Evaluation of inter- and intrafractional motion of liver tumors using interstitial markers and implantable electromagnetic radiotransmitters in the context of image-guided radiotherapy (IGRT) – the ESMERALDA trial

Background: With the development of more conformal and precise radiation techniques such as Intensity-Modulated Radiotherapy (IMRT), Stereotactic Body Radiotherapy (SBRT) and Image-Guided Radiotherapy (IGRT), patients with hepatic tumors could be treated with high local doses by sparing normal liver tissue. However, frequently occurring large HCC tumors are still a dosimetric challenge in spite of modern high sophisticated RT modalities. This interventional clinical study has been set up to evaluate the value of different fiducial markers, and to use the modern imaging methods for further treatment optimization using physical and informatics approaches. Methods and design: Surgically implanted radioopaque or electromagnetic markers are used to detect tumor local-ization during radiotherapy. The required markers for targeting and observation during RT can be implanted in a previously defined optimal position during the oncologically indicated operation. If there is no indication for a surgical resection or open biopsy, markers may be inserted into the liver or tumor tissue by using ultrasound-guidance. Primary study aim is the detection of the patients´ anatomy at the time of RT by observation of the marker position during the indicated irradiation (IGRT). Secondary study aims comprise detection and recording of 3D liver and tumor motion during RT. Furthermore, the study will help to develop technical strategies and mechanisms based on the recorded information on organ motion to avoid inaccurate dose application resulting from fast organ motion and deformation. Discussion: This is an open monocentric non-randomized, prospective study for the evaluation of organ motion using interstitial markers or implantable radiotransmitter. The trial will evaluate the full potential of different fiducial markers to further optimize treatment of moving targets, with a special focus on liver lesions

Analyzing human decisions in IGRT of head-and-neck cancer patients to teach image registration algorithms what experts know

Background: In IGRT of deformable head-and-neck anatomy, patient setup corrections are derived by rigid registration methods. In practice, experienced radiation therapists often correct the resulting vectors, thus indicating a different prioritization of alignment of local structures. Purpose of this study is to transfer the knowledge experts apply when correcting the automatically generated result (pre-match) to automated registration. Methods: Datasets of 25 head-and-neck-cancer patients with daily CBCTs and corresponding approved setup correction vectors were analyzed. Local similarity measures were evaluated to identify the criteria for human corrections with regard to alignment quality, analogous to the radiomics approach. Clustering of similarity improvement patterns is applied to reveal priorities in the alignment quality. Results: The radiation therapists prioritized to align the spinal cord closest to the high-dose area. Both target volumes followed with second and third highest priority. The bony pre-match influenced the human correction along the crania-caudal axis. Based on the extracted priorities, a new rigid registration procedure is constructed which is capable of reproducing the corrections of experts. Conclusions: The proposed approach extracts knowledge of experts performing IGRT corrections to enable new rigid registration methods that are capable of mimicking human decisions. In the future, the deduction of knowledge-based corrections for different cohorts can be established automating such supervised learning approaches

Correction of patient positioning errors based on in-line cone beam CTs: clinical implementation and first experiences

BACKGROUND: The purpose of the study was the clinical implementation of a kV cone beam CT (CBCT) for setup correction in radiotherapy. PATIENTS AND METHODS: For evaluation of the setup correction workflow, six tumor patients (lung cancer, sacral chordoma, head-and-neck and paraspinal tumor, and two prostate cancer patients) were selected. All patients were treated with fractionated stereotactic radiotherapy, five of them with intensity modulated radiotherapy (IMRT). For patient fixation, a scotch cast body frame or a vacuum pillow, each in combination with a scotch cast head mask, were used. The imaging equipment, consisting of an x-ray tube and a flat panel imager (FPI), was attached to a Siemens linear accelerator according to the in-line approach, i.e. with the imaging beam mounted opposite to the treatment beam sharing the same isocenter. For dose delivery, the treatment beam has to traverse the FPI which is mounted in the accessory tray below the multi-leaf collimator. For each patient, a predefined number of imaging projections over a range of at least 200 degrees were acquired. The fast reconstruction of the 3D-CBCT dataset was done with an implementation of the Feldkamp-David-Kress (FDK) algorithm. For the registration of the treatment planning CT with the acquired CBCT, an automatic mutual information matcher and manual matching was used. RESULTS AND DISCUSSION: Bony landmarks were easily detected and the table shifts for correction of setup deviations could be automatically calculated in all cases. The image quality was sufficient for a visual comparison of the desired target point with the isocenter visible on the CBCT. Soft tissue contrast was problematic for the prostate of an obese patient, but good in the lung tumor case. The detected maximum setup deviation was 3 mm for patients fixated with the body frame, and 6 mm for patients positioned in the vacuum pillow. Using an action level of 2 mm translational error, a target point correction was carried out in 4 cases. The additional workload of the described workflow compared to a normal treatment fraction led to an extra time of about 10–12 minutes, which can be further reduced by streamlining the different steps. CONCLUSION: The cone beam CT attached to a LINAC allows the acquisition of a CT scan of the patient in treatment position directly before treatment. Its image quality is sufficient for determining target point correction vectors. With the presented workflow, a target point correction within a clinically reasonable time frame is possible. This increases the treatment precision, and potentially the complex patient fixation techniques will become dispensable

Tissue-specific transformation model for CT-images

During radiotherapy, posture changes and volume changing deformations like growing or shrinking tissue result in anatomical deformations. The basis for investigating the impact of such deformations on dose uncertainties, are model-based tools for deformation analysis. In this context, we propose a transformation model based on the information of CT-images, which allows an on-the-fly calculation of voxel volumes. Our model is based on the concept of the chainmail algorithm and describes deformation on voxel-level. With an exemplary input of a set of landmark pairs, generated by a kinematic head-and-neck skeleton model, CT-images (512x512x126 voxel) can be deformed with an on-the-fly volume calculation in less than 70s. The volume calculation delivers insight into model-characteristic volume changes and is a prerequisite for implementing tissue growth and shrinkage