Kyle Jon Lafata

Journal article Kidney360 · May 26, 2026 BACKGROUND: Slope of estimated glomerular filtration rate (eGFR) is an important measurement of kidney disease progression and clinical outcome in glomerular disease. However, the length of time required to reliably estimate long-term eGFR slopes is unknow ... Full text Link to item Cite

Authors' Reply: Computational Lymphocyte Topology: A Roadmap to Mechanism and Clinical Translation?

Journal article J Am Soc Nephrol · April 1, 2026 Full text Link to item Cite

Computational Characterization of Lymphocyte Topology on Whole Slide Images of Glomerular Diseases.

Journal article J Am Soc Nephrol · March 1, 2026 BACKGROUND: The distribution of inflammation in the kidney and its clinical relevance is understudied. This study aimed to computationally quantify lymphocyte topology and test its prediction of disease progression. METHODS: NEPhrotic syndrome sTUdy NEtwor ... Full text Link to item Cite

Demographic distribution matching between real-world and virtual phantom population.

Journal article Med Phys · March 2026 BACKGROUND: The adoption of virtual imaging trials (VITs) is rapidly expanding, offering a cost-effective and ethically viable alternative to large-scale clinical trials for imaging system evaluation. However, differences in demographic composition between ... Full text Open Access Link to item Cite

Evaluation of unified harmonization of CT images across multiple tasks: A step towards AI generalizability.

Journal article Med Phys · November 2025 BACKGROUND: In medical imaging, harmonization is pivotal for mitigating variability stemming from diverse imaging devices and protocols. Virtual imaging trials (VITs) can provide a way to simulate diverse imaging conditions in silico and thus provide a uni ... Full text Link to item Cite

Investigating the Role of Area Deprivation Index in Observed Differences in CT-Based Body Composition by Race.

Journal article J Am Coll Radiol · October 2025 OBJECTIVES: Differences in CT-based body composition (BC) have been observed by race. We sought to investigate whether indices reporting census block group-level disadvantage, Area Deprivation Index (ADI) and Social Vulnerability Index (SVI), age, gender, ... Full text Link to item Cite

Development and application of a novel tumor habitat analysis technique based on dynamical modeling.

Journal article Med Phys · September 2025 BACKGROUND: Oropharyngeal cancer (OPC) exhibits varying responses to chemoradiation therapy, making treatment outcome prediction challenging. Traditional imaging-based methods often fail to capture the spatial heterogeneity within tumors, which influences ... Full text Link to item Cite

Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis.

Journal article Kidney Int · August 2025 BACKGROUND: Visual scoring of tubular damage has limitations in capturing the full spectrum of structural changes and prognostic potential. Here, we investigated if computationally quantified tubular features can enhance prognostication and reveal spatial ... Full text Link to item Cite

The Duke Lung Cancer Screening (DLCS) Dataset: A Reference Dataset of Annotated Low-Dose Screening Thoracic CT.

Journal article Radiol Artif Intell · July 2025 The Duke Lung Cancer Screening (DLCS) dataset is a large collection of lung cancer screening low-dose CT scans for lung nodule classification with annotations performed in a semiautomated manner, requiring substantially reduced radiologist effort. ... Full text Link to item Cite

XCAT 3.0: A comprehensive library of personalized digital twins derived from CT scans.

Journal article Med Image Anal · July 2025 Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and physiology, play a central role in VITs. However, the current libraries of c ... Full text Open Access Link to item Cite

Virtual Lung Screening Trial (VLST): An In Silico Study Inspired by the National Lung Screening Trial for Lung Cancer Detection.

Journal article ArXiv · April 4, 2025 Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a solution by simulating clinical trial components in a controlled, risk-free en ... Link to item Cite

Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.

Journal article Artif Intell Med · February 2025 In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predictions ... Full text Link to item Cite

Clinical Relevance of Computational Pathology Analysis of Interplay between Kidney Microvasculature and Interstitial Microenvironment.

