Conformal radiotherapy (CRT) planning for lung cancer: analysis of intrathoracic organ motion during extreme phases of breathing

Variability of gross tumour volume delineation: MRI and CT based tumour and lymph node delineation for Lung radiotherapy

PURPOSE

To compare gross tumour volume (GTV) delineation of lung cancer on magnetic resonance imaging (MRI) and positron emission tomography (PET) versus computed tomography (CT) and PET.

METHODS

Three experienced thoracic radiation oncologists delineated GTVs on twenty-six patients with lung cancer, based on CT registered to PET, T2-weighted MRI registered to PET and T1-weighted MRI registered with PET. All observers underwent education on reviewing T1 and T2 images along with guidance on window and level setup. Interobserver and intermodality variation was performed based ondice similarity coefficient (DSC), Hausdorff distance (HD), and average Hausdorff distance (AvgHD) metrics. To compute interobserver variability (IOV) a simultaneous truth and performance level estimation (STAPLE) volume for each image modality was used as reference volume. For intermodality analysis, each observers CT based primary and nodal GTV was used as reference volume.

RESULTS

A mean DSC of 0.9 across all observers for primary GTV (GTVp) and a DSC of > 0.7 for nodal GTV (GTVn) was demonstrated for IOV. Mean T2 and T1 GTVp and GTVn were smaller than CT GTVp and GTVn but the difference in volume between modalities was not statistically significant. Significant difference (p<0.01) for GTVp and GTVn was found between T2 and T1 GTVp and GTVn compared to CT GTVp and GTVn based on DSC metrics. Large variation in volume similarity was noted based on HD of up-to 5.4cm for observer volumes compared to STAPLE volume.

CONCLUSION

Interobserver variability in GTV delineation was similar for MRI and PET versus CT and PET. The significant difference between MRI compared to CT delineated volumes needs to be further explored.

Palpation of the Respiratory System in Osteopathic Manual Medicine: From the Trachea to the Lungs

There is a lack of published literature in osteopathic manual medicine on how to perform palpation of the lower respiratory tree such as the trachea, main bronchi, and lungs. Several authors have studied the osteopathic effect and respiratory response of palpation but have failed to demonstrate how to perform palpation of the visceral areas involved in breathing, either in the context of a clinical trial or as a case report. This paper reviews the innervation of these anatomical areas, the mechano-metabolic weight of the passage of fluids and air in the respiratory tract, the anatomical topography, and the movements involved in respiration. Drawing from current knowledge, this article illustrates, for the first time, how to place the hands for an effective osteopathic assessment of the tracheal, bronchial, and pulmonary structures. Understanding how to perform palpation of the lower areas is a fundamental tool in the clinic and potential therapy in osteopathic manual medicine.

Motion estimation and correction in SPECT, PET and CT

Patient motion impacts single photon emission computed tomography (SPECT), positron emission tomography (PET) and X-ray computed tomography (CT) by giving rise to projection data inconsistencies that can manifest as reconstruction artifacts, thereby degrading image quality and compromising accurate image interpretation and quantification. Methods to estimate and correct for patient motion in SPECT, PET and CT have attracted considerable research effort over several decades. The aims of this effort have been two-fold: to estimate relevant motion fields characterizing the various forms of voluntary and involuntary motion; and to apply these motion fields within a modified reconstruction framework to obtain motion-corrected images. The aims of this review are to outline the motion problem in medical imaging and to critically review published methods for estimating and correcting for the relevant motion fields in clinical and preclinical SPECT, PET and CT. Despite many similarities in how motion is handled between these modalities, utility and applications vary based on differences in temporal and spatial resolution. Technical feasibility has been demonstrated in each modality for both rigid and non-rigid motion, but clinical feasibility remains an important target. There is considerable scope for further developments in motion estimation and correction, and particularly in data-driven methods that will aid clinical utility. State-of-the-art machine learning methods may have a unique role to play in this context.

Respiratory gating in patients with lung carcinoma undergoing radiotherapy

Aim:

This study aims to compare the gating signals of patients with lung cancer recorded during the planning computed tomography scan with the ones recorded during treatment fractions. The results provide insights into how representative the respiratory signals from the planning scan are for radiation dose partitioning.

Materials and methods:

The amplitude and frequency of the respiratory signals of 29 patients with lung carcinoma were analysed and compared with the amplitude and frequency of those recorded during their planning scans. Moreover, a cross-correlation analysis was performed between the difference between the planning scan and fractions and features from the planning scan.

Results:

Two patients showed significantly different amplitude and frequency during treatment fractions compared to those from the planning scan. These patients showed low variances in frequency and amplitude during the different fractions. The difference between planning scan and fractions is correlated with the variances within the planning scan.

Findings:

Respiratory signals can differ between the planning scan and the fractions. In this case, a new planning scan may be beneficial. The respiratory signals from the planning scan may be predictive of whether the planning scan will be representative and usable as a control measure during radiotherapy fractions.

A study of the interplay effect for VMAT SBRT using a four-axes motion phantom

Purpose

To assess the accuracy of volumetric modulated arc therapy (VMAT) stereotactic body radiation therapy (SBRT) when treating moving targets (such as lung or liver lesions), focusing on the impact of the interplay effect in the event of complex breathing motion and when a gating window is used.

