Purpose
To extract and study comprehensive spatial–temporal 18F-FDG PET features for the prediction of pathologic tumor response to neoadjuvant chemoradiotherapy (CRT) in esophageal cancer.
Methods and Materials
Twenty patients with esophageal cancer were treated with trimodality therapy (CRT plus surgery) and underwent FDG PET/CT scans both before (pre-CRT) and after (post-CRT) CRT. The two scans were rigidly registered. A tumor volume was semiautomatically delineated using a threshold of standardized uptake value (SUV) ≥ 2.5, followed by manual editing. Comprehensive features were extracted to characterize the SUV intensity distribution, spatial patterns (texture), tumor geometry, and associated changes resulting from CRT. The usefulness of each feature in predicting pathologic tumor response to CRT was evaluated using the area under the receiver operating characteristic curve (AUC).
Results
The best traditional response measure was maximum SUV (SUVmax) decline (AUC 0.76). Two new intensity features (SUVmean decline and skewness) and three texture features (inertia, correlation, and cluster prominence) were found to be significant predictors with AUCs ≥ 0.76. According to these features, a tumor was more likely a responder when the mean SUV decline was larger, when there were relatively fewer voxels with higher SUVs pre-CRT, or when FDG uptake post-CRT was relatively homogeneous. All of the most accurate predictive features were extracted from the entire tumor rather than from the most active part of the tumor. For SUV intensity features and tumor size features, changes were more predictive than pre- or post-CRT assessments alone.
Conclusion
Spatial–temporal FDG PET features were found to be useful predictors of pathologic tumor response to neoadjuvant chemoradiotherapy in esophageal cancer. Key words: FDG PET/CT, Tumor response, Esophageal cancer, Quantitative image analysis
Liposomes have been extensively studied and are used in the treatment of several diseases. Liposomes improve the therapeutic efficacy by enhancing drug absorption while avoiding or minimizing rapid degradation and side effects, prolonging the biological half-life and reducing toxicity. The unique feature of liposomes is that they are biocompatible and biodegradable lipids, and are inert and non-immunogenic. Liposomes can compartmentalize and solubilize both hydrophilic and hydrophobic materials. All these properties of liposomes and their flexibility for surface modification to add targeting moieties make liposomes more attractive candidates for use as drug delivery vehicles. There are many novel liposomal formulations that are in various stages of development, to enhance therapeutic effectiveness of new and established drugs that are in preclinical and clinical trials. Recent developments in multimodality imaging to better diagnose disease and monitor treatments embarked on using liposomes as diagnostic tool. Conjugating liposomes with different labeling probes enables precise localization of these liposomal formulations using various modalities such as PET, SPECT, and MRI. In this review, we will briefly review the clinical applications of liposomal formulation and their potential imaging properties.
Significant differences between planned and delivered treatments may occur due to respiration-induced tumour motion, leading to underdosing of parts of the tumour and overdosing of parts of the surrounding critical structures. Existing methods proposed to counter tumour motion include breath-holds, gating and MLC-based tracking. Breath-holds and gating techniques increase treatment time considerably, whereas MLC-based tracking is limited to two dimensions. We present an alternative solution in which a robotic couch moves in real time in response to organ motion. To demonstrate proof-of-principle, we constructed a miniature adaptive couch model consisting of two movable platforms that simulate tumour motion and couch motion, respectively. These platforms were connected via an electronic feedback loop so that the bottom platform responded to the motion of the top platform. We tested our model with a seven-field step-and-shoot delivery case in which we performed three film-based experiments: (1) static geometry, (2) phantom-only motion and (3) phantom motion with simulated couch motion. Our measurements demonstrate that the miniature couch was able to compensate for phantom motion to the extent that the dose distributions were practically indistinguishable from those in static geometry. Motivated by this initial success, we investigated a real-time couch compensation system consisting of a stereoscopic infra-red camera system interfaced to a robotic couch known as the Hexapod, which responds in real time to any change in position detected by the cameras. Optical reflectors placed on a solid water phantom were used as surrogates for motion. We tested the effectiveness of couch-based motion compensation for fixed fields and a dynamic arc delivery cases. Due to hardware limitations, we performed film-based experiments (1), (2) and (3), with the robotic couch at a phantom motion period and dose rate of 16 s and 100 MU min(-1), respectively. Analysis of film measurements showed near-equivalent dose distributions (
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