MRI-LINAC: A transformative technology in radiation oncology

Advances in radiotherapy technologies have enabled more precise target guidance, improved treatment verification, and greater control and versatility in radiation delivery. Amongst the recent novel technologies, Magnetic Resonance Imaging (MRI) guided radiotherapy (MRgRT) may hold the greatest potential to improve the therapeutic gains of image-guided delivery of radiation dose. The ability of the MRI linear accelerator (LINAC) to image tumors and organs with on-table MRI, to manage organ motion and dose delivery in real-time, and to adapt the radiotherapy plan on the day of treatment while the patient is on the table are major advances relative to current conventional radiation treatments. These advanced techniques demand efficient coordination and communication between members of the treatment team. MRgRT could fundamentally transform the radiotherapy delivery process within radiation oncology centers through the reorganization of the patient and treatment team workflow process. However, the MRgRT technology currently is limited by accessibility due to the cost of capital investment and the time and personnel allocation needed for each fractional treatment and the unclear clinical benefit compared to conventional radiotherapy platforms. As the technology evolves and becomes more widely available, we present the case that MRgRT has the potential to become a widely utilized treatment platform and transform the radiation oncology treatment process just as earlier disruptive radiation therapy technologies have done.

Noise-robust breathing-phase estimation on marker-free, ultra low dose X-ray projections for real-time tumor localization via surrogate structures

PURPOSE

This paper presents a novel strategy for feature-based breathing-phase estimation on ultra low-dose X-ray projections for tumor motion control in radiation therapy.

METHODS

Coarse-scaled Curvelet coefficients are identified as motion sensitive but noise-robust features for this purpose. For feature-based breathing-phase estimation, an ensemble strategy with two classifiers is used. This consensus-based estimation substantially increases tracking reliability by rejection of false positives. The algorithm is evaluated on both synthetic and measured phantom data: Monte Carlo simulated ultra low dose projections for a C-arm X-ray and on the basis of 4D-chest-CTs of eight patients on one hand side and real measurements based on a motion phantom.

RESULTS

To achieve an accuracy of breathing-phase estimation of more than 95% a fluence between 20 and 400 photons per pixel (open field) is required depending on the patient. Furthermore, the algorithm is evaluated on real ultra low dose projections from an XVI R5.0 system (Elekta AB, Stockholm, Sweden) using an additional lead filter to reduce fluence. The classifiers-consensus-based-gating method estimated the correct position of the test projections in all test cases at a fluence of ∼180 photons per pixel and 92% at a fluence of ∼40 photons per pixel. The deposited dose to patient per image is in the range of nGy.

CONCLUSIONS

A novel method is presented for estimation of breathing-phases for real-time tumor localization at ultra low dose both on a simulation and a phantom basis. Its accuracy is comparable to state of the art X-ray based algorithms while the released dose to patients is reduced by two to three orders of magnitude compared to conventional template-based approaches. This allows for continuous motion control during irradiation without the need of external markers.

Conditional random fields for phase-based lung feature tracking with ultra-low-dose x-rays

PURPOSE

During radiation therapy, a continuous internal tumor monitoring without additional imaging dose is desirable. In this study, a sequential feature-based position estimation with ultra-low-dose (ULD) kV x rays using linear-chain conditional random fields (CRFs) is performed.

METHODS

Four-dimensional computed tomography (4D-CTs) of eight patients serve as a-priori information from which ULD projections are simulated using a Monte Carlo method. CRFs are trained with Local Energy-based Shape Histogram features extracted from the ULD images to estimate one out of ten breathing phases from the 4D-CT associated with the tumor position.

RESULTS

Compared to a mean accuracy for ±1 breathing phase of 0.867 using a support vector machine (SVM), a mean accuracy of 0.958 results for the CRF with ten incident photons per pixel. This corresponds to a position estimation with a discretization error of 2.4-5.3 mm assuming a linear displacement relation between the breathing phases and a systematic error of 2.0-4.4 mm due to motion underestimation of the 4D-CT.

CONCLUSIONS

The tumor position estimation is comparable to state-of-the-art methods despite its low imaging dose. Training CRFs further allows a prediction of the following phase and offers a precise post-treatment evaluation tool when decoding the full image sequence.

