Image Analysis and Quantitation
In order to accomplish our goals we have invested great effort in engineering software for image visualization and analysis. The application we have designed, RT_Image, is a full-featured application for the visualization and quantitation of a variety of medical images. RT_Image is written in the Interactive Data Language (IDL) and is open source, allowing developers to easily add functionality and freely distribute the software. To date, RT_Image has been applied towards segmenting clinical PET images in order to extract prognostic information and quantitating multimodality small animal imaging data, including CT, MRI, PET, and optical images. Currently this code framework is being used to develop the treatment planning interface for the small animal radiotherapy system described above. This program is designed to streamline data analysis and expedite development of new quantitative methods.
Current research projects in this area include:
- Development of novel PET segmentation methods for radiotherapy target volume definition
- Development of interfaces for volume image visualization, registration, and 3D ROI analysis
- Implementation of small animal radiotherapy treatment planning and dose calculation tools within RT_Image
- Ali R, Gunduz-Demir C, Szilágyi T, Durkee B, Graves EE. Semi-automatic segmentation of subcutaneous tumours from micro-computed tomography images. Physics in Medicine and Biology 2013; 58(22):8007-8019. [Epub ahead of print]
- Bazan JG, Koong AC, Kapp DS, Quon A, Graves EE, Loo BW, Chang DT. Metabolic tumor volume predicts for disease progression and survival in patients with squamous cell carcinoma of the anal canal. Journal of Nuclear Medicine 2013; 54 (1): 27-32.
- Chennupati S, Quon A, Kamaya A, Pai RK, La T, Krakow TE, Graves E, Koong A, Chang DT. Positron Emission Tomography for Predicting Pathologic Response Following Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer. American Journal of Clinical Oncology 2012; 35:334-339.
- Lee P, Bazan JG, Lavori PW, Weerasuriya DK, Quon A, Le QT, Wakelee HA, Graves EE, Loo BW. Metabolic Tumor Volume is an Independent Prognostic Factor in Patients Treated Definitively for Non-Small Cell Lung Cancer. Clinical Lung Cancer 2012; 13:52-58.
- Chu KP, Murphy JD, La TH, Krakow TE, Graves E, Hsu A, Maxim PG, Loo B, Chang DT, Le QT. Prognostic Value of Metabolic Tumor Volume and Velocity in Predicting Head and Neck Cancer Outcomes. International Journal of Radiation Oncology Biology Physics 2012; 83:1521-1527.
- Tang C, Murphy JD, Khong B, La TH, Kong C, Fischbein NJ, Colevas AD, Iagaru AH, Graves EE, Le QT. Validation that Metabolic Tumor Volume Predicts Outcome in Head and Neck Cancer. International Journal of Radiation Oncology Biology Physics 2012; 83:1514-1520.
- Jayachandran P, Pai RK, Quon A, Graves E, Krakow TE, La T, Loo BW; Koong AC, Chang DT. Postchemoradiotherapy Positron Emission Tomography Predicts Pathologic Response and Survival in Patients with Esophageal Cancer. International Journal of Radiation Oncology Biology Physics 2012; 84:471-477.
- Le QT, Fisher R, Oliner KS, Young RJ, Cao H, Kong C, Graves E, Hicks RJ, McArthur GA, Peters L, O'Sullivan B, Giaccia A, Rischin D. Prognostic and predictive significance of plasma HGF and IL-8 in a phase III trial of chemoradiation with or without tirapazamine in locoregionally advanced head and neck cancer. Clinical Cancer Research 2012; 18:1798-1807.
- Nair VS, Gevaert O, Davidzon G, Napel S, Graves EE, Hoang CD, Shrager JB, Quon A, Rubin DL, Plevritis SK. Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer. Cancer Research 2012; 72:3725-3734.
- Abelson JA, Murphy JD, Trakul N, Bazan JG, Maxim PG, Graves EE, Quon A, Le QT, Diehn M, Loo BW Jr. Metabolic imaging metrics correlate with survival in early stage lung cancer treated with stereotactic ablative radiotherapy. Lung Cancer 2012; 78:219-224.
- Tseng D, Rachakonda LP, Su Z, Advani R, Horning S, Hoppe RT, Quon A, Graves EE, Loo BW Jr, Tran PT. Interim-treatment quantitative PET parameters predict progression and death among patients with Hodgkin's disease. Radiation Oncology2012; 7:5.
- Murphy JD, La TH, Chu K, Quon A, Fischbein NJ, Maxim PG, Graves EE, Loo BW, Le QT. Post-Radiation Metabolic Tumor Volume Predicts Outcome in Head-and-Neck Cancer.International Journal of Radiation Oncology Biology Physics 2011; 80:514-521.
- Kozak M, Murphy J, Schipper ML, Donington JS, Zhou L, Whyte, RI, Shrager JB, Hoang, C, Bazan J, Maxim PG, Graves EE, Diehn M, Hara W, Quon A, Le QT, Wakelee HA, Loo BW. Tumor Volume as a Potential Imaging-Based Risk-Stratification Factor in Trimodality Therapy for Locally Advanced Non-small Cell Lung Cancer. Journal of Thoracic Oncology 2011; 6:920-926.
- Murphy JD, Chisholm KM, Daly ME, Wiegner EA, Truong D, Iagaru A, Maxim PG, Loo BW, Graves EE, Kaplan MJ, Kong C, Le QT. Correlation between metabolic tumor volume and pathologic tumor volume in squamous cell carcinoma of the oral cavity. Radiotherapy and Oncology 2011; 80:514-521.
- Schellenberg D, Quon A, Minn YA, Graves EE, Kunz P, Ford JM, Fisher GA, Goodman KA, Koong AC, Chang DT.18Fluorodoxyglucose-PET is prognostic of progression free and overall survival in locally advanced pancreas cancer treated with stereotactic radiotherapy. International Journal of Radiation Oncology Biology Physics 2010; 77:1420-1425.
- La TH, Filion EJ, Turnbull BB, Chu JN, Lee P, Nguyen K, Maxim P, Loo BW, Quon A, Graves EE, Le QT. Metabolic Tumor Volume Predicts for Recurrence and Death in Head and Neck Cancer. International Journal of Radiation Oncology Biology Physics 2009; 74:1335-1341.
- Graves EE, Quon A, Loo BW. RT_Image: An Open Source Tool for Investigating PET in Radiation Oncology. Technology in Cancer Research and Therapy 2007, 6:111-121.
- Lee P, Weerasuriya D, Le Q, Lavori PW, Quon A, Hara W, Wakelee H, Graves E, Loo BW. Metabolic Tumor Burden Predicts for Disease Progression in Lung Cancer. International Journal of Radiation Oncology Biology Physics 2007, 69: 328-333.