Optimal Gating Window for Respiratory-Gated Radiotherapy with Real-Time Position Management and Respiration Guiding System for Liver Cancer Treatment

Data driven surrogate signal extraction for dynamic PET using selective PCA: time windows versus the combination of components

Objective.Respiratory motion correction is beneficial in positron emission tomography (PET), as it can reduce artefacts caused by motion and improve quantitative accuracy. Methods of motion correction are commonly based on a respiratory trace obtained through an external device (like the real time position management system) or a data driven method, such as those based on dimensionality reduction techniques (for instance principal component analysis (PCA)). PCA itself being a linear transformation to the axis of greatest variation. Data driven methods have the advantage of being non-invasive, and can be performed post-acquisition. However, their main downside being that they are adversely affected by the tracer kinetics of the dynamic PET acquisition. Therefore, they are mostly limited to static PET acquisitions. This work seeks to extend on existing PCA-based data-driven motion correction methods, to allow for their applicability to dynamic PET imaging.Approach.The methods explored in this work include; a moving window approach (similar to the Kinetic Respiratory Gating method from Schleyeret al(2014)), extrapolation of the principal component from later time points to earlier time points, and a method to score, select, and combine multiple respiratory components. The resulting respiratory traces were evaluated on 22 data sets from a dynamic [18F]-FDG study on patients with idiopathic pulmonary fibrosis. This was achieved by calculating their correlation with a surrogate signal acquired using a real time position management system.Main results.The results indicate that all methods produce better surrogate signals than when applying conventional PCA to dynamic data (for instance, a higher correlation with a gold standard respiratory trace). Extrapolating a late time point principal component produced more promising results than using a moving window. Scoring, selecting, and combining components held benefits over all other methods.Significance.This work allows for the extraction of a surrogate signal from dynamic PET data earlier in the acquisition and with a greater accuracy than previous work. This potentially allows for numerous other methods (for instance, respiratory motion correction) to be applied to this data (when they otherwise could not be previously used).

Population-based asymmetric margins for moving targets in real-time tumor tracking

BACKGROUND

Both geometric and dosimetric components are commonly considered when determining the margin for planning target volume (PTV). As dose distribution is shaped by controlling beam aperture in peripheral dose prescription and dose-escalated simultaneously integrated boost techniques, adjusting the margin by incorporating the variable dosimetric component into the PTV margin is inappropriate; therefore, geometric components should be accurately estimated for margin calculations.

PURPOSE

We introduced an asymmetric margin-calculation theory using the guide to the expression of uncertainty in measurement (GUM) and intra-fractional motion. The margins in fiducial marker-based real-time tumor tracking (RTTT) for lung, liver, and pancreatic cancers were calculated and were then evaluated using Monte Carlo (MC) simulations.

METHODS

A total of 74 705, 73 235, and 164 968 sets of intra- and inter-fractional positional data were analyzed for 48 lung, 48 liver, and 25 pancreatic cancer patients, respectively, in RTTT clinical trials. The 2.5th and 97.5th percentiles of the positional error were considered representative values of each fraction of the disease site. The population-based statistics of the probability distributions of these representative positional errors (PD-RPEs) were calculated in six directions. A margin covering 95% of the population was calculated using the proposed formula. The content rate in which the clinical target volume (CTV) was included in the PTV was calculated through MC simulations using the PD-RPEs.

RESULTS

The margins required for RTTT were at most 6.2, 4.6, and 3.9 mm for lung, liver, and pancreatic cancer, respectively. MC simulations revealed that the median content rates using the proposed margins satisfied 95% for lung and liver cancers and 93% for pancreatic cancer, closer to the expected rates than the margins according to van Herk's formula.

CONCLUSIONS

Our proposed formula based on the GUM and motion probability distributions (MPD) accurately calculated the practical margin size for fiducial marker-based RTTT. This was verified through MC simulations.