Feasibility of using single photon counting X-ray for lung tumor position estimation based on 4D-CT

PURPOSE

In stereotactic body radiation therapy of lung tumors, reliable position estimation of the tumor is necessary in order to minimize normal tissue complication rate. While kV X-ray imaging is frequently used, continuous application during radiotherapy sessions is often not possible due to concerns about the additional dose. Thus, ultra low-dose (ULD) kV X-ray imaging based on a single photon counting detector is suggested. This paper addresses the lower limit of photons to locate the tumor reliably with an accuracy in the range of state-of-the-art methods, i.e. a few millimeters.

METHOD

18 patient cases with four dimensional CT (4D-CT), which serves as a-priori information, are included in the study. ULD cone beam projections are simulated from the 4D-CTs including Poisson noise. The projections from the breathing phases which correspond to different tumor positions are compared to the ULD projection by means of Poisson log-likelihood (PML) and correlation coefficient (CC), and template matching under these metrics.

RESULTS

The results indicate that in full thorax imaging five photons per pixel suffice for a standard deviation in tumor positions of less than half a breathing phase. Around 50 photons per pixel are needed to achieve this accuracy with the field of view restricted to the tumor region. Compared to CC, PML tends to perform better for low photon counts and shifts in patient setup. Template matching only improves the position estimation in high photon counts. The quality of the reconstruction is independent of the projection angle.

CONCLUSIONS

The accuracy of the proposed ULD single photon counting system is in the range of a few millimeters and therefore comparable to state-of-the-art tumor tracking methods. At the same time, a reduction in photons per pixel by three to four orders of magnitude relative to commercial systems with flatpanel detectors can be achieved. This enables continuous kV image-based position estimation during all fractions since the additional dose to the patient is negligible.

An externally and internally deformable, programmable lung motion phantom

PURPOSE

Most clinically deployed strategies for respiratory motion management in lung radiotherapy (e.g., gating and tracking) use external markers that serve as surrogates for tumor motion. However, typical lung phantoms used to validate these strategies are based on a rigid exterior and a rigid or a deformable-interior. Such designs do not adequately represent respiration because the thoracic anatomy deforms internally as well as externally. In order to create a closer approximation of respiratory motion, the authors describe the construction and experimental testing of an externally as well as internally deformable, programmable lung phantom.

METHODS

The outer shell of a commercially available lung phantom (RS-1500, RSD, Inc.) was used. The shell consists of a chest cavity with a flexible anterior surface, and embedded vertebrae, rib-cage and sternum. A custom-made insert was designed using a piece of natural latex foam block. A motion platform was programmed with sinusoidal and ten patient-recorded lung tumor trajectories. The platform was used to drive a rigid foam "diaphragm" that compressed/decompressed the phantom interior. Experimental characterization comprised of determining the reproducibility and the external-internal correlation of external and internal marker trajectories extracted from kV x-ray fluoroscopy. Experiments were conducted to illustrate three example applications of the phantom-(i) validating the geometric accuracy of the VisionRT surface photogrammetry system; (ii) validating an image registration tool, NiftyReg; and (iii) quantifying the geometric error due to irregular motion in four-dimensional computed tomography (4DCT).

RESULTS

The phantom correctly reproduced sinusoidal and patient-derived motion, as well as realistic respiratory motion-related effects such as hysteresis. The reproducibility of marker trajectories over multiple runs for sinusoidal as well as patient traces, as characterized by fluoroscopy, was within 0.25 mm RMS error. The motion trajectories of internal and external radio-opaque markers as measured by fluoroscopy were found to be highly correlated (R > 0.95). Using the phantom, it was demonstrated that the motion trajectories of regions-of-interest on the surface as measured by VisionRT are highly consistent with corresponding fluoroscopically acquired surface marker trajectories, with RMS errors within 0.26 mm. Furthermore, it was shown that the trajectories of external and internal marker trajectories derived from NiftyReg deformation vector fields were within 1 mm root mean square errors comparing to trajectories obtained by segmenting markers from individual fluoro frames. Finally, it was shown that while 4DCT can be used to localize internal markers for sinusoidal motion with reasonable accuracy, the localization error increases significantly (by a factor of ∼ 2) in the presence of cycle-to-cycle variations that are observed in patient-derived respiratory motion.

CONCLUSIONS

The authors have developed a realistic externally and internally deformable, programmable lung phantom that will serve as a valuable tool for clinical and investigational motion management studies in thoracic and abdominal radiation therapies.