Methods

A dedicated programmable motion platform was implemented. This platform can carry large quality assurance (QA) phantoms and achieve complex three‐dimensional (3D) motion. Volumetric modulated arc therapy SBRT plans were delivered with TrueBeam linac to this moving setup and the measured dose was compared to the computed one. Several parameters were assessed such as breathing period, dose rate, dose prescription, shape of the breathing pattern, the use of a planning target volume (PTV) margin, and the use of a gating window.

Results

Loss of dose coverage (D95%) was acceptable in most situations. The doses received by 95% of the CTV, D95% ( CTVm) ranged from 94 to 101% (mean 98%) and the doses received by 2% of the CTV D2% ( CTVm) ranged from 94% to 110% of the prescribed dose. A visible interplay effect was observed when no margin was used or when the number of breathing cycles during the treatment delivery was lower than 20.

Conclusions

In our clinical context, treating lung and liver lesions using VMAT SBRT is reasonable. The interplay effect was moderated and acceptable in all simulated situations.

Characterization of Respiration-Induced Motion in Prone Versus Supine Patient Positioning for Thoracic Radiation Therapy

Purpose

Variations in the breathing characteristics, both on short term (intrafraction) and long term (interfraction) time scales, may adversely affect the radiation therapy process at all stages when treating lung tumors. Prone position has been shown to improve consistency (ie, reduced intrafraction variability) and reproducibility (ie, reduced interfraction variability) of the respiratory pattern with respect to breathing amplitude and period as a result of natural abdominal compression, with no active involvement required from the patient. The next natural step in investigating breathing-induced changes is to evaluate motion amplitude changes between prone and supine targets or organs at risk, which is the purpose of the present study.

Methods and Materials

Patients with lung cancer received repeat helical 4-dimensional computed tomography scans, one prone and one supine, during the same radiation therapy simulation session. In the maximum-inhale and maximum-exhale phases, all thoracic structures were delineated by an expert radiation oncologist. Geometric centroid trajectories of delineated structures were compared between patient orientations. Motion amplitude was measured as the magnitude of difference in structure centroid position between inhale and exhale.

Results

Amplitude of organ motion was larger when the patient was in the prone position compared with supine for all structures except the lower left lobe and left lung as a whole. Across all 12 patients, significant differences in mean motion amplitude between orientations were identified for the right lung (3.0 mm, P = .01), T2 (0.5 mm, P = .01) and T12 (2.1 mm, P < .001) vertebrae, the middle third of the esophagus (4.0 mm, P = .03), and the lung tumor (1.7 mm, P = .02).

Conclusions

Respiration-induced thoracic organ motion was quantified in the prone position and compared with that of the supine position for 12 patients with thoracic lesions. The prone position induced larger organ motion compared with supine, particularly for the lung tumor, likely requiring increases in planning margins compared with supine.

Tumor motion tracking based on a four-dimensional computed tomography respiratory motion model driven by an ultrasound tracking technique

Background

An ultrasound image tracking algorithm (UITA) was combined with four-dimensional computed tomography (4DCT) to create a real-time tumor motion-conversion model. The real-time position of a lung tumor phantom based on the real-time diaphragm motion trajectories detected by ultrasound imaging in the superior-inferior (SI) and medial-lateral (ML) directions were obtained.

Methods

Three different tumor motion-conversion models were created using a respiratory motion simulation system (RMSS) combined with 4DCT. The tumor tracking error was verified using cone-beam computed tomography (CBCT). The tumor motion-conversion model was produced by using the UITA to monitor the motion trajectories of the diaphragm phantom in the SI direction, and using 4DCT to monitor the motion trajectories of the tumor phantom in the SI and ML directions over the same time period, to obtain parameters for the motion-conversion model such as the tumor center position and the amplitude and phase ratios.

Results

The tumor movement was monitored for 90 s using CBCT to determine the real motion trajectories of the tumor phantom and using ultrasound imaging to simultaneously record the diaphragm movement. The absolute error of the motion trajectories of the real and estimated tumor varied between 0.5 and 2.1 mm in the two directions.

Conclusions

This study has demonstrated the feasibility of using ultrasound imaging to track diaphragmatic motion combined with a 4DCT tumor motion-conversion model to track tumor motion in the SI and ML directions. The proposed method makes tracking a lung tumor feasible in real time, including under different breathing conditions.

Prediction of lung tumor motion using nonlinear autoregressive model with exogenous input

The present note addresses the development of a lung tumor position predictor to be used in dynamic tumor tracking radiotherapy, abbreviated as DTT-RT. As there exists 50-500 ms positioning lag in the control of the multi-leaf collimator (MLC) of commercial medical linear accelerators, prediction of future lung tumor position with sufficiently long prediction horizon is inevitable for the successful implementation of DTT-RT. The present article proposes a lung tumor position predictor, which is classified as a nonlinear autoregressive model with exogenous input (NARX). The proposed predictor was trained using seven lung tumor motion trajectories of patients who underwent respiratory gated radiotherapy at Yamaguchi University Hospital. We considered three different prediction horizons, 600 ms, 800 ms and 1 s, which were sufficiently long to compensate for the possible positioning control lag of the MLC. A patient-specific model corresponding to an intended prediction horizon was obtained by training it using the selected tumor motion trajectory with the specified horizon. Accordingly, we obtained three NARX predictors for a single patient. We calculated two performance metrics: the RMS prediction errors and the rate of coverage of the entire tumor trajectory defined by the number of samples of the measured tumor position which was inside the 4 mm cube centered at the corresponding predicted tumor position. The latter quantifies the feasibility of the predictors to generate future gating cubes in the implementation of DTT-RT. The [Formula: see text] (mean [Formula: see text] standard deviation) values of the rates of 600 ms, 800 ms and 1 s prediction horizon calculated using the proposed NARX predictors were [Formula: see text]%, [Formula: see text]% and [Formula: see text]%, respectively.

