An open environment CT-US fusion for tissue segmentation during interventional guidance.

Therapeutic ultrasound (US) can be noninvasively focused to activate drugs, ablate tumors and deliver drugs beyond the blood brain barrier. However, well-controlled guidance of US therapy requires fusion with a navigational modality, such as magnetic resonance imaging (MRI) or X-ray computed tomography (CT). Here, we developed and validated tissue characterization using a fusion between US and CT. The performance of the CT/US fusion was quantified by the calibration error, target registration error and fiducial registration error. Met-1 tumors in the fat pads of 12 female FVB mice provided a model of developing breast cancer with which to evaluate CT-based tissue segmentation. Hounsfield units (HU) within the tumor and surrounding fat pad were quantified, validated with histology and segmented for parametric analysis (fat: -300 to 0 HU, protein-rich: 1 to 300 HU, and bone: HU>300). Our open source CT/US fusion system differentiated soft tissue, bone and fat with a spatial accuracy of ∼1 mm. Region of interest (ROI) analysis of the tumor and surrounding fat pad using a 1 mm(2) ROI resulted in mean HU of 68±44 within the tumor and -97±52 within the fat pad adjacent to the tumor (p<0.005). The tumor area measured by CT and histology was correlated (r(2) = 0.92), while the area designated as fat decreased with increasing tumor size (r(2) = 0.51). Analysis of CT and histology images of the tumor and surrounding fat pad revealed an average percentage of fat of 65.3% vs. 75.2%, 36.5% vs. 48.4%, and 31.6% vs. 38.5% for tumors <75 mm(3), 75-150 mm(3) and >150 mm(3), respectively. Further, CT mapped bone-soft tissue interfaces near the acoustic beam during real-time imaging. Combined CT/US is a feasible method for guiding interventions by tracking the acoustic focus within a pre-acquired CT image volume and characterizing tissues proximal to and surrounding the acoustic focus

Expanding the use of real-time electromagnetic tracking in radiation oncology.

In the past 10 years, techniques to improve radiotherapy delivery, such as intensity-modulated radiation therapy (IMRT), image-guided radiation therapy (IGRT) for both inter- and intrafraction tumor localization, and hypofractionated delivery techniques such as stereotactic body radiation therapy (SBRT), have evolved tremendously. This review article focuses on only one part of that evolution, electromagnetic tracking in radiation therapy. Electromagnetic tracking is still a growing technology in radiation oncology and, as such, the clinical applications are limited, the expense is high, and the reimbursement is insufficient to cover these costs. At the same time, current experience with electromagnetic tracking applied to various clinical tumor sites indicates that the potential benefits of electromagnetic tracking could be significant for patients receiving radiation therapy. Daily use of these tracking systems is minimally invasive and delivers no additional ionizing radiation to the patient, and these systems can provide explicit tumor motion data. Although there are a number of technical and fiscal issues that need to be addressed, electromagnetic tracking systems are expected to play a continued role in improving the precision of radiation delivery

Optimization strategies for respiratory motion management in stereotactic body radiation therapy

