Danny Lee

Audiovisual biofeedback improves diaphragm motion reproducibility in MRI.

PURPOSE In lung radiotherapy, variations in cycle-to-cycle breathing results in four-dimensional computed tomography imaging artifacts, leading to inaccurate beam coverage and tumor targeting. In previous studies, the effect of audiovisual (AV) biofeedback on the external respiratory signal reproducibility has been investigated but the internal anatomy motion has not been fully studied. The aim of this study is to test the hypothesis that AV biofeedback improves diaphragm motion reproducibility of internal anatomy using magnetic resonance imaging (MRI). METHODS To test the hypothesis 15 healthy human subjects were enrolled in an ethics-approved AV biofeedback study consisting of two imaging sessions spaced ∼1 week apart. Within each session MR images were acquired under free breathing and AV biofeedback conditions. The respiratory signal to the AV biofeedback system utilized optical monitoring of an external marker placed on the abdomen. Synchronously, serial thoracic 2D MR images were obtained to measure the diaphragm motion using a fast gradient-recalled-echo MR pulse sequence in both coronal and sagittal planes. The improvement in the diaphragm motion reproducibility using the AV biofeedback system was quantified by comparing cycle-to-cycle variability in displacement, respiratory period, and baseline drift. Additionally, the variation in improvement between the two sessions was also quantified. RESULTS The average root mean square error (RMSE) of diaphragm cycle-to-cycle displacement was reduced from 2.6 mm with free breathing to 1.6 mm (38% reduction) with the implementation of AV biofeedback (p-value < 0.0001). The average RMSE of the respiratory period was reduced from 1.7 s with free breathing to 0.3 s (82% reduction) with AV biofeedback (p-value < 0.0001). Additionally, the average baseline drift obtained using a linear fit was reduced from 1.6 mm∕min with free breathing to 0.9 mm∕min (44% reduction) with AV biofeedback (p-value = 0.012). The diaphragm motion reproducibility improvements with AV biofeedback were consistent with the abdominal motion reproducibility that was observed from the external marker motion variation. CONCLUSIONS This study was the first to investigate the potential of AV biofeedback to improve the motion reproducibility of internal anatomy using MRI. The study demonstrated the significant improvement in diaphragm motion reproducibility using AV biofeedback combined with MRI. This system can potentially provide clinically beneficial motion management of internal anatomy in MRI and radiotherapy.

Motion prediction in MRI-guided radiotherapy based on interleaved orthogonal cine-MRI

In-room cine-MRI guidance can provide non-invasive target localization during radiotherapy treatment. However, in order to cope with finite imaging frequency and system latencies between target localization and dose delivery, tumour motion prediction is required. This work proposes a framework for motion prediction dedicated to cine-MRI guidance, aiming at quantifying the geometric uncertainties introduced by this process for both tumour tracking and beam gating. The tumour position, identified through scale invariant features detected in cine-MRI slices, is estimated at high-frequency (25 Hz) using three independent predictors, one for each anatomical coordinate. Linear extrapolation, auto-regressive and support vector machine algorithms are compared against systems that use no prediction or surrogate-based motion estimation. Geometric uncertainties are reported as a function of image acquisition period and system latency. Average results show that the tracking error RMS can be decreased down to a [0.2; 1.2] mm range, for acquisition periods between 250 and 750 ms and system latencies between 50 and 300 ms. Except for the linear extrapolator, tracking and gating prediction errors were, on average, lower than those measured for surrogate-based motion estimation. This finding suggests that cine-MRI guidance, combined with appropriate prediction algorithms, could relevantly decrease geometric uncertainties in motion compensated treatments.

Audiovisual Biofeedback Improves Cine–Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency

PURPOSE To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. METHODS AND MATERIALS Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, and the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. RESULTS Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). CONCLUSIONS These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures.