Journal article Clin J Am Soc Nephrol · February 1, 2025 KEY POINTS: There is a modulatory effect between peritubular capillaries (PTCs) and areas of interstitial fibrosis and tubular atrophy (IFTA). The spatial architecture of non-IFTA PTCs on the cortex is significantly associated with glomerular disease progr ... Full text Link to item Cite

The Role of Harmonization: A Systematic Analysis of Various Task-based Scenarios.

Journal article Proc SPIE Int Soc Opt Eng · February 2025 In medical imaging, harmonization plays a crucial role in reducing variability arising from diverse imaging devices and protocols. Patient images obtained under different computed tomography (CT) scan conditions may show varying performance when analyzed u ... Full text Link to item Cite

Long-term, automated stool monitoring using a novel smart toilet: A feasibility study.

Journal article Neurogastroenterol Motil · January 2025 BACKGROUND: Patients' report of bowel movement consistency is unreliable. We demonstrate the feasibility of long-term automated stool image data collection using a novel Smart Toilet and evaluate a deterministic computer-vision analytic approach to assess ... Full text Link to item Cite

Uncertainty quantification in multi-parametric MRI-based meningioma radiotherapy target segmentation.

Journal article Front Oncol · 2025 PURPOSE: This work investigates the use of a spherical projection-based U-Net (SPU-Net) segmentation model to improve meningioma segmentation performance and allow for uncertainty quantification. METHODS: A total of 76 supratentorial meningioma patients tr ... Full text Link to item Cite

Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction.

Journal article Int J Radiat Oncol Biol Phys · October 1, 2024 PURPOSE: To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). METHODS AND MATERIALS: A total of 114 brain metastases (BMs) from 82 patients were evalu ... Full text Link to item Cite

Characterization of arteriosclerosis based on computer-aided measurements of intra-arterial thickness.

Journal article J Med Imaging (Bellingham) · September 2024 PURPOSE: Our purpose is to develop a computer vision approach to quantify intra-arterial thickness on digital pathology images of kidney biopsies as a computational biomarker of arteriosclerosis. APPROACH: The severity of the arteriosclerosis was scored (0 ... Full text Link to item Cite

Advancing blood glucose prediction with neural architecture search and deep reinforcement learning for type 1 diabetics

Journal article Biocybernetics and Biomedical Engineering · July 1, 2024 For individuals with Type-1 diabetes mellitus, accurate prediction of future blood glucose values is crucial to aid its regulation with insulin administration, tailored to the individual's specific needs. The authors propose a novel approach for the integr ... Full text Cite

Lung Cancer Screening in Clinical Practice: A 5-Year Review of Frequency and Predictors of Lung Cancer in the Screened Population.

Journal article J Am Coll Radiol · May 2024 PURPOSE: The aims of this study were to evaluate (1) frequency, type, and lung cancer stage in a clinical lung cancer screening (LCS) population and (2) the association between patient characteristics and Lung CT Screening Reporting & Data System (Lung-RAD ... Full text Link to item Cite

Quantifying U-Net uncertainty in multi-parametric MRI-based glioma segmentation by spherical image projection.

Journal article Med Phys · March 2024 BACKGROUND: Uncertainty quantification in deep learning is an important research topic. For medical image segmentation, the uncertainty measurements are usually reported as the likelihood that each pixel belongs to the predicted segmentation region. In pot ... Full text Link to item Cite

Prognostic value of different discretization parameters in 18fluorodeoxyglucose positron emission tomography radiomics of oropharyngeal squamous cell carcinoma.

Journal article J Med Imaging (Bellingham) · March 2024 PURPOSE: We aim to interrogate the role of positron emission tomography (PET) image discretization parameters on the prognostic value of radiomic features in patients with oropharyngeal cancer. APPROACH: A prospective clinical trial (NCT01908504) enrolled ... Full text Link to item Cite

Artificial intelligence across oncology specialties: current applications and emerging tools.