MRI in medical practice and its future use in radiation oncology. Resume of XXV GOCO Congress (Montpellier) 2017

This publication is a resume of the GOCO Congress (Montpellier 2017). A part of this congress was about the use of MRI in clinical practice, focused on the oncology field. The role of this tool was described in diagnosis, staging of tumors, evaluation of treatment response and the future use in prognostic and investigation (radiomics). After that, in the context of the present and future uses of MRI in radiation oncology, MRI guided radiotherapy was explained, as a method that allows an increased precision in image guided treatments. This publication is a resume of the GOCO Congress (Montpellier 2017). A part of this congress was about the use of MRI in clinical practice, focused on the oncology field. The role of this tool was described in diagnosis, staging of tumors, evaluation of treatment response and the future use in prognostic and investigation (radiomics).

Selection of patient for gated treatment based on the information from 4DCT imaging in stereotactic body radiotherapy of non-small cell lung cancer

Purpose

Stereotactic body radiotherapy (SBRT) is widely used for the treatment of stage-I non-small cell lung cancer (NSCLC). Patient-specific motion correlated with 4DCT could be essential for hypofractionated SBRT. All patients undergoing SBRT do not require motion management during the dose delivery. The objective of this study was to evaluate which patient may benefit from Gated SBRT.

Materials and methods

Treatment planning of 20 patients of stage-I NSCLC was analysed. Conventional and 4DCT scans were taken. Internal target volume as well as planning target volume (ITV and PTV) were determined in the CT data sets. PTVall phases created using 4DCT data sets and PTV15mm created using conventional CT data were compared. Also, ITVall phases were compared with ITV created from maximum intensity projections (ITVMIP). Suitability of patients for motion management-based treatment delivery was also evaluated.

Results

The average ITVMIP to ITVall phases ratio is 1·06 indicating good agreement between them. Based on the ratio of intensity projections, 9 out of 17 patients were found suitable for our existing gated treatment.

Conclusion

4D CT is the main requirement in SBRT to identify the patients who can benefit from motion management during the dose delivery.

Inspiratory Lung Expansion in Patients with Interstitial Lung Disease: CT Histogram Analyses

This study aimed to evaluate inspiratory lung expansion in patients with interstitial lung disease (ILD) using histogram analyses based on advanced image registration between inspiratory and expiratory CT scans. We included 16 female ILD patients and eight age- and sex-matched normal controls who underwent full-inspiratory and expiratory CT scans. The CT scans were sequentially aligned based on the surface, landmarks, and attenuation of the lung parenchyma. Histogram analyses were performed on the degree of lung expansion (DLE) of each pixel between the aligned images in x-, y-, z-axes, and 3-dimensionally (3D). The overall mean registration error was 1.9 mm between the CT scans. The DLE_3D in ILD patients was smaller than in the controls (mean, 17.6 mm vs. 26.9 mm; p = 0.023), and less heterogeneous in terms of standard deviation, entropy, and uniformity (p < 0.05). These results were mainly due to similar results in the DLE_Z of the lower lungs. A forced vital capacity tended to be weakly correlated with mean (r² = 0.210; p = 0.074), and histogram parameters (r² = 0.194-0.251; p = 0.048-0.100) of the DLE_3D in the lower lung in ILD patients. Our findings indicate that reduced and less heterogeneous inspiratory lung expansion in ILD patients can be identified by using advanced accurate image registration.

Variations of target volume definition and daily target volume localization in stereotactic body radiotherapy for early-stage non-small cell lung cancer patients under abdominal compression

We aimed to compare gross tumor volumes (GTV) in 3-dimensional computed tomography (3DCT) simulation and daily cone beam CT (CBCT) with the internal target volume (ITV) in 4-dimensional CT (4DCT) simulation in stereotactic body radiotherapy (SBRT) treatment of patients with early-stage non-small cell lung cancer (NSCLC) under abdominal compression. We retrospectively selected 10 patients with NSCLC who received image-guided SBRT treatments under abdominal compression with daily CBCT imaging. GTVs were contoured as visible gross tumor on the planning 3DCT and daily CBCT, and ITVs were contoured using maximum intensity projection (MIP) images of the planning 4DCT. Daily CBCTs were registered with 3DCT and MIP images by matching of bony landmarks in the thoracic region to evaluate interfractional GTV position variations. Relative to MIP-based ITVs, the average 3DCT-based GTV volume was 66.3 ± 17.1% (range: 37.5% to 92.0%) (p < 0.01 in paired t-test), and the average CBCT-based GTV volume was 90.0 ± 6.7% (daily range: 75.7% to 107.1%) (p = 0.02). Based on bony anatomy matching, the center-of-mass coordinates for CBCT-based GTVs had maximum absolute shift of 2.4 mm (left-right), 7.0 mm (anterior-posterior [AP]), and 5.2 mm (superior-inferior [SI]) relative to the MIP-based ITV. CBCT-based GTVs had average overlapping ratio of 81.3 ± 11.2% (range: 45.1% to 98.9%) with the MIP-based ITV, and 57.7 ± 13.7% (range: 35.1% to 83.2%) with the 3DCT-based GTV. Even with abdominal compression, both 3DCT simulations and daily CBCT scans significantly underestimated the full range of tumor motion. In daily image-guided patient setup corrections, automatic bony anatomy-based image registration could lead to target misalignment. Soft tissue-based image registration should be performed for accurate treatment delivery.

