David V Fried1, Osama Mawlawi2, Lifei Zhang3, Xenia Fave4, Shouhao Zhou5, Geoffrey Ibbott4, Zhongxing Liao6, Laurence E Court4. 1. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: dvfried@mdanderson.org. 2. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas. 3. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas. 4. Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas. 5. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas. 6. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Abstract
PURPOSE: To determine whether previously identified quantitative image features (QIFs) based on (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) (co-occurrence matrix energy and solidity) are able to isolate subgroups of patients who would receive a benefit or detriment from dose escalation in terms of overall survival (OS) or progression-free survival (PFS). METHODS AND MATERIALS: Subgroups of a previously analyzed 225 patient cohort were generated with the use of 5-percentile increment cutoff values of disease solidity and primary tumor co-occurrence matrix energy. The subgroups were analyzed with a log-rank test to determine whether there was a difference in OS and PFS between patients treated with 60 to 70 Gy and those receiving 74 Gy. RESULTS: In the entire patient cohort, there was no statistical difference in terms of OS or PFS between patients receiving 74 Gy and those receiving 60 to 70 Gy. It was qualitatively observed that as disease solidity and primary co-occurrence matrix energy increased, patients receiving 74 Gy had an improved OS and PFS compared with those receiving 60 to 70 Gy. The opposite trend (detriment of receiving 74 Gy) was also observed regarding low values of disease solidity and primary co-occurrence matrix energy. CONCLUSIONS: FDG-PET-based QIFs were found to be capable of isolating subgroups of patients who received a benefit or detriment from dose escalation.
PURPOSE: To determine whether previously identified quantitative image features (QIFs) based on (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) (co-occurrence matrix energy and solidity) are able to isolate subgroups of patients who would receive a benefit or detriment from dose escalation in terms of overall survival (OS) or progression-free survival (PFS). METHODS AND MATERIALS: Subgroups of a previously analyzed 225 patient cohort were generated with the use of 5-percentile increment cutoff values of disease solidity and primary tumor co-occurrence matrix energy. The subgroups were analyzed with a log-rank test to determine whether there was a difference in OS and PFS between patients treated with 60 to 70 Gy and those receiving 74 Gy. RESULTS: In the entire patient cohort, there was no statistical difference in terms of OS or PFS between patients receiving 74 Gy and those receiving 60 to 70 Gy. It was qualitatively observed that as disease solidity and primary co-occurrence matrix energy increased, patients receiving 74 Gy had an improved OS and PFS compared with those receiving 60 to 70 Gy. The opposite trend (detriment of receiving 74 Gy) was also observed regarding low values of disease solidity and primary co-occurrence matrix energy. CONCLUSIONS: FDG-PET-based QIFs were found to be capable of isolating subgroups of patients who received a benefit or detriment from dose escalation.
Authors: Rachel B Ger; Carlos E Cardenas; Brian M Anderson; Jinzhong Yang; Dennis S Mackin; Lifei Zhang; Laurence E Court Journal: J Vis Exp Date: 2018-01-08 Impact factor: 1.355
Authors: M Dosani; R Yang; M McLay; D Wilson; M Liu; C J Yong-Hing; J Hamm; C R Lund; R Olson; D Schellenberg Journal: Curr Oncol Date: 2019-02-01 Impact factor: 3.677
Authors: Rachel B Ger; Joseph G Meier; Raymond B Pahlka; Skylar Gay; Raymond Mumme; Clifton D Fuller; Heng Li; Rebecca M Howell; Rick R Layman; R Jason Stafford; Shouhao Zhou; Osama Mawlawi; Laurence E Court Journal: PLoS One Date: 2019-09-05 Impact factor: 3.240