Index of content:
Volume 40, Issue 10, October 2013
A family of fluorine-18 (18F)-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) features based on histogram distances is proposed for predicting pathologic tumor response to neoadjuvant chemoradiotherapy (CRT). These features describe the longitudinal change of FDG uptake distribution within a tumor.Methods:
Twenty patients with esophageal cancer treated with CRT plus surgery were included in this study. All patients underwent PET/CT scans before (pre-) and after (post-) CRT. The two scans were first rigidly registered, and the original tumor sites were then manually delineated on the pre-PET/CT by an experienced nuclear medicine physician. Two histograms representing the FDG uptake distribution were extracted from the pre- and the registered post-PET images, respectively, both within the delineated tumor. Distances between the two histograms quantify longitudinal changes in FDG uptake distribution resulting from CRT, and thus are potential predictors of tumor response. A total of 19 histogram distances were examined and compared to both traditional PET response measures and Haralick texture features. Receiver operating characteristic analyses and Mann-Whitney U test were performed to assess their predictive ability.Results:
Among all tested histogram distances, seven bin-to-bin and seven crossbin distances outperformed traditional PET response measures using maximum standardized uptake value (AUC = 0.70) or total lesion glycolysis (AUC = 0.80). The seven bin-to-bin distances were:L 2 distance (AUC = 0.84), χ 2 distance (AUC = 0.83), intersection distance (AUC = 0.82), cosine distance (AUC = 0.83), squared Euclidean distance (AUC = 0.83), L 1 distance (AUC = 0.82), and Jeffrey distance (AUC = 0.82). The seven crossbin distances were: quadratic-chi distance (AUC = 0.89), earth mover distance (AUC = 0.86), fast earth mover distance (AUC = 0.86), diffusion distance (AUC = 0.88), Kolmogorov-Smirnov distance (AUC = 0.88), quadratic form distance (AUC = 0.87), and match distance (AUC = 0.84). These crossbin histogram distance features showed slightly higher prediction accuracy than texture features on post-PET images.Conclusions:
The results suggest that longitudinal patterns in18F-FDG uptake characterized using histogram distances provide useful information for predicting the pathologic response of esophageal cancer to CRT.
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An introduction to molecular imaging in radiation oncology: A report by the AAPM Working Group on Molecular Imaging in Radiation Oncology (WGMIR)40(2013); http://dx.doi.org/10.1118/1.4819818View Description Hide Description
Molecular imaging is the direct or indirect noninvasive monitoring and recording of the spatial and temporal distribution of in vivo molecular, genetic, and/or cellular processes for biochemical, biological, diagnostic, or therapeutic applications. Molecular images that indicate the presence of malignancy can be acquired using optical, ultrasonic, radiologic, radionuclide, and magnetic resonance techniques. For the radiation oncology physicist in particular, these methods and their roles in molecular imaging of oncologic processes are reviewed with respect to their physical bases and imaging characteristics, including signal intensity, spatial scale, and spatial resolution. Relevant molecular terminology is defined as an educational assist. Current and future clinical applications in oncologic diagnosis and treatment are discussed. National initiatives for the development of basic science and clinical molecular imaging techniques and expertise are reviewed, illustrating research opportunities in as well as the importance of this growing field.