The Potential And Challenges Of Whole-Body Magnetic Resonance Imaging, Mohadese Ahmadzade, Mohammad Ghasemi-Rad

Faculty, Staff and Students Publications

In this editorial, we comment on the article by Lambert et al, published in the recent issue of the World Journal of Radiology. The focus of the editorial is to explore the advancements in whole-body magnetic resonance imaging (WB-MRI) technology, its current clinical applications, and the challenges that must be addressed to fully realize its potential in oncological imaging. WB-MRI has emerged as a pivotal tool in oncological imaging, offering comprehensive disease assessment without ionizing radiation. Its applications span the detection of bone metastases, evaluation of hematologic malignancies, and staging of a wide range of cancers, including lymphoma, …


Bridging Gaps In Cancer Care: Utilizing Large Language Models For Accessible Dietary Recommendations, Julia A. Logan, Sriya Sadhu, Cameo Hazlewood, Melissa Denton, Sara Burke, Christina A. Simone-Soule, Caroline Black, Corey Ciaverelli, Jacqueline Stulb, Hamidreza Nourzadeh, Yevgeniy Vinogradskiy, Amy Leader, Adam Dicker, Wookjin Choi, Nicole L Simone 2025 Thomas Jefferson University

Bridging Gaps In Cancer Care: Utilizing Large Language Models For Accessible Dietary Recommendations, Julia A. Logan, Sriya Sadhu, Cameo Hazlewood, Melissa Denton, Sara Burke, Christina A. Simone-Soule, Caroline Black, Corey Ciaverelli, Jacqueline Stulb, Hamidreza Nourzadeh, Yevgeniy Vinogradskiy, Amy Leader, Adam Dicker, Wookjin Choi, Nicole L Simone

Department of Radiation Oncology Faculty Papers

Background/Objectives: Weight management is directly linked to cancer recurrence and survival, but unfortunately, nutritional oncology counseling is not typically covered by insurance, creating a disparity for patients without nutritional education and food access. Novel ways of imparting personalized nutrition advice are needed to address this issue. Large language models (LLMs) offer a promising path toward tailoring dietary advice to individual patients. This study aimed to assess the capacity of LLMs to offer personalized dietary advice to patients with breast cancer. Methods: Thirty-one prompt templates were designed to evaluate dietary recommendations generated by ChatGPT and Gemini with variations within …


Quality Control Of Clinical Protocols Of Ct Using The Accreditation Phantom, Walaiporn Suksancharoen, Apawadee Chakrapong, Sakultala Ruenjit, Anchali Krisanachinda 2025 King Chulalongkorn Memorial Hospital

Quality Control Of Clinical Protocols Of Ct Using The Accreditation Phantom, Walaiporn Suksancharoen, Apawadee Chakrapong, Sakultala Ruenjit, Anchali Krisanachinda

Chulalongkorn Medical Journal

Background: The daily quality control of the Computed Tomography system consists of the measurement of the accuracy of CT Number and the artifact evaluation. The annual quality control includes the clinical protocol review. The CT radiologist is responsible for ensuring that all Quality Assurance (QA) requirements are met. The clinical team reviews and manages the CT protocol to deliver the appropriate radiation dose to the patient for each examination.

Objectives: To verify CT Number Accuracy, to review clinical protocols and to verify that the low-contrast performance of clinical protocols is adequate for diagnosis.

Methods: American College of Radiology (ACR) CT …


Chemoradiation Treatment With Or Without Concurrent Tumor-Treating Fields (Ttfields) Therapy In Newly Diagnosed Glioblastoma (Gbm) Patients In China, Liping Liang, Lingchao Chen, Chunxia Ni, Wenyin Shi, Zhirui Zhou, Shu Chen, Wenjia Zhu, Jiabing Liu, Xianxin Qiu, Wanzun Lin, Junyan Zhang, Zhiyong Qin, Yang Wang 2025 Thomas Jefferson University

Chemoradiation Treatment With Or Without Concurrent Tumor-Treating Fields (Ttfields) Therapy In Newly Diagnosed Glioblastoma (Gbm) Patients In China, Liping Liang, Lingchao Chen, Chunxia Ni, Wenyin Shi, Zhirui Zhou, Shu Chen, Wenjia Zhu, Jiabing Liu, Xianxin Qiu, Wanzun Lin, Junyan Zhang, Zhiyong Qin, Yang Wang

Department of Radiation Oncology Faculty Papers

BACKGROUND: Tumor-treating fields (TTFields) therapy and radiotherapy may have synergistic anti-glioma effect based on preclinical studies. The combination of chemoradiation therapy (CRT) with TTFields therapy has noticeably attracted clinicians' attention. This study aimed to provide insights into the clinical outcomes of patients with newly diagnosed glioblastoma who received either concurrent CRT and TTFields therapy or adjuvant TTFields therapy following CRT. The findings were based on a cohort of patients who were treated at Huashan Hospital (Shanghai, China).

