Radiation treatment planning
In radiotherapy, radiation treatment planning is the process in which a team consisting of radiation oncologists, radiation therapist, medical physicists and medical dosimetrists plan the appropriate external beam radiotherapy or internal brachytherapy treatment technique for a patient with cancer.
Typically, medical imaging (i.e., x-ray computed tomography often the primary image set for treatment planning, magnetic resonance imaging excellent secondary image set for soft tissue contouring, and positron emission tomography less commonly used and reserved for cases where specific uptake studies can enhance planning target volume delineation) are used to form a virtual patient for a computer-aided design procedure. Treatment simulations are used to plan the geometric, radiological, and dosimetric aspects of the therapy using radiation transport simulations and optimization. For intensity modulated radiation therapy (IMRT), this process involves selecting the appropriate beam energy (photons, and perhaps protons), energy (e.g. 6 MV, 18 MV) and arrangements. For brachytherapy, involves selecting the appropriate catheter positions and source dwell times  (in HDR brachytherapy) or seeds positions (in LDR brachytherapy). The more formal optimization process is typically referred to as forward planning and inverse planning. Plans are often assessed with the aid of dose-volume histograms, allowing the clinician to evaluate the uniformity of the dose to the diseased tissue (tumor) and sparing of healthy structures.
Today, treatment planning is almost entirely computer based using patient computed tomography (CT) data sets. Modern treatment planning systems provide tools for multimodality image matching, also known as image coregistration or fusion.
Forward planning is a technique used in external-beam radiotherapy to produce a treatment plan. In forward planning, a treatment [Dosimetrist] places beams into a radiotherapy treatment planning system which can deliver sufficient radiation to a tumour while both sparing critical organs and minimising the dose to healthy tissue. The required decisions include how many radiation beams to use, which angles each will be delivered from, whether attenuating wedges be used, and which multileaf collimator configuration will be used to shape the radiation from each beam.
Once the treatment planner has made an initial plan, the treatment planning system calculates the required monitor units to deliver a prescribed dose to a specific area in the patient which is dependent on beam modifiers that include wedges, specialized collimation, field sizes, tumor depth, etc. The information from a prior CT scan of the patient allows more accurate modeling of the behaviour of the radiation as it travels through the patient's tissues. Different dose prediction models are available, including pencil beam, convolution-superposition and monte carlo simulation, with precision versus computation time being the relevant trade-off.
This type of planning is used for the majority of external-beam radiotherapy treatments, but is only sufficiently adept to handle relatively simple cases—cases in which the tumour has a simple shape and is not near any critical organs. For more sophisticated plans, inverse planning is used to create an intensity-modulated treatment plan. This is now also used as a part of post-mastectomy radiotherapy (PMRT) planning.
Inverse planning is a technique used to design a radiotherapy treatment plan. A radiation oncologist defines a patient's critical organs and tumour then a dosimetrist gives target doses and importance factors for each. Then, an optimisation program is run to find the treatment plan which best matches all the input criteria.
- Karabis, A; Belloti, P; Baltas, D (2009). O. Dössel and W.C. Schlegel, eds. Optimization of Catheter Position and Dwell Time in Prostate HDR Brachytherapy using HIPO and Linear Programming. World Congress on Medical Physics and Biomedical Engineering. IFMBE Proceedings 25 (1) (Munich). pp. 612–615. doi:10.1007/978-3-642-03474-9_172.
- Lahanas, M; Baltas, D; Giannouli, S (7 March 2003). "Global convergence analysis of fast multiobjective gradient-based dose optimization algorithms for high-dose-rate brachytherapy.". Physics in medicine and biology 48 (5): 599–617. doi:10.1088/0031-9155/48/5/304. PMID 12696798.
- Galvin, James M; Ezzell, Gary; Eisbrauch, Avraham; Yu, Cedric; Butler, Brian; Xiao, Ying; Rosen, Isaac; Rosenman, Julian; Sharpe, Michael; Xing, Lei; Xia, Ping; Lomax, Tony; Low, Daniel A; Palta, Jatinder (April 2004), "Implementing IMRT in clinical practice: a joint document of the American Society for Therapeutic Radiology and Oncology and the American Association of Physicists in Medicine.", Int J Radiat Oncol Biol Phys. 58 (5), pp. 1616–34., doi:10.1016/j.ijrobp.2003.12.008, PMID 15050343
- Hendee W., Ibbott G. and Hendee E. (2005). Radiation Therapy Physics. Wiley-Liss Publ. ISBN 0-471-39493-9.
- Gintz, D; Latifi, K; Caudell, J; Nelms, B; Zhang, G; Moros, E; Feygelman, V (8 May 2016). "Initial evaluation of automated treatment planning software.". Journal of applied clinical medical physics 17 (3): 6167. doi:10.1120/jacmp.v17i3.6167. PMID 27167292.