The primary distinction between real-time and off-line image-guided adaptive radiotherapy is that the latter uses software to control radiation therapy. For example, real-time image-guided adaptive radiotherapy will necessitate a more sophisticated model with stopping rules to halt treatment when the deviation from the treatment plan reaches a certain threshold. Aside from the advantages of real-time image-guided adaptive radiotherapy, the latter will necessitate a more complex model capable of performing more advanced tasks, such as patient monitoring.
Offline adaptive radiotherapy is more complicated than online adaptive radiotherapy. Previously, programming for offline adaptive radiotherapy relied primarily on manual calculations, but it now requires the assistance of sophisticated software. MIM software, for example, enables clinicians to project final doses and keep track of daily doses. This allows them to create boost plans and make off-line adaptive radiotherapy clinically manageable. The benefits and drawbacks of off-line adaptive radiotherapy will be discussed in this article.
CBCT is the most commonly used imaging modality in oncology. It assists radiotherapists in tailoring a radiotherapy plan to the patient's body mass. Because the amount of soft tissue surrounding the target can vary by several centimeters, using data from CBCT scans is an effective method. Every day, CBCT images are taken to build a library of plans for a single patient.
The goal of intensity-modulated radiation therapy (IMRT) is to deliver high doses to tumors while sparing healthy tissue. Optimization-based treatment planning results in sharp dose gradients between tumors and healthy tissues. Furthermore, random shifts during the treatment process can result in significant dose differences between the two groups. As a result, IMRT treatment plans deliver the dose in small fractions over a 35-day period.
The model formulation for off-line adaptive radiotherapy necessitates careful consideration of all aspects of the treatment. In general, it is advised to select the online adaptation well before the start of treatment. It also necessitates meticulous planning and the participation of physicians and physicists. In most cases, this technique works best in predictable situations, such as stereotactic body radiotherapy. This technique is especially useful when daily anatomic changes are predictable, such as those associated with bowel filling or peristalsis.
Offline ART relies on high-quality imaging to detect changes that necessitate offline treatment. Some changes are visible without images, such as weight loss or volume changes in superficial tumors. Other changes, such as internal anatomy, necessitate imaging for visualization. Standard cone-beam CT technology, which is available in most modern medical linear accelerators, is useful for detecting changes in the volume of a lung tumor, an exophytic lesion, or a fiducial marker. Furthermore, planar X-ray imaging can detect changes in fiducial markers. Planar X-ray imaging can also detect fiducial marker motion using auxiliary detector systems.
The study also compared adaptive plans to non-adaptive ones. The results showed that the adaptive plan reduced the amount of time patients spent on the treatment table and improved resource allocation. The clinical threshold for adaptation in the study will be determined by the location of treatment, type of treatment, and organ-at-risk. Pre-specified criteria can also help to avoid indecision at the time of delivery. They are an important step in optimizing off-line adaptive radiotherapy.
Off-line adaptive radiotherapy is a type of radiation therapy in which the treatment plan is chosen by a radiation oncologist after considering various trade-offs. It is given in multiple sessions to a large number of cancer patients. Optimization models aid physicians in achieving the best possible outcomes for each patient. An optimization model, for example, can optimize the dose for a specific tumor while protecting healthy tissues.
Stochastic control refers to optimization techniques that use the LQR model to determine treatment plans. The authors estimate the tumor response using either a log-linear cell kill model or a standard LQ model. Their goal is to reduce the number of tumor cells at the end of treatment. Their method focuses on beam intensities and fixed sessions to achieve optimal treatment planning. Constrained optimization methods for off-line adaptive radiotherapy are not only based on tumor response criteria, but they are also computationally efficient.
The offline ART planning process is similar to the standard clinical workflow. Typically, the angle of the beam in an adaptive plan is close to the patient's initial position during simulation. However, because the patient's organs and targets will be moving during treatment, a solid plan is required to account for these changes. For example, gastrointestinal OARs can move closer to the target than their initial position on a given day. Non-adaptive planning prioritizes the OARs that are closest to the target, but this is not the case with online adaptation.