Results from a clinical trial evaluating the efficacy of real-time body surface visual feedback in reducing patient motion during lung cancer radiotherapy

A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications

Cone-beam CT (CBCT) is the most commonly used onboard imaging technique for target localization in radiation therapy. Conventional 3D CBCT acquires x-ray cone-beam projections at multiple angles around the patient to reconstruct 3D images of the patient in the treatment room. However, despite its wide usage, 3D CBCT is limited in imaging disease sites affected by respiratory motions or other dynamic changes within the body, as it lacks time-resolved information. To overcome this limitation, 4D-CBCT was developed to incorporate a time dimension in the imaging to account for the patient's motion during the acquisitions. For example, respiration-correlated 4D-CBCT divides the breathing cycles into different phase bins and reconstructs 3D images for each phase bin, ultimately generating a complete set of 4D images. 4D-CBCT is valuable for localizing tumors in the thoracic and abdominal regions where the localization accuracy is affected by respiratory motions. This is especially important for hypofractionated stereotactic body radiation therapy (SBRT), which delivers much higher fractional doses in fewer fractions than conventional fractionated treatments. Nonetheless, 4D-CBCT does face certain limitations, including long scanning times, high imaging doses, and compromised image quality due to the necessity of acquiring sufficient x-ray projections for each respiratory phase. In order to address these challenges, numerous methods have been developed to achieve fast, low-dose, and high-quality 4D-CBCT. This paper aims to review the technical developments surrounding 4D-CBCT comprehensively. It will explore conventional algorithms and recent deep learning-based approaches, delving into their capabilities and limitations. Additionally, the paper will discuss the potential clinical applications of 4D-CBCT and outline a future roadmap, highlighting areas for further research and development. Through this exploration, the readers will better understand 4D-CBCT's capabilities and potential to enhance radiation therapy.

Surrogate-driven respiratory motion model for projection-resolved motion estimation and motion compensated cone-beam CT reconstruction from unsorted projection data

Objective.As the most common solution to motion artefact for cone-beam CT (CBCT) in radiotherapy, 4DCBCT suffers from long acquisition time and phase sorting error. This issue could be addressed if the motion at each projection could be known, which is a severely ill-posed problem. This study aims to obtain the motion at each time point and motion-free image simultaneously from unsorted projection data of a standard 3DCBCT scan.Approach.Respiration surrogate signals were extracted by the Intensity Analysis method. A general framework was then deployed to fit a surrogate-driven motion model that characterized the relation between the motion and surrogate signals at each time point. Motion model fitting and motion compensated reconstruction were alternatively and iteratively performed. Stochastic subset gradient based method was used to significantly reduce the computation time. The performance of our method was comprehensively evaluated through digital phantom simulation and also validated on clinical scans from six patients.Results.For digital phantom experiments, motion models fitted with ground-truth or extracted surrogate signals both achieved a much lower motion estimation error and higher image quality, compared with non motion-compensated results.For the public SPARE Challenge datasets, more clear lung tissues and less blurry diaphragm could be seen in the motion compensated reconstruction, comparable to the benchmark 4DCBCT images but with a higher temporal resolution. Similar results were observed for two real clinical 3DCBCT scans.Significance.The motion compensated reconstructions and motion models produced by our method will have direct clinical benefit by providing more accurate estimates of the delivered dose and ultimately facilitating more accurate radiotherapy treatments for lung cancer patients.

Evaluation of irregular breathing effects on internal target volume definition for lung cancer radiotherapy

PURPOSE

Irregular breathing may compromise the treated volume for free-breathing lung cancer patients during radiotherapy. We try to find a measure based on a breathing amplitude surrogate that can be used to select the patients who need further investigation of tumor motion to ensure that the internal target volume (ITV) provides reliant coverage of the tumor.

MATERIAL AND METHODS

Fourteen patients were scanned with four-dimensional computed tomography (4DCT) during free-breathing. The breathing motion was detected by a pneumatic bellows device used as a breathing amplitude surrogate. In addition to the 4DCT, a breath-hold (BH) scan and three cine CT imaging sessions were acquired. The cine images were taken at randomized intervals at a rate of 12 per minute for 8 minutes to allow tumor motion determination during a typical hypo-fractionated treatment scenario. A clinical target volume (CTV) was segmented in the BH CT and propagated over all cine images and 4DCT bins. The center-of-volume of the translated CTV (CTV_COV ) in the ten 4DCT bins were interconnected to define the 4DCT determined tumor trajectory (4DCT-TT). The volume of CTV inside ITV for all cine CTs was calculated and reported at the 10th percentile (V_CTV10% ). The deviations between CTV_COV in the cine CTs and the 4DCT-TT were calculated and reported at its 90th percentile (d_90% ). The standard deviation of the bellows amplitude peaks (SDP) and the ratio between large and normal inspirations, κ_rel , were tested as surrogates for V_CTV10% and d_90% .