METHODS: This retrospective study analyzed ndGBM patients' clinical outcomes who were treated at Huashan Hospital and received TTFields therapy. Patients were categorized into …


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 2025 The Texas Medical Center Library

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 …


Triswinunetr Lobe Segmentation Model For Computing Dir-Free Ct-Ventilation, Gabriela Roque Oliveira Nomura, Aarom T. Luong, Ananya Prakash, Annabelle Alemand, Tanish Bhowmick, Alisa Ali, Jaimie Ren, Basil Rehani, Girish Nair, Richard Castillo, Yevgeniy Vinogradskiy, Edward Castillo 2025 Thomas Jefferson University

Triswinunetr Lobe Segmentation Model For Computing Dir-Free Ct-Ventilation, Gabriela Roque Oliveira Nomura, Aarom T. Luong, Ananya Prakash, Annabelle Alemand, Tanish Bhowmick, Alisa Ali, Jaimie Ren, Basil Rehani, Girish Nair, Richard Castillo, Yevgeniy Vinogradskiy, Edward Castillo

Department of Radiation Oncology Faculty Papers

Purpose: Functional radiotherapy avoids the delivery of high-radiation dosages to high-ventilated lung areas. Methods to determine CT-ventilation imaging (CTVI) typically rely on deformable image registration (DIR) to calculate volume changes within inhale/exhale CT image pairs. Since DIR is a non-trivial task that can bias CTVI, we hypothesize that lung volume changes needed to calculate CTVI can be computed from AI-driven lobe segmentations in inhale/exhale phases, without DIR. We utilize a novel lobe segmentation pipeline (TriSwinUNETR), and the resulting inhale/exhale lobe volumes are used to calculate CTVI. Methods: Our pipeline involves three SwinUNETR networks, each trained on 6,501 CT image pairs …


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 2025 Thomas Jefferson University

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 2025 Marshall University Joan C. Edwards School of Medicine

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 2025 Thomas Jefferson University

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, …


Developing Real-Time, Online Beam Control Of Uhdr Irradiators To Facilitate Flash Translational Investigations, Austin M. Sloop 2025 Dartmouth College

Developing Real-Time, Online Beam Control Of Uhdr Irradiators To Facilitate Flash Translational Investigations, Austin M. Sloop

Dartmouth College Ph.D Dissertations

The field of radiation oncology seeks novel techniques to increase the therapeutic ratio to treat malignancies while minimizing damage and toxicities in healthy tissues. While it was observed that delivering therapeutic doses at high dose rate could elicit lower biological effects over a half-century ago, the field of ultra-high dose rate (UHDR) radiation therapy (colloquially known as FLASH RT) has seen a resurgence in recent years due to an alignment of accelerator capability, dosimetric advances, and improved biotechnological techniques. This has opened the door to studying potential underlying mechanisms such that we may leverage the effects of FLASH tissue sparing …


Reduced Set-Shifting Processing Speed In Male Rats Following Low Dose (10 Cgy) Proton Exposure, Hui Ho Vanessa Chang, Gyutae Kim, Kyu-Sung Kim, Richard A. Britten 2025 Inha University

Reduced Set-Shifting Processing Speed In Male Rats Following Low Dose (10 Cgy) Proton Exposure, Hui Ho Vanessa Chang, Gyutae Kim, Kyu-Sung Kim, Richard A. Britten