Continuous time-resolved estimated synthetic 4D-CTs for dose reconstruction of lung tumor treatments at a 0.35 T MR-linac

Objective.To experimentally validate a method to create continuous time-resolved estimated synthetic 4D-computed tomography datasets (tresCTs) based on orthogonal cine MRI data for lung cancer treatments at a magnetic resonance imaging (MRI) guided linear accelerator (MR-linac).Approach.A breathing porcine lung phantom was scanned at a CT scanner and 0.35 T MR-linac. Orthogonal cine MRI series (sagittal/coronal orientation) at 7.3 Hz, intersecting tumor-mimicking gelatin nodules, were deformably registered to mid-exhale 3D-CT and 3D-MRI datasets. The time-resolved deformation vector fields were extrapolated to 3D and applied to a reference synthetic 3D-CT image (sCTref), while accounting for breathing phase-dependent lung density variations, to create 82 s long tresCTs at 3.65 Hz. Ten tresCTs were created for ten tracked nodules with different motion patterns in two lungs. For each dataset, a treatment plan was created on the mid-exhale phase of a measured ground truth (GT) respiratory-correlated 4D-CT dataset with the tracked nodule as gross tumor volume (GTV). Each plan was recalculated on the GT 4D-CT, randomly sampled tresCT, and static sCTrefimages. Dose distributions for corresponding breathing phases were compared in gamma (2%/2 mm) and dose-volume histogram (DVH) parameter analyses.Main results.The mean gamma pass rate between all tresCT and GT 4D-CT dose distributions was 98.6%. The mean absolute relative deviations of the tresCT with respect to GT DVH parameters were 1.9%, 1.0%, and 1.4% for the GTVD98%,D50%, andD2%, respectively, 1.0% for the remaining nodulesD50%, and 1.5% for the lungV20Gy. The gamma pass rate for the tresCTs was significantly larger (p< 0.01), and the GTVD50%deviations with respect to the GT were significantly smaller (p< 0.01) than for the sCTref.Significance.The results suggest that tresCTs could be valuable for time-resolved reconstruction and intrafractional accumulation of the dose to the GTV for lung cancer patients treated at MR-linacs in the future.

Respiratory motion management using a single rapid MRI scan for a 0.35 T MRI-Linac system

BACKGROUND

MRI has a rapidly growing role in radiation therapy (RT) for treatment planning, real-time image guidance, and beam gating (e.g., MRI-Linac). Free-breathing 4D-MRI is desirable in respiratory motion management for therapy. Moreover, high-quality 3D-MRIs without motion artifacts are needed to delineate lesions. Existing MRI methods require multiple scans with lengthy acquisition times or are limited by low spatial resolution, contrast, and signal-to-noise ratio.

PURPOSE

We developed a novel method to obtain motion-resolved 4D-MRIs and motion-integrated 3D-MRI reconstruction using a single rapid (35-45 s scan on a 0.35 T MRI-Linac.

METHODS

Golden-angle radial stack-of-stars MRI scans were acquired from a respiratory motion phantom and 12 healthy volunteers (n = 12) on a 0.35 T MRI-Linac. A self-navigated method was employed to detect respiratory motion using 2000 (acquisition time = 5-7 min) and the first 200 spokes (acquisition time = 35-45 s). Multi-coil non-uniform fast Fourier transform (MCNUFFT), compressed sensing (CS), and deep-learning Phase2Phase (P2P) methods were employed to reconstruct motion-resolved 4D-MRI using 2000 spokes (MCNUFFT2000) and 200 spokes (CS200 and P2P200). Deformable motion vector fields (MVFs) were computed from the 4D-MRIs and used to reconstruct motion-corrected 3D-MRIs with the MOtion Transformation Integrated forward-Fourier (MOTIF) method. Image quality was evaluated quantitatively using the structural similarity index measure (SSIM) and the root mean square error (RMSE), and qualitatively in a blinded radiological review.

RESULTS

Evaluation using the respiratory motion phantom experiment showed that the proposed method reversed the effects of motion blurring and restored edge sharpness. In the human study, P2P200 had smaller inaccuracy in MVFs estimation than CS200. P2P200 had significantly greater SSIMs (p < 0.0001) and smaller RMSEs (p < 0.001) than CS200 in motion-resolved 4D-MRI and motion-corrected 3D-MRI. The radiological review found that MOTIF 3D-MRIs using MCNUFFT2000 exhibited the highest image quality (scoring > 8 out of 10), followed by P2P200 (scoring > 5 out of 10), and then motion-uncorrected (scoring < 3 out of 10) in sharpness, contrast, and artifact-freeness.

CONCLUSIONS

We have successfully demonstrated a method for respiratory motion management for MRI-guided RT. The method integrated self-navigated respiratory motion detection, deep-learning P2P 4D-MRI reconstruction, and a motion integrated reconstruction (MOTIF) for 3D-MRI using a single rapid MRI scan (35-45 s) on a 0.35 T MRI-Linac system.

