Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer

Purpose: To determine whether CT texture features can yield prognostic information in addition to conventional prognostic factors in stage III non-small cell lung cancer (NSCLC).Methods: We conducted a retrospective review of 91 patients with stage III NSCLC treated with definitive chemoradiation. All patients received a four-dimensional (4D) CT simulation, where we utilized the average image (average-CT) and an expiratory image (T50-CT), and a diagnostic contrast enhanced CT image (CE-CT). A penalized cox regression model was used for covariate selection and model development. Models incorporating texture features from the 3 image types and clinical factors were compared to models incorporating clinical factors alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Stratification into low-risk and high-risk groups was based on a patient’s predicted outcome being greater or less than the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients. The concordance correlation coefficient (CCC) was used to assess texture feature reproducibility and classification accuracy was used to assess reproducibility of texture features within the context of our models.         Results: Models incorporating both texture and clinical features demonstrated a significant improvement in stratification compared to models using clinical features alone in cross-validated Kaplan-Meier curves in terms of OS (p = 0.046), LRC (p = 0.01), and FFDM (p = 0.005). The average CCC was 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility uncertainties within our model yielded 80.4 (SD = 3.7), 78.3 (SD = 4.0), and 78.8 (SD = 3.9) percent classification accuracy for OS, LRC, and FFDM, respectively.    Conclusion: Pretreatment tumor texture may provide prognostic information in additional to routinely obtained clinical features. Reproducibility of CE-CT appears inferior to average-CT and T50-CT; however model classification accuracy rates of ~80% were still achieved.----------------------Cite this article as: Fried DV, Tucker SL, Zhou S, Liao ZX, Ibbott GS, Court LE.   Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer. Int J Cancer Ther Oncol 2014; 2(2):020223. DOI: 10.14319/ijcto.0202.2

MRI characterization of cobalt dichloride-N-acetyl cysteine (C4) contrast agent marker for prostate brachytherapy

Brachytherapy, a radiotherapy technique for treating prostate cancer, involves the implantation of numerous radioactive seeds into the prostate. While the implanted seeds can be easily identified on a CT image, distinguishing the prostate and surrounding soft tissues is not as straightforward. Magnetic Resonance Imaging (MRI) offers superior anatomical delineation, but the seeds appear as dark voids and are difficult to identify, thus creating a conundrum. Cobalt dichloride-N-acetylcysteine (C4) has previously been shown to be promising as an encapsulated contrast agent marker. We performed spin-lattice relaxation time (T1) and spin-spin relaxation time (T2) measurements of C4 solutions with varying cobalt dichloride concentrations to determine the corresponding relaxivities, r1 and r2. These relaxation parameters were investigated at different field strengths, temperatures and orientations. T1 measurements obtained at 1.5 T and 3.0 T, as well as at room and body temperature, showed that r1 is field-independent and temperatureindependent. Conversely, the T2 values at 3.0 T were shorter than at 1.5 T, while the T2 values at body temperature were slightly higher than at room temperature. By examining the relaxivities with the C4 vials aligned in three different planes, we found no orientation-dependence. With these relaxation characteristics, we aim to develop pulse sequences that will enhance the C4 signal against prostatic stroma. Ultimately, the use of C4 as a positive contrast agent marker will encourage the use of MRI to obtain an accurate representation of the radiation dose delivered to the prostate and surrounding normal anatomical structures

Safety considerations for IMRT: Executive summary

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98742/1/MPH005067.pd

International Conference on Advances in Radiation Oncology (ICARO): Outcomes of an IAEA Meeting

The IAEA held the International Conference on Advances in Radiation Oncology (ICARO) in Vienna on 27-29 April 2009. The Conference dealt with the issues and requirements posed by the transition from conventional radiotherapy to advanced modern technologies, including staffing, training, treatment planning and delivery, quality assurance (QA) and the optimal use of available resources. The current role of advanced technologies (defined as 3-dimensional and/or image guided treatment with photons or particles) in current clinical practice and future scenarios were discussed

Minicourse: Radiation Oncology Physics—Acceptance Testing and Quality Assurance of Treatment Planning Systems

