The liver is a critically important organ that has numerous functions including the production of bile, metabolism of ingested nutrients, elimination of many waste products, glycogen storage, and plasma protein synthesis. The liver is often incidentally irradiated during radiation therapy (RT) for tumors in the upper- abdomen, right lower lung, distal esophagus, or during whole abdomen or whole body RT. This article describes the endpoints, time-course, and dose-volume effect of radiation on the liver.
Traditionally, the goal of nanoparticle-based chemotherapy has been to decrease normal tissue toxicity by improving drug specificity to tumors. The EPR effect (Enhanced Permeability and Retention) can permit passive accumulation into tumor interstitium. However, suboptimal delivery is achieved with most nanoparticles because of heterogeneities of vascular permeability, which limits nanoparticle penetration. Further, slow drug release limits bioavailability. We developed a fast drug-releasing liposome triggered by local heat that has already shown substantial anti-tumor efficacy and is in human trials. Here, we demonstrate that thermally sensitive liposomes release doxorubicin inside the tumor vasculature. Real-time confocal imaging of doxorubicin delivery to murine tumors in window chambers and histologic analysis of flank tumors illustrates that intravascular drug release increases free drug in the interstitial space. This increases both the time that tumor cells are exposed to maximum drug levels and the drug penetration distance, compared with free drug or traditional pegylated liposomes. These improvements in drug bioavailability establish a new paradigm in drug delivery: rapidly triggered drug release in the tumor bloodstream.
Purpose
The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.
Approach
A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.
Findings
A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.
Conclusions
Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to ...
The goal of intensity-modulated radiation therapy (IMRT) treatment plan optimization is to produce a cumulative dose distribution that satisfies both the dose prescription and the normal tissue dose constraints. The typical manual treatment planning process is iterative, time consuming, and highly dependent on the skill and experience of the planner. We have addressed this problem by developing a knowledgebased approach that utilizes a database of prior plans to leverage the planning expertise of physicians and physicists at our institution. We developed a case-similarity algorithm that uses mutual information to identify a similar matched case for a given query case, and various treatment parameters from the matched case are then adapted to derive new treatment plans that are patient specific.We used 10 randomly selected cases matched against a knowledge base of 100 cases to demonstrate that new, clinically acceptable IMRT treatment plans can be developed. This approach substantially reduced planning time by skipping all but the last few iterations of the optimization process. Additionally, we established a simple metric based on the areas under the curve (AUC) of the dose volume histogram (DVH), specifically for the planning target volume (PTV), rectum, and bladder. This plan quality metric was used to successfully rank order the plan quality of a collection of knowledgebased plans. Further, we used 100 pre-optimized plans (20 query x 5 matches) to show that the average normalized MI score can be used as a surrogate of overall plan quality.Plans of lower pre-optimized plan quality tended to improve substantially after optimization, though its final plan quality did not improve to the same level as a plan that has a higher pre-optimized plan quality to begin with. Optimization usually improved PTV coverage slightly while providing substantial dose sparing for both v bladder and rectum of 12.4% and 9.1% respectively. Lastly, we developed new treatment plans for cases selected from an outside institution matched against our sitespecific database. The knowledge-based plans are very comparable to the original manual plan, providing adequate PTV coverage as well as substantial improvement in dose sparing to the rectum and bladder.In conclusion, we found that a site-specific database of prior plans can be effectively used to design new treatment plans for our own institution as well as outside cases. Specifically, knowledge-based plans can provide clinically acceptable planning target volume coverage and clinically acceptable dose sparing to the rectum and bladder. This approach has been demonstrated to improve the efficiency of the treatment planning process, and may potentially improve the quality of patient care by enabling more consistent treatment planning across institutions.vi
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