An autotuning respiration compensation system based on ultrasound image tracking

The purpose of this study was to develop an ultrasound image tracking algorithm (UITA) for extracting the exact displacement of internal organs caused by respiratory motion. The program can track organ displacements in real time, and analyze the displacement signals associated with organ displacements via a respiration compensating system (RCS). The ultrasound imaging system is noninvasive and has a high spatial resolution and a high frame rate (around 32 frames/s), which reduces the radiation doses that patients receive during computed tomography and X-ray observations. This allows for the continuous noninvasive observation and compensation of organ displacements simultaneously during a radiation therapy session.This study designed a UITA for tracking the motion of a specific target, such as the human diaphragm. Simulated diaphragm motion driven by a respiration simulation system was observed with an ultrasound imaging system, and then the induced diaphragm displacements were calculated by our proposed UITA. These signals were used to adjust the gain of the RCS so that the amplitudes of the compensation signals were close to the target movements. The inclination angle of the ultrasound probe with respect to the surface of the abdomen affects the results of ultrasound image displacement tracking. Therefore, the displacement of the phantom was verified by a LINAC with different inclination-angle settings of the ultrasound probe. The experimental results indicate that the best inclination angle of the ultrasound probe is 40 degrees, since this results in the target displacement of the ultrasound images being close to the actual target motion. The displacement signals of the tracking phantom and the opposing displacement signals created by the RCS were compared to assess the positioning accuracy of our proposed ultrasound image tracking technique combined with the RCS.When the ultrasound probe was inclined by 40 degrees in simulated respiration experiments using sine waves, the correlation between the target displacement on the ultrasound images and the actual target displacement was around 97%, and all of the compensation rates exceeded 94% after activating the RCS. Furthermore, the diaphragm movements on the ultrasound images of three patients could be captured by our image tracking technique. The test results show that our algorithm could achieve precise point locking and tracking functions on the diaphragm. This study has demonstrated the feasibility of the proposed ultrasound image tracking technique combined with the RCS for compensating for organ displacements caused by respiratory motion.This study has shown that the proposed ultrasound image tracking technique combined with the RCS can provide real-time compensation of respiratory motion during radiation therapy, without increasing the overall treatment time. In addition, the system has modest space requirements and is easy to operate.

Superior sulcus non-small cell lung carcinoma: A comparison of IMRT and 3D-RT dosimetry

AIM

A dosimetric study comparing intensity modulated radiotherapy (IMRT) by TomoTherapy to conformational 3D radiotherapy (3D-RT) in patients with superior sulcus non-small cell lung cancer (NSCLC).

BACKGROUND

IMRT became the main technique in modern radiotherapy. However it was not currently used for lung cancers. Because of the need to increase the dose to control lung cancers but because of the critical organs surrounding the tumors, the gains obtainable with IMRT is not still demonstrated.

MATERIAL AND METHODS

A dosimetric comparison of the planned target and organs at risk parameters between IMRT and 3D-RT in eight patients who received preoperative or curative intent irradiation.

RESULTS

In the patients who received at least 66 Gy, the mean V95% was significantly better with IMRT than 3D-RT (p = 0.043). IMRT delivered a lower D2% compared to 3D-RT (p = 0.043). The IH was significantly better with IMRT (p = 0.043). The lung V 5 Gy and V 13 Gy were significantly higher in IMRT than 3D-RT (p = 0.043), while the maximal dose (D max) to the spinal cord was significantly lower in IMRT (p = 0.043). The brachial plexus D max was significantly lower in IMRT than 3D-RT (p = 0.048). For patients treated with 46 Gy, no significant differences were found.

CONCLUSION

Our study showed that IMRT is relevant for SS-NSCLC. In patients treated with a curative dose, it led to a reduction of the exposure of critical organs, allowing a better dose distribution in the tumor. For the patients treated with a preoperative schedule, our results provide a basis for future controlled trials to improve the histological complete response by increasing the radiation dose.