A Dosimetric Study Comparing Different Radiotherapy Planning Techniques With and Without Deep Inspiratory Breath Hold for Breast Cancer

Objective

To analyze whether deep inspiratory breath hold (DIBH) would be dosimetrically beneficial irrespective of radiotherapy planning techniques for patients with left breast cancers requiring adjuvant radiotherapy.

Methods

Planning CT scans were taken in free-breathing (FB) as well as deep-inspiration breath hold (DIBH) for patients requiring adjuvant radiotherapy for left breast cancers. After registration, three radiotherapy plans - 3D-conformal radiotherapy (3DCRT), intensity modulated RT (IMRT), and volumetric modulated arc-therapy (VMAT) - were generated for both FB and DIBH scans for each patient. The dose-volume parameters were collected from the dose-volume histogram and analyzed. A paired t-test is used for statistical analysis of the parameters.

Findings

The study was conducted on thirteen patients. The mean dose of the left lung was reduced with DIBH by 32%, 24%, and 6% (8.6 Gy, 6.6 Gy, and 6.4 Gy) with 3DCRT, IMRT, and VMAT, respectively. The mean heart dose was reduced by 3.3 Gy (2.2 vs 5.5 Gy), 2.2 Gy (7.5 vs 9.7 Gy), and 1.2 Gy (5.8 vs 7 Gy) with 3DCRT, IMRT, and VMAT with DIBH. Similarly, the left anterior descending artery (LAD) mean dose was relatively reduced by 80%, 34%, and 20% when compared with the FB scans for 3DCRT, IMRT, and VMAT respectively, with max dose in the 3DCRT plan.

Novelty/Applications

DIBH appears to have maximum benefit in achieving a better sparing of organs-at-risk for patients being considered for 3DCRT, and to a lesser extent with even IMRT and VMAT techniques.

A transit portal dosimetry method for respiratory gating quality assurance with a dynamic 3D printed tumor phantom

BACKGROUNDS

Respiratory gating is one of the motion management techniques that is used to deliver radiation dose to a tumor at a specific position under free breathing. However, due to the dynamic feedback process of this approach, regular equipment quality assurance (QA) and patient-specific QA checks need to be performed. This work proposes a new QA methodology using electronic portal imaging detector (EPID) to determine the target localization accuracy of phase gating.

METHODS

QA tools comprising 3D printed spherical tumor phantoms, programmable stages, and an EPID detector are characterized and assembled. Algorithms for predicting portal dose (PD) through moving phantoms are developed and verified using gamma analysis for two spherical tumor phantoms (2 cm and 4 cm), two different 6 MV volumetric modulated arc therapy plans, and two different gating windows (30%-70% and 40%-60%). Comparison between the two gating windows is then performed using the Wilcoxon signed-rank test. An optimizer routine, which is used to determine the optimal window, based on maximal gamma passing rate (GPR), was applied to an actual breathing curve and breathing plan. This was done to ascertain if our method yielded a similar result with the actual gating window.

RESULTS

High GPRs of more than 97% and 91% were observed when comparing the predicted PD with the measured PD in moving phantom at 2 mm/2% and 1 mm/1% levels, respectively. Analysis of gamma heatmaps shows an excellent agreement with the tumor phantom. The GPR of 40%-60% PD was significantly lower than that of the 30%-70% PD at the 1 mm/1% level (p = 0.0064). At the 2 mm/2% level, no significant differences were observed. The optimizer routine could accurately predict the center of the gating window to within a 10% range.

CONCLUSION

We have successfully performed and verified a new method for QA with the use of a moving phantom with EPID for phase gating with real-time position management.

3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility

This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumor displacement. Specifically, the proposed scheme is driven by two time-series deep-learning algorithmic models: the respiratory-phase classification model and the regression-based prediction model. To assess the performance of the proposed scheme, the classification and prediction models were tested with four categories of datasets: patient-based datasets with regular and irregular breathing patterns; and pseudopatient-based datasets with regular and irregular breathing patterns. In this study, 'pseudopatients' refer to a dynamic thorax phantom with a lung tumor programmed with varying breathing patterns and breaths per minute. The total accuracy of the respiratory-phase classification model was 100%, 100%, 100%, and 92.44% for the four dataset categories, with a corresponding mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R²) of 1.2-1.6%, 0.65-0.8%, and 0.97-0.98, respectively. The results demonstrate that the time-series deep-learning classification and regression-based prediction models can classify the respiratory phases and predict the lung tumor displacement with high accuracy. Essentially, the novelty of this research lies in the use of a low-cost 3D Kinect camera with time-series deep-learning algorithms in the medical field to efficiently classify the respiratory phase and predict the lung tumor displacement.