Journal article BMJ Oncol · 2024 Oncology is becoming increasingly personalised through advancements in precision in diagnostics and therapeutics, with more and more data available on both ends to create individualised plans. The depth and breadth of data are outpacing our natural ability ... Full text Link to item Cite

Computational staining of CD3/CD20 positive lymphocytes in human tissues with experimental confirmation in a genetically engineered mouse model.

Journal article Front Immunol · 2024 INTRODUCTION: Immune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging bio ... Full text Link to item Cite

Digital staining in optical microscopy using deep learning - a review

Journal article Photonix · December 1, 2023 Until recently, conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics, fundamental research and biotechnology. Despite this role as gold-standard, staining pro ... Full text Cite

A neural ordinary differential equation model for visualizing deep neural network behaviors in multi-parametric MRI-based glioma segmentation.

Journal article Med Phys · August 2023 PURPOSE: To develop a neural ordinary differential equation (ODE) model for visualizing deep neural network behavior during multi-parametric MRI-based glioma segmentation as a method to enhance deep learning explainability. METHODS: By hypothesizing that d ... Full text Link to item Cite

A Faster Prostate MRI: Comparing a Novel Denoised, Single-Average T2 Sequence to the Conventional Multiaverage T2 Sequence Regarding Lesion Detection and PI-RADS Score Assessment.

Journal article J Magn Reson Imaging · August 2023 BACKGROUND: The T2 w sequence is a standard component of a prostate MRI examination; however, it is time-consuming, requiring multiple signal averages to achieve acceptable image quality. PURPOSE/HYPOTHESIS: To determine whether a denoised, single-average ... Full text Link to item Cite

Exploratory analysis of mesenteric-portal axis CT radiomic features for survival prediction of patients with pancreatic ductal adenocarcinoma.

Journal article Eur Radiol · August 2023 OBJECTIVE: To develop and evaluate task-based radiomic features extracted from the mesenteric-portal axis for prediction of survival and response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Consecutive patients ... Full text Link to item Cite

Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality.

Journal article Med Phys · June 2023 BACKGROUND: Due to intrinsic differences in data formatting, data structure, and underlying semantic information, the integration of imaging data with clinical data can be non-trivial. Optimal integration requires robust data fusion, that is, the process o ... Full text Link to item Cite

Systematic Analysis of Common Factors Impacting Deep Learning Model Generalizability in Liver Segmentation.

Journal article Radiol Artif Intell · May 2023 PURPOSE: To investigate the effect of training data type on generalizability of deep learning liver segmentation models. MATERIALS AND METHODS: This Health Insurance Portability and Accountability Act-compliant retrospective study included 860 MRI and CT a ... Full text Link to item Cite

Clinical Relevance of Computationally Derived Attributes of Peritubular Capillaries from Kidney Biopsies.

Journal article Kidney360 · May 1, 2023 KEY POINTS: Computational image analysis allows for the extraction of new information from whole-slide images with potential clinical relevance. Peritubular capillary (PTC) density is decreased in areas of interstitial fibrosis and tubular atrophy when mea ... Full text Link to item Cite

Comparing Survival Outcomes of Patients With LI-RADS-M Hepatocellular Carcinomas and Intrahepatic Cholangiocarcinomas.

Journal article J Magn Reson Imaging · January 2023 BACKGROUND: There is a sparsity of data evaluating outcomes of patients with Liver Imaging Reporting and Data System (LI-RADS) (LR)-M lesions. PURPOSE: To compare overall survival (OS) and progression free survival (PFS) between hepatocellular carcinoma (H ... Full text Link to item Cite

CT-derived body composition measurements as predictors for neoadjuvant treatment tolerance and survival in gastroesophageal adenocarcinoma.