A technique of quantitatively monitoring both respiratory and nonrespiratory motion in patients using external body markers

The purpose of this study was to develop a technique that could quantitatively monitor the nonrespiratory motion of a patient during stereotactic body radiotherapy (SBRT). Multiple infrared external markers were placed on the patient's chest and abdominal surface to obtain patient motion signals. These motion signals contained both respiratory and nonrespiratory motion information. The respiratory motion usually has much larger amplitude on the abdominal surface than on the chest surface. Assuming that the nonrespiratory motion is a rigid body translation, we have developed a computer algorithm to derive both the respiratory and nonrespiratory motion signals instantly from two sets of motion signals. In first-order approximation, the respiratory motion was represented by the motion signal on the abdominal surface, and the nonrespiratory motion was represented by the motion signal on the chest surface subtracting its respiratory component. The algorithm was retrospectively tested on 24 patients whose motion signals were recorded during a gated-CT simulation procedure. The result showed that the respiratory noise in the nonrespiratory motion signal was reduced to less than 1 mm for almost all patients, demonstrating that the technique was able to detect nonrespiratory motion with a sensitivity of about 1 mm. It also showed that 50% of the patients had > or =2 mm, and 2 patients had > or =3 mm slow drift during the 15-25 min simulation procedure, suggesting that nonrespiratory motion could exist during prolonged treatment. This technique can potentially be used to control the nonrespiratory motion during SBRT. However, further validation is required for its clinical use.

Emerging Role of MRI for Radiation Treatment Planning in Lung Cancer

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and allows for specific scanning sequences to optimize differentiation between various tissue types and properties. Moreover, it offers the potential for real-time motion imaging. This makes magnetic resonance imaging an ideal candidate imaging modality for radiation treatment planning in lung cancer. Although the number of clinical research protocols for the application of magnetic resonance imaging for lung cancer treatment is increasing (www.clinicaltrials.gov) and the magnetic resonance imaging sequences are becoming faster, there are still some technical challenges. This review describes the opportunities and challenges of magnetic resonance imaging for radiation treatment planning in lung cancer.

Minimal Inter-Fractional Fiducial Migration during Image-Guided Lung Stereotactic Body Radiotherapy Using SuperLock Nitinol Coil Fiducial Markers

Objectives

Stereotactic body radiotherapy (SBRT) is being increasingly used for the treatment of patients with lung cancer or lung metastasis who are medically unfit to undergo resection. In order to improve accuracy and confidence in targeting tumors, many centers rely on fiducial implantation. We evaluated the migration of a novel fiducial marker specifically designed for lung tissue implanted via electromagnetic navigation bronchoscopy (ENB).

Methods

We retrospectively quantified the individual and group migrations of SuperLock nitinol coil fiducials for 15 patients receiving lung stereotactic body radiotherapy (SBRT), in order to evaluate the reliability of using these fiducials as a target surrogate for cases where tumors cannot be clearly delineated on cone beam CTs (CBCTs). For each fraction, we compared the individual and group migrations of the fiducials between the planning CT and the acquired CBCT. The group migration was defined as the distance between the centroids of the fiducial group and GTV.

Results

A total of 16 lung targets were included in our study for these 15 patients (one patient with two targets). Of 55 fiducials placed, we observed a 100% retention rate. The mean individual migration was 1.87 mm (range, 0.63–5.25 mm) with a standard deviation of 1.26 mm. The mean group migration was 1.94 mm (range, 0.03–6.19 mm) with a standard deviation of 1.45 mm. Overall, there was minimal change in the relative locations of the markers with respect to each other, as well as to the target.

Conclusions

We found that the SuperLock nitinol coil fiducial marker positions are stable throughout the radiation treatment, and can be used as a reliable surrogate to target, and to avoid geometric misses during gated treatments.

Are therapeutic radiographers able to achieve clinically acceptable verification for stereotactic lung radiotherapy treatment (SBRT)?

Purpose

The aim of this study was to assess the feasibility of radiographer led verification of cone-beam computed tomography (CBCT) images for patients with solitary lung tumours treated with stereotactic body radiotherapy treatment (SBRT).

Material and methods

CBCT setup images of 20 patients from the first fraction of each patient were retrospectively registered by therapeutic radiographers. The displacements recorded were compared with the clinical oncologist’s original online match. The time taken by radiographers to verify the CBCT images was also recorded.

Results

Overall agreement for all radiographers when compared with the clinical oncologist match was 91%. Interobserver variations between radiographers were X plane 0·87 (0·76–0·94); Y plane 0·74 (0·51–0·88); and Z plane 0·88 (0·78–0·95) intraclass correlation coefficient and 95% confidence interval. The average time taken for verification was 128 seconds.

Conclusion

Therapeutic radiographers are able to verify CBCT images for thorax SBRT with results comparable to the ‘gold standard’ clinical oncologists’ match, however additional training will be provided for online verification. The time taken was within acceptable limits.

Enhancing 18F-FDG-PET/CT analysis in lung cancer patients

Aim: To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/ CT for lung cancer staging. Methods: Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semitransparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Results: Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. Conclusion: This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.

Controlling motion prediction errors in radiotherapy with relevance vector machines

PURPOSE

Robotic radiotherapy can precisely ablate moving tumors when time latencies have been compensated. Recently, relevance vector machines (RVM), a probabilistic regression technique, outperformed six other prediction algorithms for respiratory compensation. The method has the distinct advantage that each predicted point is assumed to be drawn from a normal distribution. Second-order statistics, the predicted variance, were used to control RVM prediction error during a treatment and to construct hybrid prediction algorithms.