Respiratory motion management for external radiotherapy treatment

We present the update of the recommendations of the French society of oncological radiotherapy on respiratory motion management for external radiotherapy treatment. Since twenty years and the report 62 of ICRU, motion management during the course of radiotherapy treatment has become an increasingly significant concern, particularly with the development of hypofractionated treatments under stereotactic conditions, using reduced safety margins. This article related orders of motion amplitudes for different organs as well as the definition of the margins in radiotherapy. An updated review of the various movement management strategies is presented as well as main technological solutions enabling them to be implemented: when acquiring anatomical data, during planning and when carrying out treatment. Finally, the management of these moving targets, such as it can be carried out in radiotherapy departments, will be detailed for a few concrete examples of localizations (abdominal, thoracic and hepatic).

Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia

OBJECTIVE

Pneumonia is the single largest cause of death in children worldwide due to infectious diseases. According to WHO guidelines, fast breathing and chest indrawing are the key indicators of pneumonia in children requiring antibiotic treatments. The aim of this study was to develop a video-based novel method for simultaneous monitoring of respiratory rate and chest indrawing without upsetting babies.

APPROACH

Respiratory signals, corresponding to periodic movements of chest-abdominal walls during breathing, were extracted by analyzing RGB (red, green, blue) components in video frames captured by a smartphone camera. Respiratory rate was then obtained by applying fast fourier transform on the de-noised respiratory signal. Chest indrawing was detected by analysing relative phases of regional chest-abdominal wall mobility. The performance of the developed algorithm was evaluated on both healthy and pneumonia children.

MAIN RESULTS

The proposed method can measure respiratory rate with an overall mean absolute error of 1.8 bpm in the range 18-105 bpm. Phase difference between regional chest wall movements in the chest indrawing (pneumonia) cases was found to be 143±23.9 degrees, which was significantly higher than that in the healthy cases 52.3 ±32.6 degrees (p<0.001).

SIGNIFICANCE

Being non-intrusive and non-subjective, this computer-aided method can be useful in the monitoring for respiratory rate and chest indrawing for the diagnosis of pneumonia and its severity in children.

Tailoring PTV expansion to improve the dosimetry of post modified radical mastectomy intensity-modulated radiotherapy for left-sided breast cancer patients by using 4D CT combined with cone beam CT

PURPOSE

Our study aimed to improve the dosimetry of post modified radical mastectomy intensity-modulated radiotherapy (PMRM-IMRT) for left-sided breast cancer patients by tailoring and minimizing PTV expansion three-dimensionally utilizing 4D CT combined with on-board cone beam CT (CBCT).

METHODS

We enrolled a total of 10 consecutive left-sided breast cancer patients to undergo PMRM-IMRT. We measured the intra-fractional CTV displacement attributed to respiratory movement by defining 9 points on the left chest wall and quantifying their displacement by using the 4D CT, and measured the inter-fractional CTV displacement resulting from the integrated effect of respiratory movement, thoracic deformation and set up errors by using CBCT. We created 3 different PMRM-IMRT plans for each of the patients using PTV_t (tailored PTV expansion three-dimensionally), PTV_0.5 and PTV_0.7 (isotropic 0.5- cm and isotropic 0.7- cm expanding margin of CTV), respectively. We performed paired samples t test to establish a hierarchy in terms of plan quality and dosimetric benefits. P < 0.05 was considered statistically significant.

RESULTS

The inter-fractional CTV displacement (2.6 ± 2.2 mm vertically, 2.8 ± 2.3 mm longitudinally, and 1.7 ± 1.2 mm laterally) measured by CBCT was much larger than the intra-fractional one (0.5 ± 0.5 mm vertically, 0.5 ± 1.0 mm longitudinally, and 0.3 ± 0.3 mm laterally, respectively) measured by 4D CT. Intensity-modulated radiotherapy with tailored PTV expansion based on inter-fractional CTV displacement had dosimetrical advantages over those with PTV_0.5 or those with PTV_0.7 owing to its perfect PTV dose coverage and better OARs sparing(especially of heart and left lung).

