The new SPR parametrization gave lower RMSEs than the two other published DECT methods, and was in particular more robust against added noise. The method has potential for reducing range uncertainty margins in treatment planning of proton therapy.
CT texture analysis can help differentiate between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer
Abstract
BackgroundIn patients with Non-Small-Cell Lung Carcinoma NSCLC the lymph node staging in the mediastinum is important due to impact on management and prognosis. Computed tomography texture analysis (CTTA) is a post processing technique that can evaluate the heterogeneity of marked regions in images.
PurposeTo evaluate if CTTA can differentiate between malignant and benign lymph nodes in a cohort of patients with suspected lung cancer.
Material and MethodsWith tissue sampling as reference standard, 46 lymph nodes from 29 patients were analyzed using CTTA. For each lymph node, CTTA was performed using a research software "TexRAD" by drawing region of interest (ROI)on all available axial contrast enhanced computed tomography (CT) slices covering the entire volume of the lymph node. Lymph node CTTA comprised image filtration-histogram analysis undertakes 2 stages: First step comprised an application of a Laplacian of Gaussian filter to highlight fine to coarse textures within the ROI, followed by a quantification of textures via histogram analysis using mean grey-level intensity from the entire volume of the lymph nodes.
Results
2CTTA demonstrated a statistically significant difference between the malignant and the benign lymph nodes (p=0,001), and by binary logistic regression we obtained a sensitivity of 53% and specificity of 97% in the test population. The area under the Receiver Operating Curve was 83.4% and reproducibility was excellent.
ConclusionCTTA may be helpful in differentiating between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer, with a low intraobserver variance.
The assignment of phases to the observed structure factor amplitude is the most crucial, albeit most complicated, step in structure determination. As the phases cannot be directly measured, their elucidation remains the least predictable task, even for average-sized proteins. Clearly, for large macromolecular assemblies the magnitude and the complexity of phasing is greatly enhanced.
Background and purpose: Patients with head and neck (HN) cancer may benefit from proton therapy due to the potential for sparing of normal tissue. For planning of proton therapy, dual-energy CT (DECT) has been shown to provide superior stopping power ratio (SPR) determination in phantom materials and organic tissue samples, compared to single-energy CT (SECT). However, the benefit of DECT in HN cancer patients has not yet been investigated. This study therefore compared DECT-and SECT-based SPR estimation for HN cancer patients. Materials and methods: Fourteen HN cancer patients were DECT scanned. Eight patients were scanned using a dual source DECT scanner and six were scanned with a conventional SECT scanner by acquiring two consecutive scans. SECT image sets were computed as a weighted summation of the low and high energy DECT image sets. DECT-and SECT-based SPR maps were derived. Water-equivalent path lengths (WEPLs) through the SPR maps were compared in the eight cases with dual source DECT scans. Mean SPR estimates over region-of-interests (ROIs) in the cranium, brain and eyes were analyzed for all patients. Results: A median WEPL difference of 1.9 mm (1.5%) was found across the eight patients. Statistically significant SPR differences were seen for the ROIs in the brain and eyes, with the SPR estimates based on DECT overall lower than for SECT. Conclusions: Clinically relevant WEPL and SPR differences were found between DECT and SECT, which could imply that the accuracy of treatment planning for proton therapy would benefit from DECT-based SPR estimation.
Non-calcified plaques can be identified and classified by CCTA. However, the luminal density affects the absolute HU of both non-calcified and calcified plaques. Characterization and classification of non-calcified plaques by absolute CT values therefore requires standardization of contrast protocols.
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