RESULTS

The values of d_90% ranged from 0.6 to 5.2 mm with a mean of 2.2 mm. The values of V_CTV10% ranged from 59-93% with a mean of 78 %. The SDP had a moderate correlation (r = 0.87) to d_90% . Less correlation was seen between SDP and V_CTV10% (r = 0.77), κ_rel and d_90% (r = 0.75) and finally κ_rel and V_CTV10% (r = 0.75).

CONCLUSIONS

The ITV coverage had a large variation for some patients. SDP seems to be a feasible surrogate measure to select patients that needs further tumor motion determination.

Quantitative evaluation of 4D Cone beam CT scans with reduced scan time in lung cancer patients

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Fast (2 min) 4D CBCT can be simulated accurately from long (4 min) scans.

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Registration was accurate for 96.6% of simulated 2 min scans.

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Acquired 2 min scan registration was accurate in 6/8 patients.

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2 min 4D CBCT produces sufficient image quality for IGRT in lung cancer patients.

Purpose

Image guided radiotherapy (IGRT) based on respiration correlated cone-beam CT (4D-CBCT) provides accurate tumour localisation in lung cancer patients by taking into account respiratory motion when deriving setup correction. However, 4D-CBCT scan times are typically longer than for acquisition of 3D-CBCT scans, e.g. 4 min. This work aims to quantitatively evaluate the effect of reduced scan times on 4D-CBCT image quality and registration accuracy in lung cancer patients.

Methods and materials

Scan times down to 1 min were simulated by retaining only projection images corresponding to every second, third or fourth respiratory cycle in forty-four 4D-CBCTs from 15 lung cancer patients. In addition twenty 2-minute scans were acquired for 12 lung cancer patients. Image quality was quantified by assessing registration accuracy in the shorter scan times, comparing to the 4-minute scan registration result where available as reference.

Results

Use of 2-minute scans had little impact on registration accuracy or ability to detect tumour motion: automatic registration accuracy was within 2 mm in 6/8 scans analysed with 2-minute acquisitions, and 96.6% of registration discrepancies were within 2 mm for the simulated scans. When the scan time simulated was below 2 min, automatic registration results still agreed within 2 mm for 84.7% of scans, however visual image quality was considerably degraded.

Conclusion

A 4D-CBCT acquisition time of 2 min produces scans of sufficient image quality for IGRT in most lung cancer patients, as demonstrated quantitatively by assessing the impact on automatic registration accuracy in simulated and real acquisitions.

Respiratory level tracking with visual biofeedback for consistent breath-hold level with potential application in image-guided interventions

BACKGROUND

To present and evaluate a new respiratory level biofeedback system that aids the patient to return to a consistent breath-hold level with potential application in image-guided interventions.

METHODS

The study was approved by the local ethics committee and written informed consent was waived. Respiratory motion was recorded in eight healthy volunteers in the supine and prone positions, using a depth camera that measures the mean distance to thorax, abdomen and back. Volunteers were provided with real-time visual biofeedback on a screen, as a ball moving up and down with respiratory motion. For validation purposes, a conversion factor from mean distance (in mm) to relative lung volume (in mL) was determined using spirometry. Subsequently, without spirometry, volunteers were given breathing instructions and were asked to return to their initial breath-hold level at expiration ten times, in both positions, with and without visual biofeedback. For both positions, the median and interquartile range (IQR) of the absolute error in lung volume from initial breath-hold were determined with and without biofeedback and compared using Wilcoxon signed rank tests.

RESULTS

Without visual biofeedback, the median difference from initial breath-hold was 124.6 mL (IQR 55.7-259.7 mL) for the supine position and 156.3 mL (IQR 90.9-334.7 mL) for the prone position. With the biofeedback, the difference was significantly decreased to 32.7 mL (IQR 12.8-59.6 mL) (p < 0.001) and 22.3 mL (IQR 7.7-47.0 mL) (p < 0.001), respectively.

CONCLUSIONS

The use of a depth camera to provide visual biofeedback increased the reproducibility of breath-hold expiration level in healthy volunteers, with a potential to eliminate targeting errors caused by respiratory movement during lung image-guided procedures.