Biomedical subjects

Tiezhi Zhang

Publications and source records attributed to Tiezhi Zhang.

6 recordsLinked to original sources

PubMed2006

Clinical implementation of target tracking by breathing synchronized delivery.

Target-tracking techniques can be categorized based on the mechanism of the feedback loop. In real time tracking, breathing-delivery phase correlation is provided to the treatment delivery hardware. Clinical implementation of target tracking in real time requires major hardware modifications. In breathing synchronized delivery (BSD), the patient is guided to breathe in accordance with target motion derived from four-dimensional computed tomography (4D-CT). Violations of mechanical limitations of hardware are to be avoided at the treatment planning stage. Hardware modifications are not required. In this article, using sliding window IMRT delivery as an example, we have described step-by-step the implementation of target tracking by the BSD technique: (1) A breathing guide is developed from patient's normal breathing pattern. The patient tries to reproduce this guiding cycle by following the display in the goggles; (2) 4D-CT scans are acquired at all the phases of the breathing cycle; (3) The average tumor trajectory is obtained by deformable image registration of 4D-CT datasets and is smoothed by Fourier filtering; (4) Conventional IMRT planning is performed using the images at reference phase (full exhalation phase) and a leaf sequence based on optimized fluence map is generated; (5) Assuming the patient breathes with a reproducible breathing pattern and the machine maintains a constant dose rate, the treatment process is correlated with the breathing phase; (6) The instantaneous average tumor displacement is overlaid on the dMLC position at corresponding phase; and (7) DMLC leaf speed and acceleration are evaluated to ensure treatment delivery. A custom-built mobile phantom driven by a computer-controlled stepper motor was used in the dosimetry verification. A stepper motor was programmed such that the phantom moved according to the linear component of tumor motion used in BSD treatment planning. A conventional plan was delivered on the phantom with and without motion. The BSD plan was also delivered on the phantom that moved with the prescheduled pattern and synchronized with the delivery of each beam. Film dosimetry showed underdose and overdose in the superior and inferior regions of the target, respectively, if the tumor motion is not compensated during the delivery. BSD delivery resulted in a dose distribution very similar to the planned treatments.

Algorithms↗

PubMed2005

On the automated definition of mobile target volumes from 4D-CT images for stereotactic body radiotherapy.

Stereotactic body radiotherapy (SBRT) can be used to treat small lesions in the chest. A vacuum-based immobilization system is used in our clinic for SBRT, and a motion envelope is used in treatment planning. The purpose of this study is to automatically derive motion envelopes using deformable image registration of 4D-CT images, and to assess the effect of abdominal pressure on the motion envelopes. 4D-CT scans at ten phases were acquired prior to treatment for both free and restricted breathing using a vacuum-based immobilization system that includes an abdominal pressure pillow. To study the stability of the motion envelope over the course of treatment, a mid-treatment 4D-CT scan was obtained after delivery of the third fraction for two patients. The planning target volume excluding breathing motion (PTV(ex)) was defined on the image set at full exhalation phase and transformed into all other phases using displacement maps from deformable image registration. The motion envelope was obtained as the union of PTV(ex) masks of all phases. The ratios of the motion envelope to PTV(ex) volume ranged from 1.3 to 2.5. When pressure was applied, the ratios were reduced by as much as 29% compared to free breathing for some patients, but increased by up to 9% for others. The abdominal pressure pillow has more motion restriction effects on the anterior/inferior region of the lung. For one of the two patients for whom the 4D-CT scan was repeated at mid-treatment, the motion envelope was reproducible. However, for the other patient the tumor location and lung motion pattern significantly changed due to changes in the anatomy surrounding the tumor during the course of treatment, indicating that an image-guided approach to SBRT may increase the efficacy of this treatment.

Algorithms↗

PubMed2005

Potential for radiation therapy technology innovations to permit dose escalation for non-small-cell lung cancer.