Quantification of lung tumor rotation with automated landmark extraction using orthogonal cine MRI images

The quantification of tumor motion in sites affected by respiratory motion is of primary importance to improve treatment accuracy. To account for motion, different studies analyzed the translational component only, without focusing on the rotational component, which was quantified in a few studies on the prostate with implanted markers. The aim of our study was to propose a tool able to quantify lung tumor rotation without the use of internal markers, thus providing accurate motion detection close to critical structures such as the heart or liver. Specifically, we propose the use of an automatic feature extraction method in combination with the acquisition of fast orthogonal cine MRI images of nine lung patients. As a preliminary test, we evaluated the performance of the feature extraction method by applying it on regions of interest around (i) the diaphragm and (ii) the tumor and comparing the estimated motion with that obtained by (i) the extraction of the diaphragm profile and (ii) the segmentation of the tumor, respectively. The results confirmed the capability of the proposed method in quantifying tumor motion. Then, a point-based rigid registration was applied to the extracted tumor features between all frames to account for rotation. The median lung rotation values were  -0.6   ±   2.3° and  -1.5   ±   2.7° in the sagittal and coronal planes respectively, confirming the need to account for tumor rotation along with translation to improve radiotherapy treatment.

Audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI

The purpose of this study was to test the hypothesis that audiovisual (AV) biofeedback can improve image quality and reduce scan time for respiratory-gated 3D thoracic MRI. For five healthy human subjects respiratory motion guidance in MR scans was provided using an AV biofeedback system, utilizing real-time respiratory motion signals. To investigate the improvement of respiratory-gated 3D MR images between free breathing (FB) and AV biofeedback (AV), each subject underwent two imaging sessions. Respiratory-related motion artifacts and imaging time were qualitatively evaluated in addition to the reproducibility of external (abdominal) motion. In the results, 3D MR images in AV biofeedback showed more anatomic information such as a clear distinction of diaphragm, lung lobes and sharper organ boundaries. The scan time was reduced from 401±215 s in FB to 334±94 s in AV (p-value 0.36). The root mean square variation of the displacement and period of the abdominal motion was reduced from 0.4±0.22 cm and 2.8±2.5 s in FB to 0.1±0.15 cm and 0.9±1.3 s in AV (p- value of displacement <0.01 and p-value of period 0.12). This study demonstrated that audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI. These results suggest that AV biofeedback has the potential to be a useful motion management tool in medical imaging and radiation therapy procedures.

The impact of breathing guidance and prospective gating during thoracic 4DCT imaging: an XCAT study utilizing lung cancer patient motion.

Two interventions to overcome the deleterious impact irregular breathing has on thoracic-abdominal 4D computed tomography (4DCT) are (1) facilitating regular breathing using audiovisual biofeedback (AVB), and (2) prospective respiratory gating of the 4DCT scan based on the real-time respiratory motion. The purpose of this study was to compare the impact of AVB and gating on 4DCT imaging using the 4D eXtended cardiac torso (XCAT) phantom driven by patient breathing patterns. We obtained simultaneous measurements of chest and abdominal walls, thoracic diaphragm, and tumor motion from 6 lung cancer patients under two breathing conditions: (1) AVB, and (2) free breathing. The XCAT phantom was used to simulate 4DCT acquisitions in cine and respiratory gated modes. 4DCT image quality was quantified by artefact detection (NCCdiff), mean square error (MSE), and Dice similarity coefficient of lung and tumor volumes (DSClung, DSCtumor). 4DCT acquisition times and imaging dose were recorded. In cine mode, AVB improved NCCdiff, MSE, DSClung, and DSCtumor by 20% (p  =  0.008), 23% (p  <  0.001), 0.5% (p  <  0.001), and 4.0% (p  <  0.003), respectively. In respiratory gated mode, AVB improved NCCdiff, MSE, and DSClung by 29% (p  <  0.001), 34% (p  <  0.001), 0.4% (p  <  0.001), respectively. AVB increased the cine acquisitions by 15 s and reduced respiratory gated acquisitions by 31 s. AVB increased imaging dose in cine mode by 10%. This was the first study to quantify the impact of breathing guidance and respiratory gating on 4DCT imaging. With the exception of DSCtumor in respiratory gated mode, AVB significantly improved 4DCT image analysis metrics in both cine and respiratory gated modes over free breathing. The results demonstrate that AVB and respiratory-gating can be beneficial interventions to improve 4DCT for cancer radiation therapy, with the biggest gains achieved when these interventions are used simultaneously.