LEARNING OBJECTIVES1) To demonstrate the importance of the quality assurance (QA) of radiation treatment planning systems (RTPS) by reviewing significant treatment errors associated with their use. 2) To review the major functionality of a modern RTPS. 3) To highlight and summarize various reports that have made recommendations regarding acceptance, commissioning and QA of RTPSs with special emphasis on IEC-62083 and IAEA TRS-430. 4) To discuss accuracy requirements and criteria of acceptability of the modern RTPS. 5) To summarize acceptance testing procedures as proposed by the IAEA for a modern RTPS. 6) To provide an overview of commissioning a modern RTPS. 7) To provide an overview of the quality control associated with a modern RTPS.ABSTRACTDuring the last decade there has been a technological revolution in radiation oncology. Enhanced use of imaging combined with computer-controlled methods of dose delivery provides a capability of escalating tumor doses without increasing morbidity. A pivotal component of this modern technology is the computerized radiation treatment planning system (RTPS) which is used to develop optimal treatment techniques for individual patients. Modern RTPSs make increased use of patient images, enhanced 3-D displays, more sophisticated dose calculation algorithms, more complex treatment plan evaluation tools, combined with the generation of images which can be used for treatment verification. The implementation of intensity modulated radiation therapy (IMRT) combined with automated optimization software has added a further complexity to the RTPS. In recent years, various national and international organizations have developed reports that have made recommendations regarding the commissioning and quality assurance (QA) of RTPSs. In 1998, the AAPM published the TG53 report giving guidelines for users and vendors on QA for radiation therapy planning. In 2000, the International Electrotechnical Commission (IEC) produced a report (IEC 62083) identifying safety requirements for manufacturers of RTPSs. In 2004, both the International Atomic Energy Agency (IAEA) and the European Society of Therapeutic Radiation Oncology (ESTRO) published reports on commissioning and QA of RTPSs. Furthermore, the IAEA has recently developed a protocol for the acceptance testing of RTPSs. In 2006, the Netherlands Commission of Radiation Dosimetry also produced a report on QA of RTPSs. All of these reports indicate that a thorough commissioning of a modern 3-D RTPS has become a daunting task. This refresher course will specifically look at the IEC and IAEA reports and review issues associated with acceptance testing, commissioning, and quality assurance of the modern RTPS.URL\u27shttp://rpc.mdanderson.org/RPC/home.ht

Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer

Purpose: To determine whether CT texture features can yield prognostic information in addition to conventional prognostic factors in stage III non-small cell lung cancer (NSCLC).Methods: We conducted a retrospective review of 91 patients with stage III NSCLC treated with definitive chemoradiation. All patients received a four-dimensional (4D) CT simulation, where we utilized the average image (average-CT) and an expiratory image (T50-CT), and a diagnostic contrast enhanced CT image (CE-CT). A penalized cox regression model was used for covariate selection and model development. Models incorporating texture features from the 3 image types and clinical factors were compared to models incorporating clinical factors alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Stratification into low-risk and high-risk groups was based on a patient’s predicted outcome being greater or less than the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients. The concordance correlation coefficient (CCC) was used to assess texture feature reproducibility and classification accuracy was used to assess reproducibility of texture features within the context of our models.         Results: Models incorporating both texture and clinical features demonstrated a significant improvement in stratification compared to models using clinical features alone in cross-validated Kaplan-Meier curves in terms of OS (p = 0.046), LRC (p = 0.01), and FFDM (p = 0.005). The average CCC was 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility uncertainties within our model yielded 80.4 (SD = 3.7), 78.3 (SD = 4.0), and 78.8 (SD = 3.9) percent classification accuracy for OS, LRC, and FFDM, respectively.    Conclusion: Pretreatment tumor texture may provide prognostic information in additional to routinely obtained clinical features. Reproducibility of CE-CT appears inferior to average-CT and T50-CT; however model classification accuracy rates of ~80% were still achieved.----------------------Cite this article as: Fried DV, Tucker SL, Zhou S, Liao ZX, Ibbott GS, Court LE.   Pretreatment CT texture features for prognostication in patient with Stage III Non-Small Cell Lung Cancer. Int J Cancer Ther Oncol 2014; 2(2):020223. DOI: 10.14319/ijcto.0202.23</p