Journal article Abdom Radiol (NY) · January 2023 PURPOSE: Treatment for gastroesophageal adenocarcinomas can result in significant morbidity and mortality. The purpose of this study is to supplement methods for choosing treatment strategy by assessing the relationship between CT-derived body composition, ... Full text Link to item Cite

Development of a multi-feature-combined model: proof-of-concept with application to local failure prediction of post-SBRT or surgery early-stage NSCLC patients.

Journal article Front Oncol · 2023 OBJECTIVE: To develop a Multi-Feature-Combined (MFC) model for proof-of-concept in predicting local failure (LR) in NSCLC patients after surgery or SBRT using pre-treatment CT images. This MFC model combines handcrafted radiomic features, deep radiomic fea ... Full text Link to item Cite

Quantification of lung function on CT images based on pulmonary radiomic filtering.

Journal article Med Phys · November 2022 PURPOSE: To develop a radiomics filtering technique for characterizing spatial-encoded regional pulmonary ventilation information on lung computed tomography (CT). METHODS: The lung volume was segmented on 46 CT images, and a 3D sliding window kernel was i ... Full text Link to item Cite

Prognostic Model for Intracranial Progression after Stereotactic Radiosurgery: A Multicenter Validation Study.

Journal article Cancers (Basel) · October 22, 2022 Stereotactic radiosurgery (SRS) is a standard of care for many patients with brain metastases. To optimize post-SRS surveillance, this study aimed to validate a previously published nomogram predicting post-SRS intracranial progression (IP). We identified ... Full text Link to item Cite

Radiomics: a primer on high-throughput image phenotyping.

Journal article Abdom Radiol (NY) · September 2022 Radiomics is a high-throughput approach to image phenotyping. It uses computer algorithms to extract and analyze a large number of quantitative features from radiological images. These radiomic features collectively describe unique patterns that can serve ... Full text Link to item Cite

Modifying LI-RADS on Gadoxetate Disodium-Enhanced MRI: A Secondary Analysis of a Prospective Observational Study.

Journal article J Magn Reson Imaging · August 2022 BACKGROUND: The Liver Imaging Reporting and Data System (LI-RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)- ... Full text Link to item Cite

Can radiomic analysis of a single-phase dual-energy CT improve the diagnostic accuracy of differentiating enhancing from non-enhancing small renal lesions?

Journal article Acta Radiol · June 2022 BACKGROUND: The value of dual-energy computed tomography (DECT)-based radiomics in renal lesions is unknown. PURPOSE: To develop DECT-based radiomic models and assess their incremental values in comparison to conventional measurements for differentiating e ... Full text Link to item Cite

Photon Counting CT and Radiomic Analysis Enables Differentiation of Tumors Based on Lymphocyte Burden.

Journal article Tomography · March 10, 2022 The purpose of this study was to investigate if radiomic analysis based on spectral micro-CT with nanoparticle contrast-enhancement can differentiate tumors based on lymphocyte burden. High mutational load transplant soft tissue sarcomas were initiated in ... Full text Open Access Link to item Cite

Data-Driven Modification of the LI-RADS Major Feature System on Gadoxetate Disodium-Enhanced MRI: Toward Better Sensitivity and Simplicity.

Journal article J Magn Reson Imaging · February 2022 BACKGROUND: The Liver Imaging Reporting and Data System (LI-RADS) is widely accepted as a reliable diagnostic scheme for hepatocellular carcinoma (HCC) in at-risk patients. However, its application is hampered by substantial complexity and suboptimal diagn ... Full text Link to item Cite

The Role of Machine Learning in Cardiovascular Pathology.

Journal article Can J Cardiol · February 2022 Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, but the ... Full text Link to item Cite

Post-Radiotherapy PET Image Outcome Prediction by Deep Learning Under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application.

Journal article Front Oncol · 2022 PURPOSE: To develop a method of biologically guided deep learning for post-radiation 18FDG-PET image outcome prediction based on pre-radiation images and radiotherapy dose information. METHODS: Based on the classic reaction-diffusion mechanism, a novel bio ... Full text Link to item Cite

CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study.

