Diffusion-weighted MRI versus 18F-FDG PET/CT: performance as predictors of tumor treatment response and patient survival in patients with non-small cell lung cancer receiving chemoradiotherapy.
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Y. Ohno | K. Sugimura | T. Yoshikawa | H. Koyama | N. Aoyama | Y. Onishi | Keiko Matsumoto
[1] Leyun Pan,et al. Prediction of Short-term Survival in Patients with Advanced Nonsmall Cell Lung Cancer Following Chemotherapy Based on 2-Deoxy-2-[F-18]fluoro-d-glucose-Positron Emission Tomography: A Feasibility Study , 2007, Molecular Imaging and Biology.
[2] C. Claussen,et al. Correlation of Simultaneously Acquired Diffusion-Weighted Imaging and 2-Deoxy-[18F] fluoro-2-D-glucose Positron Emission Tomography of Pulmonary Lesions in a Dedicated Whole-Body Magnetic Resonance/Positron Emission Tomography System , 2013, Investigative radiology.
[3] S. Graziano. Non-small cell lung cancer: clinical value of new biological predictors , 1997 .
[4] M. Forsting,et al. Diffusion-weighted imaging as part of hybrid PET/MRI protocols for whole-body cancer staging: does it benefit lesion detection? , 2013, European journal of radiology.
[5] M. van Glabbeke,et al. New guidelines to evaluate the response to treatment in solid tumors , 2000, Journal of the National Cancer Institute.
[6] A. Salan,et al. Monitoring the chemotherapeutic response in primary lung cancer using 99mTc-MIBI SPET , 2001, European Journal of Nuclear Medicine.
[7] D. Collins,et al. Competing Technology for PET/Computed Tomography: Diffusion-weighted Magnetic Resonance Imaging. , 2013, PET clinics.
[8] Matthias Reimold,et al. 18F-FDG PET for assessment of therapy response and preoperative re-evaluation after neoadjuvant radio-chemotherapy in stage III non-small cell lung cancer , 2007, European Journal of Nuclear Medicine and Molecular Imaging.
[9] Hyae-Young Kim,et al. Early Prediction of Response to First-Line Therapy Using Integrated 18F-FDG PET/CT for Patients with Advanced/Metastatic Non-small Cell Lung Cancer , 2009, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.
[10] M. Matoba,et al. Lung carcinoma: diffusion-weighted mr imaging--preliminary evaluation with apparent diffusion coefficient. , 2007, Radiology.
[11] N. Müller,et al. Small peripheral pulmonary carcinomas evaluated with dynamic MR imaging: correlation with tumor vascularity and prognosis. , 2003, Radiology.
[12] D. Collins,et al. Predicting response of colorectal hepatic metastasis: value of pretreatment apparent diffusion coefficients. , 2007, AJR. American journal of roentgenology.
[13] Takeshi Yoshikawa,et al. Magnetic Resonance Imaging for Lung Cancer , 2013, Journal of thoracic imaging.
[14] K. Kihara,et al. Apparent diffusion coefficient as a prognostic biomarker of upper urinary tract cancer: a preliminary report , 2013, European Radiology.
[15] S. Matsumoto,et al. Detection of bone metastases in non‐small cell lung cancer patients: Comparison of whole‐body diffusion‐weighted imaging (DWI), whole‐body MR imaging without and with DWI, whole‐body FDG‐PET/CT, and bone scintigraphy , 2009, Journal of magnetic resonance imaging : JMRI.
[16] Jan Wolber,et al. Diffusion MRI for prediction of response of rectal cancer to chemoradiation , 2002, The Lancet.
[17] T Matsuoka,et al. Assessment of early treatment response after CT-guided radiofrequency ablation of unresectable lung tumours by diffusion-weighted MRI: a pilot study. , 2009, The British journal of radiology.
[18] G. Scagliotti,et al. Early response to chemotherapy in patients with non-small-cell lung cancer assessed by [18F]-fluoro-deoxy-D-glucose positron emission tomography and computed tomography. , 2013, Clinical lung cancer.
