J Lamb

On a PCA-based lung motion model

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.

Intraoperative Ultrasonography-Guided Positioning of Iodine 125 Plaque Brachytherapy in the Treatment of Choroidal Melanoma

PURPOSE To report intraoperative ultrasonography-guided positioning of iodine 125 (I(125)) plaques for brachytherapy of choroidal melanoma as a quality improvement measure. DESIGN Retrospective, single-center, consecutive case-cohort study. PARTICIPANTS One hundred fifty consecutive patients with choroidal melanoma. METHODS Patients with choroidal melanoma who were treated with I(125) plaque brachytherapy from January 2007 through January 2011 with at least 6 months of clinical follow-up were included. MAIN OUTCOME MEASURES Patient and tumor characteristics at diagnosis were tabulated. The need for plaque repositioning if intraoperative ultrasonography showed the plaque to be either not centered on the tumor or if there was less than 1.0 mm of plaque margin beyond the tumor border was recorded. The rate of local treatment failure and occurrence of distant metastasis were determined. RESULTS The average interval from surgery to last follow-up was 21.5 months. Fifty-four (36%) of 150 patients required plaque repositioning. Of tumors located in the macula, equator, and periphery, 15 (36.6%), 26 (36.6%), and 13 (34.2%) required repositioning. There was no case of local treatment failure during a mean follow-up of 21.5 months (range, 6-48 months). Clinical evidence of choroidal melanoma metastasis developed in 9 patients. The cumulative 2-year Kaplan-Meier rate of local treatment failure in the cohort was statistically lower compared with the Collaborative Ocular Melanoma Study, which did not require ultrasonography-guided plaque positioning. CONCLUSIONS Intraoperative ultrasonography identified the need to reposition I(125) plaques to achieve centration and plaque margin (>1.0 mm) beyond the tumor border in 36% of eyes. Neither tumor size nor tumor location correlated with the need to reposition the plaque. There was no case of local treatment failure during follow-up in this series. Correct plaque position is an essential component of quality outcomes in brachytherapy. Intraoperative ultrasonography reduces geographic errors in placement in eye plaque therapy and may help to reduce local treatment failure in choroidal melanoma.

Generating lung tumor internal target volumes from 4D-PET maximum intensity projections.

PURPOSE Positron emission tomography (PET) of lung tumors suffers from breathing-motion induced blurring. Respiratory-correlated PET ameliorates motion blurring and enables visualization of lung tumor functional uptake throughout the breathing cycle but has achieved limited clinical use in radiotherapy planning. In this work, the authors propose a process for generating a gated PET maximum intensity projection (MIP), a breathing-phase projection of the 4D image set comprising gated PET images, as a technique to quantitatively and efficiently incorporate respiratory-correlated PET information into radiotherapy treatment planning. METHODS 4D-CT and respiratory-gated PET using [(18)F]fluorodeoxyglucose (FDG) were acquired of three patients with a total of four small (4-18 cc), clearly defined lower-lobe lung tumors. Internal target volumes (ITVs) for the lung tumors were generated by threshold-based segmentation of PET-MIP images and ungated PET images (ITV(PET-MIP) and ITV(3D-PET), respectively), and by manual contouring of CT-MIP and end-exhale and end-inhale phases of 4D-CT (ITV(CT-MIP)) by a radiation oncologist. Because of the sensitivity of tumor segmentation to threshold value, several different thresholds were tested for ITV generation, including 40%, 30%, and 20% of maximum standardized uptake value (SUV(max)) for FDG as well as absolute SUV thresholds of 2.5 and 3.0. The normalized overlap and relative volumes of ITV(PET-MIP) and ITV(3D-PET) with respect to ITV(CT-MIP) were compared. The images were also visually compared. ITV(CT-MIP) was considered a gold standard for these tumors with CT-visible morphology. RESULTS The mean and standard deviation normalized overlap and relative volumes between ITV(PET-MIP) and ITV(CT-MIP) were 0.68 ± 0.07 and 1.07 ± 0.42, respectively, averaged over all four tumors and all five threshold values. The mean and standard deviation normalized overlap and relative volumes of ITV(3D-PET) and ITV(CT-MIP) were 0.47 ± 0.12 and 0.69 ± 0.56, respectively. CONCLUSIONS PET-MIP images better match CT-MIP images for this sample of four small CT-visible tumors as compared to ungated PET images, based on the metrics of volumetric overlap and relative volumes as well as visual interpretation. The PET-MIP is a way to incorporate 4D-PET imaging into the process of lung tumor contouring that is time-efficient for the radiation oncologist and involves minimal effort to implement in treatment planning software, because it requires only a single PET image beyond contouring on CT alone.