METHODS

First, the duty cycle and the precision were correlated to the variance by interrupting the treatment if the variance exceeds a threshold. Second, two hybrid algorithms based on the variance were developed, one consisting of multiple RVMs (HYB(RVM)) and the other of a combination between a wavelet-based least mean square algorithm (wLMS) and a RVM (HYB(wLMS-RVM)). The variance for different motion traces was analyzed to reveal a characteristic variance pattern which gives insight in what kind of prediction errors can be controlled by the variance.

RESULTS

Limiting the variance by a threshold resulted in an increased precision with a decreased duty cycle. All hybrid algorithms showed an increased prediction accuracy compared to using only their individual algorithms. The best hybrid algorithm, HYB(RVM), can decrease the mean RMSE over all 304 motion traces from 0.18 mm for a linear RVM to 0.17 mm.

CONCLUSIONS

The predicted variance was shown to be an efficient metric to control prediction errors, resulting in a more robust radiotherapy treatment. The hybrid algorithm HYB(RVM) could be translated to clinical practice. It does not require further parameters, can be completely parallelised and easily further extended.

Optimized order estimation for autoregressive models to predict respiratory motion

PURPOSE

To successfully ablate moving tumors in robotic radio-surgery, it is necessary to compensate for motion of inner organs caused by respiration. This can be achieved by tracking the body surface and correlating the external movement with the tumor position as it is implemented in the CyberKnife[Formula: see text] Synchrony system. Tracking errors, originating from system immanent time delays, are typically reduced by time series prediction. Many prediction algorithms exploit autoregressive (AR) properties of the signal. Estimating the optimal model order [Formula: see text] for these algorithms constitutes a challenge often solved via grid search or prior knowledge about the signal.

METHODS

Aiming at a more efficient approach instead, this study evaluates the Akaike information criterion (AIC), the corrected AIC, and the Bayesian information criterion (BIC) on the first minute of the respiratory signal. Exemplarily, we evaluated the approach for a least mean square (LMS) and a wavelet-based LMS (wLMS) predictor.

RESULTS

Analyzing 12 motion traces, orders estimated by AIC had the highest prediction accuracy for both prediction algorithms. Extending the investigations to 304 real motion traces, the prediction error of wLMS using AIC was found to decrease significantly by 85.1 % of the data compared to the original implementation

CONCLUSIONS

The overall results suggest that using AIC to estimate the model order [Formula: see text] for prediction algorithms based on AR properties is a valid method which avoids intensive grid search and leads to high prediction accuracy.

Respiratory Gating for Radiotherapy: Main Technical Aspects and Clinical Benefits

Respiratory-gated radiotherapy offers a significant potential for improvement in the irradiation of tumor sites affected by respiratory motion such as lung, breast, and liver tumors. An increased conformality of irradiation fields leading to decreased complication rates of organs at risk is expected. Five main strategies are used to reduce respiratory motion effects: integration of respiratory movements into treatment planning, forced shallow breathing with abdominal compression, breath-hold techniques, respiratory gating techniques, and tracking techniques. Measurements of respiratory movements can be performed either in a representative sample of the general population, or directly on the patient before irradiation. Reduction of breathing motion can be achieved by using either abdominal compression, breath-hold techniques, or respiratory gating techniques. Abdominal compression can be used to reduce diaphragmatic excursions. Breath-hold can be achieved with active techniques, in which airflow of the patient is temporarily blocked by a valve, or passive techniques, in which the patient voluntarily breath-holds. Respiratory gating techniques use external devices to predict the phase of the breathing cycle while the patient breathes freely. Another approach is tumor-tracking technique, which consists of a real-time localization of a constantly moving tumor. This work describes these different strategies and gives an overview of the literature.

Evaluation of the potential of multi-modal sensors for respiratory motion prediction and correlation

In modern robotic radiotherapy, precise radiation of moving tumors is possible by tracking external optical surrogates. The surrogates are used to compensate for time delays and to predict internal landmarks using a correlation model. The correlation depends significantly on the surrogate position and breathing characteristics of the patient. In this context, we aim to increase the accuracy and robustness of prediction and correlation models by using a multi-modal sensor setup. Here, we evaluate the correlation coefficient of a strain belt, an acceleration and temperature sensor (air flow) with respect to external optical sensors and one internal landmark in the liver, measured by 3D ultrasound. The focus of this study is the influence of breathing artefacts, like coughing and harrumphing. Evaluating seven subjects, we found a strong decrease of the correlation for all modalities in case of artefacts. The results indicate that no precise motion compensation during these times is possible. Overall, we found that apart from the optical markers, the strain belt and temperature sensor data show the best correlation to external and internal motion.

Double CT imaging can measure the respiratory movement of small pulmonary tumors during stereotactic ablative radiotherapy

PURPOSE

The purpose of this study was to investigate the application of double CT imaging to measuring the respiratory movement of small pulmonary tumors during stereotactic ablative radiotherapy (SABR).

METHODS

A total of 122 small pulmonary tumors were measured in 45 patients. CT scans were conducted twice in all 122 tumors, once at the end of quiet inhalation and once at the end of exhalation. CT scans were conducted three times including at the end of quiet inhalation, at the end of exhalation and at free breathing in 36 tumors of 17 patients. The displacement of the tumor center in three directions was measured.