CONCLUSION

The CTV displacement in PMRM-IMRT predominantly arises from inter-fraction rather than from intra-fraction during natural respiration and differs in 3 coordinate axes either inter-fractionally or intra-fractionally. Tailoring and minimizing PTV expansion three-dimensionally significantly improves the dosimetry of PMRM-IMRT for left-sided breast cancer patients.

Radiobiological effects of the interruption time with Monte Carlo Simulation on multiple fields in photon beams

PURPOSE

The interruption time is the irradiation interruption that occurs at sites and operations such as the gantry, collimator, couch rotation, and patient setup within the field in radiotherapy. However, the radiobiological effect of prolonging the treatment time by the interruption time for tumor cells is little evaluated. We investigated the effect of the interruption time on the radiobiological effectiveness with photon beams based on a modified microdosimetric kinetic (mMK) model.

METHODS

The dose-mean lineal energy y_D (keV/µm) of 6-MV photon beams was calculated by the particle and heavy ion transport system (PHITS). We set the absorbed dose to 2 or 8 Gy, and the interruption time (τ) was set to 1, 3, 5, 10, 30, and 60 min. The biological parameters such as α_0, β_0, and DNA repair constant rate (a + c) values were acquired from a human non-small-cell lung cancer cell line (NCI-H460) for the mMK model. We used two-field and four-field irradiation with a constant dose rate (3 Gy/min); the photon beams were paused for interruption time τ. We calculated the relative biological effectiveness (RBE) to evaluate the interruption time's effect compared with no interrupted as a reference.

RESULTS

The y_D of 6-MV photon beams was 2.32 (keV/µm), and there was little effect by changing the water depth (standard deviation was 0.01). The RBE with four-field irradiation for 8 Gy was decreased to 0.997, 0.975, 0.900, and 0.836 τ = 1, 10, 30, 60 min, respectively. In addition, the RBE was affected by the repair constant rate (a + c) value, the greater the decrease in RBE with the longer the interruption time when the (a + c) value was large.

CONCLUSION

The ~10-min interruption of 6-MV photon beams did not significantly impact the radiobiological effectiveness, since the RBE decrease was <3%. Nevertheless, the RBE's effect on tumor cells was decreased about 30% by increasing the 60 min interruption time at 8 Gy with four-field irradiation. It is thus necessary to make the interruption time as short as possible.

Quantification of Intrafraction and Interfraction Tumor Motion Amplitude and Prediction Error for Different Liver Tumor Trajectories in Cyberknife Synchrony Tracking

PURPOSE

To research the fiducial-based, real-time tracking intrafraction (during the fraction [intra-]) and interfraction (between fractions [inter-]) tumor respiration amplitude, motion trajectory, and prediction error and quantify their relationships for different types of motion trajectories during Cyberknife-based stereotactic ablation radiotherapy.

METHODS AND MATERIALS

Twelve patients with liver tumors were treated using a Cyberknife system, and 58 fractions were involved in this study. Real-time target motion tracking data were extracted and transformed from the robot coordinate system into the patient coordinate system by the rotation matrix. Only the time sessions of the beam on were studied according to the data information generated from the Cyberknife motion tracking system. The motion correlation model between the external marker signal and internal fiducial position was built to present the type of motion trajectory.

RESULTS

Using the correlation model as a function of external marker signal and internal fiducial position, we knew 4 motion trajectories mainly existed for liver cancer patients as follows: perfect linearity (group I), simple linearity (group II), hysteresis (group III), and area respiratory (group IV) patterns. More than half of the patients had a linear breathing trajectory. Analyzing all patients together, the intra-amplitudes were slightly less than those of the inter-amplitudes. The amplitude from large to small was in the superior-inferior, left-right and anterior-posterior directions, regardless of inter- and intra-amplitudes. Then, patients with a larger peak-to-peak have a larger standard deviation of amplitude and a larger amplitude in all fractions/sessions. The prediction errors of the linear motion trajectory were generally less than 1 mm. The prediction errors of the regular hysteresis breathing model were smaller than those of the irregular hysteresis model. Scattered breathing would result in a larger tracking error, such as the area respiratory trajectory. It was logical that prediction errors were larger for patients who showed much variation in their breathing amplitude.

