Implementation of free breathing respiratory amplitude-gated treatments

Purpose

The purpose of this study was to provide guidance in developing and implementing a process for the accurate delivery of free breathing respiratory amplitude‐gated treatments.

Methods

A phase‐based 4DCT scan is acquired at time of simulation and motion is evaluated to determine the exhale phases that minimize respiratory motion to an acceptable level. A phase subset average CT is then generated for treatment planning and a tracking structure is contoured to indicate the location of the target or a suitable surrogate over the planning phases. Prior to treatment delivery, a 4DCBCT is acquired and a phase subset average is created to coincide with the planning phases for an initial match to the planning CT. Fluoroscopic imaging is then used to set amplitude gate thresholds corresponding to when the target or surrogate is in the tracking structure. The final imaging prior to treatment is an amplitude‐gated CBCT to verify both the amplitude gate thresholds and patient positioning. An amplitude‐gated treatment is then delivered. This technique was commissioned using an in‐house lung motion phantom and film measurements of a simple two‐field 3D plan.

Results

The accuracy of 4DCBCT motion and target position measurements were validated relative to 4DCT imaging. End to end testing showed strong agreement between planned and film measured dose distributions. Robustness to interuser variability and changes in respiratory motion were demonstrated through film measurements.

Conclusions

The developed workflow utilizes 4DCBCT, respiratory‐correlated fluoroscopy, and gated CBCT imaging in an efficient and sequential process to ensure the accurate delivery of free breathing respiratory‐gated treatments.

Long-term Inter-protocol kV CBCT image quality assessment for a ring-gantry linac via automated QA approach

We develop a fully automated QA process to compare the image quality of all kV CBCT protocols on a Halcyon linac with ring gantry design, and evaluate image quality stability over a 10-month period. A total of 19 imaging scan and reconstruction protocols were characterized with measurement on a newly released QUART phantom. A set of image analysis algorithms were developed and integrated into an automated analysis suite to derive key image quality metrics, including HU value accuracy on density inserts, HU uniformity using the background plate, high contrast resolution with the modulation transfer function (MTF) from the edge profiles, low contrast resolution using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), slice thickness with the air gap modules, and geometric accuracy with the diameter of the phantom. Image quality data over 10 months was tracked and analyzed to evaluate the stability of the Halcyon kV imaging system. The HU accuracy over all 19 protocols is within tolerance (±50HU). The maximum uniformity deviation is 12.2 HU. The SNR and CNR, depending on the protocol selected, range from 18.5-911.9 and 1.9-102.8, respectively. A much-improved SNR and CNR were observed for iterative reconstruction (iCBCT) modes and protocols designed for large subjects over low dose and fast scanning modes. The Head and Image Gently protocols have the greatest high contrast resolution with MTF_10% over 1 lp/mm and MTF_50% over 0.6 lp/mm. The iCBCT mode slightly improved the MTF_10% and MTF_50% compared to the Feldkamp-Davis-Kress approach. The slice thickness (maximum error of 0.31 mm) and geometry metrics (maximum error of 0.7 mm) are all within tolerance (±0.5 mm for slice thickness and ±1 mm for geometry metrics). The long-term study over 10-month showed no significant drift for all key image quality metrics, which indicated the kV CBCT image quality is stable over time.

Evaluation and Clinical Application of a Commercially Available Iterative Reconstruction Algorithm for CBCT-Based IGRT

PURPOSE

We have quantitatively evaluated the image quality of a new commercially available iterative cone-beam computed tomography reconstruction algorithm over standard cone-beam computed tomography image reconstruction results.

METHODS

This iterative cone-beam computed tomography reconstruction pipeline uses a finite element solver (AcurosCTS)-based scatter correction and a statistical (iterative) reconstruction in addition to a standard kernel-based correction followed by filtered back-projection-based Feldkamp-Davis-Kress cone-beam computed tomography reconstruction. Standard full-fan half-rotation Head, half-fan full-rotation Head, and standard Pelvis cone-beam computed tomography protocols have been investigated to scan a quality assurance phantom via the following image quality metrics: uniformity, HU constancy, spatial resolution, low contrast detection, noise level, and contrast-to-noise ratio. An anthropomorphic head phantom was scanned for verification of noise reduction. Clinical patient image data sets for 5 head/neck patients and 5 prostate patients were qualitatively evaluated.

RESULTS

Quality assurance phantom study results showed that relative to filtered back-projection-based cone-beam computed tomography, noise was reduced from 28.8 ± 0.3 HU to a range between 18.3 ± 0.2 and 5.9 ± 0.2 HU for Full-Fan Head scans, from 14.4 ± 0.2 HU to a range between 12.8 ± 0.3 and 5.2 ± 0.3 HU for Half-Fan Head scans, and from 6.2 ± 0.1 HU to a range between 3.8 ± 0.1 and 2.0 ± 0.2 HU for Pelvis scans, with the iterative cone-beam computed tomography algorithm. Spatial resolution was marginally improved while results for uniformity and HU constancy were similar. For the head phantom study, noise was reduced from 43.6 HU to a range between 24.8 and 13.0 HU for a Full-Fan Head and from 35.1 HU to a range between 22.9 and 14.0 HU for a Half-Fan Head scan. The patient data study showed that artifacts due to photon starvation and streak artifacts were all reduced, and image noise in specified target regions were reduced to 62% ± 15% for 10 patients.

CONCLUSION

Noise and contrast-to-noise ratio image quality characteristics were significantly improved using the iterative cone-beam computed tomography reconstruction algorithm relative to the filtered back-projection-based cone-beam computed tomography method. These improvements will enhance the accuracy of cone-beam computed tomography-based image-guided applications.

Current State of Image Guidance in Radiation Oncology: Implications for PTV Margin Expansion and Adaptive Therapy

Image guidance technology has evolved and seen widespread application in the past several decades. Advancements in the diagnostic imaging field have found new applications in radiation oncology and promoted the development of therapeutic devices with advanced imaging capabilities. A recent example is the development of linear accelerators that offer magnetic resonance imaging for real-time imaging and online adaptive planning. Volumetric imaging, in particular, offers more precise localization of soft tissue targets and critical organs which reduces setup uncertainty and permit the use of smaller setup margins. We present a review of the status of current imaging modalities available for radiation oncology and its impact on target margins and use for adaptive therapy.