Development and clinical evaluation of a simple optical method to detect and measure patient external motion

A simple and independent system to detect and measure the position of a number of points in space was devised and implemented. Its application aimed to detect patient motion during radiotherapy treatments, alert of out‐of‐tolerances motion, and record the trajectories for subsequent studies. The system obtains the 3D position of points in space, through its projections in 2D images recorded by two cameras. It tracks black dots on a white sticker placed on the surface of the moving object. The system was tested with linear displacements of a phantom, circular trajectories of a rotating disk, oscillations of an in‐house phantom, and oscillations of a 4D phantom. It was also used to track 461 trajectories of points on the surface of patients during their radiotherapy treatments. Trajectories of several points were reproduced with accuracy better than 0.3 mm in the three spatial directions. The system was able to follow periodic motion with amplitudes lower than 0.5 mm, to follow trajectories of rotating points at speeds up to 11.5 cm/s, and to track accurately the motion of a respiratory phantom. The technique has been used to track the motion of patients during radiotherapy and to analyze that motion. The method is flexible. Its installation and calibration are simple and quick. It is easy to use and can be implemented at a very affordable price. Data collection does not involve any discomfort to the patient and does not delay the treatment, so the system can be used routinely in all treatments. It has an accuracy similar to that of other, more sophisticated, commercially available systems. It is suitable to implement a gating system or any other application requiring motion detection, such as 4D CT, MRI or PET.

PACS numbers: 87.55.N, 87.56.Da

Assessment of tumor motion reproducibility with audio-visual coaching through successive 4D CT sessions

This study aimed to compare combined audio-visual coaching with audio coaching alone and assess their respective impact on the reproducibility of external breathing motion and, one step further, on the internal lung tumor motion itself, through successive sessions. Thirteen patients with NSCLC were enrolled in this study. The tumor motion was assessed by three to four successive 4D CT sessions, while the breathing signal was measured from magnetic sensors positioned on the epigastric region. For all sessions, the breathing was regularized with either audio coaching alone (AC, n = 5) or combined with a real-time visual feedback (A/VC, n = 8) when tolerated by the patients. Peak-to-peak amplitude, period and signal shape of both breathing and tumor motions were first measured. Then, the correlation between the respiratory signal and internal tumor motion over time was evaluated, as well as the residual tumor motion for a gated strategy. Although breathing and tumor motions were comparable between AC and AV/C groups, A/VC approach achieved better reproducibility through sessions than AC alone (mean tumor motion of 7.2 mm ± 1 vs. 8.6 mm ± 1.8 mm, and mean breathing motion of 14.9 mm ± 1.2 mm vs. 13.3mm ± 3.7 mm, respectively). High internal/external correlation reproducibility was achieved in the superior-inferior tumor motion direction for all patients. For the anterior posterior tumor motion direction, better correlation reproducibility has been observed when visual feedback has been used. For a displacement-based gating approach, A/VC might also be recommended, since it led to smaller residual tumor motion within clinically relevant duty cycles. This study suggests that combining real-time visual feedback with audio coaching might improve the reproducibility of key characteristics of the breathing pattern, and might thus be considered in the implementation of lung tumor radiotherapy.

Development of real-time motion verification system using in-room optical images for respiratory-gated radiotherapy

Phase‐based respiratory‐gated radiotherapy relies on the reproducibility of patient breathing during the treatment. To monitor the positional reproducibility of patient breathing against a 4D CT simulation, we developed a real‐time motion verification system (RMVS) using an optical tracking technology. The system in the treatment room was integrated with a real‐time position management system. To test the system, an anthropomorphic phantom that was mounted on a motion platform moved on a programmed breathing pattern and then underwent a 4D CT simulation with RPM. The phase‐resolved anterior surface lines were extracted from the 4D CT data to constitute 4D reference lines. In the treatment room, three infrared reflective markers were attached on the superior, middle, and inferior parts of the phantom along with the body midline and then RMVS could track those markers using an optical camera system. The real‐time phase information extracted from RPM was delivered to RMVS via in‐house network software. Thus, the real‐time anterior‐posterior positions of the markers were simultaneously compared with the 4D reference lines. The technical feasibility of RMVS was evaluated by repeating the above procedure under several scenarios such as ideal case (with identical motion parameters between simulation and treatment), cycle change, baseline shift, displacement change, and breathing type changes (abdominal or chest breathing). The system capability for operating under irregular breathing was also investigated using real patient data. The evaluation results showed that RMVS has a competence to detect phase‐matching errors between patient's motion during the treatment and 4D CT simulation. Thus, we concluded that RMVS could be used as an online quality assurance tool for phase‐based gating treatments.