Journal article Radiology · December 2021 Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preope ... Full text Open Access Link to item Cite

Deep learning segmentation of glomeruli on kidney donor frozen sections.

Journal article J Med Imaging (Bellingham) · November 2021 Purpose: Recent advances in computational image analysis offer the opportunity to develop automatic quantification of histologic parameters as aid tools for practicing pathologists. We aim to develop deep learning (DL) models to quantify nonsclerotic and s ... Full text Link to item Cite

Week 4 Liver Fat Reduction on MRI as an Early Predictor of Treatment Response in Participants with Nonalcoholic Steatohepatitis.

Journal article Radiology · August 2021 Background Pharmacologic treatment of nonalcoholic steatohepatitis (NASH) is long term in nature; thus, early noninvasive treatment response assessment is important for therapeutic decision making. Purpose To investigate potential early predictors of the 1 ... Full text Link to item Cite

Intrinsic radiomic expression patterns after 20 Gy demonstrate early metabolic response of oropharyngeal cancers.

Journal article Med Phys · July 2021 PURPOSE: This study investigated the prognostic potential of intra-treatment PET radiomics data in patients undergoing definitive (chemo) radiation therapy for oropharyngeal cancer (OPC) on a prospective clinical trial. We hypothesized that the radiomic ex ... Full text Link to item Cite

A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms.

Journal article Phys Med Biol · May 31, 2021 Objective. Synthesize realistic and controllable respiratory motions in the extended cardiac-torso (XCAT) phantoms by developing a generative adversarial network (GAN)-based deep learning technique.Methods. A motion generation model was developed using bic ... Full text Link to item Cite

Radiogenomic Analysis of Locally Advanced Lung Cancer Based on CT Imaging and Intratreatment Changes in Cell-Free DNA.

Journal article Radiol Imaging Cancer · April 2021 The radiologic appearance of locally advanced lung cancer may be linked to molecular changes of the disease during treatment, but characteristics of this phenomenon are poorly understood. Radiomics, liquid biopsy of cell-free DNA (cfDNA), and next-generati ... Full text Link to item Cite

Digital pathology and computational image analysis in nephropathology.

Journal article Nat Rev Nephrol · November 2020 The emergence of digital pathology - an image-based environment for the acquisition, management and interpretation of pathology information supported by computational techniques for data extraction and analysis - is changing the pathology ecosystem. In par ... Full text Link to item Cite

Automatic detection of pulmonary nodules on CT images with YOLOv3: development and evaluation using simulated and patient data.

Journal article Quant Imaging Med Surg · October 2020 BACKGROUND: To develop a high-efficiency pulmonary nodule computer-aided detection (CAD) method for localization and diameter estimation. METHODS: The developed CAD method centralizes a novel convolutional neural network (CNN) algorithm, You Only Look Once ... Full text Link to item Cite

Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).

Journal article Phys Med Biol · March 19, 2020 Develop a machine learning-based method to generate multi-contrast anatomical textures in the 4D extended cardiac-torso (XCAT) phantom for more realistic imaging simulations. As a pilot study, we synthesize CT and CBCT textures in the chest region. For tra ... Full text Link to item Cite

Digital phantoms for characterizing inconsistencies among radiomics extraction toolboxes.

Journal article Biomed Phys Eng Express · March 2, 2020 PURPOSE: to develop digital phantoms for characterizing inconsistencies among radiomics extraction methods based on three radiomics toolboxes: CERR (Computational Environment for Radiological Research), IBEX (imaging biomarker explorer), and an in-house ra ... Full text Link to item Cite

Dose-Distribution-Driven PET Image-Based Outcome Prediction (DDD-PIOP): A Deep Learning Study for Oropharyngeal Cancer IMRT Application.