Various challenges arise during the treatment of lung tumors with stereotactic body radiation therapy (SBRT), which is a form of hypofractionated high precision conformal radiation therapy delivered to small targets. The dose is applied in only a few fractions and respiratory organ and tumor motion is a source of uncertainty additional to interfractional set-up errors. Respiratory organ and tumor motion is highly patient-specific and it affects the whole radiotherapy treatment chain. In this thesis, motion management techniques for SBRT are evaluated and improved in a clinical setting. A clinical need for improvement has been present at the LMU university hospital for each issue addressed in this thesis: Initially, the usage of respiratory correlated computed tomography (4DCT), which is vital for SBRT treatment, was seen as impractical and prone to uncertainties in the data reconstruction in its current form. Therefore, the 4DCT reconstruction workflow has been improved to minimize these potential error sources. Secondly, treatment planning for tumors affected by respiratory motion was evaluated and subsequently improved. Finally, the treatment technique of respiratory gating was implemented at the clinic, which led to the need of evaluating the respiratory gating characteristics of the novel system configuration. At first, the 4DCT reconstruction workflow used in clinical practice was investigated, as in the presence of respiratory motion the knowledge of tumor position over time is essential in SBRT treatments. Using 4DCT, the full motion range of the individual tumor can be determined. However, certain 4DCT reconstruction methods can under- or overestimate tumor motion due to limitations in the data acquisition scheme and due to the incorrect sorting of certain X-ray computed tomography (CT) image slices into different respiratory phases. As the regular clinical workflow of cycle-based sorting (CBS) without maximum inspiration detection (and therefore no clear starting point for the individual breathing cycles) seemed to be affected by these potential errors, the usage of CBS with correct maximum detection and another sorting algorithm of the respiration states, so-called local amplitude-based sorting (LAS), both have been implemented for a reduction of image artifacts and improved 4DCT quality. The three phase binning algorithms have been investigated in a phantom study (using 10 different breathing waveforms) and in a patient study (with 10 different patients). The mis-representation of the tumor volume was reduced in both implemented sorting algorithms compared to the previously used CBS approach (without correct maximum detection) in the phantom and the patient study. The clinical recommendation was the use of CBS with improved maximum detection, as too many manual interventions would be needed for the LAS workflow. Secondly, a combination of the actual patient breathing trace during treatment, the log files generated by the linear accelerator (LINAC), and Monte Carlo (MC) four-dimensional (4D) dose calculations for each individual fraction was implemented as a 4D dose evaluation tool. This workflow was tested in a clinical environment for SBRT treatment planning on multiple CT datasets featuring: a native free-breathing 3DCT, an average intensity projection (AIP) as well as a maximum intensity projection (MIP), both obtained from the patient's 4DCT, and density overrides (DOs) in a 3DCT. This study has been carried out for 5 SBRT patients for three-dimensional conformal radiation therapy (3D-CRT) and volumetric modulated arc therapy (VMAT) treatment plans. The dose has been recalculated on each 4DCT breathing phase according the the patient's breathing waveform and accumulated to the gross tumor volume (GTV) at the end-of-exhale (EOE) breathing phase using deformable image registration. Even though the least differences in planned and recalculated dose were found for AIP and MIP treatment planning, the results indicate a strong dependency on individual tumor motion due to the variability of breathing motion in general, and on tumor size. The combination of the patient's individual breathing trace during each SBRT fraction with 4D MC dose calculation based on the LINAC log file information leads to a good approximation of actual dose delivery. Finally, in order to ensure precise and accurate treatment for respiratory gating techniques, the technical characteristics of the LINAC in combination with a breathing motion monitoring system as s surrogate for tumor motion have to be identified. The dose delivery accuracy and the latency of a surface imaging system in connection with a modern medical LINAC were investigated using a dynamic breathing motion phantom. The dosimetric evaluation has been carried out using a static 2D-diode array. The measurement of the dose difference between gated and ungated radiation delivery was found to be below 1% (for clinical relevant gating levels of about 30%). The beam-on latency, or time delay, determined using radiographic films was found to be up to 851 ms±100 ms. With these known parameters, an adjustment of the pre-selected gating level or the internal target volume (ITV) margins could be made. With the highly patient-specific character of respiratory motion, lung SBRT faces many additional challenges besides the specific issues addressed in this thesis. However, the findings of this thesis have improved clinical workflows at the Department of Radiation Oncology of the LMU University hospital. In a future perspective, a workflow using evaluation of the actual 4D dose in combination with accurate 4DCT image acquisition and specialized treatment delivery (such as respiratory gating) has the potential for a safe further reduction of treatment margins and increased sparing of organs-at-risk (OARs) in SBRT without compromising tumor dose targeting accuracy

Evaluation of Radiation Dose-Response in a Breast Cancer Brain Metastasis Model

The second incidence of brain metastases is from breast cancer. Radiotherapy, a standard treatment for brain metastasis, limits cancer division by inducing DNA double-stranded breaks (DSBs). Currently, identical radiation doses are prescribed for all types of brain metastases but little is known about their histological responses. In this thesis, we initiated a radiation dose-response study in a triple-negative human breast cancer brain metastasis mouse model using a custom designed 3D-printed restrainer to assist half-brain irradiation. We quantified the amount of DSBs in tumors and mouse brain tissues using γ-H2AX marker at 30 minutes (acute) and 11 days (longitudinal) after treatment with doses of 8-24 Gy. We also evaluated tumors’ response using histology and MRI. In the longitudinal study we found significant differences in the amount of DSBs, tumor cell density, and nucleus size between irradiated surviving and non-irradiated tumors. These results gave insights to brain metastasis response after radiotherapy

