Technical Note: Evaluation of audiovisual biofeedback smartphone application for respiratory monitoring in radiation oncology

A Couch Mounted Smartphone-based Motion Monitoring System for Radiation Therapy

PURPOSE

Surface-guided radiation-therapy (SGRT) systems are being adopted into clinical practice for patient setup and motion monitoring. However, commercial systems remain cost prohibitive to resource-limited clinics around the world. Our aim is to develop and validate a smartphone-based application using LiDAR cameras (such as on recent Apple iOS devices) for facilitating SGRT in low-resource centers. The proposed SGRT application was tested at multiple institutions and validated using phantoms and volunteers against various commercial systems to demonstrate feasibility.

METHODS AND MATERIALS

An iOS application was developed in Xcode and written in Swift using the Augmented-Reality (AR) Kit and implemented on an Apple iPhone 13 Pro with a built-in LiDAR camera. The application contains multiple features: 1) visualization of both the camera and depth video feeds (at a ∼60Hz sample-frequency), 2) region-of-interest (ROI) selection over the patient's anatomy where motion is measured, 3) chart displaying the average motion over time in the ROI, and 4) saving/exporting the motion traces and surface map over the ROI for further analysis. The iOS application was tested to evaluate depth measurement accuracy for: 1) different angled surfaces, 2) different field-of-views over different distances, and 3) similarity to a commercially available SGRT systems (Vision RT AlignRT and Varian IDENTIFY) with motion phantoms and healthy volunteers across 3 institutions. Measurements were analyzed using linear-regressions and Bland-Altman analysis.

RESULTS

Compared with the clinical system measurements (reference), the iOS application showed excellent agreement for depth (r = 1.000, P < .0001; bias = -0.07±0.24 cm) and angle (r = 1.000, P < .0001; bias = 0.02±0.69°) measurements. For free-breathing traces, the iOS application was significantly correlated to phantom motion (institute 1: r = 0.99, P < .0001; bias =-0.003±0.03 cm; institute 2: r = 0.98, P < .0001; bias = -0.001±0.10 cm; institute 3: r = 0.97, P < .0001; bias = 0.04±0.06 cm) and healthy volunteer motion (institute 1: r = 0.98, P < .0001; bias = -0.008±0.06 cm; institute 2: r = 0.99, P < .0001; bias = -0.007±0.12 cm; institute 3: r = 0.99, P < .0001; bias = -0.001±0.04 cm).

CONCLUSIONS

The proposed approach using a smartphone-based application provides a low-cost platform that could improve access to surface-guided radiation therapy accounting for motion.

Shallow kinetics induced by a metronome (SKIM): A novel contactless respiratory motion management

OBJECTIVES

As an alternative to conventional compression amidst the COVID-19 pandemic, we developed a contactless motion management strategy. By increasing the patient's breathing rate to induce shallow breathing with the aid of a metronome, our hypothesis is that the motion magnitude of the target may be minimized without physical contact or compression.

METHODS

Fourteen lung stereotactic body radiation therapy (SBRT) patients treated under fast shallow-breathing (FSB) were selected for inclusion in this retrospective study. Our proposed method is called shallow kinetics induced by a metronome (SKIM). We induce FSB by setting the beats-per-minute (BPM) high (typically in the range of 50-60). This corresponded to a patient breathing rate of 25-30 (breathing) cycles per minute. The magnitude of target motion in 3D under SKIM was evaluated using 4DCT datasets. Comparison with free breathing (FB) 4DCT was also made for a subset for which FB data available.

RESULTS

The overall effectiveness of SKIM was evaluated with 18 targets (14 patients). Direct comparison with FB was performed with 12 targets (10 patients). The vector norm mean ± SD value of motion magnitude under SKIM for 18 targets was 8.2 ± 4.1 mm. The mean ± SD metronome BPM was 54.9 ± 4.0 in this group. The vector norm means ± SD values of target motion for FB and SKIM in the 12 target sub-group were 14.6 ± 8.5 mm and 9.3 ± 3.7 mm, respectively. The mean ± SD metronome BPM for this sub-group was 56.3 ± 2.5.

CONCLUSION

Compared with FB, SKIM can significantly reduce respiratory motion magnitude of thoracic targets. The difference in maximum motion reduction in the overall vector norm, S-I, and A-P directions was significant (p = 0.033, 0.042, 0.011). Our proposed method can be an excellent practical alternative to conventional compression due to its flexibility and ease of implementation.