[19] M. Schwaiger,et al. Positron emission tomography in non-small-cell lung cancer: prediction of response to chemotherapy by quantitative assessment of glucose use. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[20] H. Klomp,et al. Is 18F-FDG PET/CT Useful for the Early Prediction of Histopathologic Response to Neoadjuvant Erlotinib in Patients with Non–Small Cell Lung Cancer? , 2010, The Journal of Nuclear Medicine.
[21] S. Matsumoto,et al. Non-small cell lung cancer: whole-body MR examination for M-stage assessment--utility for whole-body diffusion-weighted imaging compared with integrated FDG PET/CT. , 2008, Radiology.
[22] Vicky Goh,et al. Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis , 2012, European Journal of Nuclear Medicine and Molecular Imaging.
[23] T. Tsuchida,et al. Imaging the early response to chemotherapy in advanced lung cancer with diffusion‐weighted magnetic resonance imaging compared to fluorine‐18 fluorodeoxyglucose positron emission tomography and computed tomography , 2013, Journal of magnetic resonance imaging : JMRI.
[24] Jürgen Griebel,et al. Tumor microcirculation and diffusion predict therapy outcome for primary rectal carcinoma. , 2003, International journal of radiation oncology, biology, physics.
[25] D. Altman,et al. STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.
[26] S. Marnitz,et al. Value of 18F-Fluoro-2-Deoxy-d-Glucose-Positron Emission Tomography/Computed Tomography in Non–Small-Cell Lung Cancer for Prediction of Pathologic Response and Times to Relapse after Neoadjuvant Chemoradiotherapy , 2006, Clinical Cancer Research.
[27] Y. Tomizawa,et al. Usefulness of FDG-PET for early prediction of the response to gefitinib in non-small cell lung cancer. , 2008, Lung cancer.
[28] H. Kim,et al. Fluorodeoxyglucose positron-emission tomography ratio in non-small cell lung cancer patients treated with definitive radiotherapy , 2013, Radiation oncology journal.
[29] M. Brundage,et al. Prognostic factors in non-small cell lung cancer: a decade of progress. , 2002, Chest.
[30] H. Oizumi,et al. Role of diffusion-weighted magnetic resonance imaging for predicting of tumor invasiveness for clinical stage IA non-small cell lung cancer. , 2009, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.
[31] Yukiko Arisaka,et al. 18F-FDG uptake as a biologic prognostic factor for recurrence in patients with surgically resected non-small cell lung cancer. , 2002, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[32] A. K. Sivrioğlu,et al. Diffusion-weighted MRI as predictor of tumor treatment response. , 2012, AJR. American journal of roentgenology.
[33] N Zamboglou,et al. Predictive factors in radiotherapy for non-small cell lung cancer: present status. , 2001, Lung cancer.
[34] M. Kusumoto,et al. Predicting the prognosis of non-small cell lung cancer patient treated with conservative therapy using contrast-enhanced MR imaging , 2000, European Radiology.
[35] Bradford A Moffat,et al. Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[36] Stephan E Maier,et al. Pretreatment prediction of brain tumors' response to radiation therapy using high b-value diffusion-weighted MRI. , 2004, Neoplasia.
[37] S. Matsumoto,et al. Prognostic value of dynamic MR imaging for non‐small‐cell lung cancer patients after chemoradiotherapy , 2005, Journal of magnetic resonance imaging : JMRI.
[38] S. Shiraishi,et al. Diffusion-Weighted Magnetic Resonance Imaging for Diagnosing Malignant Pulmonary Nodules/Masses: Comparison with Positron Emission Tomography , 2008, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.
[39] David E Morris,et al. Chemotherapeutic management of stage IV non-small cell lung cancer. , 2003, Chest.
[40] A. Jemal,et al. Cancer Statistics, 2010 , 2010, CA: a cancer journal for clinicians.
[41] D. Collins,et al. Diffusion-weighted MRI in the body: applications and challenges in oncology. , 2007, AJR. American journal of roentgenology.