A novel fast helical 4D-CT acquisition technique to generate low-noise sorting artifact-free images at user-selected breathing phases.

PURPOSE To develop a novel 4-dimensional computed tomography (4D-CT) technique that exploits standard fast helical acquisition, a simultaneous breathing surrogate measurement, deformable image registration, and a breathing motion model to remove sorting artifacts. METHODS AND MATERIALS Ten patients were imaged under free-breathing conditions 25 successive times in alternating directions with a 64-slice CT scanner using a low-dose fast helical protocol. An abdominal bellows was used as a breathing surrogate. Deformable registration was used to register the first image (defined as the reference image) to the subsequent 24 segmented images. Voxel-specific motion model parameters were determined using a breathing motion model. The tissue locations predicted by the motion model in the 25 images were compared against the deformably registered tissue locations, allowing a model prediction error to be evaluated. A low-noise image was created by averaging the 25 images deformed to the first image geometry, reducing statistical image noise by a factor of 5. The motion model was used to deform the low-noise reference image to any user-selected breathing phase. A voxel-specific correction was applied to correct the Hounsfield units for lung parenchyma density as a function of lung air filling. RESULTS Images produced using the model at user-selected breathing phases did not suffer from sorting artifacts common to conventional 4D-CT protocols. The mean prediction error across all patients between the breathing motion model predictions and the measured lung tissue positions was determined to be 1.19 ± 0.37 mm. CONCLUSIONS The proposed technique can be used as a clinical 4D-CT technique. It is robust in the presence of irregular breathing and allows the entire imaging dose to contribute to the resulting image quality, providing sorting artifact-free images at a patient dose similar to or less than current 4D-CT techniques.

Longitudinal diffusion MRI for treatment response assessment: Preliminary experience using an MRI-guided tri-cobalt 60 radiotherapy system

PURPOSE To demonstrate the preliminary feasibility of a longitudinal diffusion magnetic resonance imaging (MRI) strategy for assessing patient response to radiotherapy at 0.35 T using an MRI-guided radiotherapy system (ViewRay). METHODS Six patients (three head and neck cancer, three sarcoma) who underwent fractionated radiotherapy were enrolled in this study. A 2D multislice spin echo single-shot echo planar imaging diffusion pulse sequence was implemented on the ViewRay system and tested in phantom studies. The same pulse sequence was used to acquire longitudinal diffusion data (every 2-5 fractions) on the six patients throughout the entire course of radiotherapy. The reproducibility of the apparent diffusion coefficient (ADC) measurements was assessed using reference regions and the temporal variations of the tumor ADC values were evaluated. RESULTS In diffusion phantom studies, the ADC values measured on the ViewRay system matched well with reference ADC values with <5% error for a range of ground truth diffusion coefficients of 0.4-1.1 × 10(-3) mm(2)/s. The remote reference regions (i.e., brainstem in head and neck patients) had consistent ADC values throughout the therapy for all three head and neck patients, indicating acceptable reproducibility of the diffusion imaging sequence. The tumor ADC values changed throughout therapy, with the change differing between patients, ranging from a 40% drop in ADC within the first week of therapy to gradually increasing throughout therapy. For larger tumors, intratumoral heterogeneity was observed. For one sarcoma patient, postradiotherapy biopsy showed less than 10% necrosis score, which correlated with the observed 40% decrease in ADC from the fifth fraction to the eighth treatment fraction. CONCLUSIONS This pilot study demonstrated that longitudinal diffusion MRI is feasible using the 0.35 T ViewRay MRI. Larger patient cohort studies are warranted to correlate the longitudinal diffusion measurements to patient outcomes. Such an approach may enable response-guided adaptive radiotherapy.

A treatment planning comparison between modulated tri-cobalt-60 teletherapy and linear accelerator–based stereotactic body radiotherapy for central early-stage non−small cell lung cancer