BACKGROUND: Innovations in radiation therapy (RT) technology could have the potential to allow for radiation dose escalation by evaluating tumor motion, minimizing and compensating for motion, and evaluating delivery technologies such as 3-dimensional (3D) conformal radiation therapy (CRT) and intensity-modulated RT (IMRT) using tomotherapy. MATERIALS AND METHODS: Ninety different RT plans were generated using 3 different treatment techniques for 10 patients. These were evaluated using dosimetric tools such as dose-volume histogram (DVH) analysis, tumor equivalent uniform dose (EUD), and dosimetric parameters predictive for lung toxicity, such as the volume of lung receiving > 20 Gy of radiation (V20) and the normalized mean total radiation dose to the lung (NTDmean). The 3 techniques studied included free breathing using 3D CRT, 3D CRT with maximum-inspiration breath-hold (MIBH) to minimize tumor motion, and IMRT delivery with MIBH; the combination of 3 separate planning treatment-volume sets resulted in the generation of 90 different treatment plans. To plan these, patients underwent treatment-planning computed tomography in MIBH and free breathing followed by simulation with measurement of tumor motion and generation/evaluation of DVHs, EUDs, V20, and NTDmean. RESULTS: Average tumor motion was 1.54 cm in the cephalocaudad directions, 1.26 cm in the anteroposterior directions, and 0.56 cm in the lateral directions between maximum inspiration and expiration. Maximum-inspiration breath-hold produced superior lung sparing evidenced by lower V20 and NTDmean values, and these parameters predicted lower modeled pneumonitis rates. Tomotherapy-based IMRT provided further lung sparing. CONCLUSION: Treatment in MIBH results in lower V20 and NTDmean values and lower modeled pneumonitis rates. This effect is enhanced by the use of IMRT. The use of MIBH with IMRT may therefore aid in escalating the dose in RT.

Adenocarcinoma↗

PubMed2004

Treatment plan optimization incorporating respiratory motion.

Similar to conventional conformal radiotherapy, during lung tomotherapy, a motion margin has to be set for respiratory motion. Consequently, large volume of normal tissue is irradiated by intensive radiation. To solve this problem, we have developed a new motion mitigation method by incorporating target motion into treatment optimization. In this method, the delivery-breathing correlation is determined prior to treatment plan optimization. Beamlets are calculated by using the CT images at the corresponding breathing phases from a dynamic (four-dimensional) image sequence. With the displacement vector fields at different breathing phases, a set of deformed beamlets is obtained by mapping the dose to the primary phase. Optimization incorporating motion is then performed by using the deformed beamlets obtained by dose mapping. During treatment delivery, the same breathing-delivery correlation can be reproduced by instructing the patient to breathe following a visually displayed guiding cycle. This method was tested using a computer-simulated deformable phantom and a real lung case. Results show that treatment optimization incorporating motion achieved similar high dose conformality on a mobile target compared with static delivery. The residual motion effects due to imperfect breathing tracking were also analyzed.

Biophysical Phenomena↗

PubMed2004

Technical note: A novel boundary condition using contact elements for finite element based deformable image registration.

Deformable image registration is an important tool for image-guided radiotherapy. Physics-model-based deformable image registration using finite element analysis is one of the methods currently being investigated. The calculation accuracy of finite element analysis is dependent on given boundary conditions, which are usually based on the surface matching of the organ in two images. Such a surface matching, however, is hard to obtain from medical images. In this study, we developed a new boundary condition to circumvent the traditional difficulties. Finite element contact-impact analysis was employed to simulate the interaction between the organ of interest and the surrounding body. The displacement loading is not necessarily specified. The algorithm automatically deforms the organ model into the minimum internal energy state. The analysis was performed on CT images of the lung at two different breathing phases (exhalation and full inhalation). The result gave the displacement vector map inside the lung. Validation of the result showed satisfactory agreement in most parts of the lung. This approach is simple, operator independent and may provide improved accuracy of the prediction of organ deformation.

Algorithms↗

PubMed2003

Application of the spirometer in respiratory gated radiotherapy.

The signal from a spirometer is directly correlated with respiratory motion and is ideal for target respiratory motion tracking. However, its susceptibility to signal drift deters its application in radiotherapy. In this work, a few approaches are investigated to control spirometer signal drift for a Bernoulli-type spirometer. A method is presented for rapid daily calibration of the spirometer to obtain a flow sensitivity function. Daily calibration assures accurate airflow measurement and also reduces signal drift. Dynamic baseline adjustment further controls the signal drift. The accuracy of these techniques was studied and it was found that the spirometer is able to provide a long-term drift-free breathing signal. The tracking error is comprised of two components: calibration error and stochastic signal baseline variation error. The calibration error is very small (1% of 3 l) and therefore negligible. The stochastic baseline variation error can be as large as 20% of the normal breathing amplitude. In view of these uncertainties, the applications of spirometers in treatment techniques that rely on breathing monitoring are discussed. Spirometer-based monitoring is noted most suitable for deep inspiration breath-hold but less important for free breathing gating techniques.

Calibration↗