PACS number: 87.55.Qr

The effect of an inconsistent breathing amplitude on the relationship between an external marker and internal lung deformation in a porcine model

PURPOSE

Investigate the relationship between the motion of the Varian Real-time Position Management (RPM) device and the internal motion of a pig during induced inconsistencies in the amplitude of breathing.

METHODS

Twelve studies were performed on four ventilated female Landrace cross pigs using a GE Healthcare, Discovery CT 750 HD scanner. In each study, a 4.0 cm section (64 slices) of the pig's lungs was repeatedly scanned 20 times using cine mode, each time lasting more than one breathing cycle. During these cine scans, a Varian RPM device was used to collect respiratory amplitudes and the ventilator air return tube was periodically crimped to induce inconsistent breathing amplitudes. Each breathing cycle and its associated cine scan were categorized as either consistent or inconsistent, based on thresholds of the minimum expiration and maximum inspiration amplitudes. From the group of consistent amplitude cine scans in a study, a reference scan was chosen. The effect of inconsistent breathing amplitudes on the relationship between the motion of the RPM marker and the motion within three regions of interest (in each lung and the chest wall) was investigated with two methods: (1) A 4D-CT sorting algorithm based on RPM amplitude was used to sort volumes into 4D-CT phase bins. Within each phase bin, the nonlinear deformation of volumes collected during consistent and inconsistent breathing amplitude was calculated with respect to the reference volume. The magnitude of the deformations (in mm) were compared to determine if inconsistent breathing amplitude caused greater deformations. (2) Nonlinear deformations between each CT volume from a cine scan and the maximum expiration volume of the reference scan were calculated. Regression analyses between the nonlinear deformations within three regions of interest (in each lung and the chest wall) and the RPM amplitudes were performed to test the effect of inconsistent breathing amplitudes on the linearity of the relationship between the 3D motion of internal anatomy and the 1D motion of the RPM external marker.

RESULTS

(1) Inconsistent versus consistent breathing amplitudes caused a significant increase in deformation relative to the reference scan within the left lung (1.40 +/- 0.42 versus 1.29 +/- 0.36 mm, p < 0.05). (2) One-to-one correspondences between motions of internal anatomies and motion of the RPM external marker did not exist. The regression lines between the two types of motions did not yield an identity relationship (unity slope and zero intercept). Inconsistent breathing produced significantly different regression lines than consistent breathing in ten of the 12 studies within a left lung region of interest.

CONCLUSIONS

The results of these two studies indicate that inconsistency in the amplitude of breathing disrupted the correspondence between the motion of the external marker and internal anatomies. As a consequence, radiation therapy of tumors embedded in lung tissue may be prone to significant errors if inconsistent breathing amplitudes occur during treatment.

Inferring positions of tumor and nodes in Stage III lung cancer from multiple anatomical surrogates using four-dimensional computed tomography

PURPOSE

To investigate the feasibility of modeling Stage III lung cancer tumor and node positions from anatomical surrogates.

METHODS AND MATERIALS

To localize their centroids, the primary tumor and lymph nodes from 16 Stage III lung cancer patients were contoured in 10 equal-phase planning four-dimensional (4D) computed tomography (CT) image sets. The centroids of anatomical respiratory surrogates (carina, xyphoid, nipples, mid-sternum) in each image set were also localized. The correlations between target and surrogate positions were determined, and ordinary least-squares (OLS) and partial least-squares (PLS) regression models based on a subset of respiratory phases (three to eight randomly selected) were created to predict the target positions in the remaining images. The three-phase image sets that provided the best predictive information were used to create models based on either the carina alone or all surrogates.

RESULTS

The surrogate most correlated with target motion varied widely. Depending on the number of phases used to build the models, mean OLS and PLS errors were 1.0 to 1.4 mm and 0.8 to 1.0 mm, respectively. Models trained on the 0%, 40%, and 80% respiration phases had mean (+/- standard deviation) PLS errors of 0.8 +/- 0.5 mm and 1.1 +/- 1.1 mm for models based on all surrogates and carina alone, respectively. For target coordinates with motion >5 mm, the mean three-phase PLS error based on all surrogates was 1.1 mm.