Impact of residual and intrafractional errors on strategy of correction for image-guided accelerated partial breast irradiation

<p>Abstract</p> <p>Background</p> <p>The cone beam CT (CBCT) guided radiation can reduce the systematic and random setup errors as compared to the skin-mark setup. However, the residual and intrafractional (RAIF) errors are still unknown. The purpose of this paper is to investigate the magnitude of RAIF errors and correction action levels needed in cone beam computed tomography (CBCT) guided accelerated partial breast irradiation (APBI).</p> <p>Methods</p> <p>Ten patients were enrolled in the prospective study of CBCT guided APBI. The postoperative tumor bed was irradiated with 38.5 Gy in 10 fractions over 5 days. Two cone-beam CT data sets were obtained with one before and one after the treatment delivery. The CBCT images were registered online to the planning CT images using the automatic algorithm followed by a fine manual adjustment. An action level of 3 mm, meaning that corrections were performed for translations exceeding 3 mm, was implemented in clinical treatments. Based on the acquired data, different correction action levels were simulated, and random RAIF errors, systematic RAIF errors and related margins before and after the treatments were determined for varying correction action levels.</p> <p>Results</p> <p>A total of 75 pairs of CBCT data sets were analyzed. The systematic and random setup errors based on skin-mark setup prior to treatment delivery were 2.1 mm and 1.8 mm in the lateral (LR), 3.1 mm and 2.3 mm in the superior-inferior (SI), and 2.3 mm and 2.0 mm in the anterior-posterior (AP) directions. With the 3 mm correction action level, the systematic and random RAIF errors were 2.5 mm and 2.3 mm in the LR direction, 2.3 mm and 2.3 mm in the SI direction, and 2.3 mm and 2.2 mm in the AP direction after treatments delivery. Accordingly, the margins for correction action levels of 3 mm, 4 mm, 5 mm, 6 mm and no correction were 7.9 mm, 8.0 mm, 8.0 mm, 7.9 mm and 8.0 mm in the LR direction; 6.4 mm, 7.1 mm, 7.9 mm, 9.2 mm and 10.5 mm in the SI direction; 7.6 mm, 7.9 mm, 9.4 mm, 10.1 mm and 12.7 mm in the AP direction, respectively.</p> <p>Conclusions</p> <p>Residual and intrafractional errors can significantly affect the accuracy of image-guided APBI with nonplanar 3DCRT techniques. If a 10-mm CTV-PTV margin is applied, a correction action level of 5 mm or less is necessary so as to maintain the RAIF errors within 10 mm for more than 95% of fractions. Pre-treatment CBCT guidance is not a guarantee for safe delivery of the treatment despite its known benefits of reducing the initial setup errors. A patient position verification and correction during the treatment may be a method for the safe delivery.</p

Optimization strategies for respiratory motion management in stereotactic body radiation therapy