Quantifying the accuracy of the tumor motion and area as a function of acceleration factor for the simulation of the dynamic keyhole magnetic resonance imaging method

PURPOSE The dynamic keyhole is a new MR image reconstruction method for thoracic and abdominal MR imaging. To date, this method has not been investigated with cancer patient magnetic resonance imaging (MRI) data. The goal of this study was to assess the dynamic keyhole method for the task of lung tumor localization using cine-MR images reconstructed in the presence of respiratory motion. METHODS The dynamic keyhole method utilizes a previously acquired a library of peripheral k-space datasets at similar displacement and phase (where phase is simply used to determine whether the breathing is inhale to exhale or exhale to inhale) respiratory bins in conjunction with central k-space datasets (keyhole) acquired. External respiratory signals drive the process of sorting, matching, and combining the two k-space streams for each respiratory bin, thereby achieving faster image acquisition without substantial motion artifacts. This study was the first that investigates the impact of k-space undersampling on lung tumor motion and area assessment across clinically available techniques (zero-filling and conventional keyhole). In this study, the dynamic keyhole, conventional keyhole and zero-filling methods were compared to full k-space dataset acquisition by quantifying (1) the keyhole size required for central k-space datasets for constant image quality across sixty four cine-MRI datasets from nine lung cancer patients, (2) the intensity difference between the original and reconstructed images in a constant keyhole size, and (3) the accuracy of tumor motion and area directly measured by tumor autocontouring. RESULTS For constant image quality, the dynamic keyhole method, conventional keyhole, and zero-filling methods required 22%, 34%, and 49% of the keyhole size (P < 0.0001), respectively, compared to the full k-space image acquisition method. Compared to the conventional keyhole and zero-filling reconstructed images with the keyhole size utilized in the dynamic keyhole method, an average intensity difference of the dynamic keyhole reconstructed images (P < 0.0001) was minimal, and resulted in the accuracy of tumor motion within 99.6% (P < 0.0001) and the accuracy of tumor area within 98.0% (P < 0.0001) for lung tumor monitoring applications. CONCLUSIONS This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiation therapy requiring the MR monitoring of thoracic tumors. Based on the results from this study, the dynamic keyhole method could increase the imaging frequency by up to a factor of five compared with full k-space methods for real-time lung tumor MRI.

Dynamic keyhole: A novel method to improve MR images in the presence of respiratory motion for real-time MRI

PURPOSE In this work, the authors present a novel magnetic resonance imaging reconstruction method to improve the quality of MR images in the presence of respiratory motion for real-time thoracic image-guided radiotherapy. METHODS This new reconstruction method is called dynamic keyhole and utilizes a library of previously acquired, peripheral k-space datasets from the same (or similar) respiratory state in conjunction with central k-space datasets acquired in real-time. Internal or external respiratory signals are utilized to sort, match, and combine the two separate peripheral and central k-space datasets with respect to respiratory displacement, thereby reducing acquisition time and improving image quality without respiratory-related artifacts. In this study, the dynamic keyhole, conventional keyhole, and zero-filling methods were compared to full k-space acquisition (ground truth) for 60 coronal datasets acquired from 15 healthy human subjects. RESULTS For the same image-quality difference from the ground-truth image, the dynamic keyhole method reused 79% of the prior peripheral phase-encoding lines, while the conventional keyhole reused 73% and zero-filling 63% (p-value < 0.0001), corresponding to faster acquisition speed of dynamic keyhole for real-time imaging applications. CONCLUSIONS This study demonstrates that the dynamic keyhole method is a promising technique for clinical applications such as image-guided radiotherapy requiring real-time MR monitoring of the thoracic region. Based on the results from this study, the dynamic keyhole method could increase the temporal resolution by a factor of five compared with full k-space methods.