CONCLUSIONS

Our results establish the feasibility of inferring primary tumor and nodal motion from anatomical surrogates in 4D CT scans of Stage III lung cancer. Using inferential modeling to decrease the processing time of 4D CT scans may facilitate incorporation of patient-specific treatment margins.

On-the-fly motion-compensated cone-beam CT using an a priori model of the respiratory motion

Respiratory motion causes artifacts in cone-beam (CB) CT images acquired on slow rotating scanners integrated with linear accelerators. Respiration-correlated CBCT has been proposed to correct for the respiratory motion but only a subset of the CB projections is used to reconstruct each frame of the 4D CBCT image and, therefore, adequate image quality requires long acquisition times. In this article, the authors develop an on-the-fly solution to estimate and compensate for the respiratory motion in the reconstruction of a 3D CBCT image from all the CB projections. An a priori motion model of the patient respiratory cycle is estimated from the 4D planning CT. During the acquisition, the model is correlated with the respiration using a respiratory signal extracted from the CB projections. The estimated motion is next compensated for in an optimized reconstruction algorithm. The motion compensated for is forced to be null on average over the acquisition time to ensure that the compensation results in a CBCT image which describes the mean position of each organ, even if the a priori motion model is inaccurate. Results were assessed on simulated, phantom, and patient data. In all experiments, blur was visually reduced by motion-compensated CBCT. Simulations showed robustness to inaccuracies of the motion model observed on patient data such as amplitude variations, phase shifts, and setup errors, thus proving the efficiency of the compensation using an a priori motion model. Noise and view-aliasing artifacts were lower on motion-compensated CBCT images with 1 min scan than on respiration-correlated CBCT images with 4 min scan. Finally, on-the-fly motion estimation and motion-compensated reconstruction were within the acquisition time of the CB projections and the CBCT image available a few seconds after the end of the acquisition. In conclusion, the authors developed and implemented a method for correcting the respiratory motion during the treatment fractions which can replace respiration-correlated CBCT for improving image quality while decreasing acquisition time.

A novel analytical approach to the prediction of respiratory diaphragm motion based on external torso volume change

An analytical approach to predict respiratory diaphragm motion should have advantages over a correlation-based method, which cannot adapt to breathing pattern changes without re-calibration for a changing correlation and/or linear coefficient. To quantitatively calculate the diaphragm motion, a new expandable 'piston' respiratory (EPR) model was proposed and tested using 4DCT torso images of 14 patients. The EPR model allows two orthogonal lung motions (with a few volumetric constraints): (1) the lungs expand (DeltaV(EXP)) with the same anterior height variation as the thoracic surface, and (2) the lungs extend (DeltaV(EXT)) with the same inferior distance as the volumetrically equivalent 'piston' diaphragm. A volume conservation rule (VCR) established previously (Li et al 2009 Phys. Med. Biol. 54 1963-78) was applied to link the external torso volume change (TVC) to internal lung volume change (LVC) via lung air volume change (AVC). As the diaphragm moves inferiorly, the vacant space above the diaphragm inside the rib cage should be filled by lung tissue with a volume equal to DeltaV(EXT) (=LVC-DeltaV(EXP)), while the volume of non-lung tissues in the thoracic cavity should conserve. It was found that DeltaV(EXP) accounted for 3-24% of the LVC in these patients. The volumetric shape of the rib cage, characterized by the variation of cavity volume per slice over the piston motion range, deviated from a hollow cylinder by -1.1% to 6.0%, and correction was made iteratively if the variation is >3%. The predictions based on the LVC and TVC (with a conversion factor) were compared with measured diaphragm displacements (averaged from six pivot points), showing excellent agreements (0.2 +/- 0.7 mm and 0.2 +/- 1.2 mm, respectively), which are within clinically acceptable tolerance. Assuming motion synchronization between the piston and points of interest along the diaphragm, point motion was estimated but at higher uncertainty ( approximately 10% +/- 4%). This analytical approach provides a patient-independent technique to calculate the patient-specific diaphragm motion, using the anatomical and respiratory volumetric constraints.