Inverse problems in radiation cancer therapy

One of the most remarkable realizations in the field of inverse problems was the invention of an inversion algorithm for Computed Tomography (CT) and its experimental demonstration in CT imaging. After five decades of its invention, CT has become the primary imaging modality for radiation therapy dose calculations and image guidance for accurate dose localization in patients for the last two decades. After the invention of CT imaging, another inverse (optimization) method, namely, intensity modulated radiation therapy (IMRT) and in its more recent version- volumetric arc therapy (VMAT) have arguably made the most profound impact in the field of radiation therapy in terms of the ability to exquisitely shape dose distributions delivered to patients for treatment of various diseases. In IMRT, radiation beams are divided into many small beamlets, whose intensities are individually adjusted in order to deliver a dose of radiation that conforms to the shape of the tumor. Having the availability of the physical and biological parameters of the irradiated object (patient) and the specifications of the treatment machine, finding the radiation intensity function (individual beamlets) from a desired dose distribution prescribed by the physician is the inverse problem in IMRT. In clinical applications, robust decision making about the optimality of the solution, deliverability, and organ motion are some of the factors that confound the problem. This presentation will provide an overview of the inverse planning process in radiation therapy and the current state of its relevant issues prom the perspective of a practicing clinical physicist.