RESULTS

The 3D motion of 122 tumors was 10.10±7.16 mm. On average, the tumors moved 1.96±2.03 mm (rang, 0-9 mm) in the X direction, 5.19±4.69 mm (rang, 0-19 mm) in the Y direction, and 7.38±6.48 mm (rang, 0-26 mm) in the Z direction. The 3D motion of tumors in the lower lung (13.00±7.64 mm) was significantly greater than that in the upper lung (7.15±5.14 mm), P<0.01. The 3D motion of the lower left lung was 16.35±7.31 mm, which was significantly greater than that of the lower right lung (11.40±7.04 mm), P<0.05. Movement in the anterior lung in the Y direction was significantly larger than in the posterior lung. The motion was 7.49±5.43 mm and 4.04±3.82 mm respectively, P<0.01.

CONCLUSIONS

Double CT imaging provides accurate data for determining the outline of each target area during stereotactic ablative radiotherapy plane. The location of small pulmonary tumor foci was significantly affected by respiratory and cardiac motion.

A three dimensional drive system for use with fillable emission phantoms for SPECT and PET imaging

Respiratory motion artefacts pose significant challenges for imaging of the lung and thorax. Dynamic phantoms have previously been applied to the study of respiratory motion, however, most moving platforms have been capable of movement in either one or two dimensions only. We describe a moving platform suitable for SPECT-CT and PET-CT imaging. The platform allows a fillable emission phantom to simulate rigid motion in three dimensions. Elliptical periodical motion of 1.5 cm in all three orthogonal planes was simulated using a series of cams moving a baseplate up and across a slope of 45°. The frequency of movement can be varied manually between 5 and 25 cycles per minute in a known calibrated and reproducible manner (This encompasses the range of physiological respiratory motion). Preliminary studies demonstrated that the phantom can be used to identify motion parameters and for the qualitative assessment of motion blurring in reconstructed images.

Quasi-breath-hold technique using personalized audio-visual biofeedback for respiratory motion management in radiotherapy

PURPOSE

To introduce a respiratory motion management technique, so called quasi-breath-hold (QBH) technique and evaluate its feasibility. As a hybrid technique combining free-breathing-based gating (denoted as gating for convenience) and breath-hold (BH), the QBH is designed to overcome typical limitations existing in either one such as phase-shift, residual motion, complexity, and discomfort.

METHODS

The QBH is realized using an audio-visual biofeedback system (AVBFS) and a respiratory motion management program (RMMP). The AVBFS, consisting of two infra-red stereo cameras and a head mounted display, monitors respiratory motion and provides dynamic feedback to patients. The RMMP establishes a personalized respiration model based on deep free breathing. The model is further processed to generate a QBH model by inserting a short breath-hold period into the end point of the-end-of-expiration phase. Then the patient is guided to follow the QBH model through the AVBFS. A simulation study with ten volunteers was performed to evaluate the feasibility of the proposed technique. In the simulation, an in-house developed macro program automatically controlled the QBH procedure to virtually deliver an intensity modulated radiation therapy (IMRT) plan. For each volunteer subject, three QBH maneuvers with different breath-hold times of 3, 5, and 7s (denoted as QBH3s, QBH5s, and QBH7s, respectively) and a conventional gating maneuver with 30% duty cycle (for comparison purpose) were applied. External respiration motion signals obtained during the gating window were analyzed to obtain mean absolute error (MAE) between the measured and guiding curve, mean absolute deviation (MAD) of the measured curve, and an inverse uncertainty time histogram (IUTH).

RESULTS

Every volunteer successfully performed all of the four maneuvers (1 gating and 3 QBH patterns). The average treatment times were 466.8, 452.3, and 430.8 s for the QBH3s, QBH5s, and QBH7s, respectively, compared to 530.4 s for the gating technique. The mean absolute errors between measured and guiding curve during the gating window were 0.9 +/- 0.7, 0.8 +/- 0.6, 0.7 +/- 0.6, and 0.6 +/- 0.7 mm for the gating, QBH3s, QBH5s, and QBH7s, respectively. The mean absolute deviations of the measured curve during the gating window were 0.7 +/- 0.7, 0.5 +/- 0.5, 0.5 +/- 0.4, and 0.5 +/- 0.6 mm for the gating, QBH3s, QBH5s, and QBH7s, respectively. In the analysis of the IUTH during the gating window, the QBH simulations showed similar (QBH3s) or less (QBH5s and QBH7s) motion uncertainties compared to the gating simulation.

CONCLUSIONS

The proposed QBH technique with personalized audio-visual biofeedback was feasible for respiratory motion management. It showed equivalent or less motion uncertainty and shorter treatment time than the conventional free-breathing-based gating technique did. The technique is expected to optimally compromise between patient comfort and treatment efficiency.

Breathing adapted radiotherapy: a 4D gating software for lung cancer

PURPOSE

Physiological respiratory motion of tumors growing in the lung can be corrected with respiratory gating when treated with radiotherapy (RT). The optimal respiratory phase for beam-on may be assessed with a respiratory phase optimizer (RPO), a 4D image processing software developed with this purpose.