SU‐E‐J‐142: Respiratory Guidance for Lung Cancer Patients: An Investigation of Audiovisual Biofeedback Training and Effectiveness

Purpose: Irregular breathing can exacerbate errors in medical imaging and radiotherapy. The audiovisual biofeedback (AV) system has been proposed to facilitate regular patient respiration. The purpose of this work was to identify predictive factors from two lung cancer studies to extract information regarding each studys results and conduct to determine how to produce maximal respiratory guidance effectiveness for future studies. Methods: An analysis of respiratory regularity was performed on respiratory traces from two AV biofeedback lung cancer studies: one from a recent study performed at Stanford (Stanford study) and another, retrospectively, using data from George, et al (2006) (VCU study). Stanford study: 10 lung cancer patients, each had their external respiratory motion monitored whilst they breathed both with and without the guidance of AV biofeedback. VCU study: 24 lung cancer patients. Each patient participated in up to 5 study sessions, received training with the AV biofeedback system and shorter study sessions. Breathing regularity was quantified as the root mean square error (RMSE) of displacement and period. Results: The VCU study demonstrated AV biofeedback to be effective in producing regular respiration over free breathing (reduction in RMSE of 20% (p < 0.001) and 14% (p = 0.06) for displacement and period, respectively). However, the Stanford study did not (no reduction in RMSE displacement and reduction of RMSE in period by 31% (p = 0.17)). Distinguishing features in the conduct between these two studies was the AV biofeedback training, and the repeated and shorter sessions provided in the VCU study. Conclusion: This is the first study to retrospectively analyze the conduct and results from AV biofeedback studies and demonstrate the importance of patient familiarity and training with the AV biofeedback system. This will be used to develop ideal training and information for patients to maximize the efficiency of future AV biofeedback sessions. This work was supported by Sydney Medical School New Staff/Early; Career Researcher Scheme grant, NIH/NCI R01CA93626 and an NHMRC Australia Fellowship.

Audiovisual biofeedback improves the correlation between internal/external surrogate motion and lung tumor motion

PURPOSE Breathing management can reduce breath-to-breath (intrafraction) and day-by-day (interfraction) variability in breathing motion while utilizing the respiratory motion of internal and external surrogates for respiratory guidance. Audiovisual (AV) biofeedback, an interactive personalized breathing motion management system, has been developed to improve reproducibility of intra- and interfraction breathing motion. However, the assumption of the correlation of respiratory motion between surrogates and tumors is not always verified during medical imaging and radiation treatment. Therefore, the aim of the study was to test the hypothesis that the correlation of respiratory motion between surrogates and tumors is the same under free breathing without guidance (FB) and with AV biofeedback guidance for voluntary motion management. METHODS For 13 lung cancer patients receiving radiotherapy, 2D coronal and sagittal cine-MR images were acquired across two MRI sessions (pre- and mid-treatment) with two breathing conditions: (a) FB and (b) AV biofeedback, totaling 88 patient measurements. Simultaneously, the external respiratory motion of the abdomen was measured. The internal respiratory motion of the diaphragm and lung tumor was retrospectively measured from 2D coronal and sagittal cine-MR images. The correlation of respiratory motion between surrogates and tumors was calculated using Pearsons correlation coefficient for: (a) abdomen to tumor (abdomen-tumor) and (b) diaphragm to tumor (diaphragm-tumor). The correlations were compared between FB and AV biofeedback using several metrics: abdomen-tumor and diaphragm-tumor correlations with/without ≥5 mm tumor motion range and with/without adjusting for phase shifts between the signals. RESULTS Compared to FB, AV biofeedback improved abdomen-tumor correlation by 11% (p = 0.12) from 0.53 to 0.59 and diaphragm-tumor correlation by 13% (p = 0.02) from 0.55 to 0.62. Compared to FB, AV biofeedback improved abdomen-tumor correlation by 17% (p = 0.01) and diaphragm-tumor correlation by 15% (p < 0.01) while correcting 0.3 s (p = 0.54) and 0.2 s (p = 0.19) phase shifts, respectively. In addition, AV biofeedback with ≥5 mm tumor motion range, compared to FB improved abdomen-tumor correlation by 14% (p = 0.18) and diaphragm-tumor correlation by 17% (p = 0.01). The highest abdomen-tumor and diaphragm-tumor correlations were found using ≥5 mm tumor motion range and phase shifts, resulting in a 12% improvement in AV biofeedback. CONCLUSIONS Our results demonstrated that AV biofeedback improves the correlation of respiratory motion between surrogates and the tumor. This suggests a need for AV biofeedback for respiratory guidance utilizing respiratory surrogates during image-guided and MRI-guided radiotherapy in thoracic regions.