Imaging opportunities for treatment planning in intraoperative electron beam radiotherapy (IOERT): Developments in the context of RADIANCE system

Soft-tissue simulation of the breast for intraoperative navigation and fusion of preoperative planning

Computational preoperative planning offers the opportunity to reduce surgery time and patient risk. However, on soft tissues such as the breast, deviations between the preoperative and intraoperative settings largely limit the applicability of preoperative planning. In this work, we propose a high-performance accurate simulation model of the breast, to fuse preoperative information with the intraoperative deformation setting. Our simulation method encompasses three major elements: high-quality finite-element modeling (FEM), efficient handling of anatomical couplings for high-performance computation, and personalized parameter estimation from surface scans. We show the applicability of our method on two problems: 1) transforming high-quality preoperative scans to the intraoperative setting for fusion of preoperative planning data, and 2) real-time tracking of breast tumors for navigation during intraoperative radiotherapy. We have validated our methodology on a test cohort of nine patients who underwent tumor resection surgery and intraoperative radiotherapy, and we have quantitatively compared simulation results to intraoperative scans. The accuracy of our simulation results suggest clinical viability of the proposed methodology.

Practical issues regarding angular and energy response in in vivo intraoperative electron radiotherapy dosimetry

AIM

To estimate angular response deviation of MOSFETs in the realm of intraoperative electron radiotherapy (IOERT), review their energy dependence, and propose unambiguous names for detector rotations.

BACKGROUND

MOSFETs have been used in IOERT. Movement of the detector, namely rotations, can spoil results.

MATERIALS AND METHODS

We propose yaw, pitch, and roll to name the three possible rotations in space, as these unequivocally name aircraft rotations. Reinforced mobile MOSFETs (model TN-502RDM-H) and an Elekta Precise linear accelerator were used. Two detectors were placed in air for the angular response study and the whole set of five detectors was calibrated as usual to evaluate energy dependence.

RESULTS

The maximum readout was obtained with a roll of 90° and 4 MeV. With regard to pitch movement, a substantial drop in readout was achieved at 90°. Significant overresponse was measured at 315° with 4 MeV and at 45° with 15 MeV. Energy response is not different for the following groups of energies: 4, 6, and 9 MeV; and 12 MeV, 15 MeV, and 18 MeV.

CONCLUSIONS

Our proposal to name MOSFET rotations solves the problem of defining sensor orientations. Angular response could explain lower than expected results when the tip of the detector is lifted due to inadvertent movements. MOSFETs energy response is independent of several energies and differs by a maximum of 3.4% when dependent. This can limit dosimetry errors and makes it possible to calibrate the detectors only once for each group of energies, which saves time and optimizes lifespan of MOSFETs.

Defining Action Levels for In Vivo Dosimetry in Intraoperative Electron Radiotherapy

In vivo dosimetry is recommended in intraoperative electron radiotherapy (IOERT). To perform real-time treatment monitoring, action levels (ALs) have to be calculated. Empirical approaches based on observation of samples have been reported previously, however, our aim is to present a predictive model for calculating ALs and to verify their validity with our experimental data. We considered the range of absorbed doses delivered to our detector by means of the percentage depth dose for the electron beams used. Then, we calculated the absorbed dose histograms and convoluted them with detector responses to obtain probability density functions in order to find ALs as certain probability levels. Our in vivo dosimeters were reinforced TN-502RDM-H mobile metal-oxide-semiconductor field-effect transistors (MOSFETs). Our experimental data came from 30 measurements carried out in patients undergoing IOERT for rectal, breast, sarcoma, and pancreas cancers, among others. The prescribed dose to the tumor bed was 90%, and the maximum absorbed dose was 100%. The theoretical mean absorbed dose was 90.3% and the measured mean was 93.9%. Associated confidence intervals at P = .05 were 89.2% and 91.4% and 91.6% and 96.4%, respectively. With regard to individual comparisons between the model and the experiment, 37% of MOSFET measurements lay outside particular ranges defined by the derived ALs. Calculated confidence intervals at P = .05 ranged from 8.6% to 14.7%. The model can describe global results successfully but cannot match all the experimental data reported. In terms of accuracy, this suggests an eventual underestimation of tumor bed bleeding or detector alignment. In terms of precision, it will be necessary to reduce positioning uncertainties for a wide set of location and treatment postures, and more precise detectors will be required. Planning and imaging tools currently under development will play a fundamental role.

Feasibility assessment of the interactive use of a Monte Carlo algorithm in treatment planning for intraoperative electron radiation therapy

This work analysed the feasibility of using a fast, customized Monte Carlo (MC) method to perform accurate computation of dose distributions during pre- and intraplanning of intraoperative electron radiation therapy (IOERT) procedures. The MC method that was implemented, which has been integrated into a specific innovative simulation and planning tool, is able to simulate the fate of thousands of particles per second, and it was the aim of this work to determine the level of interactivity that could be achieved. The planning workflow enabled calibration of the imaging and treatment equipment, as well as manipulation of the surgical frame and insertion of the protection shields around the organs at risk and other beam modifiers. In this way, the multidisciplinary team involved in IOERT has all the tools necessary to perform complex MC dosage simulations adapted to their equipment in an efficient and transparent way. To assess the accuracy and reliability of this MC technique, dose distributions for a monoenergetic source were compared with those obtained using a general-purpose software package used widely in medical physics applications. Once accuracy of the underlying simulator was confirmed, a clinical accelerator was modelled and experimental measurements in water were conducted. A comparison was made with the output from the simulator to identify the conditions under which accurate dose estimations could be obtained in less than 3 min, which is the threshold imposed to allow for interactive use of the tool in treatment planning. Finally, a clinically relevant scenario, namely early-stage breast cancer treatment, was simulated with pre- and intraoperative volumes to verify that it was feasible to use the MC tool intraoperatively and to adjust dose delivery based on the simulation output, without compromising accuracy. The workflow provided a satisfactory model of the treatment head and the imaging system, enabling proper configuration of the treatment planning system and providing good accuracy in the dosage simulation.