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

Space radiation (SR) exposure poses significant biomedical risks, including effects on the central nervous system (CNS). These risks are particularly relevant to cognitive function during long-duration space missions. One critical cognitive skill is decision-making, which requires attentional set-shifting (ATSET)—the ability to quickly assess problems, evaluate options, and select the best actions. Previous studies have shown that exposure to However, the impact of low LET (< 1 keV/μm) protons, which significantly contribute to the total radiation flux astronauts encounter within spacecraft, on ATSET performance is unknown. To address this gap, we evaluated the effects of cranial irradiation with 10 cGy of 100 MeV/n protons (LET = 0.732 keV/μm) on ATSET performance in male Sprague-Dawley rats. We also investigated whether concurrent exposure to variable gravity (hypergravity step-up, step down, purported to have the same effect as exposure to microgravity (another major spaceflight stressor) exacerbated SR-induced cognitive deficits. Our findings indicate that proton exposure alone significantly impaired ATSET performance, as evidenced by decreased processing speed while performing compound discrimination reversal and extra-dimensional shifting. Notably, no additive or synergistic effects were observed when hypergravity was combined with proton exposure. The impact that low-dose proton exposure has on CNS functionality, particularly in reducing processing speed during complex tasks, warrant further investigation. If similar cognitive deficits were to occur in astronauts exposed to galactic cosmic rays, mission success and safety could be significantly compromised.


A Knowledge-Based Planning Model To Identify Fraction-Reduction Opportunities In Brain Stereotactic Radiotherapy, Shane McCarthy, William St. Clair, Damodar Pokhrel 2025 University of Kentucky

A Knowledge-Based Planning Model To Identify Fraction-Reduction Opportunities In Brain Stereotactic Radiotherapy, Shane Mccarthy, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

Objective: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the number of fractions while achieving acceptable organs-at-risk (OAR) doses with improved target biological effective dose (BED) to brain lesions. Methods: Thirty-nine high-quality clinical three-fraction HyperArc brain SRT plans (24–27 Gy) were used to train the HARP model, with a separate 10 plans used to validate its effectiveness. Fifty-eight five-fraction HyperArc brain SRT plans (30–40 Gy) attempted to be retrospectively replanned for three fractions scheme using the HARP …


An Investigation Into The Feasibility And Efficacy Of Stereotactic Radiosurgery For 1–3 Cm Single Brain Lesions On The Ring-Mounted Halcyon Linac, Kristin J. Hazelwood, Shane McCarthy, Josh Misa, David Castelvetere, William St. Clair, Damodar Pokhrel 2025 University of Kentucky

An Investigation Into The Feasibility And Efficacy Of Stereotactic Radiosurgery For 1–3 Cm Single Brain Lesions On The Ring-Mounted Halcyon Linac, Kristin J. Hazelwood, Shane Mccarthy, Josh Misa, David Castelvetere, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

Purpose: An evaluation of the accuracy, safety, and efficiency of the Halcyon ring delivery system (RDS) for stereotactic radiosurgery (SRS) treatment to relatively small (1–3 cm) brain lesions.

Methods: After completing the extensive in-house quality assurance checks including Winston–Lutz test and independent dose verification via MD Anderson IROC SRS head phantom irradiation on Halcyon, fifteen brain SRS patients previously treated with a single dose of 20 Gy on TrueBeam (6MV-FFF) with HyperArc geometry were retrospectively replanned on Halcyon (6MV-FFF). Plan quality metrics including conformity index (CI), gradient index (GI), gradient distance (GD), PTV coverage, gross tumor volume (GTV) dose, heterogeneity …


A Predictive Quality Assurance Model For Patient-Specific Gamma Passing Rate Of Hyperarc-Based Stereotactic Radiotherapy And Radiosurgery Of Brain Metastases, Shane McCarthy, Brent Harrison, Damodar Pokhrel 2025 University of Kentucky

A Predictive Quality Assurance Model For Patient-Specific Gamma Passing Rate Of Hyperarc-Based Stereotactic Radiotherapy And Radiosurgery Of Brain Metastases, Shane Mccarthy, Brent Harrison, Damodar Pokhrel

Radiation Medicine Faculty Publications

Objective: Measurement-based patient specific quality assurance (PSQA) is an increasingly debated topic among medical physicists. Developments like online adaptive radiotherapy and same-day stereotactic treatments limit the time to do measurement-based PSQA. Herein, we develop a predictive machine learning model to supplement PSQA by predicting the gamma passing rate (GPR) per stereotactic arc. This streamlines PSQA, providing planners the insight to replan potentially sub-optimal plans, to mitigate machine time inefficiencies.