METHODS AND MATERIALS

Fourteen patients with lung cancer were included in the study. Every patient underwent a 4D-CT providing ten datasets of ten phases of the respiratory cycle (0-100% of the cycle). We defined two morphological parameters for comparison of 4D-CT images in different respiratory phases: tumor-volume to lung-volume ratio and tumor-to-spinal cord distance. The RPO automatized the calculations (200 per patient) of these parameters for each phase of the respiratory cycle allowing to determine the optimal interval for RT.

RESULTS

Lower lobe lung tumors not attached to the diaphragm presented with the largest motion with breathing. Maximum inspiration was considered the optimal phase for treatment in 4 patients (28.6%). In 7 patients (50%), however, the RPO showed a most favorable volumetric and spatial configuration in phases other than maximum inspiration. In 2 cases (14.4%) the RPO showed no benefit from gating. This tool was not conclusive in only one case.

CONCLUSIONS

The RPO software presented in this study can help to determine the optimal respiratory phase for gated RT based on a few simple morphological parameters. Easy to apply in daily routine, it may be a useful tool for selecting patients who might benefit from breathing adapted RT.

Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for radiotherapy treatment planning

PURPOSE

Four-dimensional computed tomography (4D-CT) is commonly used to account for respiratory motion of target volumes in radiotherapy to the thorax. From the 4D-CT acquisition, a maximum-intensity projection (MIP) image set can be created and used to help define the tumor motion envelope or the internal gross tumor volume (iGTV). The purpose of this study was to quantify the differences in automatically contoured target volumes for usage in the delivery of stereotactic body radiation therapy using MIP data sets generated from one of the four methods: (1) 4D-CT phase-binned (PB) based on retrospective phase calculations, (2) 4D-CT phase-corrected phase-binned (PC-PB) based on motion extrema, (3) 4D-CT amplitude-binned (AB), and (4) cine CT built from all available images.

METHODS

MIP image data sets using each of the four methods were generated for a cohort of 28 patients who had prior thoracic 4D-CT scans that exhibited lung tumor motion of at least 1 cm. Each MIP image set was automatically contoured on commercial radiation treatment planning system. Margins were added to the iGTV to observe differences in the final simulated planning target volumes (PTVs).

RESULTS

For all patients, the iGTV measured on the MIP generated from the entire cine CT data set (iGTVcine) was the largest. Expressed as a percentage of iGTVcine, 4D-CT iGTV (all sorting methods) ranged from 83.8% to 99.1%, representing differences in the absolute volume ranging from 0.02 to 4.20 cm3; the largest average and range of 4D-CT iGTV measurements was from the PC-PB data set. Expressed as a percentage of PTVcine (expansions applied to iGTVeine), the 4D-CT PTV ranged from 87.6% to 99.6%, representing differences in the absolute volume ranging from 0.08 to 7.42 cm3. Regions of the measured respiratory waveform corresponding to a rapid change of phase or amplitude showed an increased susceptibility to the selection of identical images for adjacent bins. Duplicate image selection was most common in the AB implementation, followed by the PC-PB method. The authors also found that the image associated with the minimum amplitude measurement did not always correlate with the image that showed maximum tumor motion extent.

CONCLUSIONS

The authors identified cases in which the MIP generated from a 4D-CT sorting process under-represented the iGTV by more than 10% or up to 4.2 cm3 when compared to the iGTVcine. They suggest utilization of a MIP generated from the full cine CT data set to ensure maximum inclusive tumor extent.

AN ADAPTIVE TRACKING ALGORITHM OF LUNG TUMORS IN FLUOROSCOPY USING ONLINE LEARNED COLLABORATIVE TRACKERS

Accurate tracking of tumor movement in fluoroscopic video sequences is a clinically significant and challenging problem. This is due to blurred appearance, unclear deforming shape, complicate intra- and inter- fractional motion, and other facts. Current offline tracking approaches are not adequate because they lack adaptivity and often require a large amount of manual labeling. In this paper, we present a collaborative tracking algorithm using asymmetric online boosting and adaptive appearance model. The method was applied to track the motion of lung tumors in fluoroscopic sequences provided by radiation oncologists. Our experimental results demonstrate the advantages of the method.

Conformal Radiotherapy Planning for Lung Cancer: Analysis of Set-Up Uncertainties

The objective of this study was to evaluate set-up uncertainties using a portal imaging system in a population of inoperable non-small cell lung cancer. Twenty-one patients were treated by a conformal radiotherapy technique with a personalized immobilization cast. The beam was verified by comparison with a corresponding digitally reconstructed radiograph by superimposition of anatomical structures. One thousand eight hundred eighty three images were analyzed. The mean intrafraction and interfraction errors (+/-SD) were 2.17 mm and 0.9 +/- 3.7 mm, 2.3 mm and 0.9 +/- 3.1 mm, 3 mm and 0.7 +/- 3 mm on the lateral (x), cranio-caudal (y) and anterior-posterior (z) axes, respectively. The mean systematic error was small, less than 1 mm, in all directions. The random errors were 2.5 mm, 2.4 mm, and 1.8 mm on the x, y, and z axes, respectively. No correlation between errors and the patient's height, weight, age, or sex was found. Set-up errors accuracy depending on practices, each institution should review their own treatments to quantify and reduce set-up errors in clinical practice.