Journal article Front Oncol · 2020 PURPOSE: To develop a deep learning-based AI agent, DDD-PIOP (Dose-Distribution-Driven PET Image Outcome Prediction), for predicting 18FDG-PET image outcomes of oropharyngeal cancer (OPC) in response to intensity-modulated radiation therapy (IMRT). METHODS ... Full text Open Access Link to item Cite

An Exploratory Radiomics Approach to Quantifying Pulmonary Function in CT Images.

Journal article Sci Rep · August 8, 2019 Contemporary medical imaging is becoming increasingly more quantitative. The emerging field of radiomics is a leading example. By translating unstructured data (i.e., images) into structured data (i.e., imaging features), radiomics can potentially characte ... Full text Open Access Link to item Cite

Association of pre-treatment radiomic features with lung cancer recurrence following stereotactic body radiation therapy.

Journal article Phys Med Biol · January 8, 2019 The purpose of this work was to investigate the potential relationship between radiomic features extracted from pre-treatment x-ray CT images and clinical outcomes following stereotactic body radiation therapy (SBRT) for non-small-cell lung cancer (NSCLC). ... Full text Open Access Link to item Cite

Data clustering based on Langevin annealing with a self-consistent potential

Journal article Quarterly of Applied Mathematics · January 1, 2019 This paper introduces a novel data clustering algorithm based on Langevin dynamics, where the associated potential is constructed directly from the data. To introduce a self-consistent potential, we adopt the potential model from the established Quantum Cl ... Full text Open Access Cite

Dynamic Changes in Circulating Tumor DNA During Chemoradiation for Locally Advanced Lung Cancer.

Journal article Adv Radiat Oncol · 2019 PURPOSE: Concurrent chemoradiation therapy (CRT) is the principal treatment modality for locally advanced lung cancer. Cell death due to CRT leads to the release of cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) into the bloodstream, but the kinet ... Full text Link to item Cite

An investigation of machine learning methods in delta-radiomics feature analysis.

Journal article PLoS One · 2019 PURPOSE: This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the effec ... Full text Open Access Link to item Cite

Spatial-temporal variability of radiomic features and its effect on the classification of lung cancer histology.

Journal article Phys Med Biol · November 8, 2018 The purpose of this research was to study the sensitivity of Computed Tomography (CT) radiomic features to motion blurring and signal-to-noise ratios (SNR), and investigate its downstream effect regarding the classification of non-small cell lung cancer (N ... Full text Open Access Link to item Cite

Stereotactic body radiation therapy versus sublobar resection for stage I NSCLC.

Journal article Lung Cancer · November 2018 PURPOSE: To compare sublobar resection and stereotactic body radiation therapy (SBRT) in patients with stage I non-small cell lung cancer (NSCLC). METHODS: Patients undergoing sublobar resection or SBRT for stage I NSCLC from 2007 to 2014 at Duke Universit ... Full text Link to item Cite

Effects of Motion on Radiomics Analysis of Thoracic Cancers.

Journal article Int J Radiat Oncol Biol Phys · May 1, 2017 Full text Link to item Cite

A simple technique for the generation of institution-specific nomograms for permanent prostate cancer brachytherapy.

Journal article J Contemp Brachytherapy · October 2014 PURPOSE: Nomograms once had a vital role in prostate brachytherapy practice. Although some of their functions have been assumed by computerized dosimetry, many programs still find them useful to determine the number and strength of seeds to be ordered in a ... Full text Link to item Cite

Early pulmonary toxicity following lung stereotactic body radiation therapy delivered in consecutive daily fractions.

Journal article Radiother Oncol · May 2011 BACKGROUND AND PURPOSE: Identify the incidence of early pulmonary toxicity in a cohort of patients treated with lung stereotactic body radiation therapy (SBRT) on consecutive treatment days. MATERIAL AND METHODS: A total of 88 lesions in 84 patients were t ... Full text Link to item Cite