Methods: 122 patients that had previously received HyperArc stereotactic radiosurgery/radiotherapy on a TrueBeam LINAC (Millenium 120 MLCs, 6MV-FFF) were used to generate a long short-term memory (LSTM) recurrent neural network to …


Automated Hippocampal Sparing Whole Brain Radiotherapy With Simultaneous Integrated Boost For Multiple Brain Metastases: Halcyon, Hyperarc On Truebeam, And Coplanar Truebeam, Shane McCarthy, Ryan Clark, Anthony Magliari, William St. Clair, Damodar Pokhrel 2025 University of Kentucky

Automated Hippocampal Sparing Whole Brain Radiotherapy With Simultaneous Integrated Boost For Multiple Brain Metastases: Halcyon, Hyperarc On Truebeam, And Coplanar Truebeam, Shane Mccarthy, Ryan Clark, Anthony Magliari, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

Purpose: To demonstrate the ease and feasibility that hippocampal sparing whole brain (WB) simultaneous integrated boost (HSWB-SIB) plans can be generated using knowledge-based planning and Eclipse Scripting Application Programming Interface (ESAPI) for three different modalities, HyperArc on TrueBeam (TB-HA), a coplanar beam arrangement on TrueBeam (TB-Co), and the ring-mounted Halcyon LINAC (Hal).

Methods: Twelve patients with 2–14 brain metastases were retrospectively replanned for HSWB-SIB using a published HSWB RapidPlan model with modifications for the automated addition of SIB to metastases. Prescribed dose was 30 Gy to the WB planning target volume (PTV) and 50 Gy to the metastases in 10 …


Feasibility Of Treatment Planning With Hyperarc Stereotactic Radiosurgery Methods For Ocular Tumors, Chase Cochran, Shane McCarthy, William St. Clair, Damodar Pokhrel 2025 University of Kentucky

Feasibility Of Treatment Planning With Hyperarc Stereotactic Radiosurgery Methods For Ocular Tumors, Chase Cochran, Shane Mccarthy, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

Purpose/objectives

Currently, ocular disease is primarily managed with COMS plaque brachytherapy. Various stereotactic radiosurgery (SRS) platforms have also been employed, yet widespread access remains a challenge. Herein, we demonstrate the feasibility of using the HyperArc SRS system to provide an additional platform for the treatment of ocular malignancies.

Materials/methods

Twenty previously treated COMS patients with ocular melanoma were selected for a retrospective HyperArc SRS planning study. The average gross tumor volume (GTV) derived from MRI was 1.19 ± 0.60 cc. Planning target volumes (PTV) were generated from a 2 mm expansion of the GTVs. HyperArc plans were created for a …


Machine Learning Models For Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages And Treatments Using The Surveillance, Epidemiology, And End Results (Seer) Database, Aditya Chakraborty, Mohan D. Pant 2025 Macon & Joan Brock Virginia Health Sciences at Old Dominion University

Machine Learning Models For Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages And Treatments Using The Surveillance, Epidemiology, And End Results (Seer) Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pancreatic cancer is among the most lethal malignancies, with poor prognosis and limited survival despite treatment advances. Accurate survival modeling is critical for prognostication and clinical decision-making. This study had three primary aims: (1) to determine the best-fitting survival distribution among patients diagnosed and deceased from pancreatic cancer across stages and treatment types; (2) to construct and compare predictive risk classification models; and (3) to evaluate survival probabilities using parametric, semi-parametric, non-parametric, machine learning, and deep learning methods for Stage IV patients receiving both chemotherapy and radiation. Methods: Using data from the SEER database, parametric models (Generalized Extreme Value, …


Demonstration Of An Enhanced Dosing Pattern For Debulking Large And Bulky Unresectable Tumors Via Differential Hole-Size Spatially Fractionated Radiotherapy, Joshua Misa, William St. Clair, Damodar Pokhrel 2025 University of Kentucky

Demonstration Of An Enhanced Dosing Pattern For Debulking Large And Bulky Unresectable Tumors Via Differential Hole-Size Spatially Fractionated Radiotherapy, Joshua Misa, William St. Clair, Damodar Pokhrel

Radiation Medicine Faculty Publications

Purpose/objective

We propose a novel lattice deployment for spatially fractionated radiotherapy (SFRT) treatments. In this approach, a larger diameter high-dose sphere is centrally placed in the bulky tumor mass and surrounded by smaller diameter high-dose spheres.

Materials/methods

Thirty SFRT patients (10 head and neck [HN], 10 abdominal/pelvis, and 10 chest/lung cases) treated with an MLC-based crossfire method were retrospectively analyzed. Eleven differential hole-size lattice patterns were benchmarked against the clinically delivered SFRT plans (1 cm diameter cylinders, 2 cm spacing) and the standard uniform lattice pattern (1.5 cm diameter spheres, 3 cm spacing). These patterns varied in core diameter (C: …


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