Various challenges arise during the treatment of lung tumors with stereotactic body radiation therapy (SBRT), which is a form of hypofractionated high precision conformal radiation therapy delivered to small targets. The dose is applied in only a few fractions and respiratory organ and tumor motion is a source of uncertainty additional to interfractional set-up errors. Respiratory organ and tumor motion is highly patient-specific and it affects the whole radiotherapy treatment chain. In this thesis, motion management techniques for SBRT are evaluated and improved in a clinical setting. A clinical need for improvement has been present at the LMU university hospital for each issue addressed in this thesis: Initially, the usage of respiratory correlated computed tomography (4DCT), which is vital for SBRT treatment, was seen as impractical and prone to uncertainties in the data reconstruction in its current form. Therefore, the 4DCT reconstruction workflow has been improved to minimize these potential error sources. Secondly, treatment planning for tumors affected by respiratory motion was evaluated and subsequently improved. Finally, the treatment technique of respiratory gating was implemented at the clinic, which led to the need of evaluating the respiratory gating characteristics of the novel system configuration. At first, the 4DCT reconstruction workflow used in clinical practice was investigated, as in the presence of respiratory motion the knowledge of tumor position over time is essential in SBRT treatments. Using 4DCT, the full motion range of the individual tumor can be determined. However, certain 4DCT reconstruction methods can under- or overestimate tumor motion due to limitations in the data acquisition scheme and due to the incorrect sorting of certain X-ray computed tomography (CT) image slices into different respiratory phases. As the regular clinical workflow of cycle-based sorting (CBS) without maximum inspiration detection (and therefore no clear starting point for the individual breathing cycles) seemed to be affected by these potential errors, the usage of CBS with correct maximum detection and another sorting algorithm of the respiration states, so-called local amplitude-based sorting (LAS), both have been implemented for a reduction of image artifacts and improved 4DCT quality. The three phase binning algorithms have been investigated in a phantom study (using 10 different breathing waveforms) and in a patient study (with 10 different patients). The mis-representation of the tumor volume was reduced in both implemented sorting algorithms compared to the previously used CBS approach (without correct maximum detection) in the phantom and the patient study. The clinical recommendation was the use of CBS with improved maximum detection, as too many manual interventions would be needed for the LAS workflow. Secondly, a combination of the actual patient breathing trace during treatment, the log files generated by the linear accelerator (LINAC), and Monte Carlo (MC) four-dimensional (4D) dose calculations for each individual fraction was implemented as a 4D dose evaluation tool. This workflow was tested in a clinical environment for SBRT treatment planning on multiple CT datasets featuring: a native free-breathing 3DCT, an average intensity projection (AIP) as well as a maximum intensity projection (MIP), both obtained from the patient's 4DCT, and density overrides (DOs) in a 3DCT. This study has been carried out for 5 SBRT patients for three-dimensional conformal radiation therapy (3D-CRT) and volumetric modulated arc therapy (VMAT) treatment plans. The dose has been recalculated on each 4DCT breathing phase according the the patient's breathing waveform and accumulated to the gross tumor volume (GTV) at the end-of-exhale (EOE) breathing phase using deformable image registration. Even though the least differences in planned and recalculated dose were found for AIP and MIP treatment planning, the results indicate a strong dependency on individual tumor motion due to the variability of breathing motion in general, and on tumor size. The combination of the patient's individual breathing trace during each SBRT fraction with 4D MC dose calculation based on the LINAC log file information leads to a good approximation of actual dose delivery. Finally, in order to ensure precise and accurate treatment for respiratory gating techniques, the technical characteristics of the LINAC in combination with a breathing motion monitoring system as s surrogate for tumor motion have to be identified. The dose delivery accuracy and the latency of a surface imaging system in connection with a modern medical LINAC were investigated using a dynamic breathing motion phantom. The dosimetric evaluation has been carried out using a static 2D-diode array. The measurement of the dose difference between gated and ungated radiation delivery was found to be below 1% (for clinical relevant gating levels of about 30%). The beam-on latency, or time delay, determined using radiographic films was found to be up to 851 ms±100 ms. With these known parameters, an adjustment of the pre-selected gating level or the internal target volume (ITV) margins could be made. With the highly patient-specific character of respiratory motion, lung SBRT faces many additional challenges besides the specific issues addressed in this thesis. However, the findings of this thesis have improved clinical workflows at the Department of Radiation Oncology of the LMU University hospital. In a future perspective, a workflow using evaluation of the actual 4D dose in combination with accurate 4DCT image acquisition and specialized treatment delivery (such as respiratory gating) has the potential for a safe further reduction of treatment margins and increased sparing of organs-at-risk (OARs) in SBRT without compromising tumor dose targeting accuracy

Anatomical Segmentation of CT images for Radiation Therapy planning using Deep Learning

Radiation therapy is one of the key cancer treatment options. To avoid adverse effect in tissue surrounding the tumor, the treatment plan needs to be based on accurate anatomical models of the patient. In this thesis, an automatic segmentation solution is constructed for the female breast, the female pelvis and the male pelvis using deep learning. The deep neural networks applied performed as well as the current state of the art networks while improving inference speed by a factor of 15 to 45. The speed increase was gained through processing the whole 3D image at once. The segmentations done by clinicians usually take several hours, whereas the automatic segmentation can be done in less than a second. Therefore, the automatic segmentation provides options for adaptive treatment planning