CONCLUSIONS

This paper showed that the liver motion trajectory model included perfect linearity, sample linearity, hysteresis, and area. The linear motion trajectory presented the minimum tracking error and the best stability, and the hysteresis and area trajectory were the worst. Therefore, breathing management, including respiration training, control, and evaluation of motion trajectory in all directions, was significantly necessary during liver SABR treatment.

Capacitive monitoring system for real-time respiratory motion monitoring during radiation therapy

Summary

This work introduces a novel capacitive‐sensing technology capable of detecting respiratory motion with high temporal frequency (200 Hz). The system does not require contact with the patient and has the capacity to sense motion through clothing or plastic immobilization devices.

Abstract

Purpose

This work presents and evaluates a novel capacitive monitoring system (CMS) technology for continuous detection of respiratory motion during radiation therapy. This modular system provides real‐time motion monitoring without any contact with the patient, ionizing radiation, or surrogates such as reflective markers on the skin.

Materials and methods

The novel prototype features an array of capacitive detectors that are sensitive to the position of the body and capable of high temporal frequency readout. Performance of this system was investigated in comparison to the RPM infrared (IR) monitoring system (Varian Medical Systems). The prototype included three (5 cm × 10 cm) capacitive copper sensors in one plane, located at a distance of 8–10 cm from the volunteer. Capacitive measurements were acquired for central and lateral‐to‐central locations during chest free‐breathing and abdominal breathing. The RPM IR data were acquired with the reflector block at corresponding positions simultaneously. The system was also tested during deep inspiration and expiration breath‐hold maneuvers.

Results

Capacitive monitoring system data demonstrate close agreement with the RPM status quo at all locations examined. Cross‐correlation analysis on RPM and CMS data showed an average absolute lag of 0.07 s (range: 0.03–0.23 s) for DIBH and DEBH data and 0.15 s (range: 0–0.43 s) for free‐breathing. Amplitude difference between the normalized CMS and RPM signal during chest and abdominal breathing was within 0.15 for 94.3% of the data points after synchronization. CMS performance was not affected when the subject was clothed.

Conclusion

This novel technology permits sensing of both free‐breathing and breath‐hold respiratory motion. It provides data comparable to the RPM system but without the need for an IR tracking camera in the treatment room or use of reflective markers on the patient.

Feasibility study of surface motion tracking with millimeter wave technology during radiotherapy

PURPOSE

Continuous monitoring of patient movement is crucial to administering safe radiation therapy (RT). Conventional optical approaches often cannot be used when the patient's surface is blocked by immobilization devices. Millimeter waves (mmWaves) are capable of penetrating nonconductive objects. In this study, we investigated using mmWave technology to monitor patient surface displacements, as well as breathing and cardiac phases, through clothing and body fixtures.

METHODS

A mmWave device was mounted inside the bore of a ring-based radiotherapy linear accelerator and pointed at a reflective surface on top of the couch. Measurements were obtained at displacements of 10, 7.5, 5.0, 2.5, and 1.0 mm at heights 100, 150, and 200 mm below isocenter. Submillimeter displacements were performed at a height of 200 mm. Additionally, millimeter and submillimeter displacements were measured with and without a gown and body mold placed between the surface and the sensor. The device was programmed to transmit chirp signals at 77-81 GHz. The subject's surface was detected by fast Fourier transform (FFT) of the reflected chirp signal within a rough range bin. Fine displacements within that range bin were calculated through phase extraction and phase demodulation. The displacement data were sent through two separate bandpass filters with passbands of 0.1-0.6 and 0.8-2.0 Hz to obtain the subject's breathing and cardiac waveforms, respectively. The breathing and cardiac measurements were compared to those of a Vernier Respiration Monitor Belt and an electrocardiogram (EKG), respectively, to assess validity.

RESULTS

The device was able to detect millimeter and submillimeter displacements as small as 0.1 mm, as well as monitor displacement with an accuracy within 1 mm in the presence of an obstructive object. The device's breathing and cardiac waveforms exhibited a strong phase correlation between the respiration monitor belt (ρ = 0.9156) and EKG (ρ = 0.7895), respectively.

CONCLUSIONS

The mmWave device can monitor surface displacements with an accuracy better than 0.1 mm without obstructions and better than 1 mm with obstructions. It can also provide real-time monitoring of breathing and cardiac waveforms simultaneously with high correlation with traditional respiratory and cardiac monitoring devices. Overall, mmWave technology demonstrates potential for motion monitoring in the field of radiation oncology.