We evaluated the feasibility of planning stereotactic body radiotherapy (SBRT) for large central early-stage non-small cell lung cancer with a tri-cobalt-60 (tri-(60)Co) system equipped with real-time magnetic resonance imaging (MRI) guidance, as compared to linear accelerator (LINAC)-based SBRT. In all, 20 patients with large central early-stage non-small cell lung cancer who were treated between 2010 and 2015 with LINAC-based SBRT were replanned using a tri-(60)Co system for a prescription dose of 50Gy in 4 fractions. Doses to organs at risk were evaluated based on established MD Anderson constraints for central lung SBRT. R100 values were calculated as the total tissue volume receiving 100% of the dose (V100) divided by the planning target volume and compared to assess dose conformity. Dosimetric comparisons between LINAC-based and tri-(60)Co SBRT plans were performed using Student׳s t-test and Wilcoxon Ranks test. Blinded reviews by radiation oncologists were performed to assess the suitability of both plans for clinical delivery. The mean planning target volume was 48.3cc (range: 12.1 to 139.4cc). Of the tri-(60)Co SBRT plans, a mean 97.4% of dosimetric parameters per patient met MD Anderson dose constraints, whereas a mean 98.8% of dosimetric parameters per patient were met with LINAC-based SBRT planning (p = 0.056). R100 values were similar between both plans (1.20 vs 1.21, p = 0.79). Upon blinded review by 4 radiation oncologists, an average of 90% of the tri-(60)Co SBRT plans were considered acceptable for clinical delivery compared with 100% of the corresponding LINAC-based SBRT plans (p = 0.17). SBRT planning using the tri-(60)Co system with built-in MRI is feasible and achieves clinically acceptable plans for most central lung patients, with similar target dose conformity and organ at risk dosimetry. The added benefit of real-time MRI-guided therapy may further optimize tumor targeting while improving normal tissue sparing, which warrants further investigation in a prospective feasibility clinical trial.

Distribution of lung tissue hysteresis during free breathing

PURPOSE To characterize and quantify free breathing lung tissue motion distributions. METHODS Forty seven patient data sets were acquired using a 4DCT protocol consisting of 25 ciné scans at abutting couch positions on a 16-slice scanner. The tidal volume of each scan was measured by simultaneously acquiring spirometry and an abdominal pneumatic bellows. The concept of a characteristic breath was developed to manage otherwise natural breathing pattern variations. The characteristic breath was found by first dividing the breathing traces into individual breaths, from maximum exhalation to maximum exhalation. A linear breathing drift model was assumed and the drift removed for each breath. Breaths that exceeded one standard deviation in period or amplitude were removed from further analysis. A characteristic breath was defined by normalizing each breath to a common amplitude, aligning the peak inhalation times for all of the breaths, and determining the average time at each tidal volume, keeping inhalation and exhalation separate. Breathing motion trajectories were computed using a previously published five-dimensional lung tissue trajectory model which expresses the position of internal lung tissue, X, as: X(v,f:X0)=X0+α(X0)v+β(X0)f, where X0 is the internal lung tissue position at zero tidal volume and zero airflow, the scalar values v and f are the measured tidal volume and airflow, respectively, and the vectors α and β are fitted free parameters. In order to characterize the motion patterns, the trajectory elongations were examined throughout the subjects lungs. Elongation was defined here by generating a rectangular bounding box with one side parallel to the α vector and the box oriented in the plane defined by the α and β motion vectors. Hysteresis motion was defined as the ratio of the box dimensions aligned orthogonal to and parallel to the α vector. The 15th and 85th percentile of the elongation were used to characterize tissue trajectory hysteresis. RESULTS The 15th and 85th percentile bounding box elongations were 0.090 ± 0.005 and 0.083 ± 0.013 in the upper left lung and 0.187 ± 0.037 and 0.203 ± 0.053, in the lower left lung. The 15th and 85th percentiles for the upper right lung were 0.092 ± 0.006 and 0.085 ± 0.013, and 0.184 ± 0.038, and 0.196 ± 0.043 in the lower right lung. Both percentiles were calculated for tidal volume displacements between 5 and 15 mm. In the left lung, the average elongations in the upper and lower lung were ζ=0.120 ± 0.064 and ζ=0.090 ± 0.055, respectively. The average elongations in the upper and lower right lung were ζ=0.107 ± 0.060 and ζ=0.082 ± 0.048, respectively. The elongation varied smoothly throughout the lungs. CONCLUSIONS The hysteresis motion was relatively small compared to the volume-filling motion, contributing between 8% and 20% of the overall motion. Statistically significant differences were observed in the range of hysteresis contribution for upper and lower lung regions. The characteristic breath process provided an excellent method for defining an average breath. The characteristic breath had continuous tidal volume and airflow characteristics when the breath was continuously repeated,useful for generating patterns representative of realistic motion for breathing motion studies.

A comparison of amplitude-based and phase-based positron emission tomography gating algorithms for segmentation of internal target volumes of tumors subject to respiratory motion.

PURPOSE To quantitatively compare the accuracy of tumor volume segmentation in amplitude-based and phase-based respiratory gating algorithms in respiratory-correlated positron emission tomography (PET). METHODS AND MATERIALS List-mode fluorodeoxyglucose-PET data was acquired for 10 patients with a total of 12 fluorodeoxyglucose-avid tumors and 9 lymph nodes. Additionally, a phantom experiment was performed in which 4 plastic butyrate spheres with inner diameters ranging from 1 to 4 cm were imaged as they underwent 1-dimensional motion based on 2 measured patient breathing trajectories. PET list-mode data were gated into 8 bins using 2 amplitude-based (equal amplitude bins [A1] and equal counts per bin [A2]) and 2 temporal phase-based gating algorithms. Gated images were segmented using a commercially available gradient-based technique and a fixed 40% threshold of maximum uptake. Internal target volumes (ITVs) were generated by taking the union of all 8 contours per gated image. Segmented phantom ITVs were compared with their respective ground-truth ITVs, defined as the volume subtended by the tumor model positions covering 99% of breathing amplitude. Superior-inferior distances between sphere centroids in the end-inhale and end-exhale phases were also calculated. RESULTS Tumor ITVs from amplitude-based methods were significantly larger than those from temporal-based techniques (P=.002). For lymph nodes, A2 resulted in ITVs that were significantly larger than either of the temporal-based techniques (P<.0323). A1 produced the largest and most accurate ITVs for spheres with diameters of ≥2 cm (P=.002). No significant difference was shown between algorithms in the 1-cm sphere data set. For phantom spheres, amplitude-based methods recovered an average of 9.5% more motion displacement than temporal-based methods under regular breathing conditions and an average of 45.7% more in the presence of baseline drift (P<.001). CONCLUSIONS Target volumes in images generated from amplitude-based gating are larger and more accurate, at levels that are potentially clinically significant, compared with those from temporal phase-based gating.

Biomechanical interpretation of a free-breathing lung motion model

The purpose of this paper is to develop a biomechanical model for free-breathing motion and compare it to a published heuristic five-dimensional (5D) free-breathing lung motion model. An ab initio biomechanical model was developed to describe the motion of lung tissue during free breathing by analyzing the stress-strain relationship inside lung tissue. The first-order approximation of the biomechanical model was equivalent to a heuristic 5D free-breathing lung motion model proposed by Low et al in 2005 (Int. J. Radiat. Oncol. Biol. Phys. 63 921-9), in which the motion was broken down to a linear expansion component and a hysteresis component. To test the biomechanical model, parameters that characterize expansion, hysteresis and angles between the two motion components were reported independently and compared between two models. The biomechanical model agreed well with the heuristic model within 5.5% in the left lungs and 1.5% in the right lungs for patients without lung cancer. The biomechanical model predicted that a histogram of angles between the two motion components should have two peaks at 39.8° and 140.2° in the left lungs and 37.1° and 142.9° in the right lungs. The data from the 5D model verified the existence of those peaks at 41.2° and 148.2° in the left lungs and 40.1° and 140° in the right lungs for patients without lung cancer. Similar results were also observed for the patients with lung cancer, but with greater discrepancies. The maximum-likelihood estimation of hysteresis magnitude was reported to be 2.6 mm for the lung cancer patients. The first-order approximation of the biomechanical model fit the heuristic 5D model very well. The biomechanical model provided new insights into breathing motion with specific focus on motion trajectory hysteresis.

Investigation of a breathing surrogate prediction algorithm for prospective pulmonary gating

PURPOSE A major challenge of four dimensional computed tomography (4DCT) in treatment planning and delivery has been the lack of respiration amplitude and phase reproducibility during image acquisition. The implementation of a prospective gating algorithm would ensure that images would be acquired only during user-specified breathing phases. This study describes the development and testing of an autoregressive moving average (ARMA) model for human respiratory phase prediction under quiet respiration conditions. METHODS A total of 47 4DCT patient datasets and synchronized respiration records was utilized in this study. Three datasets were used in model development and were removed from further evaluation of the ARMA model. The remaining 44 patient datasets were evaluated with the ARMA model for prediction time steps from 50 to 1000 ms in increments of 50 and 100 ms. Thirty-five of these datasets were further used to provide a comparison between the proposed ARMA model and a commercial algorithm with a prediction time step of 240 ms. RESULTS The optimal number of parameters for the ARMA model was based on three datasets reserved for model development. Prediction error was found to increase as the prediction time step increased. The minimum prediction time step required for prospective gating was selected to be half of the gantry rotation period. The maximum prediction time step with a conservative 95% confidence criterion was found to be 0.3 s. The ARMA model predicted peak inhalation and peak exhalation phases significantly better than the commercial algorithm. Furthermore, the commercial algorithm had numerous instances of missed breath cycles and falsely predicted breath cycles, while the proposed model did not have these errors. CONCLUSIONS An ARMA model has been successfully applied to predict human respiratory phase occurrence. For a typical CT scanner gantry rotation period of 0.4 s (0.2 s prediction time step), the absolute error was relatively small, 0.06 +/- 0.02 s at peak inhalation and 0.05 +/- 0.04 s at peak exhalation. The application of the ARMA model for prospective pulmonary gating has been demonstrated.